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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 1,225 records · Page 68

Extreme-scale Algorithms and Solver Resilience

A widening gap exists between the peak performance of high-performance computers and the performance achieved by complex applications running on these platforms. Over the next decade, extreme-scale systems will present major new challenges to algorithm development that could amplify this mismatch in such a way that it prevents the productive use of future DOE Leadership computers due to the following; Extreme levels of parallelism due to multicore processors; An increase in system fault rates requiring algorithms to be resilient beyond just checkpoint/restart; Complex memory hierarchies and costly data movement in both energy and performance; Heterogeneous system architectures (mixing CPUs, GPUs, etc.); and Conflicting goals of performance, resilience, and power requirements.

97 MATHEMATICS AND COMPUTING↗

Portable, heterogeneous ensemble workflows at scale using libEnsemble

libEnsemble is a Python-based toolkit for running dynamic ensembles, developed as part of the DOE Exascale Computing Project. The toolkit utilizes a unique generator–simulator–allocator paradigm, where generators produce input for simulators, simulators evaluate those inputs, and allocators decide whether and when a simulator or generator should be called. The generator steers the ensemble based on simulation results. Generators may, for example, apply methods for numerical optimization, machine learning, or statistical calibration. libEnsemble communicates between a manager and workers. Flexibility is provided through multiple manager–worker communication substrates each of which has different benefits. These include Python’s multiprocessing, mpi4py, and TCP. Multisite ensembles are supported using Balsam or Globus Compute. We overview the unique characteristics of libEnsemble as well as current and potential interoperability with other packages in the workflow ecosystem. We highlight libEnsemble’s dynamic resource features: libEnsemble can detect system resources, such as available nodes, cores, and GPUs, and assign these in a portable way. These features allow users to specify the number of processors and GPUs required for each simulation; and resources will be automatically assigned on a wide range of systems, including Frontier, Aurora, and Perlmutter. Such ensembles can include multiple simulation types, some using GPUs and others using only CPUs, sharing nodes for maximum efficiency. We also describe the benefits of libEnsemble’s generator–simulator coupling, which easily exposes to the user the ability to cancel, and portably kill, running simulations based on models that are updated with intermediate simulation output. We demonstrate libEnsemble’s capabilities, scalability, and scientific impact via a Gaussian process surrogate training problem for the longitudinal density profile at the exit of a plasma accelerator stage. In conclusion, the study uses gpCAM for the surrogate model and employs either Wake-T or WarpX simulations, highlighting efficient use of resources that can easily extend to exascale.

Dynamic ensembles↗

Evaluation of PETSc on a Heterogeneous Architecture, the OLCF Summit System: Part II - Basic Communication Performance

Nearest-neighbor communication is at the heart of many high-performance parallel computations. We report on the performance of such communication on the Oak Ridge Leadership Computing Facility system Summit in the context of the PETSc communication module. The analysis in this report includes basic Ping-Pong point-to-point communication and regular and irregular nearest-neighbor communication.

97 MATHEMATICS AND COMPUTING↗

SU-E-T-67: Clinical Implementation and Evaluation of the Acuros Dose Calculation Algorithm

Purpose: The main aim of the current study is to present a detailed description of the implementation of the Acuros XB Dose Calculation Algorithm, and subsequently evaluate its clinical impacts by comparing it with AAA algorithm. Methods: The source models for both Acuros XB and AAA were configured by importing the same measured beam data into Eclipse treatment planning system. Both algorithms were evaluated by comparing calculated dose with measured dose on a homogeneous water phantom for field sizes ranging from 6cm × 6cm to 40cm × 40cm. Central axis and off-axis points with different depths were chosen for the comparison. Similarly, wedge fields with wedge angles from 15 to 60 degree were used. In addition, variable field sizes for a heterogeneous phantom were used to evaluate the Acuros algorithm. Finally, both Acuros and AAA were tested on VMAT patient plans for various sites. Does distributions and calculation time were compared. Results: On average, computation time is reduced by at least 50% by Acuros XB compared with AAA on single fields and VMAT plans. When used for open 6MV photon beams on homogeneous water phantom, both Acuros XB and AAA calculated doses were within 1% of measurement. For 23 MV photon beams, the calculated doses were within 1.5% of measured doses for Acuros XB and 2% for AAA. When heterogeneous phantom was used, Acuros XB also improved on accuracy. Conclusion: Compared with AAA, Acuros XB can improve accuracy while significantly reduce computation time for VMAT plans.

