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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Measurement Requirements for Improved Modeling of Arcjet Facility Flows

Current efforts to develop new reusable launch vehicles and to pursue low-cost robotic planetary missions have led to a renewed interest in understanding arc-jet flows. Part of this renewed interest is concerned with improving the understanding of arc-jet test results and the potential use of available computational-fluid- dynamic (CFD) codes to aid in this effort. These CFD codes have been extensively developed and tested for application to nonequilibrium, hypersonic flow modeling. It is envisioned, perhaps naively, that the application of these CFD codes to the simulation of arc-jet flows would serve two purposes: first. the codes would help to characterize the nonequilibrium nature of the arc-jet flows; and second. arc-jet experiments could potentially be used to validate the flow models. These two objectives are, to some extent, mutually exclusive. However, the purpose of the present discussion is to address what role CFD codes can play in the current arc-jet flow characterization effort, and whether or not the simulation of arc-jet facility tests can be used to eva1uate some of the modeling that is used to formu1ate these codes. This presentation is organized into several sections. In the introductory section, the development of large-scale, constricted-arc test facilities within NASA is reviewed, and the current state of flow diagnostics using conventional instrumentation is summarized. The motivation for using CFD to simulate arc-jet flows is addressed in the next section, and the basic requirements for CFD models that would be used for these simulations are briefly discussed. This section is followed by a more detailed description of experimental measurements that are needed to initiate credible simulations and to evaluate their fidelity in the different flow regions of an arc-jet facility. Observations from a recent combined computational and experiment.al investigation of shock-layer flows in a large-scale arc-jet facility are then used to illustrate the current state of development of diagnostic instrumentation, CFD simulations, and general knowledge in the field of arc-jet characterization. Finally, the main points are summarized and recommendations for future efforts are given.

Fletcher, Douglas G.↗
NASA NTRS1998

Executive Summary: Special Section on Credible Computational Fluid Dynamics Simulations

This summary presents the motivation for the Special Section on the credibility of computational fluid dynamics (CFD) simulations, its objective, its background and context, its content, and its major conclusions. Verification and validation (V&V) are the processes for establishing the credibility of CFD simulations. Validation assesses whether correct things are performed and verification assesses whether they are performed correctly. Various aspects of V&V are discussed. Progress is made in verification of simulation models. Considerable effort is still needed for developing a systematic validation method that can assess the credibility of simulated reality.

Mehta, Unmeel B.↗
NASA NTRS2008

Dimensions of Credibility in Models and Simulations

Based on the National Aeronautics and Space Administration's (NASA's) work in developing a standard for models and simulations (M&S), the subject of credibility in M&S became a distinct focus. This is an indirect result from the Space Shuttle Columbia Accident Investigation Board (CAIB), which eventually resulted in an action, among others, to improve the rigor in NASA's M&S practices. The focus of this action came to mean a standardized method for assessing and reporting results from any type of M&S. As is typical in the standards development process, this necessarily developed into defming a common terminology base, common documentation requirements (especially for M&S used in critical decision making), and a method for assessing the credibility of M&S results. What surfaced in the development of the NASA Standard was the various dimensions credibility to consider when accepting the results from any model or simulation analysis. The eight generally relevant factors of credibility chosen in the NASA Standard proved only one aspect in the dimensionality of M&S credibility. At the next level of detail, the full comprehension of some of the factors requires an understanding along a couple of dimensions as well. Included in this discussion are the prerequisites for the appropriate use of a given M&S, the choice of factors in credibility assessment with their inherent dimensionality, and minimum requirements for fully reporting M&S results.

