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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Integration of Information Management System, Workflow and Computational Tools Enabling Multiscale Modeling Within an ICME Paradigm

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to develop a set of Python functions that exchange information between NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset and its Integrated Computational Materials Engineering (ICME), Granta MI® database schema is presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.

multiscale modeling; Micromechanics; Computational↗
NASA NTRSDate not supplied

A Gaussian Process Enhancement to Linear Parameter Varying Models

Simulation and analysis for modern engineering systems now routinely requires the merging of multiple disciplines, physical-domains, time-scales, and data sets — all at ever increasing levels. These capabilities are especially needed in the domain of Advanced Air Mobility, where rapidly emerging vehicle designs are significantly more complex, while having to be both cost-effective and safe. To meet these engineering challenges, machine learning methods are an attractive option for merging models and data across multiple areas while providing uncertainty quantification and maintaining computational efficiency. This paper examines the use of Gaussian process machine learning to generalize and enhance the commonly used class of quasi-Linear Parameter Varying models for fast full-envelope simulation while also supporting control system design and analysis with model uncertainty. Gaussian process machine learning is selected because it: can fuse multiple data sets, enables an easy trade-off between data fitting and smoothing, provides model uncertainty quantification, scales well with increasing complexity, and does not generally require starting from a large training data set. To demonstrate the benefits of the approach, a robust stability analysis with Gaussian process uncertainty is shown for a NASA reference design of an electric quad-rotor air-taxi concept vehicle with motor parameter uncertainty.

Gaussian Process↗
NASA NTRSDate not supplied

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗
DOE OSTI2023

Extending the Air and Moisture Leakage Calculator to add Residential Buildings and Additional Commercial Buildings

The DOE Windows and Building Envelope Research and Development Roadmap for Emerging Technologies shows that in 2010, infiltration was responsible for 4 quads of space conditioning primary energy use in the residential and commercial sectors. The relative contribution of air leakage in building heating and cooling load is increasing with improvement in the thermal resistance of building envelopes. Advanced air barrier technologies and construction practices have been developed to reduce air leakage in buildings. However, limited information on the impact of air barrier technologies on energy consumption and the durability of buildings has hindered their adoption. In the past Oak Ridge National Laboratory (ORNL), the National Institute of Standards and Technology (NIST), Air Barrier Association of America (ABBA), and U.S.-China Clean Energy Research Center for Building Energy Efficiency (CERC-BEE) collaborated to develop an online calculator that estimates the potential energy and cost savings in major U.S., Canadian and Chinese cities from improvement in air tightness in commercial buildings. In 2018–2019, the calculator was expanded to add moisture transfer calculations given that air leakage through the building envelope can have a significant impact on moisture transfer and associated impacts. In this study, the calculator is expanded further by adding data for two additional commercial buildings (strip mall and primary school) and a residential building. The team investigated the impact of airtightness on energy consumption and moisture transfer of the added buildings. The study includes the analysis of air tightness in 52 major cities in the U.S. and 5 cities in Canada.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Smart Ventilation Controls Boost Energy Efficiency and Indoor Air Quality

The average American household spends more than $2,200 a year on energy, and heating, ventilating, and air conditioning (HVAC) costs comprise nearly half of the bill. This is one reason why home builders focus on tightening building envelopes to save energy. Yet, limiting the potential for air exchange can negatively impact indoor air quality (IAQ). When outdoor conditions are most extreme during occupied periods, there may be comfort implications from continuing high levels of ventilation during associated weather events. This is true even with heat recovery. To mitigate risks, the Florida Solar Energy Center developed and tested approaches for “smart” ventilation system controls that enable more reliable design, installation, and operation to achieve desired IAQ while also minimizing energy and comfort impacts.

Building America↗
DOE OSTI2020

Smart Ventilation Controls Boost Energy Efficiency and Indoor Air Quality

The average American household spends more than $2,200 a year on energy, and heating, ventilating, and air conditioning (HVAC) costs comprise nearly half of the bill. This is one reason why home builders focus on tightening building envelopes to save energy. Yet, limiting the potential for air exchange can negatively impact indoor air quality (IAQ). When outdoor conditions are most extreme during occupied periods, there may be comfort implications from continuing high levels of ventilation during associated weather events. This is true even with heat recovery. To mitigate risks, the Florida Solar Energy Center developed and tested approaches for “smart” ventilation system controls that enable more reliable design, installation, and operation to achieve desired IAQ while also minimizing energy and comfort impacts.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Nucleosynthetic yields from neutron stars accreting in binary common envelopes

