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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multiphysics simulation of recent experiments on alkali‐silica reaction expansion in reinforced concrete members

Alkali‐silica reaction (ASR) is an important degradation process that causes volumetric expansion and damage in concrete, and is affected significantly by the local temperature, moisture and stress conditions that often vary across the regions of a structure. Numerical simulation is essential to predict the progression and effects of ASR on the performance of structures. Because of the interactions between thermal and moisture transport and mechanical deformation, it is important for numerical models to represent all these physical phenomena and the coupling between them. Simulations of ASR in reinforced concrete (RC) structures are further complicated by the need to capture interactions between concrete and embedded reinforcing bars. Here, this paper describes the implementation of a scalable, coupled‐physics ASR model for simulating RC structures and assesses the ability of that model to predict ASR‐induced expansion in recent laboratory tests on RC block and beam specimens. These laboratory tests and the simulation approach were selected because of their applicability to RC structural‐scale simulations. This validation study helps builds confidence the ability of this approach to model ASR expansion in large, complex RC structures, which is a current high‐priority need.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analysis of predicted mean vote-based model predictive control for residential HVAC systems

Model Predictive Control (MPC) is an advanced process control method that has attracted much attention in building heating, ventilation, and air conditioning (HVAC) systems. Here, this paper analyzes the optimal precooling performance in residential buildings using MPC with two different comfort indices, namely, temperature and predicted mean vote (PMV). It first formulates, for each comfort index, an optimization problem that accounts for different factors, such as weather, home thermal condition, prediction horizon, time-of use (TOU) utility rate, and rated cooling capacity. The problem is then solved, resulting in an MPC strategy that determines the HVAC on/off control signal and minimizes energy cost over a receding time horizon while maintaining thermal comfort. The energy performance difference between temperature-based and PMV-based MPC strategies is subsequently investigated, especially in light of the interior wall surface temperature and under different combinations of the factors. Extensive simulation results demonstrated that the proposed MPC strategies are adaptive and their performances depend primarily on weather, home thermal condition, and prediction horizon, while the impact of TOU utility rate and rated cooling capacity is relatively small. Because the PMV-based MPC strategy can take advantage of the lower interior wall surface temperature due to precooling, it resulted in 8–45% cost savings for the scenarios investigated and an average increase of 0.042–0.113 in the absolute value of the PMV index compared to the temperature-based MPC strategy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Dynamic Parameter Estimation with Physics-based Neural Ordinary Differential Equations

Accurate estimation of dynamic parameters of gen-erators is crucial to building a reliable model for dynamical studies and reliable operation of the power system. This paper develops a physics-based neural ordinary differential equations (ODE) approach to learn the parameters of generator dynamic model using phasor measurement units (PMU) data. We design a physics-based neural network to represent the swing equations of the power system dynamics. A loss function is defined as the difference between dynamic simulation results from the physics-based neural networks and pseudo PMU measurements. The parameters of generator dynamic model are iteratively updated using the neural ODEs and the adjoint method. By exploiting the mini-batch scheme in neural ODE training, the parameter estimation performance is significantly improved. Numerical study results on a 3-machine 9-bus system show that the proposed algorithm outperforms state-of-the-art baseline method in both computation time and dynamic parameter estimation accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Viscosity Measurements of the HLW APPS Glasses

The U.S. Department of Energy is responsible for building the Hanford Waste Treatment and Immobilization Plant (WTP) at the Hanford site in Washington to remediate 56 million gallons of radioactive waste historically stored in 177 underground tanks. The Office of River Protection has requested that the Savannah River National Laboratory (SRNL) contribute in areas of recognized capabilities and expertise for glass waste form development to support successful startup of the WTP. SRNL support of this work is defined in the Task Technical and Quality Assurance Plan.1 This report provides results from viscosity measurements on a series of simulated nuclear waste glasses designed and fabricated at Pacific Northwest National Laboratory (PNNL). The glasses were designated the high-level waste – Aspen Process Performance Simulation (HLW-APPS) study glasses. The data provided in this report is to be used in the development, validation, and implementation of enhanced property/composition models for nuclear waste glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

The Impact of Operated Window Shading on Visual Comfort, Non-Visual Health, and Energy Demand from Electric Lighting

This paper introduces a simulation-based workflow to assess annual circadian lighting performance, glare risk and energy demand for an array of seated view positions under operated shading and electric lighting conditions. This workflow uses a combination of 9-band and 81-band simulations to represent daylight and electric lighting respectively. Annual daylight-driven calculations rely on a python-based code provided in the LARK simulation engine which was used to run 180-degree high dynamic range (HDR) renderings with 9-bands of spectral resolution. The results reveal the impact of shading systems on equivalent melanopic lux (EML) and daylight glare probability (DGP) over time and the energy demand (kWh) from electric lighting systems to supplement eye-level recommendations from the WELL v2 Building Standard.

