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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Modeling and Simulation at NASA

This slide presentation is composed of two topics. The first reviews the use of modeling and simulation (M&S) particularly as it relates to the Constellation program and discrete event simulation (DES). DES is defined as a process and system analysis, through time-based and resource constrained probabilistic simulation models, that provide insight into operation system performance. The DES shows that the cycles for a launch from manufacturing and assembly to launch and recovery is about 45 days and that approximately 4 launches per year are practicable. The second topic reviews a NASA Standard for Modeling and Simulation. The Columbia Accident Investigation Board made some recommendations related to models and simulations. Some of the ideas inherent in the new standard are the documentation of M&S activities, an assessment of the credibility, and reporting to decision makers, which should include the analysis of the results, a statement as to the uncertainty in the results,and the credibility of the results. There is also discussion about verification and validation (V&V) of models. There is also discussion about the different types of models and simulation.

Steele, Martin J.↗
DOE OSTI2025

Optimization of direct air capture processes using reactive transport models of adsorption-desorption cycles

In this study, we develop and implement a reactive transport model in COMSOL Multiphysics® to address the challenges of direct air carbon capture. The model is validated against experimental data and used to simulate the cyclic steady state of the adsorption-desorption process. The optimization of this model is achieved through advanced trust-region methods integrated with Gaussian Processes. Key decision variables, including adsorption and desorption times, desorption temperature and pressure, input velocity, bed porosity, column length, and radius were optimized to minimize the capture cost. After optimization, a sensitivity analysis revealed the complex interplay between the decision variables and their effect on the specific energy and cost of removing the CO 2 . We optimized the capture cost while taking into account the trade-off between energy consumption and productivity. The resulting minimum capture cost was determined to be 265.2 $/t-CO 2 , which aligns with expected values reported in the literature. Numerical results suggest the effectiveness of the optimization strategies applied, and underscore the importance of simultaneous decision variable selection in improving the performance in direct air capture processes. We also extend the modeling approach to a 2D axisymmetric model to better visualize CO₂ uptake and temperature profiles, revealing significant radial gradients during the regeneration step. As a main drawback, this enhanced model comes with a computational cost approximately 40 times higher than that of the 1D model.

Adsorption-desorption process↗
NASA NTRS2011

Facility Targeting, Protection and Mission Decision Making Using the VISAC Code

The Visual Interactive Site Analysis Code (VISAC) has been used by DTRA and several other agencies to aid in targeting facilities and to predict the associated collateral effects for the go, no go mission decision making process. VISAC integrates the three concepts of target geometric modeling, damage assessment capabilities, and an event/fault tree methodology for evaluating accident/incident consequences. It can analyze a variety of accidents/incidents at nuclear or industrial facilities, ranging from simple component sabotage to an attack with military or terrorist weapons. For nuclear facilities, VISAC predicts the facility damage, estimated downtime, amount and timing of any radionuclides released. Used in conjunction with DTRA's HPAC code, VISAC also can analyze transport and dispersion of the radionuclides, levels of contamination of the surrounding area, and the population at risk. VISAC has also been used by the NRC to aid in the development of protective measures for nuclear facilities that may be subjected to attacks by car/truck bombs.

Morris, Robert H.↗
DOE OSTI2025

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Strategies for Flood Resilience and Grid Investment Among Iowa's Electric Distribution Utilities

Flooding poses a growing threat to Iowa's electric distribution system, yet utilities face significant data and modeling challenges in planning effective resilience investments. This report provides a foundational assessment of how distribution utilities in Iowa, investor-owned, municipal, and cooperative, approach resilience planning, with a focus on flood risk. It combines hazard characterization, review of state and utility practices, and application of NLR's Energy Resilience Analysis for Distribution Systems (ERAD) and Capacity Expansion Decision Support for Distribution Networks (CADET) tools. Using FEMA floodplains, Iowa Flood Center depth grids, and utility infrastructure data, the analysis quantifies asset exposure, simulates outage risks, and evaluates resilience strategies such as pole hardening, undergrounding, and substation protection. Results indicate that while feeder-level upgrades provide incremental benefits, the most significant reductions in outage risk are achieved through targeted substation interventions. The report highlights key data gaps, such as limited elevation data and fragility functions, and underscores the need for probability-weighted investment frameworks to address both frequent and catastrophic flood events. These insights aim to support utilities, state agencies, and federal partners in prioritizing resilience investments that safeguard Iowa's electric grid against future flooding.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1987

An overview of the mathematical and statistical analysis component of RICIS

Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.

