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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Environmental Permitting and Compliance Cost Reduction Strategies for the MHK Industry: Lessons Learned from Other Industries

The marine and hydrokinetic (MHK) industry plays a vital role in the U.S. clean energy strategy by providing a renewable, domestic energy source that may offset the need for traditional energy sources. The first MHK deployments in the U.S. have incurred very high permitting costs and long timelines for deploying projects, which increases project risk and discourages investment. A key challenge to advancing an economically competitive U.S. MHK industry is reducing the time and cost required for environmental permitting and compliance with government regulations. Other industries such as offshore oil and gas, offshore wind energy, subsea power and data cables, onshore wind energy, and solar energy facilities have all developed more robust permitting and compliance pathways that provide lessons for the MHK industry in the U.S. and may help inform the global consenting process. Based on in-depth review and research into each of the other industries, we describe the environmental permitting pathways, the main environmental concerns and types of monitoring typically associated with them, and factors that appear to have eased environmental permitting and compliance issues.

other industries↗
DOE OSTI2020

A Model Tree Generator (MTG) Framework for Simulating Hydrologic Systems: Application to Reservoir Routing

Data-driven algorithms have been widely used as effective tools to mimic hydrologic systems. Unlike black-box models, decision tree algorithms offer transparent representations of systems and reveal useful information about the underlying process. A popular class of decision tree models is model tree (MT), which is designed for predicting continuous variables. Most MT algorithms employ an exhaustive search mechanism and a pre-defined splitting criterion to generate a piecewise linear model. However, this approach is computationally intensive, and the selection of the splitting criterion can significantly affect the performance of the generated model. These drawbacks can limit the application of MTs to large datasets. To overcome these shortcomings, a new flexible Model Tree Generator (MTG) framework is introduced here. MTG is equipped with several modules to provide a flexible, efficient, and effective tool for generating MTs. The application of the algorithm is demonstrated through simulation of controlled discharge from several reservoirs across the Contiguous United States (CONUS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Navigating Epistemic Uncertainty in the Management of Flash Droughts

Abstract: Flash droughts, characterized by their rapid onset, sharply contrast with the typically gradual development of traditional droughts. These events are triggered by a combination of low rainfall and high evaporation rates, driven by elevated temperatures, making them particularly challenging to predict and prepare for. As a relatively new concept, flash drought is not well understood, which introduces significant epistemic uncertainties regarding their nature and detection methods. This under-detection hinders planners' ability to effectively manage these events. Despite these uncertainties, flash droughts can have significant impacts, raising the question: how can decision-makers prepare for such events given the current knowledge gaps? To address this, we propose a methodological framework aimed at enhancing flash drought preparedness by guiding the selection of appropriate indicators based on their detection capabilities and the decision-makers' level of risk aversion. Our approach involves evaluating six different flash drought indicators and analyzing the level of agreement among them. Additionally, we consider the decision-makers' risk aversion, distinguishing between those who require consensus across all methods (risk-takers) and those who act based on a single method's indication (risk-averse). The insights gained from this study offer a pathway towards more informed decision-making processes regarding flash droughts, potentially mitigating their adverse effects through better preparedness and response strategies.

climate resilience↗
DOE OSTI2020

HVAC End-of-Life: Options and Best Practices

When heating, ventilating, and air-conditioning (HVAC) systems reach end-of-life status, building owners typically seek the quickest, most cost-effective replacement. Although there are several rooftop unit (RTU) replacement tool kits and programs to guide clients through this process, there is limited information on how to handle end-of-life HVAC systems. This fact sheet provides relevant information to help building owners manage proper disposal of HVAC systems, how to navigate regulations, and how to recover economic value from old systems.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

