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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

2013 Metropolitan Area Planning Agency External Travel Survey

# 2013 Metropolitan Area Planning Agency External Travel Survey The 2013 Metropolitan Area Planning Agency (MAPA) External Travel Survey was conducted to measure and identify travel patterns into, within, and out of the greater Omaha/Council Bluffs metropolitan area in Nebraska. MAPA sponsored the survey in conjunction with the Federal Highway Administration, the Nebraska Department of Roads, and the Iowa Department of Transportation. ## Data Collection Agency MAPA conducted the survey. ## Methodology The purpose of the survey was to collect information and data needed as input for MAPA’s travel-demand model. The survey employed a combination of nine survey methods and data-collection activities, including Bluetooth technology, intercept surveys, postcard handouts, travel-time studies, vehicle classification counts, and a web-based survey. ## Survey Records Survey records include a total of 729 participants. ## Transportation Data This study provides Bluetooth records and supplementary data for 17,434 passenger trips and 3,123 commercial trips, accounting for 714,218 vehicle miles traveled. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2013-2014 Greater Fairbanks, Alaska, Transportation Survey

# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2013 Metropolitan Area Planning Agency External Travel Survey

# 2013 Metropolitan Area Planning Agency External Travel Survey The 2013 Metropolitan Area Planning Agency (MAPA) External Travel Survey was conducted to measure and identify travel patterns into, within, and out of the greater Omaha/Council Bluffs metropolitan area in Nebraska. MAPA sponsored the survey in conjunction with the Federal Highway Administration, the Nebraska Department of Roads, and the Iowa Department of Transportation. ## Data Collection Agency MAPA conducted the survey. ## Methodology The purpose of the survey was to collect information and data needed as input for MAPA’s travel-demand model. The survey employed a combination of nine survey methods and data-collection activities, including Bluetooth technology, intercept surveys, postcard handouts, travel-time studies, vehicle classification counts, and a web-based survey. ## Survey Records Survey records include a total of 729 participants. ## Transportation Data This study provides Bluetooth records and supplementary data for 17,434 passenger trips and 3,123 commercial trips, accounting for 714,218 vehicle miles traveled. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2013-2014 Greater Fairbanks, Alaska, Transportation Survey

# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2013 Metropolitan Area Planning Agency External Travel Survey

# 2013 Metropolitan Area Planning Agency External Travel Survey The 2013 Metropolitan Area Planning Agency (MAPA) External Travel Survey was conducted to measure and identify travel patterns into, within, and out of the greater Omaha/Council Bluffs metropolitan area in Nebraska. MAPA sponsored the survey in conjunction with the Federal Highway Administration, the Nebraska Department of Roads, and the Iowa Department of Transportation. ## Data Collection Agency MAPA conducted the survey. ## Methodology The purpose of the survey was to collect information and data needed as input for MAPA’s travel-demand model. The survey employed a combination of nine survey methods and data-collection activities, including Bluetooth technology, intercept surveys, postcard handouts, travel-time studies, vehicle classification counts, and a web-based survey. ## Survey Records Survey records include a total of 729 participants. ## Transportation Data This study provides Bluetooth records and supplementary data for 17,434 passenger trips and 3,123 commercial trips, accounting for 714,218 vehicle miles traveled. Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2013-2014 Greater Fairbanks, Alaska, Transportation Survey

# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

ambrosia: An R package for calculating and analyzing food demand that is responsive to changing incomes and prices

The ambrosia R package was developed to calculate food demand for staples and non-staple commodities that is responsive to changing levels of incomes and prices. ambrosia implements the framework to quantify food demand as established by Edmonds et al. (Edmonds et al. 2017) and allows the user to explore and estimate different variables related to the food demand system. Currently ambrosia provides 3 main functions: (1) calculation of food demand for any given set of parameters including income levels and prices (2) estimation of parameters within a given a dataset. Note: ambrosia is used to calculate parameters for the food demand model implemented in the Global Change Analysis Model(GCAM) (3) exploration and preparation of raw data before starting a parameter estimation

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Assessment of the Economic Potential of Distributed Wind in Colorado, Minnesota, and New York

This work seeks to identify current and future spatial distributions of economic potential for behind-the-meter distributed wind, serving primarily rural or suburban homes, farms, and manufacturing facilities in Colorado, Minnesota, and New York. These states were identified by technical experts based on their current favorability for distributed wind deployment. We use NREL's Distributed Wind Market Demand Model (dWind) (Lantz et al. 2017; Sigrin et al. 2016) to identify and rank counties in each of the states by their overall and per capita potential. From this baseline assessment, we also explore how and where improvements in cost, performance, and other market sensitivities affect distributed wind potential.