Steele, Martin J.↗
NASA NTRS2007

An Approach to Improved Credibility of CFD Simulations for Rocket Injector Design

Computational fluid dynamics (CFD) has the potential to improve the historical rocket injector design process by simulating the sensitivity of performance and injector-driven thermal environments to. the details of the injector geometry and key operational parameters. Methodical verification and validation efforts on a range of coaxial injector elements have shown the current production CFD capability must be improved in order to quantitatively impact the injector design process.. This paper documents the status of an effort to understand and compare the predictive capabilities and resource requirements of a range of CFD methodologies on a set of model problem injectors. Preliminary results from a steady Reynolds-Average Navier-Stokes (RANS), an unsteady Reynolds-Average Navier Stokes (URANS) and three different Large Eddy Simulation (LES) techniques used to model a single element coaxial injector using gaseous oxygen and gaseous hydrogen propellants are presented. Initial observations are made comparing instantaneous results, corresponding time-averaged and steady-state solutions in the near -injector flow field. Significant differences in the flow fields exist, as expected, and are discussed. An important preliminary result is the identification of a fundamental mixing mechanism, accounted for by URANS and LES, but missing in the steady BANS methodology. Since propellant mixing is the core injector function, this mixing process may prove to have a profound effect on the ability to more correctly simulate injector performance and resulting thermal environments. Issues important to unifying the basis for future comparison such as solution initialization, required run time and grid resolution are addressed.

Tucker, Paul K.↗
NASA NTRSDate not supplied

Development and Future of the Ten Simple Rules for Credible Practice of Models and Simulations in HealthCare

In this session, we will review the development and implementation history of the Ten Simple Rules (TSR) for credible practice in models and simulations that support healthcare. Our focus will be initially on the need and background for the Committee on Credible Practice of Models and Simulations in Healthcare (CPMS) as well as the TSR development process and implementation. This will flow into a demonstration of how the TSR has evolved as means of communicating and understanding the model development process, likely successful application and where the model could fail. We will end this presentation with a discussion on future development avenue, the CPMS efforts to develop a comprehensive rubric supporting current TSR implementation, and efforts to support further adoption of the TSR. The audience will be encouraged to comment on the current state of the TSR, share their TSR application experiences, and provide their insights on future development.

model↗
NASA NTRS2020

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Credibility↗
NASA NTRS2008

Towards a Credibility Assessment of Models and Simulations

A scale is presented to evaluate the rigor of modeling and simulation (M&S) practices for the purpose of supporting a credibility assessment of the M&S results. The scale distinguishes required and achieved levels of rigor for a set of M&S elements that contribute to credibility including both technical and process measures. The work has its origins in an interest within NASA to include a Credibility Assessment Scale in development of a NASA standard for models and simulations.

Blattnig, Steve R.↗
NASA NTRSDate not supplied

Credible Practice of Models and Simulations for Healthcare

As computational models penetrate clinical care and drive healthcare policy decisions, there is increasing need to communicate that model creation and testing follows reasonable credible practice. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. This presentation introduces the Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative multidisciplinary analysis and practitioner survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. Although some of these are common sense guidelines, many are often missed or misconstrued, even by seasoned practitioners.

credibility↗
DOE OSTI2026

From models to reality: a systematic review on simulated and measured residential heat pump energy savings

High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower than measured EUIs, but percentage energy savings fall in similar ranges, implying simulations capture directional effects while underestimating energy use. Factors associated with variability and model–measurement differences include system characterization and control representation (e.g., backup heat engagement, thermostat/setpoint strategies, commissioning/installation quality), occupant behavior, weather normalization, metering scope, and envelope characterization. This paper also outlines the proposed methodology for comparing simulation and measured data for heat pumps. It emphasizes the metrics used for comparison and units harmonization, building characteristics matching, and compact metadata are needed for simulations to match measured data. The proposed methodology is expected to improve the credibility of simulated savings as measured evidence grows.

Yu, Lili↗
NASA NTRS1995

Verification and Validation of Simulation Models for High-Speed Flow Fields

This paper is largely based on the paper titled "Guide to Credible Computational Fluid Dynamics Simulations (Invited)" (AIAA Paper 95-2225). The significance of computational fluid dynamics (CFD) simulations depends solely on their credibility. A customer of CFD products -- simulations and software -- expects that these products are credible for the intended use. Simulation model verification and validation are critical in establishing the credibility of simulations and in certifying simulation software. The only thing that matters in establishing the credibility is uncertainty, not veracity or validity. The sensitivity-uncertainty analysis is the key to the establishment of this credibility. Assessing the credibility of complex simulation results poses a significant challenge. Terminology, concepts, framework, and guidelines are presented for addressing this challenge. Verification assesses whether the problem is solved correctly and estimates the level of computational accuracy of simulations; validation determines whether the right problem is solved and assesses the level of validity of the simulation model by estimating the degree to which simulations accurately represent reality. These concepts and the related guidelines are discussed with examples from high-speed flow fields.