60 APPLIED LIFE SCIENCES↗

Computational mechanics for geosystems management to support the energy and natural resources mission.

U.S. energy needs - minimizing climate change, mining and extraction technologies, safe waste disposal - require the ability to simulate, model, and predict the behavior of subsurface systems. They propose development of a coupled thermal, hydrological, mechanical, chemistry (THMC) modeling capability for massively parallel applications that can address these critical needs. The goal and expected outcome of this research is a state-of-the-art, extensible, simulation capability, based upon SIERRA Mechanics, to address multiphase, multicomponent reactive transport coupled to nonlinear geomechanics in heterogeneous (geologic) porous materials. The THMC code provides a platform for integrating research in numerical mathematics and algorithms for chemically reactive multiphase systems with computer science research in adaptive coupled solution control and framework architecture.

54 ENVIRONMENTAL SCIENCES↗

Computational Efficient Upscaling Methodology for Predicting Thermal Conductivity of Nuclear Waste forms

This study evaluated different upscaling methods to predict thermal conductivity in loaded nuclear waste form, a heterogeneous material system. The efficiency and accuracy of these methods were compared. Thermal conductivity in loaded nuclear waste form is an important property specific to scientific researchers, in waste form Integrated performance and safety code (IPSC). The effective thermal conductivity obtained from microstructure information and local thermal conductivity of different components is critical in predicting the life and performance of waste form during storage. How the heat generated during storage is directly related to thermal conductivity, which in turn determining the mechanical deformation behavior, corrosion resistance and aging performance. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling models were developed and implemented. Due to the absence of experimental data, prediction results from finite element method (FEM) were used as reference to determine the accuracy of different upscaling models. Micrographs from different loading of nuclear waste were used in the prediction of thermal conductivity. Prediction results demonstrated that in term of efficiency, boundary models (Taylor and Sachs model) are better than self consistent model, statistical upscaling method and FEM. Balancing the computation resource and accuracy, statistical upscaling is a computational efficient method in predicting effective thermal conductivity for nuclear waste form.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An optimum approximation of n-point correlation functions of random heterogeneous material systems

An approximate solution for n-point correlation functions is developed in this study. In the approximate solution, weight functions are used to connect subsets of (n-1)-point correlation functions to estimate the full set of n-point correlation functions. In previous related studies, simple weight functions were introduced for the approximation of three and four-point correlation functions. In this work, the general framework of the weight functions is extended and derived to achieve optimum accuracy for approximate n-point correlation functions. Such approximation can be utilized to construct global n-point correlation functions for a system when there exist limited information about these functions in a subset of space. To verify its accuracy, the new formulation is used to approximate numerically three-point correlation functions from the set of two-point functions directly evaluated from a virtually generated isotropic heterogeneous microstructure representing a particulate composite system. Similarly, three-point functions are approximated for an anisotropic glass fiber/epoxy composite system and compared to their corresponding reference values calculated from an experimental dataset acquired by computational tomography. Results from both virtual and experimental studies confirm the accuracy of the new approximation. The new formulation can be utilized to attain a more accurate approximation to global n-point correlation functions for heterogeneous material systems with a hierarchy of length scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ERAS: Enabling the Integration of Real-World Intellectual Properties (IPs) in Architectural Simulators

Sandia National Laboratories is investigating scalable architectural simulation capabilities with a focus on simulating and evaluating highly scalable supercomputers for high performance computing applications. There is a growing demand for RTL model integration to provide the capability to simulate customized node architectures and heterogeneous systems. This report describes the first steps integrating the ESSENTial Signal Simulation Enabled by Netlist Transforms (ESSENT) tool with the Structural Simulation Toolkit (SST). ESSENT can emit C++ models from models written in FIRRTL to automatically generate components. The integration workflow will automatically generate the SST component and necessary interfaces to ’plug’ the ESSENT model into the SST framework.

