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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 OSTI2025

The Viskores User's Guide (V.1.0)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created Viskores: the visualization toolkit for multi-/many-core architectures. Viskores supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. Viskores also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although Viskores provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Neglecting Model Parametric Uncertainty Can Drastically Underestimate Flood Risks

Abstract Floods drive dynamic and deeply uncertain risks for people and infrastructures. Uncertainty characterization is a crucial step in improving the predictive understanding of multi‐sector dynamics and the design of risk‐management strategies. Current approaches to estimate flood hazards often sample only a relatively small subset of the known unknowns, for example, the uncertainties surrounding the model parameters. This approach neglects the impacts of key uncertainties on hazards and system dynamics. Here we mainstream a recently developed method for Bayesian inference to calibrate a computationally expensive distributed hydrologic model. We compare three different calibration approaches: (a) stepwise line search, (b) precalibration or screening, and (c) the Fast Model Calibrations (FaMoS) approach. FaMoS deploys a particle‐based approach that takes advantage of the massive parallelization afforded by modern high‐performance computing systems. We quantify how neglecting parametric uncertainty and data discrepancy can drastically underestimate extreme flood events and risks. Precalibration improves prediction skill score over a stepwise line search. The Bayesian calibration improves the uncertainty characterization of model parameters and flood risk projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ultraefficient resistance switching between charge ordered phases in 1 T -TaS 2 with a single picosecond electrical pulse

Progress in high-performance computing demands significant advances in memory technology. Among novel memory technologies that promise efficient device operation on a sub-ns timescale, resistance switching between charge ordered phases of 1T-TaS 2 has shown to be potentially useful for development of high-speed, energy efficient nonvolatile memory devices. Measurement of the electrical operation of such devices in the picosecond regime is technically challenging and hitherto still largely unexplored. Here, we use an optoelectronic “laboratory-on-a-chip” experiment for measurement of ultrafast memory switching, enabling accurate measurement of electrical switching parameters with 100 fs temporal resolution. Photoexcitation and electro-optic sampling on a (Cd,Mn)Te substrate are used to generate and, subsequently, measure electrical pulse propagation with intra-band excitation and sub-gap probing, respectively. We demonstrate high contrast nonvolatile resistance switching from high to low resistance states of a 1T-TaS 2 device using single sub-2ps electrical pulses. Using detailed modeling, we find that the switching energy density per unit area is exceptionally small, E A =9.4 fJ/μm 2 . Finally, the speed and energy efficiency of an electronic “write” process place the 1T-TaS 2 devices into a category of their own among new generation nonvolatile memory devices.

42 ENGINEERING↗
DOE OSTI2012

From nucleons to nuclei to fusion reactions

Nuclei are prototypes of many-body open quantum systems. Complex aggregates of protons and neutrons that interact through forces arising from quantum chromo-dynamics, nuclei exhibit both bound and unbound states, which can be strongly coupled. In this respect, one of the major challenges for computational nuclear physics, is to provide a unified description of structural and reaction properties of nuclei that is based on the fundamental underlying physics: the constituent nucleons and the realistic interactions among them. This requires a combination of innovative theoretical approaches and high-performance computing. In this contribution, we present one of such promising techniques, the ab initio no-core shell model/resonating-group method, and discuss applications to light nuclei scattering and fusion reactions that power stars and Earth-base fusion facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Kokkos v.4.0

SAND2023-07883O Kokkos software implements C++ performance portability programming models, tools and math libraries, which enables science and engineering software developers to use single-source codes for a wide range of computer architectures. Kokkos also provides implementations of existing and proposed C++ standard features that support programming model and math libraries that are used for implementing performance-portable scientific and engineering applications. The Kokkos libraries provide algorithms, data structures, and tools to enable high-performance computing developers to write performance-portable code. Capabilities fall into three broad categories: Kokkos Core, Kokkos Kernels, and Kokkos Tools. 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.