Massive-star binaries can undergo a phase where one of the two stars expands during its advanced evolutionary stage as a giant and envelops its companion, ejecting the hydrogen envelope and tightening its orbit. Such a common envelope phase is required to tighten the binary orbit in the formation of many of the observed X-ray binaries and merging compact binary systems. In the formation scenario for neutron star binaries, the system might pass through a phase where a neutron star spirals into the envelope of its giant star companion. These phases lead to mass accretion on to the neutron star. Accretion on to these common-envelope-phase neutron stars can eject matter that has undergone burning near to the neutron star surface. This paper presents nucleosynthetic yields of this ejected matter, using population synthesis models to study the importance of these nucleosynthetic yields in a galactic chemical evolution context. Depending on the extreme conditions in temperature and density found in the accreted material, both proton-rich and neutron-rich nucleosynthesis can be obtained, with efficient production of neutron-rich isotopes of low Z material at the most extreme conditions, and proton-rich isotopes, again at low Z, in lower density models. Final yields are found to be extremely sensitive to the physical modelling of the accretion phase. Finally, we show that neutron stars accreting in binary common envelopes might be a new relevant site for galactic chemical evolution, and therefore more comprehensive studies are needed to better constrain nucleosynthesis in these objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

City-level impacts of building tune-ups: Findings from Seattle's building tune-ups program

Many U.S. cities are implementing policies to reduce greenhouse gas (GHG) emissions of their buildings. These range from building energy benchmarking and disclosure to building performance standards (BPS) that require buildings to meet specific targets of energy use or emissions. The City of Seattle adopted a climate action plan in 2013 that set a goal of zero net GHG emissions in the road transportation, buildings, and waste sectors by 2050, with a number of near and long term actions. Seattle implemented mandatory building tune-ups in 2016, applying to commercial buildings larger than 50,000 sqft. Building tune-ups1 involve assessment and implementation of operational and maintenance (O + M) improvements to achieve energy and water efficiency, such as changes to thermostat set points or adjusting lighting or irrigation schedules. Seattle's tune-ups program covered 27 such improvements in HVAC, lighting, domestic hot water, and envelope systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
NASA NTRS1984

Flight testing the digital electronic engine control in the F-15 airplane

The digital electronic engine control (DEEC) is a full-authority digital engine control developed for the F100-PW-100 turbofan engine which was flight tested on an F-15 aircraft. The DEEC hardware and software throughout the F-15 flight envelope was evaluated. Real-time data reduction and data display systems were implemented. New test techniques and stronger coordination between the propulsion test engineer and pilot were developed which produced efficient use of test time, reduced pilot work load, and greatly improved quality data. The engine pressure ratio (EPR) control mode is demonstrated. It is found that the nonaugmented throttle transients and engine performance are satisfactory.

Myers, L. P.↗
DOE OSTI2025

Optimizing Control for Efficient Load Shifting with Thermal Energy Storage in Existing HVAC Systems

This project developed the integration of a direct-contact heat exchanger (DCHX) based thermal energy storage (TES) system with a chiller–air handling unit (AHU) plant to evaluate its potential for reducing building energy costs. Detailed physical models of the TES unit, building envelope, and HVAC components were developed alongside simplified control-oriented models to support both high-fidelity simulation and real-time optimization. Two control strategies were implemented and compared: a rule-based control (RBC) aligned with utility time-of-use (ToU) rates, and a model predictive control (MPC) framework leveraging forecasts of building load, weather, and internal gains.Simulation results show that the RBC strategy reduced daily electricity costs by around 30% by shifting cooling production from on-peak to off-peak hours. In contrast, the MPC strategy achieved significantly greater performance, reducing daily operating costs by up to 44% and peak-hour costs by more than 60%. Both strategies maintained indoor thermal comfort within acceptable limits, with MPC further improving load distribution and reducing equipment cycling.The outcomes confirm that TES integration, particularly when coordinated with advanced predictive control, can provide substantial cost savings and on-peak demand reduction. . These findings directly support the U.S. Department of Energy’s goals for grid-interactive efficient buildings and demonstrate the potential of TES-enabled HVAC systems for scalable deployment across the commercial building.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Optimizing Control for Efficient Load Shifting with Thermal Energy Storage in Existing HVAC Systems

This project developed the integration of a direct-contact heat exchanger (DCHX) based thermal energy storage (TES) system with a chiller–air handling unit (AHU) plant to evaluate its potential for reducing building energy costs. Detailed physical models of the TES unit, building envelope, and HVAC components were developed alongside simplified control-oriented models to support both high-fidelity simulation and real-time optimization. Two control strategies were implemented and compared: a rule-based control (RBC) aligned with utility time-of-use (ToU) rates, and a model predictive control (MPC) framework leveraging forecasts of building load, weather, and internal gains. Simulation results show that the RBC strategy reduced daily electricity costs by around 30% by shifting cooling production from on-peak to off-peak hours. In contrast, the MPC strategy achieved significantly greater performance, reducing daily operating costs by up to 44% and peak-hour costs by more than 60%. Both strategies maintained indoor thermal comfort within acceptable limits, with MPC further improving load distribution and reducing equipment cycling. The outcomes confirm that TES integration, particularly when coordinated with advanced predictive control, can provide substantial cost savings and on-peak demand reduction. . These findings directly support the U.S. Department of Energy’s goals for grid-interactive efficient buildings and demonstrate the potential of TES-enabled HVAC systems for scalable deployment across the commercial building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Texas Residential Energy Code Field Study: Baseline Report

