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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Design of Power System Architectures for Small Spacecraft Systems

The objective of this research is to perform a trade study on several candidate power system architectures for small spacecrafts to be used in NASA's new millennium program. Three initial candidate architectures have been proposed by NASA and two other candidate architectures have been proposed by Howard University. Howard University is currently conducting the necessary analysis, synthesis, and simulation needed to perform the trade studies and arrive at the optimal power system architecture. Statistical, sensitivity and tolerant studies has been performed on the systems. It is concluded from present studies that certain components such as the series regulators, buck-boost converters and power converters can be minimized while retaining the desired functionality of the overall architecture. This in conjunction with battery scalability studies and system efficiency studies have enabled us to develop more economic architectures. Future studies will include artificial neural networks and fuzzy logic to analyze the performance of the systems. Fault simulation studies and fault diagnosis studies using EMTP and artificial neural networks will also be conducted.

Momoh, James A.↗
DOE OSTI2022

Developing a PSCAD Model of the Reduced 240-Bus WECC Test System: Preprint

Fast-acting controls of inverter-based resources (IBR) introduce unprecedented dynamics to bulk power systems and island power grids, especially the high-frequency dynamics ranging from $>5$ Hz to hundreds of Hz. These oscillatory stability problems cannot be captured by the phasor domain simulations, e.g., in PSS/E, Powerworld and TSAT, due to insufficient modeling. Instead, they should be studied by electromagnetic transient (EMT) simulations by using proper EMT dynamic models. This paper develops and validates the PSCAD model of the reduced 240-bus Western Electricity Coordinating Council (WECC) test system. The PSCAD model will be released to the public, which can be used by both academia and power industry practitioners for studying the fast dynamic problems without any Critical Energy/Electric Infrastructure Information (CEII).

240-bus WECC test system↗
NASA NTRS2007

Relativistic Particle-in-Cell Simulation Studies of Prompt and Early Afterglows Observed by GLAST

Nonthermal radiation observed from astrophysical systems containing relativistic jets and shocks, e.g., gamma-ray bursts (GRBs), active galactic nuclei (AGNs), and Galactic microquasar systems usually have power-law emission spectra. Recent PIC simulations using injected relativistic electron-ion (electro-positron) jets show that acceleration occurs within the downstream jet. Shock acceleration is a ubiquitous phenomenon in astrophysical plasmas. Plasma waves and their associated instabilities (e.g., the Buneman instability, other two-streaming instability, and the Weibel instability) created in the shocks are responsible for particle (electron, positron, and ion) acceleration. The simulation results show that the Weibel instability is responsible for generating and amplifying highly nonuniform, small-scale magnetic fields. These magnetic fields contribute to the electron's transverse deflection behind the jet head. The "'jitter" radiation from deflected electrons has different properties than synchrotron radiation which is calculated in a uniform magnetic field. This jitter radiation may be important to understanding the complex time evolution and/or spectral structure in gamma-ray bursts, relativistic jets, and supernova remnants.

Mizuno, Y.↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Contribution to solving the energy crisis - Simulating the prospects for low cost energy through silicon solar cells

PECAN (Photovoltaic Energy Conversion Analysis) is a highly interactive decision analysis and support system. It simulates the prospects for widespread use of solar cells for the generation of electrical power. PECAN consists of a set of integrated APL functions for evaluating the potential of terrestrial photovoltaics. Specifically, the system is a deterministic simulator, which translates present and future manufacturing technology into economic and financial terms, using the production unit concept. It guides solar cell development in three areas: tactical decision making, strategic planning, and the formulation of alternative options.

Kran, A.↗
DOE OSTI2022

Task Information Presentation System

Demonstrate a novel computer-based procedure solution for a multi-unit power plant. TIPS is developed to demonstrate a way to operate a highly automated plant. Currently, there are no plants (nuclear or non-nuclear) that can support this high level of automation. The purpose of TIPS is to help the industries think beyond the current conduct of operations. TIPS is designed to work with the GSE Systems' Combine-cycle gas turbine power plant simulator. TIPS uses the plant data from the simulator to make the user experience of the computer-based procedure more realistic.

