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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of a Sizing and Modeling Platform for District Energy Systems with Geothermal Heat Pumps

Existing tools for community or urban scale energy system modeling and simulation are often limited in their capabilities and require expert-level modeling proficiency to develop system models. To fill this gap, this paper proposes an integrated sizing and modeling platform for district energy systems with geothermal heat pumps. The proposed platform takes in geometric and non-geometric user inputs related to the buildings, borefield, and district energy loop. Then, the platform sizes the geothermal heat exchanger, generates a corresponding district energy system model, and runs an annual simulation automatically. We validated the simulation performance of the borefield in our tool against EnergyPlus. A case study is provided in this paper to demonstrate the workflow and simulation result plausibility of the proposed platform.

decarbonization↗
DOE OSTI2021

Standardizing Performance Metrics for Building-Level Electrical Distribution Systems

Building-level electrical distribution systems comprise a myriad of current-carrying equipment, conversion devices, and protection devices that deliver power from the utility or local distributed energy resources to end-use building loads. Electric power has traditionally been generated, transmitted, and distributed in alternating current (AC). However, the last decade has seen a significant increase in the integration of native direct current (DC) equipment that has elevated the importance of DC distribution systems. Numerous studies have comparatively examined the performance of various electrical distribution systems in buildings but have failed to achieve uniform conclusions, primarily because of a lack of consistent and analogous performance evaluation methods. This paper aims to fill this gap by providing a standard set of metrics and measurement boundaries to consistently evaluate the performance of AC, DC, or hybrid AC/DC electrical distribution systems. The efficacy of the proposed approach is evaluated on a representative medium-sized commercial office building model with AC distribution and an equivalent hybrid AC/DC and DC distribution model, wherein the AC distribution model is concluded to be the most efficient. The simulation results show variation in computed metrics with different selected boundaries that verify the effectiveness of the proposed approach in ensuring consistent computation of the performance of building-level electrical distribution systems. This paper provides an initial set of guidelines for building energy system stakeholders to adopt appropriate solutions, thus leading to more efficient energy systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Thermoplastic Composite Lunar Tower Truss Structure: Design Development and Verification Plans

The National Aeronautics and Space Administration (NASA) Space Technology and Mission Directorate (STMD) is advancing thermoplastic composite (TPC) technologies for exploration missions. The Technology Development for Exploration Applications (TDEA) project goals are to develop and mature TPC materials, designs, analyses tools and techniques, and mature manufacturing processes. This includes development of manufacturing and joining approaches relevant to space environments. To these ends TDEA endeavors toward demonstrating a TPC truss structure for a lunar tower configuration. The design, predicated on robotic assembly, uses open section truss elements fused to a joint splice plate, without a structural adhesive. This presentation details the TDEA lunar truss structure design development approach including design heritage, the requirements established, the mechanical design and analyses, and thermal analyses demonstrating structural requirements conformance, as well as planned building block verification efforts either underway or planned. The mechanical analyses show the most severe environment is a moon-quake the truss dynamic responses. The thermal analyses show the extreme cold for on-orbit welding, the window for less severe on-orbit welding, as well as the large thermal gradients on the truss. The building block approach shown includes ultrasonic welding and lap shear coupon testing on various truss element thicknesses and layups. Knockdown factor determinations due to lunar dust contamination (simulated) and effects of welding in a vacuum are presented. The most highly loaded truss joint configuration sub-element verification test matrix is outlined. Lastly, plans to build, inspect, and test a 2-bay truss representative unit cell that is 1.5 meters by 1.5 meters by 3.0 meters tall are detailed.

Lunar Tower↗
NASA NTRSDate not supplied

Improving Kinetic Consistency Across Elastic Model Transitions With Quadratic Inequality Constrained Weighted Least Squares (WLSQI)

Flexible body modeling presents a large challenge in the development of simulations to aid in design of flight control systems for launch and landing vehicles. Typically, the flexible body model is not a single continuous model but are rather discrete sets of Linear Time Invariant (LTI) Finite Element Models (FEM) incremented by propellant levels. This introduces the problem of smoothly transitioning modal and physical states of the vehicle when switching from one FEM to the next. This paper introduces a new approach to optimally transition flexible body states with weighted least squares, building off previous methods.

