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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Demonstrate Capability of NEAMS Tools to Generate Reactor Kinetics Parameters for Pebble-Bed HTGRs Transient Modeling

The system analysis of anticipated operating occurrences and design basis accident for pebblebed reactor systems requires knowledge of the neutron kinetic parameters. These parameters take into account various types of feedback from the pebble-bed core and are typically integrated into system analysis tools such as the System Analysis Module (SAM) in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) tool package. These parameters are typically generated by a higher fidelity full-core coupled neutronics/thermal fluids analysis, such as using Griffin and Pronghorn, in 2D or 3D. The delayed neutron fractions (beta) and the neutron lifetimes (lambda) are typically generated by applying the adjoint solution of the neutron flux. Temperature reactivity coefficients are the most important feedback for all anticipated operating occurrences and design basis accident, then depending on the transient other effects might be important as rector control system worth, s-curves, and Xenon generation. This work package will establish a methodology and process for calculating the reactor kinetics parameters for high-temperature gas-cooled reactor and provide them in a suitable form for system level analyses of typical anticipated operating occurrences and design basis accident.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

INTEGRATION OF FLEX EQUIPMENT AND OPERATOR ACTIONS IN PLANT FORCE-ON-FORCE MODELS WITH DYNAMIC RISK ASSESSMENT

The overall operation and maintenance cost to protect nuclear power plants accounts for approximately 7% of the total cost of power generation, with labor accounting for half of this cost. In the current research, from interaction with utilities and other stakeholders, it was determined that physical security forces account for nearly 20% of the entire workforce at several nuclear power plants. Labor costs continue to rise in the U.S., so any measures to reduce the cost of operating a nuclear power plant will need to include a reduction in labor. The physical security pathway within the DOE’s Light Water Reactor Sustainability program aims to lower the cost of physical security through directed research into modeling and simulation, application of advanced sensors or deployment of advanced weapons. This report presents a modeling and simulation framework for integrating Diverse and Flexible Mitigation Capability (FLEX) portable equipment performance with Force on Force models of a plant’s physical security posture. The generic framework is described in detail, followed by a case study of modeling an adversarial attack aimed at causing a radiological release by sabotaging the plant’s power supply and its ultimate heat sink capabilities at a hypothetical nuclear power plant. Two different FLEX deployment strategies, series and parallel, are modeled with distinct timelines. The results of the adversarial attack modeled in a commercial Force on Force tool are integrated with the FLEX deployment model in INL’s dynamic modeling tool EMRALD. Monte Carlo simulation is used to model the distribution of the timeline in FLEX deployment strategies. The results demonstrate that, even in the extreme case of a successful adversarial attack, deployment of FLEX equipment can result in a significantly high likelihood of preventing radiological release. The modeling and simulation framework integrating FLEX equipment with Force on Force models enables the nuclear power plants to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

A Strategy for Autogeneration of Space Shuttle Ground Processing Simulation Models for Project Makespan Estimations

Space Shuttle Processing is a complicated and highly variable project. The planning and scheduling problem, categorized as a Resource Constrained - Stochastic Project Scheduling Problem (RC-SPSP), has a great deal of variability in the Orbiter Processing Facility (OPF) process flow from one flight to the next. Simulation Modeling is a useful tool in estimation of the makespan of the overall process. However, simulation requires a model to be developed, which itself is a labor and time consuming effort. With such a dynamic process, often the model would potentially be out of synchronization with the actual process, limiting the applicability of the simulation answers in solving the actual estimation problem. Integration of TEAMS model enabling software with our existing schedule program software is the basis of our solution. This paper explains the approach used to develop an auto-generated simulation model from planning and schedule efforts and available data.

Madden, Michael G.↗
DOE OSTI2022

Produced Water-Economic, Socio, Environmental Simulation Model (PW-ESEim) Model: Proof-of-Concept for Southeastern New Mexico

A proof-of-concept tool, the Produced Water-Economic, Socio, Environmental Simulation model (PW-ESESim), was developed to support ease of analysis. The tool was designed to facilitate head-to-head comparison of alternative produced water source, treatment, and reuse water management strategies. A graphical user interface (GUI) guides the user through the selection and design of alternative produced water treatment and reuse strategies and the associated health and safety risk and economic benefits. At the highest conceptual level, alternative water strategies include the selection of a source water (locally or regionally available produced water), treatment strategy (pre-treatment, physical, chemical, biological, desalination, and post-treatment processes) and product water purpose (e.g., irrigation, industrial processing, environmental). After selection of these details, the PW-ESESim output a number of key economic, societal, environmental, public/ecological health and safety metrics to support user decision-making; specific examples include, cost of treatment, improvements in freshwater availability, human and ecologic health impacts and growth in local jobs and the economy. Through the simulation of different produced water treatment and management strategies, tradeoffs are identified and used to inform fit-for-purpose produced water treatment and reuse management decisions. While the tool was initially designed using Southeastern New Mexico (Permian Basin) as a case study, the general design of the PW-ESESim model can be extended to support other oil and gas regions of the U.S.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.