40th Eastern Regional Photosynthesis Conference

Photosynthesis has shaped global biochemistry and geochemistry in its production of almost all atmospheric oxygen, and almost every electron that supports the processes of life on Earth was extracted from water by the light-dependent reactions, many of which were then used to fix carbon in the dark reactions. To humans, that fixed carbon is the originator of all fossil fuels and a critical step in conversion of solar photons to human-usable energy. The Eastern Regional Photosynthesis Conference (ERPC) serves as a forum for advancement of science in this field. As a regional-level conference, it specializes in providing developmental opportunities for early-career researchers from undergraduates to pre-tenure professors, as well as broadening the field in terms of participating scholars and research approaches to produce new interdisciplinary collaborations. Funding from the Department of Energy is used to mitigate registration and attendance costs for junior (non-PI) researchers. The ERPC is one of the three regional conferences in the field of photosynthesis research in the United States, alongside the Western Photosynthesis Conference (currently in California) and the Midwestern Photosynthesis Conference (Turkey Run, Indiana). A longstanding incubator for scientific discourse, discovery, and collaborations, this conference has spawned many collaborations which led to Department of Energy-funded projects and brought two full generations of scientists into the field. In 2023 the landmark 40th such conference was held at the Woods Hole Marine Biological Laboratory in Massachusetts. The conference was held April 14th-16th, 2023. The majority of the total attendees are traditionally undergraduates, graduate students, and postdoctoral researchers, whose scientific development greatly benefits from conferences like these. Almost all talks besides the ones given by invited speakers were given by young scientists who benefited from this award. Many posters presented at this conference were also the work of junior scientists. This conference is many young scientists' first exposure to the photosynthesis research community and its primary goal is to provide a positive atmosphere for those attendees, as exemplified by the three poster sessions and dedicated interactions between senior and junior scientists. Additionally, this was the first year of a successful equitable outreach and speaker recruitment plan to provide fair representation at the conference in line with Department of Energy policies and mission. The central focus of the ERPC is the understanding of energy flow from photons to usable chemical products in both natural and artificial photosynthesis. We support the DOE-BES aim of understanding of the biochemical/biophysical processes of photosynthesis to inform new technology development and field applications. This year’s theme, “Photosynthesis Across Scales,” reflected the scope of work being done from the individual exciton to the crop scale. This research encompasses applied biology, chemistry, physics, and materials engineering. The aim of this conference is to present new discoveries, techniques, and questions which can be sourced from any of these disciplines and provide an audience which is broadly qualified to use or respond to these developments.

08 HYDROGEN↗
DOE OSTI2026

RH-TRU Waste Streams: HFDA Crucibles Create New Complex Waste Stream

This project focuses on the removal of the Hot Fuel Dissolution Apparatus (HFDA) crucibles from the Hot Fuel Examination Facility’s (HFEF) hot cells to create space for upcoming projects. The project team has created a crucible and pyro-salt non-debris waste stream that can be disposed of at Waste Isolation Pilot Plant (WIPP). Chemical Compatibility Examinations (CCEs) must be performed on candidate waste by reviewing the types of chemicals used in the experiments, information found in INL Process Knowledge Summary Reports (PKSRs), and Environmental Protection Agency guides on chemical compatibility. The CCEs identify which chemicals can be safely combined to ensure adverse reactions do not occur in the waste packages. The CCEs are then used to update the PKSR, Basis of Knowledge, and Acceptable Knowledge documents and demonstrate compliance with the WIPP Waste Acceptance Criteria. Once documents are finalized, they are reviewed and approved by the WIPP Central Characterization Project (CCP) to ensure proper waste stream characterization. After the documents are approved, the crucibles can be packaged and shipped to the Idaho Nuclear Technical and Engineering Center for storage awaiting certification. CCP will certify the waste using the approved documents and a series of confirmatory testing before being shipped and disposed in WIPP’s deep geological repository. Currently, the CCE is in progress and the PKSRs are being updated.

Basis of Knowledge↗
DOE OSTI2021

Time-of-Flight Estimation for Nondestructive Evaluation

Ultrasonic testing (UT) for nondestructive evaluation (NDE) is a critical entity necessary to resolve both the quality and precision questions of complex parts evolving from the classical approaches to the innovative additive manufacturing (AM) process. This modality provides the essential quantitative information for acceptance and potential flaw detectionof apart under investigation. A primary ingredient in UT besides the required precision robotic hardware for theacquisition of high-qualitymeasurement data is the underlying signal processing. It is here that much of the system performance capability resides. In this report,we discuss the basic steps in UT signal processing along with current capabilities that must be achieved in order to satisfy the criticaldemands of the various LLNL programs.In itsbasic foundations, signal processing is essentially the “extraction of critical information (signals) from noisy, uncertain data.” Clearly, in a perfect world the best signal processing is none---just make a reliable, noise-free, uncertainty-free, measurement. Unfortunately, even the best of systems is still straddled within the confines and limitations of physical instrumentation. With this in mind, we discuss the development of signal processing techniques toextract the desired UT information from noisy measurement data. We start with a discussion of a simple homogeneous representation of a “part” under investigation and its insonification by an ultrasonicexcitation from a physics-based perspective. Once developed, we briefly discussthe various choices of excitation signals and their tradeoffs.Next,we discuss a simulation approach employing simple models from the signal processing perspective and then move on to the development of the basic signal processing approach to ultrasonic signal processing all based on estimating the pulse arrival estimation. Starting with simple peak detection techniques, progressing to the processing workhorse so-called “matched-filter” and finally to the more sophisticated “model-based matched filter.”The underlying pre-and post-processing of noisy measurement data along with the application of these techniques are subsequently demonstrated on experimental ultrasonic data.Finally, we present some results for processing “weld” data when the ultrasonic excitation signal is not directly available.

