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Diagnostics of Data-Driven Models: Uncertainty Quantification of PM7 Semi-Empirical Quantum Chemical Method

Abstract We report an evaluation of a semi-empirical quantum chemical method PM7 from the perspective of uncertainty quantification. Specifically, we apply Bound-to-Bound Data Collaboration, an uncertainty quantification framework, to characterize (a) variability of PM7 model parameter values consistent with the uncertainty in the training data and (b) uncertainty propagation from the training data to the model predictions. Experimental heats of formation of a homologous series of linear alkanes are used as the property of interest. The training data are chemically accurate , i.e., they have very low uncertainty by the standards of computational chemistry. The analysis does not find evidence of PM7 consistency with the entire data set considered as no single set of parameter values is found that captures the experimental uncertainties of all training data. A set of parameter values for PM7 was able to capture the training data within ±1 kcal/mol, but not to the smaller level of uncertainty in the reported data. Nevertheless, PM7 was found to be consistent for subsets of the training data. In such cases, uncertainty propagation from the chemically accurate training data to the predicted values preserves error within bounds of chemical accuracy if predictions are made for the molecules of comparable size. Otherwise, the error grows linearly with the relative size of the molecules.

42 ENGINEERING↗

Development of Efficient Process for Manufacturing of Thermoplastic Composites with Tailored Properties (CRADA 511)

This is a collaborative effort between Battelle Memorial Institute as manager and operator of Pacific Northwest National Laboratory (PNNL) and ESI North America Inc. (“ESI” or “Participant”) to apply computation and data analytics to the challenge of light weighting with a focus on the battery enclosures of electric vehicles (EVs). EVs use heavy batteries to increase range and power. A complex-shaped battery enclosure is required to meet a host of challenging performance requirements. The ability to virtually develop composite parts such as battery enclosure with tailored properties to meet required performance will be highly valuable to the automotive industry. However, efficient simulation of composite-manufacturing processes remains a challenging issue since simulation involves multiscale models in space and time, highly non-linear and anisotropic behavior, strongly coupled multi-physics, and complex geometries. This work will advance the state of the art by reducing the computational burden of composite optimization by using simulation data from a limited number of configurations off-line and then developing a reduced order model (ROM) using data analytics and machine learning (ML). Develop a data driven approach to link features of the material and manufacturing processes to the mechanical properties of thermoplastic composite parts.

42 ENGINEERING↗

Downselection and Basic Properties of Additively Manufactured ODS Alloys

In the AMMT program the work package for development of new materials aimed to explore the advanced manufacturing techniques that are feasible for the manufacturing of advanced materials components. A merit-based feasibility study was attempted to identify an accelerated development path for dispersion strengthened (ODS) alloys by creatively combining additive manufacturing (AM) technologies with the recent advances in ODS materials and traditional manufacturing technologies. For the fiscal year, the primary tasks were focused to develop additive manufacturing (AM) and post-build processing route for oxide dispersion strengthened (ODS) ferritic (Fe-Cr alloy or 14YWT) and austenitic (Fe-Cr-Ni alloys or 316L and 316H) alloys and to perform basic microstructural and mechanical characterizations to provide feedbacks to the alloy and processing design. Further, the multi-laboratory effort created collaboratively a decision criteria matrix to evaluate and downselect the new materials processed by advanced manufacturing methods. This report is to describe the ODS alloy processing routes combining AM processes and post-build thermomechanical treatments, mechanical and microstructural characteristics of the newly developed materials, and the application results of the decision criteria matrix for the AM ODS alloys including a downselected material and feasible processing route. Key mechanical test results including tensile strength, tensile ductility, and fracture toughness data and are reported and explained. Higher strength was measured from the ferritic ODS alloys, while higher ductility and fracture toughness were measured from the austenitic ODS alloys. Many of the decision criteria were scored the same for the AM ferritic and austenitic ODS alloys, however, the generally known fact that the austenitic alloys have higher corrosion resistance and significantly better ductility. Although these scores are not significantly different to make them highly discernable, the austenitic ODS alloys were downselected to be the primary materials group in the future research on ODS materials in AMMT program.

