As we develop new materials to increase performance of lithium ion batteries for electric vehicles, the impact of potential safety and reliability issues become increasingly important. In addition to electrochemical performance increases (capacity, energy, cycle life, etc.), there are a variety of materials advancements that can be made to improve lithium-ion battery safety. Issues including energetic thermal runaway, electrolyte decomposition and flammability, anode SEI stability, and cell-level abuse tolerance behavior. Introduction of a next generation materials, such as silicon based anode, requires a full understanding of the abuse response and degradation mechanisms for these anodes. This work aims to understand the breakdown of these materials during abuse conditions in order to develop an inherently safe power source for our next generation electric vehicles. The effect of materials level changes (electrolytes, additives, silicon particle size, silicon loading, etc.) to cell level abuse response and runaway reactions will be determined using several techniques. Experimentation will start with base material evaluations in coin cells and overall runaway energy will be evaluated using techniques such as differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and accelerating rate calorimetry (ARC). The goal is to understand the effect of materials parameters on the runaway reactions, which can then be correlated to the response seen on larger cells (18650). Experiments conducted showed that there was significant response from these electrodes. Efforts to minimize risk during testing were taken by development of a smaller capacity cylindrical design in order to quantify materials decision and how they manifest during abuse response.
The goal of this project is to develop and execute methods for characterizing uncertainty in data products that are deve loped and distributed by the DOE Consequence Management (CM) Program. A global approach to this problem is necessary because multiple sources of error and uncertainty from across the CM skill sets contribute to the ultimate p roduction of CM data products. This report presents the methods used to develop a probabilistic framework to characterize this uncertainty and provides results for an uncertainty analysis for a study scenario analyzed using this framework.
Evlyukhin, Egor; Kim, Eunja; Goldberger, David; Cifligu, Petrika; Weck, Philippe F.; Pravica, Michael
X-ray induced damage has been known for decades and has largely been viewed as a tremendous nuisance. We, on the other hand, harness the highly ionizing and penetrating properties of hard X-rays to initiate novel decomposition and synthetic chemistry. Here, we show that powdered cesium oxalate monohydrate pressurized to ≤0.5 GPa and irradiated with X-rays of energies near the cesium K-edge undergoes molecular and structural transformations with one of the final products exhibiting a new type of bcc crystal structure that has previously not been observed. Additionally, based on cascades of ultrafast electronic relaxation steps triggered by the absorption of one X-ray photon, we propose a model explaining the X-ray induced damage of multitype bounded matter. As X-rays are ubiquitous, these results show promise in the preparation of novel compounds and novel structures that are inaccessible via conventional methods. They may offer insight into the formation of complex organic compounds in outer space.
Through long-term investments in computing, algorithms, facilities, and instrumentation, DOE is an established leader in massive-scale, high-fidelity simulations, as well as science-leading experimentation. In both cases, DOE is generating more data than it can analyze and the problem is intensifying quickly. The need for advanced algorithms that can automatically convert the abundance of data into a wealth of useful information by discovering hidden structures is well recognized. Such efforts however, are hindered by the massive volume of the data and its high velocity. Here, the challenge is developing unsupervised learning methods to discover hidden structure in high-volume, high-velocity data.
Zero emission hydrogen fuel cell technology has the potential to drastically reduce total “well-to-waves” maritime emissions. Through realistic design studies of five commercially-relevant passenger vessels, this study examines the most cost-effective entry points in the US fleet for deploying today’s available technology, and includes analysis of resulting well-to-waves emission profiles. The results show that per-passenger mile vessel energy use is directly correlated to increased emissions, capital costs, and operating costs. As a consequence, low speed, large capacity vessels offer a cost-effective starting place today. Increases in vessel efficiency through such measures as hull design and light-weighting can have large impacts in reducing cost and emissions of these systems. Overall this work showed all five vessel types to be feasible with today’s hydrogen fuel cell technology and presents more options to fleets that are committed to reducing maritime emissions in cost effective ways.
This paper documents the history of the TRU program at Sandia, previous and current activities associated with TRU material and waste, interfaces with other TRU waste generator sites and the Waste Isolation Pilot Plan (WIPP), and paths forward for TRU material and waste. This document is a snapshot in time of the TRU program and should be updated as necessary, or when significant changes have occurred in the Sandia TRU program or in the TRU regulatory environment. This paper should serve as a roadmap to capture past TRU work so that efforts are not repeated and ground is not lost due to future inactivity and personnel changes.
Safety basis analysts throughout the U.S. Department of Energy (DOE) complex rely heavily on the information provided in the DOE Handbook, DOE-HDBK-3010, Airborne Release Fractions/Rates and Respirable Fractions for Nonreactor Nuclear Facilities, to determine radionuclide source terms from postulated accident scenarios. In calculating source terms, analysts tend to use the DOE Handbook’s bounding values on airborne release fractions (ARFs) and respirable fractions (RFs) for various categories of insults (representing potential accident release categories). This is typically due to both time constraints and the avoidance of regulatory critique. Unfortunately, these bounding ARFs/RFs represent extremely conservative values. Moreover, they were derived from very limited small-scale bench/laboratory experiments and/or from engineered judgment. Thus, the basis for the data may not be representative of the actual unique accident conditions and configurations being evaluated. The goal of this research is to develop a more accurate and defensible method to determine bounding values for the DOE Handbook using state-of-art multi-physics-based computer codes.
Diesel on-road vehicles with a Gross Vehicle Weight Rating (GVWR) greater than 14,000 pounds that operate in California are subject to the On-Road Diesel-Vehicle Regulation. SNL/CA operates eight diesel vehicles that are subject to this regulation; four of the vehicles are classified as low-use vehicles and four of the vehicles have Particulate Matter Filters installed as original equipment. This regulation requires that all fleets using flexibility options, such as the low-use exemption, report annually by January 31 in order to extend the exemption for that year. CA ARB encourages facilities to complete the reporting requirements using the TRUCRS on-line reporting tool.
This report describes tests conducted using a full-size rail cask, the ENSA ENUN 32P, involving handling of the cask and transport of the cask via truck, ships, and rail. The purpose of the tests was to measure strains and accelerations on surrogate pressurized water reactor fuel rods when the fuel assemblies were subjected to Normal Conditions of Transport within the rail cask. In addition, accelerations were measured on the transport platform, the cask cradle, the cask, and the basket within the cask holding the assemblies. These tests were an international collaboration that included Equipos Nucleares S.A., Sandia National Laboratories, Pacific Northwest National Laboratory, Coordinadora Internacional de Cargas S.A., the Transportation Technology Center, Inc., the Korea Radioactive Waste Agency, and the Korea Atomic Energy Research Institute. All test results in this report are PRELIMINARY – complete analyses of test data will be completed and reported in FY18. However, preliminarily: The strains were exceedingly low on the surrogate fuel rods during the rail-cask tests for all the transport and handling modes. The test results provide a compelling technical basis for the safe transport of spent fuel.
Within the SEQUOIA project, funded by the DARPA EQUiPS program, we pursue algorithmic approaches that enable comprehensive design under uncertainty, through inclusion of aleatory/parametric and epistemic/model form uncertainties within scalable forward/inverse UQ approaches. These statistical methods are embedded within design processes that manage computational expense through active subspace, multilevel-multifidelity, and reduced-order modeling approximations. To demonstrate these methods, we focus on the design of devices that involve multi-physics interactions in advanced aerospace vehicles. A particular problem of interest is the shape design of nozzles for advanced vehicles such as the Northrop Grumman UCAS X-47B, involving coupled aero-structural-thermal simulations for nozzle performance. In this paper, we explore a combination of multilevel and multifidelity forward and inverse UQ algorithms to reduce the overall computational cost of the analysis by leveraging hierarchies of model form (i.e., multifidelity hierarchies) and solution discretization (i.e., multilevel hierarchies) in order of exploit trade offs between solution accuracy and cost. In particular, we seek the most cost effective fusion of information across complex multi-dimensional modeling hierarchies. Results to date indicate the utility of multiple approaches, including methods that optimally allocate resources when estimator variance varies smoothly across levels, methods that allocate sufficient sampling density based on sparsity estimates, and methods that employ greedy multilevel refinement.
Backscatter Particle Image Velocimetry via Optical Time-of-flight Sectioning (PIVOTS) is a novel method of performing PIV in situations where conventional PIV presents difficulties. The PIVOTS technique is introduced along with recent applications and results.
