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At least 865 records · Page 48

All sources NASA NTRS DOE OSTI

DOE OSTI2022

An Advanced Meso-Scale Peridynamic Modeling Technology using High-Performance Computing for Cost-Effective Product Design and Testing of Carbon Fiber Reinforced Polymer Composites in Light-weight Vehicles

We study a peridynamic composite modeling technology based on the discontinuous Galerkin finite element method, implemented in the commercial LS-DYNA software, for modeling and prediction of failure in carbon fiber reinforced polymer composites. The proposed technology is developed for the material failure analysis at the meso-scale, which provides the prevailing fiber-matrix interaction mechanism, without adoption of the representative volume element method and thus avoiding complicated numerical calibration procedures. Three types of experimental tests—in-plane coupon test, out-of-plane coupon test, and a component crash test—are simulated in a high-performance computing environment to assess the performance of the proposed peridynamic composite modeling technology.

36 MATERIALS SCIENCE↗

DOE OSTI2022

High performance sparse multifrontal solvers on modern GPUs

Here, we have ported the numerical factorization and triangular solve phases of the sparse direct solver STRUMPACK to GPU. STRUMPACK implements sparse LU factorization using the multifrontal algorithm, which performs most of its operations in dense linear algebra operations on so-called frontal matrices of various sizes. Our GPU implementation off-loads these dense linear algebra operations, as well as the sparse scatter–gather operations between frontal matrices. For the larger frontal matrices, our GPU implementation relies on vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs and rocBLAS and rocSOLVER for AMD GPUs. For the smaller frontal matrices we developed custom CUDA and HIP kernels to reduce kernel launch overhead. Overall, high performance is achieved by identifying submatrix factorizations corresponding to sub-trees of the multifrontal assembly tree which fit entirely in GPU memory. The multi-GPU setting uses SLATE (Software for Linear Algebra Targeting Exascale) as a modern GPU-aware replacement for ScaLAPACK. On 4 nodes of SUMMIT the code runs ~10X faster when using all 24 V100 GPUs compared to when it only uses the 168 POWER9 cores. On 8 SUMMIT nodes, using 48 V100 GPUs, the sparse solver reaches over 50TFlop/s. Compared to SuperLU, on a single V100, for a set of 17 matrices our implementation is faster for all but one matrix, and is on average 5X (median 4X) faster

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2004

Development of an Experiment High Performance Nozzle Research Program

As proposed in the above OAI/NASA Glenn Research Center (GRC) Co-Operative Agreement the objective of the work was to provide consultation and assistance to the NASA GRC GTX Rocket Based Combined Cycle (RBCC) Program Team in planning and developing requirements, scale model concepts, and plans for an experimental nozzle research program. The GTX was one of the launch vehicle concepts being studied as a possible future replacement for the aging NASA Space Shuttle, and was one RBCC element in the ongoing NASA Access to Space R&D Program (Reference 1). The ultimate program objective was the development of an appropriate experimental research program to evaluate and validate proposed nozzle concepts, and thereby result in the optimization of a high performance nozzle for the GTX launch vehicle. Included in this task were the identification of appropriate existing test facilities, development of requirements for new non-existent test rigs and fixtures, develop scale nozzle model concepts, and propose corresponding test plans. Also included were the evaluation of originally proposed and alternate nozzle designs (in-house and contractor), evaluation of Computational Fluid Dynamics (CFD) study results, and make recommendations for geometric changes to result in improved nozzle thrust coefficient performance (Cfg).

Source record↗

DOE OSTI2025

US Department of Energy, Office of Science, High-Performance Computing Facility 2024 Operational Assessment Oak Ridge Leadership Computing Facility

The Oak Ridge Leadership Computing Facility (OLCF) was established to accelerate scientific discovery by providing world-leading computational performance and advanced data infrastructure to the US Department of Energy (DOE) computing community. As a DOE Office of Science user facility, the OLCF has managed the successful deployment and operation of a succession of leadership-class resources dedicated to open science. In addition to these resources, the OLCF staff continually strive to develop innovative processes and technologies, improve security, and empower users through effective allocation management and comprehensive user support and training. These efforts support the advancement of science by the OLCF users and benefit high-performance computing (HPC) facilities around the world.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Full Scale HEPA Filter Encapsulation in Ultra-High-Performance Grout - Proof of Concept

