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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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At least 955 records · Page 53

Writing the Programs of Programmable Catalysis

It has long been known that non-steady state and periodic catalytic reactor operation in terms of temperature, pressure, and composition can lead to higher overall productivity and/or product selectivity than the best steady operation. Recently, the emergence of catalysts whose intrinsic properties can be made to oscillate with time, introduces advanced forcing capabilities that can be “programmed” into the catalysts to broaden the scope and applicability of periodic operation to surface chemistry. In this work, an algorithmic approach is implemented to significantly accelerate the discovery and optimization of periodic steady states of catalytic reactors. Decomposition of complex dynamics into fundamental mechanistic fast–slow steps is seen to improve conceptual understanding of the relationship between binding energy oscillation protocols and overall catalytic rates. Finding structured forcing protocols, optimally tailored to the multiple time scales of a given individual mechanism, requires an efficient search of high-dimensional parameter spaces. Here, this is enabled here through active learning (Bayesian optimization, enhanced by our proposed Bayesian continuation). Implementation of these methods is shown to accelerate the evaluation of catalyst programs by up to several orders of magnitude. Faster screening of programmable catalysts to discover periodic steady states enables the optimization of catalytic operating protocols and thus opens the possibility for catalyst engineering based on optimal forcing programs to control rate and product selectivity, even for complex multistep catalytic mechanisms.

catalysis↗

Performance evaluation of OpenFOAM on many-core architectures

In this article application of Open Source Field Operation and Manipulation (OpenFOAM) C++ libraries for solving engineering problems on many-core architectures is presented. Objective of this article is to present scalability of OpenFOAM on parallel platforms solving real engineering problems of fluid dynamics. Scalability test of OpenFOAM is performed using various hardware and different implementation of standard PCG and PBiCG Krylov iterative methods. Speed up of various implementations of linear solvers using GPU and MIC accelerators are presented in this paper. Numerical experiments of 3D lid-driven cavity flow for several cases with various number of cells are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Data-driven electrolyte design for lithium metal anodes

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

25 ENERGY STORAGE↗

Comparison of Multi-Scale Nonlinear and Conventional Linear Methods for Stress Analysis of Nb 3 Sn Superconducting Magnets

Here this is an extension of the work on a multi-scale nonlinear procedure that demonstrated how to conduct nonlinear stress analysis of Nb 3 Sn superconducting accelerator magnets. The nonlinear procedure uses measured stress-strain curves of annealed copper, Nb 3 Sn strands and coil samples as inputs, which reduces the number of assumptions made for material properties—key uncertainties of any engineering analysis. The results from nonlinear analysis, semi-nonlinear analysis, and linear analysis of the same QFFB2 Nb 3 Sn quadrupole magnet under the same temperature and loads, were compared and discussed. The comparison illustrates that nonlinear stress analysis is significantly more accurate than other methods. As the superconducting coil block is a complex, composite material, it would be inadequate to assume the whole coil block to be linear, either isotropic or orthotropic. It is imperative to conduct nonlinear analysis by simulating the superconducting coil to the level of detail of the individual cables and individual strands. The nonlinear stress analysis procedure can be used to simulate not only Nb 3 Sn magnets, but also NbTi and HTS magnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Novel Carbon Storage Monitoring Methods

Conference presentation at American Institute of Chemical Engineers (AIChE) Annual Meeting, San Diego, California, October 27–31, 2024. We presented a high-level overview of many novel and sustainable carbon storage monitoring methods that are at various stages of planning or demonstration to accelerate the deployment of CCS technologies at future CCS sites across the United States. Our work impacts the general CCS industry by providing novel and more sustainable methods for tracking CO 2 plume migration and performing assurance monitoring. Our work primarily benefits three parties: 1) CCS community members through knowledge sharing of lessons learned; 2) CCS operators through commercialization of additional methods, including improvements on workflows and simplification of fieldwork; and 3) stakeholders of CCS projects through implementation of low-impact and more autonomous monitoring solutions.

02 PETROLEUM↗

Reusability First: Toward FAIR Workflows

The FAIR principles of open science (Findable, Accessible, Interoperable, and Reusable) have had transformative effects on modern large-scale computational science. In particular, they have encouraged more open access to and use of data, an important consideration as collaboration among teams of researchers accelerates and the use of workflows by those teams to solve problems increases. How best to apply the FAIR principles to workflows themselves, and software more generally, is not yet well understood. We argue that the software engineering concept of technical debt management provides a useful guide for application of those principles to workflows, and in particular that it implies reusability should be considered as ‘first among equals’. Moreover, our approach recognizes a continuum of reusability where we can make explicit and selectable the tradeoffs required in workflows for both their users and developers.To this end, we propose a new abstraction approach for reusable workflows, with demonstrations for both synthetic workloads and real-world computational biology workflows. Through application of novel systems and tools that are based on this abstraction, these experimental workflows are refactored to rightsize the granularity of workflow components to efficiently fill the gap between end-user simplicity and general customizability. Our work makes it easier to selectively reason about and automate the connections between trade-offs across user and developer concerns when exposing degrees of freedom for reuse. Additionally, by exposing fine-grained reusability abstractions we enable performance optimizations, as we demonstrate on both institutional-scale and leadership-class HPC resources.

