The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the computationally most efficient basis set, can have memory requirements exceeding the capacity of a single computational node. This situation has traditionally forced a difficult choice of either using slow internode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
The temperature response of luminescent ionizable polymers confined into far from equilibrium nanoparticles without chemical links was studied using molecular dynamics simulations. These nanoparticles, often referred to as polydots, are emerging as a promising tool for nanomedicine. Incorporating ionizable groups into these polymers enables biofunctionality; however, they also affect the delicate balance of interactions that hold these nanoparticles together. Here polydots formed by a model polymer dialkyl p-phenylene ethynylene with varying number of carboxylate groups along the polymer backbone were probed. We find that increasing temperature affects neutral and charged polydots differently, where neutral polydots exhibit a transition above which their structure becomes dynamic and they unravel. The dependence of the transition temperature on the surface to volume ratio of these polydots is much stronger than what has previously been observed in polymeric thin films. Charged polydots become dynamic enabling migration of the ionizable groups toward the particle interface, while retaining the overall particle shape.
Wellbore integrity is of paramount importance to subsurface resource extraction, energy storage and hazardous waste disposal. We introduce a simple non-invasive technology for casing integrity screening, based on the continuity of electrical current flow. Applying low frequency current to a wellhead, with a distant return electrode, produces a casing current dependent on the properties and depth extent of the well casing as well as the background formation. These currents in-turn generate surface electrical fields that can be captured in a radial profile and be used to analyze properties of the well casing. Numerical modeling results reveal a strong relation of the electric field to the casing properties and depth extent of the well. A small breakage in the casing produces a profile coincident to a cased well with a completion depth above the break. A corroded patch, where the casing conductivity is reduced, also alters the field profiles and its depth may be estimated by comparing to the profile expected from the well completion diagrams. The electric field profiles are also strongly dependent on background resistivity distributions and on whether the well was drilled using water or oil-based drilling fluids. We validate the proof of concept in a field experiment, where we applied currents at the wellheads of two wells with different casing lengths. The two profiles were similar in appearance but offset in amplitude by more than a factor of 5, consistent with the theoretical analysis as well as the 3D modeling results. These results demonstrate that our proposed approach has promise for mapping the general casing condition without well intervention. This approach can be a practical and effective tool for rapidly screening a number of wells before expensive logging-based technologies are employed for casing inspection in detail.
To better understand the factors contributing to electromagentic (EM) observables in developed field sites, we examine in detail through finite element analysis the specific effects of casing completion design. The presense of steel casing has long been exploited for improved subsurface interrogation and there is growing interest in remote methods for assessing casing integrity accross a range of geophysical scenarios related to resource development and sequestration/storage activities. Accurate modeling of the casing response to EM stimulation is recognized as relevant, and a difficult computational challenge because of the casing's high conductivity contrast with geomaterials and its relatively small volume fraction over the field scale. We find that casing completion design can have a significant effect on the observed EM fields, especially at zero frequency. This effect appears to originate in the capacitive coupling between inner production casing and the outer surface casing. Furthermore we show that an equivalent “effective conductivity” for the combined surface/production casing system is inadequate for replicating this effect, regardless of whether the casings are grounded to one another or not. Lastly, we show that in situations where this coupling can be ignored and knowledge of casing currents is not required, simplifying the casing as a perfectly conducting line can be an effective strategy for reducing the computational burden in modeling field-scale response.
Fractures are an interest of many engineering problems. They present complex spatial distributions and hydraulic properties that vary over a wide range of length scales. The multi-length-scale nature as well as the volumetric insignificance of fractures at the filed scale demand an explosive computational effort to account of fractures in standard DC resistivity modeling. Here, we use the hierarchical finite element method (Hi-FEM) to model complex fracture networks in 3D conducting media. The HiFEM method is based on the hierarchy in the electrical properties of 3D geologic media that drastically reduces the computational cost, such that thin conductive fractures can easily be represented by a set of connected 2D facet elements or linear conductive features can be approximated by connected 1D edge elements. Here, we present a demonstrative numerical study of the 3D DC resistivity responses of a complex fractured network consisting of a large number of randomly-oriented fractures. We also simulate the time lapse response of an evolving fracture network as a demonstration of real-time 4D monitoring. Our results indicate that the amplitude and the distribution of DC electric potentials are substantially controlled by fracture properties; moreover, the DC resistivity measurements over a growing fracture network reflect the spatial and the temporal state of the network connectivity.
The prediction of heat flux over a sphere in hypersonic flow is an interesting and challenging problem. When using solutions to the Navier-Stokes equations to predict the heat flux, a common source of numerical error is a phenomenon known as 'grid imprinting'. Rather than the axisymmetric heat flux profile expected for a spherical surface, the topology of the grid can be seen in the surface heat flux distribution. We will examine the origin of this phenomenon; specifically the regions of the grid that contribute most. Comparisons will be made between second order finite volume and Discontinuous Galerkin (DG) results — the DG results will range from 2nd to 4th order. The Dual Weighted Residual (DWR) framework is used to obtain local error estimates for the heat flux integrated over the surface with respect to the grid for the DG results.
International collaborations on nuclear waste disposal R&D are an integral part of the Spent Fuel Waste Science and Technology (SFWST) campaign within the DOE Fuel Cycle and Technology (FCT) program. These partnerships with international repository R&D programs provide key opportunities to participate in experiments developing laboratory/field data (underground research laboratories (URL)) of engineered barrier system (EBS) interactions (e.g., near-field) and characterization of transport phenomena in the host rock (e.g., far-field). The results of these experiments are used in the evaluation of coupled processes and their representation via state-of-the-art simulation approaches to evaluate repository performance. During the thermal heating period, increases in temperature from radionuclide decay in the spent fuel (SF) waste canisters will increase temperature in the surrounding EBS driving chemical and transport processes in the near- and far-field domains of the repository. URL heater-tests for extended periods of times (e.g., years) provide key information and data on thermal effects affecting engineered barriers in response to temperature and water saturation levels. Groundwater interactions with cementitious barriers are also important to in-drift chemistry and EBS performance during post-closure. Descriptions of the various URL experiments for various disposal design concepts according to the host country repository program and relevance to the US program is given elsewhere (Birkholzer et al.,2017;Jové Col& et al., 2016). The DECOVALEX-2019 Task C involves collaboration with the GREET (Groundwater REcovery Experiment in Tunnel) at the Mizunami URL, Japan ,which targets the development of monitoring methodologies of groundwater in granitic rock with applications to THMC simulations (Iwatsuki et al., 2005;Iwatsuki et al.,2015,2017). Some of the goals of GREET is to conduct a facility-scale geochemical characterization study of short- and long-term effects of tunnel excavation activities, impacts on groundwater flow and transport, and influences on groundwater chemistry (Iwatsuki et al.,2015). The data obtained from these URL activities is then used in the development and evaluation of THC models to support post-closure safety and performance assessments of the repository environment.
Certification of successful completion of ASC CSSE Level 2 Milestone 6362: Local Failure Local Recovery (LFLR) Resiliency for Asynchronous Many Task (AMT) Programming and Execution Models
International collaborations on nuclear waste disposal is an integral part of the Spent Fuel Waste Science and Technology (SFWST) campaign within the DOE Fuel Cycle and Technology (FCT) program. These engagements with international repository R&D programs provide key opportunities to participate in experiments with international partners on research investigations developing laboratory/field (underground research laboratories (URL) experiments) data of engineered barrier system (EBS) components (e.g., near-field) and characterization of transport phenomena in the host rock (e.g., far-field). The results of these field and laboratory experiments are used in the evaluation of coupled processes and the development of state-of-the-art simulation approaches to evaluate repository performance. Thermal heating from radionuclide decay in the waste canisters will increase temperature in the surrounding EBS driving chemical and transport processes in the near- and far-field domains of the repository. URL heater-tests for extended periods of times (e.g., years) provide key information and data of thermal effects on barrier responses to temperature and water saturation levels.
In this work, we study the interlayer interactions between sheets of blue phosphorus with quantum Monte Carlo (QMC) methods. We find that as previously observed in black phosphorus, interlayer binding of blue phosphorus cannot be described by van der Waals (vdW) interactions alone within the density functional theory framework. Specifically, while some vdW density functionals produced reasonable binding curves, none of them could provide a correct, even qualitatively, description of charge redistribution due to interlayer binding. We also show that small systematic errors in common practice QMC calculations, such as the choice of optimized geometry and finite-size corrections, are non-negligible given the energy and length scales of this problem. We mitigate some of the major sources of error and report QMC-optimized lattice constant, stacking, and interlayer binding energy for blue phosphorus. It is strongly suggested that these considerations are important and quite general in the modeling of two-dimensional phosphorus allotropes.
Techno-economic analyses of energy storage currently use constant-efficiency energy flow models. In practice, charge/discharge efficiency of energy storage varies as a function of state-of-charge, temperature, charge/discharge power. Therefore, using the constant-efficiency energy flow models will cause suboptimal results. This work focuses on incorporating nonlinear energy flow models based on nonlinear efficiency models in the revenue maximization problem of energy storage. Dynamic programming is used to solve the optimization problem. A case studies is conducted to maximize the revenue of a Vanadium Redox Flow Battery (VRFB) system in PJM's energy and frequency regulation market.
Through the use of advanced control techniques, wave energy converters have significantly improved energy absorption. The motion of the WEC device is a significant contribution to the energy absorbed by the device. Reactive control (complex conjugate control) maximizes the energy absorption due to the impedance matching. The issue with complex conjugate control is that the controller is non-causal, which requires prediction into the oncoming waves to the device. This paper explores the potential of using system identification (SID) techniques to build a causal transfer function that approximates the complex conjugate controller over a specific frequency band of interest. The resulting controller is stable, and the average efficiency of the power captured by the causal controller is 99%, when compared to the non-causal complex conjugate.
