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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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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Novel artificial neural network model for instantaneous power losses and operational efficiency mapping of MW-scale vanadium redox flow battery for improved technoeconomic analysis

A novel data-driven, machine-learning-based method for modeling the instantaneous power losses of a distribution-sited 2 MW/8MWh vanadium redox flow battery (VRFB), a grid-scale electrochemical storage technology, is introduced and compared against benchmark empirical modeling approaches, including symmetric and asymmetric models, as well as a recent convex hull modeling approach. The novel loss modeling method introduces several advantages over the benchmark models and over simplistic efficiency estimates, the most significant of which is that the model can accurately reflect the stepwise and non-linear parasitic losses associated with the duty cycles of mechanical auxiliary systems like pump motor drives and blower fans. Residuals of the models are compared; the proposed data driven model features significantly improved accuracy over the benchmark models. The model's coefficient of determination is also improved relative to that of the benchmark models. Furthermore, a novel method for visualization of operational efficiency of the grid-scale storage technology is introduced. To demonstrate the benefits of the novel data-driven method for modeling the VRFB, the benchmark models and the proposed models are embedded into an Open DSS distribution network model to study two applications of the grid-scale electrical storage system: load leveling for grid support and energy arbitrage. This article demonstrates that the accuracy of the instantaneous power loss model significantly impacts the understanding of the state of charge of the VRFB. In turn, the accuracy of the efficiency modeling of the VRFB impacts the understanding of the potential economic value and technical benefits to the distribution network operators. In conclusion, the presented power loss modeling approach is, therefore, highly relevant for utility-stakeholders, battery asset owners, system engineers, system designers, and financial planners interested in evaluating or optimizing the operation of grid-scale VRFBs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1985

Multidimensional Modeling of Atmospheric Effects and Surface Heterogeneities on Remote Sensing

The overall goal of this project is to establish a modeling capability that allows a quantitative determination of atmospheric effects on remote sensing including the effects of surface heterogeneities. This includes an improved understanding of aerosol and haze effects in connection with structural, angular, and spatial surface heterogeneities. One important objective of the research is the possible identification of intrinsic surface or canopy characteristics that might be invariant to atmospheric perturbations so that they could be used for scene identification. Conversely, an equally important objective is to find a correction algorithm for atmospheric effects in satellite-sensed surface reflectances. The technical approach is centered around a systematic model and code development effort based on existing, highly advanced computer codes that were originally developed for nuclear radiation shielding applications. Computational techniques for the numerical solution of the radiative transfer equation are adapted on the basis of the discrete-ordinates finite-element method which proved highly successful for one and two-dimensional radiative transfer problems with fully resolved angular representation of the radiation field.

Gerstl, S. A. W.↗
NASA NTRS1995

Development of a model protection and dynamic response monitoring system for the national transonic facility

A state-of-the-art, computerized mode protection and dynamic response monitoring system has been developed for the NASA Langley Research Center National Transonic Facility (NTF). This report describes the development of the model protection and shutdown system (MPSS). A technical description of the system is given along with discussions on operation and capabilities of the system. Applications of the system to vibration problems are presented to demonstrate the system capabilities, typical applications, versatility, and investment research return derived from the system to date. The system was custom designed for the NTF but can be used at other facilities or for other dynamic measurement/diagnostic applications. Potential commercial uses of the system are described. System capability has been demonstrated for forced response testing and for characterizing and quantifying bias errors for onboard inertial model attitude measurement devices. The system is installed in the NTF control room and has been used successfully for monitoring, recording and analyzing the dynamic response of several model systems tested in the NTF.

Young, Clarence P., Jr.↗
DOE OSTI2025

FAIR Surrogate Benchmarks Supporting AI and Simulation Research (Final Report)

Computational Science is being revolutionized by integrating AI and simulation and, in particular, by deep learning surrogate models that can replace all or part of traditional large‐scale HPC computations. Such surrogates can achieve remarkable performance improvements, as much as several orders of magnitude, and save both compute time and energy. The Surrogate Benchmark Initiative (SBI) project creates a community repository and FAIR (Findable, Accessible, Interoperable, and Reusable) data ecosystem for HPC application surrogate benchmarks. The SBI team comes from Argonne National Laboratory (ANL), Indiana University (IU), Rutgers University, the University of Tennessee, Knoxville (UTK), and the University of Virginia (UVA). SBI repositories include data, code, and all relevant collateral artifacts that the science and engineering community need to use and reuse these data sets and surrogates. SBI repositories generate active research from both the participants in SBI and the broad community of AI and domain scientists. This project develops surrogates that use several different neural nets to learn and quickly infer the results of simulations and data systems and captures them as surrogate benchmarks with a rich set of metadata covering: Data; Model; Metrics specification; Machine specification; and Science, Speed, and Power Results. We research FAIR metadata for these benchmarks. We develop application surrogate examples as benchmarks across many fields (ANL, UTK, IU, UVA). We also study non-Surrogate benchmarks that have many common features and similar issues as regards FAIRness. We work with MLCommons (UVA, UTK), which is a major machine learning benchmarking activity where we get metadata ontologies, software, and benchmarks, Benchmarks have datasets, models, and metadata and they need a technical framework developed by UTK and Rutgers and deployed by UVA. We study features of Surrogates including performance, training set size, and uncertainty quantification (Rutgers, UVA and IU).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model

