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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Utah FORGE: High-Resolution DAS Microseismic Data from Well 78-32

This regards a high-resolution DAS microseismic dataset produced by Silixa from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. It is a very large dataset and as such it is currently not directly available on GDR. However, it is available for download from the Center for High Performance Computing (CHPC) at the University of Utah using the shell script below. Additional survey information and tips for running the script are available in the attached downloadable Word Document file.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Smoothers for Matrix-Free Algebraic Multigrid Preconditioning of High-Order Finite Elements

We investigate smoothers for use in matrix-free algebraic multigrid (AMG) preconditioning of high-order finite element problems. These AMG preconditioners are matrix-free in the sense that they are built from a related low-order refined finite element problem whose system matrix can be much more rapidly assembled than the high-order problem. Our proposed smoother, which we call distributive relaxation, is more robust to the anisotropy present in many low-order refined meshes which feature a clustering of nodes near the boundaries between high-order finite elements. For solving the low-order refined problem, we show that this new distributive relaxation smoother possesses significantly improved performance compared to more traditional smoothers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

PyDREAM: high-dimensional parameter inference for biological models in python

Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis [DREAM(ZS)] algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012). PyDREAM achieves excellent performance for complex, parameter-rich models and takes full advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPU-intensive biological models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Manufacturability and performance response of developed Ni-based alloys for reactor environments

Under the Advanced Materials and Manufacturing Technologies program, two Ni-based alloys fabricated by laser powder bed fusion (LPBF) at ORNL and laser powder directed energy deposition (LP-DED) at INL have been evaluated: γ′-strengthened Haynes 282 and solution-strengthened Inconel 625. Printing defects were observed in the LPBF 282 alloy fabricated using a Renishaw AM250 machine, likely due to particle spattering during printing. For both the LPBF and LP-DED 282 alloys, annealing at 1,180°C for 1 h resulted in partial recrystallization and a bimodal grain distribution, while subsequent aging for 4 h at 800°C led to the formation of a high density of nano size γ′-strengthening precipitates. Creep testing performed at 750°C revealed lower creep life and ductility for the LPBF and LP-DED 282 compared with wrought 282. X-ray computed tomography combined with optical and scanning electron microscopy microstructural characterization revealed crack formation in the LPBF 282 alloy during creep testing, initiated either from printing defects or from creep cavitation at grain boundaries. Creep cavitation and cracking at grain boundaries were also observed for the LP-DED 282 alloy, and optimization of the printing strategies and post heat treatments will be needed to fabricate high performance 282 components for high temperature nuclear applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1981

Spacecraft contamination prediction and testing techniques

Techniques used in the prediction of spacecraft contamination for the Galileo Jupiter Orbiter and in the determination of the effects of such contamination are presented. Following a quick-look assessment of the contributions of ground-based initial contaminant loading, launch vehicle interface effects, vacuum-exposed outgassing deposition and attitude control thruster impingement and venting to the spacecraft contamination burden, the evaluations centered on the effects of the attitude control thruster on the scan platform optics, including calculations of thruster flowfields and a high-fidelity computer simulation of contaminant distribution. The evaluations revealed a considerable problem with thruster contamination, which could be solved by the use of a thrust shield and the avoidance of thruster operation at certain scan platform orientations. The effects of the various possible contaminants on spacecraft thermal and optical system performances were also investigated in studies of the optical transmittance of deposited monomethyl hydrazine nitrate, vacuum optical degradation due to contaminant outgassing and re-emission outgassing, and an operational satellite contaminant monitor on the NOAA-C satellite. It is concluded that with a good evaluation and testing program, contamination control may become a necessary portion of system design procedures, and recommendations for the implementation of various practices and tests to minimize contamination effects are presented.