Oxstrand, Johanna↗
DOE OSTI2021

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea . We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py . Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Propulsion Research at the Propulsion Research Center of the NASA Marshall Space Flight Center

The Propulsion Research Center of the NASA Marshall Space Flight Center is engaged in research activities aimed at providing the bases for fundamental advancement of a range of space propulsion technologies. There are four broad research themes. Advanced chemical propulsion studies focus on the detailed chemistry and transport processes for high-pressure combustion, and on the understanding and control of combustion stability. New high-energy propellant research ranges from theoretical prediction of new propellant properties through experimental characterization propellant performance, material interactions, aging properties, and ignition behavior. Another research area involves advanced nuclear electric propulsion with new robust and lightweight materials and with designs for advanced fuels. Nuclear electric propulsion systems are characterized using simulated nuclear systems, where the non-nuclear power source has the form and power input of a nuclear reactor. This permits detailed testing of nuclear propulsion systems in a non-nuclear environment. In-space propulsion research is focused primarily on high power plasma thruster work. New methods for achieving higher thrust in these devices are being studied theoretically and experimentally. Solar thermal propulsion research is also underway for in-space applications. The fourth of these research areas is advanced energetics. Specific research here includes the containment of ion clouds for extended periods. This is aimed at proving the concept of antimatter trapping and storage for use ultimately in propulsion applications. Another activity in this involves research into lightweight magnetic technology for space propulsion applications.

Blevins, John↗
NASA NTRSDate not supplied

Moon to Mars Planetary Autonomous Construction Technology (MMPACT) Lunar Surface Construction Activity at NASA Marshall Space Flight Center

Introduction: The goal of the Moon to Mars Planetary Autonomous Construction Technology (MMPACT) Project at NASA Marshall Space Flight Center (MSFC) is to develop, deliver, and demonstrate on-demand capabilities to protect astronauts and create infrastructure elements on the lunar surface via construction of landing pads, habitats, shelters, roadways, berms, and blast shields using lunar regolith-based materials. MSFC has strong collaborations with industry, academia, and other NASA Centers to accomplish this goal. The MMPACT project consists of three elements. The first focuses on the development of an autonomous construction system. The second focuses on construction feedstock materials development. The third element focuses on the development of a microwave sintering construction capability. The team plans to demonstrate construction on a small Commercial Lunar Payload Services (CLPS) lander in the 2025 timeframe, with a future goal of constructing a subscale landing pad in 2028-2029.The MMPACT project is funded through the Lunar Surface Innovation Initiative, which is part of the Space Technology Mission Directorate. Technology Development: The MMPACT team will evaluate multiple autonomous construction and microwave construction technologies, materials, and construction element forms. Selected technologies will be matured; processes and operations will be defined for the two flight missions. Evaluations of materials, as well as the technology itself, will be demonstrated in simulated lunar environments as part of the technology maturation process. The team is keenly aware of the properties of the lunar environment. Its temperature swings, negligible exosphere, and unprepared site foundations factor into the materials for both construction and hardware, the concept of operations, and the technology’s interdependencies. Materials: The team is looking at materials that can be produced from in-situ resources in an effort to make lunar construction cost-effective. The particular focus of the materials team is cementitious materials, metals, and sintered and melted regolith. These materials will be studied for tensile, compressive, and flexural strength. They will also be tested for their ability to handle thermal swings and vacuum. They will be fully characterized using various microscopy techniques to examine micro-structures, chemistry, and crystal formation. Interdependencies: There are many interdependencies that MMPACT has already identified. These include: •Excavation interface •Regolith feedstock beneficiation •Regolith feedstock storage and provision •Requirements for structures •Site-to-site mobility systems •Availability of lunar simulant •Lander off-loading capabilities •Navigation systems •Power •Regolith composition and mineralogy •Lander specifications •Communication protocols Technology developments in these additional areas would be beneficial to MMPACT.

