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At least 865 records · Page 48

Non-intrusive nonlinear model reduction via machine learning approximations to low-dimensional operators

Abstract Although projection-based reduced-order models (ROMs) for parameterized nonlinear dynamical systems have demonstrated exciting results across a range of applications, their broad adoption has been limited by their intrusivity: implementing such a reduced-order model typically requires significant modifications to the underlying simulation code. To address this, we propose a method that enables traditionally intrusive reduced-order models to be accurately approximated in a non-intrusive manner. Specifically, the approach approximates the low-dimensional operators associated with projection-based reduced-order models (ROMs) using modern machine-learning regression techniques. The only requirement of the simulation code is the ability to export the velocity given the state and parameters; this functionality is used to train the approximated low-dimensional operators. In addition to enabling nonintrusivity, we demonstrate that the approach also leads to very low computational complexity, achieving up to $$10^3{\times }$$ 10 3 × in run time. We demonstrate the effectiveness of the proposed technique on two types of PDEs. The domain of applications include both parabolic and hyperbolic PDEs, regardless of the dimension of full-order models (FOMs).

42 ENGINEERING↗

A Collaboration Website for Muon Catalyzed Fusion and Muon Beam Production

This research initiative establishes a dynamic online platform geared towards supporting the burgeoning Muon Catalyzed Fusion collaboration, focusing on the concurrent development of particle accelerators and transport beamlines for muon beams. The central feature of this endeavor is the creation of a multifaceted website comprising both public facing and private sections to cater to diverse user needs. The public segment is meticulously designed to serve as an educational hub, featuring information pages targeted at the general public alongside private pages exclusively accessible to collaboration members. These pages will host an array of multimedia elements, ranging from images and text animations to video lectures, covering an extensive spectrum of topics integral to the science of Muon Catalyzed Fusion. Encompassing areas such as Acceleration, Applications, Instrumentation, Beamline Design, and beam dynamics design codes, the educational content aims to make complex scientific concepts more accessible to a broader audience. Ensuring seamless accessibility across various devices and operating systems, the website incorporates integration with collaborative tools such as Google Docs for document collaboration, GitHub for code repository management, and WordPress for blogging with interactive commenting features. The bifurcation between public and private sections is a strategic approach to maintaining transparency while safeguarding proprietary research and works in progress. The public pages are strategically crafted to disseminate information, showcasing the latest endeavors and achievements within the NK Labs collaboration, including lectures, published papers, and regular blog posts open to public comments. On the other hand, the private section provides collaboration members with a secure space to share unpublished or nonpublic research, fostering collaborative efforts through integrated Google Docs and Python Plotty for shared graphing work. In essence, this ambitious project endeavors to bridge the gap between complex scientific knowledge and public understanding, enhance collaboration among researchers, and serve as a dynamic and inclusive platform for sharing and advancing the state-of-the-art in Muon Catalyzed Fusion and Accelerators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The interaction of wholesale electricity market structures under futures with decarbonization policy goals: A complexity conundrum

Competitive wholesale electricity markets can help facilitate energy system decarbonization by incentivizing investments in clean energy technologies that meet evolving system needs. We explore market structure impacts on generator operations and deployment by risk-averse, heterogeneous investor firms using the Electricity Markets and Investment Suite - Agent-based Simulation (EMIS-AS) model. Here we apply clean energy targets of 45%-100% by 2035 considering energy, ancillary services, capacity, and clean energy credit products and pricing and eligibility rules. Results highlight a complexity conundrum, whereby finding the "right" market design to achieve decarbonization goals and avoid unintended consequences can be a highly-nuanced, non-incremental challenge. Carefully designed energy-only markets can achieve the same clean energy targets as capacity market structures but with different revenue and profitability outcomes. Operating reserve demand curve-based scarcity pricing can substitute capacity markets for similar deployment outcomes. Carbon pricing alone is most effective at achieving decarbonization levels at low clean energy targets, and clean energy credit markets and carbon pricing are substitutionary at high clean energy targets. Restricting technology participation in capacity and operating reserve markets can impact deployment and operations, even for nonrestricted technologies. Adding an inertia product with fast frequency response yields insufficient provision at high clean energy targets, but work is needed to understand frequency requirements and capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Split representation of adaptively compressed polarizability operator