36 MATERIALS SCIENCE↗

Multiphase Fluid Flow in Deformable Variable-Aperture Fractures (Final Report, February 1, 2009 – January 31, 2014)

Fractures provide flow paths that can potentially lead to fast migration of fluids or contaminants. A number of energy-­related applications involve fluid injections that significantly perturb both the pressures and chemical composition of subsurface fluids. These perturbations can cause both mechanical deformation and chemical alteration of host rocks with potential for significant changes in permeability. In fractured rock subjected to coupled chemical and mechanical stresses, it can be difficult to predict the sign of permeability changes, let alone the magnitude. This project integrated experimental and computational studies to improve mechanistic understanding of these coupled processes and develop and test predictive models and monitoring techniques. The project involved three major components: (1) study of two-­phase flow processes involving mass transfer between phases and dissolution of minerals along fracture surfaces (Detwiler et al., 2009; Detwiler, 2010); (2) study of fracture dissolution in fractures subjected to normal stresses using experimental techniques (Ameli, et al., 2013; Elkhoury et al., 2013; Elkhoury et al., 2014) and newly developed computational models (Ameli, et al., 2014); (3) evaluation of electrical resistivity tomography (ERT) as a method to detect and quantify gas leakage through a fractured caprock (Breen et al., 2012; Lochbuhler et al., 2014). The project provided support for one PhD student (Dr. Pasha Ameli; 2009-­2013) and partially supported a post-­doctoral scholar (Dr. Jean Elkhoury; 2010-­2013). In addition, the project provided supplemental funding to support collaboration with Dr. Charles Carrigan at Lawrence Livermore National Laboratory in connection with (3) and supported one MS student (Stephen Breen; 2011-­2013). Major results from each component of the project include the following: (1) Mineral dissolution in fractures occupied by two fluid phases (e.g., oil-­water or water-­CO 2 ) causes changes in local capillary forces and redistribution of fluids. These coupled processes enhance channel formation and the potential for development of fast flow paths through fractures. (2) Dissolution in fractures subjected to normal stress can result in behaviors ranging from development of dissolution channels and rapid permeability increases to fracture healing and significant permeability decreases. The timescales associated with advective transport of dissolved ions in the fracture, mineral dissolution rates, and diffusion within the adjacent porous matrix dictate the sign and magnitude of the resulting permeability changes. Furthermore, a high--resolution mechanistic model that couples elastic deformation of contacts and aperture-­dependent dissolution rates predicts the range of observed behaviors reasonably well. (3) ERT has potential as a tool for monitoring gas leakage in deep formations. Using probabilistic inversion methods further enhances the results by providing uncertainty estimates of inverted parameters.

02 PETROLEUM↗

Construction Methodology Transformation for the Benefit of Workforce Development

Construction is a key economic engine driving both national and global economies. While manual, onsite construction methods dominate the U.S. construction industry, a major shift towards offsite methods has been underway due to its efficiency, speed, and potential cost savings. The workforce necessary for offsite construction growth does not exist in its current form because of the focus on onsite methodologies and the lack of exposure to offsite building methods at all levels of a student’s learning journey. The growth of the U.S. construction industry and competitiveness in an increasingly global construction market over the coming decades can only be supported by a dramatic increase in the use of offsite methods, which requires ramping up workforce training for certain skillsets. The goal of Construction Methodology Transformation for the Benefit of Workforce Development was to understand the opportunities and barriers in both education and industry and to identify best practices for offering curriculum and training to educators, industry, and students that would support skills needed for careers in offsite construction. Our team proposed combining three offsite construction workforce development needs: content development, exposure and training, and job placement - under a single Platform model that would increase experience and career opportunities for students and help match them with potential industry members. Through our proposed solution we expected to see: developed offsite curriculum being utilized by educators and students; an increase in the identification of construction technology and offsite construction methods; an average increase in knowledge gain of at least 25% after participation in pilots; better equipped candidates who are prepared for jobs in offsite construction; and a beta workforce development platform that helps build more pathways for students looking for careers in offsite construction. The two pilots included almost 250 students and resulted in an average knowledge gain of 37 percent. Our research has identified areas of opportunity, for both education and industry to make collaborative training programs more efficient and successful. The chosen techniques for this program are extremely effective when both the school and factory have solid processes and cultures in place to accept students into training programs. This project serves as an important stepping stone to industrywide collaboration to move workforce development for offsite construction forward across the country. With continued collaboration programs like this can provide much needed early exposure and training in offsite construction and we can begin to fill important positions for the future of construction.

