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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Denoising Convolutional Networks to Accelerate Detector Simulation [Poster]

The high accuracy of detector simulation is crucial for modern particle physics experiments. However, this accuracy comes with a high computational cost, which will be exacerbated by the large datasets and complex detector upgrades associated with next-generation facilities such as the High Luminosity LHC. We explore the viability of regression-based machine learning (ML) approaches using convolutional neural networks (CNN) to ``denoise'' faster, lower-quality detector simulations, augmenting them to produce a higher-quality final result with a reduced computational burden. The denoising CNN works in concert with classical detector simulation software rather than replacing it entirely, increasing its reliability compared to other ML approaches to simulation. We obtain promising results from a prototype based on photon showers in the CMS electromagnetic calorimeter. Future directions are also discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Applying the ATOM drug discovery platform to small-molecule antivirals (Annual Report)

The objective of this project is to advance our understanding of the ML approaches needed to find the most potent inhibitor through an AI guided search that simultaneously optimizes for limited off-target safety activity and desirable pharmacokinetics (PK) properties. The methods will be tested for inhibiting SARS-CoV-2 activity through inhibition of the main protease as a demonstration, but the methodology will be developed to apply to any biothreat target using a small-molecule protein binding-based intervention, with limited experimental data. Computational experiments are conducted using our ATOM generative molecular design (GMD) loop software, which is the implementation of our AI/ML drug design pipeline.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

National Smart Manufacturing Strategic Plan: To Facilitate More Rapid Development, Deployment and Adoption of Smart Manufacturing Technologies

Smart manufacturing technologies provide real-time data and insight to improve the productivity, efficiency, and competitiveness of U.S. manufacturing, creating the potential for new jobs in the manufacturing sector. These technologies can support U.S. manufacturers’ ability to increase throughput and energy efficiency, and decrease waste, defects, and costs. A wide range of manufacturing and industrial subsectors, particularly energy-intensive and energy-dependent industries, have the potential to benefit from smart manufacturing technologies. There are technical improvements still needed to reduce the costs and barriers (trained workforce and upskilling, software-hardware integration, cost, and technical barriers to deployment of advanced sensors, computing, and communication technologies for existing manufacturing assets) to the adoption of smart manufacturing technologies, especially to small and medium-sized manufacturers, and subsequently, increase the overall adoption rate of smart manufacturing technologies. This report outlines the Department of Energy’s (DOE) strategic plan to accelerate the development and implementation of smart manufacturing technologies in the United States and the actions DOE has taken to use these technologies in smart manufacturing for the United States. DOE’s plan to facilitate more rapid development, deployment and widespread adoption of smart manufacturing technologies derive from the 2018 Strategy for American Leadership in Advanced Manufacturing. The strategy outlines a vision for America’s leadership in advanced manufacturing including the development of intelligent manufacturing systems to optimize manufacturing facilities and support the manufacturing of transformative materials. DOE’s Clean Energy Smart Manufacturing Innovation Institute (CESMII), a Manufacturing USA Institute, focuses on accelerating the development and adoption of advanced sensors, controls, platforms, and models needed for smart manufacturing. The objective is to enhance U.S. manufacturing productivity and global competitiveness through the research and development of these technologies. Smart manufacturing has the potential to improve the overall performance, energy productivity, and efficiency of manufacturing, fostering the economic competitiveness of the manufacturing sector.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

FAUST - Benchmark and Validation Framework [Slides]

This presentation discusses Python packages for nuclear data applications and for benchmarking. It also discusses the goals and objectives for FAUST which include providing input and output processing for different calculation codes, allowing for exchanging results between different applications and codes, running benchmarks and processing the results, automating and simplify plot and report generation, and providing a basis for developing applications useful for nuclear data evaluators. The presentation also discusses how the packages can be used both inside and outside LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

