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Results for “Simulation, Modeling, Performance, and Visualization”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

New framework for benchmarking decadal predictions leveraging the PCMDI Metric Package with interactive visualization

Reliable climate predictions across multiple timescales are increasingly critical as climate-related risks continue to rise. With the growing number and diversity of climate prediction systems, systematic intercomparison has become essential. Here, we present a comprehensive evaluation framework based on the PCMDI Metric Package to assess the performance of multiple decadal climate prediction systems. Unlike uninitialized simulations, initialized predictions exhibit bias and predictive skill that evolve with forecast lead time. To address this, we introduce (1) model-by-lead-time portrait plots, which efficiently summarize metrics of global temperature, precipitation, and Arctic/Antarctic sea-ice extent, and (2) an HTML-based interactive visualization platform that provides detailed regional and seasonal diagnostics of model bias, skill scores, and ensemble spread for each model and lead time. Comparisons with uninitialized simulations further quantify the relative impacts of initialization and external forcing on prediction skill. The proposed framework provides a scalable and transparent approach for multi-model climate prediction assessments and can be readily extended to a wide range of operational and research forecasting systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Research on Intelligent Synthesis Environments

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

Noor, Ahmed K.↗
NASA NTRS2011

Comparative Assessment and Decision Support System for Strategic Military Airlift Capability

The Lockheed Martin Aeronautics Company has been awarded several programs to modernize the aging C-5 military transport fleet. In order to ensure its continuation amidst budget cuts, it was important to engage the decision makers by providing an environment to analyze the benefits of the modernization program. This paper describes an interface that allows the user to change inputs such as the scenario airfields, take-off conditions, and reliability characteristics. The underlying logistics surrogate model was generated using data from a discrete-event simulation. Various visualizations such as intercontinental flight paths illustrated in 3D, have been created to aid the user in analyzing scenarios and performing comparative assessments for various output logistics metrics. The capability to rapidly and dynamically evaluate and compare scenarios was developed enabling real time strategy exploration and trade-offs.

Salmon, John↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Implementation of the Glued Sphere Discrete Element Model for Non-Spherical Particles in MFiX Software

To enhance solver capabilities, simulation flexibility and model validation within the MFiX software, the U.S. Department of Energy (DOE) is funding efforts to develop and integrate the glued-sphere discrete element method into the latest version of MFiX as a dedicated computational module. The glued-sphere discrete element method is a numerical technique to depict the behavior of non-spherical particles in granular flows or particulate systems by representing them as a collection of component spheres. These spheres are bonded together to approximate the shape and mechanical/chemical properties of a more complex particle. The method effectively reuses the existing sphere-sphere collision algorithm, interphase momentum and heat transfer calculations utilized in the traditional discrete element method, extending these capabilities to non-spherical particles. Additionally, this method explicitly resolves intra-particle temperature and species distributions. The MFiX glued-sphere computational module includes tools for generating glued sphere configurations, a dedicated solver, and visualization capabilities in post-processing. More specifically within the computational module, collision detection and calculations were first performed on component spheres and then mapped onto non-spherical particles. The linear spring-dashpot model was utilized to simulate the sphere-sphere interactions.