The polarizability operator plays a central role in density functional perturbation theory and other perturbative treatment of first principle electronic structure theories. The cost of computing the polarizability operator generally scales as O(Ne4) where Ne is the number of electrons in the system. The recently developed adaptively compressed polarizability operator (ACP) formulation [L. Lin, Z. Xu and L. Ying, Multiscale Model. Simul. 2017] reduces such complexity to O(Ne 3 ) in the context of phonon calculations with a large basis set for the first time, and demonstrates its effectiveness for model problems. In this paper, we improve the performance of the ACP formulation by splitting the polarizability into a near singular component that is statically compressed, and a smooth component that is adaptively compressed. The new split representation maintains the O(Ne 3 ) complexity, and accelerates nearly all components of the ACP formulation, including Chebyshev interpolation of energy levels, iterative solution of Sternheimer equations, and convergence of the Dyson equations. For simulation of real materials, we discuss how to incorporate nonlocal pseudopotentials and finite temperature effects. In this work, we demonstrate the effectiveness of our method using one-dimensional model problem in insulating and metallic regimes, as well as its accuracy for real molecules and solids.

97 MATHEMATICS AND COMPUTING↗

Experimental Investigation of Inhibitive Drilling Fluids Performance: Case Studies from United States Shale Basins

Shale formations are attractive prospects due to their potential in oil and gas production. Some of the largest shale formations in the mainland US, such as the Tuscaloosa Marine Shale (TMS), have reserves estimated to be around 7 billion barrels. Despite their huge potential, shale formations present major concerns for drilling operators. These prospects have unique challenges because of all their alteration and incompatibility issues with drilling and completion fluids. Most shale formations undergo numerous chemical and physical alterations, making their interaction with the drilling and completion fluid systems very complex to understand. In this study, a high-pressure, high-temperature (HPHT) drilling simulator was used to mimic real time drilling operations to investigate the performance of inhibitive drilling fluid systems in two major shale formations (Eagle Ford Shale and Tuscaloosa Marine Shale). A series of drilling experiments using the drilling simulator and clay swelling tests were conducted to evaluate the drilling performance of the KCl drilling fluid and cesium formate brine systems and their effectiveness in minimizing drilling concerns. Cylindrical cores were used to mimic vertical wellbores. It was found that the inhibitive muds systems (KCl and cesium formate) provided improved drilling performance compared to conventional fluid systems. Among the inhibitive systems, the cesium formate brine showed the best drilling performances due to its low swelling rate and improved drilling performance.

04 OIL SHALES AND TAR SANDS↗

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluating aqueous flow battery electrolytes: a coordinated approach

Here, we outline some basic pitfalls in the electrochemical investigation of aqueous metal complexes and advocate for the use of bulk electrolysis in redox flow cells for electrolyte analysis. We demonstrate the methods of operation and performance of a lab scale redox flow battery (RFB), which is assembled from unmodified, commercially available material and cycled with a vanadium electrolyte in order to provide a comparative baseline of expected performance. Common misconceptions about the thermodynamic window for water splitting are addressed and further express the need to develop next-generation aqueous redox flow battery electrolytes. Although non-aqueous electrolytes are a popular approach, they suffer from distinct challenges that limit energy and power density in comparison with aqueous electrolytes. Expanding the scope of aqueous electrolytes to include metal–chelate complexes allows electrolytes to be as tailorable as organic species, while maintaining robust metal-based redox processes. A flow battery assembly and operation guide is provided to help facilitate the use of flow battery testing in the evaluation of next-generation electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving energy yield in photovoltaic modules with photonic structures