99 GENERAL AND MISCELLANEOUS↗

2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗

Coherent dynamics in the rotor tip shear layer of utility-scale wind turbines

Here, recent field experiments conducted in the near wake (up to 0.5 rotor diameters downwind of the rotor) of a Clipper Liberty C96 2.5 MW wind turbine using snow-based super-large-scale particle image velocimetry (SLPIV) were successful in visualizing tip vortex cores as areas devoid of snowflakes. The so-visualized snow voids, however, suggested tip vortex cores of complex shape consisting of circular cores with distinct elongated comet-like tails. We employ large-eddy simulation (LES) to elucidate the structure and dynamics of the complex tip vortices identified experimentally. We show that the LES, with inflow conditions representing as closely as possible the state of the flow approaching the turbine when the SLPIV experiments were carried out, reproduce vortex cores in good qualitative agreement with the SLPIV results, essentially capturing all vortex core patterns observed in the field in the tip shear layer. The computed results show that the visualized vortex patterns are formed by the tip vortices and a second set of counter-rotating spiral vortices intertwined with the tip vortices. To probe the dependence of these newly uncovered coherent flow structures on turbine design, size and approach flow conditions, we carry out LES for three additional turbines: (i) the Scaled Wind Farm Technology (SWiFT) turbine developed by Sandia National Laboratories in Lubbock, TX, USA; (ii) the wind turbine developed for the European collaborative MEXICO (Model Experiments in Controlled Conditions) project; and (iii) the model turbine, and the Clipper turbine under varying inflow turbulence conditions. We show that similar counter-rotating vortex structures as those observed for the Clipper turbine are also observed for the SWiFT, MEXICO and model wind turbines. However, the strength of the counter-rotating vortices relative to that of the tip vortices from the model turbine is significantly weaker. We also show that incoming flows with low level turbulence attenuate the elongation of the tip and counter-rotating vortices. Sufficiently high turbulence levels in the incoming flow, on the other hand, tend to break up the coherence of spiral vortices in the near wake. To elucidate the physical mechanism that gives rise to such rich coherent dynamics we examine the stability of the turbine tip shear layer using the theory. We show that for all simulated cases the theory consistently indicates the flow to be unstable exactly in the region where counter-rotating spirals emerge. We thus postulate that centrifugal instability of the rotating turbine tip shear layer is a possible mechanism for explaining the phenomena we have uncovered herein.

17 WIND ENERGY↗

EV SALaD 2023 Demonstration: Best Practices and Mitigations for Protecting EVSE Infrastructure

The Electric Vehicle Secure Architecture Laboratory Demonstration (EV SALaD) program is a demonstration of cybersecurity best practices for high-power electric vehicle (EV) charging infrastructure led by Idaho National Laboratory (INL), in collaboration with other DOE National Laboratories participating in the EVs at Scale Consortium.a Sandia National Laboratories (SNL) and Pacific Northwest National Laboratory (PNNL) participated in the first 2-year (FY22-23) demonstration cycle for EV SALaD. This report documents the FY23 demonstration, the second in a series of demonstrations and collaborations in deploying and operating cybersecure EV charging infrastructure. It includes a summary of improvements from the FY22 demonstration, technical analysis of the FY23 demonstration, how the research demonstrates cyber-physical and cybersecurity best practices for high-power EV charging infrastructure, and related impacts to national and energy security. For EV SALaD, the FY22 demonstration focused on the detection, ranking, and prioritization of anomalous events for high-power EV charging. The FY23 demonstration additionally included the demonstration of cybersecurity best practices, which included protection and mitigation solutions to prevent, respond, and recover from anomalous events. During the demonstrations, the multi-lab EV SALaD team conducted a Test Effect Payload (TEP)b evaluation on extreme fast charger (XFC) hardware equipped with Cerberus, a detection and response solution, to demonstrate anomaly detection and mitigation cybersecurity best practices against cyber-enabled events.

