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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Results of the Analyses of the SRNL Solvent Components

At the request of the Savannah River Mission Completion (SRMC), personnel at Savannah River Site (SRS) performed analyses on the remaining solvent components that are being stored at the Savannah River National Laboratory (SRNL). This was done to determine if the remaining stock of materials were still suitable for use for the Salt Waste processing Facility (SWPF). Two drums of Modifier, two drums BOBCalix, four drums of MAXCalix, and four jars of TiDG*HCl were analyzed. All were found to be of acceptable purity for use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1999

A Design Heritage-Based Forecasting Methodology for Risk Informed Management of Advanced Systems

The development of next generation systems often carries with it the promise of improved performance, greater reliability, and reduced operational costs. These expectations arise from the use of novel designs, new materials, advanced integration and production technologies intended for functionality replacing the previous generation. However, the novelty of these nascent technologies is accompanied by lack of operational experience and, in many cases, no actual testing as well. Therefore some of the enthusiasm surrounding most new technologies may be due to inflated aspirations from lack of knowledge rather than actual future expectations. This paper proposes a design heritage approach for improved reliability forecasting of advanced system components. The basis of the design heritage approach is to relate advanced system components to similar designs currently in operation. The demonstrated performance of these components could then be used to forecast the expected performance and reliability of comparable advanced technology components. In this approach the greater the divergence of the advanced component designs from the current systems the higher the uncertainty that accompanies the associated failure estimates. Designers of advanced systems are faced with many difficult decisions. One of the most common and more difficult types of these decisions are those related to the choice between design alternatives. In the past decision-makers have found these decisions to be extremely difficult to make because they often involve the trade-off between a known performing fielded design and a promising paper design. When it comes to expected reliability performance the paper design always looks better because it is on paper and it addresses all the know failure modes of the fielded design. On the other hand there is a long, and sometimes very difficult road, between the promise of a paper design and its fulfillment; with the possibility that sometimes the reliability promise is not fulfilled at all. Decision makers in advanced technology areas have always known to discount the performance claims of a design to a degree in proportion to its stage of development, and at times have preferred the more mature design over the one of lesser maturity even with the latter promising substantially better performance once fielded. As with the broader measures of performance this has also been true for projected reliability performance. Paper estimates of potential advances in design reliability are to a degree uncertain in proportion to the maturity of the features being proposed to secure those advances. This is especially true when performance-enhancing features in other areas are also planned to be part of the development program.

Maggio, Gaspare↗
DOE OSTI2019

Hardware Evaluation Outreach: Application development Challenges Now and for the Exascale Era

The intent of this document is to assist the programmer in understanding details of contemporary and Exascale hardware system design and how these designs provide opportunities and place constraints on next-generation simulation software design. We attempt to clarify hardware organization and component details for our most current and Exascale systems to help program developers understand how software needs to change in order to take best advantage of the performance available. Exascale success is specifically defined for ECP as a 50x improvement over baseline in the aggregate "capability volume" on several KPP axes, of which raw floating point performance is only one, but also includes characteristics such as problem size, system memory size, node memory size, power, and efficiency. This multi-axis approach is particularly important to understand in the context of delivered improvements in real applications, since, for instance, the floating point computation may comprise less than 10% of the actual computational work required. Given the Exascale requirements and the constraints these requirements put on the performance expectations of fundamental system components, the programmer will be forced to re-think several application implementation details in order to achieve exaflop performance on these systems. The remainder of this document aims to present more detail on Exascale era system hardware and the specific areas that the programmer should address to extract performance from these systems. We attempt to give the programmer guidance at both a high- and low-level, providing some abstract suggestions on how to refactor codes given the expected system architectures and some low-level recommendations on how to implement these modifications. We also include a section on training resources that are helpful for both programmers that are just beginning to understand code modifications for contemporary and Exascale systems and for those that have done some refactoring and are now trying to extract maximal application performance from these systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

2D High‐Entropy Transition Metal Dichalcogenides for Carbon Dioxide Electrocatalysis

Abstract High‐entropy alloys combine multiple principal elements at a near equal fraction to form vast compositional spaces to achieve outstanding functionalities that are absent in alloys with one or two principal elements. Here, the prediction, synthesis, and multiscale characterization of 2D high‐entropy transition metal dichalcogenide (TMDC) alloys with four/five transition metals is reported. Of these, the electrochemical performance of a five‐component alloy with the highest configurational entropy, (MoWVNbTa)S 2 , is investigated for CO 2 conversion to CO, revealing an excellent current density of 0.51 A cm −2 and a turnover frequency of 58.3 s −1 at ≈ −0.8 V versus reversible hydrogen electrode. First‐principles calculations show that the superior CO 2 electroreduction is due to a multi‐site catalysis wherein the atomic‐scale disorder optimizes the rate‐limiting step of CO desorption by facilitating isolated transition metal edge sites with weak CO binding. 2D high‐entropy TMDC alloys provide a materials platform to design superior catalysts for many electrochemical systems.

