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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2020

Software Requirements for a Consequence Management Sample Data Simulator for Training and Drills

This document describes the requirements for a software tool that will enable FRMAC to simulate large sets of sample result data that is based realistically on simulated radionuclide deposition grids from NARAC. The user of this tool would be scientists involved in exercise and drill planning or part of the simulation cell of an exercise controller team. A key requirement is that this tool must be able to be run with a reasonable amount of training and job aids by any person within the Assessment, Laboratory Analysis, or Monitoring and Sampling divisions of the FRMAC to support any level of exercise from the small IPX to the national level full scale exercise. This tool should be relatively lean and stand-alone so that the user can run it in the field with limited IT resources. This document will describe the desired architecture, design characteristics, order of operations, and algorithms that can be given to a software development team to assist them in project scoping, costing, and eventually, development.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

A Perspective into Operando Methods for Probing Catalytic Interfaces

Rational design of electrocatalysts for (photo)electrochemical (PEC) processes like hydrogen and oxygen evolution and CO2 reduction reactions is aided by the recent improvements in capabilities of operando measurements, where morphology, composition, and/or function are probed during active catalysis. Through operando microscopy and spectroscopy, structure, catalytic microenvironment, oxidation state, adsorbates, and products can be measured to gain a better understanding of catalyst behavior and suggest possible improvements. Visualizing evolving catalyst morphologies, surface compositions, and electrochemical behavior also helps address many fundamental research questions for a better understanding of catalytic mechanisms. Correlating morphology with chemical identity or functional behavior using a variety of innovative microscopy methods is particularly promising for guiding development of next generation catalysts, and there are also many recent examples of using AI and robotics tools to innovate and speed development. In this Perspective, advances made over the past few years in operando imaging of catalysts relevant to solar fuels will be explored, followed by an outlook on technological developments in instrumentation, sample design, and computational power that may be applied to this field.

Catalysts↗
DOE OSTI2025

Benchmark microgravity experiments and computations for 3D dendritic-array stability in directional solidification

In this study, we present a comprehensive quantitative analysis of stability bands for dendritic arrays during directional solidification of a transparent succinonitrile-0.46 wt % camphor alloy, spanning a broad range of pulling velocities. Taking advantage of the microgravity environment aboard the International Space Station where most convection effects are suppressed, we obtain unique measurements that quantify the stable primary spacing range of spatially extended three-dimensional dendritic array structures under purely diffusive growth conditions. Through carefully designed velocity jump experiments and detailed examination of sub-grain boundary dynamics, we characterize key instabilities, including elimination and tertiary branching, shedding new light on the mechanisms governing dynamic dendritic spacing selection in extended 3D arrays. Phase field simulations are performed to characterize the stability limits of dendritic array structures for quantitative comparison with the flight experiments. Although the simulations capture general trends, significant deviations are noted at the upper stability boundary, indicating the influence of additional, unexplored factors. These findings contribute to a deeper understanding of dendritic growth dynamics and offer valuable benchmark data that could aid in refining predictive models and improving control of dendritic microstructures in metallurgical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structural and Spectroscopic Properties of Butanediol-Modified Boehmite Materials

Glycoboehmite (GB) materials are synthesized by a solvothermal reaction to form layered aluminum oxyhydroxide (boehmite) modified by intercalated butanediol molecules. These hybrid materials offer a platform to design materials with potentially novel sorption, wetting, and catalytic properties. Several synthetic methods have been used, resulting in different structural and spectroscopic properties, but atomistic detail is needed to determine the interlayer structure to explore the synthetic control of GB materials. Here, in this study, we use classical molecular dynamics (MD) simulations to compare the structural properties of GB interlayers containing chemisorbed butanediol molecules as a function of diol loading. Accompanying quantum (density functional theory, DFT) static calculations and MD simulations are used to validate the classical model and compute the infrared spectra of various models. Classical MD results reveal the existence of two unique interlayer environments at higher butanediol loading, corresponding to smaller (cross-linked) and expanded interlayers. DFT-computed infrared spectra reveal the sensitivity of the aluminol O–H stretch frequencies to the interlayer environment, consistent with the spectrum of the synthesized material. Insight from these simulations will aid in the characterization of the newly synthesized GB materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Future Circular Collider Feasibility Study Report

