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DOE OSTI2022

Travel Patterns and Characteristics of Elderly Population in New York State: 2017 Update

According to US Census Bureau, the elderly population (individuals 65 years and older) has grown by over a third during the past decade (2010 to 2019), and by 3.2% from 2018 to 2019. It is essential for policymakers and planners to understand transportation issues associated with the elderly to meet their increasing travel demands. These issues include transportation and mobility of the elderly population, factors impacting their travel behavior, and transportation safety. In this study, Oak Ridge National Laboratory was tasked by the New York State Department of Transportation (NYSDOT) to conduct a detailed examination of travel behaviors and identify patterns and trends of its elderly residents. The National Household Travel Survey (NHTS) was used as the primary data source to analyze subjects and address questions such as: Are there differences in traveler demographics between the elderly population and those of younger age groups who live in various New York State (NYS) regions, e.g., New York City (NYC), other urban areas of NYS, or other parts of the country? How do they compare with the population at large? Are there any regional differences (e.g., urban versus rural)? Do any unique travel characteristics or patterns exist within the elderly group? How did these patterns change over time? In addition to the analysis of NHTS data, roadway travel safety concerns associated with elderly travelers were also investigated. Specifically, data on crashes involving the elderly (including drivers, passengers, and pedestrians) as captured in the Fatal Analysis Reporting System database was analyzed to examine elderly drivers and elderly pedestrian travel safety issues in NYS. This study report provides a summary of travel behavior and social-demographic characteristics of NYS elderly residents. These statistics could be used to examine equity issue concerning elderly New Yorkers, as well as to evaluate how well their mobility needs are being met. With a deeper understanding of issues and needs that this special population group is facing, policymakers and transportation planners would be able to make informed decisions on transportation investments and design services that could better address them.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Verifying LLM generative agents reflect human behavior in contested information environments to effectively simulate disinformation campaigns (Proteus)

Disinformation poses a significant and evolving threat to today’s online environment. Individuals encounter challenges in detecting disinformation, subsequently influencing their behavior and decision-making processes. Our research examines the potential use of large language model (LLM) generative agents (LGAs) to replicate human behavior to better understand how disinformation is spread in online environments. Using human subjects research, we first investigate how personality traits, individual differences, and demographic factors relate to decision-making in simulated online disinformation environments. Then, we examine whether LGAs can effectively replicate human responses in the same simulated online environments when assigned personality traits, demographic characteristics and behavioral attributes. Our findings indicate that LGAs can align with human decisions in these scenarios; however, alignment is contingent upon scenario context, persona settings and LLM selection. Results provide valuable insights for methodology refinement in future research and in utilizing LGAs to model complex national security challenges such as disinformation campaigns.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

ResStock Technical Reference Documentation (V.3.3.0)

ResStock™ is the best-in-class building stock energy model for simulating and publishing energy use, utility bills, and greenhouse gas emissions from the residential sector of the U.S. ResStock answers two primary questions: (1) How is energy used in the U.S. residential building stock? and (2) What is the timeseries aggregate impact of energy technologies? Specifically, ResStock quantifies energy use across geographical locations, demographic groups, building types, fuels, end uses, and time of day. Additionally, it details the impact of efficiency or electrification measures: total changes in the amount of energy used by measure; where or in what use cases efficiency or electrification upgrade measures save energy; when or at what times of day savings occur; and which building stock or demographic segments have the biggest savings potential. This model, and the datasets it produces, are foundational to identifying pathways to affordable and equitable decarbonization of the U.S. residential buildings sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Exploring Nonmotorized Travel in New York State Using 2017 National Household Travel Survey Data

This report presents systematic analysis of nonmotorized travel behavior within New York State (NYS) utilizing 2017 National Household Travel Survey data. As walking and biking assume increasingly prominent roles in advancing active transportation objectives, accessible mobility, and sustainable transportation systems, comprehensive understanding of these modal patterns becomes essential for evidence-based policy development and strategic planning initiatives. Recognizing the substantial geographic, demographic, and socioeconomic heterogeneity characterizing NYS—spanning from the concentrated urban fabric of New York City (NYC) to dispersed suburban and rural contexts—this analysis employs the structured "4Ws" analytical framework to examine participant demographics, spatial and temporal distributions, and motivational factors underlying active transportation choices relative to motorized alternatives. This methodological approach captures modal behavior patterns, user characteristics, trip purposes, and temporal variations across the state's diverse contexts. Additionally, the research examines behavioral differences among distinct user classifications, including walk-only and bike-only travelers, while conducting comparative analysis of nonmotorized travel patterns between ALICE (Asset Limited, Income Constrained, Employed) and non-ALICE household categories.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Myriad World Baseline: Global Geodemographic Estimates

