Tensor Train Methods in Quantum Algorithms for Molecular Dynamics
Explore the source record for details and available documents.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
SEARCH · Engineering Papers
Results for “Physics - Plasma physics , Mathematics and Computing, Physics”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
COG Software Architecture Design Description Document
This COG Software Architecture Design Description Document describes the organization and functionality of the COG Multiparticle Monte Carlo Transport Code for radiation shielding and criticality calculations, at a level of detail suitable for guiding a new code developer in the maintenance and enhancement of COG. The intended audience also includes managers and scientists and engineers who wish to have a general knowledge of how the code works. This Document is not intended for end-users.
61 RADIATION PROTECTION AND DOSIMETRY↗
SCALE 6.3 Validation: Spent Nuclear Fuel
This report is the fifth volume in a series documenting the validation of SCALE 6.3 with ENDF/B-VII.1 libraries for nuclear criticality safety, reactor physics, radiation shielding, and spent nuclear fuel applications. This fifth volume, which focuses on validating SCALE capabilities that impact spent nuclear fuel applications, provides an update of the similar validation reported for SCALE 6.2.4.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Efficient and Accurate Pre-Inversion of Equation of State Data
In this report, we evaluate the trade-offs between accuracy and performance in three equation of state interpola- tion strategies- EOSPAC, SpinerEOSDependsRhoT, and SpinerEOSDependsRhoSie-using SESAME tabular data. We also investigate ways to reduce nonlinearity in the data through invertible transformations within the SpinerEOS- DependsRhoSie class with the goal of impacting interpolation accuracy. We include a variety of benchmarking tests that vary the grid densities and how memory is accessed.
36 MATERIALS SCIENCE↗
"Isotopics by nuclides" tool performance in InterSpec
This report provides a performance summary of the “Isotopics by Nuclides” tool in InterSpec. The primary objective of the NA-241 FY25 project was the detection and characterization of non-homogeneous uranium samples. However, the tool also demonstrates effectiveness in determining the enrichment of homogeneous uranium or plutonium from single gamma spectra. This paper presents a subset of evaluated data to avoid distribution limitations while offering potential users’ insight into the tool's performance.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Contributions of Nuclear Data to Today’s Particle Transport Ecosystem
Explore the source record for details and available documents.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
JCZ3: An Equation of State Based on the Exponential-Six Intermolecular Potential – Update: Formulation
This report presents a comprehensive analysis of the JCZ3 equation of state (EOS) as implemented in the TIGER code, focusing on its thermodynamic framework, mathematical formulations, and implications for modeling gas phase behavior under varying conditions. Overall, the report affirms the TIGER code's foundational robustness and its potential as a valuable tool for simulating high-pressure, high-temperature gas mixtures, while also highlighting areas for further refinement and validation.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Critical Simulation Pipeline for COG Suites [Poster]
The CRItical Simulation Pipeline (CRISP) is a Python package for automating validation of reactor criticality benchmarks. CRISP supplies COG—a multi-particle radiation transport code maintained by the Nuclear Criticality Safety Division—with a pipeline to calculate k eff performance for 400+ benchmark experiments with 3,400+ configurations from the International Criticality Safety Benchmark Evaluation Project (ICSBEP). The pipeline includes four stages: materials configuration, input card templating, cluster submission, and results analysis. CRISP includes a command-line interface to facilitate user interaction.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
ESAC v1: Enhanced AI-Powered Chatbot for EQ-SANS Experiment Automation Improvements and Updates
ESAC (EQ-SANS Assisting Chatbot) is an advanced AI-powered application designed to streamline the workflow of neutron scattering experiments at the Spallation Neutron Source (SNS). This report documents the significant advancements in ESAC v1, which include the integration of a combined In-Context Learning (ICL) + Retrieval-Augmented Generation (RAG) capability, a robust integrated development environment, and standalone executable distribution. These enhancements address the limitations of the original version, making ESAC v1 a transformative tool for researchers. The report also discusses the technical challenges encountered during development and their resolution, highlighting the impact of these improvements on the neutron scattering research community.