Moon to Mars Planetary Autonomous Construction Tec↗
NASA NTRS2017

Analyzing the Operational Behavior of the Alignment and Phasing System of the Thirty Meter Telescope using SysML

The Alignment and Phasing System (APS) of the Thirty Meter Telescope (TMT) is responsible for positioning individual segments of the primary mirror, as well as the secondary and tertiary mirrors. Given its essential role, understanding the as-speci ed behavior and verifying related requirements is vital to the correct operation of the TMT. Analyzing the behavior of APS is challenging due to the variety of interactions with other subsystems. This paper presents results from developing an integrated system model that captures the structure, behavior, and requirements in a formal modeling language to enable automated veri cation using appropriate solvers. Speci cally, demonstrated and discussed are the results of applying a Systems Modeling Language (SysMLTM) based approach in which operational modes, behavior speci cations and use case scenarios are used for the purpose of verifying requirements on timing, power, and pointing error through system-level simulation using a single, integrated model.

Troy, Mitchell↗
NASA NTRSDate not supplied

Integrated Bosch Process System Models for In-Situ Oxygen and Carbon Production

In-Situ Resource Utilization (ISRU) technology is a vital component to NASA’s mission of a sustainable presence on the Moon and Mars. Local resources can be leveraged to reduce resupply frequency and mass. Elements of the Bosch process, combined with the carbothermal reduction process, can produce oxygen on the lunar surface with minimal consumables. The Bosch process can also produce oxygen on the Martian surface by using the CO 2 -rich environment. Between both systems, adsorption pump, solar thermal energy, carbon formation reactor, and water recovery subsystems are modeled and integrated to create a functional model in MATLAB software. The model is used to simulate performance of the system and reduce mass, power, and volume requirements. This integrated system model provides a tool to scale ISRU technologies for oxygen and carbon production. The MATLAB model is created by developing a system of independent subsystem models that are solved for their quasi-steady state values which can be integrated with respect to time to determine the change in current states. A flexible time stepping method is used to ensure a high level of accuracy during periods of rapid change while still making use of a simple explicit integration method. The flexible time step is calculated for each independent subsystem and the minimum value from those is used as the overall time step. A flexible time step is calculated by dividing a resolution value, or the maximum change per time step, by the variables current rate of change. The maximum value from all points in space is used for subsystem models that contain multiple values. The process is done for every variable that is being monitored in each subsystem and the global minimum is used as that iteration’s timestep. Several assumptions used in the MATLAB model for fluid flow dynamics, such as 1-D gas flow through the sorption pump, are supported by modeling in Ansys Fluent software. The Lunar oxygen production system is outlined in Fig. 1. The carbothermal reduction subsystem uses solar energy to heat a mixture of lunar regolith and carbon powder to produce carbon monoxide. To begin, the carbon monoxide feeds to the modified Bosch subsystem along with hydrogen gas. The reactants then enter the carbon formation reactor where water and carbon powder are produced. Solar thermal energy is used to add energy to the reactor, but waste heat from the carbothermal process is another potential heat source. The water is collected and electrolyzed to produce hydrogen which reenters the Bosch subsystem, and the oxygen is stored for downstream use. The carbon powder is collected and feeds back into the carbothermal subsystem. The Martian oxygen production system uses the full Bosch process and is outlined in Fig 2. A CO 2 adsorption pump thermally cycles to scrub and pressurize CO 2 from the environment. Along with an initial supply of hydrogen, the reactants enter the Reverse Water Gas Shift Reactor (RWGSR) which produces carbon monoxide and water. Carbon monoxide and unreacted hydrogen enter the carbon formation reactor to produce water and carbon powder. The water is collected from both reactors and electrolyzed to reintroduce hydrogen and store oxygen for propellant production or life support. Carbon is removed from the carbon formation reactor and stored. The adsorption pump utilizes rapid cycle temperature swings within a stack of zeolite coated surfaces. The subsystem model solves 1-D quasi-steady conservation laws of the quasi-steady form, shown in Eq. 1, for the gas stream and heat exchange liquid to predict performance parameters such as breakthrough capacity and optimum cycle time. The source term S is used to capture interactions between the fluid flows and the sorbent. A quasi-steady-state scheme is used where no time derivatives appear in the governing equations, except for those in the source terms. This results in an autonomous system, where ∂F/∂x = ƒ(F). The fluxes F are provided at the inlet, and an explicit method is used to solve for the spatial distribution of F. The heat and mass flows to the sorbent are then extracted from the source terms. These flows are numerically integrated to produce a 1-D solution for the system’s state as a function of both time and space. The body of the adsorption pump is separated into two semi-independent models: the heat exchanger fluid flow and gas flow through the zeolite coated surfaces. Both models are solved using the above-described method to find a 1-D solution as a function of space and interact only once a timestep is taken. The interaction point is the sorbent through which all heat transfer between the two models must occur. Sorbent mass adsorption is calculated using the Lagergren model, shown in Eq. 2, where the transfer coefficient, λ D , is found by solving a system of nondimensionalized equations derived by using the heat and mass transfer analogy for transport phenomena. Using Grade 544 Type 13X zeolite as the sorbent material, the equilibrium concentration, θ eq , is calculated using the k-site Langmuir isotherm and fit parameters. Additionally, the enthalpy of adsorption used in the model is computed by interpolation of available data [1]. The subsystem model was validated using the Rapid Cycle Temperature Swing Adsorption (RC-TSA) pump. The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC). The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC).

