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A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.

Bernholdt, David↗

Experiential findings for sustainable software ecosystems to support experimental and observational science

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. Here, the study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: (i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and (ii) data management requirements for data-driven science using artificial intelligence.

97 MATHEMATICS AND COMPUTING↗

Dendrite Growth Morphology Modeling in Liquid and Solid Electrolytes

The main goal of this project is to develop a multi-scale modeling approach that connects micron-scale phase-field models and atomic-scale density functional theory (DFT)-based simulations via parameter- and relationship-passing in order to predict Li-metal dendrite morphology evolution, in both liquid and solid electrolytes. The key hypothesis of the DFT-informed phase-field multiscale modeling approach is that it can capture the electrochemical-mechanical driving forces and incorporate the roles of nano-meter-thin solid electrolyte interphase (SEI) in liquid electrolytes as well as of the microstructures of micro-meter-thick solid electrolytes (SEs) for all-solid-state batteries. In this project, we have formulated and implemented phase-field models to incorporate the electrochemical driving forces in liquid electrolytes and then incorporate mechanical driving forces to simulate dendrite growth in solid electrolytes with resolved microstructures. We have implemented two treatments for the SEI: an explicit model to include the microstructure of the SE or SEI in the phase field model and an implicit model to simulate the impact of nano-meter thick SEI in liquid electrolytes by varying the electrode/electrolyte interfacial properties. The key interfacial properties, including the electronic and ionic transport properties, the charge transfer reaction kinetics, and mechanical properties, were computed by DFT-based calculations. At the DFT-based model, one key advancement is to directly predict the charge transfer reaction kinetics at a complex Li/SEI/electrolyte interface by linking DFT with density functional tight binding (DFTB) calculations. As the main accomplishments, we have demonstrated two successful predictions in both solid electrolyte and liquid electrolyte based on this multiscale approach. The predicted intergranular Li dendrite growth in LLZO revealed the importance of trapped electrons at internal interfaces in the microstructure of LLZO. The predicted electroplating morphology of mossy Li and faceted Mg agreed well with experiments. The insights provided by the multiscale model and the model enabled electrolyte and SEI design will accelerate the development of Li-metal electrode for high energy density batteries, that meet DOE’s target on cell density (>350 Wh/kg) and cost below $100/kWhuse for EV applications.

25 ENERGY STORAGE↗

Multi-Messenger In-situ Tolerance Optimization of Mixed Perovskite Photovoltaics. Final Report

The main objectives for this project were to formulate, validate and disseminate a new procedure based on Environmental X-ray Photoelectron Spectroscopy (EXPS) for the accelerated degradation testing of metal hybrid perovskite (MHP) PV materials. With this capability, we can aid US efforts to improve MHP tolerance for illumination in damp heat conditions. This capability will benefit the public by supporting new industry efforts to create stable MHP formulations.

14 SOLAR ENERGY↗

Tightest Mixed-Integer Programming Formulations for Quadratic SCUC Optimization

In this project, we developed new, tighter Mixed-Integer Programming (MIP) formulations for the combined Alternating Current (AC) Security-Constrained Unit Commitment (SCUC) and Security-Constrained Optimal Power Flow (SCOPF). The work addresses a critical challenge in power system operations: efficiently determining which generation units to commit and how to optimally dispatch them while maintaining network reliability constraints for both normal and contingency scenarios. Our efforts: 1. Advance the Understanding of SCUC/SCOPF Modeling: By introducing tighter MIP formulations and leveraging cutting-edge optimization tools (Julia/JuMP, PowerModels.jl), this project has pushed forward the state of the art in efficient power systems scheduling. 2. Enhance Technical and Economic Feasibility: The methods developed provide more accurate and potentially faster solutions to large-scale, realistic scheduling and dispatch problems in electric power systems, which can translate into improved reliability and potentially lower costs for grid operations. 3. Benefit to the Public: Greater efficiency in power system operations leads to cost savings for utilities and end-users. Improved reliability and integration of advanced modeling approaches can facilitate the adoption of clean energy resources and better accommodate uncertainties in renewable generation. Because this technology could impact bulk power markets and reliability, these innovations have far-reaching public benefits in terms of cost savings, reliability, and sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Projecting the number of new HIV infections to formulate the "Getting to Zero" strategy in Illinois, USA