Ke, Renjie↗
NASA NTRS2004

Turnaround Time Modeling for Conceptual Rocket Engines

Recent years have brought about a paradigm shift within NASA and the Space Launch Community regarding the performance of conceptual design. Reliability, maintainability, supportability, and operability are no longer effects of design; they have moved to the forefront and are affecting design. A primary focus of this shift has been a planned decrease in vehicle turnaround time. Potentials for instituting this decrease include attacking the issues of removing, refurbishing, and replacing the engines after each flight. less, it is important to understand the operational affects of an engine on turnaround time, ground support personnel and equipment. One tool for visualizing this relationship involves the creation of a Discrete Event Simulation (DES). A DES model can be used to run a series of trade studies to determine if the engine is meeting its requirements, and, if not, what can be altered to bring it into compliance. Using DES, it is possible to look at the ways in which labor requirements, parallel maintenance versus serial maintenance, and maintenance scheduling affect the overall turnaround time. A detailed DES model of the Space Shuttle Main Engines (SSME) has been developed. Trades may be performed using the SSME Processing Model to see where maintenance bottlenecks occur, what the benefits (if any) are of increasing the numbers of personnel, or the number and location of facilities, in addition to trades previously mentioned, all with the goal of optimizing the operational turnaround time and minimizing operational cost. The SSME Processing Model was developed in such a way that it can easily be used as a foundation for developing DES models of other operational or developmental reusable engines. Performing a DES on a developmental engine during the conceptual phase makes it easier to affect the design and make changes to bring about a decrease in turnaround time and costs.

Nix, Michael↗
NASA NTRS1994

Performance Measurement, Visualization and Modeling of Parallel and Distributed Programs

This paper presents a methodology for debugging the performance of message-passing programs on both tightly coupled and loosely coupled distributed-memory machines. The AIMS (Automated Instrumentation and Monitoring System) toolkit, a suite of software tools for measurement and analysis of performance, is introduced and its application illustrated using several benchmark programs drawn from the field of computational fluid dynamics. AIMS includes (i) Xinstrument, a powerful source-code instrumentor, which supports both Fortran77 and C as well as a number of different message-passing libraries including Intel's NX Thinking Machines' CMMD, and PVM; (ii) Monitor, a library of timestamping and trace -collection routines that run on supercomputers (such as Intel's iPSC/860, Delta, and Paragon and Thinking Machines' CM5) as well as on networks of workstations (including Convex Cluster and SparcStations connected by a LAN); (iii) Visualization Kernel, a trace-animation facility that supports source-code clickback, simultaneous visualization of computation and communication patterns, as well as analysis of data movements; (iv) Statistics Kernel, an advanced profiling facility, that associates a variety of performance data with various syntactic components of a parallel program; (v) Index Kernel, a diagnostic tool that helps pinpoint performance bottlenecks through the use of abstract indices; (vi) Modeling Kernel, a facility for automated modeling of message-passing programs that supports both simulation -based and analytical approaches to performance prediction and scalability analysis; (vii) Intrusion Compensator, a utility for recovering true performance from observed performance by removing the overheads of monitoring and their effects on the communication pattern of the program; and (viii) Compatibility Tools, that convert AIMS-generated traces into formats used by other performance-visualization tools, such as ParaGraph, Pablo, and certain AVS/Explorer modules.

Yan, Jerry C.↗
DOE OSTI2026

Near-Real-Time Statistical Analysis and Visualization of Streamflow from a Deep-Learning Rainfall-Runoff Model

Near-real-time (NRT) streamflow data are critical importance for timely water resources management. Here, we developed an open-source tool, FlowStats, for NRT streamflow analysis and visualization in Germany, based on NRT meteorological data from the German Weather Service and simulated streamflow from a long short-term memory neural network (LSTM). The LSTM model achieved very good overall performance, median NSE of 0.80 for the test period across 1,479 catchments. FlowStats provides options for deriving various streamflow statistics, from normal and abnormal streamflow detection to drought and flood analyses. An example analysis from FlowStats revealed widespread below-normal to extreme low-flow conditions across Germany from March to May 2025, which weakened from June to September 2025. Drought analysis for September 2025 highlighted severe to extreme drought conditions in northwestern Germany, while flood classifications indicated that high-flow events occurred in southwestern Germany. FlowStats can be used for various hydrological assessments to support water resources management.

