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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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DOE OSTI2022

CRADA Number NFE-18-07313 with Nth Cycle, Inc. (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-18-07313 between Oak Ridge National Laboratory (ORNL) and Nth Cycle Inc. focused on developing a technology for sustainable recycling of rare earth and specialty metals (e.g., Y, Co, Li; RESE), as well as bulk and precious metals from industrial manufacturing and waste streams through the use of electrochemical carbon nanotube-enabled filters. The project outcome was expected to be a stronger mechanistic understanding of the electrochemical recovery of metals from real manufacturing process streams and e-waste streams, and the development of an optimized high-throughput pilot-scale device ready for commercialization. Testing, design, and development of a v1 prototype to prove the technology was unsuccessful (we were not able to reach the go/no-go outlined in Objective 1) and we were unable to continue our redesign due to COVID-19 lockdown and no access to lab from March 2020 – until our graduation from the program.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Transmission Interconnection Roadmap: Transforming Bulk Transmission Interconnection by 2035

The U.S. electricity system is amid a rapidly occurring and widespread energy transition. Regional, Tribal, state, and customer demand for new energy resources, combined with favorable policies, is driving a rapid rise of interconnection requests. Interconnection processes will need to evolve to handle this larger number of requests today and into the future, as policy and economic drivers continue to motivate significant resource development. This roadmap identifies and organizes nearer- and longer-term solutions to enable transmission interconnection processes to meet this expected demand, and it is intended for a diverse audience of stakeholders participating within transmission interconnection processes. The roadmap is a result of the Interconnection Innovation e-Xchange (i2X) program launched by the U.S. Department of Energy (DOE) in June 2022 to convene stakeholders and address interconnection challenges. The roadmap is organized into four primary goal areas, each important to the overall i2X mission to enable a simpler, faster, and fairer interconnection of clean energy resources while enhancing the reliability, resiliency, and security of our electric grid. The first goal aims to improve interconnection data transparency, to aid interconnection customers’ ability to screen and site potential projects, better enable third-party modeling, facilitate more process automation, enhance competition while ensuring equitable outcomes, and enable benchmarking, tracking, and auditing of interconnection processes and reforms. The second goal covers solutions to improve queue management practices, affected system studies, fair processes, and workforce development. The third goal incorporates solutions that aim to improve cost allocation, reduce costs to electricity consumers, enhance the coordination between transmission planning and the interconnection process, and optimize the rightsizing of transmission investment through improvements in interconnection studies. The fourth and final goal aims to reduce the performance issues not identified during interconnection studies by updating technical requirements within interconnection studies, models, and tools while also improving industry interconnection standards.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

E2C Cohort on Major Energy Disruptions in the Southeast: Trade-Offs and Feasibility of Energy Sector Investment for Community Resilience [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Planning for Major Energy Disruptions in the Southeast" focuses on strategies for entities in the Southeast to quickly recover from impacts to energy infrastructure caused by extreme events, such as severe weather and natural disasters. This presentation focuses on the tradeoffs and relative costs of different strategies to improve outcomes from these extreme events. The workshop is on May 21, 2026.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Developing Separate Effects Transient Test Experiments Using an Out-of-Pile Flowing Water Loop

In 2017 the Transient Reactor Test Facility was restarted after being placed in a standby state since 1994. This Test Reactor’s restart has since enabled the progressive development of new nuclear technologies within the U.S. that were previously required to outsource to other countries. While the reactor’s restart was a large feat worthy of recognition, the experimental use of its characteristics has required the further development of in-pile experimental infrastructure sufficient to support programmatic needs. This hardware have taken the form of capsule designs (compact and elongated) as well as loop concepts representing the phenomena of interest for a subset of separate effects tests desire for each respective testing campaign. The Transient Testing Program has a large-integrated effort that aligns with the U.S. Department of Energy’s current needs. This study compliments those programmatic elements by developing, fabricating and demonstrating a full-scale flowing water loop in an out-of-pile environment. The goal of this effort is to develop a pragmatic understanding of the engineering capabilities and limitations associated with geometric form-factors, metering technology, and controls logic under representative thermal hydraulic conditions that would be experienced within the TREAT reactor during an in-pile reactivity initiated accident test. The outcomes of this study result in an evaluation of the conceptual design of a comprehensive flowing water loop including objective figures of merit (FoMs) for comparing unique instrumentation and the basis for their selection during operations. These efforts directly contribute to and are required for the further advancement of transient testing capabilities within the U.S.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Molten Salt Reactor Signatures and Modeling Study