36 MATERIALS SCIENCE↗
A spline-based method to obtain spatially dependent viscosity in confined flows
Coupling chemical physics to continuum theories is a critical step to understanding multi-scale phenomena. This paper will connect non-equilibrium molecular dynamics simulations to a continuum-based Navier-Stokes equation that has relaxed the assumption of spatial uniformity in viscosity. Using a form for viscosity based on spline interpolation, viscosity as a function of position is obtained from the least squares fit of the velocity profile measured from molecular simulations of flow in a nanochannel. Viscosity can vary widely, particularly near the channel boundaries, indicating that uniform viscosity is no longer appropriate. Variations of the viscosity near the channel surfaces imply that considering solution and surface chemistry could be necessary to rigorously understand molecular-scale flows in nanochannels.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Application of SAMMY for Non-Destructive Characterization of Irradiated Samples Using Neutron Transmission Measurements at VENUS
This report presents the application of SAMMY (Larson 2008), an R-matrix Bayesian fitting system, for analyzing neutron transmission data to enable non-destructive isotopic identification. Transmission measurements were conducted at the VENUS (Bilheux et al. 2023) beamline of the Spallation Neutron Source (SNS) using samples with unknown or partially characterized compositions. Through the application of SAMMY’s R-matrix Bayesian fitting capabilities to the measured transmission spectra and comparison against evaluated nuclear data libraries, isotopic constituents can be quantitatively determined based on their characteristic neutron resonance signatures. This methodology demonstrates significant potential for applications in nuclear safeguards, forensics, and post-irradiation examination.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Modeling Material Interfaces with the Six-Equation Model in FLEXO
FLEXO is a multiphysics code developed at Sandia National Laboratories for predictive simulation of pulsed power target physics with extended magnetohydrodynamics modeling. Given this application space, FLEXO must be able to perform high-fidelity simulations of pulsed-power systems that include multiple materials. This work presents the augmentation of FLEXO with a six-equation model for multimaterial flow. We design and analyze discretizations of the six-equation model, emphasizing desirable properties for robust multimaterial simulation. We also present solution limiting, bounds preservation, and pressure equilibration/relaxation techniques that enhance the robustness of the overall multimaterial scheme. We present a suite of test problems to document these new capabilities of the FLEXO code.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Microreactor Program Technology Maturation MACS system reports
This submission contains several reports associated with the DOE Microreactor Program Technology Maturation MACS system. These include milestone reports: M3AT-24IN0804031-Optimized MACS architecture M3AT-24IN0804033-Light and temp sensor integration M4AT-23IN0804055-Update Microreactor Automated Control System (MACS) hardware based on input from demonstration M2AT-23IN0804054-Demonstrate actuation of control system using Microreactor Automated Control System (MACS)
46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
Continuous-Energy Verification of MCNP Calculations Using One-Group Spherical and Slab Criticality Benchmarks
This work presents a continuous-energy Monte Carlo verification study of one group spherical and slab criticality benchmarks using the MCNP ®1 code. Classical tabulations and newly generated benchmark solutions obtained by direct numerical evaluation by the author are considered. The benchmarks span weakly to strongly multiplying regimes and provide analytically defined critical radii as functions of a single parameter, c .
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments
The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Machine-Learned, Finite Temperature Fermi-Operator Expansions Suitable for GPUs and AI-Hardware
Explore the source record for details and available documents.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
An Introduction to Variational Calculus
Variational Calculus is an advanced topic in mathematics. This document exists to compile the basics of Variational Calculus in a readable and digestible manner for application by engineers. This document is a living document and will be updated as time moves forward. It is the hope that by reading this document, the basics of Variational Calculus can be readily applied to any system/function of interest. This does not serve as a replacement for textbooks or other learned sources but should act as a companion piece to better serve the reader in times of confusion and distress.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)
The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