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At least 1,207 records · Page 67

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Ongoing solution reproducibility of earth system models as they progress toward exascale computing

We present a methodology for solution reproducibility for the Energy Exascale Earth System Model during its ongoing software infrastructure development to prepare for exascale computers. The nonlinear chaotic nature of climate system simulations precludes traditional model verification approaches since machine precision differences—resulting from code refactoring, changes in software environment, and so on—grow exponentially to a different weather state. Here, we leverage the nature of climate as a statistical description of the atmosphere in order to establish model reproducibility. We evaluate the degree to which two-sample equality of distribution tests can confidently detect the change in climate from minor tuning parameter changes on model output variables in order to establish the level of difference that indicates a new climate. To apply this (baselined test), we target a section of the model’s development cycle wherein no intentional science changes have been applied to its source code. We compare an ensemble of short simulations that were conducted using a verified model configuration against a new ensemble with the same configuration but with the latest software infrastructure (Common Infrastructure for Modeling the Earth, CIME5.0), compiler versions, and software libraries. We also compare these against ensemble simulations conducted using the original version of the software infrastructure (CIME4.0) of the earlier model configuration, but with the latest compilers and software libraries, to test the impact of new compilers and libraries in isolation from additional software infrastructure. The two-sample equality of distribution tests indicates that these ensembles indeed represent the same climate.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Combustion Research I.1 Sprays, Flow, Heat Transfer and Turbulent Mixing

LANL is working with the Partnership for Advance Combustion Engines (PACE) a DOE sponsored consortium of national laboratories for the research and development for creating smarter engine design tools for sustainable transportation. Much of that effort is focused on heat, mass and momentum transfer within and engine. LANL’s focus in 2019, in particular under PACE has been spray modeling and engine mixture formulation, development of conjugate heat transfer analysis (heat transfer to the environment surrounding the combustion chamber). Our efforts relay on the Fast, Easy, Accurate and Robust Continuum Engineering (FEARCE) software developed at LANL as the next generation of engine modeling software for turbulent reactive and multiphase flow, a 2019 R&D 100 winner. This work is relevant to the DOE Vehicle Technologies Office efforts at addressing national energy security as well. Less dependence on petroleum products leads to greater energy security. By Environmental Protection Agency standards, some vehicles are now reaching 42–50 mpg mark. These are conventional gasoline engines. With continued investment and research into new technical innovations, the potential exists to save more than 4 million barrels of oil per day or approximately $200 to $400 million per day. This would be a significant decrease in emissions and use of petroleum and a very large stimulus to the U.S. economy. Better understanding of fuel injection and fuel–air mixing, thermodynamic combustion losses, and combustion/emission formation processes enhances our ability to minimize fuel use and unwanted emissions. Helping to accomplish this understanding, the FEARCE modeling program is working to provide state-of-theart capability for accurately simulating combustion processes: to have a predictive methodology in a software helping industry and researchers not only meet national goals on fuel usage and emissions, but global goals. In addition, a predictive, robust, and accurate capability for simulating the engine combustion process helps to minimize time and labor for development of new engine technology.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1990

Generation and analysis of large reliability models

An effort has been underway for several years at NASA's Langley Research Center to extend the capability of Markov modeling techniques for reliability analysis to the designers of highly reliable avionic systems. This effort has been focused in the areas of increased model abstraction and increased computational capability. The reliability model generator (RMG), a software tool which uses as input a graphical, object-oriented block diagram of the system, is discussed. RMG uses an automated failure modes-effects analysis algorithm to produce the reliability model from the graphical description. Also considered is the ASSURE software tool, a parallel processing program which uses the ASSIST modeling language and SURE semi-Markov solution technique. An executable failure modes-effects analysis is used by ASSURE. The successful combination of the power of graphical representation, automated model generation, and parallel computation leads to the conclusion that large system architectures can now be analyzed.

Aerospace electronics↗

NASA NTRSDate not supplied

Zemax Modeling of a Self-aligned Focusing Schlieren System with Simulated Compressible Flow

A self-aligned focusing schlieren system is simulated in the ANSYS Zemax OpticStudio software environment. The model uses a custom scatter-defining dynamic link library on the retroreflective background in order to scatter rays in the direction of the incident ray rather than the specular ray. Simulated compressible flow refractive index fields are imported into Zemax by use of the grid gradient object and a workaround to the maximum point limit is introduced. The Ronchi ruling is built as a high resolution bitmap image in MATLAB and set in Zemax as a slide object allowing the bitmap image to either transmit or terminate rays at each line pair. The Zemax simulations are compared to computational numerical schlieren and experimental conventional, path-integrated schlieren results from a hypersonic stagnation point injection flow configuration and an experimental image of a shock wave from a laser-induced breakdown. In the stagnation point injection simulations, the Zemax schlieren images capture complex flow features such as the Mach disk, shear layers, contact surface, and bow shock well, but contains long, curved features (striations) between the model and the bow shock that are not present in the synthetic schlieren image from the CFD or the experimental image. The image from Zemax of the spark-induced shock wave captures the shape and curvature of the shock but appears blurry due to grid discretization in the computational data.