A research project in the state of Texas identified opportunities to reduce homeowner utility bills in residential single-family new construction by increasing compliance with the state energy code. The study was initiated in October 2014; data collection began in March 2015, and continued through October 2015. During this period, research teams visited 133 homes in 30 counties in and around Houston during various stages of construction, resulting in a substantial data set based on observations made directly in the field. Stakeholders in the state agreed that these 30 counties represented the levels of energy codes and enforcement seen across the state. Analysis of the data has led to a better understanding of the energy features present in homes, and, when extrapolated across the entire state, indicates over $16 million in potential annual savings to Texas homeowners that could result from increased code compliance. Public and private entities within the state can use this information to justify and catalyze future investments in energy code training and related energy efficiency programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Searching for Rapid Orbital Decay of WASP-18b

The WASP-18 system, with its massive and extremely close-in planet, WASP-18b ( M{sub p} = 10.3 M{sub J}, a = 0.02 au, P = 22.6 hr), is one of the best-known exoplanet laboratories to directly measure Q ′, the modified tidal quality factor and proxy for efficiency of tidal dissipation, of the host star. Previous analysis predicted a rapid orbital decay of the planet toward its host star that should be measurable on the timescale of a few years, if the star is as dissipative as is inferred from the circularization of close-in solar-type binary stars. We have compiled published transit and secondary eclipse timing (as observed by WASP, TRAPPIST, and Spitzer ) with more recent unpublished light curves (as observed by TRAPPIST and Hubble Space Telescope ) with coverage spanning nine years. We find no signature of a rapid decay. We conclude that the absence of rapid orbital decay most likely derives from Q ′ being larger than was inferred from solar-type stars and find that Q ′ ≥ 1 × 10{sup 6}, at 95% confidence; this supports previous work suggesting that F stars, with their convective cores and thin convective envelopes, are significantly less tidally dissipative than solar-type stars, with radiative cores and large convective envelopes.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1979

Multivariable control altitude demonstration on the F100 turbofan engine

The F100 Multivariable control synthesis (MVCS) program, was aimed at demonstrating the benefits of LGR synthesis theory in the design of a multivariable engine control system for operation throughout the flight envelope. The advantages of such procedures include: (1) enhanced performance from cross-coupled controls, (2) maximum use of engine variable geometry, and (3) a systematic design procedure that can be applied efficiently to new engine systems. The control system designed, under the MVCS program, for the Pratt & Whitney F100 turbofan engine is described. Basic components of the control include: (1) a reference value generator for deriving a desired equilibrium state and an approximate control vector, (2) a transition model to produce compatible reference point trajectories during gross transients, (3) gain schedules for producing feedback terms appropriate to the flight condition, and (4) integral switching logic to produce acceptable steady-state performance without engine operating limit exceedance.

Lehtinen, B.↗
NASA NTRS1946

Compressive Strength of 24S-T Aluminum-alloy Flat Panels with Longitudinal Formed Hat-section Stiffeners

Results are presented for a part of a test program on 24S-T aluminum alloy flat compression panels with longitudinal formed hat-section stiffeners. This part of the program is concerned with panels in which the thickness of the stiffener materials is 0.625 times the skin thickness. The results, presented in tabular and graphical form, show the effect of the relative dimensions of the panel on the buckling stress and the average stress at maximum load. Comparative envelope curves are presented for hat-stiffened and Z-stiffened panels having the same ratio of stiffener thickness to sheet thickness. These curves provide some indication of the relative structural efficiencies of the two types of panel.

Schuette, Evan H↗
DOE OSTI2012

Achieving Very High Efficiency and Net Zero Energy in an Existing Home in a Hot-Humid Climate: Long-Term Utility and Monitoring Data (Revised)

This study summarizes the first six months of detailed data collected on a single family home that experienced a series of retrofits targeting reductions in energy use. The project was designed to develop data on how envelope modifications and renewable measures can result in considerable energy reductions and potentially net zero energy for an existing home. Originally published in February2012, this revised version of the report contains further research conducted on the Parker residence. Key updates include one full year of additional data, an analysis of cooling performance of the mini-split heat pump, an evaluation of room-to-room temperature distribution, and an evaluation of plug-in automobile charging performance, electricity consumption, and load shape.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Achieving Very High Efficiency and Net Zero Energy in an Existing Home in a Hot-Humid Climate: Long-Term Utility and Monitoring Data

This study summarizes the first six months of detailed data collected on a single family home that experienced a series of retrofits targeting reductions in energy use. The project was designed to develop data on how envelope modifications and renewable measures can result in considerable energy reductions and potentially net zero energy for an existing home. Originally published in February 2012, this revised version of the report contains further research conducted on the Parker residence. Key updates include one full year of additional data, an analysis of cooling performance of the mini-split heat pump, an evaluation of room-to-room temperature distribution, and an evaluation of plug-in automobile charging performance, electricity consumption, and load shape.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