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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

FASTSim™ (Future Automotive Systems Technology Simulator) [SWR-20-101 and SWR-12-07]

The Future Automotive Systems Technology Simulator (FASTSim™) provides a simple way to compare powertrains and estimate the impact of technology improvements on light-, medium-, and heavy-duty vehicle efficiency, performance, cost, and battery life. This extremely fast simulation tool features a streamlined user interface and can rapidly perform a variety of tasks using basic computing resources: • less than 0.1 second to simulate second-by-second standard duty cycles • less than 10 seconds to estimate vehicle efficiency, fuel economy, acceleration, battery life, and cost • less than 5 minutes to perform powertrain comparisons of efficiency and cost. FASTSim models a variety of vehicle powertrains and fuel converter types: • Conventional vehicles - spark ignition, Atkinson, diesel, and hybrid diesel • Electric-drive vehicles - hybrid, plug-in hybrid, and all-electric • Hydrogen fuel cell vehicles. The default model includes a variety of vehicles and duty cycles and an option for adding additional vehicles and custom cycles: • Packaged with more than 20 vehicles • User interface enables addition of more vehicles • Includes standard U.S. drive cycles as well as European and Japanese cycles. FASTSim is available for download in Microsoft Excel and Python formats here: https://www.nrel.gov/transportation/fastsim.html

Baker, Chad↗
DOE OSTI2017

Adverse Events Involving Radiation Oncology Medical Devices: Comprehensive Analysis of US Food and Drug Administration Data, 1991 to 2015

Purpose: Radiation oncology relies on rapidly evolving technology and highly complex processes. The US Food and Drug Administration collects reports of adverse events related to medical devices. We sought to characterize all events involving radiation oncology devices (RODs) from the US Food and Drug Administration's postmarket surveillance Manufacturer and User Facility Device Experience (MAUDE) database, comparing these with non–radiation oncology devices. Methods and Materials: MAUDE data on RODs from 1991 to 2015 were sorted into 4 product categories (external beam, brachytherapy, planning systems, and simulation systems) and 5 device problem categories (software, mechanical, electrical, user error, and dose delivery impact). Outcomes included whether the device was evaluated by the manufacturer, adverse event type, remedial action, problem code, device age, and time since 510(k) approval. Descriptive statistics were performed with linear regression of time-series data. Results for RODs were compared with those for other devices by the Pearson χ{sup 2} test for categorical data and 2-sample Kolmogorov-Smirnov test for distributions. Results: There were 4234 ROD and 4,985,698 other device adverse event reports. Adverse event reports increased over time, and events involving RODs peaked in 2011. Most ROD reports involved external beam therapy (50.8%), followed by brachytherapy (24.9%) and treatment planning systems (21.6%). The top problem types were software (30.4%), mechanical (20.9%), and user error (20.4%). RODs differed significantly from other devices in each outcome (P<.001). RODs were more likely to be evaluated by the manufacturer after an event (46.9% vs 33.0%) but less likely to be recalled (10.5% vs 37.9%) (P<.001). Device age and time since 510(k) approval were shorter among RODs (P<.001). Conclusions: Compared with other devices, RODs may experience adverse events sooner after manufacture and market approval. Close postmarket surveillance, improved software design, and manufacturer–user training may help mitigate these events.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Medical Device Recalls in Radiation Oncology: Analysis of US Food and Drug Administration Data, 2002-2015

Purpose: To analyze all recalls involving radiation oncology devices (RODs) from the US Food and Drug Administration (FDA)'s recall database, comparing these with non–radiation oncology device recalls to identify discipline-specific trends that may inform improvements in device safety. Methods and Materials: Recall data on RODs from 2002 to 2015 were sorted into 4 product categories (external beam, brachytherapy, planning systems, and simulation systems). Outcomes included determined cause of recall, recall class (severity), quantity in commerce, time until recall termination (date FDA determines recall is complete), and time since 510(k) approval. Descriptive statistics were performed with linear regression of time-series data. Results for RODs were compared with those for other devices by Pearson χ{sup 2} test for categorical data and 2-sample Kolmogorov-Smirnov test for distributions. Results: There were 502 ROD recalls and 9534 other class II device recalls during 2002 to 2015. Most recalls were for external beam devices (66.7%) and planning systems (22.9%), and recall events peaked in 2011. Radiation oncology devices differed significantly from other devices in all recall outcomes (P≤.04). Recall cause was commonly software related (49% vs 10% for other devices). Recall severity was more often moderate among RODs (97.6% vs 87.2%) instead of severe (0.2% vs 4.4%; P<.001). Time from 510(k) market approval to recall was shorter among RODs (P<.001) and progressively shortened over time. Radiation oncology devices had fewer recalled devices in commerce than other devices (P<.001). Conclusions: Compared with other class II devices, RODs experience recalls sooner after market approval and are trending sooner still. Most of these recalls were moderate in severity, and software issues are prevalent. Comprehensive analysis of recall data can identify areas for device improvement, such as better system design among RODs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Validity of path thermodynamic description of reactive systems: Microscopic simulations

