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DOE OSTI2025

Packages of Distributed Energy Technologies Demonstrating Demand Flexibility at Community Scale

The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Pore-Scale Oil Connectivity and Displacement by Controlled-Ionic-Composition Waterflooding Using Synchrotron X-Ray Microtomography

Controlled-ionic-composition waterflooding is an economic and effective method to improve oil recovery in carbonate oil reservoirs. Recent studies show controlling the salinity and ionic composition of injection water can alter the wettability of carbonate mineral surfaces. The pore-scale oil connectivity and displacement by controlled-ionic-composition waterflooding in heterogeneous carbonate reservoirs, especially at the early stage, is still unclear. The goal of this study is to examine the role of ion concentrations and types in the oil displacement efficiency and investigate the impact of the waterflooding on the pore-scale oil displacement using the national synchrotron facility. A carbonate rock sample was flooded with synthetic high-salinity water and other water solutions with different sulfate concentrations. The waterflooding processes were visualized with synchrotron X-ray microtomography to follow the evolution of pore-scale oil/brine interactions at typical field flow rates. Experimental results show that the water with lower sulfate concentration and higher salinity did not change the wettability of the pore surfaces. Higher sulfate ion concentrations in the water, in contrast, altered the wettability of carbonate pore surfaces from oil-wet to neutral-wet within the first few minutes of waterflooding. Finally, novel insight was gained on the ability of water with high-sulfate concentration to displace oil in the small pores and through abundant oil channels, which could consequently lead to higher oil recovery from the carbonate rock.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2026

Pore-Scale Study on the Positive Feedback Between Stress and Porosity Caused by Pressure Solution in Porous Media

Pressure solution is an important process in the evolution of sedimentary rocks, which provide storage space for most of our petroleum resources. It directly influences the generation, migration, and storage of petroleum fluids in subsurface sedimentary rocks. Here, in this paper, we develop a pore-scale, mechanochemical model to demonstrate a possible positive feedback between the local porosity and pore surface stress, in which a higher local porosity causes a higher local pore surface stress, thus enhancing pressure solution and consequently further increasing the local porosity. Pore surface stress represents stress on a solid grain adjacent to a pore. Specifically, the pore-scale, mechanochemical model directly simulates the stress distribution over solid and pore surfaces using a finite element model. The dissolution of solids at the solid-pore interfaces under a far-from-equilibrium condition is simulated using a first-order kinetics model that accounts for the local stress distribution. The updated pore geometry, caused by pore surface dissolution, is then used in the stress simulation in the next numerical iteration. Two types of porous media, the Oriskany sandstone and an artificial porous medium with spherical pores, were tested in the mechanochemical simulation. The positive stress-porosity feedback during pressure solution was observed in both samples. In addition, the model quantitatively illustrated the distribution of local mineral dissolution rates on all pore surfaces, as well as its relation to the effective mineral dissolution rate of the entire sample. Based on the comparison between the two porous media, the local mineral dissolution was regulated by pore space distribution, geometry, and coalescence during pressure solution. This work is the first that uses direct, pore-scale numerical simulation to demonstrate the positive stress-porosity feedback during pressure solution, which has the potential to advance the understanding of the mechanical-chemical (MC) coupling in many geological processes that are relevant to subsurface energy systems, such as the recovery of petroleum hydrocarbons and geothermal energy.

