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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

EJFAT: Towards Intelligent Compute Destination Load Balancing

To handle increased data flow, Jefferson Lab (JLab) is partnering with ESnet for development of an AI/ML directed compute work Load Balancer (LB) of UDP streamed data. The LB is FPGA based featuring dynamically configurable, low latency and high throughput destination address switching. The LB provides integration of edge and core computing to support JLab experimental programs, the Electron-Ion Collider, as well as data centers of the future. In the ESnet/JLab FPGA Accelerated Transport (EJFAT) initiative, the function of the LB Data Plane (DP) is to redirect data streams to selectable (but unknown to sender) destination hosts based on current worload and within that host to destination ports as a function of sub- stream id. This effects hierarchical scaling, first across compute machines for processing over a series of events and second, across ports so different data source sub-streams may be assigned to different processors for further parallelization. The LB Control Plane (CP) programs the DP using compute farm telemetry to direct and balance workloads across a compute cluster as the operating conditions require. While Proportional/Integrative/Derivative (PID) controllers are often seen in similar applications, here we investigate the feasibility of a Reinforcement Learning (RL) based schedule manager running in the CP to provide dynamic updates to the DP scheduling policy.

Lawrence, David↗
DOE OSTI2023

Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destination Data

Truck transportation remains the dominant mode of US freight transportation because of its advantages, such as the flexibility of accessing pickup and drop-off points and faster delivery. Because of the massive freight volume transported by trucks, understanding the effects of population and employment characteristics on truck flows is critical for better transportation planning and investment decisions. The US Federal Highway Administration published a truck travel origin-destination data set as part of the Next Generation National Household Travel Survey program. This data set contains the total number of truck trips in 2020 within and between 583 predefined zones encompassing metropolitan and nonmetropolitan statistical areas within each state and Washington, DC. In this study, origin-destination-level truck trip flow data was augmented to include zone-level population and employment characteristics from the US Census Bureau. Census population and County Business Patterns data were included. The final data set was used to train a machine learning algorithm-based model, Extreme Gradient Boosting (XGBoost), where the target variable is the number of total truck trips. Shapley Additive ExPlanation (SHAP) was adopted to explain the model results. Results showed that the distance between the zones was the most important variable and had a nonlinear relationship with truck flows.

Uddin, Majbah↗
DOE OSTI2022

The Experience Economy in a Wine Destination—Analysing Visitor Reviews

Wine tourism in rural territories, sometimes organised along wine routes, increasingly attracts visitors, tourism agents, wine producers and those responsible for developing rural territories. Wine tourism is located at the intersection of two distinct business sectors: the agribusiness-oriented wine production and the hedonic service/experience-oriented tourism activity. From the tourism perspective, the visitor experience is paramount and requires an understanding of its nature, conditioning factors and possible outcomes. This study analyses tourist experiences of the Bairrada wine route/Portugal, as reported by regional visitors on TripAdvisor. Results reveal not only the overall quite positive evaluation of these experiences, but also the importance of the aesthetic and educational experience dimensions, when applying Pine and Gilmore’s consumer experience framework. Diverse experience contexts contribute to a rich terroir experiencescape, where contents are far from limited to wine, wine cellars or wineries. These contexts seem to be connected distinctly to diverse experience dimensions, whose analysis should help regional developers understand the role of core resources and conditions for attracting, satisfying and delighting visitors. Additional understanding of the relationship between experience dimensions and outcomes, namely satisfaction and destination loyalty, should further help develop wine destinations more successfully.