Wolf, Matthew↗

A Unified Testing Platform to Mature Blockchain Applications for Grid Emulation Environments: Preprint

Blockchain technology is a relatively novel technology that can be used to develop more decentralized, autonomous and tamper-evident solutions. A feature that can aid Transactive Energy Systems to reach their goals by enabling individual actors to communicate and reach consensus with other participants in a more decentralized fashion. However, technical barriers to evaluate and adopt this type of technology within the electrical domain still exist. To facilitate this task, BLOSEM Unified Testing Platform (UTP), a DOE-sponsored, multi-lab effort intends to accelerate the development of solutions by offering a common set of reusable services that can be used to interconnect existent grid tools with blockchain services. UTP is intended to serve as development platform that can provide application engineers with the technical means to evaluate potential blockchain solutions, by enabling them to concentrate on the actual application functionalities while at the same time abstracting the connectivity and performance measurement tasks. The use of BLOSEM UTP is further demonstrated by implementing two potential use cases that are intended to validate both the feasibility of implementing these applications as blockchain-based solutions while also demonstrating the features provided by UTP.

blockchain↗

Preparatory Verification of a New Monte Carlo Code cosRMC based on VERA Core Physics Benchmark

To promote nuclear power plant system design and simulation software self-reliance development, DOE of China approved a R and D key project to develop an integrated engine for pressurized water reactor core and system design and analysis, referred as COSINE hereafter. The scope of this code package includes reactor physics, thermal hydraulics, safety analysis, severe accidents, probability safety assessment and etc. Many universities, research institutes and nuclear related corporations in China are involved in the code development, among which the State Nuclear Power Software Development Center (SNPSDC) plays the leading role. With the requirement of accurate three-dimensional modeling of the advanced, special or new complex core in reactor neutronics and shielding analysis, Monte Carlo method is becoming a more powerful tool for reactor analysis. Thus, a new Monte Carlo transport code named cosRMC (abbreviation for COSINE Reactor Monte Carlo) has been developed jointly by SNPSDC and Department of Engineering Physics, Tsinghua University, the main developer of RMC code. The cosRMC now has many functions as criticality calculation, fixed-source calculation, burnup calculation, and etc. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation have been implemented in cosRMC to improve the efficiency. In order to ensure its reliability, several types of V and V work have been and are being carried out for cosRMC. In this paper, some preparatory verification results based on VERA Core Physics Benchmark are presented. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

TINES - Time Integration, Newton and Eigen Solver v. 1.0

SAND2021-1505 O. TINES is an open source software providing math infrastructure for solving many stiff time ordinary differential equations (ODEs) and/or differential algebraic equations (DAEs) using a batch hierarchical parallelism. The code is written using a parallel programming model (i.e., Kokkos) to future-proof the next generation parallel computing platforms such as GPU accelerators. This code is developed to support Exascale Catalytic Chemistry (ECC) Project. The code provides fundamental math helpers that can aid other research projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Kim, Kyungjoo↗

ATOM - Accelerating therapeutics through opportunities in medicine

Create a new paradigm of drug discovery that would reduce the time from an identified drug target to clinical candidate from the current ~6 years to just 12 months. ATOM will develop, test, and validate a multidisciplinary approach to drug discovery in which modern science, technology and engineering, supercomputing, simulations, data science, and artificial intelligence are highly integrated into a single drug-discovery platform that can ultimately be shared with the drug development community at-large.

60 APPLIED LIFE SCIENCES↗

Demonstration of improved dilution tolerance using a production-intent compact nanosecond pulse ignition system

Transient plasma ignition using nanosecond pulses has demonstrated the potential to enable improved fuel economy and reduced emissions by enabling lean and EGR limit extension in dilute burn engines. Existing spark ignition technology is not adequate because the energy transfer mechanisms between the spark and the fuel-air mixture are not efficient enough to guarantee stable ignition for dilute mixtures at high-load conditions. Additionally, long duration sparks and other advanced ignition solutions that require increased energy delivered accelerate spark plug electrode wear. To date, non-thermal plasma ignition with nanosecond pulses have demonstrated a lean ignition limit beyond an air/fuel ratio of 24 [1], demonstrated high-pressure ignition at densities equivalent to over 100 bar at the time of ignition [2], and demonstrated stable (COV <3 %) ignition at EGR dilution levels >20 % [3]. While low-energy nanosecond pulses have demonstrated strong performance compared to existing solutions, they currently only exist on the market in laboratory systems, rather than a production ready system in a single rugged, weather-proof, under-the-hood enclosure. Transient Plasma Systems (TPS) has recently demonstrated the potential for a retroffitable solution similar to coil-on-plug architecture that allows a direct replacement of existing ignition technology without any engine modification. The system was run on a gasoline direct injection engine at Argonne National Laboratory and demonstrated the same trends as previously observed with research grade systems, including lean and EGR limit extension and more stable ignition across a range of loads. The system was capable of delivering 30 kV pulses in bursts of up to 20 pulses at 30 kHz, and demonstrated stable combustion at an air/fuel ratio of 23.5, exhaust gas recirculation of 23 %, and ignition at 19.2 bar with COV <3 % using only 20 kV pulses.