The Hanford Tank Waste Treatment and Immobilization Plant (WTP) currently being constructed to treat radioactive waste, includes vitrification facilities for both the high-level waste (HLW) and low activity waste (LAW) fractions. Operation of the WTP will produce contaminated high-efficiency particulate air filters (HEPA), as part of the solid secondary waste (SSW) stream. The HEPA filters receive off-gas from the vessel vent header and primary off-gas treatment system in LAW Facility and remove particulate contaminants including 99 Tc and 129 I salts. The current disposal method for HEPA filters is encapsulation in metal containers using cementitious material (CM) and disposal in the Integrated Disposal Facility (IDF). Results from the 2017 IDF Performance Assessment (PA) WRPS (2018) demonstrated that while compliance is maintained for the 1000 year compliance period mandated by DOE O 435.1 and its accompanying manual, release of constituents from the HEPA filters result in exceedance of the performance objective imposed as the groundwater regulatory limit at later times. For example, at about 1500 years post-closure, solid secondary waste (SSW), including HEPA filters is predicted to become a dominant contributor to 99 Tc release and over the 10,000-year sensitivity analysis period, SSW is the dominant contributor of 129 I release to the groundwater. The estimated release could potentially be reduced if the HEPA filters are not compacted and waste containers could be distributed throughout a large space, thereby diluting the contaminant release. Additionally, a better cementitious material could be used to encapsulate the HEPA filters. One alternative method for disposal of contaminated HEPA filters is encapsulation of the filters in ultra high-performance grout (UHPG). UHPG is a variation of ultra-high-performance concrete (UHPC) is commonly used in the prestressed concrete industry for large structural members. Recent studies of UHPG show it has excellent properties for containing radionuclides such as 99 Tc and 129 I Nichols and Kaplan (2021). This report presents the results of the first attempt to encapsulate a clean, full-size HEPA filter in UHPG and evaluate the effectiveness of the immobilization process and final waste form. A full-scale proof-of-concept simulated waste form was prepared by encapsulating a HEPA filter in a 110-gallon stainless steel (SS) drum using UHPG. A change from Type I/II PC to Type 1L PLC was made after American Rock Products informed the team that they would no longer be using Type I/II by the end of 2024 and the northwest was phasing out Type I/II PC overall. Type I/II PC used in previous studies of UHPG for encapsulation (Nichols and Kaplan 2021). After the UHPG was cured both the scaled mockup and the full-scale simulated waste forms were sectioned for visual examination. UHPG completely encapsulated the filters and bonded to the external surfaces of materials comprising the filters. No cracks were observed in the sectioned waste forms.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1997

Advanced Algorithms and High-Performance Testbed for Large-Scale Site Characterization and Subsurface Target Detecting Using Airborne Ground Penetrating SAR

A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.

Fijany, Amir↗

NASA NTRS1996

Lateral-Directional Eigenvector Flying Qualities Guidelines for High Performance Aircraft

This report presents the development of lateral-directional flying qualities guidelines with application to eigenspace (eigenstructure) assignment methods. These guidelines will assist designers in choosing eigenvectors to achieve desired closed-loop flying qualities or performing trade-offs between flying qualities and other important design requirements, such as achieving realizable gain magnitudes or desired system robustness. This has been accomplished by developing relationships between the system's eigenvectors and the roll rate and sideslip transfer functions. Using these relationships, along with constraints imposed by system dynamics, key eigenvector elements are identified and guidelines for choosing values of these elements to yield desirable flying qualities have been developed. Two guidelines are developed - one for low roll-to-sideslip ratio and one for moderate-to-high roll-to-sideslip ratio. These flying qualities guidelines are based upon the Military Standard lateral-directional coupling criteria for high performance aircraft - the roll rate oscillation criteria and the sideslip excursion criteria. Example guidelines are generated for a moderate-to-large, an intermediate, and low value of roll-to-sideslip ratio.