Traditional stochastic modeling of reactive systems limits the domain of applicability of the associated path thermodynamics to systems involving a single elementary reaction at the origin of each observed change in composition. An alternative stochastic modeling has recently been proposed to overcome this limitation. These two ways of modeling reactive systems are in principle incompatible. Here, the question thus arises about choosing the appropriate type of modeling to be used in practical situations. In the absence of sufficiently accurate experimental results, one way to address this issue is through the microscopic simulation of reactive fluids, usually based on hard-sphere dynamics in the Boltzmann limit. In this paper, we show that results obtained through such simulations unambiguously confirm the predictions of traditional stochastic modeling, invalidating a recently proposed alternative.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

TECHNICAL CONSTRAINTS TO CONDUCTING OPERATOR STUDIES IN A RECONFIGURABLE CONTROL ROOM SIMULATOR

The Human Systems Simulation Laboratory (HSSL) at Idaho National Laboratory (INL) is a full scope, full scale, and reconfigurable digital representation of an analog nuclear power plant control room. The HSSL is used to conduct human factors research studies on digital technologies being introduced into legacy nuclear power plant control rooms. With the aging nuclear fleet approaching an average of 35 years, utilities are beginning to replace their analog systems with more modern technologies, and utilizing the HSSL to accomplish these tasks. This document will describe some of the constraints identified when conducting operator studies in the HSSL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

High-Resolution, Rapid-Scan Dual-Doppler Retrievals of Vertical Velocity in a Simulated Supercell

Observation system simulation experiments are used to evaluate different dual-Doppler analysis (DDA) methods for retrieving vertical velocity w at grid spacings on the order of 100 m within a simulated tornadic supercell. Variational approaches with and without a vertical vorticity equation constraint are tested, along with a typical (traditional) method involving vertical integration of the mass conservation equation. The analyses employ emulated radar data from dual-Doppler placements 15, 30, and 45 km east of the mesocyclone, with volume scan intervals ranging from 10 to 150 s. The effect of near-surface data loss is examined by denying observations below 1 km in some of the analyses. At the longer radar ranges and when no data denial is imposed, the “traditional” method produces results similar to those of the variational method and is much less expensive to implement. However, at close range and/or with data denial, the variational method is much more accurate, confirming results from previous studies. The vorticity constraint shows the potential to improve the variational analysis substantially, reducing errors in the w retrieval by up to 30% for rapid-scan observations (≤30 s) at close range when the local vorticity tendency is estimated using spatially variable advection correction. However, the vorticity constraint also degrades the analysis for longer scan intervals, and the impact diminishes with increased range. Furthermore, analyses using 30-s data also frequently outperform analyses using 10-s data, suggesting a limit to the benefit of increasing the radar scan rate for variational DDA employing the vorticity constraint.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Determination of the critical micelle concentration in simulations of surfactant systems

Alternative methods for determining the critical micelle concentration (cmc) are investigated using canonical and grand canonical Monte Carlo simulations of a lattice surfactant model. A common measure of the cmc is the “free” (unassociated) surfactant concentration in the presence of micellar aggregates. Many prior simulations of micellizing systems have observed a decrease in the free surfactant concentration with overall surfactant loading for both ionic and nonionic surfactants, contrary to theoretical expectations from mass-action models of aggregation. In the present study, we investigate a simple lattice nonionic surfactant model in implicit solvent, for which highly reproducible simulations are possible in both the canonical (NVT) and grand canonical (μVT) ensembles. We confirm the previously observed decrease of free surfactant concentration at higher overall loadings and propose an algorithm for the precise calculation of the excluded volume and effective concentration of unassociated surfactant molecules in the accessible volume of the solution. We find that the cmc can be obtained by correcting the free surfactant concentration for volume exclusion effects resulting from the presence of micellar aggregates. We also develop an improved method for determination of the cmc based on the maximum in curvature for the osmotic pressure curve determined from μVT simulations. Excellent agreement in cmc and other micellar properties between NVT and μVT simulations of different system sizes is observed. The methodological developments in this work are broadly applicable to simulations of aggregating systems using any type of surfactant model (atomistic/coarse grained) or solvent description (explicit/implicit)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Historical global Earth System Model simulations with E3SM's dynamic root module

