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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data-driven modeling of dynamic occupant thermostat override behavior for demand response applications

Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.

Sharma, Kunind [Northeastern University] (ORCID:00↗
NASA NTRS1976

USB environment measurements based on full-scale static engine ground tests

Flow turning parameters, static pressures, surface temperatures, surface fluctuating pressures and acceleration levels were measured in the environment of a full-scale upper surface blowing (USB) propulsive-lift test configuration. The test components included a flightworthy CF6-50D engine, nacelle and USB flap assembly utilized in conjunction with ground verification testing of the USAF YC-14 Advanced Medium STOL Transport propulsion system. Results, based on a preliminary analysis of the data, generally show reasonable agreement with predicted levels based on model data. However, additional detailed analysis is required to confirm the preliminary evaluation, to help delineate certain discrepancies with model data and to establish a basis for future flight test comparisons.

Sussman, M. B.↗
NASA NTRS1976

USB environment measurements based on full-scale static engine ground tests

Flow turning parameters, static pressures, surface temperatures, surface fluctuating pressures and acceleration levels were measured in the environment of a full-scale upper surface blowing (USB) propulsive lift test configuration. The test components included a flightworthy CF6-50D engine, nacelle, and USB flap assembly utilized in conjunction with ground verification testing of the USAF YC-14 Advanced Medium STOL Transport propulsion system. Results, based on a preliminary analysis of the data, generally show reasonable agreement with predicted levels based on model data. However, additional detailed analysis is required to confirm the preliminary evaluation, to help delineate certain discrepancies with model data, and to establish a basis for future flight test comparisons.

Sussman, M. B.↗
NASA NTRS2018

A Standard Reference Model for Data Archives

An implementable Data Archive Architecture is being developed for trusted digital repositories based on the Reference Model for an Open Archival Information System (OAIS) – ISO 14721. A set of interoperable protocols and interface specifications are planned that will offer capabilities for accessing, merging, and re-using data, both within and across the operational boundaries of trustworthy digital repositories. The model will also provide support for the fundamental scientific need to verify the reproducibility of results. This standards development task is being performed by the Data Archive Interoperability (DAI) working group within the Consultative Committee for Space Data Systems (CCSDS). The architecture integrates concepts from the OAIS Reference Model, the ISO/IEC 11179 Metadata Registry (MDR) standard, the CCSDS Reference Architecture for Space Information Management (RASIM), the proposed draft recommended practice document, Information Preparation to Enable Long Term Use (IPELTU), and three decades of digital repository development for science research.

Ambacher, Bruce↗
NASA NTRS1979

Development of Integrated Programs for Aerospace-vehicle design (IPAD): Integrated information processing requirements

The engineering-specified requirements for integrated information processing by means of the Integrated Programs for Aerospace-Vehicle Design (IPAD) system are presented. A data model is described and is based on the design process of a typical aerospace vehicle. General data management requirements are specified for data storage, retrieval, generation, communication, and maintenance. Information management requirements are specified for a two-component data model. In the general portion, data sets are managed as entities, and in the specific portion, data elements and the relationships between elements are managed by the system, allowing user access to individual elements for the purpose of query. Computer program management requirements are specified for support of a computer program library, control of computer programs, and installation of computer programs into IPAD.

Southall, J. W.↗
NASA NTRS1990

Modeling strength data for CREW CHIEF

The Air Force has developed CREW CHIEF, a computer-aided design (CAD) tool for simulating and evaluating aircraft maintenance to determine if the required activities are feasible. CREW CHIEF gives the designer the ability to simulate maintenance activities with respect to reach, accessibility, strength, hand tool operation, and materials handling. While developing the CREW CHIEF, extensive research was performed to describe workers strength capabilities for using hand tools and manual handling of objects. More than 100,000 strength measures were collected and modeled for CREW CHIEF. These measures involved both male and female subjects in the 12 maintenance postures included in CREW CHIEF. The data collection and modeling effort are described.

Mcdaniel, Joe W.↗
NASA NTRS2018

Seven Keys for Practical Understanding and Use of CGNS

We present key features of the CGNS standard, focusing on its two main elements, the data model (CGNS/SIDS) and its implementations (CGNS/HDF5 and CGNS/Python). The data model is detailed to emphasize how the topological user oriented information, such as families, are separated from the actual meshing that could be split or modified during the CFD work flow, and how this topological information is traced during the meshing process. We also explain why the same information can be described in multiple ways and how to handle such alternatives in an application. Two implementations, using HDF5 and Python, are illustrated in several use examples, both for archival and interoperability purposes. The CPEX extension formalized process is explained to show how to add new features to the standard in a consensual way; we present some of the next extensions to come. Finally we conclude by showing how powerful a consensual public approach like CGNS can be, as opposed to a stand-alone private one. All throughout the paper, we demonstrate how the use of CGNS could be of great benefit for both the meshing and CFD solver communities.