Objectives: Getting to Zero (GTZ) initiatives focus on expanding use of antiretroviral treatment (ART) and pre-exposure prophylaxis (PrEP) to eliminate new HIV infections. Computational models help inform policies for implementation of ART and PrEP continuums. Such models, however, vary in their design, and may yield inconsistent predictions. Using multiple approaches can help assess the consistency in results obtained from varied modeling frameworks, and can inform optimal implementation strategies. Methods: A study using three different modeling approaches is conducted. Two approaches use statistical time series analysis techniques that incorporate temporal HIV incidence data. A third approach uses stochastic stimulation, conducted using an agent-based network model (ABNM). All three approaches are used to project HIV incidence among a key population, young Black MSM (YBMSM), over the course of the GTZ implementation period (2016-2030). Results: All three approaches suggest that simultaneously increasing PrEP and ART uptake is likely to be more effective than increasing only one, but increasing ART and PrEP by 20% points may not eliminate new HIV infections among YBMSM. The results further suggest that a 20% increase in ART is likely to be more effective than a 20% increase in PrEP. All three methods consistently project that increasing ART and PrEP by 30% simultaneously can help reach GTZ goals. Conclusions: Increasing PrEP and ART uptake by about 30% might be necessary to accomplish GTZ goals. Such scale-up may require addressing psychosocial and structural barriers to engagement in HIV and PrEP care continuums. ABNMs and other flexible modeling approaches can be extended to examine specific interventions that address these barriers and may provide important data to guide the successful intervention implementation.

60 APPLIED LIFE SCIENCES↗

Light Water Reactor Sustainability Program Plant Modernization Technical Program Plan for FY 2021

This report presents the Technical Program Plan for FY 2019 for the Department of Energy Light Water Reactor Sustainability Program – Plant Modernization research pathway. A summary of the vision and strategy is provided to explain how this program addresses key issues and barriers for modernizing instrumentation and control technologies and infrastructure in domestic nuclear power plants. The report describes the pilot projects that have been formulated to develop and validate enabling technologies over the next several years that will result in digital alternatives to the legacy analog II&C systems in place today. This will allow much needed modernization of these systems to address reliability and obsolescence problems, as well as serve as a platform for substantial operational improvement. The report further describes key project resources and cooperative relationships, including the Electric Power Research Institute, the Nuclear Energy Institute )NEI), the Institute of Nuclear Power Operations (INPO), the IFE Halden Reactor Project, the Nuclear Regulatory Commission, and industry suppliers, that are instrumental to the success of the program. The report also lists the schedule for all program products, including the titles and report numbers for all published reports under this program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Light Water Reactor Sustainability Program Plant Modernization Technical Program Plan for FY 2021

This report presents the Technical Program Plan for FY 2019 for the Department of Energy Light Water Reactor Sustainability Program – Plant Modernization research pathway. A summary of the vision and strategy is provided to explain how this program addresses key issues and barriers for modernizing instrumentation and control technologies and infrastructure in domestic nuclear power plants. The report describes the pilot projects that have been formulated to develop and validate enabling technologies over the next several years that will result in digital alternatives to the legacy analog II&C systems in place today. This will allow much needed modernization of these systems to address reliability and obsolescence problems, as well as serve as a platform for substantial operational improvement. The report further describes key project resources and cooperative relationships, including the Electric Power Research Institute, the Nuclear Energy Institute )NEI), the Institute of Nuclear Power Operations (INPO), the IFE Halden Reactor Project, the Nuclear Regulatory Commission, and industry suppliers, that are instrumental to the success of the program. The report also lists the schedule for all program products, including the titles and report numbers for all published reports under this program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Adjoint Petrov–Galerkin method for non-linear model reduction