CT scanning↗

DOE OSTI2020

Hot Electron Scaling and Energy Coupling In Nonlinear Laser Plasma Interactions

Energy conversion from high power lasers to energetic hot electrons is a fundamental phenomenon in laser-plasma interactions. At laser intensities above a few times 10 14 W/cm 2 , nonlinear laser-plasma interactions lead to the generation of hot electrons with a broad energy distribution at typical temperatures of 10’s – 100’s kilo-electron-volt (keV). The fraction of laser energy transferred to hot electrons, their energy distribution and energy coupling efficiency to the targets are strongly affected by the laser intensity, wavelength and the plasma condition. Most investigations to date that are related to the fusion of high-energy-density laboratory plasmas (HEDLP) are carried out with relatively moderate laser intensity and lower laser wavelength to minimize hot electron generation, as electron preheating can degrade the fuel assembly. An alternative fusion scheme known as shock ignition (SI) has been proposed, requiring a high intensity spike pulse at the end of a fuel assembly phase to generate a strong shock to ignite the fuel. An initial shock pressure of 0.3 Gbar is required for ignition-scale targets using the SI scheme, requiring a relatively high on-target laser intensity of 5-10X10 15 W/cm 2 for the spike pulse. At such intensities, copious hot electrons can be produced by laser-plasma-instabilities (LPI), e.g., Stimulated Raman Scattering (SRS) and Two-Plasmon Decay (TPD). While very energetic electrons (>200 keV) could preheat the fuel, electrons with moderate energies may actually be beneficial for the SI scheme. Electrons in the 50-100 keV range can be stopped in the compressed high-density outer ablator layer leading to an increase in the ignitor shock strength and therefore enhancing overall efficiency in the SI scheme. Considering this importance of total energy and temperature of hot electrons, it is necessary to understand the LPI in the SI high intensity regime. Characterizing the hot electron source and energy coupling is key to investigating the viability of the SI concept. The overall goal of the HEDLP award was to perform a detailed study of the scaling of hot electron generation and energy coupling on high power laser systems, with intensity, wavelength, and target ablator material relevant to the nonlinear laser-plasma interaction at SI relevant conditions. This was a collaborative project between the Center for Energy Research at the University of California, San Diego (UCSD) and General Atomics. The experiment was performed at the Omega Laser Facility at the Laboratory for Laser Energetics (LLE) in the University of Rochester. Specific objectives of the work were to: understand the basic physics of laser-plasma interactions and instabilities at high laser intensities (up to 10 17 W/cm 2 ) and the effects of low-Z ablator materials and laser wavelengths (IR pulse at 1.054 µm versus UV pulse at 0.351 µm) and intensity scaling, fully characterize the resultant hot electron energy distribution, validate hot electron energy deposition via collisional and kinetic processes in the target and the induced shocks in support of electron-assisted SI concept.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Integration of Large-Scale Renewable Energy in the Bulk Power System: Lessons from International Experiences

Deployment of increasing amounts of renewable energy (RE) presents certain challenges in reliably integrating larger quantities RE into existing bulk power system infrastructures. RE Bulk power typically refers to large-scale power generation at a centralized facility and in the context of RE can include wind farms, utility-scale solar, geothermal, hydro and biomass facilities. Based on international experiences, several actions and related good practices have emerged to support the deployment of RE in the bulk power system. This paper provides a review of emerging international best practices that support the integration of large-scale RE; examples of country-level efforts in implementing these practices; and key considerations for any country pursuing bulk power sector transformation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Multi-resolution, Multi-scale Modeling for Scalable Macroalgae Production

Macroalgae harvested along coastlines and in the open ocean has traditionally been used as food for human consumption, animal feed, and fertilizer. The U.S. ARPA-E MARINER Program estimates that the nation has suitable conditions and geography to produce at least 500 million dry metric tons of macroalgae per year, yielding approximately 2.7 quadrillion BTUs of energy in the form of liquid fuel, which is roughly 10% of the nation’s annual transportation energy demand. Adverse environmental effects of nutrient overload and ocean acidification may also be reduced by large-scale macroalgae cultivation in many coastal ocean regions. However, the successful deployment of large-scale marine macroalgae farms for fuel production depends on ambient hydrodynamic conditions and nutrient availability, as well as their interactions with macroalgae farm structures. Pacific Northwest National Laboratory led an ARPA-E MARINER project to develop a set of numerical modeling tools capable of simulating ocean hydrodynamic and biogeochemical processes, macroalgae trajectories for free-floating systems, macroalgae growth and biomass yields, and hydrodynamic load on macroalgae canopies and farm structures using a multi-resolution and multi-scale approach. This set of modeling tools provides a suite of information essential for system design, optimal project siting, risk analysis, and management of macroalgae production systems in the ocean. Better clarity can also help macroalgae system developers reduce deployment costs, operational risk, and potential impacts on the local marine environment.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Geometric Scale-up Experiments on Fluidization of Geldart B Glass Beads

The objective of this work is to provide a valuable database from controlled experiments for validating computational models. Recently, coarse-grained techniques such as particle-in-cell (PIC) or coarse-grained discrete element modeling (DEM) have gained popularity due to their computational efficiency while modeling large-scale systems; however, the influence of model parameters and their sensitivities at different geometric scales and flow conditions remain to be analyzed. These datasets are critical for the multiphase flow research community to assess predictive capability of modeling techniques as well as elucidate the hydrodynamic behavior in these systems. This study performed fluidization experiments using three different test sections with internal diameters of 2.5, 4, and 6 in. The operating conditions, bed material, and range of flow velocities at the inlet were constant in all the units, which were not hydrodynamically scaled. Glass beads having a Sauter Mean Diameter of 332 μm were used. Superficial velocity was varied from 2.97 to 5.35 times the minimum fluidization velocity and the initial static bed height was 0.1524 m. The order in which the experiments were performed was randomized and replicates were included to provide uncertainty in measurements. Statistics of differential pressure and bed height from these tests were reported. Future plans include validating PIC methodology in the open-source software, MFiX (Multiphase Flow with Interphase Exchanges) using results from this study. This could further be extended to determine optimal model parameters using inverse techniques such as deterministic calibration or Bayesian inference.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Geometric Scale-up Experiments on Fluidization of Geldart B Glass Beads

