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DOE OSTI2025

Micromechanical response of SiC-OPyC layers in TRISO fuel particles

Tristructural isotropic (TRISO)–coated particle fuel is a proposed fuel for multiple advanced reactor concepts. The performance of the particle depends on whether the silicon carbide (SiC) layer remains intact to prevent the release of metallic and gaseous fission products. Mechanical fracture of the SiC layer is a potential failure mode under various fuel configurations and operating environments, including the potential transmission of matrix-originating cracks through TRISO particles. Furthermore, this study uses instrumented indentation techniques on cross-sectioned surrogate particles to examine the mechanical stability of the critical interface between SiC and the outer pyrolytic carbon (OPyC) layer. The observed behavior at the interface is rationalized by examining the radially dependent fracture behavior of the SiC layer and performing a numerical analysis to quantify the residual stresses that develop during the processing and cross-sectioning of the as-fabricated particle. Characterizing the SiC-OPyC interface of surrogate TRISO particles using nanoindentation provides unique insight into the interface's room-temperature residual stress and mechanical stability. The modeling efforts were used to investigate the experimental procedure further, and the results are presented herein to validate this fuel form's potential mechanical failure modes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Multicycle large-eddy simulations of a direct-injection hydrogen-fueled optical engine

Hydrogen (H 2 ) is a carbon-free chemical energy carrier and one promising solution for achieving effective decarbonization of the transportation sector, particularly for internal combustion engines (ICEs). With a focus on ICEs, and compared to port-fuel injection, direct injection (DI) of gaseous H 2 during the compression stroke offers potential advantages, which include backfire avoidance and reduction of preignition occurrence. In these last two decades, much research, experimental and numerical, has been devoted to understanding H 2 's mixing and combustion processes in ICEs. Computational fluid dynamics modeling efforts commonly rely on unsteady Reynolds-averaged Navier Stokes (URANS) turbulence frameworks, mostly due to their computational affordability. However, many authors have pointed out the opportunity to perform large-eddy simulations (LESs) to investigate the cyclic variability of H 2 engines and assess potential advantages of using LES in place of URANS, especially for lean operation. This study addresses this knowledge gap and presents a computational fluid dynamics (CFD) study of the H 2 DI process in an optical engine operating at relatively low tumble conditions, using multicycle LESs. In conclusion, the manuscript presents a thorough validation of the results against experimental data available from the literature as well as direct comparison with URANS, demonstrating the feasibility of multicycle LESs for CFD modeling of DI H 2 -fueled ICEs.

Direct injection↗

DOE OSTI2024

Computational study on the impact of gasoline-ethanol blending on autoignition and soot/NO x emissions under low-load gasoline compression ignition conditions

Here, in the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine are performed to investigate the impact of gasoline-ethanol blending on autoignition, nitrogen oxide (NO x ), and soot emissions under low-load conditions. In order to represent the test gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF)+ethanol (ETPRF) surrogate (with 10% ethanol by volume; E10) is employed. A three-dimensional (3D) engine CFD model employing finite-rate chemistry with a skeletal kinetic mechanism (including NO x sub-mechanism), adaptive mesh refinement (AMR), and hybrid method of moments (HMOM) is adopted to capture the in-cylinder combustion phenomena and soot/NO x emissions. The engine CFD model is validated against experimental data for three gasoline-ethanol blends: E10, E30 and E100, with varying ethanol content by volume. Model validation is carried out for a broad range of start-of-injection (SOI) timings (−21, −27, −36, and −45 crank angle degrees (°CA) after top-dead-center (aTDC)) with respect to in-cylinder pressure, heat release rate, combustion phasing, NO x and soot emissions. For relatively later injection timings (−21 and −27 °CA aTDC), E30 yields higher amount of soot than E10; while the trend reverses for early injection cases (−36 and −45 °CA aTDC ). On the other hand, E100 yields the lowest amount of soot among all fuels irrespective of SOI timing. Further, E10 shows a non-monotonic trend in soot emissions with SOI timing: SOI-36>SOI-45>SOI-21>SOI-27, while soot emissions from E30 exhibit monotonic decrease with advancing SOI timing. NO x emissions from various fuels follow a trend of E10>E30>E100. On the other hand, NO x emissions increase as SOI timing is advanced for all fuels, with an anomaly for E10 and E100 where NO x decreases when SOI is advanced beyond −36 °CA aTDC. Detailed analysis of the numerical results is performed to investigate the soot/NO x emission trends and elucidate the impact of chemical composition and physical properties on autoignition and emissions characteristics.

