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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 OSTI2023

Integration of urban science and urban climate adaptation research: opportunities to advance climate action

There is a growing recognition that responding to climate change necessitates urban adaptation. We sketch a transdisciplinary research effort, arguing that actionable research on urban adaptation needs to recognize the nature of cities as social networks embedded in physical space. Given the pace, scale and socioeconomic outcomes of urbanization in the Global South, the specificities and history of its cities must be central to the study of how well-known agglomeration effects can facilitate adaptation. The proposed effort calls for the co-creation of knowledge involving scientists and stakeholders, especially those historically excluded from the design and implementation of urban development policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics

The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their as- sociated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

Parete-Koon, Suzanne↗
DOE OSTI2021

A convergence research perspective on graduate education for sustainable urban systems science

Sustainable urban systems (SUS) science is a new science integrating work across established and emerging disciplines, using diverse methods, and addressing issues at local, regional, national, and global scales. Advancing SUS requires the next generation of scholars and practitioners to excel at synthesis across disciplines and possess the skills to innovate in the realms of research, policy, and stakeholder engagement. Here, we outline key tenets of graduate education in SUS, informed by historical and global perspectives. The sketch is an invitation to discuss how graduates in SUS should be trained to engage with the challenges and opportunities presented by continuing urbanization.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

CROCUS Urban Fluxes of CO₂, H₂O, and Turbulence at University of Illinois Chicago

As of May 12, 2026 this dataset is currently being versioned to include data up to April 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. This dataset was collected at the UIC Plant Research Laboratory in Chicago, Illinois, as part of the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory. The site provides continuous atmospheric flux measurements, focusing on CO₂, H₂O, and heat and momentum transport in an urban setting. The data is processed at 30 minutes interval using the Eddy Covariance method and includes quality control and diagnostic data generated by EddyPro software. The data is stored in the netCDF files following CF conventions. The UIC Plant Research Laboratory is located near major highways and urban infrastructure, including buildings and parking areas. The surrounding landscape consists of a mix of turf, plants, trees, and impervious surfaces such as concrete and asphalt, making it ideal for studying urban at for studies on urban sustainability, air quality, and the effects of urbanization on atmospheric processes on urban climate dynamics, air quality, and surface-atmosphere exchanges within the city of Chicago. This dataset is funded by the U.S. Department of Energy’s Office of Science, Biological and Environmental Research (BER) program.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CROCUS 3-D wind data from Argonne Deployable Mast during Urban Canyon IOP July 2024

During the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory, this dataset was collected by METEK uSonic-3 Class A MP sonic anemometer at 10 meter height of the Argonne Deployable Mast (ADM) from July 26 to July 28, 2024, .As part of the CROCUS 2024 Urban Canyon Intensive Observation Period (IOP), 3-D sonic anemometer on the ADM was set up to provide continuous measurements of wind and temperature in Chicago during July 2024. These measurements cover winds in X-, Y- and Z- direction and sonic temperature at 30-Hz resolution. The data are formatted as NetCDF (.nc) files, making them easily accessible using common software such as MATLAB, R, and Python.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CROCUS Air Quality Dataset from the University of Illinois Chicago (UIC), July 2024

This dataset was collected by the measurement system in the Atmosphere, Climate, and Ecosystems (ACE) Lab at the University of Illinois Chicago (UIC) from July 12 to July 31, 2024, as part of the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory.To enhance understanding of urban air quality dynamics in Chicago, and as part of the CROCUS 2024 Urban Canyon Intensive Observation Period (IOP), several instruments were set up to provide continuous measurements of air quality parameters in Chicago during July 2024. These measurements cover both aerosols and gas-phase species. It focuses on particle size distribution (2.5–478 nm) measured by two Scanning Mobility Particle Sizers (SMPS) at a 4-min resolution, total particle number concentrations at a 1-s resolution, and chemical composition from a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (AMS) at a 1-min resolution. Key gas-phase species, including NO, NO₂, SO₂, and O₃, are measured at a 1-min resolution, along with high-resolution NO and dimethyl sulfide (DMS) data from a Chemical Ionization Mass Spectrometer (CIMS). Volatile organic compound (VOC) data for toluene, isoprene, and benzene are provided by a GC-PID with a time resolution of 25 minutes.The data are formatted as NetCDF (.nc) files, making them easily accessible using common software such as MATLAB, R, and Python. Each parameter is stored in an individual dataset, which includes detailed instrument information in the header, as well as the corresponding sample start time and concentration/distribution data for each sample.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Data Science and Urban Air Mobility: Challenges and Opportunities