Volume 1 of the FCC Feasibility Report presents an overview of the physics case, experimental programme, and detector concepts for the Future Circular Collider (FCC). This volume outlines how FCC would address some of the most profound open questions in particle physics, from precision studies of the Higgs and EW bosons and of the top quark, to the exploration of physics beyond the Standard Model. The report reviews the experimental opportunities offered by the staged implementation of FCC, beginning with an electron-positron collider (FCC-ee), operating at several centre-of-mass energies, followed by a hadron collider (FCC-hh). Benchmark examples are given of the expected physics performance, in terms of precision and sensitivity to new phenomena, of each collider stage. Detector requirements and conceptual designs for FCC-ee experiments are discussed, as are the specific demands that the physics programme imposes on the accelerator in the domains of the calibration of the collision energy, and the interface region between the accelerator and the detector. The report also highlights advances in detector, software and computing technologies, as well as the theoretical tools/reconstruction techniques that will enable the precision measurements and discovery potential of the FCC experimental programme. The content and structure of this report are guided by the scope and priorities defined in the mandate of the FCC Feasibility Study. It is therefore not intended to serve as an exhaustive review of the full physics potential of FCC. Several topics, already covered in earlier reports such as the FCC CDR, are not reiterated here or are addressed only briefly, in alignment with the study’s focus. This volume reflects the outcome of a global collaborative effort involving hundreds of scientists and institutions, aided by a dedicated community-building coordination, and provides a targeted assessment of the scientific opportunities and experimental foundations of the FCC programme.

Benedikt, M. [European Organization for Nuclear Re↗
DOE OSTI2022

GeN-ROM—An OpenFOAM®-based multiphysics reduced-order modeling framework for the analysis of Molten Salt Reactors

This work presents a projection-based multiphysics Model Order Reduction (MOR) framework for the analysis of nuclear systems and its application to parametric simulations of Molten Salt Reactors (MSR). The framework, named GeN-ROM, is developed using OpenFOAM® and employs a Proper Orthogonal Decomposition aided Reduced-Basis technique (POD-RB). It can be used to reduce steady-state and transient multiphysics problems involving parametric fluid dynamics, heat exchange, and neutronics phenomena. For the treatment of structural elements in the hydraulic systems, a porous medium approach has been adopted. The reduction process is data-driven and snapshot information is extracted via POD to learn the solution manifold and to build global spatial basis functions. At the data collection phase, GeN-ROM makes use of the solvers available in GeN-Foam, a similarly OpenFOAM®-based multiphysics framework developed for the analysis of nuclear reactors. The global bases are used both to approximate the solution fields and to project the full-order equations onto lower-dimensional subspaces, thus considerably reducing the number of unknowns in a numerical system. This reduction leads to significant computational speedups, which is ideal for multi-query applications such as uncertainty quantification or design optimization. The developed tool has been tested using a 2D multiphysics model of the Molten Salt Fast Reactor (MSFR) with steady-state and transient scenarios, with speedups on the order of 10 – 10 5 .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Wide Bandgap Generation (WBGen): Developing the Future Wide Bandgap Power Electronics Engineering Workforce