Molten salt reactor (MSR) technologies, either liquid fueled and cooled or only liquid cooled, pose specific, unique challenges for safeguards of the special nuclear material during the operation, fueling, and maintenance of the reactor. MSRs are one type of Generation IV technologies being invested in and considered for U.S. domestic fabrication primarily for electricity and process heat production. These designs have generated growing commercial interest for several reasons, including high (≈40%) thermal efficiency, ease of fueling, improved use of uranium fuel, potential utilization of thorium fuel, and proposed inherent safety features. U.S. companies have several planned designs that differ in fuel, cooling, and neutron energy spectrum. Driven by commercial interest and the intent of licensing MSRs, the U.S. Nuclear Regulatory Commission (NRC) has developed a vision and strategy to accommodate non-light water reactors (LWR), which include MSRs (U.S. Nuclear Regulatory Commission 2019). In addition, the Department of Energy (DOE) through the Office of Nuclear Energy (NE) Office of Advanced Reactor Technologies (ART), …sponsors research, development and deployment (RD&D) activities through its Next Generation Nuclear Plant (NGNP), Advanced Reactor Concepts (ARC), and Advanced Small Modular Reactor (aSMR) programs to promote safety, technical, economical, and environmental advancements of innovative Generation IV nuclear energy technologies. Reactor types considering the use of salts, liquid metals, or gases for coolant fall under both ARC and aSMR. Therefore, Research Design & Development is being pursued by DOE-NE through national laboratories, universities, and international and industrial collaborations. Additionally, the U.S. is a member of the Gen IV International Forum (GIF). The GIF is a cooperative, multinational organization to guide and carry out research and development needed for the GEN IV reactor systems (Forum 2018). GIF evaluated numerous reactor concepts and down-selected to the six most feasible advanced reactor technologies: gas-cooled fast reactor (GFR), lead-cooled fast reactor (LFR), MSR, supercritical watercooled reactor (SCWR), sodium-cooled fast reactor (SFR), and very high temperature reactor (VHTR). In support of the growing interest domestically and internationally, the Materials Protection, Accounting, and Control Technologies (MPACT) campaign, under the DOE-NE Fuel Cycle Technologies (FCT) program, engages in R&D activities by developing advanced instrumentation and analysis for safeguards and security of modern, advanced nuclear fuel cycle (non-LWR) facilities. Because of the historic experience in the operation of the Aircraft Reactor Experiment (ARE) and the Molten Salt Reactor Experiment (MSRE) (Robertson, MSRE Design and Operations Report Part I 1965), Oak Ridge National Laboratory (ORNL) is heavily engaged in the various R&D activities through the DOE complex related to MSRs including national technical leadership of the DOE-NE MSR campaign. This report discusses and presents the outcomes of the FY19 MPACT MSR Safeguards task. The challenges presented by MSRs for nuclear material accountancy and control (NMAC) and associated safeguards will be investigated. The objective of this research is to explore and compile the safeguards requirements and identify measurement signatures through an initial high-level MSR design and develop complementary advanced simulation and modeling capabilities. A high-level ORNL-developed MSR design called the Molten Salt Demonstration Reactor (MSDR) (Bettis, Alexander and Watts 1972) was used as the target reactor design for this research. The MSDR model incorporates technology from the MSRE and the Molten Salt Breeder Reactor (Robertson, Conceptual Design of a Single-Fluid Molten-Salt Breeder Reactor 1971). But the MSDR is a 750 MWth graphite moderated liquid fueled (low-enriched uranium) MSR compared to the MSRE’s of 7.5 MWth. The focus of this report is to discuss the evaluation of novel signatures, correlations, and indicators to understand the applicability of current safeguards instrumentation to MSRs using the modeling results from the MSDR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Energy Technology Innovation Partnership Project Strategic Energy Plan for Washington County, Maine

This Strategic Energy Plan (SEP) for Washington County, Maine was developed through the U.S. Department of Energy's Energy Technology Innovation Partnership Project (ETIPP) to address local challenges related to electricity reliability, affordability, and safety. Grounded in a "relational infrastructure" approach, the plan recognizes that improved energy outcomes depend not only on physical grid investments but also on strengthened coordination and trust between utilities and communities. Using utility-provided reliability data, public datasets, and community input, the plan identifies key risks, including vegetation-related outages, high energy burden, and vulnerability among elderly and medically dependent populations. The SEP establishes three priority areas: hazard mitigation for energy infrastructure, outage safety and emergency readiness, and energy assistance and thermal safety. It outlines community-driven actions designed to complement utility-led system improvements, including targeted outreach, municipal coordination, and expanded access to energy programs. The plan also situates local conditions within broader state policy, market dynamics, and funding opportunities. Intended as a living document, this SEP provides a scalable framework for collaborative action to improve resilience, safety, and affordability in rural energy systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Evaluating Multimodel Ensemble Seasonal Climate Forecasts on Rangeland Plant Production in the California Annual Grassland