Rockcastle, Siobhan↗
NASA NTRS2005

Developing a Framework for Effective Network Capacity Planning

As Internet traffic continues to grow exponentially, developing a clearer understanding of, and appropriately measuring, network's performance is becoming ever more critical. An important challenge faced by the Information Resources Directorate (IRD) at the Johnson Space Center in this context remains not only monitoring and maintaining a secure network, but also better understanding the capacity and future growth potential boundaries of its network. This requires capacity planning which involves modeling and simulating different network alternatives, and incorporating changes in design as technologies, components, configurations, and applications change, to determine optimal solutions in light of IRD's goals, objectives and strategies. My primary task this summer was to address this need. I evaluated network-modeling tools from OPNET Technologies Inc. and Compuware Corporation. I generated a baseline model for Building 45 using both tools by importing "real" topology/traffic information using IRD's various network management tools. I compared each tool against the other in terms of the advantages and disadvantages of both tools to accomplish IRD's goals. I also prepared step-by-step "how to design a baseline model" tutorial for both OPNET and Compuware products.

Yaprak, Ece↗
NASA NTRS2017

The Heliopause Electrostatic Rapid Transit System (HERTS) Design, Trades, and Analyses Performed in a Two Year NASA Investigation of Electric Sail Propulsion Systems

The Heliopause Electrostatic Rapid Transit System (HERTS) was one of the seven total Phase II NASA Innovative Advanced Concepts (NIAC) that was down-selected in 2015 for continued funding and research. In Phase I our team learned that a spacecraft propelled by an Electric Sail (E-Sail) can travel great astronomical distances, such as to the Heliopause region of the solar system (approx. 100 to 120 AU) in approximately one quarter of the time (10 years) versus the time it took the Voyager spacecraft launched in 1977 (36 years). The completed work within the Phase II NIAC funded effort builds upon the work that was done in the Phase I NIAC and is focused on: 1) Testing of plasma interaction with a charged wire in a MSFC simulated solar environment vacuum test chamber. 2) Development of a Particle-in-Cell (PIC) models that are validated in the plasma testing and used to extrapolate to the E-Sail propulsion system design. 3) Conceptual design of a Technology Demonstration Mission (TDM) spacecraft developed to showcase E-Sail propulsion systems. 4) Down selection of both: a) Materials for a multi km length conductor and, b) Best configuration of the proposed conductor deployment subsystem. This paper will document the findings to date (June, 2017) of the above focused areas.

Wiegmann, Bruce M.↗
DOE OSTI2026

Reduction of baseplate distortion during directed energy deposition using compliant features

Distortion in additive manufacturing (AM) remains a barrier to its adoption in precision industries. Baseplate warpage is one such issue which compromises the feasibility of post-process precision machining. The restriction to thermal contraction of the deposited part, imposed by the baseplate, generates bending moments, that in turn causes warpage. A novel distortion mitigation strategy using baseplates with integrated compliant features, which enables thermal contraction of the build is presented. Six unique design concepts are evaluated, including a solid reference, using two deposition geometries. A laser, hot-wire, directed energy deposition (DED) process is used to deposit a symmetric cylindrical part (C-part) and a T-shaped asymmetric part (T-part). Flatness deviation of baseplates is measured using structured light 3D scanning. Measurements reveal a reduction in net flatness deviation of 58.8% for the C-part and 40.9% for the T-part, compared to the solid reference. While most designs yielded reductions exceeding 30% and 20% for the C- and T-parts, respectively, one configuration resulted in increased deviation. Finite element (FE) simulations are performed to elucidate the underlying mechanisms affecting distortion of compliant baseplates during DED. Despite variations between predictions and measurements, agreement in the general trend is observed. It also revealed that initial flatness errors in baseplates significantly affect its deviation during deposition. Predictions indicate that compliant features significantly affect the thermal distribution as well as the evolution of flatness deviation in the baseplate during deposition. Notably, one design exhibited a reduction in distortion during cooling, following its initial increase during deposition. FE predictions show a maximum reduction of 60.9% and 38.8% in net flatness deviation for the C- and T-parts, respectively. The performance of compliant baseplates is found to be governed by both its the thermal and mechanical characteristics, which are crucial factors to be considered during design.