42 ENGINEERING↗
DOE OSTI2024

PhysBERT: A text embedding model for physics scientific literature

The specialized language and complex concepts in physics pose significant challenges for information extraction through Natural Language Processing (NLP). Central to effective NLP applications is the text embedding model, which converts text into dense vector representations for efficient information retrieval and semantic analysis. In this work, we introduce PhysBERT, the first physics-specific text embedding model. Pre-trained on a curated corpus of 1.2 × 106 arXiv physics papers and fine-tuned with supervised data, PhysBERT outperforms leading general-purpose models on physics-specific tasks, including the effectiveness in fine-tuning for specific physics subdomains.

Hellert, Thorsten (ORCID:0000000227970926)↗
DOE OSTI2023

Ocean Mesoscale and Frontal-Scale Ocean–Atmosphere Interactions and Influence on Large-Scale Climate: A Review

Two decades of high-resolution satellite observations and climate modeling studies have indicated strong ocean–atmosphere coupled feedback mediated by ocean mesoscale processes, including semipermanent and meandrous SST fronts, mesoscale eddies, and filaments. The air–sea exchanges in latent heat, sensible heat, momentum, and carbon dioxide associated with this so-called mesoscale air–sea interaction are robust near the major western boundary currents, Southern Ocean fronts, and equatorial and coastal upwelling zones, but they are also ubiquitous over the global oceans wherever ocean mesoscale processes are active. Current theories, informed by rapidly advancing observational and modeling capabilities, have established the importance of mesoscale and frontal-scale air–sea interaction processes for understanding large-scale ocean circulation, biogeochemistry, and weather and climate variability. However, numerous challenges remain to accurately diagnose, observe, and simulate mesoscale air–sea interaction to quantify its impacts on large-scale processes. This article provides a comprehensive review of key aspects pertinent to mesoscale air–sea interaction, synthesizes current understanding with remaining gaps and uncertainties, and provides recommendations on theoretical, observational, and modeling strategies for future air–sea interaction research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Convoluted filtering for process cycle modeling

Principles of materials science and engineering, physics, mathematics, and information science are used to extract knowledge and insights from the process-structure–property-performance relationships hidden in materials data. The process-structure modeling can be accelerated without loss of interpretability, with artificial intelligence tools that mimic the salient features of the process and process-structure relations. In this work, a novel convoluted model-filtering technique was exploited to build and successfully train the Convoluted Filter (CoFi) artifacts for Fe-based alloy heat treatment cycles. The artifacts were pre-trained to filter out deep models that change the surrogate microstructure state after the heat treatment at ambient conditions. Direct representation of the thermal cycle features within knowledge Graph facilitated development of meaningful data models for microstructure evolution, which reduce overfitting to limited datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2020

What can we learn from N 2 O isotope data? – Analytics, processes and modelling

The isotopic composition of nitrous oxide (N 2 O) provides useful information for evaluating N 2 O sources and budgets. Due to the co–occurrence of multiple N 2 O transformation pathways, it is, however, challenging to use isotopic information to quantify the contribution of distinct processes across variable spatiotemporal scales. Here, we present an overview of recent progress in N 2 O isotopic studies and provide suggestions for future research, mainly focusing on: analytical techniques; production and consumption processes; and interpretation and modelling approaches. Comparing isotope–ratio mass spectrometry (IRMS) with laser absorption spectroscopy (LAS), we conclude that IRMS is a precise technique for laboratory analysis of N 2 O isotopes, while LAS is more suitable for in situ/inline studies and offers advantages for site–specific analyses. When reviewing the link between the N 2 O isotopic composition and underlying mechanisms/processes, we find that, at the molecular scale, the specific enzymes and mechanisms involved determine isotopic fractionation effects. In contrast, at plot–to–global scales, mixing of N 2 O derived from different processes and their isotopic variability must be considered. We also find that dual isotope plots are effective for semi–quantitative attribution of co–occurring N 2 O production and reduction processes. More recently, process–based N 2 O isotopic models have been developed for natural abundance and 15 N–tracing studies, and have been shown to be effective, particularly for data with adequate temporal resolution. Here, despite the significant progress made over the last decade, there is still great need and potential for future work, including development of analytical techniques, reference materials and inter–laboratory comparisons, further exploration of N 2 O formation and destruction mechanisms, more observations across scales, and design and validation of interpretation and modelling approaches. Synthesizing all these efforts, we are confident that the N 2 O isotope community will continue to advance our understanding of N 2 O transformation processes in all spheres of the Earth, and in turn to gain improved constraints on regional and global budgets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Spatial and Temporal Interpolation Analysis Process of Shock Loading