Combustion of aluminum droplets in solid rocket propellants is studied using laser diagnostic techniques. The time-resolved droplet velocity, temperature, and size are measured using high speed digital in-line holography and imaging pyrometry at 20 kHz.
A common problem associated with the effort to better assess potential behaviors of various individuals within different countries is the shear difficulty in comprehending the dynamic nature of populations, particularly over time and considering feedback effects. This paper discusses a theory-based analytical capability designed to enable analysts to better assess the influence of events on individuals interacting within a country or region. These events can include changes in policy, man-made or natural disasters, migration, war, or other changes in environmental/economic conditions. In addition, this paper describes potential extensions of this type of research to enable more timely and accurate assessments.
Energetic materials (i.e. explosives, propellants, and pyrotechnics) have complex mesoscale features that influence their dynamic response. Direct measurement of the complex mechanical, thermal, and chemical response of energetic materials is critical for improving computational models and enabling predictive capabilities. Many of the physical phenomena of interest in energetic materials cover time and length scales spanning several orders of magnitude. Examples include chemical interactions in the reaction zone, the distribution and evolution of temperature fields, mesoscale deformation in heterogeneous systems, and phase transitions. This is particularly true for spontaneous phenomena, like thermal cook-off. The ability for MaRIE to capture multiple length scales and stochastic phenomena can significantly advance our understanding of energetic materials and yield more realistic, predictive models.
The significantly higher buoyancy of hydrogen compared to natural gas means that hazardous zones defined in the IGF code may be inaccurate if applied to hydrogen. This could place undue burden on ship design or could lead to situations that are unknowingly unsafe. We present dispersion analyses to examine three vessel case studies: (1) abnormal external vents of full blowdown of a liquid hydrogen tank due to a failed relief device in still air and with crosswind; (2) vents due to naturally-occurring boil-off of liquid within the tank; and (3) a leak from the pipes leading into the fuel cell room. The size of the hydrogen plumes resulting from a blowdown of the tank depend greatly on the wind conditions. It was also found that for normal operations releasing a small amount of "boil- off" gas to regulate the pressure in the tank does not create flammable concentrations.
Slycat™ is a web-based system for performing data analysis and visualization of potentially large quantities of remote, high-dimensional data. Slycat™ specializes in working with ensemble data. An ensemble is a group of related data sets, which typically consists of a set of simulation runs exploring the same problem space. An ensemble can be thought of as a set of samples within a multi-variate domain, where each sample is a vector whose value defines a point in high-dimensional space. To understand and describe the underlying problem being modeled in the simulations, ensemble analysis looks for shared behaviors and common features across the group of runs. Additionally, ensemble analysis tries to quantify differences found in any members that deviate from the rest of the group. The Slycat™ system integrates data management, scalable analysis, and visualization. Results are viewed remotely on a user’s desktop via commodity web clients using a multi-tiered hierarchy of computation and data storage, as shown in Figure 1. Our goal is to operate on data as close to the source as possible, thereby reducing time and storage costs associated with data movement. Consequently, we are working to develop parallel analysis capabilities that operate on High Performance Computing (HPC) platforms, to explore approaches for reducing data size, and to implement strategies for staging computation across the Slycat™ hierarchy. Within Slycat™, data and visual analysis are organized around projects, which are shared by a project team. Project members are explicitly added, each with a designated set of permissions. Although users sign-in to access Slycat™, individual accounts are not maintained. Instead, authentication is used to determine project access. Within projects, Slycat™ models capture analysis results and enable data exploration through various visual representations. Although for scientists each simulation run is a model of real-world phenomena given certain conditions, we use the term model to refer to our modeling of the ensemble data, not the physics. Different model types often provide complementary perspectives on data features when analyzing the same data set. Each model visualizes data at several levels of abstraction, allowing the user to range from viewing the ensemble holistically to accessing numeric parameter values for a single run. Bookmarks provide a mechanism for sharing results, enabling interesting model states to be labeled and saved.
Hydrogen Risk Assessment Models (HyRAM) is a software toolkit that provides a basis for quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM integrates validated, analytical models of hydrogen behavior, statistics, and a standardized QRA approach to generate useful, repeatable data for the safety analysis of various hydrogen systems. HyRAM is a software developed by Sandia National Laboratories for the U.S. Department of Energy. This document demonstrates how to use HyRAM to recreate a hydrogen system and obtain relevant data regarding potential risk. Specific examples are utilized throughout this document, providing detailed tutorials of HyRAM features with respect to hydrogen system safety analysis and risk assessment.
In this paper, we report the formulation to account for dielectrics in a first principles multipole-based cable braid electromagnetic penetration model. To validate our first principles model, we consider a one-dimensional array of wires, which can be modeled analytically with a multipole-conformal mapping expansion for the wire charges; however, the first principles model can be readily applied to realistic cable geometries. We compare the elastance (i.e., the inverse of the capacitance) results from the first principles cable braid electromagnetic penetration model to those obtained using the analytical model. The results are found in good agreement up to a radius to half spacing ratio of 0.5–0.6, depending on the permittivity of the dielectric used, within the characteristics of many commercial cables. We observe that for typical relative permittivities encountered in braided cables, the transfer elastance values are essentially the same as those of free space; the self-elastance values are also approximated by the free space solution as long as the dielectric discontinuity is taken into account for the planar mode.
Proceedings - SPE Symposium on Improved Oil Recovery
Al-Saedi, Hasan N.; Brady, Patrick V.; Flori, Ralph; Heidari, Peyman
The ever-growing global energy demand and natural decline in oil production from mature oil fields over the last several decades have been the main incentives to search for methods to increase recovery efficiency. This paper quantifies the clay role and the important role of pH in the water flooding of low salinity water in sandstone with and without clays as a function of temperature. Four chromatography columns containing different amounts of sand, illite, and kaolinite (100% sand; 5% Illite, 95% sand; 5% kaolinite, 95% sand; 2.5% Illite, 2.5% kaolinite, 95% sand) were water flooded with various salinities at four different temperatures 25, 70, 90 and 120 °C. Effluent concentrations of Ca2+ and CH3COO−, and pH were measured. The system was pre-aged for a week at 70 °C with 0.01 molar (M) sodium acetate to simulate the bonding of oil-bound carboxylic acids with the reservoir. Desorption of carboxylic groups from reservoir clay surfaces is thought to be an important control over low salinity EOR water injection and its extent should depend on pH. To quantify the impact of the presence of the clay, a clay-free sample was also used, the acetate release and Ca2+ desorption were in some cases higher than those observed in non-clay free samples. Typically, cores with higher clay content saw a great rise in pH, but the clay-free samples also saw a rise in pH, as great as that of the clay-containing cores.
Society of Petroleum Engineers - SPE EOR Conference at Oil and Gas West Asia 2018
Al-Saedi, Hasan N.; Alhuraishawy, Ali K.; Flori, R.E.; Brady, Patrick V.; Heidari, P.
Numerous quantitative and qualitative methods have been presented to measure wettability. The most well-known methods are Amott-Harvey and U.S. Bureau of Mines. The Amott method describes how the wetting phase displaces the nonwetting phase spontaneously; the main problem with this method insensitivity near neutral wettability. Another problem with this method is that imbibition can take several hours to more than two months to complete. The most important benefit of USBM that differs from the Amott method is the sensitivity close to neutral wettability, but the disadvantage is that USBM cannot recognize if the reservoir has mixed wettability or not, though Amott can. We come up with a method to measure sandstone wettability only by Ca2+ and Br− chromatographic separation according to the method described by Strand et al. (2006) on a chalk core. Three sister cores were pre-aged in formation water without Ca2+ and Br−, and the cores were then aged in oil for three weeks at 95°C. The cores were then flooded with the same formation water until Sor was established. Core#1 was flooded with high salinity water (~117,000 ppm) containing identical concentrations of Ca2+ and Br− (89 μmole). Core#2 was flooded with low salinity water d30HSW. Core#3 was sequentially flooded with HS and LS water to investigate the wettability alteration in the same core. All experiments were conducted at 25 and 70°C to examine the effect of temperature on wettability alteration by the new method. The effluents were collected by a fraction collector for chemical analysis for Ca2+ and Br−, divided by the inlet concentration of Ca2+ and Br−, and then plotted with injected pore volume (PV). The area between the Ca2+ and Br− curves was calculated (Ao). Core#4 was pre-aged in heptane in order to establish water-wet sandstone. The heptane was displaced from the core by the same formation water until residual heptane saturation was reached. The same HS water was injected into Core#3. The effluents were analyzed using the same method as for Core#1, 2. The area between the two curves was also determined using the same method as for Core#1, 2 (AH). The wettability index was then calculated by dividing Ao by AH. The wettability index ranged from 0 for strongly oil-wet to 1 for strongly water-wet and 0.5 for intermediate wettability. Another core was sequentially flooded by HS and LS water to further investigate the wettability alteration by LS water and to verify our new method. The divalent cation Ca2+ was considered as the most potential ion towards sandstone when injecting low salinity water to sandstone. An ion exchange occurred between Ca2+ and H+ during flooding which is the key point for wettability alteration, and in turn, increases oil recovery. Bromine is a tracer that has no potential to the sandstone surface area. Thus, the area between Ca2+ and Br− is proportional directly to the water-wet surface site in sandstone (i.e., both Ca2+ and Br− contact the same water-wet surface area).