This data package contains global-scale Earth System Model simulations run with DOE's E3SM Model. The package includes one set of simulations run in the default configuration and a second set of simulations run with the dynamic root module enabled. These two datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The outputs are provided here on a 0.5 x 0.5 global grid at monthly resolution. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are broken up into 20 year chunks to facilitate easier read-in. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and GrADS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Simulating PV System Performance with Component Reliability Distributions

A feature developed by Sandia National Laboratories (SNL) for simulating PV system component reliability has been integrated into the National Renewable Energy Laboratory's System Advisor Model (SAM). The PV Reliability Performance Model (PV-RPM) uses fault/failure and repair distributions to estimate impacts to power, energy production and operational costs. Realization results include the number of failures per component, failure rate, O&M costs incurred based on maintenance strategies, and energy lost based on the failure estimates. As the inputs are inherently uncertain and based on probability distributions, the model realizations include statistical confidence intervals to help bracket the probability that the sample interval contains the true mean value of the variable in question. This paper presents the current validation efforts and provides detail on how this feature is utilized in a PV performance model.

14 SOLAR ENERGY↗
DOE OSTI2022

The evolution of the Human Systems and Simulation Laboratory in nuclear power research

The events at Three Mile Island in the United States brought about fundamental changes in the ways that simulation would be used in nuclear operations. The need for research simulators was identified to scientifically study human-centered risk and make recommendations for process control system designs. This paper documents the human factors research conducted at the Human Systems and Simulation Laboratory (HSSL) since its inception in 2010 at Idaho National Laboratory. The facility’s primary purposes are to provide support to utilities for system upgrades and to validate modernized control room concepts. In the last decade, however, as nuclear industry needs have evolved, so too have the purposes of the HSSL. Thus, beyond control room modernization, human factors researchers have evaluated the security of nuclear infrastructure from cyber adversaries and evaluated human-in-the-loop simulations for joint operations with an integrated hydrogen generation plant. Lastly, our review presents research using human reliability analysis techniques with data collected from HSSL-based studies and concludes with potential future directions for the HSSL, including severe accident management and advanced control room technologies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Numerical Simulation of Systems of Shear Bands in Ductile Metal with Inclusions

These are slides for a presentation on numerical simulation of systems of shear bands in ductile metal with inclusions, performed at Los Alamos National Laboratory. The conclusions are the following: A shear band is much thinner (0.1 μm) than the spacing between inclusions (100μm). Therefore fully resolved simulation is not feasible; asymptotic analysis allows modeling of a shear band as a velocity discontinuity within a moderately sized cell; formation criterion (critical strain) is determined by rate-dependent viscoplastic flow rule; inclusions cause shear bands to form at smaller strain; under expansion, shear bands form at the same strain than under compression; this can be applied to crystal plasticity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Dynamic equation-based thermo-hydraulic pipe model for district heating and cooling systems

Simulation and optimisation of district heating and cooling networks requires efficient and realistic models of the individual network elements in order to correctly represent heat losses or gains, temperature propagation and pressure drops. Due to more recent thermal networks incorporating meshing decentralised heat and cold sources, the system often has to deal with variable temperatures and mass flow rates, with flow reversal occurring more frequently. This paper presents the mathematical derivation and software implementation in Modelica of a thermo-hydraulic model for thermal networks that meets the above requirements and compares it to both experimental data and a commonly used model. Good correspondence between experimental data from a controlled test set-up and simulations using the presented model was found. Compared to measurement data from a real district heating network, the simulation results led to a larger error than in the controlled test set-up, but the general trend is still approximated closely and the model yields results similar to a pipe model from the Modelica Standard Library. However, the presented model simulates 1.7 (for low number of volumes) to 68 (for highly discretized pipes) times faster than a conventional model for a realistic test case. A working implementation of the presented model is made openly available within the IBPSA Modelica Library. The model is robust in the sense that grid size and time step do not need to be adapted to the flow rate, as is the case in finite volume models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Equivalent Test Bed in PSCAD and PSLF for Studying Advanced Power Systems Controller Performance