97 MATHEMATICS AND COMPUTING↗

Addressing the Challenges of Anomaly Detection for Cyber Physical Energy Grid Systems

The consolidation of cyber communications networks and physical control systems within the energy smart grid introduces a number of new risks. Unfortunately, these risks are largely unknown and poorly understood, yet include very high impact losses from attack and component failures. One important aspect of risk management is the detection of anomalies and changes. However, anomaly detection within cyber security remains a difficult, open problem, with special challenges in dealing with false alert rates and heterogeneous data. Furthermore, the integration of cyber and physical dynamics is often intractable. And, because of their broad scope, energy grid cyber-physical systems must be analyzed at multiple scales, from individual components, up to network level dynamics. We describe an improved approach to anomaly detection that combines three important aspects. First, system dynamics are modeled using a reduced order model for greater computational tractability. Second, a probabilistic and principled approach to anomaly detection is adopted that allows for regulation of false alerts and comparison of anomalies across heterogeneous data sources. Third, a hierarchy of aggregations are constructed to support interactive and automated analyses of anomalies at multiple scales.

Anomaly Detection↗

Understanding Water Transport in Polymer Electrolyte Fuel Cells Using Coupled Continuum and Pore-Network Models

Water management remains a critical issue for polymer electrolyte fuel cell performance and durability, especially at lower temperatures and with ultrathin electrodes. To understand and explain experimental observations better, water transport in gas diffusion layers (GDLs) with macroscopically heterogeneous morphologies was simulated using a novel coupling of continuum and pore-network models. X-ray computed tomography was used to extract GDL material parameters for use in the pore-network model. The simulations were conducted to explain experimental observations associated with stacking of anode GDLs, where stacking of the anode GDLs increased the limiting current density. Through imaging, it is shown that the stacked anode GDL exhibited an interfacial region of high porosity. The coupled model shows that this morphology allowed more efficient water movement through the anode and higher temperatures at the cathode compared to the single GDL case. As a result, the cathode exhibited less flooding and hence better low temperature performance with the stacked anode GDL.

30 DIRECT ENERGY CONVERSION↗

Variably Saturated Flow and Multicomponent Biogeochemical Reactive Transport Modeling of a Uranium Bioremediation Field Experiment

