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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 OSTI2021

HIPPO – A Software Platform for Electricity Market Research and Development

The goal of this project is to provide Regional transmission organizations (RTOs) and independent system operators (ISOs) a market design and prototyping software, High-Performance Power-Grid Optimization (HIPPO), that they can evaluate electricity market design options, calculate market planning strategies and operational performance. With the high standards and strict reliability requirements for operating power systems, impacts of new technologies need to be fully investigated prior to any consideration for adoption. A market design and prototyping software tool which can be used to prototype electricity market design options, to calculate market planning strategies and operational performance with high precision, and to investigate the impacts for integrating future power grid technologies will be valuable to RTOs/ISOs who operate power systems, to vendors like GE and ABB who provide the market solvers, and to market participants and researchers who are actively doing market research. HIPPO is a such tool that can be used to improve the current market operations and provide capabilities for rigorous forward-looking design and prototyping of next-generation energy markets. HIPPO has a high-resolution model for the day-ahead SCUC, which was validated with MISO and GE-Grid Solutions. HIPPO is built with parallel and distributed computing capabilities and can be executed in both multi-thread and high-performance computing (HPC) settings. This capability provides fast solution speed necessary to handle the larger and more complex SCUC problems of real-world cases and the potentially growing size and complexity of future scenarios. In addition, HIPPO has a concurrent optimizer (CO) which manages multiple algorithm executions simultaneously and leverages the advantages from different algorithms. This structure provides flexibility to better benchmark competing approaches. Highly accurate market model, fast solution technologies and flexible model and algorithm control are the features which will make HIPPO an extensible platform for developing and testing multiple approaches to meet a wide range of future market needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Quantum Enhanced Tracker (Final Report)

A new concept of charged particle detector, called Quantum Enhanced Tracker (QET) is proposed and intended for optical imaging of charged particle tracks. We present a quantum-based detection method for reconstructing the spatial profile of an electron beam by passing it through a dilute vapor of rubidium atoms. The perturbation of the atomic spin’s quantum state by the electron beam’s magnetic field is detected via nonlinear magneto-optical polarization rotation. Consequently, the electron beam’s position, size and current density can be measured, and its transverse profile reconstructed by analyzing the polarization rotation of a transverse probe laser. This method was experimentally studied using e-beams with currents ranging from 1 to 200 μA and energies between 10 to 20 keV. The results show that this approach is sensitive to the e-beam current and independent of e-beam energy. This technique provides a potentially 3-D capable approach for non-invasive characterization and monitoring of charged particles used in accelerators and nuclear physics research.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Multi-phenomenology Yield Characterization

This report serves as the first delivery of a four-year applied science effort to transform and advance the error bounds for the yield estimate of an explosion. Each year’s delivery will be in this form, culminating in the submission of this work for peer review to a scientific journal. Importantly, the yearly progress reports can then also be viewed as expanding drafts working towards a formal journal article submission. For the first tranche of funding, we collaborated with Air Force Technical Applications Center (AFTAC) scientists to identify unclassified real-world data that demonstrate and validate our advanced error propagation methods. Collaboration includes visits to AFTAC and telecons. For this development, we illustrate the fusion of seismic, acoustic, optical, and surface effect signatures from an explosion. The mathematics and code being adapted to this specific application (Williams et al., 2021) involves physics models of multiple sensor signatures. We have also identified related physics models and have integrated them into code. Current methods of underground explosion yield estimation for the Threshold Test Ban Treaty (TTBT) have served the US treaty monitoring mission well for decades. A research objective of the Defense Nuclear Nonproliferation Research and Development (DNN R&D) office of the National Nuclear Security Administration (NNSA) has always been to provide new technical capabilities for monitoring lower thresholds. The general model and error propagation code to be developed in this project is based on significant advances in error modeling and propagation needed to analyze data at lower detection thresholds. The second tranche of funding for this project began on May 1, 2022, and planned work for the second tranche includes: i) completing the integration of physical model code into the general error model framework; this code accommodates a wide range of linear/nonlinear source models, fixed/ random effects, and frequentist/Bayesian analyses (the purpose of which is not to dictate to users how to analyze data, but instead to allow users the maximum flexibility in their work); ii) illustrative application of code to identified data, and; iii) initial planning with AFTAC researchers on delivery of code to the Common Development Environment at AFTAC, and continued writing of the planned final journal article submission (year two of this progress report), with particular emphasis on descriptions of data identified for this effort.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

