Research is presented for carbon emissions abatement utilizing concentrating solar power (CSP) heating for culinary industrial process heat applications of roasting peppers. For this investigation the Sandia National Laboratories (SNL) performed high-intensity flux profile heating, as high as approximately 12.2 W/cm2 roasting peppers near 615oC. This work also explores the suitability of culinary roasting as applied to different forms of CSP heating as well as techno-economic costs. Traditionally, chile pepper roasting has used propane gas source heating to achieve similar temperatures and food roasting profiles in batch style processing. Here, the investigators roasted peppers on the top level of the National Solar Thermal Test Facility (NSTTF) solar tower for multiple roasting trials, with and without water. For comparison, the team also performed roasting from a traditional propane gas heating source, monitoring the volume of propane being consumed over time to assess carbon emissions that were abated using CSP. Results found that roasting peppers with CSP facilitated approximately 26 MJ of energy that abated approximately 0.122 kg CO2/kg chile for a 10 kg bag. The team also determined that pre-wetting the peppers before roasting both under propane and CSP heat sources increased the roast time by approximately 3 minutes to achieve the same qualitative optimal roast state compared to dry peppers.
An RF switch technique applying differential signal cancellation is presented. The proposed approach enables high isolation and extremely small size by employing cascode current steering within a differential amplifier. Unlike series RF switches, isolation is limited by device mismatch, not switch parasitic capacitance, enabling high frequency operation. Since the switch is within the already present cascode devices, there is no additional insertion loss from the switch. The switch was implemented in a 180 nm CMOS process within an amplifier as part of an on-chip receiver and achieves 36-43 dB isolation across 0.5-2 GHz, while occupying an area of only 0.0006 mm2.
Applications such as counterfeit identification, quality control, and non-destructive material identification benefit from improved spatial and compositional analysis. X-ray Computed Tomography is used in these applications but is limited by the X-ray focal spot size and the lack of energy-resolved data. Recently developed hyperspectral X-ray detectors estimate photon energy, which enables composition analysis but lacks spatial resolution. Moving beyond bulk homogeneous transmission anodes toward multi-metal patterned anodes enables improvements in spatial resolution and signal-to-noise ratios in these hyperspectral X-ray imaging systems. We aim to design and fabricate transmission anodes that facilitate confirmation of previous simulation results. These anodes are fabricated on diamond substrates with conventional photolithography and metal deposition processes. The final transmission anode design consists of a cluster of three disjoint metal bumps selected from molybdenum, silver, samarium, tungsten, and gold. These metals are chosen for their k-lines, which are positioned within distinct energy intervals of interest and are readily available in standard clean rooms. The diamond substrate is chosen for its high thermal conductivity and high transmittance of X-rays. The feature size of the metal bumps is chosen such that the cluster is smaller than the 100 m diameter of the impinging electron beam in the X-ray tube. This effectively shrinks the X-ray focal spot in the selected energy bands. Once fabricated, our transmission anode is packaged in a stainless-steel holder that can be retrofitted into our existing X-ray tube. Innovations in anode design enable an inexpensive and simple method to improve existing X-ray imaging systems.
Expansion techniques are powerful tools that can take a limited measurement set and provide information on responses at unmeasured locations. Expansion techniques are used in dynamic environments specifications, full field stress measurements, model calibration, and other calculations that require response at locations not measured. However, the process of modal expansion techniques such as SEREP (System Equivalent Reduction Expansion Process) has error with the projection of the measurement set of degrees of freedom to the expanded degrees of freedom. Empirical evidence has been used in the past to qualitatively determine the error. In recent years, the modal projection error was developed to quantify the error through a projection between different domains. The modal projection error is used in this paper to demonstrate the use of the metric in quantifying the error of the expansion process and to quantify which modes of the expansion process are the most important.
Physics-constrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods is that the resulting machine learning model requires significantly fewer data to train. By incorporating physical rules into the machine learning formulation itself, the predictions are expected to be physically plausible. Gaussian process (GP) is perhaps one of the most common methods in machine learning for small datasets. In this paper, we investigate the possibility of constraining a GP formulation with monotonicity on two different material datasets, where one experimental and one computational dataset is used. The monotonic GP is compared against the regular GP, where a significant reduction in the posterior variance is observed. The monotonic GP is strictly monotonic in the interpolation regime, but in the extrapolation regime, the monotonic effect starts fading away as one goes beyond the training dataset. Imposing monotonicity on the GP comes at a small accuracy cost, compared to the regular GP. The monotonic GP is perhaps most useful in applications where data is scarce and noisy or when the dimensionality is high, and monotonicity is where supported by strong physical reasoning.