Cavin, John↗
DOE OSTI2016

Lower molar shape and size in prosimian and platyrrhine primates

Abstract The goal of this research is to evaluate the relative strength of the influences of diet, size, and phylogenetic signal on dental geometric shape. Accurate comprehension of these factors and their interaction is important for reconstructing diet and deriving characters for a cladistic analysis in fossil primates. Geometric morphometric analysis is used to identify axes of shape variation in the lower second molars of (a) prosimian primates and (b) platyrrhines. Landmarks were placed on µCT‐generated surface renderings. Landmark configurations were aligned using generalized Procrustes analysis. Principal components analysis and phylogenetic principal components analysis (pPCA) were performed on species average landmark co‐ordinates. pPCs were examined with phylogenetic generalized least squares analysis for association with size and with diet. PCs from both phylogenetic and non‐phylogenetic analyses were sufficient to separate species by broad dietary categories, including insectivores and folivores. In neither analysis was pPC1 correlated with tooth size, but some other pPCs were significantly correlated with size. The pattern of association between pPCs and size altered when centroid size and dietary variables were combined in the model; effects of diet factors typically exceeded effects of size. These results indicate a dominant phylogenetic and dietary signal in molar shape but also show some shape change correlated with size in the absence of obvious dietary associations. Geometric morphometric analysis appears to be useful for tracking functional traits in molars, particularly in tracking differences between folivorous and insectivorous species.

St. Clair, Elizabeth M.↗
DOE OSTI2021

Incorporating the Role(s) of Human Actors in Complex System Design for Safety and Security

Traditional systems engineering demonstrates the importance of customer needs in scoping and defining design requirements; yet, in practice, other human stakeholders are often absent from early lifecycle phases. Human factors are often omitted in practice when evaluating and down-selecting design options due to constraints such as time, money, access to user populations, or difficulty in proving system robustness through the inclusion of human behaviors. Advances in systems engineering increasingly include non-technical influences into the design, deployment, operations, and maintenance of interacting components to achieve common performance objectives. Furthermore, such advances highlight the need to better account for the various roles of human actors to achieve desired performance outcomes in complex systems. Many of these efforts seek to infuse lessons and concepts from human factors (enhanced decision-making through Crew Resource Management), systems safety (Rasmussen's “drift toward danger”) and organization science (Giddens' recurrent human acts leading to emergent behaviors) into systems engineering to better understand how socio-technical interactions impact emergent system performance. Safety and security are examples of complex system performance outcomes that are directly impacted by varying roles of human actors. Using security performance of high consequence facilities as a representative use case, this article will outline the System Context Lenses to understand how to include various roles of human actors into systems engineering design. Several exemplar applications of this organizing lenses will be summarized and used to highlight more generalized insights for the broader systems engineering community.

42 ENGINEERING↗
DOE OSTI2019

Evaluating LULESH Kernels on OpenCL FPGA

FPGAs are becoming promising heterogeneous computing components for high-performance computing. In this paper, we evaluate the resource utilizations, performance, and performance per watt of our implementations of the LULESH kernels in OpenCL on an Arria10-based FPGA platform. LULESH is a complex proxy application in the CORAL benchmark suite. We choose two representative kernels “CalcFBHourglassForceForElems” and “EvalEOSForElems” from the application in our study. Compared with the baseline implementations, our optimizations improve the performance by a factor of 1.65X and 2.96X for the two kernels on the FPGA, respectively. Using directives for accelerator programming, we also evaluate the performance of the kernels on an Intel Xeon 16-core CPU and an Nvidia K80 GPU. We find that the FPGA, constrained by the memory bandwidth, can perform 1.05X to 3.4X better than the CPU and GPU for small problem sizes. For the first kernel, the performance per watt on the FPGA is 1.59X and 7.1X higher than that on an Intel Xeon 16-core CPU and an Nvidia K80 GPU, respectively. For the second kernel, the performance per watt on the GPU is 1.82X higher than that on the FPGA. However, the performance per watt on the FPGA is 1.77X higher than that on the CPU.