Jeffery, J. A.↗
NASA NTRS1991

Navier-Stokes calculation of transonic flow past the NTF 65 deg delta wing

Models of four delta wings were built and tested in the 8 x 8 ft Transonic Wind Tunnel at LaRC. The wings are identical in planform shape with a swept-back angle of 65 degrees, but bear different leading edge profiles. The models were tested under pressurized and cryogenic conditions to simulate true flight Reynolds numbers. Data on the aerodynamic forces and pressure distributions at various locations on the wings were taken at various flight Mach numbers and angles of attack. Effects of high Reynolds number and leading edge radius on the aerodynamic characteristics of the wings are being accessed. To thoroughly understand the turbulent, vortical flow around the wings, an effort to perform computational aerodynamic analysis is being made. The objective of the analysis is to supplement and validate the experimental data and explain the high Reynolds number and leading edge effects. GRIDGEN, a software developed by General Dynamics, is being used to generate the grid topology for the flow field around the wings. The flow solver to be used is CFL3D, a computation fluid dynamics code developed at LaRC. Based on the geometric description of the wings, a FORTRAN program called WINGSURF was written to generate the databases defining the surface geometry of the wings. To match the true geometry of the models in the wind tunnel for realistic comparison with experimental results, databases defining the sting support for the wing models were also created by two other FORTRAN programs, STINJOIN and STINREAR. Listing of the programs are attached and the geometry of a typical wing model with the sting support is shown. Other aspects of the investigation are discussed.

Wu, Chivey C.↗
NASA NTRS1991

An improved distributed arithmetic architecture

Speed requirements have been, and will continue to be, a major consideration in the design of hardware to implement digital signal processing functions like digital filters and transforms like the DFT and DCT. The conventional approach is to increase speed by adding hardware and increasing chip area. The real challenge is to save chip area while still maintaining high speed performance. The approach we propose is based on the distributed arithmetic implementation (DA) of digital filters. The improvement is based on two observations. Firstly, a single memory element can replace several identical memory elements in a fully parallel DA implementation. Secondly, truncation or rounding may be introduced into the computation at strategic points without increasing error unduly. Both of these approaches can be used to attain area savings without impairing speed of operation.

Guo, X.↗
NASA NTRS1998

Three-Dimensional High-Lift Analysis Using a Parallel Unstructured Multigrid Solver

A directional implicit unstructured agglomeration multigrid solver is ported to shared and distributed memory massively parallel machines using the explicit domain-decomposition and message-passing approach. Because the algorithm operates on local implicit lines in the unstructured mesh, special care is required in partitioning the problem for parallel computing. A weighted partitioning strategy is described which avoids breaking the implicit lines across processor boundaries, while incurring minimal additional communication overhead. Good scalability is demonstrated on a 128 processor SGI Origin 2000 machine and on a 512 processor CRAY T3E machine for reasonably fine grids. The feasibility of performing large-scale unstructured grid calculations with the parallel multigrid algorithm is demonstrated by computing the flow over a partial-span flap wing high-lift geometry on a highly resolved grid of 13.5 million points in approximately 4 hours of wall clock time on the CRAY T3E.

Mavriplis, Dimitri J.↗
DOE OSTI2021

Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of generated data introduces additional constraints on the data layout strategies that can be used when writing data to secondary storage. We review these I/O challenges and introduce two online data layout reorganization approaches for achieving good tradeoffs between read and write performance. We demonstrate the benefits of using these two approaches for the ECP particle-in-cell simulation WarpX, which serves as a motif for a large class of important Exascale applications. Here, we show that by understanding application I/O patterns and carefully designing data layouts we can increase read performance by more than 80 percent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

miniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems

Benchmarking of high performance computing sys-tems can help provide critical insights for ef?cient design of computing systems and software applications. Although a large number of tools for benchmarking exist, there is a lack of rep-resentative benchmarks for the class of irregular computations as exempli?ed by graph analytics. In this paper, we propose miniVite as a representative graph analytics benchmark tool to test a variety of distributed-memory systems. Graph clustering, popularly known as community detection, is a prototypical graph operation used in numerous scienti?c computing and analytics applications. The goal of clustering is to partition a graph into clusters (or communities) such that each cluster consists of vertices that are densely connected within the cluster and sparsely connected to the rest of the graph. Modu-larity optimization is a popular technique for identifying clusters in a graph. Ef?cient parallelization of modularity optimization-based algorithms is challenging. One successful approach was conceived in Vite, a distributed-memory implementation of the Louvain algorithm that incorporates several heuristics. We introduce miniVite as a representative but simpli?ed variant of Vite, to serve as a prototypical graph analytics benchmarking tool. Unlike other graph-based methods such as breadth-?rst search and betweenness centrality, miniVite represents highly complex computational patterns stressing a variety of system features, which can provide crucial insight for co-design of future computing systems.

community detection, parallel, MPI↗
DOE OSTI2025

An Interfacial Engineering Approach toward Operation of a Porous Solid Electrolyte CO 2 Electrolyzer

Waste CO 2 can be repurposed as a carbon feedstock for synthesizing valuable chemicals via CO 2 electrolysis. Porous solid electrolyte (PSE) CO 2 electrolysis has been demonstrated as an economically viable method to produce high purity products. This work applies an interfacial engineering approach to determine key factors to improve performance in PSE CO 2 electrolyzers. We standardize the assembly by binding the ionic resin into an ionomer wafer and utilize Computational Fluid Dynamics (CFD) to design gaskets for uniform fluid flow. Here, we employ the distribution of relaxation times (DRT) method to determine that anionic-conducting interfaces are the primary contributor to energy losses. To address this, we demonstrate that enhancing the contact between the cathode and the anion exchange membrane (AEM) and the AEM-ionic resin interface allows for low overpotential in deionized water operation.