In this study we performed detailed comparisons of numerical computations of single turbine wakes with measured data under neutral and stable atmospheric stability conditions. LES of the ABL inflow and turbine wakes are carried out using the ExaWind/Nalu-Wind simulation codes and compared with the equivalent measurements from the SWiFT research facility at wind speeds of 8.7 m/s and 4.8 m/s. The computed ABL inflow profiles and spectra showed good agreement with measured data in both stratification conditions, and the simulated turbine power and rotor speed also agreed with the measured turbine performance. A comparison of the downstream wake deficit profiles and turbulence distributions with lidar observations also showed that the LES computations generally captured the wake evolution in both neutral and stable conditions, with some possible discrepancies due to uncertainty around the turbine thrust and yaw settings. Finally, an examination of the downstream turbulence spectra showed that the peak frequency of the wake added turbulence corresponds to the characteristic wake shedding frequency, and we show that the turbulent integral lengthscale in the wake region also decreases significantly due to the presence of smaller turbulent features.
Proceedings of ROSS 2022: International Workshop on Runtime and Operating Systems for Supercomputers, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis
Hardware design in high-performance computing (HPC) is often highly experimental. Exploring new designs is difficult and time-consuming, requiring lengthy vendor cooperation. RISC-V is an open-source processor ISA that improves the accessibility of chip design, including the ability to do hardware/software co-design using open-source hardware and tools. Co-design allows design decisions to easily flow across the hardware/software boundary and influence future design ideas. However, new hardware designs require corresponding software to drive and test them. Conventional operating systems like Linux are massively complex and modification is time-prohibitive. In this paper, we describe our port of the Kitten lightweight kernel operating system to RISC-V in order to provide an alternative to Linux for conducting co-design research. Kitten's small code base and simple resource management policies are well matched for quickly exploring new hardware ideas that may require radical operating system modifications and restructuring. Our evaluation shows that Kitten on RISC-V is functional and provides similar performance to Linux for single-core benchmarks. This provides a solid foundation for using Kitten in future co-design research involving RISC-V.
A new small-scale pressure vessel with a 5×5 fuel assembly and axially truncated PWR hardware was created to simulate commercial vacuum drying processes. This test assembly, known as the Dashpot Drying Apparatus, was built to focus on the drying of a single PWR dashpot and surrounding fuel. Drying operations were simulated for three tests with the DDA based on the pressure and temperature histories observed in the HBDP. All three tests were conducted with an empty guide tube. One test was performed with deionized water as the fill fluid. The other two tests used 0.2 M boric acid as the fill fluid to accurately simulate spent fuel pool conditions. These tests proved the capability of the DDA to mimic commercial drying processes on a limited scale and detect the presence of bulk and residual water. Furthermore, for all tests, pressure remained below the 0.4 kPa (3 Torr) rebound threshold for the final evacuation step in the drying procedure. Results indicate that after bulk fluid is removed from the pressure vessel, residual water is verifiably measured through confirmatory measurements of pressure and water content using a mass spectrometer. The final pressure rebound behaviors for the three tests conducted were well below the established regulatory limit of less than 0.4 kPa (3 Torr) within 30 minutes of isolation. The water content measurements across all tests showed that despite observing high water content within the DDA vessel at the beginning of the vacuum isolations, the water content drastically drops to below 1,200 ppmv after the isolations were conducted. The data and operational experience from these tests will guide the next evolution of experiments on a prototypic-length scale with multiple surrogate rods in a full 17×17 PWR assembly. The insight gained through these investigations is expected to support the technical basis for the continued safe storage of spent nuclear fuel into long term operations.
We present optical metrology at the Sandia fog chamber facility. Repeatable and well characterized fogs are generated under different atmospheric conditions and applied for light transport model validation and computational sensing development.
This SAND Report provides an overview of AniMACCS, the animation software developed for the MELCOR Accident Consequence Code System (MACCS). It details what users need to know in order to successfully generate animations from MACCS results. It also includes information on the capabilities, requirements, testing, limitations, input settings, and problem reporting instructions for AniMACCS version 1.3.1. Supporting information is provided in the appendices, such as guidance on required input files using both WinMACCS and running MACCS from the command line.
A sodium pool fire in the containment of a sodium-cooled fast reactor (SFR) plant can occur due to a pipe leak or break. Accumulation of the sodium in a pool would allow the sodium to react with the atmosphere of the containment, such as oxygen, to cause a fire. Sodium fire is important to model because the heat addition and aerosol generation that occur. Any fission products trapped in the leaked sodium coolant may also be released into the containment, which can affect workers and the public if the containment is breached. This paper describes progress of an international collaborative research in SFR sodium fire modeling between the United States and Japan under the framework of the Civil Nuclear Energy Research and Development Working Group (CNWG). In this collaboration between Sandia National Laboratories (SNL) and Japan Atomic Energy Agency (JAEA), the validation basis for and modeling capabilities of sodium pool fires in MELCOR of SNL and SPHINCS of JAEA are being assessed. Additional model improvements for the sodium pool fire in MELCOR are discussed. The MELCOR results for the sodium pool fire model enhancement in MELCOR agreed well with the JAEA's F7 pool fire experiments and compared closely with SPHINCS.