Inconsistencies in high-pressure H2 adsorption data and a lack of comparative experiment-theory studies have made the evaluation of both new and existing metal-organic frameworks (MOFs) challenging in the context of hydrogen storage applications. In this work, we performed grand canonical Monte Carlo (GCMC) simulations in nearly 500 experimentally refined MOF structures to examine the variance in simulation results because of the equation of state, H2 potential, and the effect of density functional theory structural optimization. We find that hydrogen capacity at 77 K and 100 bar, as well as hydrogen 100-to-5 bar deliverable capacity, is correlated more strongly with the MOF pore volume than with the MOF surface area (the latter correlation is known as the Chahine's rule). The tested methodologies provide consistent rankings of materials. In addition, four prototypical MOFs (MOF-74, CuBTC, ZIF-8, and MOF-5) with a range of surface areas, pore structures, and surface chemistries, representative of promising adsorbents for hydrogen storage, are evaluated in detail with both GCMC simulations and experimental measurements. Simulations with a three-site classical potential for H2 agree best with our experimental data except in the case of MOF-5, in which H2 adsorption is best replicated with a five-site potential. However, for the purpose of ranking materials, these two choices for H2 potential make little difference. More significantly, 100 bar loading estimates based on more accurate equations of state for the vapor-liquid equilibrium yield the best comparisons with the experiment.
Placing a crystal under extreme pressure can sometimes change its structure from one form, or phase, to another. Determining exactly how crystals change phase under compression is an important area of materials physics research. The availability of x-ray diffraction at synchrotron facilities has allowed scientists to observe compression-driven phase changes in unprecedented detail. Most of the research in this field has focused on pressure-induced phase changes using slow (static) compression on the minute timescale. Now, utilizing x-ray diffraction at the APS, a multi-institution research team led by scientists at Sandia National Laboratories has observed, over nanosecond timescales, microstructural phase changes within a two-element (calcium fluoride) crystal subjected to extreme pressures. The high pressures were achieved both through high-velocity instantaneous shock compression and by statically squeezing the samples. The researchers expect that their real-time observations of phase transitions within calcium fluoride will provide a template for the phase transitions of similarly-structured compounds. More generally, it is anticipated that the experimental methods and results of this study will lead to improved modeling of phase transitions over nanosecond timescales, within a wide range of complex materials.
Chris Saunders and three technologists are in high demand from Sandia's deep learning teams, and they're kept busy by building new clusters of computer nodes for researchers who need the power of supercomputing on a smaller scale. Sandia researchers working on Laboratory Directed Research & Development (LDRD) projects, or innovative ideas for solutions on short timeframes, formulate new ideas on old themes and frequently rely on smaller cluster machines to help solve problems before introducing their code to larger HPC resources. These research teams need an agile hardware and software environment where nascent ideas can be tested and cultivated on a smaller scale. Saunders and his team at Sandia's Science and Engineering Computing Environments are successfully enabling this research by creating pipelines for emerging code—from Cloud, to containers, to virtual machines—that build the right environment quickly to help teams solve their problems in a matter of days rather than months. While the larger HPC sources are available, it's these smaller clusters that can rapidly build a foundation for teams to build on for later development on larger systems.
A new race is emerging among nuclear powers: the hypersonic weapon. Hypersonics are flight vehicles that travel at Mach 5 (five times the speed of sound) or faster. They can cruise in the atmosphere, unlike traditional exo-atmospheric ballistic missiles, allowing stealth and maneuverability during midflight. Faster, lower, and stealthier means the missiles can better evade adversary defense systems. The U.S. has experimented with hypersonics for years, but current investments by Russia and China into their own offensive hypersonic systems may render U.S. missile defense systems ineffective. For the U.S. to avoid obsolescence in this strategically significant technology arena, hypersonics—combined with autonomy—needs to be a force multiplier. Achieving an autonomous hypersonic missile, however, that can intelligently navigate, guide, and control itself and home-in on targets ranging from traditional stationary systems to targets that are themselves hypersonic vehicles—with all the maneuverability that this entails—may sound far-fetched. But to Sandia's Autonomy for Hypersonics (A4H) team, this dream is one step closer to reality.
Many modern applications have memory footprints that are increasingly large, driving system memory capacities higher and higher. Moreover, these systems are often organized where the bulk of the memory is collocated with the compute capability, which necessitates the need for message passing APIs to facilitate information sharing between compute nodes. Due to the diversity of applications that must run on High-Performance Computing (HPC) systems, the memory utilization can fluctuate wildly from one application to another. And, because memory is located in the node, maintenance can become problematic because each node must be taken offline and upgraded individually. To address these issues, vendors are exploring disaggregated, memory-centric, systems. In this type of organization, there are discrete nodes, reserved solely for memory, which are shared across many compute nodes. Due to their capacity, low-power, and non-volatility, Non-Volatile Memories (NVMs) are ideal candidates for these memory nodes. This report discusses a new component for the Structural Simulation Toolkit (SST), Opal, that can be used to study the impact of using NVMs in a disaggregated system in terms of performance, security, and memory management. This page intentionally left blank.
In August the team was able to get CUDA-9.2 up and running on white. Ride is not update to be the same as White, to support Trilinos testing. CUDA-9.2 builds are up on both. The team also expanded ATDM testing for SPARC and finished up the KNL build. Worked on ATDM Trilinos configuration to include the packages necessary for SPARC.
In this paper, we analyze a compact silicon photonic phase modulator at 1.55 μm using epsilon-near-zero transparent conducting oxide (TCO) films. The operating principle of the non-resonant phase modulator is field-effect carrier density modulation in a thin TCO film deposited on top of a passive silicon waveguide with a CMOS-compatible fabrication process. We compare phase modulator performance using both indium oxide (In2O3) and cadmium oxide (CdO) TCO materials. Our findings show that practical phase modulation can be achieved only when using high-mobility (i.e. low-loss) epsilon-near-zero materials such as CdO. The CdO-based phase modulator has a figure of merit of 17.1°/dB in a compact 5 μm length. This figure of merit can be increased further through the proper selection of high-mobility TCOs, opening a path for device miniaturization and increased phase shifts.
When metals plastically deform, the density of line defects called dislocations increases and the microstructure is continuously refined, leading to the strain hardening behavior. Using discrete dislocation dynamics simulations, we demonstrate the fundamental role of junction formation in connecting dislocation microstructure evolution and strain hardening in face-centered cubic (fcc) Cu. The dislocation network formed consists of line segments whose lengths closely follow an exponential distribution. This exponential distribution is a consequence of junction formation, which can be modeled as a one-dimensional Poisson process. According to the exponential distribution, two non-dimensional parameters control microstructure evolution, with the hardening rate dictated by the rate of stable junction formation. Among the types of junctions in fcc crystals, we find that glissile junctions make the dominant contribution to strain hardening.
In the published article (Xiong et al., 2017), there was an error for the reaction coefficient for the dissolution reaction of Ca2C10H12N2O8•7H2O(s) in the database used for the modeling. In the database for the modeling, the coefficient for water (i.e., 7H2O) was inadvertently omitted. Because of this omission, the results in Table 3 were affected. The authors wish to make the corrections to Table 3. The corrected values are tabulated in the revised Table 3. The corrected values reproduce the experimental data in MgCl2 solutions much better (see revised Fig. 5).
In this study, we demonstrate creation of electroforming-free TaOx memristive devices using focused ion beam irradiations to locally define conductive filaments in TaOx films. Electrical characterization shows that these irradiations directly create fully functional memristors without the need for electroforming. Finally, ion beam forming of conductive filaments combined with state-of-the-art nano-patterning presents a CMOS compatible approach to wafer level fabrication of fully formed and operational memristors.
DARMA (Distributed Asynchronous Resilient Models for Applications) is a runtime library developed as part of the the Sandia ATDM (Advanced Technology Development and Mitigation) program. DARMA supports applications within 2.2.5.03 ADNN03-ASC ATDM SNL Application, which includes a number of applications featuring dynamic physics which requires load balancing and asynchronous communication for high performance. We have implemented a modern C++ programming model that can enable dynamic, asynchronous communication on top of existing data structures from a serial or MPI code. DARMA development has occurred in parallel with a verification milestone for ATDM in FY18. For FY19, DARMA will impact ATDM by enabling the performance benefits of a dynamic runtime through only incremental changes to existing verified MPI codes. The results presented here demonstrate the DARMA development process for an MPI mini-app, showing a 3-4x improvement in performance for a challenging problem relative to the parent MPI code and coming within 25 percent of the theoretically optimal performance achievable from a perfect, fine-grained load balancer for most cases.
DARMA (Distributed Asynchronous Resilient Models for Applications) is a runtime library supporting the Sandia ATDM (Advanced Technology Development and Mitigation) program. The main application drivers fall within the ECP milestone 2.2.5.03 ADNN03-ASC ATDM SNL Application, which includes applications that require load balancing and asynchronous communication for high performance. The DARMA runtime infrastructure has been modified to be compatible with Kokkos/OpenMP parallelization within tasks, which is a critical requirement for high performance for the Sandia ATDM apps. DARMA development has occurred in parallel with a verification milestone for ATDM in FY18. For FY19, DARMA should impact ATDM by enabling dynamic load balancing and communication through only incremental changes to the existing verified MPI codes. DARMA can now support the intra-kernel thread parallelization in the parent MPI apps, allowing DARMA to be easily added without rewriting individual math kernels. The results presented here demonstrate the DARMA results for an MPI mini-app.
The DARMA many-task framework provides asynchronous communication and load balancing functionality. This functionality is embedded in standard, modern C++ through the use of the template wrapper classes similar to futures. DARMA codes previously could not interoperate with Kokkos or OpenMP since each runtime assumed sole ownership of thread resources. The most recent version now allows for the use of Kokkos/OpenMP within DARMA tasks, allowing for better performance through thread-level parallelism or use of accelerators.
The DARMA many-task framework provides asynchronous communication and load balancing functionality. This functionality is embedded in standard , modern C++ through the use of the template wrapper classes similar to futures. DARMA codes previously could not interoperate with MPI. A new C++ interface and extended semantics now allow quiescence of DARMA kernels and transfer of data ownership back into MPI, allowing 1) isolated DARMA kernels to be inserted in a larger MPI code or 2) reuse of MPI libraries like solvers within a DARMA application.
