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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Removing Rotational Variations from Shoulder Thermocouples in Friction Stir Welding

Thick plate and lower temperature friction stir welding results in good post-weld properties by welding at very low tool rotational speeds. Low speeds cause large variations in the measured shoulder temperature, making temperature control difficult. This paper describes a computationally light method to correct for oscillating measured temperatures. Data is collected over the previous two revolutions and used to build a compensation table and calculate a derivative. In simulation, measured temperature variations are reduced by a factor of five to ten. Temperature data is preserved and not cornered, nor is any time delay induced by this method, unlike with filtering methods.

Friction Stir Welding, Temperature↗
DOE OSTI2024

EFT Workshop at Notre Dame

The LPC EFT workshop was held April 25-26, 2024 at the University of Notre Dame. The workshop was organized into five thematic sessions: "how far beyond linear" discusses issues of truncation and validity in interpretation of results with an eye towards practicality; "reconstruction-level results" visits the question of how best to design analyses directly targeting inference of EFT parameters; "logistics of combining likelihoods" addresses the challenges of bringing a diverse array of measurements into a cohesive whole; "unfolded results" tackles the question of designing fiducial measurements for later use in EFT interpretations, and the benefits and limitations of unfolding; and "building a sample library" addresses how best to generate simulation samples for use in data analysis. This document serves as a summary of presentations, subsequent discussions, and actionable items identified over the course of the workshop.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Ground Source Heat Pump Computational Results

This data submission includes simulation results for ground loop heat pump systems located in 6 different cities across the United States. The cities are Boston, MA, Dayton, OH, Omaha, NE, Orlando, FL, Sacramento, CA, and St. Paul, MN. These results were obtained from the two-dimensional geothermal computer code called GEO2D. GEO2D was written as part of this DOE funded grant. The results included in this submission for each of the 6 cities listed above are: 1) specific information on the building being heated or cooled by the ground loop geothermal system, 2) some extreme values for the building heating and cooling loads during the year, 3) the inputs required to carry out the simulation, 4) a plot of the hourly building heating and cooling loads throughout the year, 5) a plot of the fluid temperature exiting the ground loop for a 20 year period, 6) a plot of the heat exchange between the ground loop and the ground for a 20 year period, and 7) ground and ground loop temperature contour plots at different times of the year for the 20 year period.

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

A Comparison of Simulation Capabilities for Ducts

Typically, the cheapest way to install a central air conditioning system in residential buildings is to place the ductwork in the attic. Energy losses due to duct-attic interactions can be great, but current whole-house models are unable to capture the dynamic multi-mode physics of the interactions. The building industry is notoriously fragmented and unable to devote adequate research resources to solve this problem. Builders are going to continue to put ducts in the attic because floor space is too expensive to closet them within living space, and there are both construction and aesthetic issues with other approaches such as dropped ceilings. Thus, there is a substantial need to publicly document duct losses and the cost of energy used by ducts in attics so that practitioners, builders, homeowners and state and federal code officials can make informed decisions leading to changes in new construction and additional retrofit actions. Thus, the goal of this study is to conduct a comparison of AtticSim and EnergyPlus simulation algorithms to identify specific features for potential inclusion in EnergyPlus that would allow higher-fidelity modeling of HVAC operation and duct transport of conditioned air. It is anticipated that the resulting analysis from these simulation tools will inform energy decisions relating to the role of ducts in future building energy codes and standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2000

Simulation and Experimental Measurements of Inductively Coupled CF4 and CF4/Ar Plasmas

The recently developed code SEMS (semiconductor equipment modeling software)is applied to the simulation of CF4 and CF4/Ar inductively coupled plasmas (ICP). This work builds upon the earlier nitrogen, transformer coupled plasma (TCP) SEMS research by demonstrating its accuracy for more complex reactive mixtures, moving closer to the realization of a virtual plasma reactor. Attention is given to the etching of and/or formation of carbonaceous films on the quartz dielectric window and diagnostic aperatures. The simulations are validated through comparisons with experimental measurements using FTIR (Fourier Transform Infrared) and UV absorption spectroscopy for CFx and SiFx neutral radicals, QMS (quadrupole mass spectrometry) for the ions, and Langmuir probe measurements of electron number density and temperature in an ICP GEC reference cell.