With increasing popularity of sustainable energy resources, research on power electronic-based renewable generation modeling is gaining impetus to enhance reliability of electric grids with high penetrations of renewable energy. A set of generic and public models for renewable energy are available in commercial positive sequence power system simulation software. However, advanced controller models applicable for renewable resources are typically not included in these tools. To ensure the integrity of the newly developed controller models for renewables in positive sequence simulators for large power systems, it is necessary to validate the dynamic performance of the proposed model with detailed electromagnetic models. This paper creates an equivalent test bed in PSCAD and PSLF for validating the performance of advanced controllers associated with renewable energy sources. To demonstrate the usefulness of the test-bed, a user-defined synthetic inertia (SI) controller model was developed in PSLF and validated through the proposed test bed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study

Here, dynamic probabilistic risk assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP and MELCOR) with simulation controller codes (e.g., RAVEN and ADAPT). Whereas system simulator codes model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic and operating procedures) and stochastic (e.g., component failures and parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by sampling values of a set of parameters and simulating the system behavior for that specific set of parameter values. For complex systems, a major challenge in using DPRA methodologies is to analyze the large number of scenarios generated, where clustering techniques are typically employed to better organize and interpret the data. In this paper, we focus on the analysis of two nuclear simulation datasets that are part of the risk-informed safety margin characterization (RISMC) boiling water reactor (BWR) station blackout (SBO) case study. We provide the domain experts a software tool that encodes traditional and topological clustering techniques within an interactive analysis and visualization environment, for understanding the structures of such high-dimensional nuclear simulation datasets. We demonstrate through our case study that both types of clustering techniques complement each other for enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Framework for Model Validation and Calibration of Microgrid Components Using PMU Data

This paper presents a framework for phasor measurement-based component model validation and calibration islanded microgrids, with emphasis on grid-forming inverters. Real measurements from the Plum Island microgrid facility are used to calibrate the model of a commercial inverter in the open-source phasor-based distribution system simulator GridLAB-D.Limitations of current distribution system simulators in replicating the behavior of commercial inverters are also identified.

microgrid, Synchrophasor data, model validation↗
DOE OSTI2023

Earth System Model Simulations of Ameriflux sites using dynamic roots and dynamic leaf to root allocation

This data package contains point-scale Earth System Model simulations run with DOE's E3SM Model. The package includes four sets of simulations, one set of simulations run in the default configuration, a second set of simulations run with the dynamic root module enabled, the third set with dynamic leaf to fine root allocation, and the fourth with the combination of dynamic roots and dynamic allocation. These simulations were run in point mode a Ameriflux sites, US-MMS, US-Moz, US-Syv, and US-NR1. These datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and R.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Development and Validation of a Simulation Testbed for the Intelligent Building Agents Laboratory (IBAL) Using TRNSYS

This paper documents the development and validation of a dynamic primary cooling and thermal storage system simulation testbed. The system simulation testbed, sIBAL, is based on the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), which is a research infrastructure and testbed for the development, evaluation, and demonstration of intelligent control algorithms. The sIBAL testbed developed in this project will serve as a virtual twin of the real facility for future control algorithm development. The details of the methodologies used to develop and validate the simulation testbed, which replicates the dynamic behaviors of the primary cooling and ice storage system in the IBAL facility, are presented. The simulation testbed was developed in TRNSYS using built-in component models and MATLAB functions to replicate the two water-cooled chillers, a thermal storage tank, pumps, valves and other components for four different operation modes. Experiments on IBAL components were designed and executed to generate experimental data for model development and verification of the simulation platform. The validation of the simulation results was carried out in two phases: 1) independent component simulations for the chillers and thermal storage tank, and 2) a combined testbed simulation of the entire hydronic system. Comparison of simulation results to the experimental data obtained from the IBAL facility showed errors within 1 °C for the temperatures outputs of both the chiller and the thermal storage model. The error is within an acceptable range for further intelligent control algorithms development. The findings from the study are summarized and presented along with areas where additional research is needed. In addition, data filtering procedures and model refinement measures utilized to improve the accuracy and accelerate the computation time of the simulation are presented.

cooling systems↗