Simulating energetic materials with complex microstructure is a grand challenge, where until recently, an inherent gap in computational capabilities had existed in modelling grain-scale effects at the microscale. We have enabled a critical capability in modelling the multiscale nature of the energy release and propagation mechanisms in advanced energetic materials by implementing, in the widely used LAMMPS molecular dynamics (MD) package, several novel coarse-graining techniques that also treat chemical reactivity. Our innovative algorithmic developments rooted within the dissipative particle dynamics framework, along with performance optimisations and application of acceleration technologies, have enabled extensions in both the length and time scales far beyond those ever realised by atomistic reactive MD simulations. In this paper, we demonstrate these advances by modelling a shockwave propagating through a microstructured material and comparing performance with the state-of-the-art in atomistic reactive MD techniques. As a result of this work, unparalleled explorations in energetic materials research are now possible.
Power systems can become unstable under transient periods such as short-circuit faults, leading to equipment damage and large scale blackouts. Power system stabilizers (PSS) can be designed to improve the stability of generators by quickly regulating the exciter field voltage to damp the swings of generator rotor angle and speed. The stability achieved through exciter field voltage control can be further improved with a relatively small, fast responding energy storage system (ESS) connected at the terminals of the generator that enables electrical power damping. PSS are designed and studied using a single-machine infinite-bus (SMIB) model. In this paper, we present a comprehensive optimal-control design for a flexible ac synchronous generator PSS using both exciter field voltage and ESS control including estimation of unmeasurable states. The controller is designed to minimize disturbances in rotor frequency and angle, and thereby improve stability. The design process is based on a linear quadratic regulator of the SMIB model with a test system linearized about different operating frequencies in the range 10 Hz to 60 Hz. The optimal performance of the PSS is demonstrated along with the resulting stability improvement.
The increased penetration of renewable resources has made frequency regulation and generation control a growing concern. This has created an opportunity for Energy Storage Resource to participate in the frequency regulation market. This paper investigates the potential of Battery Energy Storage systems to participate in the German secondary frequency regulation market. A simulation model is developed to investigate the revenue opportunity of a 48 MWh Battery System participating in the secondary frequency regulation market.
Lipid-coated mesoporous silica nanoparticles (LC-MSNs) have recently emerged as a next-generation cargo delivery nanosystem combining the unique attributes of both the organic and inorganic components. The high surface area biodegradable inorganic mesoporous silica core can accommodate multiple classes of bio-relevant cargos in large amounts, while the supported lipid bilayer coating retains the cargo and increases the stability of the nanocarrier in bio-relevant media which should promote greater bio-accumulation of LC-MSNs in cancer sites. In this paper, we report on the optimization of various sol–gel synthesis (pH, stirring speed) and post-synthesis (hydrothermal treatment) procedures to enlarge the MSN pore size and tune the surface chemistry so as to enable loading and delivery of large biomolecules. Finally, the proof of concept of the dual cargo-loaded nanocarrier has been demonstrated in immortalized cervical cancer HeLa cells using MSNs of various fine-tuned pore sizes.
A wide-area controller to damp inter-area oscillations in the North American Western Interconnection (WI) by modulating power transfers in a HVDC link is used in this paper to investigate the effects that latencies in its feedback signals have on its performance. This controller uses two feedback measurements to perform its control action. The analysis show that the stabilizing effect of the controller in transient stability and small signal stability is compromised as the feedback measurements experience higher delays. The results show that one of the feedback signals can tolerate more delay than the other. The analysis was performed with Bode plots and time domain simulations on a reduced order model of the WI from which a linear version was obtained.
Power system utilities continue to strive for increased system resiliency. However, quantifying a baseline system resilience, and deciding the optimal investments to improve their resilience is challenging. This paper discusses a method to create scenarios, based on historical data, that represent the threats of severe weather events, their probability of occurrence, and the system wide consequences they generate. This paper also presents a mixed-integer stochastic nonlinear optimization model which uses the scenarios as an input to determine the optimal investments to reduce the system impacts from those scenarios. The optimization model utilizes a DC power flow to determine the loss of load during an event. Loss of load is the consequence that is minimized in this optimization model as the objective function. The results shown in this paper are from the IEEE RTS-96 three area reliability model. The scenario generation and optimization model have also been utilized on full utility models, but those results cannot be published.
A wide-area controller to damp inter-area oscillations in the North American Western Interconnection (WI) by modulating power transfers in a HVDC link is used in this paper to investigate the effects that latencies in its feedback signals have on its performance. This controller uses two feedback measurements to perform its control action. The analysis show that the stabilizing effect of the controller in transient stability and small signal stability is compromised as the feedback measurements experience higher delays. The results show that one of the feedback signals can tolerate more delay than the other. The analysis was performed with Bode plots and time domain simulations on a reduced order model of the WI from which a linear version was obtained.
Stochastic versions of the unit commitment problem have been advocated for addressing the uncertainty presented by high levels of wind power penetration. However, little work has been done to study trade-offs between computational complexity and the quality of solutions obtained as the number of probabilistic scenarios is varied. Here, we describe extensive experiments using real publicly available wind power data from the Bonneville Power Administration. Solution quality is measured by re-enacting day-ahead reliability unit commitment (which selects the thermal units that will be used each hour of the next day) and real-time economic dispatch (which determines generation levels) for an enhanced WECC-240 test system in the context of a production cost model simulator; outputs from the simulation, including cost, reliability, and computational performance metrics, are then analyzed. Unsurprisingly, we find that both solution quality and computational difficulty increase with the number of probabilistic scenarios considered. However, we find unexpected transitions in computational difficulty at a specific threshold in the number of scenarios, and report on key trends in solution performance characteristics. Our findings are novel in that we examine these tradeoffs using real-world wind power data in the context of an out-of-sample production cost model simulation, and are relevant for both practitioners interested in deploying and researchers interested in developing scalable solvers for stochastic unit commitment.
Emerging applications of metal-organic frameworks (MOFs) in electronic devices will benefit from the design and synthesis of intrinsically, highly electronically conductive MOFs. However, very few are known to exist. It is a challenging task to search for electronically conductive MOFs within the tens of thousands of reported MOF structures. Using a new strategy (i.e., transfer learning) of combining machine learning techniques, statistical multivoting, and ab initio calculations, we screened 2932 MOFs and identified 6 MOF crystal structures that are metallic at the level of semilocal DFT band theory: Mn2[Re6X8(CN)6]4 (X = S, Se,Te), Mn[Re3Te4(CN)3], Hg[SCN]4Co[NCS]4, and CdC4. Five of these structures have been synthesized and reported in the literature, but their electrical characterization has not been reported. Our work demonstrates the potential power of machine learning in materials science to aid in down-selecting from large numbers of potential candidates and provides the information and guidance to accelerate the discovery of novel advanced materials.
Whitfield's laboratory notebook covers work from late 1960 into 1974. He used the notebook to capture ideas and to summarize what he was working on—including writing papers and traveling— as well as his research. It does not offer a detailed exploration of his thinking leading up to technical advances and it only rarely explicates experimental set-ups. It also has long gaps between some entries. It is nonetheless revealing of his approach, his focus, and his results.
Switched reluctance machines (SRMs) are low cost and fault tolerant alternatives for traction applications. Due to their relatively low torque density and high torque ripple, these machines have not been used in commercialized electrified power trains yet. The double-stator magnetic configuration, where a segmental rotor shared between two stators, is proven to have superior torque density, lower acoustic noise, and torque pulsation. The double-stator SRM (DSSRM) has a high potential of being the next generation of traction motors since it combines the advantages of permanent magnet-free machines, such as low cost and independence from supply chain issues associated with rare metals, while providing high torque and power densities. In this paper, we introduce the complete design process of a 100-kW DSSRM including electromagnetic, structural, thermal, and system level design. The performance of the developed DSSRM is verified with the experimental data. This paper presents overall study of DSSRM and describes merits of DSSRM drive system.
Shi, Chenyang; Billinge, Simon J.L.; Puma, Eric; Bang, Sun H.; Bean, Nathaniel J.H.; De Sugny, Jean C.; Gambee, Robert G.; Haskell, Richard C.; Hightower, Adrian; Monson, Todd
Barium titanate (BTO) nanoparticles (sizes 10-500 nm) exhibit a displacement of the Ti atom from the center of the perovskite unit cell as inferred from synchrotron x-ray diffraction patterns (XRD) analyzed using atomic pair distribution functions (PDFs). Fits to PDFs acquired at temperatures of 20 °C-220 °C indicate that these Ti displacements (∼0.1 Å) are comparable to or even greater than those in the bulk material. Moreover, these displacements persist at temperatures well above 120 °C, where the tetragonal-to-pseudocubic phase transition occurs in the bulk. Tetragonal Raman spectral lines were observed for all sizes of these BTO nanoparticles and confirm a distorted unit cell up to 120 °C. Above 120 °C, the small BTO nanoparticles (10, 50, 100 nm) continue to display tetragonal Raman lines, though with slowly decreasing amplitudes as the temperature rises. In contrast, the tetragonal Raman lines of large BTO nanoparticles (300, 400, 500 nm) disappear abruptly above 120 °C, suggestive of bulk material. Indeed, fits to large-particle x-ray PDFs over the range 20-60 Å reveal a sharp, long-range structural change toward a cubic lattice at 120 °C, again consistent with bulk material. This sharp, long-range structural change is absent in the small particles. In fact, laboratory XRD Bragg peak profiles for the small BTO particles appear to be singlets at 20 °C, indicating that significant long-range cubic order already exists at room temperature. As temperature rises, this long-range cubic order is gradually reinforced, as inferred from long-range fits of the small particle PDFs. By combining information from x-ray PDFs, Raman spectra, and Bragg peak profiles, we conclude that small BTO nanoparticles exhibit both short-range (unit-cell) distortion and long-range (mesoscale) cubic order from 20 °C to 220 °C, while the large nanoparticles behave as bulk material, differing from small particles only by exhibiting long-range tetragonal order below 120 °C and a mesoscale structural phase change at 120 °C.