Drinking water systems face multiple challenges, including aging infrastructure, water quality concerns, uncertainty in supply and demand, natural disasters, environmental emergencies, and cyber and terrorist attacks. All of these incidents have the potential to disrupt a large portion of a water system causing damage to critical infrastructure, threatening human health, and interrupting service to customers. Recent incidents, including the floods and winter storms in the southern United States, highlight vulnerabilities in water systems and the need to minimize service loss. Simulation and analysis tools can help water utilities better understand how their system would respond to a wide range of disruptive incidents and inform planning to make systems more resilient over time. The Water Network Tool for Resilience (WNTR) is a new open source Python package designed to meet this need. WNTR integrates hydraulic and water quality simulation, a wide range of damage and response options, and resilience metrics into a single software framework, allowing for end-Toend evaluation of water network resilience. WNTR includes capabilities to 1) generate and modify water network structure and operations, 2) simulate disaster scenarios, 3) model response and repair strategies, 4) simulate pressure dependent demand and demand-driven hydraulics, 5) simulate water quality, 6) calculate resilience metrics, and 7) visualize results. These capabilities can be used to evaluate resilience of water distribution systems to a wide range of hazards and to prioritize resilience-enhancing actions. Furthermore, the flexibility of the Python environment allows the user to easily customize analysis. For example, utilities can simulate a specific incident or run stochastic analysis for a range of probabilistic scenarios. The U.S. Environmental Protection Agency and Sandia National Laboratories are working with water utilities to ensure that WNTR can be used to efficiently evaluate resilience under different use cases. The software has been used to evaluate resilience under earthquake and power outage scenarios, run fire-fighting capacity and pipe criticality analysis, evaluate sampling and flushing locations, and prioritize repair strategies. This paper includes discussion on WNTR capabilities, use cases, and resources to help get new users started using the software. WNTR can be downloaded from the U.S. Environmental Protection Agency GitHub site at https://github.com/USEPA/WNTR. The GitHub site includes links to software documentation, software testing results, and contact information.
Anthony, Stephen M.; Miller, Kyle; Tsyrenova, Ayuna; Qin, Shiyi; Yong, Xin; Jiang, Shan
Amphiphilic Janus particles demonstrate unique assembly structures when dried on a hydrophilic substrate. Particle orientations are influenced by amphiphilicity and Janus balance. A three-stage model is developed to describe the process. Simulation further indicates the dominant force is capillary attraction due to the interface pinning at rough Janus boundaries.
Boyle, Timothy J.; Perales, Diana; Rimsza, Jessica M.; Alam, Todd M.; Boye, Daniel M.; Sears, Jeremiah M.; Greathouse, Jeffery A.; Kemp, Richard A.
A pair of thallium salen derivatives was synthesized and characterized for potential use as monitors (or taggants) or as models for Group 13 complexes for subterranean fluid flows. These precursors were isolated from the reaction of thallium ethoxide with N,N′-bis(3,5-di-tert-butylsalicylidene)-ethylenediamine (H2-salo-But), or N,N′-bis(3,5-di-tert-butylsalicylidene)-1,2-phenylenediamine (H2-saloPh-But). The products were identified by single crystal X-ray diffraction as: [((μ-O)2,κ1-(N)(N′)salo-But)Tl2] (1) and {[((μ-O)2saloPh-But)Tl2][((μ-O)2,κ1-(N)(N′)saloPh-But)Tl2]} (2). Both structures are similar, wherein each O atom of the salo moiety bridges the two Tl atoms, leading to a Tl⋯Tl interaction, which is further stabilized by an intramolecular π-bond with neighboring phenyl rings. For 1, an additional Tl⋯N interaction was solved for each metal center; whereas, for 2, one of the two molecules in the matrix has a weak Tl⋯N interaction but no bonding noted in the other molecule. Both Density Functional Theory (DFT) calculations and variable temperature solution 205Tl NMR studies of 1 and 2 further confirmed the Tl⋯Tl interaction. The UV-vis absorbance spectra of these compounds had an absorbance peak at 392 nm for 1 and a broad absorbance peak centered at 469 nm for 2, which were found to be in good agreement with the DFT calculated spectra that were dominated by the singlet state. Fluorescence emission and excitation studies reveal absorptions at 360 and 380 nm for 1 and 2, respectively, which are attributed to the Tl⋯Tl metal centers. To demonstrate practicality, fluorescence spectra of 1 and 2 were obtained using a handheld 405 nm cw laser pointer and portable spectrometer where compound 1 was found to glow 15 times brighter than compound 2. Only compound 1 was found to survive the simulated deep-well conditions explored, which was attributed to the Tl⋯N interaction noted for 1 but not for 2.
When making computational simulation predictions of multi-physics engineering systems, sources of uncertainty in the prediction need to be acknowledged and included in the analysis within the current paradigm of striving for simulation credibility. A thermal analysis of an aerospace geometry was performed at Sandia National Laboratories. For this analysis a verification, validation and uncertainty quantification workflow provided structure for the analysis, resulting in the quantification of significant uncertainty sources including spatial numerical error and material property parametric uncertainty. It was hypothesized that the parametric uncertainty and numerical errors were independent and separable for this application. This hypothesis was supported by performing uncertainty quantification simulations at multiple mesh resolutions, while being limited by resources to minimize the number of medium and high resolution simulations. Based on this supported hypothesis, a prediction including parametric uncertainty and a systematic mesh bias are used to make a margin assessment that avoids unnecessary uncertainty obscuring the results and optimizes computing resources.
Diesel piston bowl geometry can affect turbulent mixing and therefore it impacts heat-release rates, thermal efficiency, and soot emissions. The focus of this work is on the effects of bowl geometry and injection timing on turbulent flow structure. This computational study compares engine behavior with two pistons representing competing approaches to combustion chamber design: a conventional, re-entrant piston bowl and a stepped-lip piston bowl. Three-dimensional computational fluid dynamics (CFD) simulations are performed for a part-load, conventional diesel combustion operating point with a pilot-main injection strategy under non-combusting conditions. Two injection timings are simulated based on experimental findings: an injection timing for which the stepped-lip piston enables significant efficiency and emissions benefits, and an injection timing with diminished benefits compared to the conventional, re-entrant piston. While the flow structure in the conventional, re-entrant combustion chamber is dominated by a single toroidal vortex, the turbulent flow evolution in the stepped-lip combustion chamber depends more strongly on main injection timing. For the injection timing at which faster mixing controlled heat release and reduced soot emissions have been observed experimentally, the simulation predicts the formation of two additional recirculation zones created by interactions with the stepped-lip. Analysis of the CFD results reveals the mechanisms responsible for these recirculating flow structures. Vertical convection of outward radial momentum drives the formation of the recirculation zone in the squish region, while adverse pressure gradients drive flow inward near the cylinder head, thereby contributing to the formation of the second recirculation zone above the step. Bulk gas density is higher for the near-TDC injection timing than for the later injection timing. This leads to increased air entrainment into the sprays and slower spray velocities, so the sprays take longer to interact with the step, and beneficial recirculating flow structures are not obseved.
This open access book examines how the social sciences can be integrated into the praxis of engineering and science, presenting unique perspectives on the interplay between engineering and social science. Motivated by the report by the Commission on Humanities and Social Sciences of the American Association of Arts and Sciences, which emphasizes the importance of social sciences and Humanities in technical fields, the essays and papers collected in this book were presented at the NSF-funded workshop ‘Engineering a Better Future: Interplay between Engineering, Social Sciences and Innovation’, which brought together a singular collection of people, topics and disciplines. The book is split into three parts: A. Meeting at the Middle: Challenges to educating at the boundaries covers experiments in combining engineering education and the social sciences; B. Engineers Shaping Human Affairs: Investigating the interaction between social sciences and engineering, including the cult of innovation, politics of engineering, engineering design and future of societies; and C. Engineering the Engineers: Investigates thinking about design with papers on the art and science of science and engineering practice.