When installed outdoors, Si solar cells typically operate 20 – 30 K above ambient conditions. These elevated operating temperatures lead to diminished performance, reducing efficiency by ~0.4%/K for crystalline Si cells and decreasing module lifetime. Since much of the elevated temperature of the modules derives from parasitic absorption of sub-bandgap sunlight by the contacts, encapsulants, or other materials, reflectors that remove the sub-bandgap radiation from the module before it is absorbed promise to reduce the operating temperature. However, there are many competing strategies to reject this light: selective reflectors could be integrated into the outer module glass, at the textured Si-encapsulant interface, or on the rear. Furthermore, many of these approaches are complex and expensive to fabricate. The issue of heating can be even more critical in bifacial modules: high fractions of rear irradiance can lead to higher operating temperatures. Prior to this project, relatively little was known about the optical strategies for temperature reduction in bifacial modules. The goal of this project was to quantitatively assess optical strategies for improving the energy yield via a combination of improved anti-reflection and sub-bandgap light rejection. We studied two complementary concepts: the performance of ideal structures to determine the upper limits to performance, and low-complexity structures made from standard materials as cost-effective implementations. We also studied the performance of these reflectors in different types of modules, including Al BSF, PERC, and bifacial. Here we build from our prior accomplishments in developing mirror optimization techniques, and make use of simulation methods that accurately capture the optical properties of the modules throughout the visible and near-infrared spectrum. We connect these optical properties to energy yield under realistic, outdoor conditions. We also experimentally fabricated mirrors, incorporated them into mini-modules, and performed outdoor testing of performance at NREL. We found definitively that spectrally-selective mirrors on the outside of the module cover glass offer the best performance, both under ideal conditions and for realistic, low- complexity mirrors. Mirrors at the Si cell/encapsulant interface are limited by the multiple reflections needed to remove sub-bandgap light. Mirrors at the cell surface and mirrors on the rear also cannot remove all the sub-bandgap light, since parasitic absorption also occurs in the cover glass, encapsulant, and front contacts, depending on the module configuration. Also, cell texturing places higher demands on any cell-surface mirror because multiple interactions with the mirror are required to reject sub bandgap light which compounds losses. For bifacial modules, mirrors on the back do provide additional cooling and energy yield improvements, and the mirrors can have the same structure. In the monofacial case up to 3.3K of cooling is possible for mirrors on the front, compared to 2.2K at the cell surface and 1.2K at the rear. For bifacial modules, up to 2.4K of cooling is possible when mirrors are included at both the front and back. Our realistic designs utilize 4 – 6 layers of common photovoltaic materials such as SiO 2 , TiO 2 , and SiN x , making them more cost effective. Finally, we used our models to study thermal management in bifacial modules with different back lamination materials, finding that glass-glass laminated modules operated hotter than equivalent glass-polymer backsheet modules, due solely to the increased absorption of light incident from the rear of the module. Improving the energy yield by 2%, which is achievable with these realistic designs, would lead to LCOE reductions of $0.03/kWh by 2030. These benefits make photovoltaic panels more accessible to the public and may reduce associated maintenance costs.

14 SOLAR ENERGY↗

Data from the Development Evolution of a Vehicle for Custom Control

In order to develop custom controllers intended to operate vehicles on a live highway, a series of data collection-focused tests were performed at increasing stages of complexity. Modern vehicles with features like Adaptive Cruise Control (ACC) feature a rich set of sensors and drive-by-wire mechanisms. The presented stages of data collection begins with the analysis of raw data provided by various vehicles, and eventually results in spoofing Controller Area Network (CAN) protocols for sending control commands to operate a vehicle. This paper covers the data and technical efforts needed at various stages. The raw data and tools to plot the data are also publicly available.

99 GENERAL AND MISCELLANEOUS↗

Upgrading Fermilab’s accelerator control system with ACORN

The Fermilab Accelerator Complex is the largest national user facility in the Office of High Energy Physics (DOE/HEP) program and the only national user facility operating at Fermilab. Fermilab serves as the host to the Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment (LBNF/DUNE), the laboratory’s flagship project for neutrino science that is under construction. LBNF/DUNE will be powered by megawatt beams from an upgraded accelerator, the Proton Improvement Plan II (PIP-II) that will replace the laboratory’s aging linear accelerator with a new one based on superconducting radio-frequency cavities. The Accelerator Controls Operations Research Network (ACORN) Project will support LBNF/DUNE and PIP-II by modernizing the accelerator control system. The project is at the conceptual design phase and looking to achieve Critical Decision 1 (CD-1) later this year. The scope and structure of the project will be presented, along with an overview of how that has changed in the past year. Current design and technology choices will be shared. Specific challenges facing the project will be addressed, along with current thinking on solutions.