The search for multivariate quadrature rules of minimal size with a specified polynomial accuracy has been the topic of many years of research. Finding such a rule allows accurate integration of moments, which play a central role in many aspects of scientific computing with complex models. The contribution of this paper is twofold. First, we provide novel mathematical analysis of the polynomial quadrature problem that provides a lower bound for the minimal possible number of nodes in a polynomial rule with specified accuracy. We give concrete but simplistic multivariate examples where a minimal quadrature rule can be designed that achieves this lower bound, along with situations that showcase when it is not possible to achieve this lower bound. Our second contribution is the formulation of an algorithm that is able to efficiently generate multivariate quadrature rules with positive weights on non-tensorial domains. Our tests show success of this procedure in up to 20 dimensions. We test our method on applications to dimension reduction and chemical kinetics problems, including comparisons against popular alternatives such as sparse grids, Monte Carlo and quasi Monte Carlo sequences, and Stroud rules. The quadrature rules computed in this paper outperform these alternatives in almost all scenarios.
Li, Shengxi; Teague, Mary T.; Doll, Gary L.; Schindelholz, Eric J.
This work aims to investigate the waterline corrosion of pure copper in 4 M NaCl solution. Three distinct regions are identified. Corrosion products formed at the waterline are characterized by micro-Raman spectroscopy, complemented by SEM/EDS, as a function of immersion time. The co-existence of four copper species is explained by thermodynamic equilibrium consideration. The composition of spreading region is determined and compared with the oxide film formation in different pH NaOH solutions. The anodic dissolution of copper exposed to the bulk electrolyte is investigated by electrochemical methods. The pH and potential profiles across three regions are proposed.
Rechargeable Zn/MnO2 alkaline batteries are a promising technology for grid storage applications since they are safe, low cost, and considered environmentally friendly. Here, a commercial ceramic sodium ion conductor which is impervious to zincate [Zn(OH)42−], a contributor to MnO2 cathode failure, is evaluated as the battery separator. As received, the ionic conductivity of this separator was measured with electrochemical impedance spectroscopy to be 3.5 mS cm−1, while its thickness is 1.0 mm, resulting in large total membrane resistance of 25.3 Ω. Reducing the thickness of the ceramic to 0.5 mm provided for a decreased resistance of 9.8 Ω. Crossover experiments conducted using inductively coupled plasma - mass spectrometry measurements failed to measure any Zn(OH)42− transport indicating a diffusion coefficient that is at least two orders of magnitude less than that for the commercial cellophane and Celgard separators. For 5% DOD at a C/5 rate, the cycle lifetime was increased by over 22% using the 0.5 mm thick ceramic separator compared to traditional Celgard and cellophane separators. Scanning electron microscopy/energy dispersive X-ray spectroscopy and X-ray diffraction characterization of cycled electrodes showed limited amounts of zinc species on the cathode utilizing the ceramic separator, consistent with its prevention of Zn(OH)42− transport.
The Magnetized Liner Inertial Fusion (MagLIF) concept [Slutz et al. Phys. Plasmas 17, 056303 (2010); Gomez et al. Phys. Rev. Lett. 113, 155003 (2014)] is being studied on the Z facility at Sandia National Laboratories. MagLIF is a specific example of the more general Magnetized Inertial Fusion (MIF) approach to fusion. Numerical simulations indicate that yields approaching 100 kJ should be possible on the Z machine and much higher yields (10–1000 MJ) should be possible with pulsed power machines producing larger drive currents (45–60 MA) [Slutz et al. Phys. Plasmas 23, 022702 (2016)]. A significant advantage of MIF is that the implosions can be driven more slowly than conventional inertial fusion. In general, the efficiency of pulsed power machines increases with the current rise-time; however, we show by numerical simulation that the current and energy required to obtain a given fusion gain increase monotonically with the current rise-time over the range (10–500 ns). In conclusion, these results can be used to optimize the design of future accelerators to drive MIF concepts such as MagLIF. We also show that the required preheat energy increases strongly with current rise-time, which indicates that very long current rise-times are not desirable at least for MagLIF.
Epoxies and resins can require careful temperature sensing and control in order to monitor and prevent degradation. To sense the temperature inside a mold, it is desirable to utilize a small, wireless sensing element. In this paper, we describe a new architecture for wireless temperature sensing and closed-loop temperature control of exothermic polymers. This architecture is the first to utilize magnetic field estimates of the temperature of permanent magnets within a temperature feedback control loop. We further improve performance and applicability by demonstrating sensing performance at relevant temperatures, incorporating a cure estimator, and implementing a nonlinear temperature controller. This novel architecture enables unique experimental results featuring closed-loop control of an exothermic resin without any physical connection to the inside of the mold. In this paper we describe each of the unique features of this approach including magnetic field-based temperature sensing, Extended Kalman Filtering (EKF) for cure state estimation, and nonlinear feedback control over time-varying temperature trajectories. We use experimental results to demonstrate how low-cost permanent magnets can provide wireless temperature sensing up to ~90°C. In addition, we use a polymer curecontrol test-bed to illustrate how internal temperature sensing can provide improved temperature control over both short and long time-scales. In conclusion, this wireless temperature sensing and control architecture holds value for a range of manufacturing applications.
This article focuses on the finite element modeling of toroidal microinductors, employing first-of-its-kind nanocomposite magnetic core material and superparamagnetic iron nanoparticles covalently cross-linked in an epoxy network. Energy loss mechanisms in existing inductor core materials are covered as well as discussions on how this novel core material eliminates them providing a path toward realizing these low form factor devices. Designs for both a 2 μH output and a 500 nH input microinductor are created via the model for a high-performance buck converter. Both modeled inductors have 50 wire turns, less than 1 cm3 form factors, less than 1 Ω AC resistance, and quality factors, Q's, of 27 at 1 MHz. In addition, the output microinductor is calculated to have an average output power of 7 W and a power density of 3.9 kW/in3 by modeling with the 1st generation iron nanocomposite core material.
Significant reductions recently seen in the size of wide-bandgap power electronics have not been accompanied by a relative decrease in the size of the corresponding magnetic components. To achieve this, a new generation of materials with high magnetic saturation and permeability are needed. Here, we develop gram-scale syntheses of superparamagnetic Fe/FexOy core-shell nanoparticles and incorporate them as the magnetic component in a strongly magnetic nanocomposite. Nanocomposites are typically formed by the organization of nanoparticles within a polymeric matrix. However, this approach can lead to high organic fractions and phase separation; reducing the performance of the resulting material. Here, we form aminated nanoparticles that are then cross-linked using epoxy chemistry. The result is a magnetic nanoparticle component that is covalently linked and well separated. By using this 'matrix-free' approach, we can substantially increase the magnetic nanoparticle fraction, while still maintaining good separation, leading to a superparamagnetic nanocomposite with strong magnetic properties.
In Part I, equal channel angular extrusion (ECAE) was demonstrated as a novel, simple-shear deformation process for producing bulk forms of the low ductility Fe-Co-2V (Hiperco 50A®) soft ferromagnetic alloy with refined grain sizes. Microstructures and mechanical properties were discussed. In this Part II contribution, the crystallographic textures and quasi-static magnetic properties of ECAE-processed Hiperco were characterized. The textures were of a simple-shear character defined by partial {110} and (111) fibers inclined relative to the extrusion direction, in agreement with the expectations for simple-shear deformation textures of BCC metals. These textures were observed throughout all processing conditions and only slightly reduced in intensity by subsequent recrystallization heat treatments. Characterization of the magnetic properties revealed a lower coercivity and higher permeability for ECAE-processed Hiperco specimens relative to the conventionally processed and annealed Hiperco bar. The effects of the resultant microstructure and texture on the coercivity and permeability magnetic properties are discussed.
The growth of High Performance Computer (HPC) systems increases the complexity with respect to understanding resource utilization, system management, and performance issues. While raw performance data is increasingly exposed at the component level, the usefulness of the data is dependent on the ability to do meaningful analysis on actionable timescales. However, current system monitoring infrastructures largely focus on data collection, with analysis performed off-system in post-processing mode. This increases the time required to provide analysis and feedback to a variety of consumers. In this work, we enhance the architecture of a monitoring system used on large-scale computational platforms, to integrate streaming analysis capabilities at arbitrary locations within its data collection, transport, and aggregation facilities. We leverage the flexible communication topology of the monitoring system to enable placement of transformations based on overhead concerns, while still enabling low-latency exposure on node. Our design internally supports and exposes the raw and transformed data uniformly for both node level and off-system consumers. We show the viability of our implementation for a case with production-relevance: run-time determination of the relative per-node files system demands.
High-performance computing (HPC) systems are critically important to the objectives of universities, national laboratories, and commercial companies. Because of the cost of deploying and maintaining these systems ensuring their efficient use is imperative. Job scheduling and resource management are critically important to the efficient use of HPC systems. As a result, significant research has been conducted on how to effectively schedule user jobs on HPC systems. Developing and evaluating job scheduling algorithms, however, requires a detailed understanding of how users request resources on HPC systems. In this paper, we examine a corpus of job data that was collected on Trinity, a leadership-class supercomputer. During the stabilization period of its Intel Xeon Phi (Knights Landing) partition, it was made available to users outside of a classified environment for the Trinity Open Science Phase 2 campaign. We collected information from the resource manager about each user job that was run during this Open Science period. In this paper, we examine the jobs contained in this dataset. Our analysis reveals several important characteristics of the jobs submitted during the Open Science period and provides critical insight into the use of one of the most powerful supercomputers in existence. Specifically, these data provide important guidance for the design, development, and evaluation of job scheduling and resource management algorithms.
The review team convened at the University of Utah March 7-8, 2018, to review the Carbon Capture Multidisciplinary Science Center (CCMSC) funded by the 2nd Predictive Science ASC Alliance Program (PSAAP II). Center leadership and researchers made very clear and informative presentations, accurately portraying their work and successes while candidly discussing their concerns and known areas in need of improvement.