This Final Technical Report (FTR) summarizes the work conducted at the Center for Power Electronics Systems (CPES) under the Wide-Bandgap Generation (WBGen) fellowship and traineeship program established by the Advanced Manufacturing and Technologies Office (AMMTO) of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy (EERE) at Virginia Tech, which had as main objective to train the next generation of U.S. citizen power engineers with wide-bandgap (WBG) power semiconductor expertise, with the intent to aid in fulfilling the future workforce needs in this field. The latter was deemed of strategic importance given the fast-paced growth observed—and predicted—in the demand of this technical expertise, whose practitioners have become the enablers and executioners of the electrification transformation process that not just the U.S., but the whole world, is currently undergoing as it seeks for more effective and efficient ways to use energy. As such, the WBGen program set forth to achieve its educational goals, which in addition sought to broaden the range of WBG-based power electronics by conducting research and development on high-efficiency grid apparatus and high-efficiency electrical power systems, and to also enhance the power engineering curriculum by formalizing WBG-oriented design procedures replacing existent yet now obsolete design procedures developed for Silicon (Si) based power electronics. This effort led CPES to spearhead the development of a new major within The Bradley Electrical and Computer Engineering (ECE) Department at Virginia Tech, namely Electronic Power and Energy Systems (EPES), which coalesced power electronics and power systems courses to provide undergraduate students with a strong formation in the power engineering field, while creating a pipeline of graduate students that could pursue the WBG-based curriculum and conduct research at CPES. In all, in what is considered a true success, eight of the twenty WBGen fellows that graduated program were recruited from the ECE department undergraduate cohort. The traineeship emphasized as well, from its beginning, the partnership with industry and national laboratories, which took advantage of the successful industry consortium at CPES that has historically been formed by 80–90 power and energy companies working in close collaboration with the center. This gave WBGen fellows the accessibility and possibility to conduct internships at partner facilities during the summer months, focused solely on the evaluation, testing, and adoption of WBG devices, which were many times tightly related to their respective research work and plans. In addition, WBGen fellows conducted their main research work within the confines of research programs at CPES conducted with these industry partners, providing them with a unique opportunity to develop not just their technical expertise—while advancing their knowledge, but to also learn and practice a slew of skills needed for their professional growth. As such, the fellows tackled a variety of WBG-related research topics, from device reliability and capability aspects as well as packaging and integration, encompassing the use of advanced materials and new structures, current sharing challenges, and insulation systems, to advanced gate-drivers with integrated sensors and protection mechanisms and active current- and voltage-based control, to optimized layouts seeking to maximize the switching and power processing performance of these devices, to power processing solutions adopting Gallium-Nitride (GaN) and Silicon-Carbide (SiC) power semiconductors for a variety of applications; including radiation-hardened converters for space dc distribution systems, direct three-phase ac-to-ac power converters for aerospace systems, dc-ac inverters for automotive traction drives, high-frequency isolated dc-dc battery chargers also for heavy transportation systems, and medium-voltage dc-dc and dc-ac converters for distribution systems and future power grids. The WBGen program ultimately graduated a total of 20 power engineers, all experts on WBG-based power electronics, awarding 18 M.S. and 2 PhD degrees in the process. These fellows, all U.S. citizens, allowed CPES to increase the number of citizens students to 33 % at the peak of the program, as the traineeship made possible the recruitment of talent with more attractive graduate research assistantship (GRA) contracts. Unfortunately, the present U.S. citizen enrollment at CPES has declined back to historic levels—approximately 10 %, as the regular GRA rates are not competitive enough when compared with entry-level industry jobs. In all, WBGen fellows published a total of 7 peer-reviewed journal articles, 44 papers at international technical conferences, made 42 presentations at international technical conferences, and filed 4 invention disclosures and patent applications, which have since then been granted by the U.S. Patent and Trademark Office (USPTO). Their contribution to CPES, Virginia Tech, the United States, and the world, has been significant, and continues to yield results thanks to the exemplary career that the fellows have initiated at many of the partners of the program, which include Wolfspeed, Raytheon Technologies, Infineon, Lockheed Martin, Dominion Energy, Northrop Grumman, Rivian, Aerospace Corporation, Sandia National Laboratory, National Renewable Energy Laboratory, John Hopkins University, and Virginia Tech.