SciDAC↗
NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗
DOE OSTI2020

Computing for the DUNE Long-Baseline Neutrino Oscillation Experiment

This is a talk given at Computers in High Energy Physics in Adelaide, South Australia, Australia in November 2019. It is partially intended to explain the context of DUNE Computing for computing specialists. The DUNE collaboration consists of over 180 institutions from 33 countries. The experiment is in preparation now with commissioning of the first 10kT fiducial volume Liquid Argon TPC expected over the period 2025-2028 and a long data taking run with 4 modules expected from 2029 and beyond. An active prototyping program is already in place with a short test beam run with a 700T, 15,360 channel prototype of single-phase readout at the neutrino platform at CERN in late 2018 and tests of a similar sized dual-phase detector scheduled for mid-2019. The 2018 test beam run was a valuable live test of our computing model. The detector produced raw data at rates of up to ~2GB/s. These data were stored at full rate on tape at CERN and Fermilab and replicated at sites in the UK and Czech Republic. In total 1.2 PB of raw data from beam and cosmic triggers were produced and reconstructed during the six week test beam run. Baseline predictions for the full DUNE detector data, starting in the late 2020's are 30-60 PB of raw data per year. In contrast to traditional HEP computational problems, DUNE's Liquid Argon TPC data consist of simple but very large (many GB) 2D data objects which share many characteristics with astrophysical images. This presents opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Grid-based minimization at scale: Feldman-Cousins corrections for light sterile neutrino search

High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form Δχ2 is often used to form the confidence intervals, however, this approach can lead to statistical inaccuracies due to the small signal rate in the region-of-interest. In this paper, we present a computational model for the computationally expensive Feldman-Cousins corrections to construct a statistically accurate confidence interval for neutrino oscillation analysis. The program performs a grid-based minimization over oscillation parameters and is written in C++. Our algorithms make use of vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by employing DIY. We demonstrate the strong scaling of the application at High-Performance Computing (HPC) sites. We utilize HDF5 along with HighFive to write the results of the calculation to file.

Wospakrik, Marianette↗
DOE OSTI2019

Multigrid treatment of implicit continuum diffusion

Implicit treatment of diffusive terms of various differential orders common in continuum mechanics modeling, such as computational fluid dynamics, is investigated with spectral and multigrid algorithms in non-periodic 2D domains. In doubly periodic time dependent problems these terms are handled efficiently by spectral methods, but in non-periodic systems solved with distributed memory parallel computing and 2D domain decomposition, this efficiency is lost for a large number of processors. Here, we built and present here a multigrid algorithm for these types of problems that outperforms a spectral solution employing the highly optimized FFTW library. This solver is suitable for high performance computing and may be able to efficiently treat implicit diffusion of arbitrary order by introducing auxiliary equations of lower order. We test these solvers for fourth and sixth order diffusion with harmonic test functions as well as turbulent 2D magnetohydrodynamic simulations. It is also shown that an anisotropic operator without mixed-derivative terms improves model accuracy and speed, and we examine the impact that the various diffusion operators have on the energy, the enstrophy, and the qualitative aspect of a simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

REVEAL: An Extensible Reduced Order Model Builder for Simulation and Modeling

Many science domains need to build computationally efficient and accurate representations of high fidelity, computationally expensive simulations. These computationally efficient versions are known as reduced-order models. This paper presents the design and implementation of a novel reduced-order model (ROM) builder, the REVEAL toolset. This toolset generates ROMs based on science- and engineering-domain specific simulations executed on high performance computing (HPC) platforms. The toolset encompasses a range of sampling and regression methods that can be used to generate a ROM, automatically quantifies the ROM accuracy, and provides support for an iterative approach to improve ROM accuracy. REVEAL is designed to be extensible in order to utilize the core functionality with any simulator that has published input and output formats. It also defines programmatic interfaces to include new sampling and regression techniques so that users can ‘mix and match’ mathematical techniques to best suit the characteristics of their model. In this paper, we describe the architecture of REVEAL and demonstrate its usage with a computational fluid dynamics model used in carbon capture.

Surrogate model, reduced order model, sensitivity ↗
DOE OSTI2025

ChatHPC: Building the Foundations for a Productive and Trustworthy AI-Assisted HPC Ecosystem

ChatHPC democratizes large language models for the high-performance computing (HPC) community by providing the infrastructure, ecosystem, and knowledge needed to apply modern generative AI technologies to rapidly create specific capabilities for critical HPC components while using relatively modest computational resources. Our divide-and-conquer approach focuses on creating a collection of reliable, highly specialized, and optimized AI assistants for HPC based on the cost-effective and fast Code Llama fine-tuning processes and expert supervision. We target major components of the HPC software stack, including programming models, runtimes, I/O, tooling, and math libraries. Thanks to AI, ChatHPC provides a more productive HPC ecosystem by boosting important tasks related to portability, parallelization, optimization, scalability, and instrumentation, among others. With relatively small datasets (on the order of KB), the AI assistants, which are created in a few minutes by using one node with two NVIDIA H100 GPUs and the ChatHPC library, can create new capabilities with Meta’s 7-billion parameter Code Llama base model to produce high-quality software with a level of trustworthiness of up to 90% higher than the 1.8-trillion parameter OpenAI ChatGPT-4o model for critical programming tasks in the HPC software stack.