The performance critical path for MPI implementations relies on fast receive side operation, which in turn requires fast list traversal. The performance of list traversal is dependent on data-locality; whether the data is currently contained in a close-to-core cache due to its temporal locality or if its spacial locality allows for predictable pre-fetching. In this paper, we explore the effects of data locality on the MPI matching problem by examining both forms of locality. First, we explore spacial locality, by combining multiple entries into a single linked list element, we can control and modify this form of locality. Secondly, we explore temporal locality by utilizing a new technique called “hot caching”, a process that creates a thread to periodically access certain data, increasing its temporal locality. In this paper, we show that by increasing data locality, we can improve MPI performance on a variety of architectures up to 4x for micro-benchmarks and up to 2x for an application.
The development of the unsteady pressure field on the floor of a rectangular cavity was studied at Mach 0.9 using high-frequency pressure-sensitive paint. Power spectral amplitudes at each cavity resonance exhibit a spatial distribution with a streamwise-oscillatory pattern; additional maxima and minima appear as the mode number is increased. This spatial distribution also appears in the propagation velocity of modal pressure disturbances. This behaviour was tied to the superposition of a downstream-propagating shear-layer disturbance and an upstream-propagating acoustic wave of different amplitudes and convection velocities, consistent with the classical Rossiter model. The summation of these waves generates a net downstream-travelling wave whose amplitude and phase velocity are modulated by a fixed envelope within the cavity. This travelling-wave interpretation of the Rossiter model correctly predicts the instantaneous modal pressure behaviour in the cavity. Subtle spanwise variations in the modal pressure behaviour were also observed, which could be attributed to a shift in the resonance pattern as a result of spillage effects at the edges of the finite-width cavity.
Recent work suggests that thermally stable nanocrystallinity in metals is achievable in several binary alloys by modifying grain boundary energies via solute segregation. The remarkable thermal stability of these alloys has been demonstrated in recent reports, with many alloys exhibiting negligible grain growth during prolonged exposure to near-melting temperatures. Pt–Au, a proposed stable alloy consisting of two noble metals, is shown to exhibit extraordinary resistance to wear. Ultralow wear rates, less than a monolayer of material removed per sliding pass, are measured for Pt–Au thin films at a maximum Hertz contact stress of up to 1.1 GPa. This is the first instance of an all-metallic material exhibiting a specific wear rate on the order of 10−9 mm3 N−1 m−1, comparable to diamond-like carbon (DLC) and sapphire. Remarkably, the wear rate of sapphire and silicon nitride probes used in wear experiments are either higher or comparable to that of the Pt–Au alloy, despite the substantially higher hardness of the ceramic probe materials. High-resolution microscopy shows negligible surface microstructural evolution in the wear tracks after 100k sliding passes. Mitigation of fatigue-driven delamination enables a transition to wear by atomic attrition, a regime previously limited to highly wear-resistant materials such as DLC.
We discuss the multiple pursuer-based intercept of a threat unmanned aerial system (UAS) with stochastic dynamics via multiple pursuing UASs, using forward stochastic reachability and receding horizon control techniques. We formulate a stochastic model for the threat that can emulate the potentially adversarial behavior and is amenable to the existing scalable results in forward stochastic reachability literature. The optimal state for the intercept for each individual pursuer is obtained via a log-concave optimization problem, and the open-loop control paths are obtained via a convex optimization problem. With stochasticity modeled as a Gaussian process, we can approximate the optimization problem as a quadratic program, to enable real-time path planning. We also incorporate real-time sensing into the path planning by using a receding horizon controller, to improve the intercept probabilities. We validate the proposed framework via hardware experiments.
This paper presents a control design methodology that addresses high penetration of variable generation or renewable energy sources and loads for networked AC /DC microgrid systems as an islanded subsystem or as part of larger electric power grid systems. High performance microgrid systems that contain large amounts of stochastic sources and loads is a major goal for the future of electric power systems. Alternatively, methods for controlling and analyzing AC/ DC microgrid systems will provide an understanding into the tradeoffs that can be made during the design phase. This method develops both a control design methodology and realizable hierarchical controllers that are based on the Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) methodology that regulates renewable energy sources, varying loads and identifies energy storage requirements for a networked AC/DC microgrid system. Both static and dynamic stability conditions are derived. A renewable energy scenario is considered for a networked three DC microgrids tied into an AC ringbus configuration. Numerical simulation results are presented.
We present analysis and modeling of Al sputtering and ionization in attached, low-power L-mode plasmas near the outer divertor strike point of the DIII-D tokamak. Al serves as a useful proxy for Be, the low-Z main wall material for ITER and JET that will undergo significant divertor plasma contact upon migrating from the first wall to the divertor. Al is easily distinguishable from background sources in DIII-D (namely C and B), has a high physical sputtering yield similar to Be, and has a long ionization mean free path compared to its gyro radius ({λi} /rgyro ∼ 2.5). Using neutral Al emission imaging techniques, we measured a toroidal and radial asymmetry in the shape of the photo-emission plumes of sputtered neutral Al that was consistent with previously observed asymmetry in the distribution of redeposited Al in these experiments. We propose that the main cause of the emission and redeposition asymmetry is due to a sputtering anisotropy caused by near-grazing angle incident ions. The observed emission asymmetry was reproduced using a simple emission/ionization model that included full angular distributions of sputtering yield and energy calculated by SDTRIM.SP, but not when symmetric, mono-energetic cosine sputtering distributions were assumed. We used an ion orbit tracking model to calculate the distributions of ion impact energies through the potential gradient in the magnetic pre-sheath and Debye sheath. We found that with the magnetic field pitch angle (1.5°-2° with respect to the surface plane), the majority of ions strike the surface at <15° with respect to the surface plane, leading to angular sputtering yield and energy distributions with significant forward-scattering bias. We also observed surface microstructure consistent with directional sputtering and ion flux shadowing expected from the calculated ion incidence angles.
The High-Performance Computing of today is much different than the supercomputing resources a few decades ago. The supercomputers of the past were huge complexes of hundreds of interconnected computers that had large teams of specialists to keep them running. Today, while supercomputers like Summit (the world's most powerful supercomputer as of June 2018, installed at Oak Ridge National Laboratory) are still in high demand for extremely fast computational power (over 200,000 trillion calculations per second, or 200 petaflops), researchers at Sandia now have access to non-traditional computing resources in the way of very powerful graphics processing units (GPUs). These GPU systems have enabled an entirely new avenue of exploration for Sandia, allowing researchers to further tackle problems in energy, advanced materials, artificial intelligence, and nuclear weapons. Many teams at Sandia utilize these GPU clusters to build models through the use of machine learning. These models are faster representations of their code-driven counterparts and can often be leveraged from the exascale computing resources of traditionally larger systems with huge boosts in performance. We highlight two resources for these smaller systems: the team that builds the hardware, and the team that researches and builds the machine learning algorithms.
EmrE is a small, homodimeric membrane transporter that exploits the established electrochemical proton gradient across the Escherichia coli inner membrane to export toxic polyaromatic cations, prototypical of the wider small-multidrug resistance transporter family. While prior studies have established many fundamental aspects of the specificity and rate of substrate transport in EmrE, low resolution of available structures has hampered identification of the transport coupling mechanism. Here we present a complete, refined atomic structure of EmrE optimized against available cryo-electron microscopy (cryo-EM) data to delineate the critical interactions by which EmrE regulates its conformation during the transport process. With the model, we conduct molecular dynamics simulations of the transporter in explicit membranes to probe EmrE dynamics under different substrate loading and conformational states, representing different intermediates in the transport cycle. The refined model is stable under extended simulation. The water dynamics in simulation indicate that the hydrogen-bonding networks around a pair of solvent-exposed glutamate residues (E14) depend on the loading state of EmrE. One specific hydrogen bond from a tyrosine (Y60) on one monomer to a glutamate (E14) on the opposite monomer is especially critical, as it locks the protein conformation when the glutamate is deprotonated. The hydrogen bond provided by Y60 lowers the pKa of one glutamate relative to the other, suggesting both glutamates should be protonated for the hydrogen bond to break and a substrate-free transition to take place. These findings establish the molecular mechanism for the coupling between proton transfer reactions and protein conformation in this proton-coupled secondary transporter.
In an effort to generate single-source precursors for the production of metal-siloxide (MSiOx) materials, the tris(trimethylsilyl)silanol (H-SST or H-OSi(SiMe3)3 (1) ligand was reacted with a series of group 4 and 5 metal alkoxides. The group 4 products were crystallographically characterized as [Ti(SST)2(OR)2] (OR = OPri (2), OBut (3), ONep (4)); [Ti(SST)3(OBun)] (5); [Zr(SST)2(OBut)2(py)] (6); [Zr(SST)3(OR)] (OR = OBut (7), ONep, (8)); [Hf(SST)2(OBut)2] (9); and [Hf(SST)2(ONep)2(py)n] (n = 1 (10), n = 2 (10a)) where OPri = OCH(CH3)2, OBut = OC(CH3)3, OBun = O(CH2)3CH3, ONep = OCH2C(CH3)3, py = pyridine. The crystal structures revealed varied SST substitutions for: monomeric Ti species that adopted a tetrahedral (T-4) geometry; monomeric Zr compounds with coordination that varied from T-4 to trigonal bipyramidal (TBPY-5); and monomeric Hf complexes isolated in a TBPY-5 geometry. For the group 5 species, the following derivatives were structurally identified as [V(SST)3(py)2] (11), [Nb(SST)3(OEt)2] (12), [Nb(O)(SST)3(py)] (13), 2[H][(Nb(μ-O)2(SST))6(μ6-O)] (14), [Nb8O10(OEt)18(SST)2·1/5Na2O] (15), [Ta(SST)(μ-OEt)(OEt)3]2 (16), and [Ta(SST)3(OEt)2] (17) where OEt = OCH2CH3. The group 5 monomeric complexes were solved in a TBPY-5 arrangement, whereas the Ta of the dinculear 16 was solved in an octahedral coordination environment. Thermal analyses of these precursors revealed a stepwise loss of ligand, which indicated their potential utility for generating the MSiOx materials. The complexes were thermally processed (350-1100 °C, 4 h, ambient atmosphere), but instead of the desired MSiOx, transmission electron microscopy analyses revealed that fractions of the group 4 and group 5 precursors had formed unusual metal oxide silica architectures.