S4PST: Sustainability for Programming Systems and Tools: May Workshop Report

The US Department of Energy (DOE) Exascale Computing Project (ECP) has fostered and strengthened the use of modern software engineering practices for developing applications and libraries, and this effort has resulted in the coordinated and interoperable E4S1 and xSDK2 ecosystems. Although this approach is cost-effective, it relies on robust programming systems and tools (PST) as the underlying foundation for our HPC software. At present, our primary PST stack consists of traditional high-performance computing (HPC) languages, namely Fortran, C, C++, and the popular Python language for data analysis and AI workflows. These languages support various programming frameworks and run-time abstractions that enable parallelism and concurrency across multiple node architectures and thousands of nodes through a variety of interconnect systems. However, to accommodate users’ diverse needs, certain aspects of the HPC ecosystem are delegated to vendor-specific or third-party implementations that extend beyond a particular scientific domain. This broader scope results in a multitude of specifications and variations, which leads to a complex orchestration of many-ecosystems. Unfortunately, this complexity in the ecosystem imposes additional overhead costs on consumers during the latter stages of the development cycle. In addition to the software ecosystem challenge, the upcoming conclusion of the ECP by December 2023 has raised significant concerns within the HPC programming systems community, from both the economic and social perspectives. The ECP has implemented a management structure for software development and funding decisions across all ECP participants by following a conventional hierarchical and centralized approach. However, this structure has prompted certain considerations within the community, particularly in anticipation of the Software Sustainability initiative by the DOE’s Advanced Scientific Computing Research Program (ASCR). For the success of this new initiative, it is of utmost importance to secure consistent funding and foster close engagement with researchers and core developers of existing programming-system products. This collaboration is vital to maintaining the critical capabilities of the current software during the transition phase while proactively adapting to future technology and workforce trends. The community recognizes the significance of adapting to emerging trends and is aware of the inherent fragility of the HPC software ecosystem, particularly in relation to programming systems that cater to all users. The ability to adapt and evolve is essential to staying relevant and effectively addressing these technical, economic, and social challenges. The S4PST team, which represents one of the six ASCR Software Sustainability seedling projects, is dedicated to tackling these challenges through community-based approaches that go beyond the scope of the DOE. This involves collaboration between national laboratories with academia, non-DOE institutions, hardware and system vendors, and international partners. By fostering these partnerships, we aim to create a robust and sustainable HPC software ecosystem that can effectively meet the needs of the community. This new community effort, driven by the eight DOE labs, will take on the responsibility of guiding funding decisions for programming-systems development and maintenance with transparency and consistency across all decisions. Additionally, the team will offer common technical services to the programming systems community, irrespective of their funding situations, and facilitate community-wide incubation to proactively nurture the software ecosystem. By actively engaging with stakeholders and employing a collaborative approach, we can collectively shape the future of programming systems and ensure a robust and thriving HPC software landscape. On May 11–12, 2023, the S4PST team conducted its inaugural kick-off workshop at the Innovative Computing Laboratory (ICL) in the University of Tennessee, Knoxville, hosted by Hartwig Anzt. The workshop encompassed various sessions dedicated to presentations and discussions, with the aim of comprehending the team members’ perspectives on the vision of software sustainability. Additionally, the workshop aimed to identify the technical, economic, and social requirements for sustaining the programming-systems community in the field of HPC. This report provides a summary of the S4PST effort by highlighting five major thrust areas discussed during the workshop: (i) community, (ii) technical support, (iii) training and diversity, (iv) verification, validation and correctness, and (v) emerging technologies. It also encompasses an overview of the presentations and discussions held throughout the event, our views and potential synergies with other seedling efforts, along with the outcomes and key takeaways from our initial discussions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DECOVALEX-2023: Task F1 Final Report