In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilation (DA) techniques have grown in importance for improving these fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model parameter values while also pinpointing possible parameterization deficiencies. Although the joint assimilation of multiple data streams is expected to constrain a wider range of model processes, their actual benefits in terms of reduction in model uncertainty are still under-researched, also given the technical challenges. In this study, we investigated with a consistent DA framework and the ORCHIDEE-LMDz TBM–atmosphere model how the assimilation of different combinations of data streams may result in different regional to global carbon budgets. To do so, we performed comprehensive DA experiments where three datasets (in situ measurements of net carbon exchange and latent heat fluxes, spaceborne estimates of the normalized difference vegetation index, and atmospheric CO 2 concentration data measured at stations) were assimilated alone or simultaneously. We thus evaluated their complementarity and usefulness to constrain net and gross C land fluxes. We found that a major challenge in improving the spatial distribution of the land C sinks and sources with atmospheric CO 2 data relates to the correction of the soil carbon imbalance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Combined TREAT-LOC & SATS Integral LOCA Experiment Plan

The Transient Reactor Test Facility (TREAT) loss-of-coolant (LOC) and highburnup (HBu) experiment series, along with the Severe Accident Test Station (SATS) HBu experiment series, are integral LOC accident (LOCA) experiments planned under the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program, which aims to support burnup extension needs by addressing identified R&D priorities in order to achieve an improved understanding of fuel fragmentation, relocation, and dispersal (FFRD) of HBu fuel during LOCA events. Priorities have been identified by the Electric Power Research Institute (EPRI)’s Collaborative Research on Advanced Fuel Technologies (CRAFT) Fuel Performance and Testing Technical Experts Group (FPTTEG). The data produced under this plan will be used to further validate and confirm existing models and inform future R&D and model development. The experimental program was specifically developed to address data gaps and opportunities identified via detailed review of the existing public knowledge base on LOCA FFRD, as well as reviewing specific experimental development activities regarding prototypic LOCA conditions for light-water reactor (LWR) systems. The test program relies on a unique combination of in- and out-of-pile experimental approaches to provide a clear tieback to the existing integral and semi-integral LOCA experiment database, using state-of-the-art facilities. More importantly, the program will systematically investigate the impacts of prototypic HBu fuel/cladding thermomechanical behaviors under postulated LWR LOCA conditions not yet fully investigated. These conditions correspond with prototypic decay-energy heatup (DEH) and stored-energy heatup (SEH) conditions. First, TREAT’s unique capability will enable the first evaluation of the impact of SEH conditions on HBu fuels. The test program will emphasize the development of an improved mechanistic understanding of key phenomena through independent experimental systems, development of a database to support fuel performance modeling tools, world-leading advanced materials characterization, and the most advanced approach to in situ diagnostics ever deployed to evaluate FFRD. The results will represent a significant leap forward in evaluating prototypic conditions and novel data to support modeling development and validation, as well as to inform the technical basis for LOCA-induced FFRD.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1996

Application of the pressure sensitive paint technique to steady and unsteady flow