Hydrological modeling↗
DOE OSTI2022

Data-centric framework for crystal structure identification in atomistic simulations using machine learning

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Computations of Complex Three-Dimensional Turbulent Free Jets

Three-dimensional, incompressible turbulent jets with rectangular and elliptical cross-sections are simulated with a finite-difference numerical method. The full Navier- Stokes equations are solved at low Reynolds numbers, whereas at high Reynolds numbers filtered forms of the equations are solved along with a sub-grid scale model to approximate the effects of the unresolved scales. A 2-N storage, third-order Runge-Kutta scheme is used for temporary discretization and a fourth-order compact scheme is used for spatial discretization. Although such methods are widely used in the simulation of compressible flows, the lack of an evolution equation for pressure or density presents particular difficulty in incompressible flows. The pressure-velocity coupling must be established indirectly. It is achieved, in this study, through a Poisson equation which is solved by a compact scheme of the same order of accuracy. The numerical formulation is validated and the dispersion and dissipation errors are documented by the solution of a wide range of benchmark problems. Three-dimensional computations are performed for different inlet conditions which model the naturally developing and forced jets. The experimentally observed phenomenon of axis-switching is captured in the numerical simulation, and it is confirmed through flow visualization that this is based on self-induction of the vorticity field. Statistical quantities such as mean velocity, mean pressure, two-point velocity spatial correlations and Reynolds stresses are presented. Detailed budgets of the mean momentum and Reynolds stresses are presented. Detailed budgets of the mean momentum and Reynolds stress equations are presented to aid in the turbulence modeling of complex jets. Simulations of circular jets are used to quantify the effect of the non-uniform curvature of the non-circular jets.

Wilson, Robert V.↗
NASA NTRS2005

Emissions Prediction and Measurement for Liquid-Fueled TVC Combustor with and without Water Injection

An investigation is performed to evaluate the performance of a computational fluid dynamics (CFD) tool for the prediction of the reacting flow in a liquid-fueled combustor that uses water injection for control of pollutant emissions. The experiment consists of a multisector, liquid-fueled combustor rig operated at different inlet pressures and temperatures, and over a range of fuel/air and water/fuel ratios. Fuel can be injected directly into the main combustion airstream and into the cavities. Test rig performance is characterized by combustor exit quantities such as temperature and emissions measurements using rakes and overall pressure drop from upstream plenum to combustor exit. Visualization of the flame is performed using gray scale and color still photographs and high-frame-rate videos. CFD simulations are performed utilizing a methodology that includes computer-aided design (CAD) solid modeling of the geometry, parallel processing over networked computers, and graphical and quantitative post-processing. Physical models include liquid fuel droplet dynamics and evaporation, with combustion modeled using a hybrid finite-rate chemistry model developed for Jet-A fuel. CFD and experimental results are compared for cases with cavity-only fueling, while numerical studies of cavity and main fueling was also performed. Predicted and measured trends in combustor exit temperature, CO and NOx are in general agreement at the different water/fuel loading rates, although quantitative differences exist between the predictions and measurements.

Brankovic, A.↗
DOE OSTI2019

Integrated Modeling and Simulation Capability For Full Scale Multi-Physics Simulation and Visualization of Microreactor Concept

Microreactors are small mobile transportable nuclear reactors with thermal power less than 20 MWt that are designed to meet the needs of remote areas, military installations, emergency operations, and disaster relief zones. These reactor are concepts that are intended to be factory-manufacturable, easily transportable, and will allow for semi- or full-autonomous operation. To assist with development of microreactors, modeling and experimentation need to be performed with verification and validation to gain confidence in the models and tools. The objective of this study is apply advanced modeling and simulation capabilities being developed by the DOE Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to perform integrated modeling and simulation capability for multiphysics simulation of the microreactor concepts. This activity will provide an opportunity to exercise the codes to provide both gain experience and to provide feedback to the developers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2024

Measurements and Computational Analysis of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow Experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This report presents and discusses the results of a recent experiment with the Juncture Flow Model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of the test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model angle of incidence. Laser Doppler velocimetry (LDV) measurements were made at three model angles of incidence (0° : fully attached, 1° : incipient separation, and 5° : separated flow) and for each angle, mean-flow and Reynolds-stress data were obtained on the fuselage and at several locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and include model and tunnel wall static pressures, tunnel wall boundary-layer profiles, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. A companion set of Reynolds-averaged Navier-Stokes (RANS) CFD simulations were also performed and those results were used to support the discussion of the experimental test results.