Nicholas A Mejia↗

DOE OSTI2020

Single-Bar SMT Testing on Alloy 617 using Software Controls

INL has performed simplified model testing using a variable in the software control program to compare with the testing performed at ORNL, which uses hardware to modify the control signal. The INL tests compared well with the ORNL tests, showing similar stress and strain values, as well as similarly shaped hysteresis loops. This demonstrates that possibility of performing simplified model testing without any hardware modifications.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Abstract This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman, et al., 2021b, https://doi.org/10.1029/2021EO153180 ) in Earth and Space Science Informatics (ESSI) and includes discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, cyberinfrastructure, and data sharing; (Section 3) Machine learning for multiscale modeling; (Section 4) Aerial and satellite remote sensing for advancing Earth system model development by integrating field and ancillary data. ESSI addresses data management practices, computation and analysis, and hardware and software infrastructure. Our role in ICON science therefore involves collaborative work to assess, design, implement, and promote practices and tools that enable effective data management, discovery, integration, and reuse for interdisciplinary work in Earth and space science disciplines. Networks of diverse people with expertise across Earth, space, and data science disciplines are essential for efficient and ethical exchanges of findable, accessible, interoperable, and reusable (FAIR) research products and practices. Our challenge is then to coordinate the development of standards, curation practices, and tools that enable integrating and reusing multiple data types, software, multi‐scale models, and machine learning approaches across disciplines in a way that is as open and/or FAIR as ethically possible. This is a major endeavor that could greatly increase the pace and potential of interdisciplinary scientific discovery.

58 GEOSCIENCES↗

DOE OSTI2026

Ecosystems for Scientific Computing in the Age of AI

Scientific computing is at an inflection point. Artificial intelligence (AI) is reshaping how scientific software is developed, how teams collaborate, how projects are governed, and how the next generation is trained. Drawing on insights from a 2025 workshop report, this article argues that the future of discovery will depend on agile, robust ecosystems built through socio-technical co-design—the intentional integration of technical and human systems. This perspective is essential for ensuring that future scientific computing remains trustworthy, sustainable, and scalable. It combines advances in AI, high-performance computing, and software with new models for cross-disciplinary collaboration, education, and workforce development. Key recommendations include building modular, trustworthy AI-enabled software ecosystems; enabling teams to integrate AI into scientific workflows while preserving human creativity, integrity, and rigor; and developing adaptive training pathways that keep pace with rapid technological change. By sharing these perspectives, we hope to stimulate broader community dialogue and encourage coordinated action.

AI↗

DOE OSTI2019

Numerical Simulations of Cathodoluminescence Measurements in Thin-Film Solar Cells

Cathodoluminescence (CL) measurements can be applied to assess grain-boundary (GB) and grain-interior (GI) recombination in thin-film solar cell materials and made quantitative if we can develop CL models that account for material and measurement complexities. Recently, we developed a three-dimensional numerical CL model, based in MATLAB, that simulates the GI CL intensity as a function of four parameters: grain size, GI lifetime, and GB and surface recombination velocities. The model assumes that GB electrostatic potentials are screened by the high excesscarrier densities used in the CL measurement such that transport is governed by ambipolar diffusion. Here, we develop models to address directly GB potentials and their effects on these measurements. First, we transfer the MATLAB-based model to COMSOL software, and then introduce shallow donors to the GBs to produce potentials. We also develop a two-dimensional model in COMSOL to simulate CL GB contrast with GB potentials. Simulations indicate that GB potentials can increase or decrease CL intensities relative to the zero-potential case. However, the high electron-beam currents typically applied in CL measurements minimize the impact of GB potentials.

14 SOLAR ENERGY↗

DOE OSTI2024

Physical & Cyber Security Modeling Interfacing Through Dante and ARCADE

Physical security is increasingly facing new threats from cyber attackers, for which there is little research in the way of characterizing this threat. This report discusses the efforts to combine cyber and physical security modeling tools to investigate this novel combinatorial threat space. To accomplish this, the Dante force-on-force modeling and simulation software and the Advanced Reactor Cyber Analysis and Development Environment (ARCADE) were integrated. Dante provides a 3D environment which models the physical world, while ARCADE provides the cyber and control systems world.

42 ENGINEERING↗

NASA NTRS2008

SPICE Module for the Satellite Orbit Analysis Program (SOAP)

