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All sources NASA NTRS DOE OSTI

DOE OSTI2026

Visualization for Insight and Data Analysis in Energy Research

This talk explores how advanced visualization technologies are transforming analytical reasoning and knowledge discovery in energy research, drawing on recent work at the National Laboratory of the Rockies' Computational Science Center. Through a series of scientific case studies, we demonstrate how immersive and high-resolution visualization environments enable scientists and engineers to identify previously unseen patterns and features - insights that often remain hidden in traditional desktop-based analysis. By embedding richer information into interactive analytics tools, these approaches support the exploration of complex, multivariate parameter spaces, where interaction itself catalyzes understanding. Beyond capability, we emphasize the critical role of visualization design grounded in perception and cognition, showing how visual encodings directly influence analytical outcomes. Spanning applications from materials science to integrated energy systems, these visualization approaches accelerate innovation and improve decision-making by enabling deeper, more reliable insight into increasingly complex energy data.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1982

NASTRAN thermal analyzer in a unified finite-element treatment of thermo-structural analyses

The NASTRAN thermal analyzer (NTA) which performs large-scale unified thermo-structural analyses with the NASTRAN (NASA structural analysis) computer program is described. The mathematical similitude between these two distinct disciplines of thermal and structure is examined. It serves as the theoretical basis upon which the implementation of the thermal capability in NASTRAN was accomplished. The program structure, the functional flow, the solution algorithms, the organization of an input data deck and the solution capabilities of NTA are summarized. Emphasis is placed on the interface of the unified approach in thermo-structural analyses where stresses, deflections, vibrations and bucklings induced by the effect of temperature change are of concern. Attentions are also directed to the preprocessor and post processors. As a specially designed preprocessor, the VIEW program is capable of generating exchange factors which can be output, at user's option, in formats compatible with that required by NTA. Two post processors that serve specific objectives are included. They are the thermal variance analysis and the graphical displaying capability of temperatures in color or black and white.

Lee, H. P.↗

NASA NTRS1989

Computational Methods for Structural Mechanics and Dynamics, part 1

The structural analysis methods research has several goals. One goal is to develop analysis methods that are general. This goal of generality leads naturally to finite-element methods, but the research will also include other structural analysis methods. Another goal is that the methods be amenable to error analysis; that is, given a physical problem and a mathematical model of that problem, an analyst would like to know the probable error in predicting a given response quantity. The ultimate objective is to specify the error tolerances and to use automated logic to adjust the mathematical model or solution strategy to obtain that accuracy. A third goal is to develop structural analysis methods that can exploit parallel processing computers. The structural analysis methods research will focus initially on three types of problems: local/global nonlinear stress analysis, nonlinear transient dynamics, and tire modeling.

Stroud, W. Jefferson↗

DOE OSTI2021

A comprehensive analysis of transient pressure and rate data from CO 2 storage projects in a depleted pinnacle reef oil field complex, Michigan, USA

Pressure and rate data are commonly recorded as part of a basic monitoring program in CCS projects. This paper discusses the application of multiple analytical techniques to interpret pressure and rate transient data from CO 2 injection and storage operations. The techniques of interest, i.e., injection-falloff analysis, injectivity/productivity index analysis and pressure pulse arrival time analysis, are commonly used in the oil and gas industry to assess reservoir properties, but not well known in the CCS literature (especially the last two). Injection-falloff analysis involves log-log pressure derivative plotting for the falloff data and history-matching of the entire injection-falloff sequence to determine permeability. In the injectivity/productivity index analysis, rate-normalized pressure buildup is plotted against material balance time or ratio of cumulative injection to injection rate to determine the injectivity index (ratio of injection rate to stabilized pressure buildup) which can be related to the permeability-thickness product. The arrival time analysis identifies the arrival of a pressure disturbance (~0.1 psi change from ambient) to determine the hydraulic diffusivity from which permeability can be estimated. The applicability of these techniques is demonstrated via illustrative examples from multiple wells in different pinnacle carbonate reefs undergoing CO 2 -EOR in Northern Michigan. The paper ends with a discussion of the relative merits of each interpretive technique, as well as recommendations that could be useful for other field projects.