33 ADVANCED PROPULSION SYSTEMS↗

Preliminary Content Evaluation of the North Anna High Burn-Up Sister Fuel Rod Segments for Transportation in the 10-160B and NAC-LWT

The U.S. Department of Energy’s (DOE’s) Used Fuel Disposition Campaign (UFDC) Program has transported high-burnup nuclear sister fuel rods from a commercial nuclear power plant for purposes of evaluation and testing. The evaluation and testing of high-burnup used nuclear fuel is integral to DOE initiatives to collect information useful in determining the integrity of fuel cladding for future safe transportation of the fuel, and for determining the effects of aging, on the integrity of UNF subjected to extended storage and subsequent transportation. The UFDC Program, in collaboration with the U.S. Nuclear Regulatory Commission and the commercial nuclear industry, has obtained individual used nuclear fuel rods for testing. The rods have been received at Oak Ridge National Laboratory (ORNL) for both separate effects testing (SET) and small-scale testing (SST). To meet the research objectives, testing on multiple 6 inch fuel rod pins cut from the rods at ORNL will be performed at Pacific Northwest National Laboratory (PNNL). Up to 10 rod equivalents will be shipped. Options were evaluated for multiple shipments using the 10-160B (based on 4.5 rod equivalents) and a single shipment using the NAC-LWT. Based on the original INL/Virginia Power transfer agreement, the rods are assumed to 152 inches in length with a 0.374-inch diameter. This report provides a preliminary content evaluation for use of the 10-160B and NAC-LWT for transporting those fuel rod pins from ORNL to PNNL. This report documents the acceptability of using these packagings to transport the fuel segments from ORNL to PNNL based on the following evaluations: enrichment, A2 evaluation, Pu-239 FGE evaluation, heat load, shielding (both gamma and neutron), and content weight/structural evaluation.

10-160B↗

Results from an International Interlaboratory Study on Light- and Elevated Temperature-Induced Degradation (LETID) in Solar Modules

This presentation reports recently submitted results from an international interlaboratory comparison study on light- and elevated temperature-induced degradation (LETID) on crystalline silicon photovoltaic (PV) modules. A large global network of PV module manufacturers and PV testing laboratories collaborated to design a protocol for LETID detection, and screen a large and diverse set of prototype modules for LETID. We summarize the range of observed degradation and provide initial conclusions on the reproducibility of results across labs. In LETID-sensitive modules, both open-circuit voltage (VOC) and short-circuit current (ISC) degrade by a roughly similar magnitude. We observe, as do previous studies, that LETID affects each cell in a module differently. An investigation of the potential mismatch losses caused by nonuniform LETID degradation found that mismatch loss is insignificant compared to the direct LETID-related losses. We summarize the conclusions drawn from the study, provide an update on a forthcoming standard technical specification for LETID testing of PV modules (IEC TS 63342 ED1), and discuss unresolved questions and potential future work on LETID in PV modules.

degradation↗

Model-based verification of I and C specifications - 184

In the field of nuclear I and C (Instrumentation and Control), the late detection of errors in the specifications and the design of I and C has a strong impact in terms of time and money. The early verification in the V cycle of I and C functions is a key issue to capture inconsistencies and errors before the implementation and on-site tests. EDF, in the framework of the collaborative project CONNEXION, has investigated methods based on simulation to formalize I and C requirements and to evaluate them at the conceptual and basic design phases. Behavioral models of the physic parts of the system and I and C functions, described as functional diagrams, are co-simulated in an integration environment based on the FMI (Functional Mockup Interface) standard. In this specific environment, test scenarios are performed on these models. These scenarios are defined on the basis of a high level model of the studied system that takes into account the states to cover (in normal and degraded situations). Requirements, once formalized, are translated into observers that evaluate their fulfillment during the simulations. Simulation logs are then a tool for the designer to analyze the causes of the possible non-fulfillment of requirements and to fix the corresponding errors in the specifications. The proposed methodology enables to detect errors in the specifications of I and C functions, to generate automatically functional test scenarios taking into account the coverage of the requirements and all the different operational modes of the system. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Project Management Plan/Progress Report: UT/GTKS Training Program Development for Commercial Building Operators (Final Report)