DECOVALEX-2023 Task F is a comparison of models and methods for post-closure performance assessment (PA) of a deep geologic repository for radioactive waste. The general aims of Task F are to build confidence in the models, methods, and software used for PA and to stimulate additional research and development in PA methodologies. The task objectives are to motivate development of PA modelling skills and capabilities, to examine the influence of model choices on calculated repository performance, and to compare the uncertainties introduced by model choices to other sources of uncertainty. Task F involves no actual experiment or site. It is a PA modelling exercise that requires the conceptual development of hypothetical repository designs and geologic settings. Because three of the teams were interested in salt and the rest of the teams were interested in crystalline rock, Task F was split into two branches: Task F1 for crystalline rock and Task F2 for salt. This report is for Task F1, crystalline rock. Teams from seven countries (Canada, Czech Republic, Germany, Korea, Sweden, Taiwan, and United States) participated in Task F1. The teams worked together to define the features, events, and processes of the reference case repository and established a set of performance measures. In addition, they defined a set of benchmark problems designed to test and compare modelling capabilities for fracture flow and transport at different scales. The repository design and benchmark problems are documented in a Task Specification that evolved over time as the group honed the specifications. The benchmark problems verified that each team can aptly model flow and transport in fractured media in 1-, 2-, and 3-dimensions. Two general approaches were used for the 3-dimensional benchmarks: discrete fracture network (DFN) and equivalent continuous porous medium (ECPM). DFN modelling involves explicit meshing of each fracture while ECPM modelling aims to capture the effective porosity and directional permeability of each cell in a space-filling mesh as affected by intersecting fractures. In some models, a combination of the two is used, i.e., DFN for large known fractures and ECPM for the rest of the domain. Transport is solved by using either the advection-dispersion equation or particle tracking. Although some variation is observed among model breakthrough curves in the benchmark problems, there is strong agreement in breakthrough behaviour up to at least the 75 th percentile for all benchmarks. At the 90 th percentile, breakthrough results show larger differences, suggesting several models retain substantially higher fractions of tracer in regions of slower moving water. In addition to the flow and transport benchmarks, several teams completed the source term benchmark, verifying capabilities for modelling radionuclide decay and ingrowth, waste package breach, instant release fractions, fuel matrix degradation rates, and radionuclide solubility limitations. The reference case is conceptualized as a generic spent fuel repository at a depth of 450 m in fractured crystalline rock. The repository has 50 parallel backfilled drifts, each with 50 deposition holes 6 m apart. Each deposition hole contains a 4-PWR waste package and bentonite buffer. The rock domain is 5 km in length, 2 km in width, and 1 km in depth. It has 6 deterministic fractured deformation zones and a multitude of stochastic fractures. Teams generally used the ECPM approach for the entire rock or a hybrid approach in which the deterministic fracture zones are modelled with a DFN and the rest of the rock is modelled by ECPM. Of the reference case problems specified, only the results of the initial reference case problem are compared in this report. The initial problem focuses on transport from the deposition holes to the surface, i.e., it neglects waste package performance. Tracers are released at all waste package locations at time zero and tracked for their releases to the near field and ground surface. The water fluxes calculated at the ground surface entry and exit regions of the domain are similar for all models except for two that have considerably lower fluxes. For tracer transport, large differences are observed among models in the magnitude of tracer transported. Much of the difference appears to be due to how the repository is implemented and hence the different degrees of repository simplification. Models that exclude the drifts, buffer, and backfill from the domain tend to show greater release of tracers and radionuclides from the repository. The initial study presented here indicates that major differences in modelling important processes within the repository (e.g., diffusion through buffer and backfill) can produce broadly different release and transport results, especially when those processes are excluded. Even for the models that included all specified features, events, and processes, the results show significant differences and demonstrate the importance of examining multiple modelling approaches in performance assessment. The differences in results observed in this study are expected to motivate teams to either increase complexity in future versions of the reference case models or to improve methods to account for the effects of simplified features and processes. Either way, future improvements in these models are expected to produce results that more closely agree.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Leveraging Artificial Intelligence to Predict Novel Eutectic Alloys