This work demonstrates that there is an impact on safety response with nanoscale silicon materials compared to graphite based anodes. Additionally, there appears to be a fundamental difference in abuse response based on more than just silicon content, particle size, and state of charge for the electrodes. Control of surface reactivity is essential to both control response homogeneity (for quantification) and understand the mechanisms during abuse conditions with silicon anodes.
Many of the BSAF participants provided source terms to be evaluated by Sandia National Laboratories by applying HYSPLIT [2,3,4,5] to treat atmospheric transport and dispersion (ATD). The objective was to estimate the deposition pattern that would have resulted from the predicted source term. For the participants who provided results for all three units, the overall deposition pattern can be compared with the observed deposition pattern; for the participants who submitted source terms for one or two units, the results can only be compared with each other. Atmospheric transport calculations were performed for a single isotope, Cs-137. It is the primary isotope of concern for long-term contamination and it is relatively easy to measure the strong gamma signal produced from its short-lived decay product, Ba-137m. All the atmospheric transport calculations used the actual location of each of the three units; the releases were not presumed to emanate from the same location. Also, when they were provided, release energies were accounted for in the analysis, so plume lofting was considered. Finally, aerosol size distribution data were considered for purposes of estimating deposition. In some cases, aerosol size distribution can significantly influence deposition patterns.
The role of Sandia National Laboratories to this project is to image in-cylinder soot and PAH under conditions where PAH and soot are on the threshold of formation due to dilution by excess nitrogen gas. The primary effect of dilution is to lower the combustion temperatures, and if sufficient dilution is provided, soot and/or PAH formation can be completely inhibited. Hence, these experimental data are useful for validation of CFD predictions of initial soot and PAH formation.
Considering the power constrained scaling of silicon complementary metal-oxide-semiconductor technology, the use of high mobility III-V compound semiconductors such as In0.53Ga0.47As in conjunction with high-κ dielectrics is becoming a promising option for future n-type metal-oxide-semiconductor field-effect-transistors. Development of low dissipation field-effect tunable III-V based photonic devices integrated with high-κ dielectrics is therefore very appealing from a technological perspective. In this work, we present an experimental realization of a monolithically integrable, field-effect-tunable, III-V hybrid metasurface operating at long-wave-infrared spectral bands. Our device relies on strong light-matter coupling between epsilon-near-zero (ENZ) modes of an ultra-thin In0.53Ga0.47As layer and the dipole resonances of a complementary plasmonic metasurface. The tuning mechanism of our device is based on field-effect modulation, where we modulate the coupling between the ENZ mode and the metasurface by modifying the carrier density in the ENZ layer using an external bias voltage. Modulating the bias voltage between ±2 V, we deplete and accumulate carriers in the ENZ layer, which result in spectrally tuning the eigenfrequency of the upper polariton branch at 13 μm by 480 nm and modulating the reflectance by 15%, all with leakage current densities less than 1 μA/cm2. Our wavelength scalable approach demonstrates the possibility of designing on-chip voltage-tunable filters compatible with III-V based focal plane arrays at mid- and long-wave-infrared wavelengths.
In high-performance computing environments, input/output (I/O) from various sources often contend for scarce available bandwidth. Adding to the I/O operations inherent to the failure-free execution of an application, I/O from checkpoint/restart (CR) operations (used to ensure progress in the presence of failures) place an additional burden as it increase I/O contention, leading to degraded performance. In this work, we consider a cooperative scheduling policy that optimizes the overall performance of concurrently executing CR-based applications which share valuable I/O resources. First, we provide a theoretical model and then derive a set of necessary constraints needed to minimize the global waste on the platform. Our results demonstrate that the optimal checkpoint interval, as defined by Young/Daly, despite providing a sensible metric for a single application, is not sufficient to optimally address resource contention at the platform scale. We therefore show that combining optimal checkpointing periods with I/O scheduling strategies can provide a significant improvement on the overall application performance, thereby maximizing platform throughput. Overall, these results provide critical analysis and direct guidance on checkpointing large-scale workloads in the presence of competing I/O while minimizing the impact on application performance.
Large-scale HPC systems increasingly incorporate sophisticated power management control mechanisms. While these mechanisms are potentially useful for performing energy and/or power-aware job scheduling and resource management (EPA JSRM), greater understanding of their operation and performance impact on real-world applications is required before they can be applied effectively in practice. In this paper, we compare static p-state control to static node-level power cap control on a Cray XC system. Empirical experiments are performed to evaluate node-to-node performance and power usage variability for the two mechanisms. We find that static p-state control produces more predictable and higher performance characteristics than static node-level power cap control at a given power level. However, this performance benefit is at the cost of less predictable power usage. Static node-level power cap control produces predictable power usage but with more variable performance characteristics. Our results are not intended to show that one mechanism is better than the other. Rather, our results demonstrate that the mechanisms are complementary to one another and highlight their potential for combined use in achieving effective EPA JSRM solutions.
We present a memory-scalable, parallel, sparse multifrontal solver for solving symmetric postive-definite systems arising in scientific and engineering applications. Factorizing sparse matrices requires memory for both the computed factors and the temporary workspaces for computing each frontal matrix - a data structure commonly used within multifrontal methods. To factorize multiple frontal matrices in parallel, the conventional approach is to allocate a uniform workspace for each hardware thread. In the manycore era, this results in increasing memory usage proportional to the number of hardware threads. We remedy this problem by using dynamic task parallelism with a scalable memory pool. Tasks are spawned while traversing an assembly tree and executed after their dependences are satisfied. We also use an idea to respawn the tasks when certain conditions are not met. Temporary workspace for frontal matrices in each task is allocated from a memory pool designed by us. If the requested memory space is not available in the memory pool, the task is respawned to yield the hardware thread to execute other tasks. The respawned task is executed after high priority tasks are executed. This approach allows to have robust parallel performance within a bounded memory space. Experimental results demonstrate the merits of our implementation on Intel multicore and manycore architectures.
Large-scale HPC systems increasingly incorporate sophisticated power management control mechanisms. While these mechanisms are potentially useful for performing energy and/or power-aware job scheduling and resource management (EPA JSRM), greater understanding of their operation and performance impact on real-world applications is required before they can be applied effectively in practice. In this paper, we compare static p-state control to static node-level power cap control on a Cray XC system. Empirical experiments are performed to evaluate node-to-node performance and power usage variability for the two mechanisms. We find that static p-state control produces more predictable and higher performance characteristics than static node-level power cap control at a given power level. However, this performance benefit is at the cost of less predictable power usage. Static node-level power cap control produces predictable power usage but with more variable performance characteristics. Our results are not intended to show that one mechanism is better than the other. Rather, our results demonstrate that the mechanisms are complementary to one another and highlight their potential for combined use in achieving effective EPA JSRM solutions.
The dragonfly network topology has attracted attention in recent years owing to its high radix and constant diameter. However, the influence of job allocation on communication time in dragonfly networks is not fully understood. Recent studies have shown that random allocation is better at balancing the network traffic, while compact allocation is better at harnessing the locality in dragonfly groups. Based on these observations, this paper introduces a novel allocation policy called Level-Spread for dragonfly networks. This policy spreads jobs within the smallest network level that a given job can fit in at the time of its allocation. In this way, it simultaneously harnesses node adjacency and balances link congestion. To evaluate the performance of Level-Spread, we run packet-level network simulations using a diverse set of application communication patterns, job sizes, and communication intensities. We also explore the impact of network properties such as the number of groups, number of routers per group, machine utilization level, and global link bandwidth. Level-Spread reduces the communication overhead by 16% on average (and up to 71%) compared to the state-of-The-Art allocation policies.
Here, a numerical scheme is presented for approximating fractional order Poisson problems in two and three dimensions. The scheme is based on reformulating the original problem posed over $\Omega$ on the extruded domain $\mathcal{C}=\Omega\times[0,\infty)$ following. The resulting degenerate elliptic integer order PDE is then approximated using a hybrid FEM-spectral scheme. Finite elements are used in the direction parallel to the problem domain $\Omega$, and an appropriate spectral method is used in the extruded direction. The spectral part of the scheme requires that we approximate the true eigenvalues of the integer order Laplacian over $\Omega$. We derive an a priori error estimate which takes account of the error arising from using an approximation in place of the true eigenvalues. We further present a strategy for choosing approximations of the eigenvalues based on Weyl's law and finite element discretizations of the eigenvalue problem. The system of linear algebraic equations arising from the hybrid FEM-spectral scheme is decomposed into blocks which can be solved effectively using standard iterative solvers such as multigrid and conjugate gradient. Numerical examples in two and three dimensions suggest that the approach is quasi-optimal in terms of complexity.
While nearly all theoretical and computational studies of entangled polymer melts have focused on uniform samples, polymer synthesis routes always result in some dispersity, albeit narrow, of distribution of molecular weights (Crossed D signM=Mw/Mn∼1.02-1.04). Here, the effects of dispersity on chain mobility are studied for entangled, disperse melts using a coarse-grained model for polyethylene. Polymer melts with chain lengths set to follow a Schulz-Zimm distribution for the same average Mw=36 kg/mol with Crossed D signM=1.0 to 1.16, were studied for times of 600-800 μs using molecular dynamics simulations. This time frame is longer than the time required to reach the diffusive regime. We find that dispersity in this range does not affect the entanglement time or tube diameter. However, while there is negligible difference in the average mobility of chains for the uniform distribution Crossed D signM=1.0 and Crossed D signM=1.02, the shortest chains move significantly faster than the longest ones offering a constraint release pathway for the melts for larger Crossed D signM.