Hash, D. B.↗
DOE OSTI2023

A multiscale recurrent neural network model for predicting energy production from geothermal reservoirs

Optimization of energy production from geothermal reservoirs requires reliable prediction of energy production performance under alternative operation and development scenarios. Traditionally, reservoir simulation models are used for the evaluation and screening of alternative production and development plans. However, simulation models require extensive data collection and modeling efforts and are time-consuming to build, run, and update. Data-driven predictive models, on the other hand, can serve as efficient prediction tools that can be used for decision support and management of daily operations and surveillance activities. Data-driven models become particularly attractive when a reservoir simulation model for a field does not exist and/or is difficult to build. Machine learning (ML)-based data-driven models that have recently become popular in several fields exploit statistical patterns and relations in training data to generate predictions. As such, they tend to perform better in interpolation problems (that is, prediction within the training data range) than when they are used to extrapolate beyond the training data. Production data from geothermal reservoirs tend to exhibit short-term variabilities as well as long-term trends, such as monotonically declining production temperatures. Capturing both short-term features and long-term trends with ML-based models is not trivial. We evaluate the use of recurrent neural networks (RNN) for the prediction of energy production from geothermal reservoirs. RNN is a class of ML architectures that are used to represent and predict sequential/dynamic data. Thus, it can be challenging to apply RNN to problems where long-term trends must be captured and extrapolation beyond the training data range is needed. We introduce the multiscale RNN architecture to extend the application of RNN to detect and predict both short-term variabilities and long-term trends in geothermal data. The developed architecture consists of a long-term component to only capture low-frequency data patterns, and a short-term component to detect features with higher frequency and more nonlinearity. The final prediction is obtained by combining the long-term and short-term predictions. Both synthetic and field data are used to evaluate the presented multiscale RNN model. The prediction performance of the multiscale RNN is compared against those obtained from the regular RNN and the autoregressive (AR) model. The results suggest that the multiscale architecture improves the long-term prediction performance of the regular RNN and enhances its robustness against noise.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Rooftop Solar Photovoltaic Technical Potential in the United States. A Detailed Assessment

How much energy could be generated if PV modules were installed on all of the suitable roof area in the nation? To answer this question, we first use GIS methods to process a lidar dataset and determine the amount of roof area that is suitable for PV deployment in 128 cities nationwide, containing 23% of U.S. buildings, and provide PV-generation results for a subset of those cities. We then extend the insights from that analysis to the entire continental United States. We develop two statistical models--one for small buildings and one for medium and large buildings--and populate them with geographic variables that correlate with rooftop's suitability for PV. We simulate the productivity of PV installed on the suitable roof area, and present the technical potential of PV on both small buildings and medium/large buildings for every state in the continental US. Within the 128 cities covered by lidar data, 83% of small buildings have a location suitable for a PV installation, but only 26% of the total rooftop area of small buildings is suitable for development. The sheer number of buildings in this class, however, gives small buildings the greatest technical potential. Small building rooftops could accommodate 731 GW of PV capacity and generate 926 TWh/year of PV energy, approximately 65% of rooftop PV's total technical potential. We conclude by summing the PV-generation results for all building sizes and therefore answering our original question, estimating that the total national technical potential of rooftop PV is 1,118 GW of installed capacity and 1,432 TWh of annual energy generation. This equates to 39% of total national electric-sector sales.

14 SOLAR ENERGY↗
DOE OSTI2016

Rooftop Solar Photovoltaic Technical Potential in the United States

How much energy could we generate if PV modules were installed on all of the suitable roof area in the nation? To answer this question, we first use GIS methods to process a lidar dataset and determine the amount of roof area that is suitable for PV deployment in 128 cities nationwide, containing 23% of U.S. buildings, and provide PV-generation results for a subset of those cities. We then extend the insights from that analysis to the entire continental United States. We develop two statistical models -- one for small buildings and one for medium and large buildings -- and populate them with geographic variables that correlate with rooftop's suitability for PV. We simulate the productivity of PV installed on the suitable roof area, and present the technical potential of PV on both small buildings and medium/large buildings for every state in the continental US. Within the 128 cities covered by lidar data, 83% of small buildings have a location suitable for a PV installation, but only 26% of the total rooftop area of small buildings is suitable for development. The sheer number of buildings in this class, however, gives small buildings the greatest technical potential. Small building rooftops could accommodate 731 GW of PV capacity and generate 926 TWh/year of PV energy, approximately 65% of rooftop PV's total technical potential. We conclude by summing the PV-generation results for all building sizes and therefore answering our original question, estimating that the total national technical potential of rooftop PV is 1,118 GW of installed capacity and 1,432 TWh of annual energy generation. This equates to 39% of total national electric-sector sales.