Seasonal precipitation and temperature directly affect total plant production in the California Annual Grassland (CAG). Technological advances have resulted in skillful seasonal climate forecasts (i.e., significant correlations between actual and forecasted climate), which could be input into plant production models to inform stocking and other rangeland management decisions. This study presents a procedure for forecasting plant production in the CAG ecosystem to predict annual plant production for grazing, restoration, or other rangeland management practices using a combination of historical gridMET climate data and seasonal hindcasts (i.e., retrospective forecasts, from the North American Multi-Model Ensemble program). Further, the results of this study first confirmed high forecast skill, throughout the growing season at all sites. We also identified skillful plant production forecasts across most of the growing season at two sites and in three of the seven forecasting months at one study site. Forecasting climate and end-of-year plant production across the growing season at three CAG sites allowed us to identify the places and times in the growing season when forecasting might be most helpful in informing management decisions. Integrating plant production forecasting into rangeland management practices could significantly improve rangeland management outcomes. These procedures provide a user guide for creating plant production forecasts for any given area of interest and may be applicable across a wide range of other agricultural and rangeland management systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

FrESCO

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information and summary statistics about cancer prevalence to facilitate population level monitoring of cancer incidence. Extracting cancer phenotype from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating this information extraction process from cancer pathology reports has the potential to improve not only the quality of the data by extracting information in a consistent manner across registries, but to improve the quality of patient outcomes by reducing the time to assimilate new data and enabling time-sensitive applications such as precision medicine. Here we present FrESCO: Framework for Exploring Scalable Computational Oncology, a modular deep-learning natural language processing (NLP) library for extracting pathology information from clinical text documents.

Spannaus, Adam [Oak Ridge National Lab. (ORNL), Oa↗
DOE OSTI2023

FrESCO: Framework for Exploring Scalable Computational Oncology

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information from electronic health records. This data is then used to create summary statistics about cancer incidence and mortality to facilitate population health monitoring. Extracting phenotypic information from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating the information extraction process from cancer pathology reports has the potential to improve data quality by extracting information in a consistent manner across registries. It can also improve patient outcomes by reducing the time from diagnosis, enabling rapid case ascertainment for clinical trials. Here we present FrESCO, a modular deep-learning natural language processing (NLP) library initially designed for extracting pathology information from clinical text documents. This repository is not solely limited to clinical medical text, but may also be used by researchers just getting started with NLP methods and those looking for a robust solution for their classification problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

LA100 Equity Strategies

In the Los Angeles 100% Renewable Energy Study (LA100), the National Renewable Energy Laboratory (NREL) found that the City of Los Angeles can achieve its ambitious goal of reliable, 100% carbon-free energy as early as 2035. While all communities will benefit from air quality and health improvements of clean energy, improving equity in participation and outcomes requires intentionally designed equity strategies. To plan for a clean energy future that benefits all Angelenos, the Los Angeles Department of Water and Power (LADWP), NREL, and the University of California Los Angeles (UCLA) partnered on the LA100 Equity Strategies project. In an innovative, community-informed approach, the LA100 Equity Strategies project integrated robust social science research techniques with rigorous data analysis - and incorporated what community members themselves know is needed to achieve a more equitable energy future. The team developed effective strategies for engaging communities, funding equitable technology and infrastructure investments, expanding existing clean energy and energy assistance programs, and designing new programs and policies to enhance equity.

community↗
DOE OSTI2020

Examining the Net Revenue and Downstream Flow Impact Trade-Offs for a Network of Cascading, Small-Scale Hydropower Facilities: Preprint

In this work, we used a price-taker model to investigate the trade-offs between net revenue and downstream flow impacts for a network of small, cascading hydro facilities. The network consisted of 36 facilities, each with a small amount of local storage (between 2 and 45 minutes). Generator sizes ranged between 0.5 and 1 MW, nominal, and the total capacity of the network was 33.5 MW. We used a multi-integer linear programing model to maximize the net revenue of the combined network subject to operating and environmental constraints. Net revenue optimizations relied on historic price data, and dry, typical, and wet years were studied to help ensure robustness. Energy and ancillary service sales were included in the net revenue calculations, and both unit commitment and dispatch simulations were performed. We found that limiting the downstream flows to ±50% of the river’s natural flows had a negligible impact on net revenues (<1% reduction), irrespective of hydrologic conditions, and even when downstream flows were limited to ±5%, net revenues were only impacted by 4%. These outcomes are significant because they demonstrate how an array of small-scale hydropower facilities can be operated to have minimal impact on natural stream flows—addressing a critical environmental concern.