TiCl3 and TiF3 additives are known to facilitate hydrogenation and dehydrogenation in a variety of hydrogen storage materials, yet the associated mechanism remains under debate. Here, experimental and computational studies are reported for the reactivity with hydrogen gas of bulk and ball-milled TiCl3 and TiF3 at the temperatures and pressures for which these additives are observed to accelerate reactions when added to hydrogen storage materials. TiCl3, in either the α or δ polymorphic forms and of varying crystallite size ranging from ∼5 to 95 nm, shows no detectable reaction with prolonged exposure to hydrogen gas at elevated pressures (∼120 bar) and temperatures (up to 200 °C). Similarly, TiF3 with varying crystallite size from ∼4 to 25 nm exhibits no detectable reaction with hydrogen gas. Post-exposure vibrational and electronic structure investigations using Fourier transform infrared spectroscopy and x-ray absorption spectroscopy confirm this analysis. Moreover, there is no significant promotion of H2 dissociation at either interior or exterior surfaces, as demonstrated by H2/D2 exchange studies on pure TiF3. The computed energy landscape confirms that dissociative adsorption of H2 on TiF3 surfaces is thermodynamically inhibited. However, Ti-based additives could potentially promote H2 dissociation at interfaces where structural and compositional varieties are expected, or else by way of subsequent chemical transformations. At interfaces, metallic states could be formed intrinsically or extrinsically, possibly enabling hydrogen-coupled electronic transfer by donating electrons.
In this study, we focus on a hydrogeological inverse problem specifically targeting monitoring soil moisture variations using tomographic ground penetrating radar (GPR) travel time data. Technical challenges exist in the inversion of GPR tomographic data for handling non-uniqueness, nonlinearity and high-dimensionality of unknowns. We have developed a new method for estimating soil moisture fields from crosshole GPR data. It uses a pilot-point method to provide a low-dimensional representation of the relative dielectric permittivity field of the soil, which is the primary object of inference: the field can be converted to soil moisture using a petrophysical model. We integrate a multi-chain Markov chain Monte Carlo (MCMC)–Bayesian inversion framework with the pilot point concept, a curved-ray GPR travel time model, and a sequential Gaussian simulation algorithm, for estimating the dielectric permittivity at pilot point locations distributed within the tomogram, as well as the corresponding geostatistical parameters (i.e., spatial correlation range). We infer the dielectric permittivity as a probability density function, thus capturing the uncertainty in the inference. The multi-chain MCMC enables addressing high-dimensional inverse problems as required in the inversion setup. The method is scalable in terms of number of chains and processors, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. The proposed inversion approach can successfully approximate the posterior density distributions of the pilot points, and capture the true values. The computational efficiency, accuracy, and convergence behaviors of the inversion approach were also systematically evaluated, by comparing the inversion results obtained with different levels of noises in the observations, increased observational data, as well as increased number of pilot points.
This work outlines the development of a two-fluid molten salt reactor process and safeguards model. The model is split into two parts consisting of a process model and a safeguards model. The process model is based on a design by Flibe Energy, the Liquid-Fluoride Thorium Reactor, which is a two-fluid molten salt reactor that performs full salt processing on-site to remove fission products and re-fuel the reactor. The model simulates feed and consumption rates of the reactor fuel and blanket salts. The process model includes the reactor core and salt processing loops. The reactor core model has a robust architecture that allows for integration with other tools and data sets as they become available. A majority of the effort to date has been focused on the process model, and the safeguards model will be developed in detail in future work. A preliminary safeguards analysis was performed based on actinide inventories, and a preliminary materials accountancy approach was initialized. The results of this analysis are presented along with a description of the model development.
This work provides a detailed explanation of the MELCOR Plot File format. MELCOR is a fully integrated, engineering-level computer code that models the progression of severe accidents in light water reactor nuclear power plants, and it primarily exports its simulation data to a binary file in the Plot File format. This work documents the Plot File's overall structure and the data types of exported information. The process of interpreting and associating time series information with MELCOR's Plot Variables for complete time histories is also presented. The format and meaning of time-independent information, called Special information, is also discussed.
Developed by the U.S. Nuclear Regulatory Commission for assessment of reactor accidents, Response Technical Manual (RTM) is a paper-based report which contains simple methods for estimating possible accident scenarios and relevant consequences for different kinds of radiological events. Based on RTM, a software called Response Technical Tools (RTT) was developed by Sandia National Laboratories to convert the paper manual into an automated and easy-to-use code. In particular, the RTT focuses on the nuclear power plant severe accidents and is informed by state-of-the-art analyses and software programs, such as MELCOR and MAAP. RTT evaluations can be used to track and predict, at a very coarse level, the progression of a severe accident in nuclear power plant. The RTT allows a user to track the progress of an accident in a nuclear power plant from the point of initiation through the point of containment breach and release to the environment.
Sandia National Laboratories performed analysis to develop conservative hazard guidelines regarding firefighters working near photovoltaic (PV) arrays. Assuming implementation of NFPA 70 system shutdown requirements, the analysis focused on DC hazards only. Several different PV variables were considered, including system grounding and DC voltage classes. The hazard scenarios considered the contact conditions, current paths through the body, and PPE. Guidelines for the hazard definitions for men and women were based on the IEC TS 60479-1 guidelines. The importance of PPE was illustrated in the results.
We describe our work to embed a Python interpreter in S3D, a highly scalable parallel direct numerical simulation reacting flow solver written in Fortran. Although S3D had no in-situ capability when we began, embedding the interpreter was surprisingly easy, and the result is an extremely flexible platform for conducting machine-learning experiments in-situ.
A critical component of the Underground Nuclear Explosion Signatures Experiment (UNESE) program is a realistic understanding of the post-detonation processes and changes in the environment that produce observable physical and radio-chemical signatures. Rock and fracture properties are essential parameters for any UNESE test bed. In response to the need for accurate modeling scenarios of these observations, an experimental program to determine the permeability and direct shear fracture properties of Barnwell core was developed. Room temperature gas permeability measurements of Barnwell core dried at 50degC yield permeability ranging from 6.24E-02 Darcys to 6.98E-08 Darcys. Friction angles from the direct shear tests vary from 28.1deg to 44.4deg for residual shear strength and average 47.9deg for peak shear strength. Cohesion averaged 3.2 psi and 13.3 psi for residual and peak shear strength values respectively. The work presented herein is the initial determination of an ongoing broader material characterization effort.
The Rapid Sample Insertion/Extraction System for Gamma Irradiation, otherwise known as the "rabbit" system, was a four-week long project which included many different aspects such as coding an Arduino, building PVC piping, and 3-D printing the "rabbit" capsules. The "rabbit" system is a system of PVC piping that allows a quick and efficient transfer of materials into and out of one of the irradiation chambers in the Gamma Irradiation Facility (GIF) with the use of a 3-D printed "rabbit." This "rabbit" encapsulates material to be irradiated and carries it from a position outside of the irradiation chamber to the basket inside of the chamber. The main purpose of this system is to save time and provide more exact data without any delays that normally occur when a person has to enter the chamber, retrieve data, and then analyze the data. This system should take measurements and retrieve the data instantaneously. The way in which the "rabbit" is sent through the PVC piping is with an advanced bi-directional, high-throughput pneumatic system, or a shop vacuum cleaner. When the vacuum is set to blow or suck then the "rabbit" will be pulled or pushed through the PVC piping to its intended destination and will hit sensors along the sides of the tubing when it reaches the end of the piping. These sensors tell the Arduino that the "rabbit" is finished moving throughout the tubing and stops a timer. Another timer is used to see how long the "rabbit" is being irradiated so when the "rabbit" reaches the sensors in the basket in the irradiation chamber another timer is started and it ends when the sensors no longer detect the "rabbit," which means that it has begun its journey back to the starting point. These times, as well as the temperatures, are the data necessary for the project and must be extremely accurate.
This chapter describes the processes that Members of the Workforce (MOW) follow to control Accountable Sealed Radioactive Sources (ASRSs) and Radioisotope Thermoelectric Generators (RTGs). It also describes the Sandia National Laboratories (SNL) program for implementing the ASRS requirements in 10 CFR 835.1202 and the ASRS and RTG requirements in DOE 0 231.1B.
This calculation documents the methodology used to determine Hazard Category (HC) II and III threshold quantities for select radioisotopes in the ISMS Software Nuclide Threshold Table.
Sandia National Laboratories has tested and evaluated three seismometers, the CMG-3V, manufactured by Guralp. These seismometers measure a single axes of broadband ground velocity in a borehole package. The purpose of the seismometer evaluation was to determine a measured sensitivity, response, passband, self-noise, dynamic range, and self-calibration ability. The Guralp CMG-3V seismometers are being evaluated for potential use in U.S. Air Force seismic monitoring systems as part of their Next Generation Qualification effort.
Cubic zirconium tungstate (α-ZrW2O8), a well-known negative thermal expansion material, has been investigated within the framework of density functional perturbation theory (DFPT), combined with experimental characterization to assess and validate computational results. Using combined Fourier transform infrared measurements and DFPT calculations, new and extensive assignments were made for the far-infrared (<400 cm−1) spectrum of α-ZrW2O8. A systematic comparison of DFPT-simulated infrared, Raman, and phonon density-of-state spectra with Fourier transform far-/mid-infrared and Raman data collected in this study, as well as with available inelastic neutron scattering measurements, shows the superior accuracy of the PBEsol exchange-correlation functional over standard PBE calculations for studying the spectroscopic properties of this material.
NoiseSpotter is currently designed for a 2-week deployment. This timeline will likely be problematic for MHK developers. Developers will want a robust/proven system that they can deploy and not worry about for longer than 2 weeks (especially for the continued monitoring of a site).