09 BIOMASS FUELS↗
DOE OSTI2019

Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

Big data has a potential to unlock novel groundbreaking opportunities in the power grid sector that enhances a multitude of technical, social, and economic gains. The currently untapped potential of applying the science of big data for better planning and operation of the power grid is a very challenging task and needs significant efforts all-around. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data sets from diverse sources. In particular, computational complexity, data security, and operational integration of big data into utility decision frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. Moreover, due to the complex nature of power grids along with the need to balance power in real time, seamless integration of big data into utility operations is very critical. In this context, big data analytics combined with grid visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into electric utility decision framework. Detailed information for utilities looking to apply big data analytics and details insights on how utilities can enhance revenue streams and bring disruptive innovation in the industry are discussed. More importantly, general guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.

13 HYDRO ENERGY↗
DOE OSTI2025

Biased degenerate ground-state sampling of small Ising models with converged quantum approximate optimization algorithm

The quantum alternating operator ansatz, a generalization of the quantum approximate optimization algorithm (QAOA), is a quantum algorithm used for approximately solving combinatorial optimization problems. QAOA typically uses the transverse field mixer as the driving Hamiltonian. One of the interesting properties of the transverse field driving Hamiltonian is that it results in nonuniform sampling of degenerate ground states of optimization problems. In this study, we numerically examine the fair sampling properties of the transverse field mixer QAOA, and Grover mixer QAOA (GM-QAOA), which provides theoretical guarantees of fair sampling of degenerate optimal solutions, up to a large enough p such that the mean expectation value converges to an optimal approximation ratio of 1. This comparison is performed with high-quality heuristically computed, but not necessarily optimal, QAOA angles, which give strictly monotonically improving solution quality as p increases. These angles are computed using the Julia based numerical simulation software JuliQAOA. Fair sampling of degenerate ground states is quantified using the Shannon entropy of the ground-state amplitudes distribution. The fair sampling properties are reported on several quantum signature Hamiltonians from previous quantum annealing fair sampling studies. Small random fully connected spin glasses are shown, which exhibit exponential suppression of some degenerate ground states with transverse field mixer QAOA. The transverse field mixer QAOA simulations show that some problem instances clearly saturate the Shannon entropy of 0 with a maximally biased distribution that occurs when the learning converges to an approximation ratio of 1 while other problem instances never deviate from a maximum Shannon entropy (uniform distribution) at any p step. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Aces4: A Platform for Computational Chemistry Calculations with Extremely Large Block-Sparse Arrays

Aces4 is a parallel programming platform comprising a DSL for Computational Chemistry and its runtime system. It offers a convenient way to express parallelism together with extensive support for extremely large, possibly sparse, distributed arrays. It aids scientists in the creation of performant, scalable, massively parallel programs that can effectively take advantage of leadership class computing systems to address important scientific questions. Aces4 has enabled the development and implementation of new methods in electronic structure theory which are breaking new ground in their ability to perform highly accurate calculations on ever larger molecular systems. In this paper the design of Aces4, which is based on the the Super Instruction Architecture approach, is described. Experimental scaling results for Molecular Cluster Perturbation Theory, a new method enabled by Aces4, and CCSD, a widely used computational chemistry method are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A GPU-based compressible combustion solver for applications exhibiting disparate space and time scales