Dynamic probabilistic risk assessment (DPRA) methodologies and the dynamic event tree (DET) methodology specifically allow traditional PRA to be complemented by insights into time-dependent behavior. The ADAPT DET driver has been enhanced recently to provide greater capability to generate DETs and analyze results. The functions that ADAPT uses to gather and present output data have been standardized and enhanced with the goal of automating as much of the process as feasible while remaining simulator and technology agnostic. These individual enhancements come together to reduce the burden on the analyst and allow insights to be discovered more quickly. A recent goal has been the use of ADAPT on high performance computing (HPC) platforms. The number and granularity of treatment of uncertain parameters in a DET may lead to a state space explosion unless DETs are truncated (e.g., using a probability threshold) which may make the complete DET to be infeasible to run on local machines or small computer clusters. Progress can be greatly accelerated by using the large capacity of HPCs. A scheme is presented by which ADAPT gains the capability to distribute jobs to an HPC and retrieve the results seamlessly alongside other types of computation hosts.
The use of exhaust gas recirculation (EGR) in spark ignition engines has been shown to have a number of beneficial effects under specific operating conditions. These include reducing pumping work under part load conditions, reducing NOx emissions and heat losses by lowering peak combustion temperatures, and by reducing the tendency for engine knock (caused by end-gas autoignition) under certain operating regimes. In this study, the effects of EGR addition on knocking combustion are investigated through a combined experimental and modeling approach. The problem is investigated by considering the effects of individual EGR constituents, such as CO2, N2, and H2O, on knock, both individually and combined, and with and without traces species, such as unburned hydrocarbons and NOx. The effects of engine compression ratio and fuel composition on the effectiveness of knock suppression with EGR addition were also investigated. A parametric, experimental matrix of diluents, compression ratio, and fuels was tested to measure knock-limited combustion phasing of each combination. The resulting knock limits were evaluated in the context of thermodynamic effects on the closed cycle, chemical interactions between the EGR constituents and the fuel-oxidizer mixture, and the effect of altered pressure-temperature trajectories on fuel-autoignition behavior. This paper provides an overview of the experimental results, and uses chemical-kinetic modeling to investigate the behavior of a particular fuel - diluent combination which had a strong sensitivity to compression ratio variation. The numerical results shed light on the complex interactions between fuel chemistry, the engine's thermodynamic cycle, and the effect of residence times on the autoignition chemistry which leads to knock. An important and fuel-dependent role of thermal stratification in the end-gas is also suggested by the chemical-kinetics modeling of the experimentally observed knock limits.
Gene therapy has long held promise to correct a variety of human diseases and defects. Discovery of the Clustered Regularly-Interspaced Short Palindromic Repeats (CRISPR), the mechanism of the CRISPRbased prokaryotic adaptive immune system (CRISPR-associated system, Cas), and its repurposing into a potent gene editing tool has revolutionized the field of molecular biology and generated excitement for new and improved gene therapies. Additionally, the simplicity and flexibility of the CRISPR/Cas9 site-specific nuclease system has led to its widespread use in many biological research areas including development of model cell lines, discovering mechanisms of disease, identifying disease targets, development of transgene animals and plants, and transcriptional modulation. In this review, we present the brief history and basic mechanisms of the CRISPR/Cas9 system and its predecessors (ZFNs and TALENs), lessons learned from past human gene therapy efforts, and recent modifications of CRISPR/ Cas9 to provide functions beyond gene editing. We introduce several factors that influence CRISPR/ Cas9 efficacy which must be addressed before effective in vivo human gene therapy can be realized. The focus then turns to the most difficult barrier to potential in vivo use of CRISPR/Cas9, delivery. We detail the various cargos and delivery vehicles reported for CRISPR/Cas9, including physical delivery methods (e.g. microinjection; electroporation), viral delivery methods (e.g. adeno-associated virus (AAV); full-sized adenovirus and lentivirus), and non-viral delivery methods (e.g. liposomes; polyplexes; gold particles), and discuss their relative merits. We also examine several technologies that, while not currently reported for CRISPR/Cas9 delivery, appear to have promise in this field. The therapeutic potential of CRISPR/Cas9 is vast and will only increase as the technology and its delivery improves.
Hansen, Nils H.; Ruwe, Lena; Moshammer, Kai; Kohse-Hoinghaus, Katharina
In this study, we experimentally investigate the high-temperature oxidation kinetics of n-pentane, 1-pentene and 2-methyl-2-butene (2M2B) in a combustion environment using flame-sampling molecular beam mass spectrometry. The selected C5 fuels are prototypes for linear and branched, saturated and unsaturated fuel components, featuring different C-C and C-H bond structures. It is shown that the formation tendency of species, such as polycyclic aromatic hydrocarbons (PAHs), yielded through mass growth reactions increases drastically in the sequence n-pentane < 1-pentene < 2M2B. This comparative study enables valuable insights into fuel-dependent reaction sequences of the gas-phase combustion mechanism that provide explanations for the observed difference in the PAH formation tendency. First, we investigate the fuel-structure-dependent formation of small hydrocarbon species that are yielded as intermediate species during the fuel decomposition, because these species are at the origin of the subsequent mass growth reaction pathways. Second, we review typical PAH formation reactions inspecting repetitive growth sequences in dependence of the molecular fuel structure. Third, we discuss how differences in the intermediate species pool influence the formation reactions of key aromatic ring species that are important for the PAH growth process underlying soot formation. As a main result it was found that for the fuels featuring a CC double bond, the chemistry of their allylic fuel radicals and their decomposition products strongly influences the combination reactions to the initially formed aromatic ring species and as a consequence, the PAH formation tendency.
In an effort to utilize their unique photoactive properties, porphyrin monomers were assembled into tetragonal microparticles by a surfactant-assisted neutralization method through the cooperative interactions between the porphyrin building blocks including π-π stacking, J-aggregation and metal-ligand coordination. Electron microscopy characterization in combination with X-ray diffraction confirmed the three-dimensional ordered tetragonal microstructures with stable crystalline frameworks and well defined external surface morphology. Optical absorption and fluorescence spectroscopy revealed enhanced absorbance properties as compared with the raw porphyrin material, favourable for chromophore excitation and energy transport. With active and responsive optical properties, these new porphyrin microparticles look to serve as promising components for a wide range of applications including sensing, diagnostics, solar cells, and optoelectronic devices.
We recently developed a vacuum assisted micelle confinement synthesis for spherical microparticles of CL-20 with outstanding monodispersity. These microparticles are promising energetic material for explosive devices with enhanced and predictable performances. In this work, to facilitate further development and application of this synthesis, the particle growth process was monitored by in-situ dynamic light scattering measurements. The result was interpreted by a finite element model to obtain critical parameters. These parameters were then used to predict the behavior and product quality of batch synthesis under various operation conditions.
A new quantum dot synthesis method based on metallic-block copolymer precursors was developed. The synthesis produced CdS QDs assembled into chains. This method provides a new model for the study of 1D QD chains to determine its effect on charge transport and optoelectronic coupling. This synthesis method was readily extended to other semiconductor materials including PbS and perovskites producing QDs of various shapes. It evidenced further promise of this synthesis method to assist in the assembly, shape and size control of various nanomaterials.
Low dimensional lead halide perovskite particles are of tremendous interest due to their size-tunable band gaps, low exciton binding energy, high absorption coefficients, outstanding quantum and photovoltaic efficiencies. Herein we report a new solution-based synthesis of stabilized Cs4PbBr6 perovskite particles with high luminescence. This method requires only mild conditions and produces colloidal particles that are ideal for highly efficient solution-based device fabrications. The synthesized microstructures not only display outstanding luminescence quantum yield but also long term stability in atmospheric conditions. Partial halide substitutions were also demonstrated to extend photoluminescence spectra of the perovskite particles. This convenient synthesis and optical tunability of Cs4PbBr6 perovskite particles will be advantageous for future applications of optoelectronic advices.