Davidson, John B.↗

DOE OSTI2020

Elucidating the differences in oxidation of high-performance α- and β- diisobutylene biofuels via Synchrotron photoionization mass spectrometry

Abstract Biofuels are a promising ecologically viable and renewable alternative to petroleum fuels, with the potential to reduce net greenhouse gas emissions. However, biomass sourced fuels are often produced as blends of hydrocarbons and their oxygenates. Such blending complicates the implementation of these fuels in combustion applications. Variations in a biofuel’s composition will dictate combustion properties such as auto ignition temperature, reaction delay time, and reaction pathways. A handful of novel drop-in replacement biofuels for conventional transportation fuels have recently been down selected from a list of over 10,000 potential candidates as part of the U.S. Department of Energy’s (DOE) Co-Optimization of Fuels and Engines (Co-Optima) initiative. Diisobutylene (DIB) is one such high-performing hydrocarbon which can readily be produced from the dehydration and dimerization of isobutanol, produced from the fermentation of biomass-derived sugars. The two most common isomers realized, from this process, are 2,4,4-trimethyl-1-pentene (α-DIB) and 2,4,4-trimethyl-2-pentene (β-DIB). Due to a difference in olefinic bond location, the α- and β- isomer exhibit dramatically different ignition temperatures at constant pressure and equivalence ratio. This may be attributed to different fragmentation pathways enabled by allylic versus vinylic carbons. For optimal implementation of these biofuel candidates, explicit identification of the intermediates formed during the combustion of each of the isomers is needed. To investigate the combustion pathways of these molecules, tunable vacuum ultraviolet (VUV) light (in the range 8.1–11.0 eV) available at the Lawrence Berkeley National Laboratory’s Advanced Light Source (ALS) has been used in conjunction with a jet stirred reactor (JSR) and time-of-flight mass spectrometry to probe intermediates formed. Relative intensity curves for intermediate mass fragments produced during this process were obtained. Several important unique intermediates were identified at the lowest observable combustion temperature with static pressure of 93,325 Pa and for 1.5 s residence time. As this relatively short residence time is just after ignition, this study is targeted at the fuels’ ignition events. Ignition characteristics for both isomers were found to be strongly dependent on the kinetics of C 4 and C 7 fragment production and decomposition, with the tert-butyl radical as a key intermediate species. However, the ignition of α-DIB exhibited larger concentrations of C 4 compounds over C 7 , while the reverse was true for β-DIB. These identified species will allow for enhanced engineering modeling of fuel blending and engine design.

09 BIOMASS FUELS↗

DOE OSTI2021

High Performance PEFC Electrode Structures

Raytheon Technologies Research Center (RTRC) in collaboration with Ion Power Inc. and the University of Arkansas at Little Rock and the FC-PAD consortium executed a project that: (1) developed comprehensive models of oxygen and proton transport in cathode catalyst layers that provided new insights about losses associated with reducing platinum loading to 0.1 mg/cm 2 , (2) designed, fabricated, characterized, and tested cells featuring carbon-supported catalyst layers with low platinum loadings that met efficiency and power density targets set forth by the Hydrogen and Fuel Cells Technology Office, and (3) designed, fabricated, characterized, and tested novel catalyst structures. The modeling efforts produced eight scientific publications that shared new descriptions of oxygen and proton transport in catalyst layers with the broader technical community. The key physical insights from the models are expressed in straightforward algebraic expressions, facilitating easy adoption by other researchers. The models developed during the project explain why resistance to oxygen transport is inversely proportional to interfacial area of platinum – an observation that eluded quantitative explanation for a decade. The models quantitatively predict polarization when measured morphological parameters and transport properties are input. Membrane-electrode assemblies made during the project met stated goals for current at high voltage and power density at rated voltage for transportation fuel cells at the end of budget period 2. High performance was achieved by developing a diffusion layer with low resistance to oxygen transport and a PtCo/C cathode catalyst layer capable of supporting rapid proton and oxygen transport. The project was subsequently directed to curtail experimental work and focus on modeling during budget period 3. Ion Power Inc. developed new expertise in fabricating catalyst layers containing platinum-cobalt catalysts, and processing very thin membranes. The University of Arkansas at Little Rock developed novel nanocolumnar self-supported thin film electrocatalysts that can be grown on carbon supports using a simple high pressure sputter deposition method. The nanocolumnar microstructure provides adequate surface-to-volume ratio for efficient platinum utilization, and the conformal platinum shell with larger crystal grain sizes covering the carbon support surface may eliminate durability issues associated with catalyst dissolution, agglomeration, and carbon corrosion.