Pressure sensitive paint is a newly-developed optical measurement technique with which one can get a continuous pressure distribution in much shorter time and lower cost than a conventional pressure tap measurement. However, most of the current pressure sensitive paint applications are restricted to steady pressure measurement at high speeds because of the small signal-to-noise ratio at low speed and a slow response to pressure changes. In the present study, three phases of work have been completed to extend the application of the pressure sensitive paint technique to low-speed testing and to investigate the applicability of the paint technique to unsteady flow. First the measurement system using a commercially available PtOEP/GP-197 pressure sensitive paint was established and applied to impinging jet measurements. An in-situ calibration using only five pressure tap data points was applied and the results showed good repeatability and good agreement with conventional pressure tap measurements on the whole painted area. The overall measurement accuracy in these experiments was found to be within 0.1 psi. The pressure sensitive paint technique was then applied to low-speed wind tunnel tests using a 60 deg delta wing model with leading edge blowing slots. The technical problems encountered in low-speed testing were resolved by using a high grade CCD camera and applying corrections to improve the measurement accuracy. Even at 35 m/s, the paint data not only agreed well with conventional pressure tap measurements but also clearly showed the suction region generated by the leading edge vortices. The vortex breakdown was also detected at alpha=30 deg. It was found that a pressure difference of 0.2 psi was required for a quantitative pressure measurement in this experiment and that temperature control or a parallel temperature measurement is necessary if thermal uniformity does not hold on the model. Finally, the pressure sensitive paint was applied to a periodically changing pressure field with a 12.8s time period. A simple first-order pole model was applied to deal with the phase lag of the paint. The unsteady pressure estimated from the time-changing pressure sensitive paint data agreed well with the pressure transducer data in regions of higher pressure and showed the possibility of extending the technique to unsteady pressure measurements. However, the model still needs further refinement based on the physics of the oxygen diffusion into the paint layer and the oxygen quenching on the paint luminescence.

Shimbo, Y.↗
DOE OSTI2024

Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study

Although considerable laboratory and modeling activities were performed to investigate the enhanced oil recovery (EOR) mechanisms and potential in unconventional reservoirs, only limited research has been reported to investigate actual EOR implementations and their surveillance in fields. Eleven EOR pilot tests that used CO2, rich gas, surfactant, water, etc., have been conducted in the Bakken unconventional play since 2008. Gas injection was involved in eight of these pilots with huff ‘n’ puff, flooding, and injectivity operations. Surveillance data, including daily production/injection rates, bottomhole injection pressure, gas composition, well logs, and tracer testing, were collected from these tests to generate time-series plots or analytics that can inform operators of downhole conditions. A technical review showed that pressure buildup, conformance issues, and timely gas breakthrough detection were some of the main challenges because of the interconnected fractures between injection and offset wells. The latest operation of co-injecting gas, water, and surfactant through the same injection well showed that these challenges could be mitigated by careful EOR design and continuous reservoir monitoring. Reservoir simulation and machine learning were then conducted for operators to rapidly predict EOR performance and take control actions to improve EOR outcomes in unconventional reservoirs.

Energy & Fuels↗
DOE OSTI2022

Optimized Machine Learning Model for Predicting Groundwater Contamination

The use of physical models to predict groundwater contaminant movement remains technically challenging due to the complexity of the phenomena, the heterogeneity of key parameters in nature, and the presence of poorly defined interactive and feedback processes. New approaches to address these challenges are needed. In this study, we evaluate various Artificial Intelligence (AI)-based approaches to understand a hexavalent chromium (Cr(VI)) plumes located on the U.S. Department of Energy’s (DOE) Hanford Site in Richland, WA. The groundwater monitoring dataset used in this study included data from the 100 Area along the Columbia River and included data collected between 2010 to 2019. This study investigates the most prominent contaminant, Cr(VI), with the Extreme Gradient Boosting (XGBoost) machine learning model. The XGBoost models were compared with optimized versions using an Empirical Bayes Search Cross-Validation technique for better prediction. The optimized XGBoost model yielded an R^2 value of 0.99 on the training set and 0.85 on the testing set, whereas XGBoost without optimization yielded a value of 0.83 on the training set and 0.85 on the testing set. This paper provides an overview of a computational method for groundwater contamination modeling that shows promise for improving current remediation efforts.

Mazumdar, Hirak↗
NASA NTRS2016

Low Ozone over Europe Doesn't Mean the Sky Is Falling, Its Actually Rising

Data Sources: NASA Aura Microwave Limb Sounder (MLS) (O3 profiles and columns), NASA Global Modeling Initiative (GMI) Chemistry and Transport Model (calculated O3depletion), and MERRA Tropopause Heights. Technical Description of Figures: The left graphics show MLS northern hemisphere stratospheric column ozone on Feb. 1, 2016. Very low columns are seen over the UK and Europe (<225 DU, inside dashed circle). The lower graphic shows the GMI-calculated O3 depletion. It's very small, suggesting the low O3 does not indicate significant depletion. The right graphics show how the high tropopause height in this region explains the observed low ozone. The lower panel shows that the high tropopause on Feb. 1 lifts the O3 profile compared to a typical profile found earlier in winter. This motion lifts the profile to lower pressures thus reducing the total column. The GMI Model shows only 4 Dobson Units (DU) of O3 depletion even though the column is more than 100 DU lower than one month earlier. Scientific significant and societal relevance: To quantitatively understand anthropogenic impacts to the stratospheric ozone layer, we must be able to distinguish between low ozone caused by ozone depleting substances and that caused by natural dynamical variability in the atmosphere. Observations and realistic simulations of atmospheric composition are both required in order to separate natural and anthropogenic ozone variability.