14 SOLAR ENERGY↗
DOE OSTI2023

The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands

There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5% and 0.5% for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4% and 7.0% for the detailed medium office building model and high-rise building model, respectively. Here this study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Building confidence in models for complex barrier systems for radionuclides

The modeling and simulation of the Cement-clay Interaction-Diffusion field (CI-D) experiment at the Mont Terri site in Switzerland presented here demonstrates that it is possible to capture the multiscale physical and chemical features of natural and engineered barrier systems for radionuclides. The simulations are successfully carried out with the newly developed CrunchODiTi high-performance computing software that accounts for multiple continua, including a continuum representing the electrical double layer (EDL) developed along negatively charged clay particles in clay rock. The simulation also accounts for both the complex three-dimensional (3D) geometry, expected as the norm in a geological waste repository, and the anisotropy of the geological formation. In addition, the high resolution of the model makes it possible to include "skin effects" developed at the interface between highly reactive materials, in this case between the high pH cement and the circumneutral but electrostatic Opalinus Clay. The successful history matching with the field experiment demonstrates that the distinct geochemical and physical properties of the cement and the Opalinus Clay in the CI-D experiment can be accounted for. Such analyses are essential for developing a defensible safety case for the underground storage of radioactive waste.

Sarsenbayev, Dauren↗
DOE OSTI2025

A Versatile Simulated Data Transport Layer for in Situ Workflows Performance Evaluation

In situ processing does not only allow scientific applications to face the explosion in data volume and velocity but also to address the time constraints of many simulation-analysis workflows by providing scientists with early insights about their applications at runtime. Multiple frameworks implement the concept of a data transport layer (DTL) to enable such in situ workflows. These tools are very versatile, directly or indirectly access the data generated on the same node, another node of the same compute cluster, or a completely distinct node, and allow data publishers and subscribers to run on the same computing resources or not. This versatility puts on researchers the onus of taking key decisions related to resource allocation and how to transport data to ensure the most efficient execution of their in situ workflows. However, domain scientists and workflow practitioners lack the appropriate tools to assess the respective performance of particular design and deployment options. In this paper we introduce a versatile simulated DTL designed to provide researchers with insights on the respective performance of different execution scenarios of in situ workflows. This open-source, standalone library builds on the SimGrid toolkit and can be linked to any SimGrid-based simulator. It facilitates the evaluation of the performance behavior, at scale, of different data transport configurations and the study of the effects of resource allocation strategies. We demonstrate the scalability, versatility, and accuracy of this simulated DTL by reproducing the execution of two synthetic benchmarks and of a real-world in situ workflow composed of an MPI application and a parallel data analysis. Results of simulations run on a single core show that the proposed library can simulate the interactions of tens of thousands of simulated processes deployed on two interconnected commodity clusters in a few seconds, and the execution by a thousand simulated processes of an in situ workflow in less than three minutes.

Suter, Fred [ORNL] (ORCID:0000000319021955)↗
DOE OSTI2020

Parallel-in-Time Simulation of Lindblad's Equation

Constructing fast quantum logic gates is critical to building a scalable quantum computer. We consider a qudit, a quantum version of a bit that can take an arbitrary number of states, coupled with a cavity. In this project, we wish to force the qudit to reach the 0-state, for any possible initial state. The coupled system changes in time according to Lindblad’s equation, an ordinary differential equation on the density matrix of the quantum system. Lindblad’s equation contains some parameters that we can control, so-called control functions. We seek control functions which force the qudit to the 0-state within 2 microseconds, which is much faster than what is currently done in practice. The search method is gradient descent, a numerical optimization method that uses gradient information to iteratively improve the control parameters. My contribution to this project is an attempt to speed up the computation of the gradient. It currently takes about 40 seconds to compute the gradient which involves solving a set of ODEs sequentially. Current supercomputers have thousands of cores, but sequential computations can only make use of 1 core at a time. We wish to divide up the work better, so that we can use many more cores at once. To this end, we have implemented the Multigrid Reduction in Time (MGRIT) algorithm. We perform a systematic parameter search on how to best apply this algorithm. Results indicate a 25 percent speed up for solving Lindblad’s equation and determining how close the final state is the 0-state.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Simulations of Resonant Intraband and Interband Tunneling Spin Filters

This viewgraph presentation reviews resonant intraband and interband tunneling spin filters It explores the possibility of building a zero-magnetic-field spin polarizer using nonmagnetic III-V semiconductor heterostructures. It reviews the extensive simulations of quantum transport in asymmetric InAs/GaSb/AlSb resonant tunneling structures with Rashba spin splitting and proposes a. new device concept: side-gated asymmetric Resonant Interband Tunneling Diode (a-RITD).

resonant tunneling↗
DOE OSTI2023

Data-Driven Approach to Transactive Energy Systems with Commercial Buildings

A microgrid with solar, storage, and responsive load resources has been implemented and tested on an urban academic campus. Through modeling and simulation, a consensus transactive energy mechanism has been implemented, with each resource participating as a virtual battery. Most owners of large buildings don't have the information and expertise to develop and validate suitable models of their buildings using available tools. To mitigate this adoption barrier, a data-driven building model has been implemented and validated. It uses 5-minute weather data, 3-second revenue meter data, energy audit information, and a load reduction test conducted by the building owner.