Mehta, Unmeel B.↗
NASA NTRS2010

The Continual Intercomparison of Radiation Codes (CIRC) Assessing Anew the Quality of GCM Radiation Algorithms

The simulation of changes in the Earth's climate due to solar and thermal radiative processes with global climate models (GCMs) is highly complex, depending on the parameterization of a multitude of nonlinearly coupled physical processes. In contrast, the germ of global climate change, the radiative forcing from enhanced abundances of greenhouse gases, is relatively well understood. The impressive agreement between detailed radiation calculations and highly resolved spectral radiation measurements in the thermal infrared under cloudless conditions (see, for example, Fig. 1) instills confidence in our knowledge of the sources of gaseous absorption. That the agreement spans a broad range of temperature and humidity regimes using instruments mounted on surface, aircraft, and satellite platforms not only attests to our capability to accurately calculate radiative fluxes under present conditions, but also provides confidence in the spectroscopic basis for computation of fluxes under conditions that might characterize future global climate (e.g., radiative forcing). Alas, the computational costs of highly resolved spectral radiation calculations cannot be afforded presently in GCMs. Such calculations have instead been used as the foundation for approximations implemented in fast but generally less accurate algorithms performing the needed radiative transfer (RT) calculations in GCMs. Credible climate simulations by GCMs cannot be ensured without accurate solar and thermal radiative flux calculations under all types of sky conditions: pristine cloudless, aerosol-laden, and cloudy. The need for accuracy in RT calculations is not only important for greenhouse gas forcing scenarios, but is also profoundly needed for the robust simulation of many other atmospheric phenomena, such as convective processes.

Oreopoulos, Lazaros↗
NASA NTRS2005

Impact of Lunar Dust on the Exploration Initiative

From the Apollo era it is known that dust on the Moon can cause serious problems for exploration activities. Such problems include adhering to clothing and equipment, reducing external visibility on landings, and causing difficulty to breathing and vision within the spacecraft. An important step in dealing with dust-related problems is to understand how dust grains behave in the lunar environment. All astronauts who walked on the Moon reported difficulties with lunar dust. Eugene Cernan, commander of Apollo 17, stated that one of the most aggravating, restricting facets of lunar surface exploration is the dust and its adherence to everything no matter what kind of material, whether it be skin, suit material, metal, no matter what it be and it's restrictive friction-like action to everything it gets on. Dust has also been highlighted as a priority by the Mars Exploration Program Assessment Group (MEPAG): 1A. Characterize both aeolian dust and particulates that would be kicked up from the martian regolith by surface operations of a human mission with fidelity sufficient to establish credible engineering simulation labs and/or software codes on Earth. We shall briefly describe the properties of lunar dust and its impact on the Apollo astronauts, and then summarize three main problems areas for understanding its behavior: Dust Adhesion and Abrasion, Surface Electric Fields and Dust Transport. These issues are all inter-related and must be well understood in order to minimize the impact of dust on lunar surface exploration.

Stubbs, T. J.↗
NASA NTRS2004

Evaluating the Credibility of Transport Processes in Simulations of Ozone Recovery using the Global Modeling Initiative Three-dimensional Model

The Global Modeling Initiative (GMI) has integrated two 36-year simulations of an ozone recovery scenario with an offline chemistry and tra nsport model using two different meteorological inputs. Physically ba sed diagnostics, derived from satellite and aircraft data sets, are d escribed and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barri er formation in the subtropics and polar regions, and extratropical w ave-driven transport. Some diagnostics are especially relevant to sim ulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The global temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of me teorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a g eneral circulation model (GMI(GCM)) showed a very good residual circulation in the tropics and Northern Hemisphere. The simulation with inp ut from a data assimilation system (GMI(DAS)) performed better in the midlatitudes than it did at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GML(GCM) has greater fidelity throughout the stratosphere tha n it does in the GMI(DAS)