42 ENGINEERING↗

DOE OSTI2023

Curifactory: A research experiment manager

Curifactory is a command line tool and framework for organizing Python experiment code, configuration parameters, and results. It is an opinionated and lightweight approach to workflow management infrastructure and is primarily intended to support researchers conducting experiments on one machine. This software was developed to support the reproducibility of results for several data science projects in the Nuclear Nonproliferation Division at Oak Ridge National Laboratory. Curifactory is intended to be a general framework and is not specific to machine learning or data science. It can aid in any field in which experiments are primarily computation-based studies and can be implemented in Python (e.g., high-energy physics, astronomy, computational chemistry). Here, the design emphasizes the automated caching of intermediate data analysis artifacts to speed up development involving computationally intensive tasks. It also allows for data provenance and experiment reproduction. Individual experiment runs are tracked through logs and their output reports, and entire copies of a run with all cached data and metadata can be exported for others to run using Curifactory on another machine. Curifactory experiments can either be integrated into a project from the beginning or can be written on top of an existing codebase without needing significant modification. A few important views of the Curifactory library can be seen in Figure 1.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Challenges in Firmware Re-Hosting, Emulation, and Analysis

System emulation and firmware re-hosting have become popular techniques to answer various security and performance related questions, such as determining whether a firmware contain security vulnerabilities or meet timing requirements when run on a specific hardware platform. While this motivation for emulation and binary analysis has previously been explored and reported, starting to either work or research in the field is difficult. To this end, we provide a comprehensive guide for the practitioner or system emulation researcher. Here, we layout common challenges faced during firmware re-hosting, explaining successive steps and surveying common tools used to overcome these challenges. We provide classification techniques on five different axes, including emulator methods, system type, fidelity, emulator purpose, and control. These classifications and comparison criteria enable the practitioner to determine the appropriate tool for emulation. We use our classifications to categorize popular works in the field and present 28 common challenges faced when creating, emulating, and analyzing a system from obtaining firmwares to post emulation analysis.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Using Global Market Demand Analysis to Guide Conceptual Design of Low-Boom Supersonic Transports

This paper uses a mathematical framework to identify the interdependencies of key variables in supersonic transportation demand analysis. The existing quantitative models for supersonic transportation demand analysis are compared for consistency in modeling the interdependencies. Unlike other quantitative models, the Low-Boom Systems Analysis Model (LBSAM2) can propagate important design characteristics of a supersonic transport aircraft concept to the level of economic metrics (such as the number of future supersonic passengers), with a consistent coupling of the market demand analysis, detailed mission analysis, and low-boom constraint. This allows the use of the detailed demand analysis results from LBSAM2 to maximize the economic viability of a supersonic transport aircraft by finding favorable system-level trades between weight, range, fuel burn, and assumed sonic boom ground noise limit for supersonic overland flight. In this paper, LBSAM2 is integrated with conceptual low-boom design to improve the economic viability of low-boom supersonic transport aircraft. A brief discussion of uncertainties in the LBSAM2 analysis is also included, focusing on their impacts on the relative economic advantages between low-boom concepts.

Consistent coupling of disciplinary analyses↗

NASA NTRSDate not supplied

Using Global Market Demand Analysis to Guide Conceptual Design of Low-Boom Supersonic Transports

Equilibrium state of supersonic market↗

NASA NTRS1982

The dynamics and control of large flexible space structures-V

A general survey of the progress made in the areas of mathematical modelling of the system dynamics, structural analysis, development of control algorithms, and simulation of environmental disturbances is presented. The use of graph theory techniques is employed to examine the effects of inherent damping associated with LSST systems on the number and locations of the required control actuators. A mathematical model of the forces and moments induced on a flexible orbiting beam due to solar radiation pressure is developed and typical steady state open loop responses obtained for the case when rotations and vibrations are limited to occur within the orbit plane. A preliminary controls analysis based on a truncated (13 mode) finite element model of the 122m. Hoop/Column antenna indicates that a minimum of six appropriately placed actuators is required for controllability. An algorithm to evaluate the coefficients which describe coupling between the rigid rotational and flexible modes and also intramodal coupling was developed and numerical evaluation based on the finite element model of Hoop/Column system is currently in progress.