GN&C↗
NASA NTRS2004

Simulations of Hyperthermal Oxygen Beam Exposures

Pulsed sources of hyper-thermal O-atoms are now being extensively used to simulate low-earth orbit (LEO) surface exposure environments. The peak flux of these sources is many orders of magnitude larger than the corresponding LEO flux. Although it is desirable to accelerate the test by using higher fluxes than found in LEO, even commonly used fluxes are large enough to produce multi-collision effects by causing a build-up of gas at the sample surface. In this paper we characterize the physical consequences to the experiment using the direct simulation Monte Carlo (DSMC) method, DSMC allows us to extract the distributions of energy and impact angle for the O-atoms that reach the surface, and to record how strongly the gas build-up at the target assembly deflects flux from downstream instrumentation. By considering a range of source fluxes, we determine the onset conditions and severity of these multi-collision effects. We find that even at common experimental fluxes with a normally incident beam string a flat surface sample, the energy distribution of incident O-atoms broadens and develops a significant low-energy tail. The angular distributions also broaden significantly. The number of O-atoms that reach downstream instrumentation is decreased by approximately 50%. These simulations will aid in the calibration of ground-based O-atom measurements,a nd provide a model for the energy and angular distributions of O-atoms that actually impinge on surface samples.

Finchum, A.↗
NASA NTRS2003

DSMC Simulations of Hyperthermal Oxygen Beam Exposures

Pulsed sources of hyper-thermal O-atoms are now being extensively used to simulate low-earth orbit (LEO) surface exposure environments. The peak flux of these sources is many orders of magnitude larger than the corresponding LEO flux. Although it is desirable to accelerate the test by using higher fluxes than found in LEO, even commonly used fluxes are large enough to produce multi-collision effects by causing a build-up of gas at the sample surface. In this paper we characterize the physical consequences to the experiment using the direct simulation Monte Carlo (DSMC) method. DSMC allows us to extract the distributions of energy and impact angle for the O-atoms that reach the surface, and to record how strongly the gas build-up at the target assembly deflects flux from downstream instrumentation. By considering a range of source fluxes, we determine the onset conditions and severity of these multi-collision effects. We find that even at common experimental fluxes with a normally incident beam striking a flat surface sample, the energy distribution of incident O-atoms broadens and develops a significant low-energy tail. The angular distributions also broaden significantly. The number of O-atoms that reach downstream instrumentation is decreased by approximately 50%. These simulations will aid in the calibration of ground-based O-atom measurements, and provide a model for the energy and angular distributions of O-atoms that actually impinge on surface samples.

Cline, Jason A.↗
DOE OSTI2022

Thermal modeling of directed energy deposition additive manufacturing using graph theory

Purpose: The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach: Here, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings: The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications: This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts. Practical implications: The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value: This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.

42 ENGINEERING↗
DOE OSTI2023

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Manufacturing Process Simulation of Large-Scale Cryotanks

NASA's Space Launch Initiative (SLI) is an effort to research and develop the technologies needed to build a second-generation reusable launch vehicle. It is required that this new launch vehicle be 100 times safer and 10 times cheaper to operate than current launch vehicles. Part of the SLI includes the development of reusable composite and metallic cryotanks. The size of these reusable tanks is far greater than anything ever developed and exceeds the design limits of current manufacturing tools. Several design and manufacturing approaches have been formulated, but many factors must be weighed during the selection process. Among these factors are tooling reachability, cycle times, feasibility, and facility impacts. The manufacturing process simulation capabilities available at NASA's Marshall Space Flight Center have played a key role in down selecting between the various manufacturing approaches. By creating 3-D manufacturing process simulations, the varying approaches can be analyzed in a virtual world before any hardware or infrastructure is built. This analysis can detect and eliminate costly flaws in the various manufacturing approaches. The simulations check for collisions between devices, verify that design limits on joints are not exceeded, and provide cycle times which aid in the development of an optimized process flow. In addition, new ideas and concerns are often raised after seeing the visual representation of a manufacturing process flow. The output of the manufacturing process simulations allows for cost and safety comparisons to be performed between the various manufacturing approaches. This output helps determine which manufacturing process options reach the safety and cost goals of the SLI.

