Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “High temperature design methodologies”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2021

Dynamic Probabilistic Safety Assessment Studies for Advanced Reactor Using RAVEN

Probabilistic Safety Assessment (PSA) is used extensively to evaluate the risks associated with complex engineering systems like Nuclear Power Plants (NPPs). Current PSA models are based on the Event-Tree/Fault-Tree (ET/FT) methodology. ET and FT models are static and are based on Boolean logic approaches. In the past, concerns have been raised in the literature regarding the capability of the traditional static modelling approaches to adequately account for the impact of process, hardware, software, firmware and human interactions on the stochastic system behaviour. To overcome the limitations of the traditional approach to PSA, several dynamic PSA methodologies have been proposed. One of the dynamic PSA methodologies used for dynamic evaluations is Dynamic Event Tree (DET) framework which can be used to assess the impact of the parameter variability and scenario dynamics on the PSA model for the initiating event. The DET framework couples the stochastic model (number of component/trains that start on demand, operator action timing, etc.) with a Thermal-Hydraulic (TH) model of the plant. This paper explores the use of DET along with a case study on advanced reactor. The initiating event selected for the study was Class IV power supply failure event. The TH analysis considering uncertainty in various parameters was performed using RELAP5 and Reactor Analysis and Virtual control ENvironment (RAVEN) tool. Based on the uncertainty analysis, it is concluded that the peak clad temperatures (PCT) are within the limits in all the code runs implying a high-degree of safety margin. However, variation in time to reach the PCT was observed among the code runs and the mean time to reach the PCT was found to be around 8590sec (approximately 2.4 hours). Hence, sufficient time margin is available for human intervention and the operator might have a relatively stress-free state during such an accident scenario. Due to the static nature of the traditional PSA models, the safety margin available was lesser, whereas, with the help of dynamic PSA models, one can demonstrate that the actual available safety margin is more in the present case study and is valuable input from the design point of view.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Advances in supervisory control strategies for a heat pump centric HVAC system − a comprehensive review on applications

There is an increase in research investigating the development and deployment of supervisory controllers that enable high efficiency electrically driven vapor compression heat pumps operating within grid interactive efficient buildings to provide demand side management. This paper reviews over sixty relevant case studies within this domain that focus on commercial off-the-shelf heat pumps whose primary task is providing space conditioning. The concept of a heat pump-centric heating, ventilation, and air-conditioning system is introduced, accompanied by a detailed overview of various kinds of electric heat pumps and building-level thermal energy storage configurations. Additionally, the different types of supervisory controller designs, including rule-based control and model predictive control, are discussed, along with the various methods for communication between a supervisory controller and a downstream heat pump’s local controller. A comparative analysis is conducted in order to categorize the reviewed case studies based on their system design, supervisory control algorithm, and validation methodology. This detailed analysis allows the review to establish current research trends, identify potential gaps, and suggest future directions for the development of this technology. Overall, the authors recommend that more future research be devoted to low-cost practical retrofits that allow for easy integration of active thermal energy storage within heat pump-centric heating, ventilation, and air-conditioning system systems that utilize direct expansion heat pumps. We also suggest more research into the development and deployment of supervisory controllers that can properly communicate with commercial off-the-shelf heat pump local controller available control inputs, e.g., zone temperature setpoint. Lastly, more rigorous experimental demonstrations of advanced supervisory control within real and or closed-loop, transient/ quasi-steady state environments are necessary to reduce industry wide skepticism of this technology.

Demand side management↗
DOE OSTI2023

Hybrid Tandem Photovoltaics

Tandem solar cell structures are the only strategy demonstrated to surpass the detailed balance efficiency limit of high-quality single-junction solar cells. To continue to improve the efficiencies of cost-effective terrestrial solar power, hybrid tandems of dissimilar subcells are being considered by many around the world, especially designs that incorporate silicon solar cells as a bottom subcell. In this project, we studied a wide variety of tandem design possibilities including those with three-terminal (3T) and four-terminal (4T) configurations. The use of 3T and 4T designs could be useful for efficient and economical hybrid tandem designs that utilize the best available subcell materials such as emerging perovskite materials. Three-terminal configurations, in particular, have not been sufficiently studied previously. We have laid the foundational groundwork in this project for understanding the operation of 3T tandems: developing a taxonomy for naming, a methodology for measuring and interconnecting, and models for simply characterizing 3T tandems. Electrical and optical subcell coupling between the subcells was also measured and modeled. An important part of this work was the fabrication of novel example tandem structures, including 4T GaAs/Si, 3T GaInP/Si, 3T GaAs/Si, and 3T GaInP/GaAs devices. Using these high-quality tandem cells, we have been able to clearly demonstrate the achievability of high-efficiencies, and subtle physical effects such as photon recycling and luminescent coupling. We have developed and demonstrated essential building-block tools such as transparent conductive adhesives (TCA) and 3T silicon bottom cells with interdigitated back contacts (IBC) that can also be used in many other tandem designs. We have tested the reliability of these tools and devices under standardized testing and outdoor measurements. We have found 4T GaAs/Si tandems to be relatively straightforward to fabricate and robust in real-world outdoor conditions. While we have demonstrated working hybrid 3T III-V/TCA/Si IBC tandems, we experienced low yields even with our best process flows yet. Further work is still needed to improve the processing yield of these devices. We therefore also created tandem cells using an all-III-V 3T tandem process which was very robust with high yields, allowing for the creation of voltage-matched strings in many different configurations using 8 nearly identical 3T tandems. Using these robust 3T tandem examples, we were able measure and precisely characterize 3T tandem behaviors to predict their operation under changing spectrum and temperature. The optoelectronic equivalent-circuit model was shown to be very general and applicable to hybrid tandems, and encompassed the operation 3T Si IBC cells. This general model has been distributed to the public in as open-source Python-based software called PVcircuit. We have calculated the implications of these new tandem device designs on the real-world energy production and shown how the relative performance of different tandem configurations is situational and can be engineered using the tools developed here.