Sodium Fast Reactors (SFRs) have an extensive operational history that can be leveraged to accelerate the licensing process for modern designs. Sandia National Laboratories (SNL) has recently reconstituted the United States SFR data from the Centralized Reliability Database Organization (CREDO) into a new modern database called the Sodium (Na) System Component Reliability Database (NaSCoRD). This new database is currently undergoing validation and usability testing to better understand the strengths and limitations of this historical data. The most common class of equipment found in the NaSCoRD database are valves. NaSCoRD contains a record of over 4,000 valves that have operated in EBR-II, FFTF, and test loops including those operated by Westinghouse and the Energy Technology Engineering Center. Valve failure events in NaSCoRD can be categorized by working fluid (e.g., sodium, water, gas), valve type (e.g., butterfly, check, throttle, block), failure mode (e.g., failure to open, failure to close, rupture), operating facility, operating temperature, or other user defined categories. Sodium valve reliability estimates will be presented in comparison to estimates provided in historical studies. The impacts of EG&G Idaho’s suggested corrections and various prior distributions on these reliability estimates will also be presented.
Containment bypass scenarios in nuclear power plants can lead to large early release of radionuclides. A residual heat removal (RHR) system interfacing system loss of coolant accident (ISLOCA) has the potential to cause a hazardous environment in the auxiliary building, a loss of coolant from the primary system, a pathway for early release of radionuclides, and the failure of a system important to safely shutting down the plant. Prevention of this accident sequence relies on active systems that may be vulnerable to cyber failures in new or retrofitted plants with digital instrumentation and control systems. RHR ISLOCA in a hypothetical pressurized water reactor is analyzed in a dynamic framework to evaluate the time-dependent effects of various uncertainties on the state of the nuclear fuel, the auxiliary building environment, and the release of radionuclides. The ADAPT dynamic event tree code is used to drive both the MELCOR severe accident analysis code and the RADTRAD dose calculation code to track the progression of the accident from the initiating event to its end states. The resulting data set is then mined for insights into key events and their impacts on the final state of the plant and radionuclide releases.
Polynomial chaos methods have been extensively used to analyze systems in uncertainty quantification. Furthermore, several approaches exist to determine a low-dimensional approximation (or sparse approximation) for some quantity of interest in a model, where just a few orthogonal basis polynomials are required. In this work, we consider linear dynamical systems consisting of ordinary differential equations with random variables. The aim of this paper is to explore methods for producing low-dimensional approximations of the quantity of interest further. We investigate two numerical techniques to compute a low-dimensional representation, which both fit the approximation to a set of samples in the time domain. On the one hand, a frequency domain analysis of a stochastic Galerkin system yields the selection of the basis polynomials. It follows a linear least squares problem. On the other hand, a sparse minimization yields the choice of the basis polynomials by information from the time domain only. An orthogonal matching pursuit produces an approximate solution of the minimization problem. Finally, we compare the two approaches using a test example from a mechanical application.
The recovery of approximately sparse or compressible coefficients in a polynomial chaos expansion is a common goal in many modern parametric uncertainty quantification (UQ) problems. However, relatively little effort in UQ has been directed toward theoretical and computational strategies for addressing the sparse corruptions problem, where a small number of measurements are highly corrupted. Such a situation has become pertinent today since modern computational frameworks are sufficiently complex with many interdependent components that may introduce hardware and software failures, some of which can be difficult to detect and result in a highly polluted simulation result. In this paper we present a novel compressive sampling-based theoretical analysis for a regularized \ell1 minimization algorithm that aims to recover sparse expansion coefficients in the presence of measurement corruptions. Our recovery results are uniform (the theoretical guarantees hold for all compressible signals and compressible corruptions vectors) and prescribe algorithmic regularization parameters in terms of a user-defined a priori estimate on the ratio of measurements that are believed to be corrupted. We also propose an iteratively reweighted optimization algorithm that automatically refines the value of the regularization parameter and empirically produces superior results. Our numerical results test our framework on several medium to high dimensional examples of solutions to parameterized differential equations and demonstrate the effectiveness of our approach.
The laser damage thresholds of optical coatings can degrade over time due to a variety of factors, including contamination and aging. Optical coatings deposited using electron beam evaporation are particularly susceptible to degradation due to their porous structure. In a previous study, the laser damage thresholds of optical coatings were reduced by roughly a factor of two from 2013 to 2017. The coatings in question were high reflectors for 1054 nm that contained SiO 2 and HfO 2 and/or TiO 2 layers, and they were stored in sealed PETG containers in a class 100 cleanroom with temperature control. At the time, it was not certain whether contamination or thin film aging effects were responsible for the reduced laser damage thresholds. Therefore, to better understand the role of contamination, the coatings were recleaned and the laser damage thresholds were measured again in 2018. The results indicate that contamination played the most dominant role in reducing the laser damage thresholds of these optical coatings, even though they were stored in an environment that was presumed to be clean.
Multi-material composite structures develop residual stresses during the curing process due to dissimilar material properties, which eventually may lead to failure in the form of fracture, delamination, or disbonding. Experimentally determining residual stresses can be both time and cost prohibitive, whereas accurate simulated predictions of residual stresses can be cheaper and provide equivalent information during the design process. Residual stresses can be simulated through several different approaches of varying complexity. The method employed in this study assumes the majority of residual stresses are developed due the mismatch of coefficients of thermal expansion and polymer shrinkage, which is indirectly accounted for by calibrating the simulation with an experimentally determined stress free temperature. This method has shown success in predicting the residual stress states across different material combinations and structures in previous studies. Simply using single, or nominal, inputs to the simulation may provide a reasonable prediction, but will be unable to provide any confidence when failure could occur. Therefore, one must consider the natural stochastic behavior of the materials and geometry through an uncertainty quantification study. However, a limitation in performing uncertainty quantification studies for more complex models exists due to the large number of material and geometry parameters that need to be considered. The results from a previously conducted survey of sensitivity analysis methods were leveraged to reduce the number of parameters considered during an uncertainty quantification study, as well as decrease the computational cost in determining the sensitive parameters. This allowed the application of uncertainty quantification methods to validate more complex multi-material structures against experimental results. The structure that will be considered is a multi-material split ring comprised of three layers: Aluminum, glass fiber composite, and carbon fiber composite.
This work demonstrates that the ionic selectivity and ionic conductivity of nanoporous membranes can be controlled independently via layer-by-layer (LbL) deposition of polyelectrolytes and subsequent selective cross-linking of these polymer layers. LbL deposition offers a scalable, inexpensive method to tune the ion transport properties of nanoporous membranes by sequentially dip coating layers of cationic polyethyleneimine and anionic poly(acrylic acid) onto polycarbonate membranes. The cationic and anionic polymers are self-assembled through electrostatic and hydrogen bonding interactions and are chemically crosslinked to both change the charge distribution and improve the intermolecular integrity of the deposited films. Both the thickness of the deposited coating and the use of chemical cross-linking agents influence charge transport properties significantly. Increased polyelectrolyte thickness increases the selectivity for cationic transport through the membranes while adding polyelectrolyte films decreases the ionic conductivity compared to an uncoated membrane. Once the nanopores are filled, no additional decrease in conductivity is observed with increasing film thickness and, upon cross-linking, a portion of the lost conductivity is recovered. The cross-linking agent also influences the ionic selectivity of the resulting polyelectrolyte membranes. Increased selectivity for cationic transport occurs when using glutaraldehyde as the cross-linking agent, as expected due to the selective cross-linking of primary amines that decreases the net positive charge. Together, these results inform deposition of chemically robust, highly conductive, ion-selective membranes onto inexpensive porous supports for applications ranging from energy storage to water purification.
The corrosion behavior of selective laser melted (SLM) 304L was investigated and compared to conventional wrought 304L in aqueous chloride and acidic solutions. Through immersed electrochemical testing and exposure in acidic solutions, the SLM 304L exhibited superior pitting resistance in the polished state compared to wrought 304L. However, the surface condition of the SLM material had a great impact on its corrosion resistance, with the grit-blasted condition exhibiting severely diminished pitting resistance. Local scale, capillary micro-electrochemical and scanning electrochemical microscopy investigations, identified porosity as a contributing factor to decreased corrosion resistance. Preferential corrosion attack was not observed to be related to the characteristic underlying cellular microstructure produced through SLM processing. This study highlights the effects of SLM microstructural features on corrosion resistance, specifically the substantial influence of surface finish on SLM corrosion behavior and the need for development and optimization of processing techniques to improve surface finish.