Field experiments at a former uranium mill tailings site have identified the potential for stimulating indigenous bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. This effectively removes uranium from solution resulting in groundwater concentrations below actionable standards. Three-dimensional, coupled variably-saturated flow and biogeochemical reactive transport modeling of a 2008 in situ uranium bioremediation field experiment is used to better understand the interplay of transport rates and biogeochemical reaction rates that determine the location and magnitude of key reaction products. A comprehensive reaction network, developed largely through previous 1-D modeling studies, was used to simulate the impacts on uranium behavior of pulsed acetate amendment, seasonal water table variation, spatially-variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. A principal challenge is the mechanistic representation of biologically-mediated terminal electron acceptor process (TEAP) reactions whose products significantly alter geochemical controls on uranium mobility through increases in pH, alkalinity, exchangeable cations, and highly reactive reduction products. In general, these simulations of the 2008 Big Rusty acetate biostimulation field experiment in Rifle, Colorado confirmed previously identified behaviors including (1) initial dominance by iron reducing bacteria that concomitantly reduce aqueous U(VI), (2) sulfate reducing bacteria that become dominant after {approx}30 days and outcompete iron reducers for the acetate electron donor, (3) continuing iron-reducer activity and U(VI) bioreduction during dominantly sulfate reducing conditions, and (4) lower apparent U(VI) removal from groundwater during dominantly sulfate reducing conditions. New knowledge on simultaneously active metal and sulfate reducers has been incorporated into the modeling. In this case, an initially small population of slow growing sulfate reducers is active from the initiation of biostimulation. Three-dimensional, variably saturated flow modeling was used to address impacts of a falling water table during acetate injection. These impacts included a significant reduction in aquifer saturated thickness and isolation of residual reactants and products, as well as unmitigated uranium, in the newly unsaturated vadose zone. High permeability sandy gravel structures resulted in locally high flow rates in the vicinity of injection wells that increased acetate dilution. In downgradient locations, these structures created preferential flow paths for acetate delivery that enhanced local zones of TEAP reactivity and subsidiary reactions. Conversely, smaller transport rates associated with the lower permeability lithofacies (e.g., fine) and vadose zone were shown to limit acetate access and reaction. Once accessed by acetate, however, these same zones limited subsequent acetate dilution and provided longer residence times that resulted in higher concentrations of TEAP products when terminal electron donors and acceptors were not limiting. Finally, facies-based porosity and reactive surface area variations were shown to affect aqueous uranium concentration distributions; however, the ranges were sufficiently small to preserve general trends. Large computer memory and high computational performance were required to simulate the detailed coupled process models for multiple biogeochemical components in highly resolved heterogeneous materials for the 110-day field experiment and 50 days of post-biostimulation behavior. In this case, a highly-scalable subsurface simulator operating on 128 processor cores for 12 hours was used to simulate each realization. An equivalent simulation without parallel processing would have taken 60 days, assuming sufficient memory was available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Automatic Time Step Control to Resolve Hydromechanically Driven Fault Reactivation, Spontaneous Nucleation, and Seismic Arrest

Abstract A physical understanding of the progression from flow‐driven (quasi‐static) poromechanical deformation to dynamic fault rupture is critical to the resilient operations of several engineering systems. These processes are bridged by a progression from fault reactivation to the spontaneous nucleation of unstable sliding. Toward addressing this challenge, novel automatic time step size control methods are developed to enable accurate and efficient simulation of these dynamics and transitions from the first principles. The controllers combine local models for discretization error and Coulomb failure conditions to automatically adjust the time step size across several orders of magnitude. The methods do not require additional empirical or theoretical input and can resolve the pre‐rupture, interseismic, and seismic periods to the allowed accuracy. The computational results reveal that the proposed methods automatically capture the onset of reactivation and nucleation for homogeneous and heterogeneous fields. Hydrodynamic and structural heterogeneity lead to disparate critical nucleation sizes compared to those predicted by theory. The results highlight its potential in predicting induced seismicity in realistic subsurface engineering systems and at practical scales.

Environmental Sciences & Ecology↗

Atomic-scale identification of active sites of oxygen reduction nanocatalysts

Heterogeneous nanocatalysts play a crucial role in both the chemical and energy industries. Despite substantial advancements in theoretical, computational and experimental studies, identifying their active sites remains a major challenge. Here we utilize atomic electron tomography to determine the three-dimensional atomic structure of PtNi and Mo-doped PtNi nanocatalysts for the electrochemical oxygen reduction reaction. We then employ the experimental atomic structures as input to first-principles-trained machine learning to identify the active sites of the nanocatalysts. Through the analysis of the structure–activity relationships, we formulate an equation termed the local environment descriptor, which balances the strain and ligand effects to provide physical and chemical insights into active sites in the oxygen reduction reaction. The ability to determine the three-dimensional atomic structure and chemical composition of realistic nanoparticles, combined with machine learning, could transform our fundamental understanding of the active sites of catalysts and guide the rational design of optimal nanocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulating Diverse HEP Workflows on Heterogeneous Architectures

We evaluate key patterns and estimate throughput bounds of simulated transformation of conventional high energy physics (HEP) data processing workflows to heterogeneous equivalents. The simulation parameter space includes the number of offloaded tasks, CPU/accelerator ratios of intra-task computations, offload latencies, and run time efficiency of offloaded computations. The simulation is performed for a diverse set of state-of-the-art event reconstruction scenarios from ATLAS, LHCb and CMS - the frontier HEP experiments of the Large Hadron Collider project.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Performance Results on CPU/GPU Exascale Architectures for OMEGA: The Ocean Model for E3SM Global Applications