Babai, Majid↗
NASA NTRS2003

Manufacturing Process Simulation of Large-Scale Cryotanks

NASA's Space Launch Initiative (SLI) is an effort to research and develop the technologies needed to build a second-generation reusable launch vehicle. It is required that this new launch vehicle be 100 times safer and 10 times cheaper to operate than current launch vehicles. Part of the SLI includes the development of reusable composite and metallic cryotanks. The size of these reusable tanks is far greater than anything ever developed and exceeds the design limits of current manufacturing tools. Several design and manufacturing approaches have been formulated, but many factors must be weighed during the selection process. Among these factors are tooling reachability, cycle times, feasibility, and facility impacts. The manufacturing process simulation capabilities available at NASA.s Marshall Space Flight Center have played a key role in down selecting between the various manufacturing approaches. By creating 3-D manufacturing process simulations, the varying approaches can be analyzed in a virtual world before any hardware or infrastructure is built. This analysis can detect and eliminate costly flaws in the various manufacturing approaches. The simulations check for collisions between devices, verify that design limits on joints are not exceeded, and provide cycle times which aide in the development of an optimized process flow. In addition, new ideas and concerns are often raised after seeing the visual representation of a manufacturing process flow. The output of the manufacturing process simulations allows for cost and safety comparisons to be performed between the various manufacturing approaches. This output helps determine which manufacturing process options reach the safety and cost goals of the SLI. As part of the SLI, The Boeing Company was awarded a basic period contract to research and propose options for both a metallic and a composite cryotank. Boeing then entered into a task agreement with the Marshall Space Flight Center to provide manufacturing simulation support. This paper highlights the accomplishments of this task agreement, while also introducing the capabilities of simulation software.

Babai, Majid↗
DOE OSTI2021

Informing the planning of rotating power outages in heat waves through data analytics of connected smart thermostats for residential buildings

Abstract With climate change, heat waves have become more frequent and intense. Rotating power outages happen when the power supply is unable to meet the cooling demand increase resulting from extreme high temperatures. Power outages during heat waves expose residents to high risks of overheating. In this study, we propose a novel data-driven inverse modelling approach to inform decision makers and grid operators on planning rotating power outages. We first infer the building thermal characteristics using the connected smart thermostat data, and used the estimated thermal dynamics to simulate the thermal resilience during a heat wave event. Our proposed method was tested for the California power outage in August 2020 by using the open source Ecobee Donate Your Data dataset. We found in California the power outage should not last more than two hours during heat waves to avoid overheating risks. Informing the residents in advance so they can prepare for it through pre-cooling is a simple but effective strategy to expand the acceptable power outage duration. In addition to assisting power outage planning, the proposed method can be used for other applications, such as to evaluate a building energy efficiency policy, to examine fuel poverty, and to estimate the load shifting potential of building stocks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandia’s DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization.

Shenoy, Rajiv R.↗
NASA NTRS1974

A wind model for an elevated STOL-port configuration

Measurements of mean velocity magnitude and direction as well as three-dimensional turbulence intensity were made in the flow over a model of an elevated STOL-port. A 1:300 scale model was placed in a wind tunnel flow simulating the mean velocity profile and turbulence characteristics of atmospheric winds over a typical city environment excluding detailed wake structures of possible nearby buildings. Hot-wire anemometer measurements of velocity and turbulence were made along approach and departure paths of aircraft operating on the runway centerline and at specified lateral distances from the centerline. Approach flow directions simulated were 0 and 30 degrees to the runway centerline.

