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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Robust Statistical Approach for Determination of Graphite Nitridation Using Bayesian Model Comparison

A better estimation of surface reaction efficiency of semiconductor-grade graphite with atomic nitrogen, as well as the calibration error are calculated using Bayesian updating based on experimental data. Compared with a conventional deterministic model, the stochastic model approach is a powerful tool in the sense that the model is capable of taking into account underlying error correlations among the data quantities. In this paper, we investigate four different stochastic models (called “stochastic system model classes” herein) corresponding to different descriptions of modeling and measurement error structures, given one deterministic physical model. These stochastic system model classes differ in the covariance matrix structure that is used in the uncertainty model to represent uncertainties associated with the physical model and experimental measurements. For each model class, Bayesian inference is used to estimate the posterior probabilities of the physical model parameters as well as of the stochastic model parameters. Model comparison and selection are then applied based on two measures including Bayesian evidence and Bayesian information criterion, as well as the deviance information criterion. Both measures suggest the stochastic model class, which considers that a correlation between errors in two data quantities among different data points is the most plausible. With the stochastic model class, the range of uncertainty in surface reaction efficiency is estimated to be about two orders of magnitude at [Formula: see text].

Engineering↗
DOE OSTI2026

What's New in System Advisor Model

This talk will give an overview of recent and planned model improvements in the NLR System Advisor Model, including improved spectral model options, improved access to snow data for PV modeling across the United States, work on hybrid PV, CSP, and thermal energy storage modeling, current research into accurately modeling tandem cells, and more.

14 SOLAR ENERGY↗
DOE OSTI2014

Adaptive model training system and method

An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Adaptive model training system and method

An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Configuration and Data Management of the NASA Power and Propulsion Element MBSE Model(s)

Systems engineers worldwide have been working to implement Model-Based Systems Engineering (MBSE) environments, tools, and methodologies. A significant, expected benefit from MBSE is a reduction in the time commitment for all aspects of systems engineering. Although advances in MBSE have occurred, a gap has emerged between the traditional configuration management (CM) processes for documents and those needed in an MBSE environment.

MBSE↗
NASA NTRS2006

Model-Based Safety Analysis

System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

Joshi, Anjali↗
DOE OSTI2019

Simulation-based Design of a Shadow Shield for the MIND Backpack System

Modeling and simulation is a cost- and time-saving method to study conceptual designs of radiation detection systems. MCNP radiation transport code has been an indispensable tool in development of radiation detection systems, and the PINS systems have also utilized MCNP modeling and simulation in the system development. MCNP models of the PINS systems have been used to understand detector responses and to fill the gap in experimental data. Recently, the MIND backpack system was announced to be developed, and its prototype design was required to conduct laboratory tests and demonstrations. A shadow shield is the component to be designed by Idaho National Laboratory in order to maximize the performance of a backpack system while meeting the sponsor’s requirements. MCNP modeling and simulation was utilized to find the best specification of a shadow shield. This study was performed to down-select a shadow shield design for the MIND system. A total of 24 designs for a shadow shield were identified to build MCNP models, and their simulation results were used to prioritize each design. As a quantitative performance metric, an equation of Figure-of-Merit was introduced in the decision making analysis. In addition, the Analytic Hierarchy Process was adopted to prioritize and recommend best performing shadow shield designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2005

Development of a Stirling System Dynamic Model With Enhanced Thermodynamics

The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.

Regan, Timothy F.↗
DOE OSTI2020

Direct Dry Cooling System Spreadsheet Model for sCO 2

The attached cost and performance spreadsheet model is for a direct dry cooling system, one of four cooling system models developed for use in optimizing indirectly-heated supercritical CO 2 (sCO 2 ) power cycles. Running the model requires that the user has REFPROP version 9 or below installed, as well as the Microsoft Excel REFPROP Add-In. Upon opening, use Excel’s Edit Links feature to link to the user’s installed REFPROP.xla or REFPROP.xlam file. For the spreadsheet model compatible with REFPROP version 10 and above, contact Nathan Weiland at nathan.weiland@netl.doe.gov. Technical documentation for the model can be found here: https://www.netl.doe.gov/energy-analysis/details?id=3199.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Indirect Dry Cooling System Spreadsheet Model for sCO2