Hallum, Cecil R.↗
NASA NTRS2006

An Overview of the Role of Systems Analysis in NASA's Hypersonics Project

NASA's Aeronautics Research Mission Directorate recently restructured its Vehicle Systems Program, refocusing it towards understanding the fundamental physics that govern flight in all speed regimes. Now called the Fundamental Aeronautics Program, it is comprised of four new projects, Subsonic Fixed Wing, Subsonic Rotary Wing, Supersonics, and Hypersonics. The Aeronautics Research Mission Directorate has charged the Hypersonics Project with having a basic understanding of all systems that travel at hypersonic speeds within the Earth's and other planets atmospheres. This includes both powered and unpowered systems, such as re-entry vehicles and vehicles powered by rocket or airbreathing propulsion that cruise in and accelerate through the atmosphere. The primary objective of the Hypersonics Project is to develop physics-based predictive tools that enable the design, analysis and optimization of such systems. The Hypersonics Project charges the systems analysis discipline team with providing it the decision-making information it needs to properly guide research and technology development. Credible, rapid, and robust multi-disciplinary system analysis processes and design tools are required in order to generate this information. To this end, the principal challenges for the systems analysis team are the introduction of high fidelity physics into the analysis process and integration into a design environment, quantification of design uncertainty through the use of probabilistic methods, reduction in design cycle time, and the development and implementation of robust processes and tools enabling a wide design space and associated technology assessment capability. This paper will discuss the roles and responsibilities of the systems analysis discipline team within the Hypersonics Project as well as the tools, methods, processes, and approach that the team will undertake in order to perform its project designated functions.

Robinson, Jeffrey S.↗
NASA NTRS2019

Gateway Modeling and Simulation Plan

This plan institutes direction across the Gateway Program and the Element Projects to ensure that Cross Program M&S are produced in a manner that (1) generate the artifacts required for NASA-STD-7009 compliance, (2) ensures interoperability of M&S exchanged and integrated across the program and, (3) drives integrated development efforts to provide cross-domain integrated simulation of the Gateway elements, space environment, and operational scenarios. This direction is flowed down via contractual enforcement to prime contractors and includes both the GMS requirements specified in this plan and the NASASTD- 7009 derived requirements necessary for compliance. Grounding principles for management of Gateway Models and Simulations (M&S) are derived from the Columbia Accident Investigation Board (CAIB) report and the Diaz team report, “A Renewed Commitment to Excellence.” As an outcome of these reports, and in response to Action 4 of the Diaz team report, the NASA Standard for Models and Simulations, NASA-STD-7009 was developed. The standard establishes M&S requirements for development and use activities to ensure proper capture and communication of M&S pedigree and credibility information to Gateway program decision makers. Through the course of the Gateway program life cycle M&S will be heavily relied upon to conduct analysis, test products, support operations activities, enable informed decision making and ultimately to certify the Gateway with an acceptable level of risk to crew and mission. To reduce risk associated with M&S influenced decisions, this plan applies the NASA-STD-7009 requirements to produce the artifacts that support credibility assessments and ensure the information is communicated to program management.

NASA-STD-7009↗
DOE OSTI2025

Improving Trustworthiness of Data-Driven Power Grid Contingency Analysis With Bayesian Residual Graph Neural Networks