The following document serves to describe the current process that is utilized by W-13 analysts to approximate the pressure-time boundary condition seen by a test object from shock tube loading. The intent of this report is to capture the current capability and to encourage continued growth and development. Information on the required input variables, mapping process, and generated output information is covered in the following sections. Throughout the document, gaps and weaknesses of the mapping process are noted to encourage future development efforts.

42 ENGINEERING↗
DOE OSTI2020

Measuring Biomass-Derived Products in Biological Conversion and Metabolic Process

Biomass can be converted to various types of products in biological and metabolic processes. For an in-depth understanding of biomass conversion, quantitative and qualitative information of products in these conversion processes are essential. Here we introduce analytical techniques including high-performance liquid chromatography (HPLC), gas chromatography (GC), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR) for biomass-based products characterization in biological and metabolic processes.

Yoo, Chang Geun↗
DOE OSTI2022

BioGeoChemistry at Interfaces (LLNL SFA OBER FY22 Program Management and Performance Report)

The focus of the BioGeoChemistry at Interfaces SFA is to identify and quantify the biogeochemical processes and the underlying mechanisms that control actinide mobility in an effort to reliably predict and control the cycling and migration of actinides in the environment. The research approach includes: (1) Field Studies that capture actinide behavior on the timescale of decades (Research Thrust 1), and (2) Fundamental Laboratory Studies that isolate specific biogeochemical processes observed in the field (Research Thrust 2). These Research Thrusts are underpinned by the unique capabilities and staff expertise at Lawrence Livermore National Laboratory, allowing the BioGeoChemistry at Interfaces SFA to advance our understanding of actinide migration behavior in the environment, and serve as an resource for environmental radiochemistry research internationally. In the past year, our greater focus on transient redox gradients across stratified waters, sediment-water interfaces, and mineral-water interfaces extended our research beyond actinides to address processes controlling cycling of redox-sensitive metals more broadly. Nevertheless, Research Thrusts 1 and 2 are guided by the following broad central hypotheses that were developed during our last program review held at the end of FY18: Thrust 1 Hypothesis: Biogeochemical processes occurring on the timescale of years to decades lead to greater actinide recalcitrance in sediments and limits their migration in surface and groundwater. Thrust 2 Hypothesis: Long-term biogeochemical processes include mineral and surface alteration, which leads to stabilization of actinide surface associations or incorporation into mineral precipitates. Our strategic goal is to use the knowledge gained from our Science Plan to advance our understanding of the behavior of actinides and other radionuclides (e.g. Cs) and provide DOE with the scientific basis for remediation and long-term stewardship of DOE’s legacy sites. More broadly, we will enhance our understanding of transport phenomena in environmental systems sciences with a particular emphasis on environmentally relevant (long-term) timescales. While we retain our focus on actinide biogeochemistry, our increased focus on overall biogeochemical processes occurring at unique Test Bed locations associated with this SFA provides fundamental information on abiotic and biotic redox processes that control the cycling of redox sensitive metals under dynamic and transient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

LLNL SFA OBER FY23 Program Management and Performance Report: BioGeoChemistry at Interfaces