M-Star ® Modeling of SME Mixing with Three Impeller Blades

Before a sample of the Slurry Mix Evaporator (SME) can be taken, the SME product sampling procedure requires that the agitator power be stable between 20 and 30 kW for at least one hour. The SME transfer to Melter Feed Tank (MFT) procedure also requires the SME agitator power be stabilized between 20 and 30 kW prior to transfer. These requirements are specified to ensure samples are homogeneous, as discussed in the Waste Form Qualification Report. During SME Batch 804, the agitator power dropped to 19 kW and struggled to achieve and maintain 20 kW. It was later discovered that the cause of the power drop was due to one of the bottom blades of the agitator breaking off. Both the sample and the transfer occurred without the power stabilizing between 20 and 30 kW. Therefore, the quality of SME Batch 804 is indeterminate, and homogeneity was questionable. To evaluate mixing in the SME with a broken agitator containing only three blades (90 degrees apart with space for a missing blade) on the bottom impeller, the Savannah River National Laboratory (SRNL) was requested to perform computer simulations of impeller mixing in the SME using M-Star ® software. The simulations will be used to determine if SME Batch 804 was well mixed and satisfies homogeneity requirements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Using Likwid and Byfl to Benchmark Hardware Performance [Poster]

Benchmark Study conducted focusing on CPU and program performance analysis. Performance data gathered using 2 different programs and comparisons made based on performance. After comparisons are made, conclusions can be drawn and improvements are made upon hardware and software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Batched Sparse Linear Algebra Phase 2 (Final Report)

The purpose of the work was to help LLNL develop a broadly applicable set of capabilities that focus on batched sparse linear functionality and its software implementation. The enablement occurred in a broader scope of the Exascale Computing Program (ECP) with an eye on the xSDK collection of applications and libraries. These served as the main dissemination targets and in the end benefitted from this project’s outcomes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Batched Sparse Linear Algebra Phase 2

The purpose of the work was to help LLNL develop a broadly applicable set of capabilities that focus on batched sparse linear functionality and its software implementation. The enablement occurred in a broader scope of the Exascale Computing Program (ECP) with an eye on the xSDK collection of applications and libraries. These served as the main dissemination targets and in the end benefitted from this project’s outcomes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Requirements Description of the PERSENT Software

This report presents the modeling and simulation capabilities of Argonne National Laboratory’s PERSENT (PERturbation and SENsitivity for Transport) code [1] that is used in modern commercial deployment reactor technologies. The identified capabilities will be used to establish the set of PERSENT verification tasks necessary to verify PERSENT for usage on commercial projects. A similar path was followed for the REBUS [2] and DIF3D [3] software packages.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

3D CAD Modeling and Mechanical Integration at the Mu2e Experiment at Fermilab

This abstract encapsulates a transformative summer internship at Fermilab, focusing on the Mu2e Experiment within the Mechanical Integration and 3D CAD Modeling group. The internship was characterized by a two-phase approach, with the initial month dedicated to the design of an aluminum platform tailored for DS Trench Maintenance. This phase encompassed a comprehensive exploration of structural integrity, material selection, and precision engineering principles, demonstrating an adeptness in CAD modeling and a keen eye for detail. The subsequent month saw a seamless transition into a dynamic phase of the project, wherein the intern played a pivotal role in effecting numerous adjustments across diverse sections of the 3D experiment structure. This phase demanded a nuanced understanding of the intricacies of the Mu2e Experiment and a high level of proficiency in CAD modeling.

3D CAD Modeling↗
DOE OSTI2020

2020 Multiscale Microbial Dynamics Modeling Course

The 2020 Multiscale Microbial Dynamics course is adapted from the virtual 2020 Mutliscale Microbial Dynamics Summer School that was hosted by Environmental Molecular Sciences Laboratory (EMSL), a U.S. Department of Energy (DOE) science user facility located on the Pacific Northwest National Laboratory (PNNL) campus, in collaboration with the Joint Genome Institute (JGI) and the DOE Systems Biology Knowledgebase (KBase). The course course covers how to incorporate microbial metagenomic and environmental metabolite data from watershed ecosystems into metabolic and community modeling using computational frameworks, such as KBase and PFLOTRAN. The curriculum includes lectures and software and data analysis tutorials. All materials are freely accessible to the community as part of the 2020 Microbial Dynamics Summer School Organization in KBase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparing Early Evolution of Flames in X-Ray Bursts in Two and Three Dimensions

We explore the early evolution of flame ignition and spreading on the surface of a neutron star in three dimensions, in the context of X-ray bursts. We look at the nucleosynthesis and morphology of the burning front and compare to two-dimensional axisymmetric simulations to gauge how important a full three-dimensional treatment of the flame is for the early dynamics. Finally, we discuss the progress toward full-star resolved flame simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Quantifying uncertainty in Pareto estimates of global lake area

This software contains the code for Bayesian uncertainty analysis of global lake area. Computed uncertainties are compared against more conventional estimation using lake size-abundance distributions. Routines are included to explore sensitivity to observational errors and ad-hoc "censoring" strategies.