08 HYDROGEN↗

NASA NTRS2013

Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing

Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and mission. Onboard computing can be aptly viewed as a "technology multiplier" in that advances provide direct dramatic improvements in flight functions and capabilities across the NASA mission classes, and enable new flight capabilities and mission scenarios, increasing science and exploration return. Space-qualified computing technology, however, has not advanced significantly in well over ten years and the current state of the practice fails to meet the near- to mid-term needs of NASA missions. Recognizing this gap, the NASA Game Changing Development Program (GCDP), under the auspices of the NASA Space Technology Mission Directorate, commissioned a study on space-based computing needs, looking out 15-20 years. The study resulted in a recommendation to pursue high-performance spaceflight computing (HPSC) for next-generation missions, and a decision to partner with the Air Force Research Lab (AFRL) in this development.

use cases↗

DOE OSTI2025

Classical Preoptimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. Furthermore, by preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

ADAPT-VQE↗

DOE OSTI2025

HPDR: High-Performance Portable Scientific Data Reduction Framework

The rapid growth in scientific data generation is outpacing advancements in computing systems necessary for efficient storage, transfer, and analysis, particularly in the context of exascale computing. With the deployment of first-generation exascale computing systems and next-generation experimental facilities, this gap is widening and necessitates effective data reduction techniques to manage enormous data volumes. Over the past decade, various data reduction methods, including lossless compression, error-controlled lossy compression, and data refactoring, have been developed to accelerate I/O in scientific workflows. Despite significant reductions in data volume, these methods introduce considerable computational overhead, which can become the new bottleneck in data processing. To mitigate this, GPU-accelerated data reduction algorithms have been introduced. However, challenges remain in their integration into exascale workflows, including limited portability across different GPU architectures, substantial memory transfer overhead, and reduced scalability on dense multi-GPU systems. To address these challenges, we propose HPDR, a high-performance and portable data reduction framework. HPDR is designed to enable the execution of state-of-the-art reduction algorithms across diverse processor architectures while reducing memory transfer overhead to 2.3 % of the original, resulting in up to 3.5× faster throughput compared to existing solutions. It also achieves up to 96% of the theoretical speedup in multi-GPU settings. In addition, evaluations on accelerating I/O operations at scale up to 1,024 nodes of the Frontier supercomputer demonstrate that HPDR can achieve up to 103 TB/s reduction throughput, providing up to 4× acceleration in parallel I/O performance compared to existing data reduction routines. This work highlights the potential of HPDR to significantly enhance data reduction efficiency in exascale computing environments.

Chen, Jieyang [University of Oregon]↗

DOE OSTI2020

Nonfused Nonfullerene Acceptors with an A–D–A'–D–A Framework and a Benzothiadiazole Core for High-Performance Organic Solar Cells

Nonfullerene acceptors (NFAs) have contributed significantly to the progress of organic solar cells (OSCs). However, most NFAs feature a large fused-ring backbone, which usually requires a tedious multiple-step synthesis, and are not applicable to commercial applications. An alternative strategy is to develop nonfused NFAs, which possess synthetic simplicity and facile tunability in optoelectronic properties and solid-state microstructures. In this work, we report two nonfused NFAs, BTCIC and BTCIC-4Cl, based on an A-D-A'-D-A architecture, which possess the same electron-deficient benzothiadiazole central core but different electron-withdrawing terminal groups. The optical properties, energy levels, and molecular crystallinities were finely tuned by changing the terminal groups. Moreover, a decent power conversion efficiency of 9.3 and 10.5% has been achieved by BTCIC and BTCIC-4Cl, respectively, by blending them with an appropriate polymer donor. These results demonstrate the potential of A-D-A'-D-A type nonfused NFAs for high-performance OSCs. Further development of nonfused NFAs will be very fruitful by employing appropriate building blocks and via side-chain optimizations.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗

NASA NTRS2001

Multidisciplinary Design Optimization of a Full Vehicle with High Performance Computing