Mathews, Ritin [ORNL] (ORCID:0000000301440828)↗
DOE OSTI2022

Realistic simulations of spin squeezing and cooperative coupling effects in large ensembles of interacting two-level systems

We describe an efficient numerical method for simulating the dynamics of interacting spin ensembles in the presence of dephasing and decay. The method builds on the discrete truncated Wigner approximation for isolated systems, which combines the mean-field dynamics of a spin ensemble with a Monte Carlo sampling of discrete initial spin values to account for quantum correlations. Here we show how this approach can be generalized for dissipative spin systems by replacing the deterministic mean-field evolution by a stochastic process, which describes the decay of coherences and populations while preserving the length of each spin. We demonstrate the application of this technique for simulating nonclassical spin-squeezing effects or the dynamics and steady states of cavity QED models with 10 5 interacting two-level systems. This opens up the possibility to perform accurate real-scale simulations of a diverse range of experiments in quantum optics or with solid-state spin ensembles under realistic laboratory conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Multiphysics modeling of accelerators through code integration

This work aims to improve the ability of particle accelerator researchers to develop high-performance accelerator cavity designs by creating an overall multiphysics framework that integrates and couples existing application codes. This framework will allow accelerator researchers to build multiphysics models that will optimize cavity design, improve understanding of whole-device performance, and reduce the development and fabrication costs of accelerator research. We utilize the open-source VizSchema data standard as an intermediate data structure interface layer to standardize interfaces between individual application codes. VizScema is extensively documented online, and plugins for VizSchema are available for popular visualization packages, including VisIt and ParaView. Currently, the work focuses on coupling the EM field solver COMSOL and the electron gun code MICHELLE to allow COMSOL field-solve results to be seamlessly used by MICHELLE for particle-solve. Later work will extend this integration to include other fields, particles, and thermodynamics simulation codes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

A Modeling Toolkit for Comparing AC and DC Electrical Distribution Efficiency in Buildings

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.

DC distribution↗
DOE OSTI2023

Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy

Recent developments integrating micromechanics and neural networks offer promising paths for rapid predictions of the response of heterogeneous materials with similar accuracy as direct numerical simulations. The deep material network is one such approaches, featuring a multi-layer network and micromechanics building blocks trained on anisotropic linear elastic properties. Once trained, the network acts as a reduced-order model, which can extrapolate the material’s behavior to more general constitutive laws, including nonlinear behaviors, without the need to be retrained. However, current training methods initialize network parameters randomly, incurring inevitable training and calibration errors. Here, we introduce a way to visualize the network parameters as an analogous unit cell and use this visualization to “quilt” patches of shallower networks to initialize deeper networks for a recursive training strategy. The result is an improvement in the accuracy and calibration performance of the network and an intuitive visual representation of the network for better explainability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Chemistry↗
NASA NTRS1991

The Biological Flight Research Facility

NASA Ames Research Center is building a research facility, the Biological Flight Research Facility (BFRF), to meet the needs of life scientists to study the long-term effects of variable gravity on living systems. The facility will be housed on Space Station Freedom and is anticipated to operate for the lifetime of the station, approximately 30 years. It will allow plant and animal biologists to study the role of gravity, or its absence, at varying gravity intensities for varying periods of time and with various organisms. The principal difference between current Spacelab missions and those on Space Station Freedom, other than length of mission, will be the capability to perform on-orbit science procedures and the capability to simulate earth gravity. Initially, the facility will house plants and rodents in habitats which can be maintained at microgravity or can be placed on a 2.5-m diam centrifuge. However, the facility is also being designed to accommodate future habitats for small primates, avian, and aquatic specimens. The centrifuge will provide 1 g for controls and will also be able to provide gravity from 0.01 to 2.0 g for threshold gravity studies as well as hypergravity studies. The BFRF will provide the means to conduct basic experiments to gain an understanding of the effects of microgravity on the structure and function of plants and animals, as well as investigate the role of gravity as a potential countermeasure for the physiological changes observed in microgravity.