Stachelek, Jemma↗
DOE OSTI2021

Bringing OpenCL to Commodity RISC-V CPUs

The importance of open-source hardware has been increasing in recent years with the introduction of the RISC-V Open ISA. This has also accelerated the push for support of the open-source software stack from compiler tools to full-blown operating systems. Parallel computing with today’s Application Programming Interfaces such as OpenCL has proven to be effective at leveraging the parallelism in commodity multi-core processors and programmable parallel accelerators. However, to the best of our knowledge, there is currently no publicly available implementation of OpenCL targeting commodity RISC-V processors that is accessible to the open-source community. Besides opening RISC-V to the existing rich variety of scientific parallel applications, OpenCL also provides access to a unique genre of benchmarks useful in computer architecture research. In this work, we extended an Open-source implementation of OpenCL to target RISC-V CPUs. Our work not only cover commodity multi-core RISC-V processors, but also plethora of low- profile embedded RISC-V CPUs that often do not support atomic instructions or multi-threading.

Tine, Blaise↗
DOE OSTI2023

noncompact_u1 (qed_m) v1.0.5

This software generates QED fields in which the photon has a finite mass, and also the 0-mode subtracted scheme. They are intended to be used with lattice QCD calculations to understand the QED corrections to nuclear physics processes that are being computed with lattice QCD. To the best of my knowledge, this will be the only publicly available software that generates background QED configurations with massive photons.

Walker-Loud, Andre Walker-Loud↗
DOE OSTI2026

Towards a Verifiable Domain-Specific Language for Hardware-Accelerated Stencils

Defining a domain-specific language (DSL) that supports vector-calculus abstractions eases the porting of partial differential equation (PDE) solvers to specialized architectures. Sufficiently high-level abstractions empower users to express universal laws with sufficient generality that the laws must always hold true within their domain of validity. A broad class of PDE solvers employs stencil-based algorithms, the target domain of Berkeley Lab's stencil accelerator chip co-design project. First released as open-source in January 2026, the Formal software framework lays a foundation for defining an embedded DSL based on composable operators that implement mimetic numerical methods -- stencil algorithms that guarantee satisfaction of discrete versions of important vector calculus theorems. The Formal DSL will be the frontend to a new class of stencil-PDE accelerators developed jointly by LBNL, UHCL, and UC Berkeley through the DOE Competitive Portfolios for Computer Science Project. This offers the potential of an order of magnitude acceleration for this important category of computational methods to serve the DOE mission. Future work on the Formal DSL will facilitate software verification via type-safe templates that enable problem-specific correctness proofs relying upon generic function theory and carefully crafted unit tests.

Rouson, Damian↗
DOE OSTI2024

Integrating quantum computing resources into scientific HPC ecosystems

Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era’s inherent external noise issues. Here, this paper discusses the integration of QC as a computational accelerator within classical scientific high-performance computing (HPC) systems. By leveraging a broad spectrum of simulators and hardware technologies, we propose a hardware-agnostic framework for augmenting classical HPC with QC capabilities. Drawing on the HPC expertise of the Oak Ridge National Laboratory (ORNL) and the HPC lifecycle management of the Department of Energy (DOE), our approach focuses on the strategic incorporation of QC capabilities and acceleration into existing scientific HPC workflows. This includes detailed analyses, benchmarks, and code optimization driven by the needs of the DOE and ORNL missions. Our comprehensive framework integrates hardware, software, workflows, and user interfaces to foster a synergistic environment for quantum and classical computing research. This paper outlines plans to unlock new computational possibilities, driving forward scientific inquiry and innovation in a wide array of research domains.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