Kulkarni, Shruti↗
NASA NTRS2006

Simulation of Lunar Surface Communications Network Exploration Scenarios

Simulations and modeling of surface-based communications networks provides a rapid and cost effective means of requirement analysis, protocol assessments, and tradeoff studies. Robust testing in especially important for exploration systems, where the cost of deployment is high and systems cannot be easily replaced or repaired. However, simulation of the envisioned exploration networks cannot be achieved using commercial off the shelf network simulation software. Models for the nonstandard, non-COTS protocols used aboard space systems are not readily available. This paper will address the simulation of realistic scenarios representative of the activities which will take place on the surface of the Moon, including selection of candidate network architectures, and the development of an integrated simulation tool using OPNET modeler capable of faithfully modeling those communications scenarios in the variable delay, dynamic surface environments. Scenarios for exploration missions, OPNET development, limitations, and simulations results will be provided and discussed.

Linsky, Thomas W.↗
DOE OSTI2021

OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)

Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim

Blonsky, Michael↗
NASA NTRS2012

A Turbine Based Combined Cycle Engine Inlet Model and Mode Transition Simulation Based on HiTECC Tool

An inlet system is being tested to evaluate methodologies for a turbine based combined cycle propulsion system to perform a controlled inlet mode transition. Prior to wind tunnel based hardware testing of controlled mode transitions, simulation models are used to test, debug, and validate potential control algorithms. One candidate simulation package for this purpose is the High Mach Transient Engine Cycle Code (HiTECC). The HiTECC simulation package models the inlet system, propulsion systems, thermal energy, geometry, nozzle, and fuel systems. This paper discusses the modification and redesign of the simulation package and control system to represent the NASA large-scale inlet model for Combined Cycle Engine mode transition studies, mounted in NASA Glenn s 10- by 10-Foot Supersonic Wind Tunnel. This model will be used for designing and testing candidate control algorithms before implementation.

Csank, Jeffrey T.↗
NASA NTRS2012

A Turbine Based Combined Cycle Engine Inlet Model and Mode Transition Simulation Based on HiTECC Tool

An inlet system is being tested to evaluate methodologies for a turbine based combined cycle propulsion system to perform a controlled inlet mode transition. Prior to wind tunnel based hardware testing of controlled mode transitions, simulation models are used to test, debug, and validate potential control algorithms. One candidate simulation package for this purpose is the High Mach Transient Engine Cycle Code (HiTECC). The HiTECC simulation package models the inlet system, propulsion systems, thermal energy, geometry, nozzle, and fuel systems. This paper discusses the modification and redesign of the simulation package and control system to represent the NASA large-scale inlet model for Combined Cycle Engine mode transition studies, mounted in NASA Glenn s 10-foot by 10-foot Supersonic Wind Tunnel. This model will be used for designing and testing candidate control algorithms before implementation.

Csank, Jeffrey↗
DOE OSTI2024

Development of a Computational Framework for Multiphysics Multiphase Species Tracking using NEAMS Tools

This report implements a high-fidelity multiphysics modeling framework using the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program tools to track isotopic species in Molten Salt Reactors (MSRs), with a specific focus on the 91-depletion chain within the Molten Salt Reactor Experiment (MSRE). The model integrates neutronics, thermal-hydraulics, depletion, and thermochemistry to simulate the production, transport, and phase transitions of isotopes under steady-state and transient conditions. The main findings reveal that isotopes such as bromine-91 largely remain in the liquid phase, while others, including krypton-91and yttrium-91, transition to the gas phase, significantly influencing the reactor’s radiological source term. The study also shows that during transients, like a reactivity insertion transient, rapid void formation and the expansion of the liquid-gas interface led to substantial transfers of dissolved isotopes into the gas phase, altering isotope distribution and largely increasing the source term in the off-gas system. Additionally, the research highlights that short-lived isotopes dominate the initial off-gas response during transients, while longer-lived isotopes determine the equilibrium state, underscoring the necessity of dynamic simulations for accurate species tracking and reactor safety analysis. The developed methodology will be applied in the future to the tracking of a larger number of species and introduce other species tracking mechanisms, such as deposition and plating.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Simulating Thermoelectric Devices Using the MOOSE Framework