The evolving energy landscape requires novel tools to efficiently perform contingency analysis and reliability assessment of power grids, potentially in real-time. The high computational cost of traditional power flow solvers limits their applicability in practice. Machine learning (ML) surrogates such as deep neural networks (NNs) accelerate power flow solvers computations, enabling high-order contingency analysis and real-time decision-making by learning highly nonlinear functions and integrating grid topology via graph architectures. However, (graph) NNs lack predictive power away from training data and do not provide predictive confidence estimates. Here, we present a Bayesian residual graph NN that integrates knowledge from low-fidelity data via residual training and embeds granular quantification of uncertainties, improving trustworthiness critical for high-consequence decision-making. Applying Bayesian concepts to NNs is challenging due to the high-dimensionality of both the parameter space, complicating derivation of a meaningful prior, and the output space in large grid systems, requiring enhanced techniques to assess the predicted high-dimensional uncertainties. Our contributions include: (1) Deriving a prior for fully connected and graph NNs that leverages low-fidelity data to guide mean predictions and appropriately control prior predictive uncertainty. (2) Integrating this prior within an ensembling with anchoring scheme for efficient approximate posterior inference. (3) Deriving enhanced metrics to assess accuracy of both the mean and uncertainty predictions in high dimensions, appropriately accounting for correlations propagated through graph layers. The resulting Bayesian residual graph NN is tested on a contingency analysis task for 14-bus and 118-bus grids.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1997

Using APEX to Model Anticipated Human Error: Analysis of a GPS Navigational Aid

The interface development process can be dramatically improved by predicting design facilitated human error at an early stage in the design process. The approach we advocate is to SIMULATE the behavior of a human agent carrying out tasks with a well-specified user interface, ANALYZE the simulation for instances of human error, and then REFINE the interface or protocol to minimize predicted error. This approach, incorporated into the APEX modeling architecture, differs from past approaches to human simulation in Its emphasis on error rather than e.g. learning rate or speed of response. The APEX model consists of two major components: (1) a powerful action selection component capable of simulating behavior in complex, multiple-task environments; and (2) a resource architecture which constrains cognitive, perceptual, and motor capabilities to within empirically demonstrated limits. The model mimics human errors arising from interactions between limited human resources and elements of the computer interface whose design falls to anticipate those limits. We analyze the design of a hand-held Global Positioning System (GPS) device used for radical and navigational decisions in small yacht recalls. The analysis demonstrates how human system modeling can be an effective design aid, helping to accelerate the process of refining a product (or procedure).

VanSelst, Mark↗
NASA NTRSDate not supplied

Impact Real World System Validation

Introduction NASA has developed a new evidence-based data-driven probabilistic risk assessment and tradespace analysis tool as a successor to the Integrated Medical Model. This updated decision support tool is known as IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). IMPACT estimates the frequency and consequences of medical conditions that might arise during exploration missions. A validation analysis of IMPACT was performed with respect to a set of International Space Station (ISS) and Shuttle Transportation System (STS) real world system (RWS) referent data due to the limited referent data available from exploration missions. Methods Observed mission and crew characteristics from STS and ISS missions were used as model inputs within MEDPRAT (Medical Extensible Dynamic Probabilistic Risk Assessment Tool). For each mission, two hundred thousand simulations were generated. For each mission, model outputs included occurrence counts for each condition, total medical events (TME), and the probability of loss of crew life (LOCL). These simulated model outputs were compared to the RWS referent data. Results The predicted number of total medical events exceeded the total RWS medical events for ISS missions and combined ISS and STS missions and fell within the 90% confidence interval for STS missions. For the 32 ISS missions simulated by IMPACT, the number of total medical events was overpredicted for 19 missions and fell within the 90% confidence interval for 13 missions. For the 21 STS missions, the total number of medical events was overpredicted for 3 missions, fell within the 90% confidence interval for 16 missions, and was underpredicted for 2 missions. Combined, 29 missions were in range, 22 were overpredicted, and 2 were underpredicted. The predicted LOCL probability for the 32 ISS missions, the 21 STS missions, and the combined ISS and STS missions was consistent with the zero LOCL events observed in the RWS referent data. The validation analysis included a comparison of the number of medical events predicted by IMPACT and the number of medical events observed in the RWS data on a condition-by-condition basis. For ISS missions, 50 conditions were in range, 52 conditions were statistically underpowered (not enough observed sample to draw any conclusions on precision), 8 conditions were overpredicted, and 9 conditions were underpredicted. Overall, only 14% (17/119) of conditions were out of range for STS missions, 40 conditions were in range, 59 conditions were statistically underpowered, 10 conditions were overpredicted, and 10 conditions were underpredicted. Overall, only 17% (20/119) of conditions were out of range. For combined ISS and STS missions, 11 conditions were overpredicted, and 11 conditions were underpredicted. Overall, only 18% (22/119) of conditions were out of range. For combined ISS and STS missions, 49 conditions were in range, 46 conditions were statistically underpowered, 18 conditions were overpredicted, and 8 conditions were underpredicted. Overall, 21% (26/121) of conditions were out of range. Conclusion The results of this validation analysis should not be interpreted as a pass/fail test of the validity of IMPACT. Instead, this validation analysis should be used to assess some of the IMPACT outcomes in terms of consistencies and inconsistencies with the ISS and STS RWS referent data.