The US Department of Energy (DOE) conducts climate simulations on some of the world’s largest supercomputers. These exascale machines use heterogeneous architectures with both CPUs and GPUs, and scientific codes must adapt to make full use of this computing power. Los Alamos National Lab is developing Omega: The Ocean Model for E3SM Global Applications, which is specifically designed for modern exascale computers. It uses external libraries that have been optimized for a variety of architectures to run on different supercomputers. Omega is an unstructured-mesh ocean model based on TRiSK numerical methods. It will be the new ocean component of the DOE’s Energy Exascale Earth System Model (E3SM). The algorithms in Omega follow those of the current ocean component, MPAS-Ocean, but it will be written in C++ rather than Fortran to take advantage of the Kokkos performance portability library. Omega spatial operators are written as Kokkos kernels to run efficiently on both CPUs and GPUs. Work on Omega began in 2023 with a new C++ framework for unstructured mesh partitioning, halo exchanges, parallel IO, and Kokkos interfaces. The current version, Omega-0, is being developed to solve the shallow water equations and at present includes all of the tendency terms but not time stepping. Here we share the results of Omega-0 verification and performance testing. Verification includes unit tests implemented with CTest as well as convergence tests in Polaris, an in-house python package with a large suite of test problems. Performance tests compare simulations conducted on CPUs versus GPUs and across different architectures: tests are run on Frontier, which has AMD “Optimized 3rd Gen EPYC” CPUs and AMD MI250X GPUs, as well as Perlmutter, which is composed of AMD EPYC 7763 CPUs and NVIDIA A100 GPUs.

58 GEOSCIENCES↗

Improving Pixel Level Cloud Optical Property Retrieval using Monte Carlo Simulations

The accurate pixel-by-pixel retrieval of cloud optical properties from space is influenced by radiative smoothing due to high order photon scattering and radiative roughening due to low order scattering events. Both are caused by cloud heterogeneity and the three-dimensional nature of radiative transfer and can be studied with the aid of computer simulations. We use Monte Carlo simulations on variable 1-D and 2-D model cloud fields to seek for dependencies of smoothing and roughening phenomena on single scattering albedo, solar zenith angle, and cloud characteristics. The results are discussed in the context of high resolution satellite (such as Landsat) retrieval applications. The current work extends the investigation on the inverse NIPA (Non-local Independent Pixel Approximation) as a tool for removing smoothing and improving retrievals of cloud optical depth. This is accomplished by: (1) Delineating the limits of NIPA applicability; (2) Exploring NIPA parameter dependences on cloud macrostructural features, such as mean cloud optical depth and geometrical thickness, degree of extinction and cloud top height variability. We also compare parameter values from empirical and theoretical considerations; (3) Examining the differences between applying NIPA on radiation quantities vs direct application on optical properties; (4) Studying the radiation budget importance of the NIPA corrections as a function of scale. Finally, we discuss fundamental adjustments that need to be considered for successful radiance inversion at non-conservative wavelengths and oblique Sun angles. These adjustments are necessary to remove roughening signatures which become more prominent with increasing absorption and solar zenith angle.

Oreopoulos, Lazaros↗

M ssbauer spectroscopy

This most comprehensive and unrivaled compendium in the field provides an up-to-date account of the chemistry of solids, nanoparticles and hybrid materials. Following a valuable introductory chapter reviewing important synthesis techniques, the handbook presents a series of contributions by about 150 international leading experts -- the "Who's Who" of solid state science. Clearly structured, in six volumes it collates the knowledge available on solid state chemistry, starting from the synthesis, and modern methods of structure determination. Understanding and measuring the physical properties of bulk solids and the theoretical basis of modern computational treatments of solids are given ample space, as are such modern trends as nanoparticles, surface properties and heterogeneous catalysis. Emphasis is placed throughout not only on the design and structure of solids but also on practical applications of these novel materials in real chemical situations.

Mossbauer spectroscopy↗