The LandScan Myriad World Baseline (MWB) method produces global, residential (nighttime/home-location) gridded geodemographic estimates based on 5-year age/gender cohorts—at 30-arcsecond (≈1 km) resolution. MWB is designed to fill gaps where detailed, georeferenced survey data (e.g., Demographic and Health Surveys (DHS)) are missing or outdated, and to provide a baseline that can support human security analysis, including consequence assessment, “patterns of life” modeling, and scenario-based population futures. MWB’s workflow spatializes household-level age/gender characteristics from the GLOPOP-S dataset by conflating household and gridded expected relative wealth adapted from Global Gridded Relative Deprivation Index (GRDI), then adjusts them to a target year of interest. Age/gender estimates are then applied to harmonize lowest-administrative-level statistics with LandScan residential counts, yielding final geodemographic estimates. Two validation case studies are presented: Ghana (2021) and Tokyo/Kanagawa, Japan (2020), illustrating spatial variability in demographic cohorts and comparing MWB outputs to official gridded statistics. Results show close overall alignment relative to validation criteria including population pyramids and age-dependency ratios.

Tuccillo, Joe [ORNL] (ORCID:0000000259300943)↗

DOE OSTI2023

Spatial Microsimulation and Activity Allocation in Python: An Update on the Likeness Toolkit

Understanding human security and social equity issues within human systems requires large-scale models of population dynamics that simulate high-fidelity representations of individuals and access to essential activities (work/school, social, errands, health). Likeness is a Python toolkit that provides these capabilities for Oak Ridge National Laboratory's (ORNL) UrbanPop spatial microsimulation project. In step with the initial development phase for Likeness (2021 - 2022), we built out several foundational examples of work/school and health service access. In this paper, we describe expansion and scaling of Likeness capabilities to metropolitan areas in the United States. We then provide an integrated demonstration of our methods based on a case study of Leon County, FL and perform validation exercises on 1) neighborhood demographic composition and 2) visits by demographic cohorts (gender/age) obtained from point of interest (POI) footfall data for essential services (grocery stores). Taking into account lessons learned from our case study, we scope improvements to our model as well as provide a roadmap of the anticipated Likeness development cycle into 2023 - 2024.

Tuccillo, Joe↗

DOE OSTI2021

Consumer Preferences and Willingness to Pay for Potting Mix with Biochar

Biochar is a co-product of advanced biofuels production from feedstocks including food, agricultural, wood wastes, or dedicated energy crops. Markets for soil amendments using biochar are emerging, but little is known about consumer preferences and willingness to pay (WTP) for these products or the depth of the products’ market potential for this product. This research provides WTP estimates for potting mix amended with 25% biochar, conditioned on consumer demographics and attitudes about product information labeling. Data were collected with an online survey of 577 Tennessee home gardeners. WTP was elicited through a referendum contingent valuation. Consumer WTP for an 8.81 L bag of 25% biochar potting mix is $8.52; a premium of $3.53 over conventional potting mix. Demographics and attitudes toward biofuels and the environment influence WTP. Biochar amounts demanded are projected for the study area’s potential market. Optimal prices, profits, and market shares are estimated across different marginal costs of producing biochar potting mix.