Thermoelectric generators (TEG) are devices that generate energy by converting heat into electricity or provide cooling via the Peltier effect. This feature of thermoelectric devices originates from the Seebeck, Peltier, Thomson, and Joule heating effects. TEGs can be applied in energy and thermal management systems such as waste heat recovery and refrigeration, respectively. Thermoelectric device design is influenced by the material selection and the device's geometry operating conditions. Therefore, predicting, verifying, and validating thermoelectric device performance using simulations tools is essential to deploying thermoelectric devices in industry. The Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework is an open-source simulation tool capable of modeling simple to complex systems. In this work, we demonstrate MOOSE's thermoelectric device modeling capabilities by simulating a unicouple, module, and exhaust gas recovery system. The Seebeck, Peltier, Thomson, and Joule heating physics are implemented into MOOSE. The MOOSE thermoelectric physics were thoroughly verified and validated using published COMSOL® results and experimental data. In addition, thermoelectric modules were integrated into an exhaust gas recovery system using the MOOSE MultiApp function as a demonstration of the model's ability. The verification and validation results and exhaust gas heat recovery system showcases MOOSE's capability to model thermoelectric devices and integrate these devices into practical energy systems.

42 - ENGINEERING↗
DOE OSTI2022

Development of a web-based screening tool for ground source heat pump applications

Ground source heat pump (GSHP) technology has great potential to help the nation meet its energy and decarbonization goals, but several barriers hinder the wide application of GSHP. Important barriers include the lack of a coherent toolset for analyzing the technical feasibility and economic viability of the GSHP application. The current design and analysis methods are ineffective and require significant expertise to apply. Although building energy modeling is increasingly important in designing buildings, the tools for GSHP modeling and simulation are lacking. A web-based free-to-use tool is being developed for quick techno-economic analysis of GSHP applications in nearly any building in the United States. This tool is enabled by improvements in the calculation methodology to allow rapid sizing of borehole configurations that provide significant cost savings. The screening tool currently uses US Department of Energy (DOE) prototype building models and an extended g-function library to size ground heat exchangers and simulate the performance of GSHP systems. The team is integrating with DOE's Oak Ridge National Laboratory's AutoBEM program to automatically create a building model based on user inputs. This paper introduces the structure, components, features, and results of the web-based screening tool for GSHP applications. Future directions for further developing the tool are also discussed.

Liu, Xiaobing↗
DOE OSTI2020

Multi-resolution, Multi-scale Modeling for Scalable Macroalgae Production

Macroalgae harvested along coastlines and in the open ocean has traditionally been used as food for human consumption, animal feed, and fertilizer. The U.S. ARPA-E MARINER Program estimates that the nation has suitable conditions and geography to produce at least 500 million dry metric tons of macroalgae per year, yielding approximately 2.7 quadrillion BTUs of energy in the form of liquid fuel, which is roughly 10% of the nation’s annual transportation energy demand. Adverse environmental effects of nutrient overload and ocean acidification may also be reduced by large-scale macroalgae cultivation in many coastal ocean regions. However, the successful deployment of large-scale marine macroalgae farms for fuel production depends on ambient hydrodynamic conditions and nutrient availability, as well as their interactions with macroalgae farm structures. Pacific Northwest National Laboratory led an ARPA-E MARINER project to develop a set of numerical modeling tools capable of simulating ocean hydrodynamic and biogeochemical processes, macroalgae trajectories for free-floating systems, macroalgae growth and biomass yields, and hydrodynamic load on macroalgae canopies and farm structures using a multi-resolution and multi-scale approach. This set of modeling tools provides a suite of information essential for system design, optimal project siting, risk analysis, and management of macroalgae production systems in the ocean. Better clarity can also help macroalgae system developers reduce deployment costs, operational risk, and potential impacts on the local marine environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems

Agent-based simulation provides a powerful tool for in silico system modeling. However, these simulations do not provide built-in methods for uncertainty quantification (UQ). Within these types of models a typical approach to UQ is to run multiple realizations of the model then compute aggregate statistics. This approach is limited due to the compute time required for a solution. When faced with an emerging biothreat, public health decisions need to be made quickly and solutions for integrating near real-time data with analytic tools are needed. We propose an integrated Bayesian UQ framework for agent-based models based on sequential Monte Carlo sampling. Given streaming or static data about the evolution of an emerging pathogen this Bayesian framework provides a distribution over the parameters governing the spread of a disease through a population. These estimates of the spread of a disease may be provided to public health agencies seeking to abate the spread. By coupling agent-based simulations with Bayesian modeling in a data assimilation, our proposed framework provides a powerful tool for modeling dynamical systems in silico. We propose a method which reduces model error and provides a range of realistic possible outcomes. Moreover, our method addresses two primary limitations of ABMs: the lack of UQ and an inability to assimilate data. Our proposed framework combines the flexibility of an agent-based model with UQ provided by the Bayesian paradigm in a workflow which scales well to HPC systems. We provide algorithmic details and results on a simulated outbreak with both static and streaming data.