Buildings, data-driven modeling, deep learning, en↗
DOE OSTI2020

MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery

Membrane-based dehumidification is currently being considered as a promising solution for the building application due to its low cost and very limited energy consumption. Developing a simple and efficient open-source code simulation tool is important for boosting the optimization and evaluation of such device in HVAC community. This paper reports a first-order physics based model which accounts for the fundamental heat and mass transfer of humid-air vapor at feed side to flow stream at permeate side. The current model comprises two membrane mass transfer submodels (i.e. microstructure model and performance map model); and it adopts a segment-by-segment methodology for discretizing heat and mass transfer governing equations. The model is capable of simulating both dehumidifiers and energy recovery ventilators with parallel-flow cross-flow, and counter-flow configurations. The model was validated with the measurements at appropriate device. The practices in dehumidification and energy recovery exchangers are also discussed. The model and open-source codes are expected to become a solid fundament for developing a more comprehensive and accurate membrane-based dehumidification in the future.

Gao, Zhiming↗
DOE OSTI2014

Coupling strength in Coulomb and Yukawa one-component plasmas

In a non-ideal classical Coulomb one-component plasma (OCP), all thermodynamic properties are known to depend only on a single parameter—the coupling parameter Γ. In contrast, if the pair interaction is screened by background charges (Yukawa OCP) the thermodynamic state depends, in addition, on the range of the interaction via the screening parameter κ. How to determine in this case an effective coupling parameter has been a matter of intensive debate. Here we propose a consistent approach for defining and measuring the coupling strength in Coulomb and Yukawa OCPs based on a fundamental structural quantity, the radial pair distribution function (RPDF). The RPDF is often accessible in experiments by direct observation or indirectly through the static structure factor. Alternatively, it is directly computed in theoretical models or simulations. Our approach is based on the observation that the build-up of correlation from a weakly coupled system proceeds in two steps: First, a monotonically increasing volume around each particle becomes devoid of other particles (correlation hole), and second (upon further increase of the coupling), a shell structure emerges around each particle giving rise to growing peaks of the RPDF. Using molecular dynamics simulation, we present a systematic study for the dependence of these features of the RPDF on Γ and κ and derive a simple expression for the effective coupling parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Optimal Energy Dispatch Controller for Fuel Cell-Integrated Multi-Zone Building

Stationary fuel cells provide potential opportunities for energy savings when integrated with buildings. Through smart dispatch of both electrical power and heat generated by the fuel cells and managing the building loads, the buildings can achieve more efficient operation. In this paper, we develop an optimal energy dispatch controller to operate a fuel cell-integrated building. The controller leverages the inherent thermal storage and the dispatchable fuel cell to reduce its operating cost and to allow the building to participate in grid services. The proposed controller is implemented on two types of commercial buildings, a large office building and a large hotel, and the effectiveness of the controller is demonstrated through simulations. The results also indicate that the potential saving varies significantly with different system parameters, including season, fuel prices, and equipment sizing, which provide helpful insights for building operators and other stake holders.

39 EE - Hydrogen and Fuel Cell Technologies (EE-3F↗
DOE OSTI2024

The hygrothermal performance of continuous and cavity wood fiber insulation

Wood fiber insulation is an emerging material known for its effective thermal performance and moisture management properties, making it a compelling alternative to conventional insulation. Its vapor permeability and ability to regulate indoor humidity contribute to improved building durability and comfort, particularly in varying climate conditions. The goal of this project is to characterize the hygrothermal performance of a new wood fiber insulation product line in U.S. climate zones and to facilitate the design and construction of the product in residential and light commercial building envelopes. This study investigates the thermal and hygrothermal performance of wood fiber insulation, both as continuous and cavity insulation. The research employs an exhaustive simulation task and an environmental chamber test of a wood fiber insulation. Over 400 simulations were conducted to study the hygrothermal characteristics of bio-based wood fiber insulation in various building envelope configurations across four climate zones. Environmental chamber tests were conducted under controlled winter conditions representative of Climate Zone 5A (Chicago, IL) to complement the simulation results. The chamber tests focused on the hygrothermal performance of the wood fiber insulation and the sheathing board to assess the insulation's ability to manage moisture in a cold climate. Simulation and environmental chamber test results were analyzed to evaluate the insulation's consistency and efficacy across diverse climatic zones. Results show that with a proper moisture control strategy, both cavity and continuous wood fiber insulation can work properly in both new and retrofit constructions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

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