09 BIOMASS FUELS↗

DOE OSTI2021

SolarSMART 2020 Georgia Survey

The SolarSMART 2020 Georgia Survey dataset provides results from a survey of 1,544 residents of the State of Georgia above the age of 18 on their perceptions of photovoltaic solar energy. The survey includes the following: demographic information for each respondent, their location in the state (by ZIP Code); the type of house they reside within; whether they have or have not adopted solar energy (and if so, how did they adopt solar energy); their personal views and perceptions of solar energy both for themselves and within their community; and their perceptions of who within Georgia and across the United States would or would not be inclined to adopt solar. Respondents were asked to provide their responses to questions addressing the following issues as they pertained to both themselves and their perceptions of others (Georgians and Americans writ large): (a) perception of how home type shape solar adoption; (b) perceptions of personal values (interpersonal, political, environmental); (c) the design of solar and the marketing of it; (d) financial dimensions of adopting solar energy; (d) and favorability towards new technologies. This data was collected via an online survey through a third-party distributor between June and September of 2020. Respondents were from 151 of the 159 counties of the State of Georgia, with representation of both urban and rural residents. In total, the dataset includes 171 variables, with one being an open-ended question coded by the research team. Variables include demographic characteristics (personal, housing, location), multiple-choice single answer, ranked-choice responses to different statements about solar, and a series of two digital map exercises where respondents highlighted geographic regions (states or parts of Georgia) based on whether the believe residents there do, do not, or they do not know if the respondents do or do not adopt solar.

14 SOLAR ENERGY↗

DOE OSTI2026

Public water supply infrastructure extensification and diversification in surface waters is insufficient to meet future demands in Texas

The data were developed to evaluate the capacity of existing and potential new surface water supply infrastructure to meet projected public water demands across districts in Texas under multiple future socioeconomic and climate scenarios. The database integrates hydrologic, water quality, infrastructure, energy, cost, demographic, and demand-projection information for candidate surface water supply locations. Candidate sites include stream reaches, waterbodies, reservoir surplus locations, and potential new reservoir sites. Water availability is characterized using historical and projected flow conditions, while site suitability is evaluated using five indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets include statewide candidate-site information, district-level demand projections under Shared Socioeconomic Pathways (SSPs), runoff-based allocation constraints, climate-stress metrics, and optimization outputs evaluating alternative infrastructure planning strategies. Optimization results compare Business-as-Usual (BAU) and All Surface Water (AllSW) demand-management approaches under both scaled and fixed cost-cap strategies. Associated validation datasets provide district-level feasibility assessments, infrastructure selection outcomes, cost-cap utilization, demand satisfaction metrics, and constraint diagnostics. Additional datasets quantify projected changes in storage and flow conditions as well as water availability stress for both existing and newly selected intake locations under the SSP5 scenario for mid-century and late-century climate conditions. Together, these datasets support assessment of the extent to which surface-water infrastructure expansion and diversification strategies can satisfy future public water demands while accounting for hydrologic, economic, and planning constraints across Texas. Dataset(s) Description Dataset_preoptimization.xlsx Comprehensive pre-optimization dataset containing candidate water-supply sites and associated hydrologic, water-quality, infrastructure, climate, demographic, runoff, and demand-projection variables used as inputs to the optimization analyses. Includes variable descriptions and the full statewide candidate-site database. District_level_site_selection.zip - Compressed archive containing all SSP-specific district-level optimization result files MESIO_ssp1_results.xlsx District-level site selection results for SSP1 (MESIO). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. MESID_ssp2_results.xlsx District-level site selection results for SSP2 (MESID). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. LCMRD_ssp3_results.xlsx District-level site selection results for SSP3 (LCMRD). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-Low_ssp4l_results.xlsx District-level site selection results for SSP4-Low (IRDev-Low). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-High_ssp4h_results.xlsx District-level site selection results for SSP4-High (IRDev-High). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. RSIM_ssp5_results.xlsx District-level site selection results for SSP5 (RSIM). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. tx_hydrological_stress.xlsx Hydrological stress dataset for existing and newly selected intake locations. Includes projected mid-century and late-century changes, gain/loss classifications, planning strategy information, and accompanying variable descriptions. Also includes water-stress metrics derived from historical and projected low-flow conditions.

Okoye, Perpetua I. (ORCID:0000000215545033)↗

NASA NTRS1975

Experimental studies for determining human discomfort response to vertical sinusoidal vibration

A study was conducted to investigate several problems related to methodology and design of experiments to obtain human comfort response to vertical sinusoidal vibration. Specifically, the studies were directed to the determination of (1) the adequacy of frequency averaging of vibration data to obtain discomfort predictors, (2) the effect of practice on subject ratings, (3) the effect of the demographic factors of age, sex, and weight, and (4) the relative importance of seat and floor vibrations in the determination of measurement and criteria specification location. Results indicate that accurate prediction of discomfort requires knowledge of both the acceleration level and frequency content of the vibration stimuli. More importantly, the prediction of discomfort was shown to be equally good based upon either floor accelerations or seat accelerations. Furthermore, it was demonstrated that the discomfort levels in different seats resulting from similar vibratory imputs were equal. Therefore, it was recommended that criteria specifications and acceleration measurements be made at the floor location. The results also indicated that practice did not systematically influence discomfort responses nor did the demographic factors of age, weight, and sex contribute to the discomfort response variation.