14 SOLAR ENERGY↗
DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Pilgrim : A thermal rate constant calculator and a chemical kinetics simulator

Pilgrim is a program written in Python and designed to use direct dynamics in the calculation of thermal rate constants of chemical reactions by the variational transition state theory (VTST), based on electronic structure calculations for the potential energy surface. Pilgrim can also simulate reaction mechanisms using kinetic Monte Carlo (KMC). For reaction processes with many elementary steps, the rate constant of each of these steps can be calculated by means of conventional transition state theory (TST) or by using VTST. In the current version, Pilgrim can evaluate thermal rates using the canonical version of reaction-path VTST, which requires the calculation of the minimum energy path (MEP) associated with each elementary step or transition structure. Multi-dimensional quantum effects can be incorporated through the small-curvature tunneling (SCT) approximation. These methodologies are available both for reactions involving a single structure of the reactants and the transition state and also for reactions involving flexible molecules with multiple conformations of the reactant and/or of the transition state. For systems with many conformers, the program can evaluate each of the elementary reaction rate constants by multipath canonical VTST or multi-structural VTST. Moreover, the reactant can be unimolecular or bimolecular. Torsional anharmonicity can be incorporated through either the MSTor or the Q2DTor programs. Dual-level calculations are also available in Pilgrim: automatic high-level single-point energies can be used to correct the energy of reactants, transition states, products, and MEP points using the interpolated single-point energies (ISPE) algorithm. When the rate constants of all the chemical processes of interest are known, by means of their calculation using Pilgrim or alternatively through analytical fits to the rate constants as functions of temperature, it is possible to simulate a multistep mechanism under specified laboratory conditions using KMC. Finally, this algorithm allows performing a kinetic simulation to monitor the evolution of each chemical species with time and obtain the product yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Optimization of thermal barrier coating performance and durability over a drive cycle

A methodology to thermo-mechanically optimize a piston thermal barrier coating over a full drive cycle was established. The optimization objective was to minimize the heat transfer to the engine wall while maintaining structural integrity of the coating. Over 800 candidate materials were investigated and the optimization required more than one million non-road transient drive cycle calculations; real materials were investigated to ensure a realizable result and the existence of thermal and mechanical properties. High computational efficiency was achieved using a recently developed analytical heat transfer technique for multilayer engine walls. An uncoupled approach was utilized for the optimization, wherein the gas temperature and heat transfer coefficient profiles from a fully coupled and calibrated baseline model over the 20-min drive cycle were employed. The coating/piston interface temperature was constrained to be below the maximum piston service temperature limit. The durability was assessed using a recently developed analytical coating delamination framework for engine in-cylinder coatings based on the energy release rate when a crack forms. Results are presented for a mechanically unconstrained optimization and for cases constrained to three fixed levels of drive-cycle maximum energy release rate, and also constrained by the individual material’s toughness. The best-performing coating materials identified were verified using the fully coupled system-level model, which compared well to the uncoupled predictions. A study on the effect of adding a sealing layer to some high-performing, but porous, coatings showed a reduction in fuel consumption benefit and an increased exhaust temperature over the cycle, but the system still outperformed the uncoated case. The results of the study elucidate the importance of including engine performance and mechanical failure considerations in thermal barrier coating design.