The goal of this project was to train an artificial neural network (ANN) to predict the fractional composition and melting point of eutectic alloys using fundamental atomic properties as inputs. The fundamental properties considered include atomic number, atomic weight, atomic radius, valence electron concentration, electronegativity, and electron affinity. The project involved several phases, starting with data preparation, where phase diagram data was harvested from the ASM International database. Approximately 1300 binary eutectics were collected and cleaned to ensure relevance and accuracy. A regression model was selected for training, utilizing a rectified linear unit as the activation function. Various model configurations were evaluated for predictive accuracy, with validation techniques employed to ensure robustness. The model demonstrated predictive capabilities above random guessing and was able to achieve up to 11% accuracy under certain conditions. An ablative test identified atomic radius and valence electron concentration as critical inputs for model performance. Incorporating the melting point of atomic constituents improved accuracy significantly, although ultimately the model’s predictive capability still fell short of the 80% target. This report details the methodology, results, and implications of the research, contributing to the understanding of employing artificial intelligence to predict the phase transition behavior of eutectic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Postdoctoral insights on mentoring excellence: a framework for best practices at Sandia National labs

The Sandia National Laboratories Strategic Plan FY24-FY27, updated for FY25, outlines Sandia’s two Big Labs-wide Goals, Accelerate Innovation and Lead in Modern Engineering. The goal of Accelerate Innovation is that “by FY27, Sandia will be a leader in scientific, engineering and operational innovation and an employer of choice for highly innovative and creative talent.” Sandia’s postdocs are leaders in innovation, well-versed in emerging techniques and cutting-edge methods, and capable of acting as a highly agile technical force across domains at the lab. As a federally funded research and development center (FFRDC), Sandia National Laboratories attracts top doctoral talent by offering a unique opportunity for postdoctoral researchers to develop at the crossroads of government, academia, and industry, working in multi-disciplinary teams and performing cutting-edge, mission-specific research that responds to immediate needs of national interest. However, this creates unique opportunities and demands of both postdoctoral appointees and the Sandia staff who act as their mentors, making mentorship key to attract talent. Since 2007 the Sandia Postdoctoral Development (SPD) Board, originally Postdoc To Professional (PD2P), a networking group at Sandia composed of a voluntary board of current postdocs and two staff liaisons, has advocated for postdoctoral development within Sandia National Labs. In this white paper, SPD board members and the Sandia Postdoctoral Development Office, organized in 2019, have come together to develop a comprehensive overview of the postdoctoral mentoring landscape at Sandia National Labs as we currently know it. By scouring various forms of data from efforts since 2018, we’ve compiled a community-derived perspective on what makes postdoctoral mentorship at Sandia unique. First, we analyze working sessions held between mentors and mentees to develop a comprehensive map of who is involved in postdoctoral mentorship at the lab and how the responsibilities are divided amongst mentors and mentees. We then combine multiple forms of data, including exit surveys, annual surveys, and community workshops, to identify the specific challenges that mentors and mentees encounter at the national lab. Finally, we use text mining and sentiment analysis to analyze mentoring award data to develop an idea of what postdocs are self-identifying as excellent mentorship within the lab. It is our goal that this white paper act as an ongoing resource to the postdoc and postdoc mentoring communities and provide a firm foundation for further conversations on the future of postdoctoral mentorship at Sandia National Labs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Real-Time Simulation of Solid Oxide Electrolyzers (SOEC) for Dynamic Operability Improvement and Cyber-Physical System Development