17 WIND ENERGY↗
DOE OSTI2019

Case Study: Integrate Nuclear Water Desalination - Regional Potable Water in Arizona

The present study analyzes the economic viability of an Integrated Energy System (IES) that couples a Reverse Osmosis (RO) water desalination facility with a Nuclear Power Plant (NPP). The case study is conducted in collaboration with Arizona Public Service (APS), the operating owner of the Palo Verde Generating Station (PVGS) NPP. Cooling water for the reactor steam cycle is derived from treated effluent from municipal wastewater treatment plants. APS has established a long-term water resources program to effect a substantial reduction in plant cooling costs through advanced treatment and cooling technologies, and through the use of alternative water sources to replace the increasingly expensive effluent. One possible option is to replace some amount of the annual volume of effluent with brackish groundwater from a local regional aquifer. Although much less expensive than the municipal effluent, the quantity of brackish groundwater that could be used for plant cooling is limited as a result of the salinity and its impact on plant operation. Consequently, supplemental treatment could be required such that a greater amount of brackish groundwater could be used to reduce the demand on effluent. A study was conducted in 2018 by Idaho National Laboratory (INL) to investigate the economics of a PVGS onsite RO desalination plant that would reduce the salinity of a municipal effluent and brackish water blend to an acceptable level. One of the main findings of that study was that the overall economics of water desalination can be greatly improved if, in addition to cooling water for PVGS, potable water could also be produced and sold for profit. In fact, the study concluded that only producing cooling water for PVGS via RO desalination is not economically viable. The present report investigates the economic impact of a large, regional RO desalination plant that could provide potable water for the region, considering the conclusions from the 2018 scoping study. The study looks in particular at the water-market situation for the developing municipalities in the west valley of Phoenix. In addition to providing potable water for the municipalities, the existing infrastructure that conveys effluent to the Palo Verde plant and onsite water treatment facilities could be used to manage the RO concentrate. The processed concentrate could lead to a cost reduction in plant cooling by replacing some amount of effluent. The analysis reported here considers two cases (for various scenarios). First, the Base Case considers that neither the regional nor the onsite RO is built. The 2018 INL study showed that some brackish water can be blended with the municipal effluent water without having to build the onsite RO. That correspond to the maximum economically profitable option. The Base Case is where APS pumps the maximum volume of less-expensive brackish water (limited by water chemistry in the circulating water system), i.e. the case for which cooling water acquisition and treatment cost are lowest (without RO). Second, the proposed RO Case includes two RO plants, one onsite at PVGS and another larger, regional RO plant close to the brackish water wells. The regional RO produces potable water that is sold to the regional municipalities, while the PVGS onsite RO treats (part of) the regional ROs' concentrate and brackish water blend. The desalinated water from the PVGS RO is used in the circulating water system at PVGS. The analysis evaluates the difference in economics, using the Net Present Value (NPV) and Internal Rate of Return (IRR), between the cases. By comparing the two cases, in addition to evaluating the economics of the regional RO, we can also assess the impact of the regional RO on PVGS operational costs and, consequently, APS economics. The study shows that there exist combinations of regional RO and PVGS RO sizes for which the total blowdown and water chemistry limits at PVGS (including regional RO concentrate treatment at PVGS) are satisfied. However, such combinations only exist if no additional brackish water is directly mixed in the tertiary water system at PVGS. This leads to higher Levelized Costs of Potable Water (LCOPW) compared to cases where additional brackish water is injected (but violate the physical constraints). Additional studies are suggested to investigate the benefit of additional brackish water injection (lowers cooling water cost) versus the cost of lifting the physical constraints, e.g. building additional evaporation ponds. Staying in the case of no additional brackish water and satisfying the existing PVGS constraints, the lowest LCOPW (~0.5 $/m 3 ) can be achieved with a size of the regional RO of ~1.4e7 m 3 /yr (11000 AF/yr) capacity, which leads to ~8.63e6 m 3 /yr (7000 AF/yr) of potable water while no onsite RO at PVGS is built. Considering the vii residential water demand model developed for the Phoenix west valley, the NPV for this regional RO would be ~$100 million if all municipalities in the vicinity participate from the beginning of the project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Changes in When and Where People are Spending Time in Response to COVID-19

The COVID-19 pandemic has resulted in a significant change in driving behavior as people respond to the new environment. However, existing methods for analyzing driver behavior such as travel surveys and travel demand models are not suited for incorporating abrupt environmental disruptions. To address this, we analyze a set of high-resolution trip data and introduce two new metrics for quantifying driving behavioral shifts as a function of time, allowing us to compare the time periods before and after pandemic began. We apply these metrics to the Denver, Colorado metropolitan statistical area (MSA) to demonstrate the utility of the metrics. Then, we present a case study for comparing two distinct MSAs, Louisville, Kentucky; and Des Moines, Iowa which exhibit significant differences in the makeup of their labor markets. The results indicate that although the regions of study exhibit certain unique driving behavioral shifts, emerging trends can be seen when comparing between seemingly distinct regions. For instance, drivers in all three MSAs are generally shown to have spent more time at residential locations and less time in workplaces in the time period after the pandemic started. In addition, workplaces that may be incompatible with remote working, such as hospitals and certain retail locations, generally retained much of their pre-pandemic travel activity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