42 ENGINEERING↗

DOE OSTI2020

Description of the Three-Dimensional Large-Scale Forcing Data from the 3D Constrained Variational Analysis (VARANAL3D)

This technical report introduces a Three-Dimensional Constrained Variational Analysis (3DCVA) (Tang and Zhang 2015) and its product of three-dimensional large-scale forcing data to drive single-column models (SCM), cloud-resolving models (CRM), and large-eddy simulation (LES) models, and to evaluate model results. The 3DCVA algorithm is an extension of the original 1D constrained variational analysis (1DCVA) (Zhang and Lin 1997, Zhang et al. 2001). The three-dimensional structure of the forcing data allows studies of spatial variation of the large-scale forcing fields and tests of physical parameterizations across scales. In the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility, the 3D forcing data are assigned the datastream name varanal3d. In this technical report, 3DCVA will be used to refer to the algorithm, while VARANAL3D will be used to refer to the data product.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Modular CO 2 Capture Processes for Integration with Modular Scale Gasification Technologies: Literature Review and Gap Analysis for Future R&D

The motivation for this report is the recent focus of the U.S. Department of Energy’s (DOE) gasification program to develop modular scale gasification processes for electricity generation and other applications. Mass-produced, modular gasification systems have been proposed to decrease the upfront capital costs and to encourage flexible deployment of advanced gasification technology using a diverse set of feedstocks. To fully realize the benefits of advanced gasification technology for power generation as well as other chemical applications, precombustion carbon dioxide (CO 2 ) capture must be considered. Therefore, the aim of this report is to assess the potential of integrating modular scale carbon capture processes with modular scale coal gasification technologies, and to help guide future research and development efforts in this area.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

ALEGRA Parallel Scaling for Shock in a Heterogeneous Structure

We investigate the strong and weak parallel scaling performance of the ALEGRA multiphysics finite element program when solving a problem involving shock propagation through a heterogeneous material. We determine that ALEGRA scales well over a wide range of problem sizes, cores, and element sizes, and that scaling generally improves as the minimum element size in the mesh increases.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Utility-Scale Solar Data Update (2020 Edition) [Slides]

Berkeley Lab’s 2020 update of utility-scale solar data and trends provides an overview of key trends in the U.S. market, with a focus on 2019. Highlights of this year’s update include: More than 4.5 GWAC of utility-scale solar (i.e., ground-mounted solar projects larger than 5 MWAC) achieved commercial operations in 2019, bringing cumulative capacity to 29 GWAC. Projects are spread across all 10 regions that we track, though more heavily concentrated in the sunniest regions. The median installed cost of projects that came online in 2019 fell to $\$$1.4/WAC ($\$$1.2/WDC), down 20% from 2018 and down by more than 70% from 2010. 77% of projects and 88% of capacity added in 2019 used single-axis tracking. Average capacity factors range from 17% in the least-sunny regions to 30% where it is sunniest. Single-axis tracking adds roughly five percentage points to capacity factor in the regions with the strongest solar resource. Nationwide average levelized power purchase agreement (PPA) prices fell to $\$$24/MWh in 2019, down 17% from 2018 and more than 80% since 2010. Thirty-nine projects (totaling 4.2 GWAC) in our PPA price sample include battery storage (totaling 2.3 GWAC and 9.5 GWh). In the “lower 48” states, a number of these recent PV+battery PPAs have been inked in the mid-$\$$20/MWh range (levelized in 2019 dollars).Not including the 30% investment tax credit (ITC), the median levelized cost of energy (LCOE) from utility-scale PV has declined by 85% since 2010, to $\$$40/MWh in 2019. When the 30% ITC is included within the LCOE calculation, the median LCOE closely tracks the median PPA price over time. In higher-penetration markets like CAISO, the value of solar has been declining, but falling PPA prices have largely kept pace, preserving solar's net value. At the end of 2019, there were nearly 370 GW of solar in interconnection queues from all 7 ISOs and 30 additional utilities across the country. Nearly a third of this proposed solar capacity is paired with battery storage.