A SPICE module for the Satellite Orbit Analysis Program (SOAP) precisely represents complex motion and maneuvers in an interactive, 3D animated environment with support for user-defined quantitative outputs. (SPICE stands for Spacecraft, Planet, Instrument, Camera-matrix, and Events). This module enables the SOAP software to exploit NASA mission ephemeris represented in the JPL Ancillary Information Facility (NAIF) SPICE formats. Ephemeris types supported include position, velocity, and orientation for spacecraft and planetary bodies including the Sun, planets, natural satellites, comets, and asteroids. Entire missions can now be imported into SOAP for 3D visualization, playback, and analysis. The SOAP analysis and display features can now leverage detailed mission files to offer the analyst both a numerically correct and aesthetically pleasing combination of results that can be varied to study many hypothetical scenarios. The software provides a modeling and simulation environment that can encompass a broad variety of problems using orbital prediction. For example, ground coverage analysis, communications analysis, power and thermal analysis, and 3D visualization that provide the user with insight into complex geometric relations are included. The SOAP SPICE module allows distributed science and engineering teams to share common mission models of known pedigree, which greatly reduces duplication of effort and the potential for error. The use of the software spans all phases of the space system lifecycle, from the study of future concepts to operations and anomaly analysis. It allows SOAP software to correctly position and orient all of the principal bodies of the Solar System within a single simulation session along with multiple spacecraft trajectories and the orientation of mission payloads. In addition to the 3D visualization, the user can define numeric variables and x-y plots to quantitatively assess metrics of interest.

Coggi, John↗

DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗

DOE OSTI2021

HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.0

HyRAM+ is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen and other alternative fuels infrastructure and transportation systems. HyRAM+ contains validated, simplified release behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO). The U.S. DOE Vehicle Technologies Office (VTO) and U.S. Department of Transportation (DOT) Pipeline and Hazardous Material Safety Administration (PHMSA) contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models. 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. SAND2021-10862 O

Groth, Katrina↗

DOE OSTI2022

HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.1.1

Groth, Katrina↗

DOE OSTI2022

Continuous-Time Models for Longitudinal Data

This software is used to estimate a probabilistic continuous-time model from data. The models capture nonlinear associations between variables that change over time. They can be used to infer future values of variables. These tools were used in the manuscript entitled "Continuous-Time Probabilistic Models for Longitudinal Electronic Health Records."

Kaplan, AlanD↗

DOE OSTI2024

HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.5.1.1

Groth, Katrina↗

NASA NTRS1993

Developing interpretable models with optimized set reduction for identifying high risk software components

Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault frequency components so that testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents the Optimized Set Reduction approach for constructing such models, intended to fulfill specific software engineering needs. Our approach to classification is to measure the software system and build multivariate stochastic models for predicting high risk system components. We present experimental results obtained by classifying Ada components into two classes: is or is not likely to generate faults during system and acceptance test. Also, we evaluate the accuracy of the model and the insights it provides into the error making process.

Briand, Lionel C.↗

NASA NTRS1990

Modeling Selective Availability of the NAVSTAR Global Positioning System

As the development of the NAVSTAR Global Positioning System (GPS) continues, there will increasingly be the need for a software centered signal model. This model must accurately generate the observed pseudorange which would typically be encountered. The observed pseudorange varies from the true geometric (slant) range due to range measurement errors. Errors in range measurement stem from a variety of hardware and environment factors. These errors are classified as either deterministic or random and, where appropriate, their models are summarized. Of particular interest is the model for Selective Availability which is derived from actual GPS data. The procedure for the determination of this model, known as the System Identification Theory, is briefly outlined. The synthesis of these error sources into the final signal model is given along with simulation results.

Braasch, Michael↗

NASA NTRS1998

Space Shuttle Main Engine Quantitative Risk Assessment: Illustrating Modeling of a Complex System with a New QRA Software Package

During 1997, a team from Hernandez Engineering, MSFC, Rocketdyne, Thiokol, Pratt & Whitney, and USBI completed the first phase of a two year Quantitative Risk Assessment (QRA) of the Space Shuttle. The models for the Shuttle systems were entered and analyzed by a new QRA software package. This system, termed the Quantitative Risk Assessment System(QRAS), was designed by NASA and programmed by the University of Maryland. The software is a groundbreaking PC-based risk assessment package that allows the user to model complex systems in a hierarchical fashion. Features of the software include the ability to easily select quantifications of failure modes, draw Event Sequence Diagrams(ESDs) interactively, perform uncertainty and sensitivity analysis, and document the modeling. This paper illustrates both the approach used in modeling and the particular features of the software package. The software is general and can be used in a QRA of any complex engineered system. The author is the project lead for the modeling of the Space Shuttle Main Engines (SSMEs), and this paper focuses on the modeling completed for the SSMEs during 1997. In particular, the groundrules for the study, the databases used, the way in which ESDs were used to model catastrophic failure of the SSMES, the methods used to quantify the failure rates, and how QRAS was used in the modeling effort are discussed. Groundrules were necessary to limit the scope of such a complex study, especially with regard to a liquid rocket engine such as the SSME, which can be shut down after ignition either on the pad or in flight. The SSME was divided into its constituent components and subsystems. These were ranked on the basis of the possibility of being upgraded and risk of catastrophic failure. Once this was done the Shuttle program Hazard Analysis and Failure Modes and Effects Analysis (FMEA) were used to create a list of potential failure modes to be modeled. The groundrules and other criteria were used to screen out the many failure modes that did not contribute significantly to the catastrophic risk. The Hazard Analysis and FMEA for the SSME were also used to build ESDs that show the chain of events leading from the failure mode occurence to one of the following end states: catastrophic failure, engine shutdown, or siccessful operation( successful with respect to the failure mode under consideration).

Smart, Christian↗