Engineering↗
DOE OSTI2021

TRANSIENT THERMAL MODELING OF THE HIGH BURNUP DEMONSTRATION RESEARCH PROJECT CASK USING STAR-CCM+ AND COBRA-SFS

The Department of Energy in collaboration with the Electric Power Research Institute is in the process of conducting the High Burnup Demonstration Project. Where the objective is to characterize the performance of high-burnup fuel in long term storage. As part of this demonstration, a TN-32B dry storage cask was instrumented and loaded with spent nuclear fuel at North Anna Nuclear Generating Station in November 2017. The project cask provides a unique opportunity to gain information on spent fuel and cask performance from an in-service operational system. The cask was instrumented with thermocouples inside of the fuel assemblies, then loaded and dried using normal procedures. After the drying process a thermal soak period where the cask was left indoors was used to obtain steady temperatures for model comparison along with surface temperatures. This paper details thermal modeling validation work that was done to model both the steady state and transient cases. Two modeling tools were used to predict temperatures in the cask. The general purpose CFD and heat transfer code STAR-CCM+ was used with both a detailed pin-by-pin model was used along with a more efficient k-effective simplification. The other code is COBRA-SFS, a purpose-built detailed thermal modeling tool developed and maintained at PNNL. Results from all the modeling tools were compared blind to the test data. Each model utilized general design information and compared reasonably well to the blind steady state data using convection and surface temperature boundary conditions. Post-test adjustments were later made to better reflect the “as built” conditions of the cask. Based on lessons learned from the steady state analysis the vacuum drying process was modeled in both codes. Utilizing the measured loading conditions the transient models were able to compare very well with the measured data. Overall the project showed an ability to model spent fuel storage conditions very well and future work is planned to generalize the methodology used for vacuum drying.

Thermal Analysis, Spent Fuel, Dry Storage↗
DOE OSTI2022

High Fidelity CFD Simulations Supporting the KP-FHR

Kairos Power, LLC, is developing its version of the Fluoride-cooled High-temperature Reactor, the KP-FHR. The design uses a pebble bed core with fluoride salt as a coolant. The pebbles used in the KP-FHR have a diameter of 4 cm, with a shell fuel region where TRISO particles are embedded. A Pebble bed core design is adopted by several Gen IV reactors, They boast many benefits, such as fuel integrity, highly efficient heat transfer, and passive safety. However, it is challenging to accurately predict temperature and flow inside a pebble bed. Traditional approaches use the porous media model, which regards the pebble bed as a continuous medium, but with different temperature fields representing different levels, such as the fluid temperature, pebble surface temperature, and pebble center temperature. Empirical heat transfer correlations are adopted to calculate the heat transfer coefficient between different phases. However, empirical correlations are usually validated with experimental data, which usually lacks detail inside the pebble bed. The available experimental data is also generally at a high Reynolds number, which falls outside of the conditions of KP-FHR. Explicit computational fluid dynamics (CFD) simulations of randomly packed pebble beds have only become feasible recently. This is thanks to the rapid development of computational power and scalable algorithms. In this work, we used the Spectral Element Method (SEM) CFD code NekRS to simulate the randomly packed pebble bed in a cylindrical container. NekRS, which is the GPU variant of Nek5000, but refactored to utilize the computational power of GPUs using the OCCA library to run on hybrid architecture high performance computing systems. It was initially developed with the libParamunal library, but truncated and tuned for large-scale turbulence simulation. As a result, the SEM reaches higher precision with the same degrees of freedom by using a high-order Lagrange polynomial basis distributed on Gauss-Lobatto-Legendre quadrature inside each element, compared to lower-order methods, such the Finite Volume Method and Finite Element Method. The report is divided into five parts. We start with a general discussion of the pebble bed reactor, along with a specific investigation into the KP-FHR. The second part presents the numerical methodology. In the third part, we study a modular pebble bed with 1741 pebbles in a container of 7 pebble-diameter radius. Beyond LES simulations done by NekRS, we also leveraged the thermal radiation model in OpenFOAM to study heat transfer under no-forced-flow scenarios. Then, in the fourth part we simulated a pebble bed similar to the size of the Hermes Test Reactor. The total number of pebbles is in these simulations is 34,374. The container radius is 14 pebble-diameters. Finally, the report concludes in part five, with a discussion of future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2023