Aviation is broadly a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Urban Air Mobility↗
NASA NTRS2020

Data Science and Urban Air Mobility: Challenges and Opportunities

Aviation is broadly a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Urban Air Mobility↗
NASA NTRS2003

The Land Use and Land Cover Dichotomy: A Comparison of Two Land Classification Systems in Support of Urban Earth Science Applications

One is likely to read the terms 'land use' and 'land cover' in the same sentence, yet these concepts have different origins and different applications. Land cover is typically analyzed by earth scientists working with remotely sensed images. Land use is typically studied by urban planners who must prescribe solutions that could prevent future problems. This apparent dichotomy has led to different classification systems for land-based data. The works of earth scientists and urban planning practitioners are beginning to come together in the field of spatial analysis and in their common use of new spatial analysis technology. In this context, the technology can stimulate a common 'language' that allows a broader sharing of ideas. The increasing amount of land use and land cover change challenges the various efforts to classify in ways that are efficient, effective, and agreeable to all groups of users. If land cover and land uses can be identified by remote methods using aerial photography and satellites, then these ways are more efficient than field surveys of the same area. New technology, such as high-resolution satellite sensors, and new methods, such as more refined algorithms for image interpretation, are providing refined data to better identify the actual cover and apparent use of land, thus effectiveness is improved. However, the closer together and the more vertical the land uses are, the more difficult the task of identification is, and the greater is the need to supplement remotely sensed data with field study (in situ). Thus, a number of land classification methods were developed in order to organize the greatly expanding volume of data on land characteristics in ways useful to different groups. This paper distinguishes two land based classification systems, one developed primarily for remotely sensed data, and the other, a more comprehensive system requiring in situ collection methods. The intent is to look at how the two systems developed and how they can work together so that land based information can be shared among different users and compared over time.

McAllister, William K.↗
DOE OSTI2020

Defining pathways to healthy sustainable urban development

Goals and pathways to achieve sustainable urban development have multiple interlinkages with human health and wellbeing. However, these interlinkages have not been examined in depth in recent discussions on urban sustainability and global urban science. This paper fills that gap by elaborating in detail the multiple links between urban sustainability and human health and by mapping research gaps at the interface of health and urban sustainability sciences. As researchers from a broad range of disciplines, we aimed to: 1) define the process of urbanization, highlighting distinctions from related concepts to support improved conceptual rigour in health research; 2) review the evidence linking health with urbanization, urbanicity, and cities and identify cross-cutting issues; and 3) highlight new research approaches needed to study complex urban systems and their links with health. This novel, comprehensive knowledge synthesis addresses issue of interest across multiple disciplines. Our review of concepts of urban development should be of particular value to researchers and practitioners in the health sciences, while our review of the links between urban environments and health should be of particular interest to those outside of public health. We identify specific actions to promote health through sustainable urban development that leaves no one behind, including: integrated planning; evidence-informed policy-making; and monitoring the implementation of policies. We also highlight the critical role of effective governance and equity-driven planning in progress towards sustainable, healthy, and just urban development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multi-Sectoral Urban Interactions: Fundamental Science Needs to Inform Pathways to More Resilient Communities in a Changing Climate Multi-Sectoral Urban Interactions: Fundamental Science Needs to Inform Pathways to More Resilient Communities in a Changing Climate

Urban areas and the supply networks that support their resource use are inherently multisectoral systems composed of infrastructural, environmental, and socio-institutional components. These systems are vulnerable to accelerating and interacting stresses from climate change, population growth, resource scarcity, and land-use pressure at the same time as they have a major influence on regional and global systems. For instance, a majority of the world’s greenhouse gas emissions, food consumption, and economic activity can be attributed to urban areas. Urban areas are highly heterogenous, both across and within cities in terms of their socio-demographic, environmental, and infrastructural characteristics. This heterogeneity shapes how urban systems interact and co-evolve and contributes to different economic, environmental, and health outcomes for communities within urban areas. Urban heterogeneity also generates differential vulnerabilities to stressors and differential capacity for adapting to change. The evolution of urban space is thus critical in shaping how human societies respond to global change as they seek to improve resilience to stressors, support prosperous and equitable communities, and use natural resources in a sustainable manner. Developing fundamental scientific understanding of urban heterogeneity and system interactions across sectors and scales is critical for mapping the resilience, sustainability, and equity implications of alternative future pathways. On July 2021 the MSD Urban Systems Working Group organized this workshop to provide a venue for coordination and identification of shared objectives, research themes, and major knowledge gaps, as well as developing a shared strategy for addressing these gaps. This report summarizes the outcomes of this workshop.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems

We describe an “Urban Observatory” facility designed for the study of complex urban systems via persistent, synoptic, and granular imaging of dynamical processes in cities. An initial deployment of the facility has been demonstrated in New York City and consists of a suite of imaging systems—both broadband and hyperspectral—sensitive to wavelengths from the visible (∼400 nm) to the infrared (∼13 micron) operating at cadences of ∼0.01–30 Hz (characteristically ∼0.1 Hz). Much like an astronomical survey, the facility generates a large imaging catalog from which we have extracted observables (e.g., time-dependent brightnesses, spectra, temperatures, chemical species, etc.), collecting them in a parallel source catalog. We have demonstrated that, in addition to the urban science of cities as systems, these data are applicable to a myriad of domain-specific scientific inquiries related to urban functioning including energy consumption and end use, environmental impacts of cities, and patterns of life and public health. We show that an Urban Observatory facility of this type has the potential to improve both a city’s operations and the quality of life of its inhabitants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city advancement

The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management. Despite their effectiveness, these applications often rely on massive amounts of high-dimensional and multi-domain data for monitoring and characterizing different urban sub-systems, presenting challenges in application areas that are limited by data quality and availability, as well as costly efforts for generating urban scenarios and design alternatives. As an emerging research area in deep learning, Generative Artificial Intelligence (GenAI) models have demonstrated their unique values in content generation. This paper aims to explore the innovative integration of GenAI techniques and urban digital twins to address challenges in the planning and management of built environments with focuses on various urban sub-systems, such as transportation, energy, water, and building and infrastructure. The survey starts with the introduction of cutting-edge generative AI models, such as the Generative Adversarial Networks (GAN), Variational Autoencoders (VAEs), Generative Pre-trained Transformer (GPT), followed by a scoping review of the existing urban science applications that leverage the intelligent and autonomous capability of these techniques to facilitate the research, operations, and management of critical urban subsystems, as well as the holistic planning and design of the built environment. Based on the review, we discuss potential opportunities and technical strategies that integrate GenAI models into the next-generation urban digital twins for more intelligent, scalable, and automated smart city development and management.

3D city modeling↗
NASA NTRSDate not supplied

Data Science Challenges for Urban Air Mobility

Aviation is a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Data Science↗
NASA NTRS2020

Data Science Challenges for Urban Air Mobility

Aviation is a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Data Science↗
DOE OSTI2024

CROCUS High-Frequency Measurements of CO₂, H₂O, Wind, and Temperature at University of Illinois Chicago

As of April 9, 2026: this dataset is currently being versioned to include data up to March 31, 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. Raw atmospheric measurements collected at the University of Illinois Chicago (UIC) as part of the Community Research on Climate and Urban Science (CROCUS) project. The data includes high-frequency measurements of carbon dioxide (CO₂) concentration, water vapor (H₂O) concentration, wind speed (U, V, W components), temperature, and atmospheric pressure. These raw data are recorded by the LI-7500DS Open Path CO₂/H₂O Analyzer and a sonic anemometer at a 10 Hz acquisition frequency, providing the necessary inputs for calculating fluxes of CO₂, H₂O, heat, and momentum. In addition to gas concentration measurements, the dataset includes diagnostic information from the instruments, including absorptance, sample and reference signals, and diagnostic values. The data were collected to study urban atmospheric conditions and contribute to flux calculations for urban climate research. These measurements form the basis for calculating 30-minute average fluxes of key atmospheric variables using the eddy covariance method. This dataset provides critical raw input data for researchers interested in atmospheric fluxes, urban air quality, and the interaction between the urban environment and atmospheric processes. The data is part of the U.S. Department of Energy’s Biological and Environmental Research (BER) program, under the CROCUS Urban Integrated Field Laboratory (UIFL) project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities]

Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems. Here, examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures), (b) structural and nuclear engineering to model the temporal evolution of the structural damage of concrete shields exposed to continuous neutron and gamma radiations emitted by the nuclear reactor core, (c) urban sciences (e.g., transportation and smart buildings), and (d) power grid systems.

97 MATHEMATICS AND COMPUTING↗