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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Streaming Compression of Scientific Data via Weak-SINDy

Here, in this paper, a streaming weak-SINDy algorithm is developed specifically for compressing streaming scientific data. The production of scientific data, either via simulation or experiments, is undergoing a stage of exponential growth, which makes data compression important and often necessary for storing and utilizing large scientific data sets. As opposed to classical “offline” compression algorithms that perform compression on a readily available data set, streaming compression algorithms compress data “online” while the data generated from simulation or experiments is still flowing through the system. This feature makes streaming compression algorithms well suited for scientific data compression, where storing the full data set offline is often infeasible. This work proposes a new streaming compression algorithm, streaming weak-SINDy, which takes advantage of the underlying data characteristics during compression. The streaming weak-SINDy algorithm constructs feature matrices and target vectors in the online stage via a streaming integration method in a memory efficient manner. The feature matrices and target vectors are then used in the offline stage to build a model through a regression process that aims to recover equations that govern the evolution of the data. For compressing high-dimensional streaming data, we adopt a streaming proper orthogonal decomposition (POD) process to reduce the data dimension and then use the streaming weak-SINDy algorithm to compress the temporal data of the POD expansion. We propose modifications to the streaming weak-SINDy algorithm to accommodate the dynamically updated POD basis. By combining the built model from the streaming weak-SINDy algorithm and a small amount of data samples, the full data flow could be reconstructed accurately at a low memory cost, as shown in the numerical tests.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗
DOE OSTI2025

Accelerating nuclear-integrated data center pursuits in the USA: SWOT analysis, power-thermal management strategies and demonstration plan

Here, this study explores the increasing interest in leveraging nuclear power to meet the escalating energy demands of data centers in the United States (U.S.) by focusing on key factors that contribute to accelerated deployment. The study highlights the importance of N+1/N+2 power supplies (where N is the required number of units), outlines research and innovations in nuclear-integrated data center thermal management and demonstration plan. It also provides updates about status and costing of various reactor system designs. A summarized strengths, weaknesses, opportunities, and threats (SWOT) analysis shows the potential options for grid connectivity, reactors, and site selection. Suitable site discussions consider land and water availability, grid access, and optical fiber connectivity, and the study presents graded prospects for Department of Energy (DOE) sites with a specific example. Community engagement and partnerships are emphasized, particularly the roles of local government, federal agencies, utilities, and data center industry partners, which are crucial for accelerating deployment, business outreach, and approvals. The study provides actionable insights for stakeholders to accelerate the deployment of nuclear-powered data centers.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

2012 California Household Travel Survey Supplement

# 2012 California Household Travel Survey Supplement The 2012 California Household Travel Survey Supplement focused on gathering specific travel information from residents for the development of next-generation, activity-based models. Called the "Augment Survey," it supplemented the [2010–2012 California Household Travel Survey](https://www.nrel.gov/transportation/secure-transportation-data/tsdc-california-travel-survey). ## Data Collection Agency The Southern California Association of Governments (SCAG) hired Abt-SRBI, Inc. to conduct the survey. ## Methodology Travel data were collected from households via in-vehicle (625 vehicles) and wearable (244 participants) global positioning system (GPS) devices. ## 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 Study records include 473 households. ## Transportation Data The SCAG data set contains data from 473 households that participated in one or more areas of study. Of these, 141 completed the wearable GPS portion of the study and 332 completed the vehicle GPS portion. There was no overlap between households participating in the two study areas (wearable and vehicle GPS). For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/caltrans_scag_data_dictionary.pdf?sfvrsn=6ec36d7a_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

Advancing Urban Water Resilience: Coproducing Knowledge through Civic–Academic Global Partnerships on Water and Climate

As extreme weather events become more pronounced, the vulnerabilities associated with the urban water supply and wastewater systems in megacities are intensified in multiple interconnected dimensions. These multifaceted water challenges can benefit from enhanced cross-sectoral collaboration and sharing of critical knowledge, which are essential for sustainable and adaptive water governance frameworks. In this context, the Megacity Alliance for Water and Climate (MAWAC)–Europe and North America Region (ENAR) Working Group convened a workshop in March 2023, followed by a subsequent workshop in London, United Kingdom, from 11 to 13 September 2024. These workshops aimed to investigate and devise solutions for the cascading hazards with water systems. The solutions examined various aspects focused on climate adaptation and mitigation, stormwater management, and the governance of water and wastewater systems. Additionally, discussions highlighted the importance of community engagement, economic considerations, equity, and effective communication in addressing these pressing challenges. Over the course of 3 days, experts from academia, government agencies, and industry engaged in meaningful discussions on digital modeling for integrated water management, climate-informed urban planning, and public–private–academic partnerships (Fig. 1). Case studies from cities such as New York, Los Angeles, London, Paris, and Chicago highlighted innovative governance strategies for managing water and wastewater systems, promoting water reuse, planning infrastructure, and fostering stakeholder-driven and stakeholder-informed adaptation. The workshop participants emphasized the need for data-driven decision-making, scalable governance models, and knowledge-sharing networks to enhance urban water governance for sustainability and resilience. This workshop report presents the key takeaways from the 3-day convening, providing a roadmap for integrating scientific research, policy frameworks, and emerging technologies to address water challenges faced by megacities.