L. Boley↗
NASA NTRS2024

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVA on the Moon and Mars are expected to be higher compared to microgravity EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We used the applied cognitive task analysis method as outlined by Militello and Hutton (1998) and conducted interviews with subject matter experts (SMEs) in EVA at NASA Johnson Space Center in summer 2024. Interviews focused on exploration EVA and elicited feedback from SMEs on the cognitive skills required for specific EVA tasks including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis will inform ongoing work to identify the key cognitive domains for safe decision-making during exploration mission class EVA on the Moon and Mars. This work will importantly provide a link between cognitive domains identified in the cognitive task analysis and operationally-relevant performance metrics collected during spaceflight and simulation EVA that can be tracked and assessed by NASA mission operations. Ultimately, this work will aid in the development and application of exploration class cognitive performance monitoring capabilities to improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗
DOE OSTI2021

Quantifying Rooftop Solar Benefits: A State-Level Value of Solar Analysis for India

Analyses that quantify the costs and benefits associated with rooftop solar (RTS) adoption and operation can inform decision-makers in the development and evaluation of RTS policies. One such analysis is a Value of Solar (VOS) study, which quantifies select costs and benefits surrounding RTS based on the electricity system context. These studies can drive changes to existing policies towards fairer, more cost-reflective RTS compensation or alternatively can provide confidence for the decision-maker to stay the course and largely maintain existing policies. This report provides a VOS analysis for two states in India: Gujarat and Jharkhand and provides details related to the methodology and key findings.

14 SOLAR ENERGY↗
NASA NTRS2024

Single Drop Cytometry Onboard the International Space Station

Real-time lab analysis is needed to support clinical decision making and research on human missions to the Moon and Mars. Powerful laboratory instruments, such as flow cytometers, are generally too cumbersome for spaceflight. Here, we show that scant test samples can be measured in microgravity, by a trained astronaut, using a miniature cytometry-based analyzer, the rHEALTH ONE, modified specifically for spaceflight. The base device addresses critical spaceflight requirements including minimal resource utilization and alignment-free optics for surviving rocket launch. To fully enable reduced gravity operation onboard the space station, we incorporated bubble-free fluidics, electromagnetic shielding, and gravity-independent sample introduction. We show microvolume flow cytometry from 10 μL sample drops, with data from five simultaneous channels using 10 μs bin intervals during each sample run, yielding an average of 72 million raw data points in approximately 2 minutes. We demonstrate the device measures each test sample repeatably, including correct identification of a sample that degraded in transit to the International Space Station. This approach can be utilized to further our understanding of spaceflight biology and provide immediate, actionable diagnostic information for management of astronaut health without the need for Earth-dependent analysis.

Daniel J. Rea↗
DOE OSTI2026

First Solar Thermal Energy Planner (STEP 1) and Nationwide Industrial Heat and Power Analysis