Here, we formulate a new projection-based reduced-order modeling technique for non-linear dynamical systems. The proposed technique, which we refer to as the Adjoint Petrov–Galerkin (APG) method, is derived by decomposing the generalized coordinates of a dynamical system into a resolved coarse-scale set and an unresolved fine-scale set. A Markovian finite memory assumption within the Mori–Zwanzig formalism is then used to develop a reduced-order representation of the coarse scales. This procedure leads to a closed reduced-order model that displays commonalities with the adjoint stabilization method used in finite elements. The formulation is shown to be equivalent to a Petrov–Galerkin method with a non-linear, time-varying test basis, thus sharing some similarities with the Least-Squares Petrov–Galerkin method. Theoretical analysis examining a priori error bounds and computational cost is presented. Numerical experiments on the compressible Navier–Stokes equations demonstrate that the proposed method can lead to improvements in numerical accuracy, robustness, and computational efficiency over the Galerkin method on problems of practical interest. Improvements in numerical accuracy and computational efficiency over the Least-Squares Petrov–Galerkin method are observed in most cases.

42 ENGINEERING↗

Development, Implementation, and Verification of Partially-Ionized Collisional Multifluid Plasma Models in Drekar

We consider the development of multifluid models for partially ionized multispecies plasmas. The models are composed of a standard set of five-moment fluid equations for each species plus a description of electromagnetics. The most general model considered utilizes a full set of fluid equations for each charge state of each atomic species, plus a set of fluid equations for electrons. The fluid equations are coupled through source terms describing electromagnetic coupling, ionization, recombination, charge exchange, and elastic scattering collisions in the low-density coronal limit. The form of each of these source terms is described in detail, and references for required rate coefficients are identified for a diverse range of atomic species. Initial efforts have been made to extend these models to incorporate some higher-density collisional effects, including ionization potential depression and three- body recombination. Some reductions of the general multifluid model are considered. First, a reduced multifluid model is derived which averages over all of the charge states (including neutrals) of each atomic species in the general multifluid model. The resulting model maintains full consistency with the general multifluid model from which it is derived by leveraging a quasi-steady-state collisional ionization equilibrium assumption to recover the ionization fractions required to make use of the general collision models. Further reductions are briefly considered to derive certain components of a single-fluid magnetohydrodynamics (MHD) model. In this case, a generalized Ohm's law is obtained, and the standard MHD resistivity is expressed in terms of the collisional models used in the general multifluid model. A number of numerical considerations required to obtain robust implementations of these multifluid models are discussed. First, an algebraic flux correction (AFC) stabilization approach for a continuous Galerkin finite element discretization of the multifluid system is described in which the characteristic speeds used in the stabilization of the fluid systems are synchronized across all species in the model. It is demonstrated that this synchronization is crucial in order to obtain a robust discretization of the multifluid system. Additionally, several different formulations are considered for describing the electromagnetics portion of the multifluid system using nodal continuous Galerkin finite element discretizations. The formulations considered include a parabolic divergence cleaning method and an implicit projection method for the traditional curl formulation of Maxwell's equations, a purely- hyperbolic potential-based formulation of Maxwell's equations, and a mixed hyperbolic-elliptic potential-based formulation of Maxwell's equations. Some advantages and disadvantages of each formulation are explored to compare solution robustness and the ease of use of each formulation. Numerical results are presented to demonstrate the accuracy and robustness of various components of our implementation. Analytic solutions for a spatially homogeneous damped plasma oscillation are derived in order to verify the implementation of the source terms for electromagnetic coupling and elastic collisions between fluid species. Ionization balance as a function of electron temperature is evaluated for several atomic species of interest by comparing to steady-state calculations using various sets of ionization and recombination rate coefficients. Several test problems in one and two spatial dimensions are used to demonstrate the accuracy and robustness of the discretization and stabilization approach for the fluid components of the multifluid system. This includes standard test problems for electrostatic and electromagnetic shock tubes in the two-fluid and ideal shock-MHD limits, a cylindrical diocotron instability, and the GEM challenge magnetic reconnection problem. A one-dimensional simplified prototype of an argon gas puff configuration as deployed on Sandia's Z-machine is used as a demonstration to exercise the full range of capabilities associated with the general multifluid model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Neural Thermal Scattering (NeTS) Modules for Graphite & Beryllium [Slides]