Hydrologic models↗
DOE OSTI2026

Data-Driven Modeling and Correction of Vehicle Dynamics

We develop a data-driven framework for learning and correcting nonautonomous vehicle dynamics. Physics-based vehicle models are often simplified for tractability and therefore exhibit inherent model-form uncertainty, motivating the need for data-driven correction. Moreover, nonautonomous dynamics are governed by time-dependent control inputs, which pose challenges in learning predictive models directly from temporal snapshot data. To address these, we reformulate the vehicle dynamics via a local parameterization of the time-dependent inputs, yielding a modified system composed ofa sequence of local parametric dynamical systems. Here, we approximate these parametric systems using two complementary approaches. First, we employ the dimension reduction and interpolation in parameter space (DRIPS) methodology to construct efficient linear surrogate models, equipped with lifted observable spaces and manifold-based operator interpolation. This enables data-efficient learning of vehicle models whose dynamics admit accurate linear representations in the lifted spaces. Second, for more strongly nonlinear systems, we employ flow map learning (FML), a deep neural network (DNN) approach that approximates the parametric evolution map without requiring special treatment of nonlinearities. We further extend FML with a transfer-learning-based model correction procedure, enabling the correction of misspecified prior models using only a sparse set of high-fidelity or experimental measurements, without assuming a prescribed form for the correction term. Through a suite of numerical experiments on unicycle, simplified bicycle, and slip-based bicycle models, we demonstrate that DRIPS offers robust and highly data-efficient learning of nonautonomous vehicle dynamics, while FML provides expressive nonlinear modeling and effective correction of model-form errors under severe data scarcity.

data-driven modeling↗
DOE OSTI2025

Determination of Scale Bar for AGHCF Metallography Data

The DOE Nuclear Energy Advanced Reactor Technologies (ART) Fast Reactor Program (FRP) has supported the development of several databases containing information on the safety performance of fast reactors, components, and fuels. This growing collection of legacy experimental data, operating data, and analysis is available online to registered users. Metallography data represents one of the most critical types of post-irradiation examination (PIE) data being collected, organized, and archived in several ART Fast Reactor Databases (https://frdb.ne.anl.gov), including the Metallic Fuels Irradiation & Physics Database (FIPD), Out-of-Pile Transient Database (OPTD), and TREAT (the Transient Reactor Test Facility) Experimental Relational Database (TREXR). These databases contain three principal sets of metallography data. The first set comprises metallography data from Experimental Breeder Reactor-II (EBR-II) and Fast Flux Test Facility (FFTF) irradiated fuel pins examined in the Hot Fuel Examination Facility (HFEF). The second set consists of metallography data from EBR-II irradiated fuel pins examined in the Alpha-Gamma Hot Cell Facility (AGHCF). The third set includes metallography data from transient-tested fuel pins (including both out-of-pile furnace tests and TREAT tests) examined in AGHCF. Since both the second and third sets were generated in AGHCF, they are governed by identical specifications. The metallography data in the databases consist of digital images scanned from either positive or negative photographic films. To analyze the microstructure of a fuel pin, a series of preparatory steps are required, including sectioning, epoxy mounting, mechanical grinding and polishing, and etching. Following sample preparation, specimens are transferred for metallographic examination. The AGHCF and HFEF metallography data were generated using optical microscopes manufactured by Leitz and Bausch and Lomb (B&L). Images were recorded on Polaroid film at preset magnifications. Magnification verification for the Leitz and B&L metallographs was conducted every two months prior to 1989 and at least every six months from 1989 through the conclusion of the IFR program. Magnifications determined from imaging of microslide standards were compared to the instrument settings for magnifications ranging from 50× to 500×. If the magnifications determined from standards deviated from the instrument settings, adjustments were made to the bellows extension until agreement was achieved. The specifications for AGHCF and HFEF legacy metallography data have been established based on available hard-copy and digital records, most of which have been incorporated into the data repositories associated with FIPD, OPTD, and TREXR. Detailed specifications including hard-copy records, digitized records, cutting diagrams and sectioning schemes, high-magnification photographs, photomosaics (composites), information tags, scale bars, and magnification verification procedures can be found in a separate report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Fracture Intersections under Stress: Laboratory Data and Code [Data set]

The connectivity of natural and induced fractures governs the injection and withdrawal of fluids from subsurface reservoirs. Connectivity depends on intersections that control how fluids mix and move through the entire system. Here, we present data sets from 3D X-ray microscopy measurements of simple fracture networks under stress. 3D printing was used to create prismatic blocks that formed fracture networks composed of 2 orthogonal fractures. The network orientation was either "x" or "+" relative to an applied vertical stress. 3D data sets were collected for normal loads of 25, 100 and 200 Newtons for samples with fracture surfaces with either correlated or uncorrelated asperity distributions. The file contains data from the 12 samples analyzed along with an example code used to extract the intersection geometry. Additional experimental details can be found in the manuscript "Geologic Stress Modulates Fluid Mixing at Fracture Intersections" (10.1038/s43247-026-03525-9)and supplemental information to appear in Communications Earth & Environment in 2026.

02 PETROLEUM↗