The First Solar Thermal Energy Planner (STEP 1) and Nationwide Industrial Heat and Power Analysis (aka the STEP 1 Project or the Project) aimed to (1) developed a brand-new web tool that could provide decision support through free, rapid techno-economic analysis of behind-the-meter solar+storage systems for industrial process heat and (2) conduct high-level analyses of the cost-competitiveness of the same systems across the US in key sectors. The STEP 1 web tool collects key location, land availability, thermal load profile, proccess heat temperature and media, and other key parameters through an easy-to-use user interface (UI). The UI was designed to meet the user at their level of understanding by minimizing the number of required inputs as much as possible while including options for more nuanced inputs if the user desires. STEP 1 advises users on which solar thermal tehcnologies that could fit their needs based on the inputs provided (namely process media and temperature). The tool can model a wide range of solar thermal technologies including flat plate collectors, evacuated tubes, parabolic troughs, linear Fresnel, and molten salt towers all with corresponding thermal energy storage (TES) - solar PV with resistive heating and TES is also included. Once the parameters are collected, a nominal thermal energy production profile for the facility's location is generated using NREL's System Advisory Model (SAM) and then passed to a modified version of NREL's REopt platform to optimize the size (capacity) and dispatch of the solar+storage system to minimize lifecycle costs subject to energy balance, fuel and electricity rates, emission reductions goals, and other constraints. This entire process takes less than 20 minutes, is completely free, requires zero coding skills, and provides the user with a high-level assessment on the techno-economic feasability of deploying solar+storage systems for their energy needs. In addition to the development of the STEP 1 web tool, the project completed two complementary analyses focused on leveraging the backend code of STEP 1, public industrial facility locations and fuel consumption data, and key sector information to assess the economic opportunity of reducing fuel costs at various levels of capacity factor around the US. Both analyses found that there are key markets, locations, industrial sectors (namely food and beverage), and degrees of offset where solar thermal technologies could be cost-effectively deployed, highlighting a key market entry point for these technologies, and assessing deployment potential. In summary, the STEP 1 project improved the opportunities for solar+storage systems to expand into the industrial process heat market through breaking down barriers to assessing these technologies.

14 SOLAR ENERGY↗
NASA NTRS2020

Mechanics-Based Modeling Approach for Rapid Prediction of Low Velocity Impact Damage in Composite Laminates

A mechanics-based modeling approach is developed to rapidly predict damage in polymer matrix composites resulting from a low velocity impact event. The approach is incorporated into a computer code that provides an efficient means to assess the damage resistance for a range of material systems, layup configurations, and impact scenarios. It is envisioned that the developed approach will aid in early design and analysis of composite structures where sizing and layup decisions must be made, and evaluating the feasibility of a large number of laminate configurations using numerical approaches such as finite element analysis (FEA) is prohibitively expensive. Therefore, the goal of the modeling approach is to predict the impact damage size given the laminate configuration and impact scenario. This information can then be used to determine the residual strength of the material. To be useful in such a context, the tool is designed to run quickly (<2 minutes) to allow a large number of design cases to be investigated. The results presented demonstrate that the model is capable of efficiently predicting low velocity impact damage size, shape, and location within an acceptable accuracy suitable for preliminary design and analysis of composite structures.

Borkowski, Luke↗
DOE OSTI2020

Risk Informed, Performance-Based, Technology-Inclusive Regulatory Infrastructure: Technology-Inclusive Determination of Mechanistic Source Terms for Offsite Dose-Related Assessments for Advanced Nuclear Reactor Facilities

This report summarizes a risk informed, performance-based and technology-inclusive approach to determine source terms for dose related assessments at advanced nuclear facilities. This approach uses a graded process which allows both the non-mechanistic source terms calculation methods, which adopt conservative approaches and assumptions based on known physical and chemical principles, and more importantly the mechanistic source term calculation methods, which consider design-specific scenarios and use best estimate models with uncertainty quantification for a range of licensing basis events (LBEs), to be used for the design and licensing of advanced nuclear technologies. The source terms developed with this graded approach, and radionuclide inventories elsewhere in the facility that are determined during source term analysis, can be used to address licensing issues to support the application processes of 10 CFR Part 50 for a construction permit and operating license or 10 CFR Part 52 for a Combined Operating License (COL), Standard Design Certification, Early Site Permit, Standard Design Approval or Manufacturing License. They can also be used for other purposes including equipment environmental qualification, control room habitability analyses, and assessments of severe accident risks in environmental impact statements. There are many advanced reactor concepts being developed including high temperature gas-cooled reactor (HGTR), sodium-cooled fast reactor (SFR), lead-cooled fast reactor (LFR), molten salt reactor (MSR), micro-reactor, etc. The graded approach presented in this report for source terms determination is, to the extent possible, generic to any of these reactor designs and to future reactor designs. This report provides information on the review of the regulatory foundation for use of conservative bounding source terms as well as event-specific mechanistic source terms for advanced nuclear reactor designs.

07 ISOTOPE AND RADIATION SOURCES↗