Computational fluid dynamics↗

DOE OSTI2023

Flexible, integrated modeling of tokamak stability, transport, equilibrium, and pedestal physics

The STEP (Stability, Transport, Equilibrium, and Pedestal) integrated-modeling tool has been developed in OMFIT to predict stable, tokamak equilibria self-consistently with core-transport and pedestal calculations. STEP couples theory-based codes to integrate a variety of physics, including magnetohydrodynamic stability, transport, equilibrium, pedestal formation, and current-drive, heating, and fueling. The input/output of each code is interfaced with a centralized ITER-Integrated Modelling & Analysis Suite data structure, allowing codes to be run in any order and enabling open-loop, feedback, and optimization workflows. This paradigm simplifies the integration of new codes, making STEP highly extensible. STEP has been verified against a published benchmark of six different integrated models. Core-pedestal calculations with STEP have been successfully validated against individual DIII-D H-mode discharges and across more than 500 discharges of the H98,y2 database, with a mean error in confinement time from experiment less than 19%. STEP has also reproduced results in less conventional DIII-D scenarios, including negative-central-shear and negative-triangularity plasmas. Predictive STEP modeling has been used to assess performance in several tokamak reactors. Simulations of a high-field, large-aspect-ratio reactor show significantly lower fusion power than predicted by a zero-dimensional study, demonstrating the limitations of scaling-law extrapolations. STEP predictions have found promising scenarios for an EXhaust and Confinement Integration Tokamak Experiment, including a high-pressure, 80%-bootstrap-fraction plasma. ITER modeling with STEP has shown that pellet fueling enhances fusion gain in both the baseline and advanced-inductive scenarios. Finally, STEP predictions for the SPARC baseline scenario are in good agreement with published results from the physics basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

District-Scale Analysis of Electricity Load and Strategies to Improve Energy Reliability Using Prototype District Models

Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Combined Experimental/Numerical Study of the Soot Formation Process in a Gasoline Direct-Injection Spray in the Presence of Laser-Induced Plasma Ignition

Here, combustion issued from an eight-hole, direct-injection spray was experimentally studied in a constant-volume pre-burn combustion vessel using simultaneous high-speed diffused back-illumination extinction imaging (DBIEI) and OH* chemiluminescence. DBIEI has been employed to observe the liquid-phase of the spray and to quantitatively investigate the soot formation and oxidation taking place during combustion. The fuel-air mixture was ignited with a plasma induced by a single-shot Nd:YAG laser, permitting precise control of the ignition location in space and time. OH* chemiluminescence was used to track the high-temperature ignition and flame. The study showed that increasing the delay between the end of injection and ignition drastically reduces soot formation without necessarily compromising combustion efficiency. For long delays between the end of injection and ignition (1.9 ms) soot formation was eliminated in the main downstream charge of the fuel spray. However, poorly atomized and large droplets formed at the end of injection (dribble) eventually do form soot near the injector even when none is formed in the main charge. The quantitative soot measurements for these spray and ignition scenarios, resolved in time and space, represents a significant new achievement. Reynolds-averaged Navier-Stokes (RANS) simulations were performed to assess spray mixing and combustion. An analysis of the predicted fuel-air mixture in key regions, defined based upon experimental observations, was used to explain different flame propagation speeds and soot production tendencies when varying ignition timing. The mixture analysis indicates that soot production can be avoided if the flame propagates into regions where the equivalence ratio (Φ) is already below 2. Reactive RANS simulations have also been performed, but with a poor match against the experiment, as the flame speed and heat-release rate are largely over estimated. This modeling weakness appears related to a very high level of turbulent viscosity predicted for the high-momentum spray in the RANS simulations, which is an important consideration for modeling ignition and flame propagation in mixtures immediately created by the spray.