As more intermittent-renewable generations are being added to the power grid, solid oxide electrolysis cells (SOEC) must enhance their rapid load transition capabilities to load follow and support grid resilience. At NETL, we developed real-time SOEC models to research SOEC transients during load step changes. The gained insights can be useful for dynamic operability improvement. These real-time SOEC models also established the basis for cyber-physical SOEC hybrid energy systems. (Virtual presentation to the 2025 MILLENNIUM CLEAN and SUSTAINABLE POWER workshop, University of Genoa, Italy)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics

A large and ever-growing body of geophysical information is measured in campaigns and at specialized observatories as a part of scientific expeditions and experiments. These collections of observed data include many essential climate variables (as defined by the Global Climate Observing System) but are often distinguished by a wide range of additional non-routine measurements that are designed to not only document the state of the environment but also the drivers that contribute to that state. These field data are used not only to further understand environmental processes through observation-based studies but also to provide baseline data to test model performance and to codify understanding to improve predictive capabilities. To address the considerable barriers and difficulty in utilizing these diverse and complex data for observation–model research, the Merged Observatory Data File (MODF) concept has been developed. A MODF combines measurements from multiple instruments into a single file that complies with well-established data format and metadata practices and has been designed to parallel the development of corresponding Merged Model Data Files (MMDFs). Using the MODF and MMDF protocols will facilitate the evolution of model intercomparison projects into model intercomparison and improvement projects by putting observation and model data “on the same page” in a timely manner. The MODF concept was developed especially for weather forecast model studies in the Arctic. The surprisingly complex process of implementing MODFs in that context refined the concept itself. Thus, this article explains the concept of MODFs by providing details on the issues that were revealed and resolved during that first specific implementation. Detailed instructions are provided on how to make MODFs, and this article can be considered a MODF creation manual.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

MODEL DEVELOPMENT AND VERIFICATION OF A 1,350°C AIR RECEIVER TEST SYSTEM

Open-loop volumetric receivers work with air at atmospheric pressure and are suitable for single-cycle or multicycle power plants. A novel additively manufactured (AM) silicon carbide (SiC), ceramic matrix composite (CMC) volumetric receiver was developed that consisted of a lattice structure, which absorbs solar radiation and converts it into heat energy. Heat energy from the porous receiver was transferred to heated ambient air. The receiver acted as a convective heat exchanger, transferring heat to the fluid through convection. Engineering was facilitated to develop a high-temperature air receiver test bed at Sandia national Laboratories (SNL) capable of demonstrating a 50kWth open-loop volumetric SiC air receiver module developed by General Electric Aerospace Research (GE Aerospace). This paper presents the development of the high temperature AM SiC-CMC air receiver, the test bed, and the first testing operations of this device, which was experimentally demonstrated to achieve 1,350°C for over 3.5 hours of operation, based on input flux levels of 67–91 W/cm2 0.5-2.5 kg/s flow rates. From the test campaign results, based on the measured convective heat transfer to the airflow and bounded radiative-loss assumptions, the solar-thermal efficiency of HOTSSTAR test module was estimated to be approximately as high as 74% for representative test conditions.