Peterka, J. A.↗
NASA NTRS2008

Advanced Stirling Convertor (ASC)--From Technology Development to Future Flight Product

The Advanced Stirling Convertor (ASC) is being developed by Sunpower Inc. under contract to NASA s Glenn Research Center (GRC) with critical technology support tasks led by GRC. The ASC development, funded by NASA s Science Mission Directorate, started in 2003 as one of 10 competitively awarded contracts that were intended to address the power conversion needs of future Radioisotope Power Systems (RPS). The ASC technology has since evolved through progressive convertor builds and successful testing to demonstrate high conversion efficiency (38 percent), low mass (1.3 kg), hermetic sealing, launch vibration simulation, EMI characterization, and is undergoing extended operation. The GRC and Sunpower team recently delivered two ASC-E convertors to the Department of Energy (DOE) and Lockheed Martin Space Systems Company for integration onto the Advanced Stirling Radioisotope Generator Engineering Unit (ASRG EU) plus one spare. The design of the next build, called the ASC-E2, has recently been initiated and is based on the heritage ASC-E with design refinements to increase reliability margin and offer higher temperature operation and improve performance. The ASC enables RPS system specific power of about 7 to 8 W/kg. This paper provides a chronology of ASC development to date and summarizes technical achievements including advancements toward flight implementation of the technology on ASRG by as early as 2013.

Wong, Wayne A.↗
DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact Scenarios

Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber (DEA) under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. The presence of this energy absorbing device reduced the peak impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to a system-integrated finite element model of the test article developed in parallel with the test program. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests were conducted to evaluate the impact performances of various components and subsystems, including new crush tubes and the DEA blocks. Parameters defined for the system-integrated finite element model were determined from these tests. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the full-scale crash test without the DEA. This combination of heuristic and quantitative methods identified modeling deficiencies, evaluated parameter importance, and proposed required model changes. The multidimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and copilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. One lesson learned was that this approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and pretest predictions. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, potentially reducing overall development costs.

Annett, Martin S.↗
DOE OSTI2020

A new spatially distributed added value index for regional climate models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles

The added value of using regional climate models (RCMs) to downscale data from general circulation models (GCMs) has often been questioned and researched. Although several studies have used different methods to identify (and in some cases quantify) the added value, there is still a need to find a general metric that quantifies the added value of any variable. This paper builds on past studies to propose a new metric of added value in the simulation of present-day climate which measures the difference in the probability density functions (PDFs) at each grid-cell between a model and an observation source, and then compares the results of the RCM and GCM in order to spatially compute the added value index. The same method is also adapted to quantify the climate change downscaling signal in a way that is consistent with the present-day metric. These new metrics are tested on the daily precipitation output from the EURO-CORDEX and CORDEX-CORE projection ensembles and reveal an overall positive added value of RCMs, especially at the tail-end of the distribution. Higher added value is obtained in areas of complex topography and coast-lines, as well as in tropical regions. Areas with large added value in present-day climate are consistent with areas of significant climate change downscaling signal in the RCP 8.5 far future simulations, and when the analysis is repeated at a low-resolution. The use of different resolution observations shows that the added value tends to decrease when models are compared to low-resolution observation datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A statistical model to predict ignition probability

Ignition capability is a critical design constraint for aeronautical gas turbines. However the current trend toward overall lean burn is detrimental to the engine ignition and relight and the ignition system must be adapted to ensure a fast and reliable light-round in all circumstances. As ignition is a stochastic phenomenon, the optimization of an ignition system requires to build ignition probability maps, which is difficult and costly with either experiment or numerical simulation as both require many tests. Here, this work proposes a model to predict the ignition probability map, knowing only flow statistics in non-reacting conditions, i.e., with only one test. The originality of the model is to construct statistics of the flame kernel trajectory, which are then combined with local flow indicators to evaluate the ignition probability at the considered sparking location. Application to a swirled burner operated in premixed, non-premixed and spray combustion modes illustrates the model concepts and demonstrates its ability to recover the experimental ignition map with good accuracy.

42 ENGINEERING↗