Dempsey, T. K.↗

NASA NTRS1986

Influences on corporate executive decision behavior in government acquisitions

This paper presents extensive exploratory research which had as its primary objective, the discovery and determination of major areas of concern exhibited by U.S. corporate executives in the preparation and submittal of proposals and bids to the Federal government. The existence of numerous unique concerns inherent in corporate strategies within the government market environment was established. A determination of the relationship of these concerns to each other was accomplished utilizing statistical factor analysis techniques resulting in the identification of major groupings of management concerns. Finally, using analysis of variance, an analysis and discovery of the interrelationship of the factors to corporate demographics was accomplished. The existence of separate and distinct concerns exhibited by corporate executives when contemplating sales and operations in the government marketplace was established. It was also demonstrated that quantifiable relationships exist between such variables and that the decision behavior exhibited by the responsible executives has an interrelationship to their company's demographics.

Wetherington, J. R.↗

NASA NTRS1994

Bureau of the Census Center for International Research

This paper describes the organization and activities of the Center for International Research at the Bureau of the Census. There is a formal publication exchange program with other government's statistical programs. This has resulted in the Center's collection being one of the world's largest in the area of international census and demographic information. Foreign statistical publications are in three libraries, one being dedicated to the former Soviet Union and one to the Peoples Republic of China. In addition to the libraries there are two computerized data bases. The International data base is a source of demographic and socio-economic statistics for all countries of the world. The second data base is the HIV/AIDS Surveillance Data Base which contains information related to the publication and dissemination of the results of seroprevalence surveys.

Pinto, Nina Pane↗

NASA NTRS2000

Predictors of Behavior and Performance in Extreme Environments: The Antarctic Space Analogue Program

To determine which, if any, characteristics should be incorporated into a select-in approach to screening personnel for long-duration spaceflight, we examined the influence of crewmember social/ demographic characteristics, personality traits, interpersonal needs, and characteristics of station physical environments on performance measures in 657 American men who spent an austral winter in Antarctica between 1963 and 1974. During screening, subjects completed a Personal History Questionnaire which obtained information on social and demographic characteristics, the Deep Freeze Opinion Survey which assessed 5 different personality traits, and the Fundamental Interpersonal Relations Orientation-Behavior (FIRO-B) Scale which measured 6 dimensions of interpersonal needs. Station environment included measures of crew size and severity of physical environment. Performance was assessed on the basis of combined peer-supervisor evaluations of overall performance, peer nominations of fellow crewmembers who made ideal winter-over candidates, and self-reported depressive symptoms. Social/demographic characteristics, personality traits, interpersonal needs, and characteristics of station environments collectively accounted for 9-17% of the variance in performance measures. The following characteristics were significant independent predictors of more than one performance measure: military service, low levels of neuroticism, extraversion and conscientiousness, and a low desire for affection from others. These results represent an important first step in the development of select-in criteria for personnel on long-duration missions in space and other extreme environments. These criteria must take into consideration the characteristics of the environment and the limitations they place on meeting needs for interpersonal relations and task performance, as well as the characteristics of the individuals and groups who live and work in these environments.

Palinkas, Lawrence A.↗

NASA NTRS2000

Crew Factors in Flight Operations XII: A Survey of Sleep Quantity and Quality in On-Board Crew Rest Facilities

Many aircraft operated on long-haul commercial airline flights are equipped with on-board crew rest facilities, or bunks, to allow crewmembers to rest during the flight. The primary objectives of this study were to gather data on how the bunks were used, the quantity and quality of sleep obtained by flight crewmembers in the facilities, and the factors that affected their sleep. A retrospective survey comprising 54 questions of varied format addressed demographics, home sleep habits, and bunk sleep habits. Crewmembers from three airlines with long-haul fleets carrying augmented crews consisting of B747-100/200, B747-400, and MD-11 aircraft equipped with bunks returned a total of 1404 completed surveys (a 37% response rate). Crewmembers from the three carriers were comparable demographically, although one carrier had older, more experienced flight crewmembers. Each group, on average, rated themselves as "good" or "very good" sleepers at home, and all groups obtained about the same average amount of sleep each night. Most were able to sleep in the bunks, and about two thirds indicated that these rest opportunities benefited their subsequent flight deck alertness and performance. Comfort, environment, and physiology (e.g., being ready for sleep) were identified as factors that most promoted sleep. Factors cited as interfering with sleep included random noise, thoughts, heat, and the need to use the bathroom. These factors, in turn, suggest potential improvements to bunk facilities and their use. Ratings of the three aircraft types suggested differences among facilities. Bunks in the MD-11 were rated significantly better than either of the B747 types, and the B747-400 bunks received better ratings than did the older, B747-100/200 facilities.