High-speed chemically active flows pose significant computational challenges due to their disparate space and time scales, with stiff chemistry often dominating simulation time. While modern scientific computing programs achieve exascale performance by leveraging graphics processing units (GPUs), existing GPU-based compressible combustion solvers face critical limitations in memory management, load balancing, and handling the highly localized nature of chemical reactions. To this end, we present a high-performance compressible reacting flow solver built on the AMReX framework and optimized for multi-GPU settings. Here, our approach addresses three GPU performance bottlenecks: memory access patterns through column-major storage optimization, computational workload variability via a bulk-sparse integration strategy for chemical kinetics, and multi-GPU load distribution for adaptive mesh refinement applications. The solver adapts existing matrix-based chemical kinetics formulations to multi-grid contexts. Using representative combustion applications, including 2D and 3D detonations and a 3D jet-in-crossflow configuration, we demonstrate 1.4–5× performance improvements over initial implementations on an in-house cluster of NVIDIA H100 GPUs, and near-ideal weak scaling on the Frontier supercomputer (Oak Ridge Leadership Computing Facility) with up to 1024 AMD Instinct MI250X GPUs. Roofline analysis reveals substantial improvements in arithmetic intensity for both convection (∼ 10 ×) and chemistry (∼ 4 ×) routines, confirming efficient utilization of GPU memory bandwidth and computational resources.

42 ENGINEERING↗
DOE OSTI2021

Water-Oil Displacement in Shale: New Insights from a Comparative Study Integrating Imbibition Tests and Multiscale Imaging

Water-oil displacement is an important process that occurs in a shale matrix after hydraulic fracturing and in water-based enhanced oil recovery. Current understanding of this displacement process is limited because of the complicated pore structure and surface properties in shale. In this work, this process and its controlling factors are investigated through a comparative study of three shale samples that have different types of pore systems and wettability. Here, an integrated method of imbibition and multiscale imaging was applied, and a modified oleic tracer that can better represent oil flow was used in imbibition testing and micro-computed tomography (CT) imaging. Scanning electron microscope (SEM) pore characterization was then performed under high magnification with guidance from the micro-CT images showing the changes caused by oil or water imbibition. New insights were obtained on the importance of both wettability and pore size effect on oil recovery and the distribution of residual oil after water-oil displacement. Connectivity of pores with different wettability is also discussed based on 3D analysis and SEM pore characterization. Collectively, these new findings improve the understanding of the complicated process of water-oil displacement and the role of influencing factors. Important implications for improved oil recovery strategy in shale are discussed for different types of reservoir rocks. The integrated imaging and imbibition technique provides a new path for further investigation of improved oil recovery in shale.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2025

Manufacturability and performance response of developed Ni-based alloys for reactor environments

Under the Advanced Materials and Manufacturing Technologies program, two Ni-based alloys fabricated by laser powder bed fusion (LPBF) at Oak Ridge National Laboratory and by laser powder directed energy deposition (LP-DED) at Idaho National Laboratory have been evaluated: γ′-strengthened Haynes 282 and solution-strengthened Inconel 625. Printing defects were observed in the LPBF 282 alloy fabricated using a Renishaw AM250 machine, likely due to particle spattering during printing. For both the LPBF and LP-DED 282 alloys, annealing at 1,180°C for 1 h resulted in partial recrystallization and a bimodal grain distribution, and subsequent aging for 4 h at 800°C led to the formation of a high density of nano-size γ′-strengthening precipitates. Creep testing performed at 750°C revealed lower creep life and ductility for the LPBF and LP-DED 282 compared with wrought 282. X-ray computed tomography combined with optical and scanning electron microscopy microstructural characterization revealed crack formation in the LPBF 282 alloy during creep testing, initiated either from printing defects or from creep cavitation at grain boundaries. Creep cavitation and cracking at grain boundaries were also observed for the LP-DED 282 alloy, and optimization of the printing strategies and postheat treatments will be needed to fabricate high-performance 282 components for high-temperature nuclear applications.

36 MATERIALS SCIENCE↗
NASA NTRS2000

ICEG2D: An Integrated Software Package for Automated Prediction of Flow Fields for Single-Element Airfoils with Ice Accretion

An integrated software package, ICEG2D, was developed to automate computational fluid dynamics (CFD) simulations for single-element airfoils with ice accretion. ICEG2D is designed to automatically perform three primary functions: (1) generating a grid-ready, surface definition based on the geometrical characteristics of the iced airfoil surface, (2) generating a high-quality grid using the generated surface point distribution, and (3) generating the input and restart files needed to run the general purpose CFD solver NPARC. ICEG2D can be executed in batch mode using a script file or in an interactive mode by entering directives from a command line. This report summarizes activities completed in the first year of a three-year research and development program to address issues related to CFD simulations for aircraft components with ice accretion. Specifically, this document describes the technology employed in the software, the installation procedure, and a description of the operation of the software package. Validation of the geometry and grid generation modules of ICEG2D is also discussed.

Thompson, David S.↗