Type 2 high-pressure hydrogen vessels for storage at hydrogen refueling stations are designed assuming a predefined operational pressure cycle and targeted autofrettage conditions. However, the resulting finite life depends significantly on variables associated with the autofrettage process and the pressure cycles actually realized during service, which many times are not to the full range of the design. Clear guidance for cycle counting is lacking, therefore industry often defaults to counting every repressurization as a full range pressure cycle, which is an overly conservative approach. In-service pressure cycles used to predict the growth of cracks in operational pressure vessels results in significantly longer life, since most in-service pressure cycles are only a fraction of the full design pressure range. Fatigue crack growth rates can vary widely for a given pressure range depending on the details of the residual strains imparted during the autofrettage process because of their influence on crack driving forces. Small changes in variables associated with the autofrettage process, e.g., the target autofrettage overburden pressure, can result in large changes in the residual stress profile leading to possibly degraded fatigue life. In this paper, computational simulation was used for sensitivity studies to evaluate the effect of both operating conditions and autofrettage conditions on fatigue life for Type 2 highpressure hydrogen vessels. The analysis in this paper explores these sensitivities, and the results are used to provide guidance on cycle counting. In particular, we identify the pressure cycle ranges that can be ignored over the life of the vessel as having negligible effect on fatigue life. This study also examines the sensitivity of design life to the autofrettage process and the impact on life if the targeted residual strain is not achieved during manufacturing.
Turbine generator power from simulations using Actuator Line Models and Actuator Disk Models with a Filtered Lifting Line Correction are compared to field data of a V27 turbine. Preliminary results of the wake characteristics are also presented. Turbine quantities of interest from traditional ALM and ADM with the Gaussian kernel (ϵ) set at the optimum value for matching power production and that resolve the kernel at all mesh sizes are also presented. The atmospheric boundary layer is simulated using Nalu-Wind, a Large Eddy Simulation code which is part of the ExaWind code suite. The effect of mesh resolution on quantities of interest is also examined.
Type 2 high-pressure hydrogen vessels for storage at hydrogen refueling stations are designed assuming a predefined operational pressure cycle and targeted autofrettage conditions. However, the resulting finite life depends significantly on variables associated with the autofrettage process and the pressure cycles actually realized during service, which many times are not to the full range of the design. Clear guidance for cycle counting is lacking, therefore industry often defaults to counting every repressurization as a full range pressure cycle, which is an overly conservative approach. In-service pressure cycles used to predict the growth of cracks in operational pressure vessels results in significantly longer life, since most in-service pressure cycles are only a fraction of the full design pressure range. Fatigue crack growth rates can vary widely for a given pressure range depending on the details of the residual strains imparted during the autofrettage process because of their influence on crack driving forces. Small changes in variables associated with the autofrettage process, e.g., the target autofrettage overburden pressure, can result in large changes in the residual stress profile leading to possibly degraded fatigue life. In this paper, computational simulation was used for sensitivity studies to evaluate the effect of both operating conditions and autofrettage conditions on fatigue life for Type 2 highpressure hydrogen vessels. The analysis in this paper explores these sensitivities, and the results are used to provide guidance on cycle counting. In particular, we identify the pressure cycle ranges that can be ignored over the life of the vessel as having negligible effect on fatigue life. This study also examines the sensitivity of design life to the autofrettage process and the impact on life if the targeted residual strain is not achieved during manufacturing.
Simple but mission-critical internet-based applications that require extremely high reliability, availability, and verifiability (e.g., auditability) could benefit from running on robust public programmable blockchain platforms such as Ethereum. Unfortunately, program code running on such blockchains is normally publicly viewable, rendering these platforms unsuitable for applications requiring strict privacy of application code, data, and results. In this work, we investigate using MPC techniques to protect the privacy of a blockchain computation. While our main goal is to hide both the data and the computed function itself, we also consider the standard MPC setting where the function is public. We describe GABLE (Garbled Autonomous Bots Leveraging Ethereum), a blockchain MPC architecture and system. The GABLE architecture specifies the roles and capabilities of the players. GABLE includes two approaches for implementing MPC over blockchain: Garbled Circuits (GC), evaluating universal circuits, and Garbled Finite State Automata (GFSA). We formally model and prove the security of GABLE implemented over garbling schemes, a popular abstraction of GC and GFSA from (Bellare et al., CCS 2012). We analyze in detail the performance (including Ethereum gas costs) of both approaches and discuss the trade-offs. We implement a simple prototype of GABLE and report on the implementation issues and experience.