Juncture Flow↗
NASA NTRS2012

Linking Plasma Conditions in the Magnetosphere with Ionospheric Signatures

Modeling of the full magnetosphere, ring current and ionosphere system has become an indispensable tool in analyzing the series of events that occur during geomagnetic storms. The CCMC has a full model suite available for the magnetosphere, together with visualization tools that allow a user to perform a large variety of analyses. The January, 21, 2005 storm was a moderate-size storm that has been found to feature a large penetration electric field and unusually large polar caps (low-latitude precipitation patterns) that are otherwise found in super storms. Based on simulations runs at CCMC we can outline the likely causes of this behavior. Using visualization tools available to the online user we compare results from different magnetosphere models and present connections found between features in the magnetosphere and the ionosphere that are connected magnetically. The range of magnetic mappings found with different models can be compared with statistical models (Tsyganenko) and the model's fidelity can be verified with observations from low earth orbiting satellites such as DMSP and TIMED.

Rastaetter, Lutz↗
DOE OSTI2021

Laboratory Evaluation of Tunable White LEDs for Circadian Lighting in Commercial Offices

Tunable white Light-Emitting Diode (LED) systems that allow users to control Correlated Color Temperature (CCT) are often marketed for circadian health, which is an emerging priority in commercial office lighting. However, the energy impacts of meeting circadian criteria with standard non-tunable LEDs and with tunable white LEDs are not well understood. The goals of this project were to implement select commercial lighting systems, including tunable white LEDs, to meet visual and circadian criteria in an office environment, and to quantify lighting performance and energy usage. Most recent studies on tunable white LEDs, circadian lighting strategies, and energy impacts have relied on computer simulations and models. While little research has directly measured tunable LED energy usage for circadian criteria, EPRI has recently published results from a lab-based evaluation of illuminance, spectral output, and energy consumption for several LED products marketed for circadian performance. The research presented here contributes to the field by quantifying the performance of market-available technologies through detailed monitoring of performance parameters (such as illuminance, spectral output, glare, and energy consumption) in a physical space (an office environment).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2005

A model to assess the Mars Telecommunications Network relay robustness

The relatively long mission durations and compatible radio protocols of current and projected Mars orbiters have enabled the gradual development of a heterogeneous constellation providing proximity communication services for surface assets. The current and forecasted capability of this evolving network has reached the point that designers of future surface missions consider complete dependence on it. Such designers, along with those architecting network requirements, have a need to understand the robustness of projected communication service. A model has been created to identify the robustness of the Mars Network as a function of surface location and time. Due to the decade-plus time horizon considered, the network will evolve, with emerging productive nodes and nodes that cease or fail to contribute. The model is a flexible framework to holistically process node information into measures of capability robustness that can be visualized for maximum understanding. Outputs from JPL's Telecom Orbit Analysis Simulation Tool (TOAST) provide global telecom performance parameters for current and projected orbiters. Probabilistic estimates of orbiter fuel life are derived from orbit keeping burn rates, forecasted maneuver tasking, and anomaly resolution budgets. Orbiter reliability is estimated probabilistically. A flexible scheduling framework accommodates the projected mission queue as well as potential alterations.

Mars Telecommunications Orbiter (MTO)↗
NASA NTRS2008

Information Extraction for System-Software Safety Analysis: Calendar Year 2007 Year-End Report

This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis on the models to identify possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations; 4) perform discrete-time-based simulation on the models to investigate scenarios where these paths may play a role in failures and mishaps; and 5) identify resulting candidate scenarios for software integration testing. This paper describes new challenges in a NASA abort system case, and enhancements made to develop the integrated tool set.

Malin, Jane T.↗