42 ENGINEERING↗

DOE OSTI2022

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. In conclusion, the interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Theory and Simulation of Metal–Insulator–Semiconductor (MIS) Photoelectrodes

A metal–insulator–semiconductor (MIS) structure is an attractive photoelectrode-catalyst architecture for promoting photoelectrochemical reactions, such as the formation of H 2 by proton reduction. The metal catalyzes the generation of H 2 using electrons generated by photon absorption and charge separation in the semiconductor. The insulator layer between the metal and the semiconductor protects the latter element from photo-corrosion and, also, significantly impacts the photovoltage at the metal surface. Understanding how the insulator layer determines the photovoltage and what properties lead to high photovoltages is critical to the development of MIS structures for solar-to-chemical energy conversion. Herein, we present a continuum model for charge-carrier transport from the semiconductor to the metal with an emphasis on mechanisms of charge transport across the insulator. The polarization curves and photovoltages predicted by this model for a Pt/HfO 2 /p-Si MIS structure at different HfO 2 thicknesses agree well with experimentally measured data. The simulations reveal how insulator properties (i.e., thickness and band structure) affect band bending near the semiconductor/insulator interface and how tuning them can lead to operation closer to the maximally attainable photovoltage, the flat-band potential. This phenomenon is understood by considering the change in tunneling resistance with insulator properties. The model shows that the best MIS performance is attained with highly symmetric semiconductor/insulator band offsets (e.g., BeO, MgO, SiO 2 , HfO 2 , or ZrO 2 deposited on Si) and a low to moderate insulator thickness (e.g., between 0.8 and 1.5 nm). Beyond 1.5 nm, the density of filled interfacial trap sites is high and significantly limits the photovoltage and the solar-to-chemical conversion rate. These conclusions are true for photocathodes and photoanodes. This understanding provides critical insight into the phenomena enhancing and limiting photoelectrode performance and how this phenomenon is influenced by insulator properties. The study gives guidance toward the development of next-generation insulators for MIS structures that achieve high performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Engineered Barrier System Research Activities at LBNL (FY2020 Progress Report)

The design of a radioactive waste repository typically involves a multi-barrier system, including the natural barrier system (NBS), i.e., the host rock and its surrounding subsurface environment, and an engineered barrier system (EBS). The EBS is to be constructed from the man-made, engineered materials placed within a repository. The repository includes the waste form, waste canisters, buffer materials, backfill, and seals. The most common buffer material for EBS is compacted bentonite, which features low permeability and high retardation of radionuclides. Extensive studies concerning the behavior of bentonite backfill in crystalline and argillite/shale geologic environments for nuclear waste disposal have been conducted by means of laboratory experiments, numerical modeling, and large-scale in situ tests in Underground Research Laboratories (URLs) in Switzerland, France, Belgium, and Japan. This report includes the results of LBNL’s research activities conducted according to the objectives and scope of the work packages “SF-20LB01030802 Engineered Barrier System R&D - LBNL” and “SF-20LB01030806 Engineered Barrier System International Collaborations - LBNL” of the Spent Fuel and Waste Science and Technology (SFWST) (formerly called Used Fuel Disposal) Campaign of the Department of Energy’s (DOE) Office of Nuclear Energy. LBNL research studies included laboratory scale tests and modeling of the evolution of the EBS bentonite and associated coupled processes, and impacts of high temperature on parameters and processes relevant to the performance of crystalline and argillite repositories, including the evaluation of the technical basis for applying the maximum allowable temperature. The results of these studies are being addressing the technical elements necessary to evaluate the EBS design concepts. Emphasis is on the study of thermal, mechanical, and chemical processes that influence the performance of EBS, and the development of modeling capability for reliable assessment of these processes, and ultimately supporting the development of the GDSA model with detailed coupled THMC process models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