14 SOLAR ENERGY↗

DOE OSTI2020

Description of the Three-Dimensional Large-Scale Forcing Data from the 3D Constrained Variational Analysis (VARANAL3D)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

42 ENGINEERING↗

DOE OSTI2021

Integration Roadmap for Multi-Scale, Multi-Physics Mass Accountancy in Molten Salt Reactors

The objective of the integration roadmap is to describe the necessary physics required and a plan for modeling and simulation approach for predicting mass accountancy in molten salt reactors on an engineering scale. The thermophysical properties and the underlying thermodynamics are fundamental inputs. Therefore, the modeling will span length scales from first principles calculations to the engineering scale. The intention is to predict where material accumulates in a reactor core and loop and to understand perturbations on the systems level, for example the downstream effects from a turbine failure

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Physical and Thermomechanical Properties of Yttrium Hydride from Large Scale Bulk Metal Hydriding Furnace

Given the superior thermal stability and highly attainable hydrogen density, yttrium hydride is an excellent high-temperature moderator material in advanced thermal neutron spectrum reactors that require small core volumes. Yttrium hydride has been selected as the moderator material for the Transformational Challenge Reactor, which was launched at Oak Ridge National Laboratory (ORNL) in 2019. However, fabrication of large-scale crack-free yttrium hydride is challenging and very limited efforts have been committed to the characterization of bulk yttrium hydride in response to the need to establish a complete database of the thermomechanical properties of YHx. In this report, the challenges associated with fabricating large-scale crack-free yttrium hydride are discussed herein. In response to those challenges, a hydriding system was designed and constructed at ORNL and was used to successfully fabricate crack-free yttrium hydride in complex geometries at large scales. This was accomplished by precisely controlling the hydrogen’s partial pressure and the retort temperature, which was informed by the well-established thermodynamic properties of the binary H-Y system. Hydrogen content in as-fabricated hydride was determined by the weight change method and vacuum hot extraction technique, complemented by the X-ray diffraction (XRD). In addition, significant efforts are being dedicated to establishing a complete database of the thermomechanical properties of as-fabricated yttrium hydride. In FY2020, we investigated the thermophysical properties of yttrium hydrides as a function of temperature (room temperature to 700°C) and hydrogen concentration (H/Y ratio ranges from 1.52 to 1.93). The results indicate that at the temperatures below 300 °C, the hydrogen content did not have a significant influence on the thermal expansion, while the specific heat capacity, the thermal diffusivity, and the calculated thermal conductivity were slightly higher for the higher H/Y ratio. Between 300°C and 700 °C, a reversible second-order endothermic transition in all measured thermal properties was observed. It was also found that the onset temperatures of the observed transition varied, with the composition having inverse dependence on the hydrogen content. An attempt was made to explain the behavior of the thermophysical properties at higher temperatures by considering the order– disorder transition as a result of hydrogen redistribution. In addition, nanoindentation was employed to determine the elastic modulus and hardness and to capture the crystal orientation dependence of these parameters. Vickers hardness was also reported. The final section of the report introduces ongoing neutron irradiation campaign of yttrium hydride.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A Call to Arms Control: Synergies between Nonproliferation Applications of Neutrino Detectors and Large-Scale Fundamental Neutrino Physics Experiments (A Snowmass White Paper)

The High Energy Physics community can benefit from a natural synergy in research activities into next-generation large-scale water and scintillator neutrino detectors, now being studied for remote reactor monitoring, discovery and exclusion applications in cooperative nonproliferation contexts. Since approximately 2010, US nonproliferation researchers, supported by the National Nuclear Security Administration (NNSA), have been studying a range of possible applications of relatively large (100 ton) to very large (hundreds of kiloton) water and scintillator neutrino detectors. In parallel, the fundamental physics community has been developing detectors at similar scales and with similar design features for a range of high-priority physics topics, primarily in fundamental neutrino physics. These topics include neutrino oscillation studies at beams and reactors, solar, and geological neutrino measurements, supernova studies, and others. Examples of ongoing synergistic work at U.S. national laboratories and universities include prototype gadolinium-doped water and water-based and opaque scintillator test-beds and demonstrators, extensive testing and industry partnerships related to large area fast position-sensitive photomultiplier tubes, and the development of concepts for a possible underground kiloton-scale water-based detector for reactor monitoring and technology demonstrations. Some opportunities for engagement between the two communities include bi-annual Applied Antineutrino Physics conferences, collaboration with U.S. National Laboratories engaging in this research, and occasional NNSA funding opportunities supporting a blend of nonproliferation and basic science R&D, directed at the U.S. academic community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