Phase-Field Modeling of Materials Interfaces and Nanostructures

Nanostructured materials offer unique properties for a wide range of energy applications. Among various known processing methods, liquid metal dealloying (LMD)—the selective dissolution of a base alloy element into a metallic melt—has emerged as a powerful technique to produce a new class of nano-/meso-scale open porous and bicontinuous composite structures with ultra-high interfacial area. LMD has recently been complemented by the advent of vapor phase dealloying (VPD), a novel technique that exploits the selective evaporation of one element from a parent alloy containing elements with very different vapor pressures, thereby enabling to fabricate open nanoporous structures of various elements from less-noble metals to inorganic elements regardless of their chemical activity without requiring high LMD temperatures and chemical etching. Together LMD and VPD have greatly expanded the scope of dealloying techniques, limited by traditional electrochemical means to noble metals, and boosted the design of new functional and structural materials that combine a wide variety of elements. Topologically-connected open porous structures with ultra-high surface area allow mass transport within the structure while preserving structural integrity, enabling them to serve as catalysts, fuel cells, supercapacitors, or high-capacity battery materials. Bicontinuous composite structures in turn can display high strength and high ductility or superior radiation-damage resistance due to the ultra-high interface area between interpenetrating solid phases. This research program makes use of state-of-the-art computational methods to understand at a basic level the self-organizing dealloying process with main focus on dealloying kinetics and interfacial pattern formation at the dealloying front controlling initial structure size, topology, and phase compositions. Phase-field simulation studies of LMD focus on solid solutions, line compounds, and intermetallic systems that can form ternary composites by nucleation and growth of a new phase. Studies of VPD employ phase-field modeling and a hybrid method combining a kinetic Monte Carlo (KMC) model of evaporation and surface diffusion with molecular dynamics for vapor-phase transport inside nanopores. Simulations explore mechanisms of interface- and diffusion-controlled dealloying kinetics, both observed in VPD but not fundamentally understood. In addition, our newly developed multi-physics phase-field approach of large-volume-change phase transformations is being used to model novel 3D anode geometries based on dealloyed nanoporous structures including novel sandwiched graphene/Si/silica for highrate Li ion battery. Those studies are aimed at elucidating geometric design principles that improve mechanical stability. We expect this research to enhance the capability to tailor nano-/mesoscale structures for a wide range of energy-related materials applications and to yield further advances in computational methodologies that benefit a broad materials research community.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Fluoride-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the Fluoride-Cooled High-Temperature Pebble-Bed Reactor reference plant models for the United States Nuclear Regulatory Commission. These models, developed with the Comprehensive Reactor Analysis Bundle, or BlueCRAB, serve as the foundation for the future development of detailed design evaluation models based on license applications. BlueCRAB is the code suite proposed for non-light-water reactor systems safety analyses, and it incorporates various simulation tools developed by the Nuclear Energy Advance Modeling and Simulation program, including the Griffin code for reactor physics, the Pronghorn and SAM codes for core thermal fluids, the BISON code for solid conduction and fuel performance, and the SAM code for system analysis. The primary objective of this work is to assess the level of readiness of BlueCRAB for modeling fluoride-cooled high-temperature pebble-bed reactors. We first developed numerical models in BlueCRAB that include the key physics for this technology, ensuring an adequate level of fidelity for modeling the core performance during accident scenarios. This was followed by simulation of transient scenarios, two loss-of-forced-cooling events (one protected and one unprotected), and two control rod withdrawal events (one delayed and one prompt supercritical reactivity insertion). The analysis includes comparisons between the 2-D thermal fluid porous media models in Pronghorn and SAM, comparisons between coupled Pronghorn-Griffin and coupled SAM-Griffin models for two loss-of-forced cooling events and one control rod withdrawal event, and comparisons between SAM single-solve and domain-overlapping approaches for multi-scale thermal fluid coupling. In addition, we performed comparisons between 3-D, 2-D, and 0-D neutronic models for the two control rod withdrawal scenarios with Pronghorn-Griffin. The results show that the BlueCRAB models led to physically intuitive solutions for the scenarios examined. The changes in the various scalar and vector fields such as the neutron flux, power, temperatures, densities, pressures, and velocities are all within the expected ranges, and their distributions can be explained from the system response of the transients and the geometric and material variations. Several comparisons suggest that the porous media models in Pronghorn and SAM can lead to similar solutions, even though they are based on different methodologies. The simulations demonstrate that there are differences between the various levels of fidelity, and it is advisable to have flexible tools that can cover the breadth and depth of needs that may arise in future technical evaluations. We believe that BlueCRAB’s capabilities represent a significant asset for confirmatory analyses aimed at resolving important safety questions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Statistical Multiobjective Optimization of Thiospinel CoNi 2 S 4 Nanocrystal Synthesis via Design of Experiments