Johnson, Catherine C.↗
NASA NTRS1993

The Biological Flight Research Facility

NASA Ames Research Center (ARC) is building a research facility, the Biological Flight Research Facility (BFRF), to meet the needs of life scientists to study the long-term effects of variable gravity on living systems. The facility will be housed on Space Station Freedom and is anticipated to operate for the lifetime of the station, approximately thirty years. It will allow plant and animal biologists to study the role of gravity, or its absence, at varying gravity intensities for varying periods of time and with various organisms. The principal difference between current Spacelab missions and those on Space Station Freedom, other than length of mission, will be the capability to perform on-orbit science procedures and the capability to simulate earth gravity. Initially the facility will house plants and rodents in habitats which can be maintained at microgravity or can be placed on a 2.5 meter diameter centrifuge. However, the facility is also being designed to accommodate future habitats for small primates, avian, and aquatic specimens. The centrifuge will provide 1 g for controls and will also be able to provide gravity from 0.01 to 2.0 g for threshold gravity studies as well as hypergravity studies. Included in the facility are a service unit for providing clean chambers for the specimens and a glovebox for manipulating the plant and animal specimens and for performing experimental protocols. The BFRF will provide the means to conduct basic experiments to gain an understanding of the effects of microgravity on the structure and function of plants and animals, as well as investigate the role of gravity as a potential countermeasure for the physiological changes observed in microgravity.

Johnson, Catherine C.↗
NASA NTRS2002

Space Operations Analysis Using the Synergistic Engineering Environment

The Synergistic Engineering Environment has been under development at the NASA Langley Research Center to aid in the understanding of the operations of spacecraft. This is accomplished through the integration of multiple data sets, analysis tools, spacecraft geometric models, and a visualization environment to create an interactive virtual simulation of the spacecraft. Initially designed to support the needs of the International Space Station, the SEE has broadened the scope to include spacecraft ranging from low-earth orbit to deep space missions. Analysis capabilities within the SEE include rigid body dynamics, kinematics, orbital mechanics, and payload operations. This provides the user the ability to perform real-time interactive engineering analyses in areas including flight attitudes and maneuvers, visiting vehicle docking scenarios, robotic operations, plume impingement, field of view obscuration, and alternative assembly configurations. The SEE has been used to aid in the understanding of several operational procedures related to the International Space Station. This paper will address the capabilities of the first build of the SEE, present several use cases of the SEE, and discuss the next build of the SEE.

Angster, Scott↗
NASA NTRS2007

The Effect of Acoustic Disturbances on the Operation of the Space Shuttle Main Engine Fuel Flowmeter

The Space Shuttle Main Engine (SSME) uses a turbine fuel flowmeter (FFM) in its Low Pressure Fuel Duct (LPFD) to measure liquid hydrogen flowrates during engine operation. The flowmeter is required to provide accurate and robust measurements of flow rates ranging from 10000 to 18000 GPM in an environment contaminated by duct vibration and duct internal acoustic disturbances. Errors exceeding 0.5% can have a significant impact on engine operation and mission completion. The accuracy of each sensor is monitored during hot-fire engine tests on the ground. Flow meters which do not meet requirements are not flown. Among other parameters, the device is screened for a specific behavior in which a small shift in the flow rate reading is registered during a period in which the actual fuel flow as measured by a facility meter does not change. Such behavior has been observed over the years for specific builds of the FFM and must be avoided or limited in magnitude in flight. Various analyses of the recorded data have been made prior to this report in an effort to understand the cause of the phenomenon; however, no conclusive cause for the shift in the instrument behavior has been found. The present report proposes an explanation of the phenomenon based on interactions between acoustic pressure disturbances in the duct and the wakes produced by the FFM flow straightener. Physical insight into the effects of acoustic plane wave disturbances was obtained using a simple analytical model. Based on that model, a series of three-dimensional unsteady viscous flow computational fluid dynamics (CFD) simulations were performed using the MSFC PHANTOM turbomachinery code. The code was customized to allow the FFM rotor speed to change at every time step according to the instantaneous fluid forces on the rotor, that, in turn, are affected by acoustic plane pressure waves propagating through the device. The results of the simulations show the variation in the rotation rate of the flowmeter due to the interaction of the flow straightener wakes and the upstream propagating acoustic waves. A detailed analysis of the acoustic disturbance effects is presented along with an assessment of the impact on measurement accuracy.

Marcu, Bogdan↗