VERAOneway Coupling for Transients

The VERAOneWay (VOW) package provides one-way coupling between two Nuclear Energy Advanced Modeling and Simulation (NEAMS) codes: the Virtual Environment for Reactor Applications (VERA) and BISON. This package was initially designed and tested on multicycle pressurized water reactor (PWR) problems. Recent work has improved VOW and extended its capability to other problems. VOW was enhanced to simulate fuel performance for reactor transients. Additional fuel types and geometries were added to cover boiling water reactor (BWR) fuels. The BISON version and templates were updated to the most recent version and best practices. The code was refactored to make it easier to add features and to extend VOW to other codes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

SCALE 6.3.0 User Manual

SCALE is a comprehensive modeling and simulation suite for nuclear safety analysis and design developed and maintained by Oak Ridge National Laboratory under contract with the U.S. Nuclear Regulatory Commission, U.S. Department of Energy, and the National Nuclear Security Administration to perform reactor physics, criticality safety, radiation shielding, and spent fuel characterization for nuclear facilities and transportation/storage package designs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

SCALE 6.3.1 User Manual

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

DPE Techno-Economic Analyses

This National Energy Technology Laboratory (NETL) report presents the results of an extensive set of techno-economic analyses for several open-cycle coal fuel oxy-fired direct power extraction (DPE) concepts. These power cycles make use of a conducting plasma accelerated through a magnetic field to generate direct current directly without the need for moving parts. Similar to gas turbines, the efficiency of the power cycle increases with increasing working fluid temperature and typically, plasma temperatures are much higher than the inlet temperature of even the most advanced gas turbine available today, affording the opportunity for very high cycle efficiencies. Most of the study uses high-fidelity models to assess a coal-fueled oxy-combustion DPE system with an AUSC steam bottoming cycle. Two baseline configurations were explored, one with relatively conservative operating point parameters and another with relatively aggressive operating point parameters. Additional analysis on the high-fidelity models as well as reduced order models were performed to analyze the cost and performance potential more thoroughly for the baseline systems and to compare their performance to two alternate open-cycle DPE systems.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

SCALE 6.3.2 User Manual

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

SCALE 6.3.3 User Manual

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Thermal Analysis of the Sirius-3 Nuclear Propulsion Fuel Experiments

To support long space missions, NASA is designing and testing different fuels for nuclear thermal propulsion. These designs include a number ceramic metallic fuels which are to be irradiated in the Tranisent Test Reactor to test the fuel’s performance at protypical conditions. The irradiation campaign of these fuels is referred to as the Sirius experiments, and includes single and stacked experiment samples. In this paper we present the thermal analysis of the Sirius-3 experiment. For this analysis, temperatures from a Bison finite element model are compared to the temperatures obtained from an experiment thermocouple where good agreement between the two are found. Because agreement of the thermocouple and Bison finite element model, insight into the heat flow is provided to experimenters as they design future experiments. As an example of this insight, the rods through the fuel specimen as shown in Sirius A and B [1] were removed and replaced with hold down rings for the Sirius-2C

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

DOE OSTI2022

CyclusJS: A Distributed Web-based Fuel Cycle Visual Analytics. Research Performance (Final Report)

The overall aim of the CyclusJS project has been to design novel approaches that support fuel cycle simulations and empower decision-makers and researchers with better tools to compare and contrast results from multiple simulations to understand the landscape of potential outcomes better. In particular, nuclear fuel cycle simulations focus on modeling the nuclear industry and ecosystem at a macroscopic level, and the analysis tools connect such simulations with decision support systems. As a demonstration of the novelty and effectiveness of the proposed approach, we study scenarios for transitioning from one technology, Light Water Reactors (LWR), to a newer Sodium-cooled Fast breeder Reactor (SFR) technology.

60 APPLIED LIFE SCIENCES↗