Thiospinels, such as CoNi 2 S 4 , are showing promise for numerous applications, including as catalysts for the hydrogen evolution reaction, hydrodesulfurization, and oxygen evolution and reduction reactions; however, CoNi 2 S 4 has not been synthesized as small, colloidal nanocrystals with high surface-area-to-volume ratios. Traditional optimization methods to control nanocrystal attributes such as size typically rely upon one variable at a time (OVAT) methods that are not only time and labor intensive but also lack the ability to identify higher-order interactions between experimental variables that affect target outcomes. Herein, we demonstrate that a statistical design of experiments (DoE) approach can optimize the synthesis of CoNi 2 S 4 nanocrystals, allowing for control over the responses of nanocrystal size, size distribution, and isolated yield. After implementing a 2 5–2 fractional factorial design, the statistical screening of five different experimental variables identified temperature, Co:Ni precursor ratio, Co:thiol ratio, and their higher-order interactions as the most critical factors in influencing the aforementioned responses. Second-order design with a Doehlert matrix yielded polynomial functions used to predict the reaction parameters needed to individually optimize all three responses. A multiobjective optimization, allowing for the simultaneous optimization of size, size distribution, and isolated yield, predicted the synthetic conditions needed to achieve a minimum nanocrystal size of 6.1 nm, a minimum polydispersity (σ/$\bar{d}$) of 10%, and a maximum isolated yield of 99%, with a desirability of 96%. The resulting model was experimentally verified by performing reactions under the specified conditions. Furthermore, our work illustrates the advantage of multivariate experimental design as a powerful tool for accelerating control and optimization in nanocrystal syntheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Insights into Methodologies and Stochastic Optimization of Thermal Energy Storage-Coupled Advanced Reactor Systems: A Comparison of Methods for Accessing Long-Term Sub-System Sizing Adequacy

This paper investigates the potential of coupling Thermal Energy Storage (TES) with Advanced Reactors (ARs) to address uncertainties posed by climate change in deep decarbonized power systems. The TES Use-case Team at Idaho National Laboratory (INL) has examined the potential of storing thermal energy from ARs during low demand periods and optimizing discharge during peak-priced hours, in both steady-state and transient conditions. Building on this groundwork, this study bridges the gaps in optimal sizing of the sub-system of TES-coupled AR systems using Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON), INL?s framework for grid optimization. By applying this framework, we present statistically-robust optimal charge, discharge including balance of plant (BOP), and storage sizing for the High-Temperature Gas-Cooled Reactor (HTGR) with 203 MWth output. To this end, we generated synthetic price samples for 30 years using 2018 ? 2021 real-time market data from ERCOT, PJM and MISO. Our results reveals that the TES-coupled HTGR system is highly effective in maximizing revenue from electricity sales. We observed a substantial increase of 40 % in ERCOT and a noteworthy 15 % increase in PJM and MISO when compared to the conventional BOP without TES. This improvement is achieved through regionally-tailored sub-system sizing, which ranges from 398 to 416 MWth for the discharge system and 610 to 1029 MWth for the TES. We find that the average electricity price directly impacts the overall economics, while price volatility influences storage size. Additional sensitivity analyses were performed to access the impact of key assumptions on system economics and sizing, differentiating the optimization window (i.e., 24 ? 219 hours of chronological observations) and by imposing storage continuity condition in tracking TES cycles. We observed that at the 120-hour of the optimization window, a reasonable balance between computation time and accuracy was achieved. Our analysis also highlights the significance of conducting multi-day cycle analysis (> 120-hour) for TES to capture interaction between electricity prices and storage dynamics, providing a comprehensive understanding of TES behavior that AR developers should integrate into their plant designs.

25 ENERGY STORAGE↗
DOE OSTI2023

Report of METL Mutual Inductance Level Sensor Development for Use in Liquid Metals – FY2023