14 SOLAR ENERGY↗
DOE OSTI2021

Sensitivity-based Similarity Metrics for New Experiment Design Optimization

The nuclear data used in advanced reactor simulations requires validation. Data from nuclear criticality experiments can provide this validation. New nuclear criticality experiment design requires extensive knowledge and expert judgement such that the experimental design parameters are selected in such a way to keep the experiment subcritical. To aide in this experimental design process, professionals can utilize sensitivity and uncertainty analysis. Sensitivity and uncertainty analysis relies on matching new application experiments with currently existing benchmark experiments. Currently, there is functionality in the Whisper 1.1 software package to calculate a similarity metric based on neutron multiplication factor sensitivity coefficients between a new application designed by the user and existing International Criticality Safety Benchmark Experiment Project (ICSBEP) benchmarks. The Whisper 1.1 software package is included in Monte Carlo N-Particle ® Code Version 6.21 (MCNP ® 6.2). This work is geared toward expanding this capability to new similarity metrics based on beta-effective sensitivity coefficients and reactivity coefficient sensitivity coefficients. While the investigation of these sensitivity coefficients is presented in detail in separate works at this same conference, this work will be primarily focused on studying the similarity metrics in more detail. These similarity metrics will then be incorporated into the optimization algorithms used for experiment design in EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data), which is a Los Alamos National Laboratory (LANL) project designed to constrain nuclear data of interest, such that adjustments can be made to possible inaccuracies. A more detailed optimization can be subsequently performed by breaking down these similarity metrics by isotope, reaction, and energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Assessing three closed-loop learning algorithms by searching for high-quality quantum control pulses

Designing a high-quality control is crucial for reliable quantum computation. Among the existing approaches, closed-loop leaning control is an effective choice. Its efficiency depends on the learning algorithm employed, thus deserving algorithmic comparisons for its practical applications. Here we assess three representative learning algorithms, including GRadient Ascent Pulse Engineering (GRAPE), improved Nelder-Mead (NMplus), and Differential Evolution (DE), by searching for high-quality control pulses to prepare the Bell state. We first implement each algorithm experimentally in a nuclear magnetic resonance system and then conduct a numerical study considering the impact of some possible significant experimental uncertainties. The experiments report the successful preparation of the high-fidelity target state by the three algorithms, while NMplus converges fastest, and these results coincide with the numerical simulations when potential uncertainties are negligible. However, under certain significant uncertainties, these algorithms possess distinct performance with respect to their resulting precision and efficiency, and DE shows the best robustness. Finally, this study provides insight to aid in the practical application of different closed-loop learning algorithms in realistic physical scenarios.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A Large Eddy Simulation Study of Flow Turbulence, Alumina Transport, and Bath Temperature Evolution in Conventional Aluminum-Smelting Cell Using OpenFOAM

In this study, a Large Eddy Simulation (LES) of the aluminum-smelting process is performed using OpenFOAM. To understand the coupled behavior of heat transfer, mass transfer, and flow of the smelting process, a multi-physics computational fluid dynamics (CFD) model based on the Eulerian–Eulerian multi-fluid approach is adopted. The model accounts for CO 2 bubble and magnetohydrodynamics (MHD)-driven flow, along with alumina dissolution, transport, and bath temperature evolution. The simulation predictions show small-scale turbulent vortical structures in the anode–cathode space caused by combined effect of MHD and CO 2 bubble-bath interactions and relatively large-scale asymmetric vortices in the inter-anode space caused by the CO 2 bubble-bath interactions. The vortex formation at the edges of the anodes evidently aids in transporting alumina from the central channel to the bottom of the anodes and prevents accumulation of gas bubbles in the periphery of the anode bottom. Symmetric bath cold spots are observed in the vicinity of the feeder. Cold spots are also observed in the anode–cathode distance space below the anode bottom due to the transport of undissolved solid to this region by the flow. The findings from the work are useful in developing and designing alumina-feeding strategy leading to reduced anode effects and smooth operation of the cell. The work also highlights the important flow structures in conventional aluminum-smelting cell.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimal resource allocation for flexible-grid entanglement distribution networks

We use a genetic algorithm (GA) as a design aid for determining the optimal provisioning of entangled photon spectrum in flex-grid quantum networks with arbitrary numbers of channels and users. After introducing a general model for entanglement distribution based on frequency-polarization hyperentangled biphotons, we derive upper bounds on fidelity and entangled bit rate for networks comprising one-to-one user connections. Simple conditions based on user detector quality and link efficiencies are found that determine whether entanglement is possible. We successfully apply a GA to find optimal resource allocations in four different representative network scenarios and validate features of our model experimentally in a quantum local area network in deployed fiber. Our results show promise for the rapid design of large-scale entanglement distribution networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Decay Dose Shielding Analysis with Hybrid Unstructured Mesh/Constructive Solid Geometry Monte Carlo Calculation and ADVANTG Acceleration