FPGA↗
DOE OSTI2022

Finding Hidden Patterns in High Resolution Wind Flow Model Simulations

Wind flow data is critical in terms of investment decisions and policy making. High resolution data from wind flow model simulations serve as a supplement to the limited resource of original wind flow data collection. Given the large size of data, finding hidden patterns in wind flow model simulations are critical for reducing the dimensionality of the analysis. In this work, we first perform dimension reduction with two autoencoder models: the CNN-based autoencoder (CNN-AE) [1], and hierarchical autoencoder (HIER-AE) [2], and compare their performance with the Principal Component Analysis (PCA). We then investigate the super-resolution of the wind flow data. By training a Generative Adversarial Network (GAN) with 300 epochs, we obtained a trained model with 2× resolution enhancement. We compare the results of GAN with Convolutional Neural Network (CNN), and GAN results show finer structure as expected in the data field images. Also, the kinetic energy spectra comparisons show that GAN outperforms CNN in terms of reproducing the physical properties for high wavenumbers and is critical for analysis where high-wavenumber kinetics play an important role.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Additive Manufacturing of Ceramic Heat Exchanger: Opportunities and Limits of the Lithography-Based Ceramic Manufacturing (LCM)

Additive manufacturing (AM) techniques allow the preparation of tailor-made structures for specific applications with a high flexibility in regard to shape and design. The lithography-based ceramic manufacturing (LCM) technology allows the AM of high-performance alumina and zirconia components. There are still some restrictions in regard to possible geometries. The opportunities and limits of the LCM technology are discussed in the following paper using the example of ceramic heat exchangers. Structures are presented which combine a large surface for heat exchange with a small component volume and low pressure drop. This paper concludes summarizing the essential remarks.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Influence of Deep Cryogenic Treatment on the Mechanical Properties of Spring Steels

Leaf springs are mechanical elements responsible for supporting the vertical load on heavy duty vehicles. For this critical structural component, the required mechanical performance depends mainly on chemical composition and heat treatment. SAE 5160 and SAE 6140 steels are widely used as springs, because after heat treatments, the strength requirements of impact and fatigue are obtained. 51CrV4-ACF steel is another spring steel option which also exhibits excellent mechanical properties. The objective of this work was to study the influence of conventional heat treatments and cryogenic treatment on properties involving fatigue and impact resistance of spring steels. Furthermore, fracture toughness was measured for these materials, and the fracture surfaces were analyzed. The results showed that the cryogenic cycles used did not provide positive effects on spring steel performance. On the other hand, the chemical composition and the application of cleanliness technology promoted higher mechanical strength: Fracture toughness of 51CrV4-ACF was 100% higher than SAE 5160 steel.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Digital-twin-based improvements to diagnosis, prognosis, strategy assessment, and discrepancy checking in a nearly autonomous management and control system

We report the Nearly Autonomous Management And Control System (NAMAC) is a comprehensive control system to assist plant operations by furnishing control recommendations to operators in a broad class of situations. This study refines a NAMAC system for making reasonable recommendations during complex loss of flow (LOF) scenarios with a validated EBR-II simulator, digital twins improved by machine-learning algorithms, a multi-attribute decision-making scheme, and a discrepancy checker for identifying unexpected recommendation effects. The performance of each NAMAC component is assessed, while the capability of NAMAC is demonstrated and evaluated in a class of LOF scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluating consumer 3D printing nozzles as a low cost alternative for mesophase pitch-derived carbon fiber production

Synthetic fibers, such as Kevlar fibers, SiC fibers, and carbon fibers, are essential components for constructing high performance structures. Whether for engineering, sports, energy storage (batteries and supercapacitors), or aerospace applications, fiber microstructure plays a critical role in fiber properties and functionalities. However, studying fiber nozzle configurations and spinning parameters to achieve the desired microstructure remains challenging, costly, and time consuming. Here, mesophase pitch-derived fibers were used as an example to demonstrate that low cost, commercially available 3D printer nozzles can “print” fibers. Four different nozzles were used to “print” fibers and the effects of their features on fiber properties were observed and compared to other lab spun and commercial pitch- derived CF. A longer orifice length resulted in higher modulus fiber whereas a larger draw-down ratio yielded a stronger fiber. Furthermore, the findings provide a new opportunity for 3D printer hardware application and open up opportunities for developing low-cost fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of nitric oxide and exhaust gases on gasoline surrogate autoignition: iso-octane experiments and modeling

Exhaust gas recirculation (EGR) is widely used in advanced internal combustion engines to reduce engine emissions as well as control combustion phasing. Among various species present in EGR gases, CO 2 and H 2 O are two major components that can thermally and chemically affect fuel autoignition. It is of fundamental interest to isolate the thermal and chemical effects of CO 2 and H 2 O on fuel autoignition, especially as such an effort has not been reported in the literature. Moreover, nitric oxide (NO) is known to exhibit strong chemical effects on fuel autoignition, which in turn affects engine combustion phasing. The effects of ultra-low NO addition (< 100 ppm) on fuel autoignition at low temperatures are also not well understood. Recognizing these problems, autoignition experiments of iso-octane (a major gasoline surrogate component) in air are performed in this study using a rapid compression machine at varying compressed pressures, equivalence ratios, dilution levels with an EGR gas analogue (consisting of CO 2 , H 2 O, O 2 , and N 2 ) and N 2 only, and varying amounts of NO addition. Furthermore, the thermal and chemical effects of the EGR gas analogue are isolated and evaluated by comparing the ignition delay time datasets of EGR and N2-only diluted cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Microstructure optimization with constrained design objectives using machine learning-based feedback-aware data-generation