A robust mutual inductance level sensor (MILS) for use in high temperature liquid metals has been developed at Argonne National Laboratory (ANL). The current design utilizes mineral insulated cables with a 300-series stainless steel sheath, magnesium oxide insulation, and a single copper conductor. Two coils are wrapped on a common core made of a 300-series stainless steel tube. One coil is energized with an alternating current (AC) source, and this electromagnetically couples with the second coil to generate an induced voltage. The voltage is measured to determine the mutual induction between the coils, and the mutual inductance measurement can be used to determine the level of a nearby liquid metal volume. The MILS can be located in an isolating thimble that is fully sealed to a vessel containing liquid metal for ease of maintenance and replacement. When the primary coil is energized with the AC source, the coil not only electromagnetic (EM) couples with the second coil, but also the surrounding liquid metal. The EM coupling with the surrounding liquid metal reduces the EM coupling with the second coil, producing an inverse-linear relationship between liquid metal level and secondary coil voltage. This has all been demonstrated at the Mechanisms Engineering Test Loop (METL) liquid sodium facility at ANL. The most current iteration of the MILS system is the MILS-MK-II. This sensor system has been commissioned in a non-sodium test stand where calibrations were performed using a sodium analog. The calibrations proved to be highly linear and repeatable. The MILS-MK-II has been installed in the METL expansion tank where high temperature sodium tests have been performed. The MILS-MK-II has been calibrated against a known standard at temperature of 300°C, and the calibrations have proved to be highly linear and repeatable. The calibrated MILS-MK-II has been in operation in the METL facility for several thousands of hours at temperatures around 300°C. The experimental data has been used to develop and validate electromagnetic finite element models in COMSOL Multiphysics, and now these models can be used to advance the development of the sensor system. Next steps will include temperature compensation to allow for operation at various temperatures. Additionally, efforts to incorporate a self-calibration methodology are underway.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Local Power Impact Experiment Design for a New Fuel Type for use in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. Reactor physics safety evaluations currently use Monte Carlo for the 21st Century (MC21), a continuous-energy Monte Carlo radiation transport code [3]. Existing MC21 models of the ATR and ATRC cores have a validation basis for use in neutronics analyses with HEU fuel. The models are used to support safety analyses that include comparisons to the safety requirements for the reactors. However, the use of the LOWE element in the ATR and ATRC is not currently covered by the current model validation basis. To deploy the new fuel type, extensive computational reactor physics support is necessary to support the use of LOWE in the ATR and ATRC. Therefore, LOWE requires a rigorous validation basis, aligned with that of HEU fuel, that takes advantage of the existing software tools and processes currently used for the ATR and ATRC. The experiment to validate of the MC21 models for determining power, the Power Impact Validation Experiment, will consist of two flux runs in the ATRC, one with fully HEU loading and one with a single LOWE element. Both flux runs will be instrumented with 20 sets of azimuthal fission wires and 3 sets of axial fission wires, as shown in Figure 4. Standard flux run methodology will be used [4]. Power Impact Validation Experiment data will be compared against MC21 calculated data, both for absolute fission rate accuracy and to determine the relative change in fission rates between the two runs. The results of the Power Impact Validation Experiment and subsequent evaluations will provide the validation basis for MC21 for use with LOWE elements. Key features of the Power Impact Validation Experiment include: (1) Two flux runs to allow for LOWE perturbed measurements to be compared to already validated measurements taken from a full core of HEU fuel, (2) Optimization of instrumentation to balance analytical needs with practical considerations (e.g., limited time window to count beta particles from fission products), and (3) Standard ATRC core loading, including both driver positions and flux traps, to minimize cost while remaining representative of typical ATR core loading.

42 ENGINEERING↗
DOE OSTI2025

Field Validation of Thermoelectric Generation System at Holcim Cement Plant in Alpena, Michigan