This presentation discusses the motivations behind the project, which include facilitating compact formulation for TSL data, extending AI knowledge, and providing advanced reactor simulation framework. It also discusses how the project accounts for beryllium and graphite complexity, including atomistic, dynamical, and neural. Additionally, new material-informed neural thermal scattering (NeTS) Modules are examined. The implications, conclusions, and plan future work for the project are also discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Flexible Service Contracting for Risk Management within Integrated Transmission and Distribution Systems

The general objective of our project has been to investigate the ability of Independent Distribution System Operators (IDSOs), functioning as linkage agents for Integrated Transmission and Distribution (ITD) systems, to facilitate the flexible availability and usage of reserve in support of ITD system operations. This general objective is in accordance with Order 2222 of the U.S. Federal Energy Regulatory Commission (FERC), titled “Participation of Distributed Energy Resource Aggregations in Markets Operated by Regional Transmission Organizations and Independent System Operators”. The Final Rule for FERC Order 2222 was issued on September 17, 2020. The primary contribution of our project is that we have formulated an innovative energy management Transactive Energy Design (TES) approach for ITD systems that provides promising support for our project objective. Specifically, we have developed a new type of IDSO-managed TES design for distribution system operations, as well as new types of swing contracts permitting IDSOs to participate in transmission system operations as providers of reserve harnessed from distribution system resources in return for appropriate compensation. Together, these design elements constitute a scalable market-based approach facilitating efficient reserve procurement for ITD system operations from a fuller range of power resources. The efficacy of our approach has been demonstrated by means of detailed conceptual analyses as well as test case simulations. To implement the latter, we have developed the ITD TES Platform V2.0, a computational platform that permits the modeling and software implementation of ITD system operations over time. The Electric Reliability Council of Texas (ERCOT) energy region has been used as the empirical anchor for the development of this platform. Our conceptual and test-case work has been reported in a Wiley/IEEE Press book, two refereed book chapters, and seven refereed journal articles. The key components comprising the ITD TES Platform V2.0 have been released as documented open-source software at online GitHub repositories.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Decomposition and Algorithmic Approaches for Solving Large-Scale Process Family Design Problems

Our most recent work expands the water desalination case study from 76 variants to 10,897 variants using the equation-oriented model built in Pyomo as part of the PARETO project. Using the discretization formulation presented in Stinchfield (2024a), rather than solving for all 10,897 variants simultaneously, we decompose the formulation into subproblems containing subsets of variants from the process family. We solve the overall problem with Progressive Hedging (PH) deployed in parallel on a distributed HPC cluster using the open-source Python package mpi-sppy (Knueven et al., 2023). This approach allowed us to solve this process family design problem to ~1.5% relative optimality gap in about 5 hours; in comparison, Gurobi reached ~50% relative optimality gap in about 6 hours (Stinchfield et al., 2024b). However, this approach still requires discretization of the common unit module design ranges; additionally, PH acts as a heuristic for MILP’s with gap-closing capabilities. Ideally, we would not have to use ML surrogates or discretization to solve this problem, instead solving the process family design problem with the equation-oriented model directly to achieve the most accurate results. However, recall that we did not consider solving the MINLP directly due to complexity and size. In this work, we aim to decompose and solve this large-scale MINLP using a Structured Nonlinear Global Optimization algorithm presented by Cao and Zavala (2019).