Rosekind, Mark R.↗

NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗

NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

Viken, Jeff↗

NASA NTRS2011

Environmental Variation and Cohort Effects in an Antarctic Predator

Understanding the potential influence of environmental variation experienced by animals during early stages of development on their subsequent demographic performance can contribute to our understanding of population processes and aid in predicting impacts of global climate change on ecosystem functioning. Using data from 4,178 tagged female Weddell seal pups born into 20 different cohorts, and 30 years of observations of the tagged seals, we evaluated the hypothesis that environmental conditions experienced by young seals, either indirectly through maternal effects and/or directly during the initial period of juvenile nutritional independence, have long-term effects on individual demographic performance. We documented an approximately 3-fold difference in the proportion of each cohort that returned to the pupping colonies and produced a pup within the first 10 years after birth. We found only weak evidence for a correlation between annual environmental conditions during the juvenile-independence period and cohort recruitment probability. Instead, the data strongly supported an association between cohort recruitment probability and the regional extent of sea ice experienced by the mother during the winter the pup was in utero. We suggest that inter-annual variation in winter sea-ice extent influences the foraging success of pregnant seals by moderating the regional abundance of competing predators that cannot occupy areas of consolidated sea ice, and by directly influencing the abundance of mid-trophic prey species that are sea-ice obligates. We hypothesize that this environmentally-induced variation in maternal nutrition dictates the extent of maternal energetic investment in offspring, resulting in cohort variation in mean size of pups at weaning which, in turn, contributes to an individual?s phenotype and its ultimate fitness. These linkages between sea ice and trophic dynamics, combined with demonstrated and predicted changes in the duration and extent of sea ice associated with climate change, suggest significant alterations in Antarctic marine ecosystems in the future.

Garrott, Robert A.↗

NASA NTRS2012

Asthma and Air Quality in the Presence of Fires - A Foundation for Public Health Policy in Florida

Outdoor air quality and its associated impacts on respiratory problems in Florida are of public health significance. Air quality in Florida can be poor during the extended wildfire season, threatening persons with compromised respiratory systems each year. Studies have demonstrated that particulate matter, which is generally elevated in the vicinity of wildfires, is associated with increases in hospital admissions and occurrences of acute asthma exacerbations. However, few studies have examined the modifying effect of socio-demographic characteristics of cities or regional areas on the relationship between air quality and health outcomes. In an ongoing university/multi-agency project, asthma hospital/emergency room (patient) data are being used to create a health outcome indicator of human response to environmental air quality. Environmental data are derived from satellite measurements, with special attention being given to the effect of wildfires and prescribed burns on air quality. This presentation will focus on the environmental data sets particulate matter, location of fires, smoke plumes that are being collected and processed for linkage with health data. After this linkage has been performed, space-time models of asthma rates as a function of air quality data and socio-demographic variables will be developed and validated. The Florida Department of Health (FDOH) will work with county health department staff and representatives from the medical community to establish a protocol with triggers for issuing public health advisories/alerts based on the developed and validated health outcome indicators. From this effort, a science-based policy for issuing public health advisories/alerts for asthma relating to air quality will be developed, giving FDOH the ability to (1) predict, with stated levels of uncertainty, case load of hospital admissions based on air quality, (2) reduce asthma exacerbations by forewarning asthmatics to limit outside activities on poor air quality days, (3) apply management practices on the rates of hospital/emergency room visits for asthma, and (4) provide information that would help translate interventions into policy decisions, thereby reducing the economic burden and increasing well being of asthmatics. Further, the results of the study will be incorporated into Florida s Environmental Public Health Tracking (EPHT) program, which is part of the Centers for Disease Control and Prevention's (CDC's) EPHT network.

Crosson, William↗