Poinot, Marc↗
NASA NTRS2014

Range-Specific High-Resolution Mesoscale Model Setup: Data Assimilation

Mesoscale weather conditions can have an adverse effect on space launch, landing, and ground processing at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. Some of these other boundaries include the Indian River breeze front, Banana River breeze front, outflows from previous convection, horizontal convective rolls, convergence lines from other inland bodies of water such as Lake Okeechobee, the trailing convergence line from convergence of sea breeze fronts due to the shape of Cape Canaveral, frictional convergence lines from the islands in the Bahamas, convergence lines from soil moisture differences, convergence lines from cloud shading, and others. All these subtle weak boundary interactions often make forecasting of operationally important weather very difficult at KSC/CCAFS during the convective season (May-Oct). These convective processes often build quickly, last a short time (60 minutes or less), and occur over small distances, all of which also poses a significant challenge to the local forecasters who are responsible for issuing weather advisories, watches, and warnings. Surface winds during the transition seasons of spring and fall pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to aid in their decision making. Both the ER and WFF would benefit greatly from high-resolution mesoscale model output to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned model at a high resolution is needed to provide improved capability. This task is a multi-year effort in which the Applied Meteorology Unit (AMU) will tune the Weather Research and Forecasting (WRF) model individually for each range. The goal of the first year, the results of which are in this report, was to tune the WRF model based on the best model resolution and run time while using reasonable computing capabilities. To accomplish this, the ER and WFF supported the tasking of the AMU to perform a number of sensitivity tests in order to determine the best model configuration for operational use at each of the ranges to best predict winds, precipitation, and temperature (Watson 2013). This task is a continuation of that work and will provide a recommended local data assimilation (DA) and numerical forecast model design optimized for the ER and WFF to support space launch activities. The model will be optimized for local weather challenges at both ranges.

Global and national scale models↗
NASA NTRSDate not supplied

Learjet Test Update

An update on the Learjet acoustic flight test was presented. The intent of the effort was to acquire flight data for the development of flight corrections to scale-model data. The flights were completed on September 8, 2022. Weather measurements were acquired with a combination of an instrumented drone and a ground based LiDAR system. Acquisition of comparative scale-model data will be completed on October 7, 2022.

jet noise↗
NASA NTRS1975

Hypersonic research engine project. Phase 2: Aerothermodynamic Integration Model (AIM) data reduction computer program, data item no. 54.16

The data reduction program used to analyze the performance of the Aerothermodynamic Integration Model is described. Routines to acquire, calibrate, and interpolate the test data, to calculate the axial components of the pressure area integrals and the skin function coefficients, and to report the raw data in engineering units are included along with routines to calculate flow conditions in the wind tunnel, inlet, combustor, and nozzle, and the overall engine performance. Various subroutines were modified and used to obtain species concentrations and transport properties in chemical equilibrium at each of the internal and external engine stations. It is recommended that future test plans include the configuration, calibration, and channel assignment data on a magnetic tape generated at the test site immediately before or after a test, and that the data reduction program be designed to operate in a batch environment.

Gaede, A. E.↗
NASA NTRSDate not supplied

Jet Noise Flyover and Scale Model Tests

Renewed interest in commercial supersonic flight has rekindled the need for accurate jet-noise predictions as this source is believed to dominate at aircraft takeoff conditions. The current study compares scale-model data acquired in the NASA Aero-Acoustic Propulsion Laboratory with data obtained using a well-instrumented Learjet 25 in a flyover test completed in September 2022. The flight test included 73 flyovers with engine conditions ranging from 1.5 to 2.0 engine pressure ratios and flight Mach numbers between 0.24 and 0.27. Acoustic data were acquired with an 800-ft linear ground plate microphone array. Wind speed data were acquired up to 1000-ft altitude with a ground-based LiDAR system. Layered ambient temperature, pressure, and humidity were acquired with a weather drone. A 6% increase in the physical scale factor for the scale-model data was found to reasonably align the peak frequencies of the scale-model and flight data and resulted in peak levels for the scale model being roughly 0.7 dB above those for the flight data at NPR = 1.56 and roughly 1 dB below those for the flight data at NPR = 1.91 in the peak jet-noise direction. Comparisons with the SAE ARP876 model were poor especially at emission angles greater than, or equal to, 110° and at high frequencies.

jet noise, supersonic transport↗
NASA NTRSDate not supplied

Jet Noise Flyover and Scale Model Tests

Renewed interest in commercial supersonic flight has rekindled the need for accurate jet-noise predictions as this source is believed to dominate at aircraft takeoff conditions. The current study compares scale-model data acquired in the NASA Aero-Acoustic Propulsion Laboratory with data obtained using a well-instrumented Learjet 25D in a flyover test completed in September 2022. The flight test included 73 flyovers with engine conditions ranging from 1.5 to 2.0 engine pressure ratios and flight Mach numbers between 0.24 and 0.27. Acoustic data were acquired with an 800-ft linear ground plate microphone array. Wind speed data were acquired up to 1000-sft altitude with a ground-based LiDAR system. Layered ambient temperature, pressure, and humidity were acquired with a weather drone. A 6% increase in the physical scale factor for the scale-model data was found to reasonably align the peak frequencies of the scale-model and flight data and resulted in peak levels for the scale model being roughly 0.7 dB above those for the flight data at NPR = 1.56 and roughly 1 dB below those for the flight data at NPR = 1.91 in the peak jet-noise direction. Comparisons with the SAE ARP876 model were poor especially at emission angles greater than, or equal to, 110° and at high frequencies.