Stratospheric↗
DOE OSTI2019

A New Methodology for Calculating The Energy Performance of Manufacturing Facilities

Total energy comparison (TEC), classic energy intensity (CEI), and linear regression models (LRM) are the three most common approaches used to track the energy performance of manufacturing facilities. TEC simply compares the total energy consumption from utility bills. TEC is rarely used because it does not consider the variation of any factors that may affect energy consumption. One step better, CEI considers the variation of production rates by using the ratio of annual total energy consumption over annual total production. However, CEI fundamentally assumes that energy consumption is zero if the production rate is zero. This is almost never true and can cause significant errors. Using linear regression models, LRM considers the impact of multiple variables and, therefore, most accurately tracks energy performance. Unfortunately, because of the lack of either required data or technical expertise, some facilities cannot create valid linear regression models. For these cases, CEI is the only option. Here, the goal of this article is to develop a new methodology, modified energy intensity (MEI), which is more accurate than CEI, but requires much less data and is easier to implement than LRM. Using the underlying principle of LRM, this article first outlines the mathematical derivation of the equations for MEI, then explains them from an engineering perspective. Finally, the implementation of MEI is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Integrated Hydro-Terrestrial Modeling: Development of a National Capability

Water is one of our most important natural resources and is essential to our national economy and security. Multiple federal government agencies have mission elements that address national needs related to water. Each water-related agency champions a unique science and/or operational mission focused on advancing a portion of the nation’s ability to meet our water-related challenges. These diverse mission needs have engendered a rich and extensive base of water-related data and modeling capabilities. While useful for their intended purposes, these capabilities are not well integrated to address complex regional problems and overarching national problems. These major investments by a number of federal agencies, however, lay the foundation for an integrated hydro-terrestrial modeling and data infrastructure that will enhance knowledge, understanding, prediction, and management of the nation’s diverse water challenges. Creating a more seamless national hydro-terrestrial modeling and data capacity presents an enormous opportunity to advance operational as well as research capabilities leading to more effective water management. Advances are necessary not only in operational tools for forecasting but also in research to identify and resolve knowledge and data gaps that lead to unacceptable uncertainties in forecast outcomes. As such, close coordination across scientific, operational, and resource management communities is required. To this end, an interagency workshop on “Integrated Hydro-Terrestrial Modeling: Development of a National Capacity” was held at the National Science Foundation (NSF) headquarters in Alexandria, Virginia in September 2019, led jointly by the NSF, the U.S. Department of Energy (DOE) and the U.S. Geological Survey (USGS) and with broader interagency support provided through an interagency steering committee. This workshop provided a venue to bring together representatives of water-related agencies and their scientific partners (including university researchers) to initiate and refine a vision for a national Integrated Hydro-Terrestrial Modeling (IHTM) and data infrastructure and advance ideas towards its development. The workshop was designed to address three critical foci to advance the development of a national IHTM capacity: “Priority Water Challenges” around which to motivate and initiate development; Technical and methodological obstacles related to data and modeling; Organizational, structural, and cultural barriers that heretofore have impeded integration of capabilities across the federal and research landscapes. The following “Priority Water Challenge” domain areas represent targets for initiating development of the IHTM and were identified and selected in alignment with priorities of the administration’s Water Sub-Cabinet: (1) Nutrient loading, hypoxia, and harmful algal blooms; (2) Water availability in the western United States; and (3) Extreme weather-related water hazards. These water challenges span agency mission boundaries and encompass a broad range of geographies, complex system dynamics and feedbacks, and critical processes spanning hydrological, climatic, and biophysical systems as well as land-use/land-cover, agricultural, built infrastructure, societal, economic, and decisional environments. These three Priority Water Challenges cannot be fully addressed without leveraging complementary and synergistic capabilities across multiple agencies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Relaxion: A landscape without anthropics

