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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Feasibility studies of time-like proton electromagnetic form factors at $\overline{\rm P}$ANDA at FAIR

Simulation results for future measurements of electromagnetic proton form factors at $\overline{\rm P}$ANDA (FAIR) within the PandaRoot software framework are reported. The statistical precision with which the proton form factors can be determined is estimated. The signal channel p¯p → e + e – is studied on the basis of two different but consistent procedures. The suppression of the main background channel, i.e. p¯p → π + π – , is studied. Furthermore, the background versus signal efficiency, statistical and systematical uncertainties on the extracted proton form factors are evaluated using two different procedures. The results are consistent with those of a previous simulation study using an older, simplified framework. Furthermore, a slightly better precision is achieved in the PandaRoot study in a large range of momentum transfer, assuming the nominal beam conditions and detector performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Full event interpretation with machine-learning-based particle-flow reconstruction in the CMS detector

The particle-flow (PF) algorithm constructs a global description of each particle collision by producing a comprehensive list of final-state particles, and is central to event reconstruction in the CMS experiment at the CERN LHC. The existing PF implementation relies on physics-motivated heuristics and assumptions that can be replaced by machine-learning (ML) models trained directly on simulated data and naturally suited to modern graphics processing units (GPUs). A state-of-the-art ML-based PF (MLPF) reconstruction algorithm, implemented within the CMS software framework, is presented. The MLPF algorithm performs a learnable full-event reconstruction on GPUs, generalizes across detector conditions and collision energies, and replaces multiple modular reconstruction steps with a single unified model. Physics performance comparable to standard PF reconstruction is achieved in both simulation and data, with improved jet energy resolution and inference time. In simulated top quark-antiquark events under LHC Run-3 (2023-2024) conditions, the jet energy resolution improves by 10-20% for jets with transverse momentum between 30-100 GeV. Inference time is evaluated using simulated multijet events, with a median of $20\,\hbox {ms}$ per event on an Nvidia L4 GPU, compared to approximately $110\,\hbox {ms}$ for the standard CMS PF reconstruction.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
DOE OSTI2015

Action Recommendation for Cyber Resilience

This paper presents an unifying graph-based model for representing the infrastructure, behavior and missions of an enterprise. We describe how the model can be used to achieve resiliency against a wide class of failures and attacks. We introduce an algorithm for recommending resilience establishing actions based on dynamic updates to the models. Without loss of generality, we show the effectiveness of the algorithm for preserving latency based quality of service (QoS). Our models and the recommendation algorithms are implemented in a software framework that we seek to release as an open source framework for simulating resilient cyber systems.

resilience, cyber security↗
DOE OSTI2019

Toward Generalized Tensor Algebra for ab initio Quantum Chemistry Methods

The widespread use of tensor operations in describing electronic structure calculations has motivated the design of software frameworks for productive development of scalable optimized tensor-based electronic structure methods. Whereas prior work focused on Cartesian abstractions for dense tensors, we present an algebra to specify and perform tensor operations on a larger class of block-sparse tensors. We illustrate the use of this framework in expressing real-world computational chemistry calculations beyond the reach of existing frameworks.

Mutlu, Erdal↗
DOE OSTI2016

rplexos [SWR-14-19]

rplexos is a R (statistical software framework; more? details below) package that processes and facilitates analysis of solution from PLEXOS. PLEXOS is a production cost model that is utilize to simulate the behavior of the power.systems and is developed and commercialized by Energy Exomplar. The intention is to make rptexos open-source so other PLEXOS users can utilize it.

Ibanez, Eduardo↗
DOE OSTI2016

Tusas, Version 1.0

Tusas is a general / flexible software framework for solving coupled systems of onlinear partial differential equations. Tusas was originally developed for phase-field simulation of solidification. In order for Tusas to be effective, the PDEs must be compatible with structured or unstructured Lagrange (nodal) finite element discretizations and explicit (Euler) or implicit (Euler, Trapezoid, BDF2) temporal discretizations.