Here, the target segments of the Oak Ridge National Laboratory Second Target Station (STS) neutron production facility become highly activated due to spallation reactions or nuclei transmutation by primary protons and emitted neutrons. Once the target segments are removed from their location within the core vessel, decay dose rates must be accurately quantified to determine the shielding configurations of remote-handling tools and transport casks and to aid in planning maintenance activities. For this analysis, we utilized a hybrid unstructured mesh (UM)/constructive solid geometry approach for calculating spallation products and neutron fluxes, activation calculations using the AARE package that includes the CINDER2008 activation code to calculate the decay photon source at different cooling times, and the ADVANTG code to accelerate the final decay photon transport calculation. Both Type 316 stainless steel (SS-316) and lead were investigated as candidates for shielding materials. The decay photon transport calculation through the thick SS-316 or lead shields exhibited between 25 and 30 orders-of-magnitude attenuations in the radial direction, depending on the shield. Such a difficult shielding calculation required advanced variance reduction. ADVANTG has some missing features, which limits its usability in spallation neutron source applications. It does not support volumetric sources created for MCNP6.2 UM capability. An approximate source was created for this problem. Not only was this approximate source needed for running the ADVANTG calculation to generate the weight windows, but also it was essential to develop source biasing (SB) parameters that were crucial for dramatically accelerating the decay photon transport in this problem. With this approximate source, the analysis was completed in a very reasonable computational time, and the design of the STS remote-handling equipment was finalized. This paper compares the efficiency of Monte Carlo simulations with different weight window and SB parameters calculated using different approximate ADVANTG calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Process Heating Assessments Using DOE’s Manufacturing Energy Assessment Software for Utility Reduction (MEASUR) Tool Suite

Process heating is the most energy-intensive manufacturing process for most sectors of industry. To quantify energy savings from various energy conservation measures, the Department of Energy (DOE) sponsored the development of the Process Heating Assessment and Survey Tool (PHAST) and similar tools for other industrial systems in the early 2000s. It has been used extensively in the Save Energy Now Program’s Energy Savings Assessments and the Better Plants Program’s In-Plant Trainings. Since the initial development of the legacy tools, both computer operating systems and software development have evolved significantly. Thus, DOE has invested in the modernization of PHAST and other legacy software tools to create the Manufacturing Energy Assessment Software for Utility Reduction (MEASUR) tool suite. MEASUR offers a collection of software tools that can aid manufacturing facilities in improving the efficiency of energy systems and equipment (specifically pumps, fans, steam, and process heating) and in conducting “Energy Treasure Hunts”. Eventually, the tool will also add compressed air and process cooling systems. The Process Heating Assessment (PHA) module of MEASUR is an upgrade of the PHAST tool. PHA provides the means to model fuel-fired, steam-based, and electric process heating systems, covering process heating for most industrial plants in manufacturing sector. It also includes several key upgrades, including the ability to consider multi-component charge loads and account for several different areas of energy losses. The new tool includes a comprehensive flue gas calculator to quantify available heat and heat loss for various gaseous, liquid, and solid fuels and new heat loss calculators. It generates a report and a dynamic Sankey diagram to show the energy consumption in various areas of energy use. MEASUR has significantly improved the user experience by adopting a modern software design. This paper details the structure and workflow of PHA and presents a real-world case study to demonstrate energy savings quantification and MEASUR’s outstanding reporting capabilities.

Nimbalkar, Sachin U.↗
DOE OSTI2024

The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models

Here, we investigate whether (and how) experimental design could aid in the estimation of the precision matrix in a Gaussian chain graph model, especially the interplay between the design, the effect of the experiment and prior knowledge about the effect. Estimation of the precision matrix is a fundamental task to infer biological graphical structures like microbial networks. We compare the marginal posterior precision of the precision matrix under four priors: flat, conjugate Normal-Wishart, Normal-MGIG and a general independent. Under the flat and conjugate priors, the Laplace-approximated posterior precision is not a function of the design matrix rendering useless any efforts to find an optimal experimental design to infer the precision matrix. In contrast, the Normal-MGIG and general independent priors do allow for the search of optimal experimental designs, yet there is a sharp upper bound on the information that can be extracted from a given experiment. We confirm our theoretical findings via a simulation study comparing (i) the KL divergence between prior and posterior and (ii) the Stein’s loss difference of MAPs between random and no experiment. Our findings provide practical advice for domain scientists conducting experiments to better infer the precision matrix as a representation of a biological network.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