Young, Aaron [ORNL] (ORCID:0000000254484667)↗
NASA NTRS1994

Space-based crystal growth and thermocapillary flow

The demand for larger crystals is increasing especially in applications associated with the electronic industry, where large and pure electronic crystals (notably silicon) are the essential material to make high-performance computer chips. Crystal growth under weightless conditions has been considered an ideal way to produce bigger and hopefully better crystals. One technique which may benefit from a microgravity environment is the float-zone crystal-growth process, a containerless method for producing high-quality electronic material. In this method, a rod of material to be refined is moved slowly through a heating device which melts a portion of it. Ideally, as the melt resolidifies it does so as a single crystal which is then used as substrate for building microelectronic devices. The possibility of contamination by contact with other material is reduced because of the 'float' configuration. However, since the weight of the material contained in the zone is supported by the surface-tension force, the size of the resulting crystal is limited in Earth-based productions; in fact, some materials have properties which prevent this process from being used to manufacture crystals of reasonable size. Consequently, there has been a great deal of interest in exploiting the microgravity environment of space to grow larger size crystals of electronic material using the float-zone method. In addition to allowing larger crystals to be grown, a microgravity environment would also significantly reduce the magnitude of convection induced by buoyancy forces during the melting state. This type of convection was once thought to be at least partially responsible for the presence of undesirable nonuniformities--called striations--in material properties observed in float-zone material. However, past experiments on crystal growth under weightless conditions found that even with the absence of gravity, the float-zone method sometimes still results striations. It is believed that another mechanism is playing a dominant role in the microgravity environment.

Shen, Yong-Hong↗
NASA NTRS2008

An Assessment of the State-of-the-art in Multidisciplinary Aeromechanical Analyses

This paper presents a survey of the current state-of-the-art in multidisciplinary aeromechanical analyses which integrate advanced Computational Structural Dynamics (CSD) and Computational Fluid Dynamics (CFD) methods. The application areas to be surveyed include fixed wing aircraft, turbomachinery, and rotary wing aircraft. The objective of the authors in the present paper, together with a companion paper on requirements, is to lay out a path for a High Performance Computing (HPC) based next generation comprehensive rotorcraft analysis. From this survey of the key technologies in other application areas it is possible to identify the critical technology gaps that stem from unique rotorcraft requirements.

Datta, Anubhav↗
DOE OSTI2016

High Resolution Model Development to Quantify the Impact of Icebergs on the Stability of the Atlantic Meridional Overturning Circulation

In the present-day North Atlantic Ocean, relatively warm and salty water moves northwards from the tropics to the high latitudes, sinks, and returns southward towards the equator as North Atlantic Deep Water, forming the so called Atlantic Meridional Overturning Circulation (AMOC). It has been found that the stability of the AMOC is non-linearly related to the freshwater budget of the North Atlantic. In this way, additional fresh water can be added to the ocean with little impact, until a tipping point is reached that causes the AMOC to suddenly weaken and the Northern Hemisphere to abruptly cool. A great deal of uncertainty still remains over the sensitivity of the AMOC to changes in freshwater discharge as a result of the unrealistic manner in which freshwater has historically been added to climate models. Frequently, freshwater is discharged in ocean models entirely as liquid water, but in reality a large fraction of freshwater entering the ocean is ice calving from marine glaciers (half for Antarctica and two-thirds for Greenland). To more accurately quantify AMOC sensitivity to past and future changes in freshwater input, this project developed a comprehensive iceberg model to more realistically simulate the interaction between the cryosphere and the oceans at high-latitudes. The iceberg model created is written in Fortran90 and designed to scale efficiently on High Performance Computing (HPC) clusters so that tens-of-thousands of icebergs can be simulated at any time. Experiments performed with our model showed that in the Pleistocene there would have been enormous floods of freshwater released into the North Atlantic that would have transported icebergs and meltwater along the entire east coast of the United States, as far south as Florida Keys. In addition, high-resolution, modern-day, model simulations showed that if the Greenland Ice Sheet continues to melt at its current rate then there will be a 6-fold increase in the number of icebergs drifting in the North Atlantic in the next 30 years, and that the strength of the AMOC could weaken by 3.5%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