Universidad del Turabo (UT), in a collaborative effort with Global Turn Key Services, Inc. (GTKS), proposed to develop a training program and a commercialization plan for the development of Commercial Building Operators (CBOs). The CBOs will operate energy efficient buildings to help maintain existing buildings up to their optimal energy performance level, and ensure that net-zero-energy buildings continuously operate at design specifications, thus helping achieve progress towards meeting BTP Strategic Goals of creating technologies and design approaches that enable net-zero-energy buildings at low incremental costs by 2025. The proposed objectives were then: (1) Develop a Commercial Building Operator (CBO) training program and accreditation that will in turn provide a certification to participants recognized by Accreditation Boards such as the North American Board of Certified Energy Practitioners (NABCEP) and Leadership in Energy & Environmental Designs (LEED). (2) Develop and implement a commercialization and sustainability plan that details marketing, deployment, financial characterization, job placement, and other goals required for long-term sustainability of the project after the funding period. (3) After program development and deployment, provide potential candidates with the knowledge and skill sets to obtain employment in the commercial building green energy (net-zero-energy building) job market. The developed CBO training program will focus on providing skills for participants, such as displaced and unemployed workers, to enter the commercial building green energy (net-zeroenergy building) job market. This course was designed to allow a participant with minimal to no experience in commercial building green technology to obtain the required skill sets to enter the job market in as little as 12 weeks of intensive multi-faceted learning. After completion of the course, the CBO staff concluded the participant will meet minimum established accreditation standards established by UT and will complete the contact hours required of training to apply to the Certification on Energy Management (CEM) offered by the Association of Energy Engineers (AEE). The CBO training program consists of a combination of theory (classroom), online & computer simulation, laboratory & hands on (onsite) training lessons. The training is addressed four basic learning elements: (1) Learn the Technology; (2) Practice Skills with hands-on the Energy Simulation Builder program; (3) Final Project and Presentation; and, (4) Accreditation and Certifications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Surface Acoustic Wave Sensors for Refrigerant Leak Detection: Compact, Inexpensive, Selective and Sensitive Sensors

Pacific Northwest National Laboratory (PNNL), in collaboration with Parker and Hannifin, is developing a compact, inexpensive, and highly sensitive and selective surface acoustic wave sensor coated with fluorophillic sorbent for detecting fluorocarbon leaks from HVAC systems. Having a highly effective sorbent sensitive to fluorocarbon refrigerant vapors provides a means to develop a sensing device for leak detection. Surface acoustic wave (SAW) sensors with a gas sensing film deposited between the delay lines or on the interdigital transducer have been used to detect gas and vapor molecules in harsh environments with high sensitivity. As part of this project, PNNL screened several sorbent materials that are shown to be selective towards fluorocarbon refrigerant (R32) molecule. The identified sorbent materials were synthesized, characterized, and tested towards R32 using various spectroscopic technique. Next, the sorbent material was coated on a SAW sensor as a thin film using vapor deposition and drop coating methods. The coated thin film was further characterized and tested towards the detection of pure R32 and R32 in ambient air at room temperature to demonstrate the SAW response towards R32 in presence of other competing gases and vapors in air.