In situ Resource Utilization↗
NASA NTRS2003

Transient Simulation of the Integrated Powerhead Demonstrator (IPD) Rocket Engine

The IPD rocket engine is the product of a joint Air Force/NASA program to demonstrate the concept of a full-flow staged combustion power cycle. In this type of rocket engine cycle, both the entire fuel flow and the entire oxidizer flow are combusted in one of two pre-bumers and used to drive two turbopumps, thus utilizing the flow work of the total propellant flow. The basis of the IPD engine program relies on integrating newly developed and pre-existing hardware to demonstrate the component and material technologies to make this concept feasible, while simultaneously saving development time and costs. To provide insight to the project team and contractors during engine development and test phases, the engine system was modeled at MSFC using the Rocket Engine Transient Simulation (ROCETS) software to analyze system performance and determine component integration issues. The ROCETS software is used extensively a MSFC to perform steady-state power-balances and transient simulations of thermodynamic power and general fluid systems. The software is favored for its capability to solve large systems of non-linear equations, its librarie of fluid properties and flow devices, its flexibility to modify existing code to improve the physics-derived approximations of real fluid thermodynamic behavior, and the ability to add unique system constraints. The purpose of this paper is to present the methodology used to model the IPD engine system, detail the pitfalls encountered with the software, and explain the approximations made to more accurately represent engine component and fluid behavior. Engine system performance output from the model will be presented and explained in comparison with real fluid and component behavior.