Roehrig, Christian [Fermilab]↗

Cobalt-Group 13 Complexes Catalyze CO 2 Hydrogenation via a Co(-I)/Co(I) Redox Cycle

The Co(-I) dihydrogen complexes, [(η 2 -H 2 )CoML]-, where ML is the group 13 metalloligand, N(o-(NCH 2 PiPr 2 )C 6 H 4 ) 3 M, and M is Al, Ga, or In, were previously reported ( J. Am. Chem. Soc. 2017, 139, 6570-6573). In this work, the related Co(-I) end-on dinitrogen adducts, [(N 2 )CoML]-, were isolated and investigated as precatalysts for CO 2 hydrogenation. The Co–Ga catalyst was highly active, achieving 19,200 formate turnovers with an initial turnover frequency of 27,000 h –1 under 34 atm of 1:1 CO 2 /H 2 and using Verkade’s proazaphosphatrane as a base at ambient temperature. The Co–Al catalyst was moderately active, while the Co–In complex was inactive. Hence, tuning the group 13 ion greatly influences the catalytic activity at the Co site. To elucidate the role of the group 13 support, experimental and theoretical mechanistic studies of the Co–Ga and Co–Al catalysts were conducted. The Co(-I) H 2 species are potent hydride donors with estimated thermodynamic hydricities (ΔG° H– ) of 32.0(1) and 37.4(1) kcal/mol in CH 3 CN for M = Al and Ga, respectively. By acting as masked Co(I) dihydrides, the Co(-I) H 2 species operate via an unusual Co(-I)/Co(I) redox cycle. After hydride transfer to CO 2 , the resulting intermediate is the Co(I) hydride complex, HCoML, which was independently synthesized and structurally characterized for M = Al and Ga. The Gibbs free energy for H 2 binding, ΔG° bind (1 atm), to generate (η 2 -H 2 )HCoML was slightly more favorable for HCoGaL (-4.2(1) kcal/mol) than for HCoAlL (-2.7(1) kcal/mol). In the subsequent step, the deprotonation reaction to regenerate the initial catalyst was much more favorable for (η 2 -H 2 )HCoGaL (pK a of 31.4, CH 3 CN) than for (η 2 -H 2 )HCoAlL (pK a of 34.3). Finally, the straightforward substitution of Al with Ga perturbs the energy profile of the catalytic reaction (|ΔΔG° H– | = 5.4 kcal/mol, |ΔΔG° bind | = 1.5 kcal/mol, and |ΔΔG° K a | = 4.0 kcal/mol) and thus provides a thermodynamic rationale for the higher catalytic efficiency of Co–Ga over Co–Al.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing scrambling and operator size distributions using random mixed states and local measurements

The dynamical spreading of quantum information through a many-body system, typically called scrambling, is a complex process that has proven to be essential to describe many properties of out-of-equilibrium quantum systems. Scrambling can, in principle, be fully characterized via the use of out-of-time-ordered correlation functions, which are notoriously hard to access experimentally. In this work, we put forward an alternative toolbox of measurement protocols to experimentally probe scrambling by accessing properties of the operator size probability distribution, which tracks the size of the support of observables in a many-body system over time. Our measurement protocols require the preparation of separable mixed states together with local operations and measurements, and combine the tools of randomized operations, a modern development of near-term quantum algorithms, with the use of mixed states, a standard tool in NMR experiments. We demonstrate how to efficiently probe the probability-generating function of the operator distribution and discuss the challenges associated with obtaining the moments of the operator distribution. We further show that manipulating the initial state of the protocol allows us to directly obtain the individual elements of the distribution for small system sizes. Published by the American Physical Society 2024

Blocher, Philip Daniel (ORCID:0000000163027567)↗

ChatBLAS: The First AI-Generated and Portable BLAS Library

We present ChatBLAS, the first AI-generated and portable Basic Linear Algebra Subprograms (BLAS) library on different CPU/GPU configurations. The purpose of this study is (i) to evaluate the capabilities of current large language models (LLMs) to generate a portable and HPC library for BLAS operations and (ii) to define the fundamental practices and criteria to interact with LLMs for HPC targets to elevate the trustworthiness and performance levels of the AI-generated HPC codes. The generated C/C++ codes must be highly optimized using device-specific solutions to reach high levels of performance. Additionally, these codes are very algorithm-dependent, thereby adding an extra dimension of complexity to this study. We used OpenAI’s LLM ChatGPT and focused on vector-vector BLAS level-1 operations. ChatBLAS can generate functional and correct codes, achieving high-trustworthiness levels, and can compete or even provide better performance against vendor libraries.