nanosecond pulsed power↗

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗

Revisiting the late-time growth of single-mode Rayleigh–Taylor instability and the role of vorticity

Growth of the single-fluid single-mode Rayleigh-Taylor instability (RTI) is revisited in 2D and 3D using fully compressible high-resolution simulations. We conduct a systematic analysis of the effects of perturbation Reynolds number (Rep) and Atwood number (A) on RTI’s late-time growth. Contrary to the common belief that single-mode RTI reaches a terminal bubble velocity, we show that the bubble re-accelerates when Rep is sufficiently large, consistent with [Ramaparabhu et al. 2006, Wei and Livescu 2012]. However, unlike in [Ramaparabhu et al. 2006], we find that for a sufficiently high Rep, the bubble’s late-time acceleration is persistent and does not vanish. Analysis of vorticity dynamics shows a clear correlation between vortices inside the bubble and re-acceleration. Due to symmetry around the bubble and spike (vertical) axes, the self-propagation velocity of vortices points in the vertical direction. If viscosity is sufficiently small, the vortices persist long enough to enter the bubble tip and accelerate the bubble [Wei and Livescu 2012]. A similar effect has also been observed in ablative RTI [Betti and Sanz 2006]. As the spike growth increases relative to that of the bubble at higher A, vorticity production shifts downward, away from the centerline and toward the spike tip. We modify the Betti-Sanz model for bubble velocity by introducing a vorticity efficiency factor η = 0.45 to accurately account for re-acceleration caused by vorticity in the bubble tip. It had been previously suggested that vorticity generation and the associated bubble re-acceleration are suppressed at high A. However, we present evidence that if the large Rep limit is taken first, bubble re-acceleration is still possible. Our results also show that re-acceleration is much easier to occur in 3D than 2D, requiring smaller Rep thresholds.

42 ENGINEERING↗

Inviscid linear stability analysis of two vertical columns of different densities in a gravitational acceleration field

Here, we study the inviscid linear stability of a vertical interface separating two fluids of different densities and subject to a gravitational acceleration field parallel to the interface. In this arrangement, the two free streams are constantly accelerated, which means that the linear stability analysis is not amenable to Fourier or Laplace solution in time. Instead, we derive the equations analytically by the initial-value problem method and express the solution in terms of the well-known parabolic cylinder function. The results, which can be classified as an accelerating Kelvin–Helmholtz configuration, show that even in the presence of surface tension, the interface is unconditionally unstable at all wavemodes. This is a consequence of the ever increasing momentum of the free streams, as gravity accelerates them indefinitely. The instability can be shown to grow as the exponential of a quadratic function of time.

42 ENGINEERING↗

On-Orbit Results for the Xilinx Virtex-4 FPGA

This paper provides information regarding the use of the Xilinx Virtex-4 field-programmable gate array in a spacecraft deployed to low earth orbit. The results are compared to pre-deployment accelerated and fault injection testing.

42 ENGINEERING↗

Uncertainty Propagation from Experiment Measurements to Modeling Approaches: A Case for SMR Steam Entrainment Testing

To license new and advanced reactor designs, regulators must be convinced that their unique safety cases—relative to existing large scale reactors—have been adequately addressed by the designed reactor protection systems. In water cooled small modular reactors (SMRs), droplet entrainment in steam flow has significant implications on the progression of accident scenarios due to its compact design features, which requires representative test data applicable to SMR designs. Computer code, modeling and simulation (M&S) tools and models require adequate verification, assessment, and qualification. This includes M&S results validation against scaled empirical data within allowable uncertainty bands to gain regulatory approvals during the various stages of reactor system design, demonstration, and commercialization. However, measurement uncertainty within the empirical datasets and test data applicability ranges requires careful consideration of M&S inputs (i.e., boundary conditions, and initial conditions), and verification and validation efforts. This study focuses on uncertainty quantification in designing scaled test facilities for SMR applications with appropriate measurements and a standard data-reduction method to estimate thermal hydraulics characteristics parameters that incorporate physics phenomena of interest. In addition, this study supports the evaluation model development and assessment process using M&S that interfaces with advanced computing tools and digital twin capabilities. This will allow synchronization between experiment and modeling approaches for droplet entrainment testing and analysis, improving diagnostics, prognostics, and decision-making to accelerate regulatory approval.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