Bainum, P. M.↗

NASA NTRS2002

Advances in space radiation shielding codes

Early space radiation shield code development relied on Monte Carlo methods and made important contributions to the space program. Monte Carlo methods have resorted to restricted one-dimensional problems leading to imperfect representation of appropriate boundary conditions. Even so, intensive computational requirements resulted and shield evaluation was made near the end of the design process. Resolving shielding issues usually had a negative impact on the design. Improved spacecraft shield design requires early entry of radiation constraints into the design process to maximize performance and minimize costs. As a result, we have been investigating high-speed computational procedures to allow shield analysis from the preliminary concept to the final design. For the last few decades, we have pursued deterministic solutions of the Boltzmann equation allowing field mapping within the International Space Station (ISS) in tens of minutes using standard Finite Element Method (FEM) geometry common to engineering design methods. A single ray trace in such geometry requires 14 milliseconds and limits application of Monte Carlo methods to such engineering models. A potential means of improving the Monte Carlo efficiency in coupling to spacecraft geometry is given.

manned↗

NASA NTRS1991

Aerodynamic sensitivity analysis methods for the compressible Euler equations

This study presents a mathematical formulation developed for aerodynamic sensitivity coefficients based on a discretized form of the compressible 2D Euler equations. A brief motivating introduction to the aerodynamic sensitivity analysis and the reasons behind an integrated flow/sensitivity analysis for design algorithms are presented. The finite difference approach and the quasi-analytical approach are used to determine the aerodynamic sensitivity coefficients. A new flow prediction concept, which is an outcome of the direct method in the quasi-analytical approach, is developed and illustrated with an example. Surface pressure coefficient distributions of a nozzle-afterbody configuration obtained from the predicted flowfield solution are compared successfully with their corresponding values obtained from a flowfield analysis code and the experimental data.

Baysal, Oktay↗

DOE OSTI2025

Analysis Facilities for the HL-LHC White Paper

This white paper presents the current status of the R&D for Analysis Facilities (AFs) and attempts to summarize the views on the future direction of these facilities. These views have been collected through the High Energy Physics (HEP) Software Foundation’s (HSF) Analysis Facilities forum (HSF Analysis Facilities Forum), established in March 2022, the Analysis Ecosystems II workshop (Analysis Ecosystems Workshop II), that took place in May 2022, and the WLCG/HSF pre-CHEP workshop (WLCG–HSF pre-CHEP Workshop), that took place in May 2023. The paper attempts to cover all the aspects of an analysis facility.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1980

Aerothermal analysis of a wing-elevon cove with variable leakage

A mathematical model of the heating associated with leakage within the space shuttle orbiter wing elevon cove was used to analyze the aerothermal response of the structure. The analysis was applied to wind tunnel results and to shuttle entry conditions. A parametric study described the mechanism by which the energy of the ingested mass is distributed as a function of the Reynolds number, wall conductivity, surface emissivity, and cove height and length. The rate at which energy was transferred into the cove interior was primarily determined by the combined effects of the convection, wall capacitance, and internal radiation terms. Correlation with wind tunnel results indicated that the cold wall convective heating rates, wall temperature, and gas temperature of the cove were predicted by the analytical model for short exposure times. Predicted transient thermal response of the elevon cove subjected to shuttle entry conditions indicated that the allowable leak area at the cove seal was 20 percent less than that previously indicated by experiment.