Stinchfield, Georgia↗

Treatment of Problematic Reactive Metal Wastes Using GeoMelt ICV - WM2020 Conference Paper

Decommissioning of sodium-cooled reactors and fast reactor technologies has generated a number of reactive metal waste configurations that are problematic to treat and typically lack cost effective treatment methods and disposition options. As a result, Veolia Nuclear Solutions, under contract with Idaho National Laboratory (owned by the U.S. Department of Energy and managed and operated by Battelle Energy Alliance, LLC) demonstrated its GeoMelt® In-Container Vitrification (ICV)™ technology to safely convert sodium metal to a non-reactive vitrified oxide form. The demonstration project, supported by glass formulation and crucible testing, consisted of a series of ICV™ melts that processed elemental sodium into stable non-reactive glass. INL is currently implementing GeoMelt® technology as a means to safely and reliably convert radioactive reactive metal residues that contaminate sodium cooled reactor components into waste forms that comply with existing disposition pathways. Reactive metal wastes require treatment in order to remove the Resource Conservation and Recovery Act (RCRA) reactivity and ignitability characteristics to comply with land disposal restrictions. GeoMelt®, which is an alternative to other potential treatment approaches, provides a robust approach that chemically converts the reactive metals to an inert oxide while also immobilizing radionuclides in a vitrified waste form with durability equal to or better than vitrified nuclear fuel reprocessing wastes (very robust and inert waste forms). Most other treatment approaches generate hydrogen gas which is problematic. In 2016, Veolia Nuclear Solutions first demonstrated the effectiveness of the GeoMelt® ICV™ process in deactivating reactive sodium metal. Crucible, bench-scale, and engineering-scale demonstrations were conducted on several surrogate waste configurations with various ratios of sodium metal and glass-formers. Each ratio and configuration demonstrated complete deactivation of the surrogate sodium metal. Follow-on work in 2017 demonstrated the deactivation of reactive sodium by GeoMelt® ICV™ at a higher waste loading relative to previously demonstrated work performed in 2016; the higher waste loading optimized glass chemistry while enhancing the economical full-scale treatment of reactive metals. Additionally, follow-on demonstration testing in 2018 and 2019 focused on more complex shapes and other reactive-metals (mocked up Experimental Breeder Reactor II [EBR-II] subassembly, sodium filled heat exchanger, and a can containing sodium potassium alloy) which were all performed at engineering-scale. Since 2018, a 10-metric ton full-scale GeoMelt unit (GeoMelt® Richland) was designed, installed, and commissioned at Perma-Fix Northwest in Richland, Washington for the treatment of reactive metal wastes. As of September 2019, over 900 55-gallon drums containing a total of around 3,500 lb of sodium with low levels of radioactivity have been treated at GeoMelt ® Richland, with resulting glass monoliths disposed at the Nevada National Security Site (NNSS). A full-scale radiological demonstration melt on an actual EBR-II subassembly has also been performed using the full-scale melter in 2019. The GeoMelt® technology is a proven radioactive waste treatment technology capable of immobilizing radioactive wastes, including bulk rubble such as drums and other steel vessels usually without pretreatment. Utilizing the GeoMelt® technology to treat reactive metals eliminates pretreatment steps resulting from having to separate the reactive metal from steel containers or jackets as GeoMelt® can easily operate at temperatures sufficient to melt the steel and expose the reactive metal for treatment. Eliminating handling steps of reactive metals is a significant safety advantage since reactive metals are pyrophoric. The results generated as a part of the 2018-2019 demonstration program are presented in the paper.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Treatment of Problematic Reactive Metal Wastes Using the GeoMelt{sup R} In-Container Vitrification (ICV{sup TM}) Process - 20326