downstream flow↗
DOE OSTI2023

MCNP6 Developments: A 2022-23 Year in Review [Slides]

A separate MCNP6.3 V&V document reports on all the default calculations for all test suites is touched on. This report does not include the subcritical multiplication benchmark suite. After some additional clean-up and finalizing the post-processing and documentation steps, the subcritical multiplication benchmark suite will be released in the next version of our vnvstats repository. We tested the new HDF5 PTRAC feature in MCNP6.3 and found encouraging outcomes. Identical results coming out of the simulation with respect to the legacy PTRAC results. The overall runtime for all simulations is reduced by ~20% with the new HDF5 PTRAC capability. We consider giving the new HDF5 PTRAC features a try and using it for all subcritical multiplication and any other relevant (PTRAC) calculations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

COMMISSIONING RESULTS OF THIRD C75 CRYOMODULE FOR CEBAF

The program to upgrade CEBAF cryomodules has been implemented to enhance the energy gain of refur-bished cryomodules up to 75 MeV. This strategy in-volves reusing the waveguide end-groups from original CEBAF cavities produced in the 1990s, and existing five elliptical cell cavities are replaced with a new optimized cell shape cavity constructed from large-grain, ingot Nb material. Following fabrication, each cavity undergoes centrifugal barrel polishing and electropolishing and is tested at 2.07 K. Eight cavities are then assembled into "cavity pairs" and tested at 2.07 K before integration into the cryomodule. This paper pre-sents the outcomes of the cavity qualification for the third C75 module, providing a detailed account of the assessment in both a vertical cryostat and the acceptance test results of the cryomodule. Furthermore, efforts have been made to address performance limitations arising from field emission and multipacting

Senevirathne, I.↗
DOE OSTI2025

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗
DOE OSTI2022

Evaluation of artificial neural network performance for classification of potato plants infected with potato virus Y using spectral data on multiple varieties and genotypes

Potato virus Y (Potyviridae, PVY) is a plant virus that poses a significant threat to potato producers on a global basis. The pathogen has disrupted seed potato supplies and negatively impacted yield and quality of commercial potato crops. The potato industry currently manages PVY infection levels via insecticide applications, regional seed certification programs that rely on field scouting to visually assess individual plants for infection status, and destructive and costly tissue sampling coupled with laboratory assays. Despite these efforts, PVY continues to confound potato industry stakeholders resulting in economic harm. Remote sensing and machine learning provide for the development of new tools to more accurately detect and spatially quantify PVY-infected plants versus the current state of the art. However, there is a need to understand how the occurrence of many different potato varieties impact the dynamics of developing models to detect potato plants impacted with PVY and their potential effectiveness. This study evaluates classification modelling outcomes using spectral datasets collected in different temporal and spatial environments (greenhouse and a production field) on multiple potato varieties consisting of labelled instances of plants infected with PVY and those not infected with the virus. A modelling framework was developed to support iterative modelling runs using artificial neural network (ANN) architectures configured as binary classifiers to develop sample populations to support statistical analysis on model performance using specific spectral subsets. When using spectral data to detect PVY-infected plants, ANN models achieved the highest mean accuracy of 0.894 on a single variety. Conversely, the same ANN model architecture only achieved a mean accuracy of 0.575 on a spectral data set representing 29 potato breeding lines. Additionally, statistical analysis indicates spectral regions including the red edge, near infrared and shortwave infrared contain more important spectral features for the ANN classifier introduced in this research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Weak lensing in DES Y3: redshift distributions, shape catalogue, and mass mapping