14 SOLAR ENERGY↗
DOE OSTI2022

BISON Validation to In-Situ Cladding Burst Test and High Burnup LOCA Experiments

The process to develop and qualify nuclear fuels for commercial nuclear application requires fundamental material development, characterization, and design; out-of-pile testing on unirradiated materials; integral fuel rod irradiations, testing, and post irradiation examinations (PIEs); and transient analyses. The historical approach depends on the generation of large empirical datasets and series of integral fuel rod irradiations, and this approach ultimately takes approximately 20 years—or sometimes longer—to acquire data through extensive sequential testing. Thus, the qualification and eventual deployment of new fuel systems constitute a long and drawn-out process. However, recent technological advancements have provided researchers the opportunity to perform out-of-cell, in-situ measurements to assess material performance for the duration of the experiment. One such example of this capability is the use of digital image coordination and thermal imaging to assess Zircaloy cladding performance under a simulated loss-of-coolant accident (LOCA) transient condition. In general, the in-situ measurements provide high-fidelity strain, strain rates, and temperature surface maps. This is critical for the United States nuclear industry, which is actively developing a technical basis to support extending the peak rod average burnup from 62 to ~75 GWd/tU and the deployment of accident-tolerant fuel. However, the Nuclear Regulatory Commission, through their research information letter, outlined a number of technical issues for the industry to address before extending burnup. One topic of specific interest is understanding the cladding balloon and rupture geometry during the LOCA heatup phase. Leveraging these advanced in-situ capabilities, this work intends to use insitu data generated from a simulated LOCA in the Severe Accident Test Station at Oak Ridge National Laboratory to better understand high-temperature creep and its impact on Zircaloy balloon and rupture performance. This work used the BISON fuel performance code to compare BISON’s high-temperature creep model predictions to in-situ data and identify limitations and gaps within the model. Additionally, BISON will subsequently be used to simulate relevant high-burnup LOCA tests. The results will be analyzed and compared to the available post-test data in a manner consistent with the approach outlined in the Nuclear Regulatory Commission research information letter.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Sample screening of uranium ore concentrates using portable spectrophotometers: investigating the correlation between visible colors and chemical signatures

A research collaboration between the Japan Atomic Energy Agency and the Department of Energy’s National Nuclear Security Administration examined nuclear forensic signatures and analytical methods for tracing the origins of uranium ore concentrates (UOCs). Here, this study focuses on utilizing portable spectrophotometers capable of reflectance measurements in the visible light spectrum as a potential rapid screening tool for nuclear forensics analysis. Unlike laboratory-based near-infrared spectroscopy or digital image analysis, this research investigated the potential to correlate visible color measurements with key nuclear forensics signatures using seven types of UOC samples with known origins and three UOC certified reference materials. Results demonstrated that distinct color groups, quantified using CIELAB values, correlated with major uranium compounds. Furthermore, the findings indicated that trace elements can influence the UOC colors, providing additional insights into material characteristics. Although this approach requires further validation across a broader range of UOC species, this study demonstrated that simple colorimetric analysis using visible spectrophotometry, which does not require complex sample preparation or data processing, can serve as a practical and novel rapid tool for preliminary screening and attribution in nuclear forensics investigations.

and nuclear chemistry↗
DOE OSTI2023

Artificial Intelligence in Nuclear Physics

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly developing fields providing data-driven algorithms to predict, classify, and make decisions based on data. Nuclear Physics Research is data-driven and AI/ML techniques have been implemented for experiment and accelerator control, in theoretical applications, and in data processing and analysis. These algorithms open possibilities for automation, thereby augmenting human capabilities. Additionally, Open Science is enabled by simultaneous analyses of multiple data sources, leading to scientific knowledge. This talk will summarize current applications of AI/ML in nuclear physics, as well as accelerator applications, and will cover upcoming initiatives and research in AI/ML.

Jeske, Torri↗
DOE OSTI2022

Introducing Small Scale Waste-to-Energy Technology in Microgrids (Cooperative Research and Development Final Report, CRADA Number CRD-17-00703)

Cogent has developed an innovative, proprietary waste-to-energy (WTE) system, the HelioStorm(TM) Gasifier, capable of efficiently operating on small amounts of heterogeneous municipal solid waste feedstocks, converting them into a clean syngas that can be used to fuel an electricity generator, all with rapid on/off cycle times. NREL will work with Cogent to complete a computer simulation of an integrated HelioStorm(TM) plasma gasifier system and dual fuel diesel generator. Cogent will test the performance of an actual HelioStorm(TM) WTE system and dual fuel diesel generator at their test facility using steady state electrical loads and provide a report describing the performance of the integrated system.