$\mathrm{Perturbo}$: A software package for ab initio electron–phonon interactions, charge transport and ultrafast dynamics

We report Perturbo is a software package for first-principles calculations of charge transport and ultrafast carrier dynamics in materials. The current version focuses on electron–phonon interactions and can compute phonon-limited transport properties such as the conductivity, carrier mobility and Seebeck coefficient. It can also simulate the ultrafast nonequilibrium electron dynamics in the presence of electron–phonon scattering. Perturbo uses results from density functional theory and density functional perturbation theory calculations as input, and employs Wannier interpolation to reduce the computational cost. It supports norm-conserving and ultrasoft pseudopotentials, spin–orbit coupling, and polar electron–phonon interactions for bulk and 2D materials. Hybrid MPI plus OpenMP parallelization is implemented to enable efficient calculations on large systems (up to at least 50 atoms) using high-performance computing. Taken together, Perturbo provides efficient and broadly applicable ab initio tools to investigate electron–phonon interactions and carrier dynamics quantitatively in metals, semiconductors, insulators, and 2D materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

University of Washington/ Northwest National Marine Renewable Energy Center Tidal Current Technology Test Protocol, Instrumentation, Design Code, and Oceanographic Modeling Collaboration: Cooperative Research and Development Final Report, CRADA Number CRD-11-452

The University of Washington (UW) - Northwest National Marine Renewable Energy Center (UW-NNMREC) and the National Renewable Energy Laboratory (NREL) will collaborate to advance research and development (R&D) of Marine Hydrokinetic (MHK) renewable energy technology, specifically renewable energy captured from ocean tidal currents. UW-NNMREC is endeavoring to establish infrastructure, capabilities and tools to support in-water testing of marine energy technology. NREL is leveraging its experience and capabilities in field testing of wind systems to develop protocols and instrumentation to advance field testing of MHK systems. Under this work, UW-NNMREC and NREL will work together to develop a common instrumentation system and testing methodologies, standards and protocols. UW-NNMREC is also establishing simulation capabilities for MHK turbine and turbine arrays. NREL has extensive experience in wind turbine array modeling and is developing several computer based numerical simulation capabilities for MHK systems. Under this CRADA, UW-NNMREC and NREL will work together to augment single device and array modeling codes. As part of this effort UW NNMREC will also work with NREL to run simulations on NREL's high performance computer system.

16 TIDAL AND WAVE POWER↗
NASA NTRS2018

NASA Blazes a Different Path to Energy-Efficient Supercomputing

For years, NASA had a very straightforward process for replacing high-performance computing hardware: over a three-year period, when it became more expensive to operate an older suite of hardware than it did to replace it with new products that could accomplish the same work, we simply replaced the old hardware. For NASA’s High-End Computing Capability (HECC) Project, that process changed when we reached the limits of our facility’s power, cooling, and floor-loading capacity, becoming a strategy of decommissioning the least productive hardware and replacing it with more capable counterparts. The impact was that we provided our users with less supercomputing capability than we would have without the limitations. Additionally, with 25% of our total power consumption going to cool our systems and 50,000 gallons of water per day being evaporated, we wanted a solution that would expand our compute facility while being sensitive to the impact on our environment.

Thigpen, William↗
DOE OSTI2023

Simulation of Reverse Osmosis Membrane Compaction Using Material Point Method (MPM)

Access to fresh drinking water in the future requires effective management of industrial wastewater and water purification from available resources. In this study, we present the simulation methodology and the analysis of a Reverse Osmosis (RO) membrane under various pressure conditions using the Material Point Method (MPM). In contrast to other numerical methods, MPM solves the continuum governing equations on material points in a Lagrangian framework. The method does not require a grid connecting the material points hence making it suitable to simulate large deformations during membrane compaction. The time integration is carried out using the explicit Euler method, while the spatial discretization is performed using linear or cubic-spline shape functions. A series of planar images containing detailed pore structures obtained from X-ray tomography experiments is converted to a three-dimensional collection of material points to simulate the membrane. Compressive loads are applied to the top layer of the membrane to simulate the experiments. The membrane deformation and pore size distribution before and after load application are reported and compared with the experimental measurements. The presentation discusses the numerical methods used, the performance of the solver on high-performance computing machines, and the results of membrane compaction in detail.

ENGINEERING,MATHEMATICS AND COMPUTING↗