The attached cost and performance spreadsheet model is for an indirect dry cooling system, one of four cooling system models developed for use in optimizing indirectly-heated supercritical CO2 (sCO2) power cycles. Running the model requires that the user has REFPROP version 9 or below installed, as well as the Microsoft Excel REFPROP Add-In. Upon opening, use Excel’s Edit Links feature to link to the user’s installed REFPROP.xla or REFPROP.xlam file. For the spreadsheet model compatible with REFPROP version 10 and above, contact Nathan Weiland at nathan.weiland@netl.doe.gov. Technical documentation for the model can be found here: https://www.netl.doe.gov/energy-analysis/details?id=3199.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2014

System Dynamics Modeling of the Colorado Basin for Optimizing Operations, Reducing Risk, and Increasing Resiliency

This paper is the output from SNL’s involvement in the Western Area Power Administration (WAPA), the Colorado River Energy Distributors Association (CREDA), and the Upper Colorado River Commission’s (UCRC) sponsored Phase II work to establish market and non-market values (NMV’s) of water and hydropower associated with Glen Canyon Dam (GCD) operations and the Colorado River ecosystem. It describes the purpose and need to develop a systems model for the Colorado River Basin that includes valuations in the economic, hydrologic, environmental, social, and cultural sectors. It outlines the benefits and unique features associated with such a model and provides a roadmap of how a systems model would be developed and implemented. While not meant to serve as a full development plan, the ideas and concepts herein represent what the Sandia National Laboratories (SNL) research team believes is the most impactful and effective path forward to address an ever increasing complex set of problems that occur at the basin-scale and beyond.

13 HYDRO ENERGY↗
NASA NTRS2017

Development of a 13 kW Hall Thruster Propulsion System Performance Model for AEPS

The Advanced Electric Propulsion System (AEPS) program will develop a flight 13kW Hall thruster propulsion system based on NASA's HERMeS thruster. The AEPS system includes the Hall Thruster, the Power Processing Unit (PPU) and the Xenon Flow Controller (XFC). These three primary components must operate together to ensure that the system generates the required combinations of thrust and specific impulse at the required system efficiencies for the desired system lifetime. At the highest level, the AEPS system will be integrated into the spacecraft and will receive power, propellant, and commands from the spacecraft. Power and propellant flow rates will be determined by the throttle set points commanded by the spacecraft. Within the system, the major control loop is between the mass flow rate and thruster current, with time-dependencies required to handle all expected transients, and additional, much slower interactions between the thruster and cathode temperatures, flow controller and PPU. The internal system interactions generally occur on shorter timescales than the spacecraft interactions, though certain failure modes may require rapid responses from the spacecraft. The AEPS system performance model is designed to account for all these interactions in a way that allows evaluation of the sensitivity of the system to expected changes over the planned mission as well as to assess the impacts of normal component and assembly variability during the production phase of the program. This effort describes the plan for the system performance model development, correlation to NASA test data, and how the model will be used to evaluate the critical internal and external interactions. The results will ensure the component requirements do not unnecessarily drive the system cost or overly constrain the development program. Finally, the model will be available to quickly troubleshoot any future unforeseen development challenges.

Stanley, Steven↗
DOE OSTI2015

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease states in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Two-Way Integration of WRF and CCSM for Regional Climate Simulations

Under the support of the DOE award DE-SC0004670, we have successfully developed an integrated climate modeling system by nesting Weather Research and Forecasting (WRF) model within the Community Climate System Model (CCSM) and the ensuing new generation Community Earth System Model (CESM). The integrated WRF/CESM system is intended as one method of global climate modeling with regional simulation capabilities. It allows interactive dynamical regional downscaling in the computational flow of present or future global climate simulations. This capability substantially simplifies the process of dynamical downscaling by avoiding massive intermediate model outputs at high frequency that are typically required for offline regional downscaling. The inline coupling also has the advantage of higher temporal resolution for the interaction between regional and global model components. With the aid of the inline coupling, a capability has also been developed to ingest other global climate simulations (by CESM or other models), which otherwise may not have necessary intermediate outputs for regional downscaling, to realize their embedded regional details. It is accomplished by relaxing the global atmospheric state of the integrated model to that of the source simulations with an appropriate time scale. This capability has the potential to open a new venue for ensemble regional climate simulations using a single modeling system. Furthermore, this new modeling system provides an effective modeling framework for the studies of physical and dynamical feedbacks of regional weather phenomena to the large scale circulation. The projected uses of this capability include the research of up-scaling effect of regional weather system, and its use as an alternative physical representation of sub-scale processes in coarser-resolution climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing

Highlights: • We combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. • Beijing is selected as a case study. • Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. • Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis.

54 ENVIRONMENTAL SCIENCES↗