DEEP CELLULAR RECURRENT NEURAL ARCHITECTURE FOR EFFICIENT MULTIDIMENSIONAL TIME-SERIES DATA PROCESSING

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in complexity and size to accommodate the additional dimensionality of time. Specifically, the biologically inspired learning based models known as artificial neural networks that have shown extraordinary success in pattern recognition, tend to grow prohibitively large and cumbersome in the presence of large scale multi-dimensional time series biomedical data such as EEG. Consequently, this work aims to develop representative ML and DL models for robust and efficient large scale time series processing. First, we design a novel ML pipeline with efficient feature engineering to process a large scale multi-channel scalp EEG dataset for automated detection of epileptic seizures. With the use of a sophisticated yet computationally efficient time-frequency analysis technique known as harmonic wavelet packet transform and an efficient self-similarity computation based on fractal dimension, we achieve state-of-the-art performance for automated seizure detection in EEG data. Subsequently, we investigate the development of a novel efficient deep recurrent learning model for large scale time series processing. For this, we first study the functionality and training of a biologically inspired neural network architecture known as cellular simultaneous recurrent neural network (CSRN). We obtain a generalization of this network for multiple topological image processing tasks and investigate the learning efficacy of the complex cellular architecture using several state-of-the?art training methods. Finally, we develop a novel deep cellular recurrent neural network (CDRNN) architecture based on the biologically inspired distributed processing used in CSRN for processing time series data. The proposed DCRNN leverages the cellular recurrent architecture to promote extensive weight sharing and efficient, individualized, synchronous processing of multi-source time series data. Experiments on a large scale multi-channel scalp EEG, and a machine fault detection dataset show that the proposed DCRNN offers state-of-the-art recognition performance while using substantially fewer trainable recurrent units.

Vidyaratne, Lasitha S.↗
DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1980

SPS market analysis

A market analysis task included personal interviews by GE personnel and supplemental mail surveys to acquire statistical data and to identify and measure attitudes, reactions and intentions of prospective small solar thermal power systems (SPS) users. Over 500 firms were contacted, including three ownership classes of electric utilities, industrial firms in the top SIC codes for energy consumption, and design engineering firms. A market demand model was developed which utilizes the data base developed by personal interviews and surveys, and projected energy price and consumption data to perform sensitivity analyses and estimate potential markets for SPS.

Goff, H. C.↗
NASA NTRS1981

Effects off system factors on the economics of and demand for small solar thermal power systems

Market penetration as a function time, SPS performance factors, and market/economic considerations was estimated, and commercialization strategies were formulated. A market analysis task included personal interviews and supplemental mail surveys to acquire statistical data and to identify and measure attitudes, reactions and intentions of prospective SPS users. Interviews encompassed three ownership classes of electric utilities and industrial firms in the SIC codes for energy consumption. A market demand model was developed which utilized the data base developed, and projected energy price and consumption data to perform sensitivity analyses and estimate potential market for SPS.

Source record↗
NASA NTRS1986

Towards effective interactive three-dimensional colour postprocessing

Recommendations for the development of effective three-dimensional, graphical color postprocessing are made. First, the evaluation of large, complex numerical models demands that a postprocessor be highly interactive. A menu of available functions should be provided and these operations should be performed quickly so that a sense of continuity and spontaneity exists during the post-processing session. Second, an agenda for three-dimensional color postprocessing is proposed. A postprocessor must be versatile with respect to application and basic algorithms must be designed so that they are flexible. A complete selection of tools is necessary to allow arbitrary specification of views, extraction of qualitative information, and access to detailed quantitative and problem information. Finally, full use of advanced display hardware is necessary if interactivity is to be maximized and effective postprocessing of today's numerical simulations is to be achieved.

Bailey, B. C.↗
NASA NTRS1990

The California corridor transportation system: A design summary

A design group was assembled to find and research criteria relevent to the design of a California Corridor Transportation System. The efforts of this group included defining the problem, conducting a market analysis, formulation of a demand model, identification and evaluation of design drivers, and the systematic development of a solution. The problems of the current system were analyzed and used to determine design drivers, which were divided into the broad categories of cost, convenience, feasibility, environment, safety, and social impact. The relative importance of individual problems was addressed, resulting in a hierarchy of design drivers. Where possible, methods of evaluating the relative merit of proposed systems with respect to each driver were developed. Short takeoff vertical landing aircraft concepts are also discussed for supersonic fighters.

Source record↗