Executive Summary Project Background The Industrial Technology Validation (ITV) program aims to identify and demonstrate the performance of new, emerging, and underutilized energy-saving technologies in the industrial sector to help inform decisions to help accelerate their commercialization and deployment, as well as to help make industries more competitive. This ITV demonstration evaluated a thermoelectric generation (TEG) technology at a cement plant, aiming to reduce energy demand in the cement industry. A median cement plant consumes 5.73 million British thermal units per ton of clinker production (resulting in 0.838 metric tons of carbon dioxide [CO₂] emissions per ton of clinker) (Boyd and Zhang 2011, EPA 2021), equivalent to approximately 6.9 trillion British thermal units (TBtu) per year in energy consumption at a cement plant producing 3,300 tons of clinker per day.¹ Collaborating with Holcim, Advanced Thermovoltaic Systems (ATS) developed and deployed a pilot-scale thermoelectric power system to efficiently capture and convert waste heat to electricity. The system leverages the Seebeck effect to convert temperature differences on two sides of semiconductor cartridges into electrical power (ScienceDirect, n.d.). This generation is realized with minimal moving parts compared to existing waste-heat-to-generation solutions and allows capture from heat sources with temperatures as low as 150°C. This project aimed to validate a scalable solution applicable for capturing medium-temperature waste heat, including ambient losses from other high-temperature processes, and high-temperature sources less suitable for other waste-heat-to-power solutions. By recovering this otherwise wasted heat, this project intends to validate improvements to overall process efficiency through reduction in purchased electricity, thereby reducing operational costs while enhancing resiliency and competitiveness. Description and Scope This study evaluated the performance of a TEG system from ATS as a solution to convert waste heat into useful power at a Holcim cement plant in Alpena, Michigan. This plant is a fully integrated cement plant that has been operating since 1907. The facility operates continuously (24/7/365) with approximately 250 employees and five long dry kilns, yielding a total production capacity of 7,852 tons of cement per day (EPA 2023). Currently, the Alpena plant uses waste heat boilers to convert waste heat from the exhaust of each kiln into steam, which drives steam turbine generators. The ATS TEG is being evaluated for its potential to supplement the steam turbines by capturing the remaining lower grade heat. This technology is also being considered for other Holcim plants where steam turbines are not a viable option. ATS installed a pilot-scale TEG unit with an array of 582 individual thermoelectric semiconductor cartridges, of which 573 were operational. The cartridges are sandwiched between 48 hot plates and 49 cold plates. Each cartridge is designed to generate 20 watts (W) of gross power at a hot-side temperature of 240°C and cold-side temperature of 20°C. As such, the total gross generation capacity of the installed system is 11.5 kilowatts (kW) at design conditions. The system configuration for the evaluation was designed to prioritize convenience of installation and minimize disruption to production at the site, while ensuring that the heat required can be obtained for evaluating the TEG system at various operational conditions. To accomplish this, a portion of the steam supplied to Alpena’s steam turbine generation system was diverted to be used as the heat source for the TEG system, while water was supplied to the cold side of the system from nearby Lake Huron. This configuration was designed for the evaluation of the pilot-scale system to assess the performance at different conditions. A commercial-scale system will likely vary from the pilot system depending on typical configurations, including both scale and application. Future commercial applications of the ATS system would involve integrating the system into the exhaust from kiln preheaters, clinker coolers, or radiant heat capture from kiln shells for the heat source. For the cold source, a range of cooling solutions can be considered, including a mechanical cooling system, depending on the location and the application. To increase the generation capacity for commercial applications, the technology provider is working toward developing a commercial-scale TEG system, which would combine multiple TEG units (each similar in design to the pilot system) together. The scope of this evaluation includes the pilot-scale TEG system and all impacted equipment including pumps, controllers, and power handling equipment. Study Objectives The evaluation's goal was to assess the potential of the ATS TEG system to generate useful electrical power by capturing waste heat from cement production kilns. The objectives of this study are to evaluate and verify the following claims made by ATS regarding the pilot-scale system installed at the Holcim Alpena plant. The following design parameters and claims are also outlined in Table ES- 1 and Table ES- 2: • Gross Power: The thermoelectric system converts heat into power to create gross power, the total measured power generated by the system. The 573 active cartridge pilot-scale system is expected to generate 11.5 kW of gross power at the designed hot-side temperature of 240°C and cold-side temperature of 20°C. Power production is dependent on the temperature difference between the heat source (ultimately from the waste heat) and cold temperature supply source. • Net Power: The net power is the total usable power provided to the site by the TEG system after deducting parasitic power loads from the gross generated power. Supplementary equipment is required to operate the TEG system including pumps, controllers, and, in certain anticipated applications, mechanical cooling, which introduce parasitic loads to system operation. After deducting the parasitic loads from the gross power generation, ATS anticipates achieving a net power generation of 7.5 kW from the pilot-scale system. • Thermal Efficiency: The thermal efficiency is the percent of the total heat transferred to the TEG system that is converted to gross power. Historically, TEGs have a thermal efficiency of 2%–5% (DOE 2008). Prior industrial-scale TEG systems, such as the E1 TEG offered by Alphabet Energy, operated at an efficiency of 2.5% (Lamonica, 2014). ATS anticipates achieving an average efficiency of 4.8% or higher in converting heat energy to usable electricity. • Cartridge Performance: The TEG system comprises 573 active individual semiconductor cartridges, each of which generates a portion of the total power. Cartridge optimization and selection is an important design consideration for potential future TEG system design performance. Therefore, understanding the distribution of gross power and efficiency within the pilot system is vital to understanding what is achievable. At a design hot-side temperature of 240°C and cold-side temperature of 20°C, ATS anticipates a cartridge performance of 20 W of gross power per cartridge at an efficiency of 4.8% per cartridge. In addition to evaluating the claimed performance of the TEG pilot-scale unit, the study estimated the potential annual impacts of a scaled-up commercial system used to capture kiln waste heat over annual operations. The evaluation estimated the gross and net annual electric generation achievable by capturing heat from the two proposed tap-in points: the kiln exhaust and the