Microstructure sensitive design has a critical impact on the performance of engineering materials. The safety and performance requirements of critical components, as well as the cost of material and machining of Titanium components, make dovetailing of the microstructure imperative. This paper addresses the optimization of several microstructure design problems for Titanium components under specific design constraints using a feedback-aware data-driven solution methodology. In this study, the microstructure is modeled with an orientation distribution function (ODF) that measures the volumes of different crystallographic orientations. Two algorithms are used to sample the entire microstructure space followed by machine learning-aided identification of a minimal subset of ODF dimensions which is subsequently explored by targeted sampling. Conventional optimization methods lead to a unique microstructure rather than yielding a comprehensive space of optimal or near-optimal microstructures. Multiple solutions are crucial for the deployment of materials design for manufacturing as traditional manufacturing processes can only generate a limited set of microstructures. Our data sampling-based methodology not only outperforms or is on par with other optimization techniques in terms of the optimal property value, but also provides numerous near-optimal solutions, 3–4 orders of magnitude more than previous methods. Consequently, the proposed framework delivers a spectrum of optimal solutions in the microstructure space which can accelerate materials development and reduce manufacturing costs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tensile behavior of diffusion bonded AA6061 - AA6061 with variation in cooling method

Hot isostatically pressed AA6061 cladding is an important structural component of the high performance, Zr-laminated U-10Mo monolithic fuel system for the application in research and test reactors. In this study, the mechanical behavior of two diffusion bonded aluminum alloy, AA6061, was examined using tensile testing. Solid-to-solid diffusion bonding between two pieces of AA6061 was performed by isothermal annealing at 560 °C for 1.5 h, and diffusion couples were subsequently cooled via three different cooling methods: furnace cooling, air cooling, and water quenching. Dog-bone shaped tensile specimens, with 10 mm in gauge length (with diffusion bonded interface in the middle), and 1.5 × 1.5 mm 2 gauge cross-sections, were fabricated from the diffusion bonded AA6061 by electro-discharge machining. Yield strength (% EL at failure) of furnace cooled, air cooled and water quenched tensile specimens determined was 82 ~ 89 MPa (10 ~ 30%), 112 ~ 116 MPa (10 ~ 14%), and 149 ~ 164 MPa (10 ~ 17%), respectively. This variation in mechanical behavior was examined with cooling-rate dependent, concentrated precipitation of Mg 2 Si at the diffusion bonded interface, with due respect for mechanical properties of the AA6061 alloy that inherently vary as a function of cooling rate from 560 °C. Finite element analysis using ABAQUS was employed to augment experimental findings with the appropriate microstructural constituents and alloy properties. Results suggest that the strength is dominated by matrix/bulk properties of AA6061, while ductility is strongly influenced by the cooling method dependent presence of Mg 2 Si precipitates at the interface.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

RF design of APEX2 two-cell continuous-wave normal conducting photoelectron gun cavity based on multi-objective genetic algorithm

High brightness, high repetition rate electron beams are key components for optimizing the performance of next generation scientific instruments, such as MHz-class X-ray Free Electron Laser (XFEL) and Ultra-fast Electron Diffraction/Microscopy (UED/UEM). In the Advanced Photo-injector EXperiment (APEX)at Berkeley Lab, a photoelectron gun based on a 185.7 MHz normal conducting re-entrant RF cavity, has been proven to be a feasible solution to provide high brightness, high repetition rate electron beam for both XFEL and UED/UEM. Based on the success of APEX, a new electron gun system, named APEX2, has been under development to further improve the electron beam brightness. For APEX2, we have designed a new 162.5 MHz two-cell photoelectron gun and achieved a significant increase on the cathode launching field and the beam exit energy. For a fixed charge per bunch, these improvements will allow for the emittance reduction and hence to an increased beam brightness. The design of APEX2 gun cavity is a complex problem with multiple design goals and restrictions, some even competing each other. In conclusion, for a systematic and comprehensive search for the optimized cavity geometry, we have developed and implemented a novel optimization method based on the Multi-Objective Genetic Algorithm (MOGA).

47 OTHER INSTRUMENTATION↗