Decommissioning of sodium-cooled reactors and fast reactor technologies has generated a number of reactive metal waste configurations that are problematic to treat and typically lack cost effective treatment methods and disposition options. As a result, Veolia Nuclear Solutions, under contract with Idaho National Laboratory (owned by the U.S. Department of Energy and managed and operated by Battelle Energy Alliance, LLC) demonstrated its GeoMelt{sup R} In-Container Vitrification (ICV){sup TM} technology to safely convert sodium metal to a non-reactive vitrified oxide form. The demonstration project, supported by glass formulation and crucible testing, consisted of a series of ICV{sup TM} melts that processed elemental sodium into stable non-reactive glass. INL is currently implementing GeoMelt{sup R} technology as a means to safely and reliably convert radioactive reactive metal residues that contaminate sodium cooled reactor components into waste forms that comply with existing disposition pathways. Reactive metal wastes require treatment in order to remove the Resource Conservation and Recovery Act (RCRA) reactivity and ignitability characteristics to comply with land disposal restrictions. GeoMelt{sup R}, which is an alternative to other potential treatment approaches, provides a robust approach that chemically converts the reactive metals to an inert oxide while also immobilizing radionuclides in a vitrified waste form with durability equal to or better than vitrified nuclear fuel reprocessing wastes (very robust and inert waste forms). Most other treatment approaches generate hydrogen gas which is problematic. In 2016, Veolia Nuclear Solutions first demonstrated the effectiveness of the GeoMelt{sup R} ICV{sup TM} process in deactivating reactive sodium metal. Crucible, bench-scale, and engineering-scale demonstrations were conducted on several surrogate waste configurations with various ratios of sodium metal and glass formers. Each ratio and configuration demonstrated complete deactivation of the surrogate sodium metal. Follow-on work in 2017 demonstrated the deactivation of reactive sodium by GeoMelt{sup R} ICV{sup TM} at a higher waste loading relative to previously demonstrated work performed in 2016; the higher waste loading optimized glass chemistry while enhancing the economical full-scale treatment of reactive metals. Additionally, follow-on demonstration testing in 2018 and 2019 focused on more complex shapes and other reactive-metals (mocked up Experimental Breeder Reactor II [EBR-II] subassembly, sodium filled heat exchanger, and a can containing sodium potassium alloy) which were all performed at engineering scale. Veolia Nuclear Solutions designed, installed, and commissioned in September 2018, at Perma-Fix Northwest in Richland Washington, a 10-metric ton full-scale GeoMelt unit (GeoMelt{sup R} Richland) for the treatment of reactive metal wastes. As of September 2019, over 900 55-gallon drums containing a total of around 3,500 lb of sodium with low levels of radioactivity have been treated at GeoMelt{sup R} Richland, with resulting glass monoliths disposed at the Nevada National Security Site (NNSS). A full-scale radiological demonstration melt on an actual EBR-II subassembly has also been performed using the full-scale melter in 2019. The GeoMelt{sup R} technology is a proven radioactive waste treatment technology capable of immobilizing radioactive wastes, including bulk rubble such as drums and other steel vessels usually without pretreatment. Utilizing the GeoMelt{sup R} technology to treat reactive metals eliminates pretreatment steps resulting from having to separate the reactive metal from steel containers or jackets as GeoMelt{sup R} can easily operate at temperatures sufficient to melt the steel and expose the reactive metal for treatment. Eliminating handling steps of reactive metals is a significant safety advantage since reactive metals are pyrophoric. The results generated as a part of the 2018-2019 demonstration program are presented in the paper. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Dynamic Binary Complexes (DBC) as Super-Adjustable Viscosity Modifiers for Hydraulic Fracturing Fluids