Newman, ChristopherK.↗
DOE OSTI2017

Tempus v. 1.0

Tempus is a software framework for the time integration of ordinary differential equations (ODEs), partial differential equations (PDEs), and differential-algebraic equations (DAEs). Examples of time-integration methods available are Forward Euler, Backward Euler, Explicit Runge-Kutta and Implicit Runge-Kutta methods. Tempus can be used from small systems of equations (e.g., single ODEs for the time evolution of plasticity models) to large-scale transient simulations requiring exascale computing (e.g., flow fields around reentry vehicles and magneto-hydrodynamics). Tempus will be released as part of Trilinos under a BSD open source license.

Obert, CurtisC.↗
DOE OSTI2022

mesoflow [SWR-22-56]

Mesoflow is a continuum scale simulation tool developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex surface morphologies (of catalysts/biomass particles among others) directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPU) compared to a single processor for representative problem sizes (2 million cell mesh).

Sitaraman, Hariswaran↗
DOE OSTI2022

Fugu v.0.1

SAND2021-15052 O Fugu provides a common software framework for designing and prototyping algorithms for spiking neuromorphic hardware and compiling to multiple hardware platforms. 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.

Aimone, James↗
DOE OSTI2024

Multiplayer Engineering

INL engineers developed a special purpose software framework designed to establish real-time connections between multiple running Unity instances. The framework is developed in Unity, a game engine development platform. This framework programmatically attaches functions to engineering models, enabling users to interact with, observe, and make changes to virtual models. These interactions are broadcasted through websocket connections, and received by other engineers in real-time.

Woodruff, Nathan↗
DOE OSTI2022

pnnl/eqc

EQC is a software framework for smart distributed quantum computer management and organization for variational quantum algorithms. EQC utilizes smart real time management of multiple independent quantum processors to maximize variational quantum algorithm throughput, for improved converged performance and improved rate of convergance.

Central, PNNL Developer↗
DOE OSTI2019

pnnl/ripples

A C++ Library for Influence Maximization Ripples is a software framework to study the Influence Maximization problem. Our goal with Ripples is to provide tools implementing fast and scalable state-of-the-art approximation algorithms to solve the influence maximization problem.

Minutoli, Marco↗
DOE OSTI2024

AMReX v2024

The software framework, AMReX, supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving the essential local descriptions of different physical processes in complex multiphysics algorithms. AMR uses a hierarchical representation of the solution at multiple levels of resolution where the solution on each level is defined on the union of data containers at that resolution. These data containers, which represent the solution over a logically rectangular subregion of the domain, can contain field data defined on a mesh, Lagrangian particles or combinations of both. In addition to these basic data types, AMReX supports a multilevel embedded boundary representation of complex geometry; linear solvers for cell-centered and nodal data; asynchronous I/O in a native format readable by ParaView, VisIt and yt; and interfaces to hypre and PETSc solvers. AMReX enables applications to run on distributed memory architectures with multicore CPUs and with GPU accelerators. AMReX uses a lightweight abstraction layer that effectively hides the details of the architecture from the application. The framework currently supports CUDA, HIP and SYCL for GPU acceleration and OpenMP for multi-core CPU architectures.

Almgren, Ann↗
DOE OSTI2024

Exascale-Enabled Models and Algorithms for Microelectronics Applications (MicroEleX) v1

The MicroEleX code package contains a variety of models and algorithms for physical modeling of microelectronic circuitry, including electrostatics, electrodynamics, superconducting physics, micromagnetics, multi-ferroic systems, and quantum transport. MicroEleX leverages the AMReX software framework to provide scalability on GPU-based supercomputing architectures. The code is open source and designed to be algorithmically flexible so developers can incorporate enhanced or customized physics.

Nonaka, Andy↗
DOE OSTI2024

pnnl/LAP

A software framework to study, from the performance and energy perspective, the efficacy of GPU-resident parallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and incomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated by an iterative process

Swirydowicz, Kasia↗
DOE OSTI2025

C4.jl [SWR-25-106]

A proof-of-concept software framework for integrating capacity expansion and production cost optimization with probabilistic resource adequacy assessment and sending feedback signals between the models.

Stephen, Gordon [National Renewable Energy Laborat↗