Guidos, Mike↗
DOE OSTI2023

Advanced Drying Cycle Simulator Thermal Response to Commercial Drying Conditions

The purpose of this report is to document updates on testing of the apparatus built to simulate commercial drying procedures for spent nuclear fuel at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention that incorporate relevant physics and well-controlled boundary conditions. This report documents testing updates for the Advanced Drying Cycle Simulator (ADCS). This apparatus was built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. These waterproof heaters are the next generation design to heater rods developed and tested at Sandia National Laboratories in FY20. This report describes preliminary testing of the ADCS through measurement and analysis of the thermal response of the system to a subset of commercial drying conditions that exclude the introduction of water, namely simulated decay heats and pressures relevant to commercial drying. This test series, referred to as a “dry” test series in this report, spans three uniform waterproof heater rod powers (representing spent fuel decay heats), four helium fill pressures, and six vacuum levels. This test series was conducted to cover the range of expected ADCS testing conditions for upcoming “wet” testing, where water will be introduced and a simulated commercial drying cycle will be performed. The dry test conditions were derived from the commercial drying conditions seen in the High Burnup Demonstration and the vacuum drying conditions chosen for a smaller scale Dashpot Drying Apparatus tested at Sandia National Laboratories in FY22. For a given uniform power and pressure/vacuum level, the ADCS was operated at constant power and pressure and allowed to reach steady state conditions. The thermal data obtained from these tests were analyzed, and the results can inform computational models built to simulate commercial drying processes by providing baseline thermal data prior to the introduction of water. Following the preliminary dry tests, a test plan for the ADCS will be developed to implement a drying procedure that begins with the introduction of water to the system and is based on measurements from the drying process used for the High Burnup Demonstration Project. While applying power to the simulated fuel rods, this procedure is expected to consist of filling the ADCS vessel with water, draining the water with applied pressure and multiple helium blowdowns, evacuating additional water with a vacuum drying sequence at successively lower pressures, and backfilling the vessel with helium. Additional investigations are expected to feature failed fuel rod simulators with engineered cladding defects and guide tubes with obstructed dashpots to challenge the drying system with multiple water retention sites. The data from these investigations is expected to inform the efficacy of commercial drying operations through the quantification of residual water in a prototypic-length dry storage canister.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

A Comprehensive Comparison of Methods for Evaluating Dispatch of Long-Duration Energy Storage in Power Systems Models

Long-duration energy storage (LDES) could play a pivotal role in the transformation of electricity grids with high shares of variable renewable energy (VRE) such as solar and wind. However, the weather-dependent nature of VRE introduces challenges for grid balancing and stability, which LDES - along with short-duration energy storage (SDES) - can help address. However, modeling LDES in production cost models (PCMs) is particularly challenging due to the need for high temporal resolution over extended optimization windows while preserving chronology, which ensures the alignment of energy storage operations with VRE generation over multi-day periods. This report compares traditional dispatch methods with advanced LDES dispatch strategies, such as the extended horizon approach, across different PCM platforms and examines tradeoffs and scalability. The comparison reveals that the traditional 1-day optimization horizon within the PCM leads to inefficient utilization of LDES. In contrast, extending the optimization horizon as much as possible significantly reduces curtailment and improves storage dispatch, especially in renewable-dense systems. There is also promise in using state-of-charge or end volume targets set by an external model, however this requires an additional modeling set and generally increases computational burden. This paper presents a comparison of these various methods in a number of power systems, showing algorithms initially in small test systems and scaling up to large, country-wide simulations. Overall, the research presents the trade-offs of various computational methods and illustrates how LDES may play an essential role in power systems of the future.

14 SOLAR ENERGY↗
NASA NTRS1979

Computer and laboratory simulation of interactions between spacecraft surfaces and charged-particle environments

Cases where the charged-particle environment acts on the spacecraft (e.g., spacecraft charging phenomena) and cases where a system on the spacecraft causes the interaction (e.g., high voltage space power systems) are considered. Both categories were studied in ground simulation facilities to understand the processes involved and to measure the pertinent parameters. Computer simulations are based on the NASA Charging Analyzer Program (NASCAP) code. Analytical models are developed in this code and verified against the experimental data. Extrapolation from the small test samples to space conditions are made with this code. Typical results from laboratory and computer simulations are presented for both types of interactions. Extrapolations from these simulations to performance in space environments are discussed.

Stevens, N. J.↗
DOE OSTI2025

Modeling of Microgrid for Critical Data Center Applications

As part of continuing efforts to develop support, understanding, and infrastructure of data center integration onto the electric grid, our work aims to model and analyze the behavior of data center loads in a microgrid power system. Our model consists of renewable energy sources, batteries, and a nuclear reactor-steam Rankine cycle to power data center loads. The simulation studies investigate the electrical behavior of the microgrid system to assess its ability in supporting large data center electrical demands.

14 - SOLAR ENERGY↗