In light- and medium-duty diesel engines, piston bowl shape influences thermal efficiency, either due to changes in wall heat loss or to changes in the heat release rate. The relative contributions of these two factors are not clearly described in the literature. In this work, two production piston bowls are adapted for use in a single cylinder research engine: a conventional, re-entrant piston, and a stepped-lip piston. An injection timing sweep is performed at constant load with each piston, and heat release analyses provide information about thermal efficiency, wall heat loss, and the degree of constant volume combustion. Zero-dimensional thermodynamic simulations provide further insight and support for the experimental results. The effect of bowl geometry on wall heat loss depends on injection timing, but changes in wall heat loss cannot explain changes in efficiency. Late cycle heat release is faster with the stepped-lip bowl than with the conventional re-entrant bowl, which leads to a higher degree of constant volume combustion and therefore higher thermal efficiency. This effect also depends on injection timing. In general, increasing the degree of constant volume combustion is significantly more effective at improving thermal efficiency than decreasing wall heat loss. Maximizing thermal efficiency will require a deeper understanding of how bowl geometry impacts flow structure, turbulent mixing, and mixing-controlled combustion.
Modeling of chemical and ionization reactions at the extreme conditions of upper-atmosphere hypersonic flow has been critical for spacecraft design from the Apollo era to the present because chemical activity in the flow reduces heat transfer. Nitrogen, which behaves as an inert gas in ambient flows, becomes chemically active under conditions of hypersonic reentry (-10,000 K). Atmospheric chemical reactions during hypersonic reentry are dominated by dissociation of diatomic nitrogen and oxygen molecules and exchange reactions involving diatomic molecules and single atoms. At higher temperatures, ionization also occurs.
The laser damage thresholds of optical coatings can degrade over time due to a variety of factors, including contamination and aging. Optical coatings deposited using electron beam evaporation are particularly susceptible to degradation due to their porous structure. In a previous study, the laser damage thresholds of optical coatings were reduced by roughly a factor of two from 2013 to 2017. The coatings in question were high reflectors for 1054 nm that contained SiO 2 and HfO 2 and/or TiO 2 layers, and they were stored in sealed PETG containers in a class 100 cleanroom with temperature control. At the time, it was not certain whether contamination or thin film aging effects were responsible for the reduced laser damage thresholds. Therefore, to better understand the role of contamination, the coatings were recleaned and the laser damage thresholds were measured again in 2018. The results indicate that contamination played the most dominant role in reducing the laser damage thresholds of these optical coatings, even though they were stored in an environment that was presumed to be clean.
The dissociative photoionization processes of methyl hydroperoxide (CH3OOH) have been studied by imaging Photoelectron Photoion Coincidence (iPEPICO) spectroscopy experiments as well as quantum-chemical and statistical rate calculations. Energy selected CH3OOH+ ions dissociate into CH2OOH+, HCO+, CH3 +, and H3O+ ions in the 11.4-14.0 eV photon energy range. The lowest-energy dissociation channel is the formation of the cation of the smallest "QOOH" radical, CH2OOH+. An extended RRKM model fitted to the experimental data yields a 0 K appearance energy of 11.647 ± 0.005 eV for the CH2OOH+ ion, and a 74.2 ± 2.6 kJ mol-1 mixed experimental-theoretical 0 K heat of formation for the CH2OOH radical. The proton affinity of the Criegee intermediate, CH2OO, was also obtained from the heat of formation of CH2OOH+ (792.8 ± 0.9 kJ mol-1) to be 847.7 ± 1.1 kJ mol-1, reducing the uncertainty of the previously available computational value by a factor of 4. RRKM modeling of the complex web of possible rearrangement-dissociation processes was used to model the higher-energy fragmentation. Supported by Born-Oppenheimer molecular dynamics simulations, we found that the HCO+ fragment ion is produced through a roaming transition state followed by a low barrier. H3O+ is formed in a consecutive process from the CH2OOH+ fragment ion, while direct C-O fission of the molecular ion leads to the methyl cation.
We present here a multi-length scale integration of compositionally tailored NaSICON-based Na+ conductors to create a high Na+ conductivity system resistant to chemical attack in strongly alkaline aqueous environments. Using the Pourbaix Atlas as a generalized guide to chemical stability, we identify NaHf2P3O12 (NHP) as a candidate NaSICON material for enhanced chemical stability at pH > 12, and demonstrate the stability of NHP powders under accelerated aging conditions of 80 °C and pH = 13-15 for a variety of alkali metal cations. To compensate for the relatively low ionic conductivity of NHP, we develop a new low temperature (775 °C) alkoxide-based solution deposition chemistry to apply dense NHP thin films onto both platinized silicon wafers and bulk, high Na+ conductivity Na3Zr2Si2PO12 (NZSP) pellets. These NHP films display Na+ conductivities of 1.35 × 10-5 S cm-1 at 200 °C and an activation energy of 0.53 eV, similar to literature reports for bulk NHP pellets. Under aggressive conditions of 10 M KOH at 80 °C, NHP thin films successfully served as an alkaline-resistant barrier, extending the lifetime of NZSP pellets from 4.26 to 36.0 h. This integration of compositionally distinct Na+ conductors across disparate length scales (nm, mm) and processing techniques (chemically-derived, traditional powder) represents a promising new avenue by which Na+ conducting systems may be utilized in alkaline environments previously thought incompatible with ceramic Na+ conductors.
Low-temperature gasoline combustion (LTGC) engines can deliver high efficiencies, with ultra-low emissions of nitrogen oxides (NOx) and particulate matter (PM). However, controlling the combustion timing and maintaining robust operation remains a challenge for LTGC engines. One promising technique to overcoming these challenges is spark assist (SA). In this work, well-controlled, fully premixed experiments are performed in a single-cylinder LTGC research engine at 1200 rpm using a cylinder head modified to accommodate a spark plug. Compression ratios (CR) of 16:1 and 14:1 were used during the experiments. Two different fuels were also tested, with properties representative of premium- and regular-grade market gasolines. SA was found to work well for both CRs and fuels. The equivalence ratio limits and the effect of intake-pressure boost on the ability of SA to compensate for a reduced Tin were studied. For the conditions studied, =0.42 was found to be most effective for SA. At lower equivalence ratios the flame propagation was too weak, whereas =0.45 was closer to the CI knock/stability limit, which resulted in a smaller range of CA50 control and Tin compensation. At =0.42, SA worked well from Pin = 1.0 to 1.6 bar, but the range of effective Tin compensation dropped progressively with boost from 21 °C at Pin = 1.0 bar to the equivalent of 12 °C at Pin = 1.6 bar. The amount of control authority using SA was demonstrated by varying the spark timing, advancing CA50 to the onset of strong knocking and then retarding CA50 to near misfire. SA provided good control, however the CA50 control range decreased from 7.2° CA at Pin = 1.0 bar to 4.2° CA at Pin = 1.6 bar. For all intake pressures at these well-mixed conditions, NOx emissions for SA were less than for compression ignition only, and all were below the US-2010 Heavy Duty limit.
Flow maldistribution in microchannel heat exchanger(MCHEs) can negatively impact heat exchanger effectiveness.Several rules of thumb exist about designing for uniform flow,but very little data are published to support these claims. In thiswork, complementary experiments and computational fluiddynamics (CFD) simulations of MCHEs enable a solidunderstanding of flow uniformity to a higher level of detail thanpreviously seen. Experiments provide a validation data source toassess CFD predictive capability. The traditional semi-circularheader geometry is tested. Experiments are carried out in a clearacrylic MCHE and water flow is measured optically with particleimage velocimetry. CFD boundary conditions are matched tothose in the experiment and the outputs, specifically velocity andturbulent kinetic energy profiles, are compared.
Rempe, Susan R.; Wen, Po C.; Vanegas, Juan M.; Tajkhorshid, Emad
Teixobactin (Txb) is a recently discovered antibiotic against Gram-positive bacteria that induces no detectable resistance. The bactericidal mechanism is believed to be the inhibition of cell wall biosynthesis by Txb binding to lipid II and lipid III. Txb binding specificity likely arises from targeting of the shared lipid component, the pyrophosphate moiety. Despite synthesis and functional assessment of numerous chemical analogs of Txb, and consequent identification of the Txb pharmacophore, the detailed structural information of Txb-substrate binding is still lacking. Here, we use molecular modeling and microsecond-scale molecular dynamics simulations to capture the formation of Txb-lipid II complexes at a membrane surface. Two dominant binding conformations were observed, both showing characteristic lipid II phosphate binding by the Txb backbone amides near the C-terminal cyclodepsipeptide (d-Thr8-Ile11) ring. Additionally, binding by Txb also involved the side chain hydroxyl group of Ser7, as well as a secondary phosphate binding provided by the side chain of l-allo-enduracididine. Interestingly, those conformations differ by swapping two groups of hydrogen bond donors that coordinate the two phosphate moieties of lipid II, resulting in opposite orientations of lipid II binding. In addition, residues d-allo-Ile5 and Ile6 serve as the membrane anchors in both Txb conformations, regardless of the detailed phosphate binding interactions near the cyclodepsipeptide ring. The role of hydrophobic residues in Txb activity is primarily for its membrane insertion, and subsidiarily to provide non-polar interactions with the lipid II tail. Based on the Txb-lipid II interactions captured in their complexes, as well as their partitioning depths into the membrane, we propose that the bactericidal mechanism of Txb is to arrest cell wall synthesis by selectively inhibiting the transglycosylation of peptidoglycan, while possibly leaving the transpeptidation step unaffected. The observed "pyrophosphate caging" mechanism of lipid II inhibition appears to be similar to some lantibiotics, but different from that of vancomycin or bacitracin.