42 ENGINEERING↗

Optimized Uncertainty Quantification Algorithm Within a Dynamic Event Tree Framework

Methods for developing Phenomenological Identification and Ranking Tables (PIRT) for nuclear power plants have been a useful tool in providing insight into modelling aspects that are important to safety. These methods have involved expert knowledge with regards to reactor plant transients and thermal-hydraulic codes to identify are of highest importance. Quantified PIRT provides for rigorous method for quantifying the phenomena that can have the greatest impact. The transients that are evaluated and the timing of those events are typically developed in collaboration with the Probabilistic Risk Analysis. Though quite effective in evaluating risk, traditional PRA methods lack the capability to evaluate complex dynamic systems where end states may vary as a function of transition time from physical state to physical state . Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. A limitation of DPRA is its potential for state or combinatorial explosion that grows as a function of the number of components; as well as, the sampling of transition times from state-to-state of the entire system. This paper presents a method for performing QPIRT within a dynamic event tree framework such that timing events which result in the highest probabilities of failure are captured and a QPIRT is performed simultaneously while performing a discrete dynamic event tree evaluation. The resulting simulation results in a formal QPIRT for each end state. The use of dynamic event trees results in state explosion as the number of possible component states increases. This paper utilizes a branch and bound algorithm to optimize the solution of the dynamic event trees. The paper summarizes the methods used to implement the branch-and-bound algorithm in solving the discrete dynamic event trees.

42 ENGINEERING↗

Investigating Deformation and Failure Mechanisms in Nanoscale Multilayer Metallic Composites

Over the history of materials science there are many examples of materials discoveries that have made superlative materials; the strongest, lightest, or toughest material is almost always a goal when we invent new materials. However, often these have been a result of enormous trial and error approaches. A new methodology, one in which researchers design, from the atoms up, new ultra-strong materials for use in energy applications, is taking hold within the science and engineering community. This project focused on one particular new classification of materials; nanolaminate metallic composites. These materials, where two metallic materials are intimately bonded and layered over and over to form sheets or coatings, have been shown over the past decade to reach strengths over 10 times that of their constituents. However, they are not yet widely used in part because while extremely strong (they don’t permanently bend), they are also not particularly tough (they break relatively easily when notched). Our program took a coupled approach to investigating new materials systems within the laminate field. We used computational materials science to explore ways to institute new deformation mechanisms that occurred when a tri-layer, rather than the more common bi-layer system was created. Our predictions suggested that copper-nickel or copper-niobium composites (two very common bi-layer systems) with layer thicknesses on the order of 20 nm and then layered 100’s of times, would be less tough than a copper-nickel-niobium metallic composite of similar thicknesses. In particular, a particular mode of permanent deformation, cross-slip, could be activated only in the tri-layer system; the crystal structure of the other bi-layers would prohibit this particular mode of deformation. We then experimentally validated this predication using a wide range of tools. We utilized a DOE user facility, the Center for Integrated Nanotechnology (CINT), to fabricate, for the first time, these tri-layer composites. CINT formed nanolaminate composites were tested in tension, with bulge testing, using nanoindentation, and using micro-compression testing to demonstrate that the tri-layer films were indeed tougher and hardened more during deformation (they got stronger as we deformed them) than equivalent bi-layers. The seven graduate students, 4 post-docs and research faculty, and the two faculty co-PI’s were able to create a collaborated computational prediction and experimental validation team to demonstrate the benefits of this class of materials to the community. The computational work crossed from atomistic to bulk simulations, and the experiments coupled form nm-scale to the mm scale; closely matching the simulations. The simulations provided viable mechanisms that explained the observed results, and new experimental results were used to push the boundaries of the simulation tools. Over the life of the 7 years of this program we proved that tri-layer nanolaminate metallic composite systems exceeded the mechanical performance of bi-layer systems if the right materials were chosen, and that the mechanism responsible for this was tied to the cross slip of dislocations. With 30 journal publications resulting from this work we have broadly disseminated this family of results to the scientific community.

36 MATERIALS SCIENCE↗

2019 accomplishments: degradation of mechanical properties in structural metals and welds for FTS reservoirs