MFiX, a general-purpose Fortran-based suite, simulates the complex flow in fluidized bed applications via BiCGStab and GMRES methods along with plane relaxation preconditioners. Trilinos, an object-oriented framework, contains various first- and second-generation Krylov subspace solvers and preconditioners. We developed a framework to integrate MFiX with Trilinos as MFiX does not possess advanced linear methods. The framework allows MFiX to access advanced linear solvers and preconditioners in Trilinos. The integrated solver is called MFiX–Trilinos, here after. In the present work, we study the performance of variants of GMRES and CGS methods in MFiX–Trilinos and BiCGStab and GMRES solvers in MFiX for a 3D gas–solid fluidized bed problem. Two right preconditioners employed along with various solvers in MFiX–Trilinos are Jacobi and smoothed aggregation. The flow from MFiX–Trilinos is validated against the same from MFiX for BiCGStab and GMRES methods. And, the effect of the preconditioning on the iterative solvers in MFiX–Trilinos is also analyzed. In addition, the effect of left and right smoothed aggregation preconditioning on the solvers is studied. The performance of the first- and second-generation solver stacks in MFiX–Trilinos is studied as well for two different problem sizes.
The search for multivariate quadrature rules of minimal size with a specified polynomial accuracy has been the topic of many years of research. Finding such a rule allows accurate integration of moments, which play a central role in many aspects of scientific computing with complex models. The contribution of this paper is twofold. First, we provide novel mathematical analysis of the polynomial quadrature problem that provides a lower bound for the minimal possible number of nodes in a polynomial rule with specified accuracy. We give concrete but simplistic multivariate examples where a minimal quadrature rule can be designed that achieves this lower bound, along with situations that showcase when it is not possible to achieve this lower bound. Our second contribution is the formulation of an algorithm that is able to efficiently generate multivariate quadrature rules with positive weights on non-tensorial domains. Our tests show success of this procedure in up to 20 dimensions. We test our method on applications to dimension reduction and chemical kinetics problems, including comparisons against popular alternatives such as sparse grids, Monte Carlo and quasi Monte Carlo sequences, and Stroud rules. The quadrature rules computed in this paper outperform these alternatives in almost all scenarios.
Many existing shape memory alloy (SMA) devices consist of slender beams and frames. To better understand SMA beam behavior, we experimentally examined the isothermal, room temperature response of superelastic NiTi rods and tubes, of similar outer diameters, subjected to four different modes of loading. Pure tension, pure compression, and pure bending experiments were first performed to establish and compare the baseline uniaxial and bending behaviors of rods and tubes. Column buckling experiments were then performed on rod and tube columns of several slenderness ratios to investigate their mechanical responses, phase transformation kinetics under combined uniaxial and bending deformation, and the interaction between material and structural instabilities. In all experiments, stereo digital image correlation measured local displacement fields in order to capture phenomena such as strain localization and propagating phase boundaries. Superelastic mechanical behavior and the nature of stress-induced phase transformation were found to be strongly affected by specimen geometry and the deformation mode. Under uniaxial tension, both the rod and tube had well-defined loading and unloading plateaus in their superelastic responses, during which stress-induced phase transformation propagated along the length of the specimen in the form of a high/low strain front. Due to the dependence of strain localization on kinematic compatibility, the high/low strain front morphologies differed between the rod and tube: for the rod, the high/low strain front consisted of a diffuse “neck”, while the high/low strain front in the tube consisted of distinct, criss-crossing “fingers.” During uniaxial compression, both cross-sectional forms exhibited higher transformation stresses and smaller transformation strains than uniaxial tension, highlighting the now well-known tension-compression asymmetry of SMAs. Additionally, phase transformation localization and propagation were absent under compressive loading. During pure bending, the moment-curvature response of both forms exhibited plateaus and strain localization during forward and reverse transformations. Rod specimens developed localized, high-curvature regions that propagated along the specimen axis and caused shear strain near the high/low curvature interface; whereas, the tube specimens exhibited finger/wedge-like high strain regions over the tensile side of the tube which caused nonlinear strain profiles through the thickness of the specimen that did not propagate. It was therefore found that classical beam theory assumptions did not hold in the presence of phase transformation localization (although, the assumptions did hold on average for the tube). During column buckling, the structures were loaded into the post-buckling regime yet recovered nearly-straight forms upon unloading. Strain localization was observed only for high aspect ratio (slender) tubes, but the mechanical responses were similar to that of rods of the same slenderness ratio. Also, an interesting “unbuckling” phenomenon was discovered in certain low aspect ratio (stout) columns, where late post-buckling straightening was observed despite continuous monotonic loading. Thus, these behaviors are some of the challenging phenomena which must be captured when developing SMA constitutive models and executing structural simulations.
Injection of large amounts of fluid into the subsurface alters the states of pore pressure and stress in the formation, potentially inducing earthquakes. Increase in the seismicity rate after shut-in is often observed at fluid-injection operation sites, but mechanistic study of the rate surge has not been investigated thoroughly. Considering full poroelastic coupling of pore pressure and stress, the earthquake occurrence after shut-in can be driven by two mechanisms: (1) post shut-in diffusion of pore pressure into distant faults and (2) poroelastic stressing caused by fluid injection. Interactions of these mechanisms can depend on fault geometry, hydraulic and mechanical properties of the formation, and injection operation. In this work, a 2D aerial view of the target reservoir intersected by strike-slip basement faults is used to evaluate the impact of injection-induced pressure buildup on seismicity rate surge. A series of sensitivity tests are performed by considering the variation in (1) permeability of the fault zone, (2) locations and the number of faults with respect to the injector, and (3) well operations with time-dependent injection rates. Lower permeability faults have higher seismicity rates than more permeable faults after shut-in due to delayed diffusion and poroelastic stressing. Hydraulic barriers, depending on their relative location to injection, can either stabilize or weaken a conductive fault via poroelastic stresses. Gradual reduction of the injection rate minimizes the coulomb stress change and the least seismicity rates are predicted due to slower relaxation of coupling-induced compression as well as pore-pressure dissipation.
AlSi10Mg tensile bars were additively manufactured using the powder-bed selective laser melting process. Samples were subjected to stress relief annealing and hot isostatic pressing. Tensile samples built using fresh, stored, and reused powder feedstock were characterized for microstructure, porosity, and mechanical properties. Fresh powder exhibited the best mechanical properties and lowest porosity while stored and reused powder exhibited inferior mechanical properties and higher porosity. The microstructure of stress relieved samples was fine and exhibited (001) texture in the z-build direction. Microstructure for hot isostatic pressed samples was coarsened with fainter (001) texture. To investigate surface and interior defects, scanning electron microscopy, optical fractography, and laser scanning microscopy techniques were employed. Hot isostatic pressing eliminated internal pores and reduced the size of surface porosity associated with the selective laser melting process. Hot isostatic pressing tended to increase ductility at the expense of decreasing strength. However, scatter in ductility of hot isostatic pressed parts suggests that the presence of unclosed surface porosity facilitated fracture with crack propagation inward from the surface of the part.
The Federal Radiological Monitoring and Assessment Center (FRMAC) has two major assets it uses to perform it responsibilities for responding to a radiological emergency. These are the National Atmospheric Release Advisory Capability (NARAC) and Turbo FRMAC. Recently NARAC updated their deposition model to the state of the art Petroff and Zhang model leading to a significant discrepancy between these two assets in regards to deposition modeling. This report describes the investigation into an appropriate deposition model for Turbo FRMAC to bring the two assets back into line. The ultimate conclusion is that Petroff and Zhang is too complicated for Turbo FRMAC, but the model of Feng is not and is equal to Petroff and Zhang in predictive capability.
Foley, Brian M.; Wallace, Margeaux; Gaskins, John T.; Paisley, Elizabeth; Johnson, Raegan; Kim, Jong W.; Ryan, Philip J.; Trolier-Mckinstry, Susan; Hopkins, Patrick E.; Ihlefeld, Jon F.
Ferroelastic domain walls in ferroelectric materials possess two properties that are known to affect phonon transport: a change in crystallographic orientation and a lattice strain. Changing populations and spacing of nanoscale-spaced ferroelastic domain walls lead to the manipulation of phonon-scattering rates, enabling the control of thermal conduction at ambient temperatures. In the present work, lead zirconate titanate (PZT) thin-film membrane structures were fabricated to reduce mechanical clamping to the substrate and enable a subsequent increase in the ferroelastic domain wall mobility. Under application of an electric field, the thermal conductivity of PZT increases abruptly at ∼100 kV/cm by ∼13% owing to a reduction in the number of phonon-scattering domain walls in the thermal conduction path. The thermal conductivity modulation is rapid, repeatable, and discrete, resulting in a bistable state or a "digital" modulation scheme. The modulation of thermal conductivity due to changes in domain wall configuration is supported by polarization-field, mechanical stiffness, and in situ microdiffraction experiments. This work opens a path toward a new means to control phonons and phonon-mediated energy in a digital manner at room temperature using only an electric field.
Most inverters for use in distribution-connected distributed energy resource applications (distributed generation and energy storage) are tested and certified to detect and cease to energize unintentional islands on the electric grid. The requirements for the performance of islanding detection methods are specified in IEEE 1547-2018, and specified conditions for certification- type testing of islanding detection are defined in IEEE 1547.1. Such certification-type testing is designed to ensure a minimum level of confidence that these inverters will not island in field applications. However, individual inverter certification tests do not address interactions between dissimilar inverters or between inverter and synchronous machines that may occur in the field. This work investigates the performance of different inverter island detection methods for these two circumstances that are not addressed by the type testing: 1) combinations of different inverters using different types of islanding detection methods, and 2) combinations of inverters and synchronous generators. The analysis took into consideration voltage and frequency ride- through requirements as specified in IEEE 1547-2018, but did not consider grid support functionality such as voltage or frequency response. While the risk of islanding is low even in these cases, it is often difficult to deal with these scenarios in a simplified interconnection screening process. This type of analysis could provide a basis to establish a practical anti- islanding screening methodology for these complex scenarios, with the goal of reducing the number of required detailed studies. Eight generic Groups of islanding detection behavior are defined, and examples of each are used in the simulations. The results indicate that islanding detection methods lose effectiveness at significantly different rates as the composition of the distributed energy resources (DERs) varies, with some methods remaining highly effective over a wide range of conditions.