Strahan, Susan E.↗
NASA NTRS2015

Credibility Assessment of Deterministic Computational Models and Simulations for Space Biomedical Research and Operations

Human missions beyond low earth orbit to destinations, such as to Mars and asteroids will expose astronauts to novel operational conditions that may pose health risks that are currently not well understood and perhaps unanticipated. In addition, there are limited clinical and research data to inform development and implementation of health risk countermeasures for these missions. Consequently, NASA's Digital Astronaut Project (DAP) is working to develop and implement computational models and simulations (M&S) to help predict and assess spaceflight health and performance risks, and enhance countermeasure development. In order to effectively accomplish these goals, the DAP evaluates its models and simulations via a rigorous verification, validation and credibility assessment process to ensure that the computational tools are sufficiently reliable to both inform research intended to mitigate potential risk as well as guide countermeasure development. In doing so, DAP works closely with end-users, such as space life science researchers, to establish appropriate M&S credibility thresholds. We will present and demonstrate the process the DAP uses to vet computational M&S for space biomedical analysis using real M&S examples. We will also provide recommendations on how the larger space biomedical community can employ these concepts to enhance the credibility of their M&S codes.

Mulugeta, Lealem↗
NASA NTRSDate not supplied

Evaluating the Feasibility of Data Simulation for Radiation Research: Estimating RBE Values for HZE Radiation

As the drive for deep space exploration intensifies, a comprehensive understanding of the health effects of radiation exposure becomes paramount to the future of human space flight. However, epidemiological data for radiation exposure, particularly to high-energy (HZE) ions, is limited, partially due to the financial and logistical costs of radiation studies. As an alternative, this study aims to assess the viability of data simulation strategies to accurately model potential study parameters prior to utilizing laboratory conditions. This study estimates a relative biological effectiveness (RBE) factor based on the solid tumor data for outbred mice provided by Edmundson et al. 2020. Excess relative risk (ERR) models for HZE-Fe ions and gamma radiation were estimated using Poisson regression with Weibull models to represent the background solid tumor hazard without radiation. RBE values were calculated from the ratio of the heavy ion linear slope to the gamma linear slope. The parameters from these models were then applied to simulate iterations of 300 datasets across HZE-Fe doses of 0.05, 0.2, 0.4, and 0.75 Gy; gamma radiation doses of 0.75, 2, and 3 Gy, as well as an unirradiated control group. Sample size per dose varied from 100-500 mice across simulations (800-4000 mice total per dataset). 1500 datasets were generated total (300 each for sample sizes 800, 1600, 3200, and 4000). For each dataset, ERR per radiation type and RBE for HZE-Fe were calculated. The RBE from the Edmondson data was calculated to be 5.55. The RBEs from the simulated data converged around this value across the increasing sample sizes. For n = 4000, the mean RBE across the 300 datasets was 5.71 (95% CI: 5.47-5.95). These results suggest that RBEs calculated from simulated data are credible. Based on this exploration, data simulation is a viable method of testing radiation studies. It provides a method of testing study assumptions and refining research questions prior to embarking on costly laboratory experiments.

Sneha Mehta↗
NASA NTRS1978

Numerical derivation of linear perturbation model from nonlinear real-time vehicle simulations - A means of validation and increased credibility

A numerical technique has been developed which generates linear perturbation models from nonlinear real-time aircraft vehicle simulations at Langley Research Center. The technique is very general and can be applied to simulations of any system described by nonlinear differential equations. Linear models about various trim conditions have been obtained from simulations of the Boeing 737, Northrop F5-E, Cessna 180, Sikorsky CH-54, and NASA/Army Rotor Systems Research Aircraft (RSRA). One use of the derived linear models is as a validation and verification tool for the nonlinear simulation.

Dieudonne, J. E.↗
DOE OSTI2024

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