TX$^2$: Transformer eXplainability and eXploration

The Transformer eXplainability and eXploration (Martindale & Stewart, 2021), or TX 2 software package, is a library designed for artificial intelligence researchers to better understand the performance of transformer models (Vaswani et al., 2017) used for sequence classification. The tool is capable of integrating with a trained transformer model and a dataset split into training and testing populations to produce an ipywidget (Project Jupyter Contributors, 2021) dashboard with a number of visualizations to understand model performance with an emphasis on explainability and interpretability. The TX 2 package is primarily intended to integrate into a workflow centered around Jupyter Notebooks (Kluyver et al., 2016), and currently assumes the use of PyTorch (Paszke et al., 2019) and Hugging Face transformers library (Wolf et al., 2020). The dashboard includes visualization and data exploration features to aid researchers, including an interactive UMAP embedding graph (McInnes et al., 2018) to understand classification clusters, a word salience map that can be updated as researchers alter textual entries in near real time, a set of tools to understand word frequency and importance based on the clusters in the UMAP embedding graph, and a set of traditional confusion matrix analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Incorporating the Impacts of Climate Change on Hydrology in a Performance Assessment Model - 20403

The evidence of climate change is increasingly well-documented and impacts should be incorporated in performance assessment studies. The current climate literature provides both observational evidence and climate model projections of climate trends and/or climate change in the late 20. and early 21. centuries for North America and the northeast United States. Probabilistic modeling is a core requirement for quantifying uncertainty and evaluating its impacts. Not evaluating future climate states in a performance assessment because of the existence of uncertainty is contradictory to good modeling practices - the most uncertain issues and parameters require the most attention in effective probabilistic modeling. Excluding climate change limits development of modeling information that could aid in effective decision making. In this work we develop methods to use the output from hydrologic models and analysis of historical aerial imagery to quantify and implement the impacts of climate change on hydrologic processes at a nuclear waste site in West Valley, New York. Specifically, we used the HELP (Hydraulic Performance of Landfill Performance) model to characterize key hydrologic processes under both current and future climate conditions to assess the impacts of changing climate on hydrology. A suite of previous climatic models were reviewed and synthesized to produce a cohesive representation of the current state of knowledge of the impact of climate change on important model inputs such as precipitation. Output from the HELP simulations was coupled to the GoldSim model that was used to develop the Probabilistic Performance Assessment (PPA) approach through the application of a novel 'nearest neighbor' technique. First, several thousand realizations were generated from the HELP model using a Latin Hypercube experimental design to ensure adequate coverage of the parameter space of explanatory variables used to drive HELP. For example, porosity is a physical parameter that is used as an input to both HELP and the GoldSim PA model. We then ran sensitivity analysis (SA) algorithms on the output of HELP for each of the responses of interest. For each predictor, each time we build an SA model we get a different value for the sensitivity index (SI). From the collection of all the SA models, the average was computed among all of the SIs to represent the predictor within the context of the nearest neighbor approach. That is, we conduct SA on each HELP outcome for each scenario. This gives us parameter sensitivity indices for the outcomes. We average the parameter sensitivity indices across the outcomes to get the average SI for a scenario. For each realization that is generated from the Goldsim PA model, Goldsim generates random values for physical/empirical parameters that HELP uses as well. For each vector of physical/empirical parameters that Goldsim generates, the vector from the 5,000 HELP runs that is most 'similar' to the Goldsim vector is computed using the nearest neighbor approach. In this context 'similar' means minimization of the SA-weighted sum of the absolute differences among the 5,000 values computed for this statistic, where each value corresponds to a different HELP realization. In order to account for the impacts of climate change, this process was repeated using the spatially downscaled future climate projections. For each of the key parameters of interest, it was assumed that a linear change depicted the relationship between the values for the present day and those for 2100. In this way, the climatically-driven changes in key parameters used to inform the GoldSim model are quantified and incorporated into the PA model output for the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