We report on mode selection and tuning properties of vertical-external-cavity surface-emitting lasers (VECSELs) containing coupled semiconductor and external cavities of total length less than 1 mm. Our goal is to create narrowlinewidth (<1MHz) single-frequency VECSELs that operate near 850 nm on a single longitudinal cavity resonance and tune versus temperature without mode hops. We have designed, fabricated, and measured VECSELs with external-cavity lengths ranging from 25 to 800 μm. We compare simulated and measured coupled-cavity mode frequencies and discuss criteria for single mode selection.
Several programs at Sandia National Laboratories have adopted energy spectra as a metric to relate the severity of mechanical insults to structural capacity. The purpose being to gain insight into the system's capability, reliability, and to quantify the ultimate margin between the normal operating envelope and the likely system failure point -- a system margin assessment. The fundamental concern with the use of energy metrics was that the applicability domain and implementation details were not completely defined for many problems of interest. The goal of this WSEAT project was to examine that domain of applicability and work out the necessary implementation details. The goal of this project was to provide experimental validation for the energy spectra based methods in the context of margin assessment as they relate to shock environments. The extensive test results concluded that failure predictions using energy methods did not agree with failure predictions using S-N data. As a result, a modification to the energy methods was developed following the form of Basquin's equation to incorporate the power law exponent for fatigue damage. This update to the energy-based framework brings the energy based metrics into agreement with experimental data and historical S-N data.
Proceedings of SPIE - The International Society for Optical Engineering
Haque, Samiul; Kindrat, Laszlo P.; Zhang, Li; Mikheev, Vikenty; Kim, Daewa; Liu, Sijing; Chung, Jooyeon; Kuian, Mykhailo; Massad, Jordan E.
We implemented a computationally efficient model for a corner-supported, thin, rectangular, orthotropic polyvinylidene fluoride (PVDF) laminate membrane, actuated by a two-dimensional array of segmented electrodes. The laminate can be used as shape-controlled electromagnetic reflector and the model estimates the reflector's shape given an array of control voltages. In this paper, we describe a model to determine the shape of the laminate for a given distribution of control voltages. Then, we investigate the surface shape error and its sensitivity to the model parameters. Subsequently, we analyze the simulated deflection of the actuated bimorph using a Zernike polynomial decomposition. Finally, we provide a probabilistic description of reflector performance using statistical methods to quantify uncertainty. We make design recommendations for nominal parameter values and their tolerances based on optimization under uncertainty using multiple methods.
An 11-channel 1-GHz bandwidth silicon photonic AWG was fabricated and measured in the lab. Two photonic architectures are presented: (1) RF-envelope detector, and (2) RF downconvertor for digital systems. The RF-envelope detector architecture was modeled based on the demonstrated AWG characteristics to determine estimated system-level RF receiver performance.
Mathematical models of Redox Flow Batteries (RFBs) can be used to analyze cell performance, optimize battery operation, and control the energy storage system efficiently. Among many other models, physics-based electrochemical models are capable of predicting internal states of the battery, such as temperature, state-of-charge, and state-of-health. In the models, estimating parameters is an important step that can study, analyze, and validate the models using experimental data. A common practice is to determine these parameters either through conducting experiments or based on the information available in the literature. However, it is not easy to investigate all proper parameters for the models through this way, and there are occasions when important information, such as diffusion coefficients and rate constants of ions, has not been studied. Also, the parameters needed for modeling charge-discharge are not always available. In this paper, an efficient way to estimate parameters of physics-based redox battery models will be proposed. This paper also demonstrates that the proposed approach can study and analyze aspects of capacity loss/fade, kinetics, and transport phenomena of the RFB system.
We consider the problem of selecting a small set (mosaic) of sensor images (footprints) whose union covers a two-dimensional Region Of Interest (ROI) on Earth. We take the approach of modeling the mosaic problem as a Mixed-Integer Linear Program (MILP). This allows solutions to this subproblem to feed into a larger remote-sensor collection-scheduling MILP. This enables the scheduler to dynamically consider alternative mosaics, without having to perform any new geometric computations. Our approach to set up the optimization problem uses maximal disk sampling and point-in-polygon geometric calculations. Footprints may be of any shape, even non-convex, and we show examples using a variety of shapes that may occur in practice. The general integer optimization problem can become computationally expensive for large problems. In practice, the number of placed footprints is within an order of magnitude of ten, making the time to solve to optimality on the order of minutes. This is fast enough to make the approach relevant for near real-time mission applications. We provide open source software for all our methods, "GeoPlace."
A novel experimental geometry is combined with acoustic emission monitoring capability to measure crack growth and damage accumulation during laboratory simulations of borehole breakout. Three different experiments are conducted in this study using Sierra White Granite. In the first experiment, the sample is deformed at a constant 17.2 MPa confining pressure without pore fluids; in the second experiment, the sample is held at a constant effective pressure of 17.2 MPa with a constant pore pressure; and in the third experiment, pore pressure is modified to induce failure at otherwise constant stress. The results demonstrate that effective pressure and stress path have controlling influence on breakout initiation and damage accumulation in laboratory simulations of wellbore behavior. Excellent agreement between the dry test and constant pore pressure test verify the application of the effective pressure law to borehole deformation. Located AE events coincide with post-test observations of damage and fracture locations. Comparison of AE behavior between the experiments with pore pressure show that breakouts develop prior to peak stress, and continued loading drives damage further into the formation and generates shear fractures.
The Mizunami Underground Research Laboratory is located in the Tono area (Central Japan). Its main purpose is providing a scientific basis for the research and development of technologies needed for deep geological disposal of radioactive waste in fractured crystalline rocks. The current work is focused on the experiments in the research tunnel (500 m depth). The collected tunnel and borehole data were shared with the participants of DEvelopment of COupled models and their VALidation against EXperiments (DECOVALEX) project. This study describes how these data were used to (1) develop the fracture model of the granite rocks around the research tunnel and (2) validate the model.
The fluid injection into deep geological formations altar the states of pore pressure and stress on the faults, potentially causing earthquakes. In the multiphase flow system, the interaction between fluid flow and mechanical deformation in porous media is critical to determine the spatio-temporal distribution of pore pressure and stress. The contrast of fluid and rock properties between different structures produces the changes in pressure gradients and subsequently stress fields. Assuming two-phase fluid flow (gas-water system), we simulate the two-dimensional reservoir including a basement fault, in which injection-induced pressure encounters the fault directly given injection scenarios. The single-phase flow model with the same setting is also conducted to evaluate the multiphase flow effects on mechanical response of the fault to gas injection. A series of sensitivity tests are performed by varying the fault permeability. The presence of gaseous phase reduces the pressure buildup within the gas-saturated region, causing less Coulomb stress change. The low-permeability fault prevent diffusion initially as observed in the single-phase flow system. Once gaseous phase approaches, the fault acts as a capillary barrier that causes increases in pressure within the fault zone, potentially inducing earthquakes even without direct diffusion.
Kerogen plays a central role in hydrocarbon generation in an oil/gas reservoir. In a subsurface environment, kerogen is constantly subjected to stress confinement or relaxation. The interplay between mechanical deformation and gas adsorption of the materials could be an important process for shale gas production but unfortunately is poorly understood. Using a hybrid Monte Carlo/molecular dynamics simulation, we show here that a strong chemo-mechanical coupling may exist between gas adsorption and mechanical strain of a kerogen matrix. The results indicate that the kerogen volume can expand by up to 5.4% and 11% upon CH4 and CO2 adsorption at 192 atm, respectively. The kerogen volume increases with gas pressure and eventually approaches a plateau as the kerogen becomes saturated. The volume expansion appears to quadratically increase with the amount of gas adsorbed, indicating a critical role of the surface layer of gas adsorbed in the bulk strain of the material. Furthermore, gas uptake is greatly enhanced by kerogen swelling. Swelling also increases the surface area, porosity, and pore size of kerogen. Our results illustrate the dynamic nature of kerogen, thus questioning the validity of the current assumption of a rigid kerogen molecular structure in the estimation of gas-in-place for a shale gas reservoir or gas storage capacity for subsurface carbon sequestration. The coupling between gas adsorption and kerogen matrix deformation should be taken into consideration.