The relaxion mechanism provides a potentially elegant solution to the hierarchy problem without resorting to anthropic or other fine-tuning arguments. This mechanism introduces an axion-like field, dubbed the relaxion, whose expectation value determines the electroweak hierarchy as well as the QCD strong C P -violating θ ¯ parameter. During an inflationary period, the Higgs mass squared is selected to be negative and hierarchically small in a theory which is consistent with ’t Hooft’s technical naturalness criteria. However, in the original model proposed by Graham, Kaplan, and Rajendran, the relaxion does not solve the strong C P problem, and in fact contributes to it, as the coupling of the relaxion to the Higgs field and the introduction of a linear potential for the relaxion produces large strong C P violation. Herein we resolve this tension by considering inflation with a Hubble scale which is above the QCD scale but below the weak scale, and estimating the Hubble temperature dependence of the axion mass. The relaxion potential is thus very different during inflation than it is today. We find that provided the inflationary Hubble scale is between the weak scale and about 3 GeV, the relaxion resolves the hierarchy, strong C P , and dark matter problems in a way that is technically natural.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Central Plateau Vadose Zone Geoframework

The objective of this environmental calculation file (ECF) is to document the revision of the three dimensional (3D) geoframework model (GFM) of the Central Plateau Vadose Zone (CPVZ) on the Hanford Site. CP-60925, Model Package Report: Central Plateau Vadose Zone Geoframework, documents the original version of the CPVZGFM (herein after called the CPVZ-Rev.0) and is the underlying basis for the CPVZ conceptual model. The CPVZ GFM provides a more detailed interpretation of the vadose zone hydrostratigraphic units (HSUs) in the Central Plateau area of the greater Hanford South geoframework model (HSGFM) (ECF-HANFORD-13-0029, Development of the Hanford South Geologic Framework Model, Hanford Site, Washington). The development of the CPVZ GFM provides a consistent vadose zone geologic framework that is needed to support the 3D, multiple-waste-site modeling approach proposed in CP-60405, Hanford Site Composite Analysis Technical Approach Description: Vadose Zone, while incorporating an appropriate level of geologic data and interpretations for the size of the model using current site-standard HSUs. Future more detailed site-specific investigations within the Central Plateau can then use the CPVZ GFM as a starting point instead of the larger scale HSGFM. This GFM was developed using the site standard and approved for use IHS Kingdom software. This ECF is a revision to the original model described in CP-60925, but the underlying assumptions and conceptual model are unchanged. Therefore, this revision is a new calculation of version 1.0 of the CPVZ GFM and not a new version of the GFM. Throughout this report, the original model documented in CP-60925 is called CPVZ-Rev.0and the calculation for this revision of the model is called CPVZ-Rev.1.

58 GEOSCIENCES↗
NASA NTRS2010

PRA in Design: Increasing Confidence in Pre-Operational Assessments of Risks (Results of a Joint NASA/NRC Workshop)

In late 2009, the National Aeronautics and Space Administration (NASA) and the U.S. Nuclear Regulatory Commission (NRC) jointly organized a workshop to discuss technical issues associated with application of risk assessments to early phases of system design. The workshop, which was coordinated by the Idaho National Laboratory, involved invited presentations from a number of PRA experts in the aerospace and nuclear fields and subsequent discussion to address the following questions: (a) What technical issues limit decision-makers' confidence in PRA results, especially at a pre-operational phase of the system life cycle? (b) What is being done to address these issues'? (c) What more can be done ? The workshop resulted in participant observations and suggestions on several technical issues, including the pursuit of non-traditional approaches to risk assessment and the verification and validation of risk models. The workshop participants also identified several important non-technical issues, including risk communication with decision makers, and the integration of PRA into the overall design process.

Youngblood, Robert↗
NASA NTRS2013

Statistical Analysis of CFD Solutions From the Fifth AIAA Drag Prediction Workshop

A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using a common grid sequence and multiple turbulence models for the June 2012 fifth Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was the Common Research Model subsonic transport wing-body previously used for the 4th Drag Prediction Workshop. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with previous workshops.

Statistical analysis↗
NASA NTRS2012

Desktop Modeling and Simulation: Parsimonious, yet Effective Discrete-Event Simulation Analysis

This paper evaluates how quickly students can be trained to construct useful discrete-event simulation models using Excel The typical supply chain used by many large national retailers is described, and an Excel-based simulation model is constructed of it The set of programming and simulation skills required for development of that model are then determined we conclude that six hours of training are required to teach the skills to MBA students . The simulation presented here contains all fundamental functionallty of a simulation model, and so our result holds for any discrete-event simulation model. We argue therefore that Industry workers with the same technical skill set as students having completed one year in an MBA program can be quickly trained to construct simulation models. This result gives credence to the efficacy of Desktop Modeling and Simulation whereby simulation analyses can be quickly developed, run, and analyzed with widely available software, namely Excel.

Bradley, James R.↗