Multidisciplinary design optimization (MDO) of a full vehicle under the constraints of crashworthiness, NVH (Noise, Vibration and Harshness), durability, and other performance attributes is one of the imperative goals for automotive industry. However, it is often infeasible due to the lack of computational resources, robust simulation capabilities, and efficient optimization methodologies. This paper intends to move closer towards that goal by using parallel computers for the intensive computation and combining different approximations for dissimilar analyses in the MDO process. The MDO process presented in this paper is an extension of the previous work reported by Sobieski et al. In addition to the roof crush, two full vehicle crash modes are added: full frontal impact and 50% frontal offset crash. Instead of using an adaptive polynomial response surface method, this paper employs a DOE/RSM method for exploring the design space and constructing highly nonlinear crash functions. Two NMO strategies are used and results are compared. This paper demonstrates that with high performance computing, a conventionally intractable real world full vehicle multidisciplinary optimization problem considering all performance attributes with large number of design variables become feasible.

Yang, R. J.↗

DOE OSTI2022

High-Performance Non-fullerene organic solar cells enabled by noncovalent Conformational locks and Side-Chain engineering

Three novel small molecular acceptors (SMAs) BO-2F, BO-C8-2F and BO-C2C6-C8-2F were designed and synthesized. These acceptors all possess planar molecular backbone because of the introduction of intramolecular noncovalent interaction. Among them, BO-C2C6-C8-2F with four side chains, which has the highest solubility, can form more appropriate nanomorphology when blending with PBDB-T. Hence, organic solar cells (OSCs) based on PBDB-T:BO-C2C6-C8-2F displayed an outstanding power convesion efficiency (PCE) of 14.25%, which is higher than BO-2F and BO-C8-2F based ones. To the best of our knowledge, the PCE of 14.25% is one of the highest for the OSCs based on A-π-D-π-A type SMAs. Finally, our results have demonstrated that the combination of side-chain engineering and intramolecular conformation lock has a great prospect in the design of high performance SMAs for OSCs.

14 SOLAR ENERGY↗

DOE OSTI2021

Organic Solvent Free Process to Fabricate High Performance Silicon/Graphite Composite Anode

Cycling stability is a key challenge for application of silicon (Si)-based composite anodes as the severe volume fluctuation of Si readily leads to fast capacity fading. The binder is a crucial component of the composite electrodes. Although only occupying a small amount of the total composite mass, the binder has major impact on the long-term electrochemical performance of Si-based anodes. In recent years, water-based binders including styrene-butadiene rubber (SBR) and carboxymethyl cellulose (CMC) have attracted wide research interest as eco-friendly and low-cost alternatives for the conventional poly(vinylidene difluoride) (PVDF) binder in Si anodes. In this study, Si-based composite anodes are fabricated by simple solid mixing of the active materials with subsequent addition of SBR and CMC binders. This approach bypasses the use of toxic and expansive organic solvents. The factors of binder, silicon, and graphite materials have been systematically investigated. It is found that the retained capacities of the anodes are more than 440 mAh/g after 400 cycles. These results indicate that organic solvent free process is a facile strategy for producing high performance silicon/graphite composite anodes.

Fang, Chen (ORCID:0000000321011991)↗

DOE OSTI2025

Dual-function lignin monomers enable high-performance graphene electrodes via interface confinement and proton transfer enhancement

Graphene oxide (GO)-based energy storage faces dual bottlenecks: unsustainable reduction methods and sluggish proton transfer kinetics. Here, we introduce a groundbreaking green strategy using lignin-derived vanillyl alcohol (VA) as a dual-function monomer to simultaneously address these challenges. By thermally annealing GO/VA films at mild temperatures (<100 °C), VA triggers an interface-confined reduction of GO while self-polymerizing into redox-active oligomers (P-VA) that intercalate between graphene layers. This dual role-reducing agent and proton highway enables a 3D conductive network with minimized graphene restacking, abundant redox sites, and rapid H + transport pathways. Density Functional Theory (DFT) reveals how P-VA optimizes proton dynamics, while the resulting rGO-P-VA4-T90 electrode achieves a record volumetric capacitance of 311.1F/cm 3 (777.8F/cm 2 ) and retains 87.8 % capacity after 10,000 cycles. Flexible solid-state supercapacitors deliver 94.2 μWh/cm 2 energy density at 63.8 μW/cm 2 , rivaling state-of-the-art devices. Furthermore, this work redefines sustainable graphene engineering, merging biomass valorization with high-performance energy storage in a scalable, eco-friendly paradigm.

Graphene oxide reduction↗