Conventional signal processing to estimate radar Doppler frequency often assumes uniform pulse/sample spacing. This is typically more for the convenience of the processing. More recent performance enhancements in processor capability allow optimally processing nonuniform pulse/sample spacing, thereby overcoming some of the baggage that attends uniform sampling, such as Doppler ambiguity and SNR losses due to sidelobe control measures.
Thousands of facilities worldwide are engaged in biological research activities. One of DTRA's missions is to fully understand the types of facilities involved in collecting, investigating, and storing biological materials. This characterization enables DTRA to increase situational awareness and identify potential partners focused on biodefense and biosecurity. As a result of this mission, DTRA created a database to identify biological facilities from publicly available, open-source information. This paper describes an on-going effort to automate data collection and entry of facilities into this database. To frame our analysis more concretely, we consider the following motivating question: How would a decision maker respond to a pathogen outbreak during the 2018 Winter Olympics in South Korea? To address this question, we aim to further characterize the existing South Korean facilities in DTRA's database, and to identify new candidate facilities for entry, so that decision makers can identify local facilities properly equipped to assist and respond to an event. We employ text and social analytics on bibliometric data from South Korean facilities and a list of select pathogen agents to identify patterns and relationships within scientific publication graphs.
For long-term dry storage, most spent nuclear fuel in the United States is placed in welded 304 SS or 316 SS canisters that are stored within passively ventilated overpacks. As the canisters cool, sea-salt aerosols deposited on the canister surfaces will deliquesce to form potentially corrosive brines. We have used thermodynamic modeling to predict the chemical composition of the brines that form by deliquescence of sea-salt aerosols, and to estimate brine volumes and salt/brine volume ratios as a function of temperature and atmospheric relative humidity. We have also mixed representative brines and measured the physical and chemical properties of those brines over a range of temperatures. These data provide a matrix that can be used to predict the evolution of deliquescent brine properties over time on storage canister surfaces, as the canisters cool and surface relative humidity increases. Brine volumes and properties affect corrosion kinetics and damage distributions on the metal surface, and may offer important constraints on the expected rate and extent of corrosion and the timing of SCC crack initiation. The predicted brines do not consider reactions with atmospheric gases that are known to affect sea-salt particle and deliquescent brine compositions under field conditions. The potential effects of such reactions are discussed, and preliminary modeling and experimental data are presented.
In situ Raman microscopy was used to study polysulfide speciation in the bulk ether electrolyte during the discharge and charge of a Li-S electrochemical cell to assess the complex interplay between chemical and electrochemical reactions in solution. During discharge, long chain polysulfides and the S3− radical appear in the electrolyte at 2.4 V indicating a rapid equilibrium of the dissociation reaction to form S3−. When charging, however, an increase in the concentration of all polysulfide species was observed. This highlights the importance of the electrolyte to sulfur ratio and suggests a loss in the useful sulfur inventory from the cathode to the electrolyte.
The U.S. Nuclear Regulatory Commission initiated the state-of-the-art reactor consequence analyses (SOARCA) project to develop realistic estimates of the offsite radiological health consequences for potential severe reactor accidents. The SOARCA analysis of an ice condenser containment plant was performed because its relatively low design pressure and reliance on igniters makes it potentially susceptible to early containment failure from hydrogen combustion during a severe accident. The focus was on station blackout accident scenarios where all alternating current power is lost. Accident progression calculations used the MELCOR computer code and offsite consequence analyses were performed with MACCS. The analysis included more than 500 MELCOR and MACCS simulations to account for uncertainty in important accident progression and offsite consequence input parameters. Consequences from severe nuclear power plant accidents modeled in this and previous SOARCA analyses are smaller than calculated in earlier studies. The delayed releases calculated provide more time for emergency response actions. The results show that early containment failure is very unlikely, even without successful use of igniters. However, these results are dependent on the distributions assigned to safety valve failure-to-close parameters, and considerable uncertainty remains on the true distributions for these parameters due to very limited test data. Even for scenarios resulting in early containment failure, the calculated individual latent fatal cancer risks are very small. Early and latent-cancer fatality risks are one focus of this paper. Regression results showing the most influential parameters are also discussed.
This study addresses predicting the internal thermochemical state in buoyant fire plumes using largeeddy simulations (LES) with a tabular flamelet library for the underlying flame chemistry. Buoyant fire plumes are characterized by moderate turbulent mixing, soot growth and oxidation and radiation transport. Soot moments, mixture fraction and enthalpy evolve in the LES with soot source terms given by the non-adiabatic flamelet library. Participating media radiation transport is predicted using the discrete ordinates method with source terms also from the flamelet library, and the LES subgrid-scale modeling is based on a one-equation kinetic-energy sub-filter model. This library is generated with flamelet states that include unsteady heat loss through extinction nominally representing radiative quenching. We describe the performance of this model both in the context of a laminar coflow configuration where extensive measurements are available and in buoyant turbulent fire plumes where measurements are more global.
Apparent char kinetic rates are commonly used to predict pulverized coal char burning rates. These kinetic rates quantify the char burning rate based on the temperature of the particle and the oxygen concentration at the particle surface, thereby inherently neglecting the impact of variations in the penetration of oxygen into the char on the predicted burning rate. To investigate the impact of variable extents of penetration during Zone II burning conditions, experimental measurements were performed of char particle combustion temperature and burnout for a common U.S. subbituminous coal burning in an optical laminar entrained flow reactor with either helium or nitrogen diluents. The combination of much higher thermal conductivity and mass diffusivity in the helium environments resulted in substantially cooler char combustion temperatures than in equivalent N2 environments. Measured char burnout was similar in the two environments for a given bulk oxygen concentration but was approximately 60% higher in helium environments for a given char combustion temperature. Detailed particle simulations of the experimental conditions confirmed a 60% higher burning rate in the helium environments as a function of char temperature, whereas catalyst theory predicts that the burning rate in helium could be as high as 90% greater than in nitrogen, in the limit of large Thiele modulus (i.e. near the diffusion limit). For application combustion in CO2 environments (e.g. for oxy-fuel combustion), these results demonstrate that due to differences in oxygen diffusivity the apparent char oxidation rates will be lower, but by no more than 9% relative to burning rates measured in nitrogen environments.
Considering that simulations of turbulent combustion are computationally expensive, this chapter takes a decidedly different perspective, that of high-performance computing (HPC). The cost scaling arguments of non-reacting turbulence simulations are revisited and it is shown that the cost scaling for reacting flows is much more stringent for comparable conditions, making parallel computing and HPC indispensable. Hardware abstractions of typical parallel supercomputers are presented which show that for design of an efficient and optimal program, it is essential to exploit both distributed memory parallelism and shared-memory parallelism, i.e. hierarchical parallelism. Principles of efficient programming at various levels of parallelism are illustrated using archetypal code examples. The vast array of numerical methods, particularly schemes for spatial and temporal discretization, are examined in terms of tradeoffs they present from an HPC perspective. Aspects of data analytics that invariably result from large feature-rich data sets generated by combustion simulations are covered briefly.
Effectively using a graphics processing unit (GPU) for Monte Carlo particle transport is a challenging task due to its memory storage requirements and traditionally divergent algorithms. Most efforts in this area have focused on the entire transport process, choosing to use atomic operations or tally replication Tor computing tallies. This work isolates the performance of the tallies from the rest of the transport process, and studies the impact of using different approaches for tallying on the GPU. Five implementations of a photon escape tally are compared, using both single and double precision data types. Results show that replicating tallies is clearly the best option overall, if there is enough memory available on the GPU to store them. When insufficient memory becomes an issue, the best method to use depends on the size, data type, and update frequency of the tally. Global atomic updates can be a reasonable option in some cases, especially if they arc infrequently used. However, there arc two alternatives for general-purpose tallying that were shown to be more effective in most of the scenarios considered. These two alternatives arc based on NVIDIA's warp shuffle feature, which allows 32 threads to simultaneously exchange or broadcast data, minimizing the number of atomic operations needed to get the final tally result.