09 BIOMASS FUELS↗
DOE OSTI2022

From legacy contamination to watershed systems science: a review of scientific insights and technologies developed through DOE-supported research in water and energy security

Abstract Water resources, including groundwater and prominent rivers worldwide, are under duress because of excessive contaminant and nutrient loads. To help mitigate this problem, the United States Department of Energy (DOE) has supported research since the late 1980s to improve our fundamental knowledge of processes that could be used to help clean up challenging subsurface problems. Problems of interest have included subsurface radioactive waste, heavy metals, and metalloids (e.g. uranium, mercury, arsenic). Research efforts have provided insights into detailed groundwater biogeochemical process coupling and the resulting geochemical exports of metals and nutrients to surrounding environments. Recently, an increased focus has been placed on constraining the exchanges and fates of carbon and nitrogen within and across bedrock to canopy compartments of a watershed and in river–floodplain settings, because of their important role in driving biogeochemical interactions with contaminants and the potential of increased fluxes under changing precipitation regimes, including extreme events. While reviewing the extensive research that has been conducted at DOE’s representative sites and testbeds (such as the Oyster Site in Virginia, Savannah River Site in South Carolina, Oak Ridge Reservation in Tennessee, Hanford in Washington, Nevada National Security Site in Nevada, Riverton in Wyoming, and Rifle and East River in Colorado), this review paper explores the nature and distribution of contaminants in the surface and shallow subsurface (i.e. the critical zone) and their interactions with carbon and nitrogen dynamics. We also describe state-of-the-art, scale-aware characterization approaches and models developed to predict contaminant fate and transport. The models take advantage of DOE leadership-class high-performance computers and are beginning to incorporate artificial intelligence approaches to tackle the extreme diversity of hydro-biogeochemical processes and measurements. Recognizing that the insights and capability developments are potentially transferable to many other sites, we also explore the scientific implications of these advances and recommend future research directions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Research to Confront Climate Change Complexity: Intersectionality, Integration, and Innovative Governance

Abstract Climate impacts increasingly unfold in interlinked systems of people, nature, and infrastructure. The cascading consequences are revealing sometimes surprising connections across sectors and regions, and prospects for climate responses also depend on complex, difficult‐to‐understand interactions. In this commentary, we build on the innovations of the United States Fifth National Climate Assessment to suggest a framework for understanding and responding to complex climate challenges. This approach involves: (a) integration of disciplines and expertise to understand how intersectionality shapes complex climate impacts and the wide‐ranging effects of climate responses, (b) collaborations among diverse knowledge holders to improve responses and better encompass intersectionality, and (c) sustained experimentation with and learning about governance approaches capable of handling the complexity of climate change. Together, these three pillars underscore that usability of climate‐relevant knowledge requires transdisciplinary coordination of research and practice. We outline actionable steps for climate research to incorporate intersectionality, integration, and innovative governance, as is increasingly necessary for confronting climate complexity and sustaining equitable, ideally vibrant climate futures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Remote Hardware-in-the-Loop Approach for Microgrid Controller Evaluation: Preprint

Utilities have been installing microgrids due to the advancements in the distributed energy resources technologies. Microgrids also improve the resiliency of the system due to their capability to isolate themselves from the grid and run in islanded mode of operation. Microgrid controllers are management systems that can run the microgrids under varied operating condition and enable the smooth operation of microgrids under various system conditions. It is of high value to de-risk the installation of such controllers. Hardware-in-the-loop evaluation is used by controller developers and utilities to evaluate the controllers under stressful conditions to understand the performance and to understand the necessary improvements to the microgrid controller. In this research work, the team has leveraged the existing infrastructure of real-time simulation at the Energy Systems Integration Facility (ESIF) and the capability of the microgrid controller to control assets over the Internet Protocol (IP) to evaluate a university developed microgrid controller in an efficient and cost-effective manner. The full paper will provide the complete setup, the experimental use cases and the results. In this abstract, one use case will be expalined, and the results from the use case is provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