Valero Lara, Pedro↗

Modelling the Liquid Waste Operation at the Savannah River Site

Modeling Successes Dounreay – Site Closure Optimization and Risk Reduction Re-structuring and streamlining a complex project plan to achieve site decommissioning in reduced time and at reduced cost, through automated task prioritization. Idaho AMWTP – Multi-stream Optimization Speeding up a complex facility with many process lines, by utilizing all of the process lines more efficiently and reducing overall plant downtime, by coordinating repairs and shutdowns. AWE –Waste Repackaging and Relocation Relocating schedule for waste material from an old storage facility to a new purpose-built one, safely, and in a timely fashion that removed the need to reassure the safety of the old facility. Sellafield – Effluent, Sludge and HAW Treatment Improving a wide range of chemical engineered processes including aqueous effluent treatment, chemically-reactive sludge management and waste vitrification processing. Strategic Petroleum Reserve – Cavern Management Linking chemistry models of petroleum prediction, through engineering cavern management to financial modeling of gasoline sales to benefit US government

Jung, Andrew W.↗

International MNSR Training Center

Plans for the conversion of the Chinese origin miniature neutron source reactors (MNSRs) to low-enriched uranium (LEU), and the return of the high- enriched uranium (HEU) core to China, were initiated in February 2011 when an international MNSR Working Group (WG) was established to coordinate these activities. Based on a Ghana Atomic Energy Commission (GAEC) decision, the MNSR core at the GHARR-1 facility was selected for pilot shipment. Working on the preparation of the HEU MNSR materials’ removal from the GHARR-1 facility as a training tool, a mock-up MNSR vessel was built for operator training. Experiencing the usefulness of the mock-up vessel in operator training in the Ghana case has since been developed further into a full-scale training facility, named the International MNSR Training Center (IMTC), which is now available for training operators from MNSR operating countries. The main objective of this Book is to document the IMTC as a full-scale MNSR training facility in operator training for HEU MNSR core discharge and packaging. The goal is to describe the IMTC in its full complexity — that is: (1) to present the IMTC’s buildings with its internal and outer areas; (2) to provide a full listing of the installed equipment, as well as a functional description, available at the IMTC site; (3) to introduce the training materials, tutorials, and training program; and (4) to present the training sessions and Dry-run demonstration of the recently completed NIRR-1 operator training, with their experiences and lessons-learned included. This Book serves as a kind of user manual for the IMTC, which contains all of the information to launch training courses at the site at any time. The target audience for this Book is the MNSR community, especially MNSR operators and regulators who are facing HEU-LEU core conversion and HEU material transportation, who require operator training to carry out their jobs safely and professionally.

99 - GENERAL AND MISCELLANEOUS↗

Low-Rate Cycling Regeneration Sustains NMC811–Graphite Battery Performance through Extreme Ultrafast Charging

Urban air mobility (UAM) systems, such as electric vertical takeoff and landing (eVTOL) aircraft, require batteries capable of extreme ultrafast charging to support high-frequency operations. Here, in this work, we evaluate the electrochemical stability of NMC811–graphite full cells using a complex mixed-modal protocol designed to simulate the aggressive turnaround demands of UAM missions. We demonstrate that incorporating a periodic low-rate (0.3C) “regeneration” cycle enables cells to maintain 96% capacity retention over 900 cycles, despite repeated exposure to ultrafast pulses. To validate the efficacy of this regeneration mechanism, we performed simplified control experiments comparing continuous 10C charging against a 10C–0.3C interleaved protocol. Advanced characterization reveals that while mechanical particle fracture is pervasive at these rates, the regeneration cycles decelerate the electrochemical degradation by resolving spatially heterogeneous Ni oxidation states and relaxing lithium-ion concentration gradients. These findings provide a vital mechanistic framework for battery operation, proving that restorative charging can effectively delay and mitigate failure in demanding UAM applications.

batteries↗

A Real-Time Degradation Estimation Approach for Batteries in PV and Battery Hybrid Plant Operation

Conventional cyclic degradation assessment for batteries is often limited in its ability to provide real-time degradation information during operation, because the estimation of degradation is commonly performed after a specific evaluation period. Modified methods can provide real-time evaluation but at the cost of high computation complexity. This paper proposes a novel estimation method that addresses these limitations. It efficiently determines the incremental degradation of any two consecutive state-of-charge (SOC) samples during battery operation, thus enabling real-time estimation. To validate the proposed method, measurement data from lithium-ion phosphate (LFP) battery testing was adopted, and the results were compared with the conventional model and the measured capacity. The results demonstrate accuracy over the evaluation period in terms of cumulative degradation, and a reduced computation cost compared with other methods. This approach has benefits in various applications, especially in cases where batteries experience irregular charging and discharging stress cycles such as PV and battery hybrid plants.

Wang, Shumeng↗

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