In the preceding project year two, we refined three DBC formulations from a selection of over 50 different chemistries. The optimization study primarily encompassed testing for (i) reversibility extent, (ii) performance in the presence of chemical additives, (iii) adhesion and friction behavior during displacement in wellbores and pipelines, (iv) corrosion protection performance, and (v) injection performance with model fracture systems at the laboratory scale. Highly promising results obtained from all these tests signify the significant potential of DBCs in enhancing hydrocarbon recovery from unconventional reservoirs. The primary activities in the third project year included publishing experimental findings across multiple articles and conducting outreach initiatives. Throughout the year, we undertook tasks such as replicating experimental results, further optimizing various formulations and their associated experimental sets, and conducting additional tests to address missing components based on reviewer feedback and suggestions. We also explored the surfactant and friction-reduction aspects of selected formulations through drag reduction tests. In addition, we constructed an improved fracturing performance setup and performed flow injection tests. The specific DBC formulations focused on during this project period were A8/B1, A12/B5, and A10/B12. We also obtained results for additional DBC formulations and a select few commercial fracturing fluids for the purpose of comparison. Within the project's scope, we aim to enhance the experimental findings with the development of various models. The first two years focused on two key aspects: (i) the creation of a high-fidelity hydraulic fracturing model for non-Newtonian fluids to gain insights into the implementation of DBC fluids in fracking environments, and (ii) the development of a multiphase flow simulator for estimating total production, fluid saturation in the reservoir, and the creation of a fracture propagation model and kinetic Monte Carlo (kMC) models for diverse applications. In the third year, we delved into the fundamental nanostructural properties of DBCs, exploring aspects such as material chemistry, pH tunability, and control of DBC formation and stability. Subsequently, in the extension year, we conducted a systematic investigation of various building blocks containing primary, secondary, and tertiary amine functional groups to understand their impact on rheological and viscoelastic properties. Furthermore, we explored a Dissipative Particle Dynamics (DPD) model to simulate self-assembly processes with precision, creating a high-fidelity representation of relevant nanostructures. The tasks performed this year with the significant results obtained have been discussed in Section 2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-scale, Multi-disciplinary, and Multi-agent Explainable AI with Koopman-Undergirded Learning, Prediction, and Analysis (M3EA KULPA) (Project Closeout Report)

The goal of this project was to develop and use domain-aware machine learning formulations, based on the Koopman Operator (KO), for modelling multi-scale, multi-disciplinary (e.g., multi-physics), and/or multi-agent systems. The project developed these formulations for the following cases: • Systems with dynamics at two separate time scales, • Systems with a bi-level hierarchical control structure, • Systems with bi-level hierarchical control and dynamics at two separate time scales (the lower level controls operating at the faster time scale), and • Systems with n separate but interacting agents/disciplines (with/without control, respectively); the controls for each agent could include bi-level hierarchical control and dynamics at two separate time scales as described above. The project then defined a set of dynamical systems consisting of different nonlinear oscillators that could be used to test these different formulations and then subsequently learned the KO models for those systems. With the KO models, we were able to do the following: • Quantify system stability, including both long-term and transient behavior, • Quantify the effects of feedbacks between the different time scales and agents/disciplines in terms of those feedbacks’ effects on system stability, • Replace a standard Proportional-Integral (PI) control in the hierarchical control structure with a KO-based Linear-Quadratic Regular (LQR), a form of optimal control, • Calculate optimal supervisory control policies a) with and without time scale separated dynamics at the lower level control levels and b) with both PI and KO-based LQR lower level control policies, and • Calculate dynamic Nash equilibria for multi-agent systems where each agent makes its own control decisions.

97 MATHEMATICS AND COMPUTING↗

Robust data-driven uncertainty quantification in water cycle extreme predictions

Climate experts apply global climate models to predict the future climate, informing decisions and adaptations. Uncertainty plays a fundamental role in this process (particularly for the water cycle simulation, the most relevant but least well-simulated). For many aspects of the water cycle there are disagreements for future climate projections, reflecting the significant uncertainty in model formulation. Also, the chaotic nature of climate dynamics, as well as indeterministic future projection emission scenarios, contribute to the uncertainty in climate predictions. New AI methods that are beginning to be adopted by the climate community have the power to improve predictions of water cycle extremes. The crucial question is how to capture all sources of uncertainty in a systematic way in order for the predictions from the AI models to be maximally leveraged by decision makers

54 ENVIRONMENTAL SCIENCES↗