This report documents work in 2019 at SRNL in support of the Aging and Lifetimes program. Specimens for fracture toughness testing were prepared in prior years by thermally pre-charging samples, provided by Sandia National Laboratories, of welded types 304L and 21-6-9 stainless steels. These samples were pre-charged in 2017. The fracture toughness of the first aged specimens was measured and compared to historical data. The measurements of the 304L and 21-6-9 weld and particularly HAZ represent some of the first fracture data relevant to modern GTS reservoirs. This work represents an on-going collaboration between SRNL and SNL to understand tritium embrittlement of structural metals in Gas Transfer System reservoirs which informs lifetime assessments. Continued testing was conducted on ongoing historical studies, including the effects of very long-term aging, and the relative performance of differently forged stockpile relevant 304L and 316L samples. New samples were pre-charged with tritium and placed in a freezer for an aging study to allow helium to build into the material. The precharged samples consist of smooth and notched tensile samples of 304L stainless steel, as well as tube tensile samples of different thermal treatments supplied by Sandia National Laboratories. Their charging marks the beginning of a new sequence of studies to explore fundamental deformation mechanisms underpinning tritium embrittlement. At predesignated times, samples will be removed from aging and tested to provide data which will help develop an understanding of material degradation with increasing aging time. Also documented is progress in employing various advanced characterization techniques including high resolution electron microscopy, thermally programed desorption, and small angle x-ray scattering, as well as facilities renovations and equipment procurements in support of sustained tritium impacts on materials program at SRNL.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Numerical Investigation of Fluid Flow and Space Charge in Liquid Argon Time Projection Chamber (LArTPC) Detectors

Overview This project focused on developing a high-fidelity numerical framework to simulate the multiphysics environment within Liquid Argon Time Projection Chamber (LArTPC) detectors. The primary objective was to characterize the complex interplay between ion transport, background fluid dynamics, and electric field distortions—a critical factor for the calibration and sensitivity of next-generation High Energy Physics experiments, such as DUNE. Technical Achievements The research successfully yielded a hybrid numerical space-charge solver utilizing a Cell-Centered Finite Volume Method (FVM) for ion transport coupled with a Finite Element Method (FEM) for electric potential. Key accomplishments include: • Verification & Validation: The 3-D solver was rigorously verified against 1-D analytical solutions, demonstrating high numerical accuracy in predicting space-charge-induced field deviations. • Field Distortion Analysis: 3D simulations revealed that space charge effects introduce significant non-uniformities in the electric field. Critically, the research identified that background LAr flow velocities, when comparable to ion drift velocities, markedly exacerbate these distortions. • Technology Transfer: The resulting source code and comprehensive user manuals were successfully transferred to collaborators at Fermilab, providing a portable computational tool for the broader scientific community. Challenges and Future Directions While the space-charge solver achieved all performance metrics, the integrated fluid dynamics modeling encountered convergence challenges stemming from the extreme 200-fold disparity in length scales between the detector's 37 mm inlet pipes and the 8-meter global domain. To address this, the project has identified a clear technical pivot toward Hierarchical Geometric Adaptive Mesh Refinement (HG-AMR). By implementing an h-type refinement strategy with hanging nodes, future iterations of this solver will be capable of resolving localized high-gradient inlet flows without the prohibitive computational costs of regular grids. This advancement, combined with data-driven uncertainty quantification based on MicroBooNE-style calibration, will enable the precise modeling of detector responses in large-scale cryogenic environments where direct measurement remains difficult. Impact The computational tools developed under this award provide a foundation for enhancing the energy resolution and spatial reconstruction of noble liquid detectors. By bridging the gap between theoretical fluid dynamics and experimental field calibration, this work supports the DOE’s mission to advance the frontiers of neutrino physics and dark matter detection.

42 ENGINEERING↗

The CLAS12 superconducting magnets

As part of the Jefferson Lab 12 GeV upgrade, the Hall B CLAS12 system requires two superconducting iron-free magnets — a torus and a solenoid. The physics requirements to maximize space for the detectors guided engineers toward particular coil designs for each of the magnets which, in turn, led to the choice of using conduction cooling. The torus consists of 6 trapezoidal NbTi coils connected in series with an operating current of 3770 A. The solenoid is an actively shielded 5 T magnet consisting of 5 NbTi coils connected in series operating at 2416 A. Within the hall, the two magnets are located in close proximity to each other and are completely covered both inside and outside by particle detectors. Stringent size limitations were imposed for both magnets and introduced particular design and fabrication challenges. This paper describes the design, construction, installation, commissioning, and operation of the two magnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