A new set of critical experiments exploring the temperature-dependence of the reactivity in a critical assembly is described. In the experiments, the temperature of the critical assembly will be varied to determine the temperature that produces the highest reactivity in the assembly. This temperature is the inversion point of the isothermal reactivity coefficient of the assembly. An analysis of relevant configurations is presented. Existing measurements are described and an analysis of these experiments presented. The overall experimental approach is described as are the modifications to the critical assembly needed to perform the experiments.
Carbon sequestration is a growing field that requires subsurface monitoring for potential leakage of the sequestered fluids through the casing annulus. Sandia National Laboratories (SNL) is developing a smart collar system for downhole fluid monitoring during carbon sequestration. This technology is part of a collaboration between SNL, University of Texas at Austin (UT Austin) (project lead), California Institute of Technology (Caltech), and Research Triangle Institute (RTI) to obtain real-time monitoring of the movement of fluids in the subsurface through direct formation measurements. Caltech and RTI are developing millimeter-scale radio frequency identification (RFID) sensors that can sense carbon dioxide, pH, and methane. These sensors will be impervious to cement, and as such, can be mixed with cement and poured into the casing annulus. The sensors are powered and communicate via standard RFID protocol at 902-928 MHz. SNL is developing a smart collar system that wirelessly gathers RFID sensor data from the sensors embedded in the cement annulus and relays that data to the surface via a wired pipe that utilizes inductive coupling at the collar to transfer data through each segment of pipe. This system cannot transfer a direct current signal to power the smart collar, and therefore, both power and communications will be implemented using alternating current and electromagnetic signals at different frequencies. The complete system will be evaluated at UT Austin's Devine Test Site, which is a highly characterized and hydraulically fractured site. This is the second year of the three-year effort, and a review of SNL's progress on the design and implementation of the smart collar system is provided.
Simple but mission-critical internet-based applications that require extremely high reliability, availability, and verifiability (e.g., auditability) could benefit from running on robust public programmable blockchain platforms such as Ethereum. Unfortunately, program code running on such blockchains is normally publicly viewable, rendering these platforms unsuitable for applications requiring strict privacy of application code, data, and results. In this work, we investigate using MPC techniques to protect the privacy of a blockchain computation. While our main goal is to hide both the data and the computed function itself, we also consider the standard MPC setting where the function is public. We describe GABLE (Garbled Autonomous Bots Leveraging Ethereum), a blockchain MPC architecture and system. The GABLE architecture specifies the roles and capabilities of the players. GABLE includes two approaches for implementing MPC over blockchain: Garbled Circuits (GC), evaluating universal circuits, and Garbled Finite State Automata (GFSA). We formally model and prove the security of GABLE implemented over garbling schemes, a popular abstraction of GC and GFSA from (Bellare et al., CCS 2012). We analyze in detail the performance (including Ethereum gas costs) of both approaches and discuss the trade-offs. We implement a simple prototype of GABLE and report on the implementation issues and experience.
Based on the rationale presented, nuclear criticality is improbable after salt creep causes compaction of criticality control overpacks (CCOs) disposed at the Waste Isolation Pilot Plant, an operating repository in bedded salt for the disposal of transuranic (TRU) waste from atomic energy defense activities. For most TRU waste, the possibility of post-closure criticality is exceedingly small either because the salt neutronically isolates TRU waste canisters or because closure of a disposal room from salt creep does not sufficiently compact the low mass of fissile material. The criticality potential has been updated here because of the introduction of CCOs, which may dispose up to 380 fissile gram equivalent plutonium-239 in each container. The criticality potential is evaluated through high-fidelity geomechanical modeling of a disposal room filled with CCOs during two representative conditions: (1) large salt block fall, and (2) gradual salt compaction (without brine seepage and subsequent gas generation to permit maximum room closure). Geomechanical models of rock fall demonstrate three tiers of CCOs are not greatly disrupted. Geomechanical models of gradual room closure from salt creep predict irregular arrays of closely packed CCOs after 1000 years, when room closure has asymptotically approached maximum compaction. Criticality models of spheres and cylinders of 380 fissile gram equivalent of plutonium (as oxide) at the predicted irregular spacing demonstrate that an array of CCOs is not critical when surrounded by salt and magnesium oxide, provided the amount of hydrogenous material shipped in the CCO (usually water and plastics) is controlled or boron carbide (a neutron poison) is mixed with the fissile contents.