Kastenholz, Elisabeth↗
DOE OSTI2025

Techno-economics of hydrocarbon fuel production and recyclables recovery from landfill-destined municipal solid waste: AI-enhanced materials recovery facility design

Sustainable aviation fuels (SAF) production from cellulosic paper fractions of municipal solid waste (MSW) destined for landfills has strong potential to advance environmental, social, and economic sustainability across the aviation and waste sectors. This study proposes an artificial intelligence-enabled material recovery facility (AI-MRF) design to efficiently characterize, separate, process, and convert recovered paper waste from MSW into intermediate chemicals and SAF. The AI-MRF, designed to process 233,091 metric tons of MSW annually, integrates smart manufacturing technologies including AI, visual and hyperspectral imaging, multi-sensor data, and traditional sorting systems. Well-characterized and sorted cellulosic paper waste was utilized for chemical and fuel production scenarios, while clean plastics, metals, and glass were considered for recycling. Conversion of paper waste into intermediate sugars achieved a net present value (NPV) of up to $\$67$ million. For sugar-to-SAF production scenarios, the minimum fuel selling price (MFSP) was calculated at $\$6.11$ per gasoline gallon equivalent (GGE) when excluding recyclable revenue, and $\$4.03$ per GGE when halving recyclable revenue. The MFSP was further reduced to $\$1.96$ per GGE when accounting for SAF sales and recyclables. Nationally, this approach could yield about 2 billion GGE of hydrocarbon fuel annually from available MSW in the United States.

09 BIOMASS FUELS↗
DOE OSTI2024

Modeling Electric Vehicle Charging Load Using Origin-Destination Data

The accelerating adoption of electric vehicles (EVs) poses challenges to the power grid, necessitating precise representation of mobility patterns for effective infrastructure upgrades. Traditional simulation-based charging demand estimation faces limitations in generating trip chains reflective of actual travel patterns without complex network modeling. Hence, an innovative agent-based trip chain generation model is introduced to overcome these challenges. Drawing from the National Household Travel Survey (NHTS) and the NextGen NHTS origin-destination add-on data for Clarke County, Georgia, this study proposes a simulation method capturing both temporal and spatial mobility patterns without relying on extensive network topology data. The resulting trip chains predict EV charging load at the Census Block Group level, validated with a 1.03 correlation to actual trip counts, affirming their reflective accuracy. Two charging scenarios, residential-only and charging-everywhere, reveal distinct demand profiles. The charging-everywhere scenario aligns closely with the trip profile, while the residential-only scenario exhibits an afternoon peak slightly surpassing the former. This study contributes a data-driven charging demand estimation methodology, offering critical insights for grid resiliency planning amid the evolving landscape of EV adoption.

Pan, Melrose↗
DOE OSTI2023

Quantifying airborne fraction trends and the destination of anthropogenic CO 2 by tracking carbon flows in a simple climate model

Abstract Atmospheric carbon dioxide (CO 2 ) concentrations have increased as a direct result of human activity and are at their highest level over the last 2 million years, with profound impacts on the Earth system. However, the magnitude and future dynamics of land and ocean carbon sinks are not well understood; therefore, the amount of anthropogenic fossil fuel emissions that remain in the atmosphere (the airborne fraction) is poorly constrained. This work aims to quantify the sources and controls of atmospheric CO 2 , the fate of anthropogenic CO 2 over time, and the likelihood of a trend in the airborne fraction. We use Hector v3.0, a coupled simple climate and carbon cycle model with the novel ability to explicitly track carbon as it flows through the Earth system. We use key model parameters in a Monte Carlo analysis of 15 000 model runs from 1750 to 2300. Results are filtered for physical realism against historical observations and CMIP6 projection data, and we calculate the relative importance of parameters controlling how much anthropogenic carbon ends up in the atmosphere. Modeled airborne fraction was roughly 52%, consistent with observational studies. The overwhelming majority of model runs exhibited a negative trend in the airborne fraction from 1960–2020, implying that current-day land and ocean sinks are proportionally taking up more carbon than the atmosphere. However, the percentage of atmospheric CO 2 derived from anthropogenic origins can be much higher because of Earth system feedbacks. We find it peaks at over 90% between 2010–2050. Moreover, when looking at the destination of anthropogenic fossil fuel emissions, only a quarter ends up in the atmosphere while more than half of emissions are taken up by the land sink on centennial timescales. This study evaluates the likelihood of airborne fraction trends and provides insights into the dynamics of anthropogenic CO 2 in the Earth system.

54 ENVIRONMENTAL SCIENCES↗