Hunt, R. L.↗

DOE OSTI2024

Improving the five-point bootstrap

We present a new algorithm for the numerical evaluation of five-point conformal blocks in d-dimensions, greatly improving the efficiency of their computation. To do this we use an appropriate ansatz for the blocks as a series expansion in radial coordinates, derive a set of recursion relations for the unknown coefficients in the ansatz, and evaluate the series using a Padé approximant to accelerate its convergence. We then study the 〈σσϵσσ〉 correlator in the 3d critical Ising model by truncating the operator product expansion (OPE) and only including operators with conformal dimension below a cutoff ∆ ⩽ ∆cutoff. We approximate the contributions of the operators above the cutoff by the corresponding contributions in a suitable disconnected five-point correlator. Using this approach, we compute a number of OPE coefficients with greater accuracy than previous methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

The Chemistry Graduate Student Experience: Findings from an ACS Survey

Graduate training is a key element in producing a scientific workforce that reflects the nation’s diversity. This paper examines data from a 2013 American Chemical Society (ACS) survey of 2,544 chemistry masters and doctoral students and reveals barriers to reaching this goal. Multivariate statistical analyses indicate that women reported significantly less supportive relationships with advisors. Women were less likely to plan to finish their degrees, and for PhD students, the discrepancy was larger for students at the start of their graduate program. Women were also less likely to pursue the next level of training, and the gender difference related to postdoctoral plans was greater for those who identified with a racial-ethnic group traditionally underrepresented in chemistry (underrepresented minority, URM). URM students who were beyond the first year of their graduate program reported significantly less supportive relationships with peers. They were also less likely to have funding sufficient to meet their needs and more often used personal resources including loans. Despite these difficulties, URM students were more likely to definitely plan to finish their degrees, and men who identified as URM were more likely to plan to pursue postdoctoral work. Independent of gender and identification as URMs, students in more highly ranked schools reported less advisor support. Extensive open-ended comments indicated that large proportions of the students desired more attention and meaningful feedback from advisors and changes within their programs to promote support for students and advisor accountability. Suggestions for future research are given, and a companion commentary discusses needed directions for change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Analytical gradients for molecular-orbital-based machine learning

We report molecular-orbital-based machine learning (MOB-ML) enables the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. Here, we present the derivation, implementation, and numerical demonstration of MOB-ML analytical nuclear gradients, which are formulated in a general Lagrangian framework to enforce orthogonality, localization, and Brillouin constraints on the molecular orbitals. The MOB-ML gradient framework is general with respect to the regression technique (e.g., Gaussian process regression or neural networks) and the MOB feature design. We show that MOB-ML gradients are highly accurate compared to other ML methods on the ISO17 dataset while only being trained on energies for hundreds of molecules compared to energies and gradients for hundreds of thousands of molecules for the other ML methods. The MOB-ML gradients are also shown to yield accurate optimized structures at a computational cost for the gradient evaluation that is comparable to a density-corrected density functional theory calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Geant4Reweight: a framework for evaluating and propagating hadronic interaction uncertainties in Geant4

Geant4Reweight is an open-source C++ framework that allows users to weight tracks produced by the Geant4 particle transport Monte Carlo simulation according to hadron interaction cross section variations and estimate uncertainties in Geant4 interaction models by comparing the simulation’s hadron interaction cross section predictions to data. The ability to weight hadron transport as simulated by Geant4 is crucial to the propagation of systematic uncertainties related to secondary hadronic interactions in current and upcoming neutrino oscillation experiments, including MicroBooNE, NOvA, and DUNE, aswell as hadron test beam experiments such as ProtoDUNE. Here, we provide motivation for weighting hadron tracks in Geant4 in the context of systematic uncertainty propagation, a description of Geant4’s transport simulation technique, and a description of our weighting technique and fitting framework in the momentum range 0–10 GeV/c, which is typical for the hadrons produced by neutrino interactions in these experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Frontiers in computing for artificial intelligence

An emerging diversity of computational platforms offers many different approaches to adopting the paradigm of artificial intelligence to the study of electron-ion collisions. Here we review several leading candidates in this computational frontier and their workflows for experimental applications of artificial intelligence that may impact the future Electron-Ion Collider. We discuss the motivation for exploring novel methods to solve artificial intelligence and machine learning problems including with customized devices, quantum simulation, and heterogeneous computing systems. Furthermore, these technologies offer promising approaches to address some of the leading concerns of future computing that may impact the Electron-Ion Collider but they will require further development and testing in order to support future planning efforts.

detector design and construction technologies and ↗