Acoustics, jet noise, supersonic transport↗
NASA NTRSDate not supplied

Jet Noise Flyover and Scale Model Tests

Renewed interest in commercial supersonic flight has rekindled the need for accurate jet-noise predictions as this source is believed to dominate at aircraft takeoff conditions. The current study compares scale-model data acquired in the NASA Aero-Acoustic Propulsion Laboratory with data obtained using a well-instrumented Learjet 25 in a flyover test completed in September 2022. The flight test included 73 flyovers with engine conditions ranging from 1.5 to 2.0 engine pressure ratios and flight Mach numbers between 0.24 and 0.27. Acoustic data were acquired with an 800-ft linear ground plate microphone array. Wind speed data were acquired up to 1000-ft altitude with a ground-based LiDAR system. Layered ambient temperature, pressure, and humidity were acquired with a weather drone. A 6% increase in the physical scale factor for the scale-model data was found to reasonably align the peak frequencies of the scale-model and flight data and resulted in peak levels for the scale model being roughly 0.7 dB above those for the flight data at NPR = 1.56 and roughly 1 dB below those for the flight data at NPR = 1.91 in the peak jet-noise direction. Comparisons with the SAE ARP876 model were poor especially at emission angles greater than, or equal to, 110° and at high frequencies.

Acoustics, jet noise, supersonic transport↗
DOE OSTI2024

Large-Scale Visualization of 3D Unstructured Groundwater Model Using Cave Automated Virtual Environment

The immersive three-dimensional (3D) virtual reality (VR) visualization of groundwater models allows us to deepen our understanding of aquifer systems and provide better solutions to present groundwater-related problems, such as groundwater recharge, water quality, and sustainability. Visualization assists in accurately developing groundwater models and revealing important subsurface features, including faulting, folding, and unconformity. However, assessing model accuracy poses challenges due to the complexity of geology and groundwater systems. This research demonstrates a workflow to visualize and analyze raw 3D unstructured groundwater model data using an immersive Cave Automated Virtual Environment (CAVE). To visualize the unstructured groundwater model data, the raw dataset is converted into interactive CAVE-compatible formats utilizing a set of tools: ParaView, Blender, and Unity. This enables researchers to immerse themselves in the data, identifying influential patterns and relationships. e resulting insights can inform the development of sophisticated machine-learning models for groundwater level prediction. The CAVE’s immersive capabilities allow intuitive exploration from various perspectives, providing a more holistic understanding of the factors affecting groundwater levels. These insights are crucial to improve predictive models. The CAVE results also facilitate collaborative analysis and have potential applications in training and education. is research demonstrates the value of immersive VR tools such as the CAVE for unraveling intricacies within high-dimensional scientific data to drive real-world forecasting and modeling applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

ANOPP Landing Gear Noise Prediction Comparisons to Model-scale Data

The NASA Aircraft NOise Prediction Program (ANOPP) includes two methods for computing the noise from landing gear: the "Fink" method and the "Guo" method. Both methods have been predominately validated and used to predict full-scale landing gear noise. The two methods are compared, and their ability to predict the noise for model-scale landing gear is investigated. Predictions are made using both the Fink and Guo methods and compared to measured acoustic data obtained for a high-fidelity, 6.3%-scale, Boeing 777 main landing gear. A process is developed by which full-scale predictions can be scaled to compare with model-scale data. The measurements were obtained in the NASA Langley Quiet Flow Facility for a range of Mach numbers at a large number of observer polar (flyover) and azimuthal (sideline) observer angles. Spectra and contours of the measured sound pressure levels as a function of polar and azimuthal angle characterize the directivity of landing gear noise. Comparisons of predicted noise spectra and contours from each ANOPP method are made. Both methods predict comparable amplitudes and trends for the flyover locations, but deviate at the sideline locations. Neither method fully captures the measured noise directivity. The availability of these measured data provides the opportunity to further understand and advance noise prediction capabilities, particularly for noise directivity.

Burley, Casey L.↗
NASA NTRS1981

A comparison of the radio data and model calculations of Jupiter's synchrotron radiation. I - The high energy electron distribution in Jupiter's inner magnetosphere. II - East-west asymmetry in the radiation belts as a function of Jovian longitude

A comparison has been made between detailed model calculations of Jupiter's synchrotron radiation and the radio data at wavelengths of 6, 21, and 50 cm. The calculations were performed for a Jovian longitude of 200 deg and were based on the multipole field configurations as derived from the Pioneer data. The electron distribution in the inner magnetosphere was derived as a function of energy, pitch angle, and spatial coordinates. In addition, the hot region or east-west asymmetry in the radiation belts is investigated. It is suggested that this asymmetry is due to the combined effect of an overabundance of electrons at jovicentric longitudes of 240-360 deg and the existence of a dusk-to-dawn directed electric field over the inner magnetosphere generated by the wind system in the upper atmosphere.

De Pater, I.↗