The focus of the BioGeoChemistry at Interfaces SFA has been to identify and quantify the biogeochemical processes and the underlying mechanisms that control actinide mobility in an effort to reliably predict and control the cycling and migration of actinides in the environment. The research approach has included: (1) Field Studies that capture actinide behavior on the timescale of decades (Research Thrust 1), and (2) Fundamental Laboratory Studies that isolate specific biogeochemical processes observed in the field (Research Thrust 2). These Research Thrusts are underpinned by the unique capabilities and staff expertise at Lawrence Livermore National Laboratory, allowing the BioGeoChemistry at Interfaces SFA to advance our understanding of actinide migration behavior in the environment, and serve as a resource for environmental radiochemistry research internationally (Figure 1). In FY23, our SFA research focused on transient redox gradients across stratified waters, sediment-water interfaces, and mineral-water interfaces to address processes controlling cycling of redox-sensitive metals. Nevertheless, Research Thrusts 1 and 2 are guided by the following broad central hypotheses that were developed during our last program review held at the end of FY18: Thrust 1 Hypothesis: Biogeochemical processes occurring on the timescale of years to decades lead to greater actinide recalcitrance in sediments and limits their migration in surface and groundwater. Thrust 2 Hypothesis: Long-term biogeochemical processes include mineral and surface alteration, which leads to stabilization of actinide surface associations or incorporation into mineral precipitates. Our strategic goal is to use the knowledge gained from our Science Plan to advance our understanding of the behavior of actinides and other radionuclides (e.g. Cs) and provide DOE with the scientific basis for remediation and long-term stewardship of DOE’s legacy sites. More broadly, we are improving our understanding of transport phenomena in environmental systems sciences with a particular emphasis on environmentally relevant (long-term) timescales. While we retained some of our historical focus on actinide biogeochemistry this past fiscal year, biogeochemical processes occurring at unique Test Bed locations associated with this SFA provide fundamental information on abiotic and biotic redox processes that control the cycling of redox sensitive metals under dynamic and transient conditions. Furthermore, in collaboration with SFA teams at Argonne National Laboratory, our SFA has begun to transition away from the current research focus and develop a new research program in terrestrial wetland systems. The Terrestrial Wetland Function and Resilience SFA program plan will be delivered to the Environmental System Science (ESS) program within BER at the end of FY23.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Biogeochemical dynamics and microbial community development under sulfate- and iron-reducing conditions based on electron shuttle amendment

Iron reduction and sulfate reduction are two of the major biogeochemical processes that occur in anoxic sediments. Microbes that catalyze these reactions are therefore some of the most abundant organisms in the subsurface, and some of the most important. Due to the variety of mechanisms that microbes employ to derive energy from these reactions, including the use of soluble electron shuttles, the dynamics between iron- and sulfate-reducing populations under changing biogeochemical conditions still elude complete characterization. Here, we amended experimental bioreactors comprised of freshwater aquifer sediment with ferric iron, sulfate, acetate, and the model electron shuttle AQDS (9,10-anthraquinone-2,6-disulfonate) and monitored both the changing redox conditions as well as changes in the microbial community over time. The addition of the electron shuttle AQDS did increase the initial rate of Fe III reduction; however, it had little effect on the composition of the microbial community. Our results show that in both AQDS- and AQDS+ systems there was an initial dominance of organisms classified as Geobacter (a genus of dissimilatory Fe III -reducing bacteria), after which sequences classified as Desulfosporosinus (a genus of dissimilatory sulfate-reducing bacteria) came to dominate both experimental systems. Furthermore, most of the ferric iron reduction occurred under this later, ostensibly “sulfate-reducing” phase of the experiment. This calls into question the usefulness of classifying subsurface sediments by the dominant microbial process alone because of their interrelated biogeochemical consequences. To better inform models of microbially-catalyzed subsurface processes, such interactions must be more thoroughly understood under a broad range of conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Photo- and Electro-Induced Hadron Production from Nuclei at Jefferson Laboratory

Understanding many-body knockout processes is crucial for nuclear physics, particularly in photo- and electro-induced reactions. In turn, understanding two- and three-body forces, including higher-order forces, is vital for a complete understanding of atoms. We present photo-induced many-proton knockout processes, with multiplicities from 1 to 6, using 12C, CH2, and C4H9OH targets in the g9a FROST dataset. Our analysis covers photon energies from 600 to 4500 MeV, significantly expanding current world data. Comparing our experimental data to the state-of-the-art GiBUU model offers a new challenge in the model’s theoretical description of many-body processes. GiBUU reasonably describes the data at lower photon energies but struggles at higher energies and missing masses, likely due to missing processes, such as initial 3-pion photoproduction. Our results will inform future developments in describing proton knockout processes, indicating GiBUU’s overall reasonable description of many-proton knockout data up to around 2.2 GeV. We also assess various electro-induced reactions using 2D, 12C, and 40Ar targets in the RGM dataset. Our results, obtained at electron beam energies of 2, 4, and 6 GeV, are compared in detail to GENIE and GiBUU, two widely used theory models in neutrino oscillation experiments. Discrepancies between model predictions and experimental data underscore the need for refining the two theoretical models. Despite discrepancies, GiBUU provides a more accurate modelling of electro-induced reactions, especially for 40Ar - crucial for future neutrino oscillation facilities such as DUNE. Understanding the fundamental nuclear physics involved in neutrino-nuclei interactions is essential for reducing the systematic uncertainties in extracting neutrino oscillation parameters. Many-body processes significantly contribute to the background processes observed in neutrino-nuclei interactions, hence the results from both analyses are crucial for developing the theoretical framework for the underlying nuclear physics.

Williams, Rhidian↗