Spannaus, Adam [ORNL] (ORCID:0000000225213657)↗
DOE OSTI2020

Fast-Spectrum Critical Assemblies with a Pb-HEU Core Surrounded by a Copper Reflector

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These M&S tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to accurately model systems of interest, the industry must improve key nuclear data measurements and our confidence of how well we understand the data. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles benchmark experiment data in a handbook that can be used by criticality safety engineers to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the neutron energy within the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. This has caused the latest nuclear cross-section libraries to over/underestimate changes in the neutron population compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Simulation of Creep Deformation and Failure in Graded AM Microstructures

This report describes modeling tools and techniques developed to simulate the long-term material performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF). A physics-based Crystal Plasticity Finite Element model is used to simulate creep in microstructures and to study the roles of grain morphology, porosity, and texture. We describe our modeling methodology, including an orientation-mapping technique to capture the spatially varying crystallographic orientation that results from the build conditions. Our study of microstructural features shows that AM microstructures produced by LPBF tend to creep faster in the build direction, while texture and grain boundaries strengthen the transverse directions. However, when grain-boundary porosity and the consequent cavity growth are included in the model, the transverse directions begin to creep faster. In examining texture, the results indicate that spatially varying orientation arising from the build conditions increases anisotropy in the material, making it critical to account for orientation gradients in the material to accurately model its mechanical behavior. We also describe a material-model calibration campaign in which we calibrated the constitutive model specifically for LPBF 316H stainless steel at 725℃ for both solution-annealed and as-built conditions. Finally, these tools and techniques are used to model creep in microstructures representing different regions of an LPBF material with graded microstructure, owing to intentional variation in processing conditions. The creep simulation results show good agreement with experimental data across all three microstructures, with future work planned to study rupture in the material.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Serious Gaming for Test & Evaluation of Clean-Slate (Ab Initio) National Airspace System (NAS) Designs

Incremental approaches to air transportation system development inherit current architectural constraints, which, in turn, place hard bounds on system capacity, efficiency of performance, and complexity. To enable airspace operations of the future, a clean-slate (ab initio) airspace design(s) must be considered. This ab initio National Airspace System (NAS) must be capable of accommodating increased traffic density, a broader diversity of aircraft, and on-demand mobility. System and subsystem designs should scale to accommodate the inevitable demand for airspace services that include large numbers of autonomous Unmanned Aerial Vehicles and a paradigm shift in general aviation (e.g., personal air vehicles) in addition to more traditional aerial vehicles such as commercial jetliners and weather balloons. The complex and adaptive nature of ab initio designs for the future NAS requires new approaches to validation, adding a significant physical experimentation component to analytical and simulation tools. In addition to software modeling and simulation, the ability to exercise system solutions in a flight environment will be an essential aspect of validation. The NASA Langley Research Center (LaRC) Autonomy Incubator seeks to develop a flight simulation infrastructure for ab initio modeling and simulation that assumes no specific NAS architecture and models vehicle-to-vehicle behavior to examine interactions and emergent behaviors among hundreds of intelligent aerial agents exhibiting collaborative, cooperative, coordinative, selfish, and malicious behaviors. The air transportation system of the future will be a complex adaptive system (CAS) characterized by complex and sometimes unpredictable (or unpredicted) behaviors that result from temporal and spatial interactions among large numbers of participants. A CAS not only evolves with a changing environment and adapts to it, it is closely coupled to all systems that constitute the environment. Thus, the ecosystem that contains the system and other systems evolves with the CAS as well. The effects of the emerging adaptation and co-evolution are difficult to capture with only combined mathematical and computational experimentation. Therefore, an ab initio flight simulation environment must accommodate individual vehicles, groups of self-organizing vehicles, and large-scale infrastructure behavior. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ab initio simulation environment is similar to online gaming environments in which player participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual player's active participation.

Allen, B. Danette↗
NASA NTRS2022

Are Soybean Models Ready for Climate Change Food Impact Assessments?

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO 2 concentration [CO 2 ] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO 2 ]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO 2 ] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO 2 ] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO 2 ] and temperature is needed to reduce the uncertainty from the individual models.

Agricultural Model Inter-comparison and Improvemen↗