The size of galaxy surveys have rapidly escalated with time, growing from thousands of galaxies of the first pioneering surveys to current and future surveys (DES, KiDS, HSC, LSST, Euclid, WFIRST), which map (or plan to map) a few hundreds millions of galaxies. These ambitious programs have the potential to answer many open questions in Cosmology (or, depending on their results, to open new exciting scenarios, involving new physics beyond the standard cosmological model and the standard model of particle physics). In particular, this thesis focuses on the first three years of data from the Dark Energy Survey (DES Y3), which comprises 100 million galaxies observed in 5 different optical bands over 5000 square degrees of the southern hemisphere. DES and the data set used in this thesis are discussed in detail in Chapter 3, which together with Chapter 1 and 2 constitutes Part I of this thesis. The scientifically positive outcome of DES and other photometric galaxy surveys goes h and in h and with a supreme understanding of the data, of the observational systematics affecting the measurements, and of the limits of the theoretical modelling of the observables. One of the main challenge of galaxy photometric surveys like DES is to correctly estimate the distance to the galaxies. Photometric surveys observe the galaxies in a limited number of broad optical bands, and the estimate of their \textit{redshifts} is somewhat uncertain, which constitutes one of the main limiting factor of their cosmological analyses. Part II and its Chapter 4 are devoted to a new auxiliary technique recently developed that allows to infer (or calibrate) redshift distributions exploiting cross-correlation with small reference samples with secure redshifts. The so called ``clustering-redshift'' method is discussed in depth, as well as its role in the overall DES Y3 redshift calibration strategy. Part III and Chapter 5 are devoted to another key aspect of photometric surveys, that enables the stu dy of weak gravitational lensing: the shape catalogue. The official DES Y3 shape catalogue is presented, together with all the systematic tests performed to validate it such that it can be considered science-ready. Last, part IV focuses on how to use weak gravitational lensing and the DES Y3 shape catalogue to create weak lensing mass maps, i.e., maps of the mass distribution of the Universe. Chapter 6 discusses different map making techniques, whereas Chapter 7 presents a simulated cosmological analysis using the high order moments of the mass maps.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Field Validation of MVA Technology for Offshore CCS: Novel Ultra-High-Resolution 3D Marine Seismic Technology (P-Cable) (Final Report)

The objectives of the proposed study were to deploy and validate a specific monitoring technology, high-resolution 3D marine seismic (HR3D), appropriate for large-demonstration and commercial-scale offshore CCS sites. The project accomplished successful acquisition two HR3D seismic surveys. The first HR3D dataset was over the offshore injection site of the Tomakomai, Japan integrated pilot CCS project, which at the time of survey acquisition was actively injecting CO 2 . The first survey also represented a successful international collaboration between the DOE NETL program and Japan’s national CCS program and was the first successful acquisition and use of HR3D over an active CO 2 injection site (Meckel, Feng et al. 2019). The Tomakomai HR3D survey successfully tested a novel 4-streamer HR3D system array in which, for the first time, no cross-cable (aka “P-Cable”) was utilized and only four GeoEel streamers were used instead of the standard 12-streamer configuration. Consequently, this was not, strictly speaking, a deployment of the “P-Cable” system of (Planke and Berndt 2004) but rather a modified version, thereof, and it is the first known demonstration of the modified system configuration. One very positive outcome from the Japanese collaboration earlier in the project was the ability to learn from the Japanese how they used tail buoys with GPS to determine the position of the seismic source and receivers in time and space. Based on that experience, GCCC designed and built six GPS receivers that could be used to position the streamer receivers and the seismic source via tail buoys. A fundamental advance that was made on the original design, was the ability to directly power the tail buoy GPS units and transfer data through the streamers (i.e., vs. the batteries used at Tomakomai). The bulkiness of the GPS batteries caused drag and episodic surging of the buoys, which affected data quality by lifting up the tail end of the streamers so the receivers were not at the same depth. The units were tested onshore for accuracy and functionality, and the design was subsequently and successfully tested in marine acquisition mode during the SLP survey acquisition. The marine acquisition test and survey satisfied Subtasks 2.2.2, Novel Positioning Technology Selection and Subtask 2.2.3, Novel Positioning Technology Deployment. Results of the novel positioning technology selection (Subtask 2.2.2) were considered successful and will be incorporated in future HR3D seismic acquisition projects to reduce costs, improve deployment safety at sea, and integrate both seismic and data recording via a single data transfer through the streamers to the recording system. The project also established a permitting process through NETL NEPA compliance, which included an Environmental Assessment in a marine setting and is required for conducting these types of surveys using Federal funding. The permitting process charted a “boilerplate,” which can allow future surveys related to other funded projects to move forward more expeditiously. Future improvements that could be considered are more robust seals on the GPS module and stronger materials (especially joints) on tail buoy fabrication. These would increase fixed costs, but would be advisable and probably more economic long-term if multiple HR3D surveys are planned. Project Accomplishments include: • Pre-survey Sensitivity Study • Marine geochemistry methods and data analysis • Successful HR3D seismic dataset acquired @ Tomakomai active CO 2 injection marine site • Developed advanced seismic processing techniques • No NRMS anomalies detected in overburden; Demonstration of containment • Repeatability study • Second survey collected @ San Luis Pass, TX • 4D application using positioning techniques developed in the project for monitoring were successful

3D seismic GPS positioning↗