clinker cooler exhaust; see Section 2.1 for details. Two use cases were examined: • Holcim Alpena: The Holcim Alpena site consists of long dry kilns with superheater boilers, which differs from the rest of Holcim’s cement plant portfolio and results in lower waste heat temperatures. The study estimates gross and net annual generation using the superheater boiler exhaust and clinker cooler exhaust, based on 2023 operational data. • Typical Installation: Common cement plants have preheater kilns with higher exhaust temperatures than Holcim Alpena across a range of production rates. The study estimates gross and net annual generation using the preheater exhaust and clinker cooler exhaust, with a sensitivity analysis to account for the typical range of preheater exhaust temperatures, clinker cooler exhaust temperatures, and clinker production rates. Methodology The evaluation methodology followed a measurement and verification (M&V) strategy based on the International Performance Measurement and Verification Protocol Option B through comprehensive measurements and analyses of the affected systems. Evaluation data was collected from March 9 to March 11, 2024, the test period of the pilot TEG system. During the test period, in coordination with the ITV team, the ATS team adjusted system operations to capture the range of variability expected for each of the variables pertinent to performance of the system. The methodology consisted of two parts: evaluating the performance of the pilot unit's TEG system and estimating the annual TEG impact in terms of gross and net power based on a given waste heat profile. First, the evaluation of the thermoelectric generation performance of the pilot unit relative to the claims was performed by analyzing the collected test data. Gross power of the pilot TEG system was directly measured. Net power was determined by deducting the measured parasitic power from the gross power. The gross power generation was compared to heat transferred to the system by the working fluid (which was heated by steam generated from the kiln waste heat) to calculate the thermal efficiency achieved by the system. Performance of individual semiconductor cartridges within the pilot array was also assessed in terms of measured gross cartridge power and calculated cartridge thermal efficiency. The second part of the evaluation estimated the annual TEG impacts in terms of gross power and net power (calculated from the difference between gross power and parasitic power). This analysis comprised development of mathematical regression models for gross power and parasitic power, with assessment of each model’s goodness-of-fit characteristics to ensure satisfaction of statistical requirements. The models predicted the gross power generation, the parasitic load based on the temperature difference between the hot working fluid and the cold-side fluid (cold water from Lake Huron) entering the system, the volumetric flow rate of the cold-side fluid at the inlet, and the volumetric flow rate of the hot working fluid at the inlet. The annual impact analysis considered a theoretical commercial-scale system sized to capture the available waste heat at a cement plant, consisting of linked pilot-scale units that receive heat from a theoretical gas-to-working-fluid heat exchanger. To estimate annual impacts at the Alpena plant, the gross power and parasitic power regression models were applied to the arrays in the theoretical commercial-scale system. The heat supplied to the unit was calculated based on the kiln run time, annual production, kiln exhaust waste heat, and clinker cooler waste heat derived from 2023 Holcim Alpena kiln operational data. Net power impacts were calculated by deducting the resulting parasitic power from the estimated gross power. Inputs for the model were generated from a combination of hourly data, assumed design considerations for TEG system scale-up from the pilot-scale unit, and assumptions regarding TEG system operations. This analysis was then used as the basis for estimating annual impacts of typical TEG installation at cement plants, by applying sensitivity analyses to key kiln operational characteristics including kiln preheater exhaust temperatures, cooler clinker exhaust temperatures, and plant daily production rates across a range of expected values. Project Results/Findings Table ES- 2 and Table ES- 2 provide a summary of the operating conditions and evaluation results compared to the stated claims from the technology provider. Key takeaways include: • Gross Power: The peak gross power achieved during the testing period was 10.0 kW, compared to the 11.5 kW expected for 573 active cartridges. The claimed gross power was associated with a target hot side of 240°C; however, the system only received a maximum hot-side mean plate temperature of 212°C during the testing period. • Net Power: The pilot-scale unit exceeded the claims for net power, achieving a peak of 7.7 kW net compared to a claim of 7.5 kW. One factor contributing to the higher achieved net power is the relatively high water pressure available through Lake Huron. The pilot TEG system did not require cold-side pumps during the test, whereas most installations would. This reduced the parasitic loads on the system, ultimately contributing to higher net power relative to the gross power. • Thermal Efficiency: The pilot-scale unit outperformed the claimed efficiency, achieving a peak system efficiency of 5.0% thermal efficiency compared to the stated 4.8%. • Cartridge Performance: To compare cartridge performance against claims, the study focused on the third day of testing, which aimed for conditions closest to the design specifications, with a hot side of 240°C and cold-side exit temperature of 6.4°–30°C. On this day, the mean gross power observed in the cartridges within the TEG array was 18.1 W/cartridge, and the peak performance was 34.7 W/cartridge. The estimated mean cartridge efficiency was 5.2%, and the estimated efficiency at peak gross cartridge power was 10%. The regression models developed for gross power generation and parasitic loads were used to estimate the generation impact for given heat input to the TEG from the working fluid (captured from the waste heat) and from the cold loop (Lake Huron) on an hourly basis for a year of operation. Based on this analysis, installation of a commercial-scale TEG system at the Holcim cement plant in Alpena, Michigan, with a waste heat exchanger of 0.85 effectiveness, would generate up to 391 kW of net power, translating to between 920,000 and 1,800,000 kilowatt-hours (kWh) in net electricity per year. Based on typical grid emissions for Alpena, this would avoid estimated net emissions by 752 metric tons of CO₂ annually.² The sensitivity analysis estimated that typical TEG system installations at cement plants could generate an average of 56–1,040 kW of net power, or between 488,000 and 9,110,000 kWh of net energy. This generation potential is most significantly affected by plant production rates and also influenced by preheater and clinker cooler exhaust temperatures. Applying the national average emission rate, typical commercial-scale installations at Holcim plants are projected to avoid between 182 and 3,401 metric tons of CO₂ annually per site. Table ES- 3 shows a summary of the estimated annual impacts.³ While parasitic loads are significant and vary by application, this analysis assumed the use of heating loop pumps and access to Lake Huron as a cold sink. This setup assumed no need for cooling loop pumps due to the available water pressure at the test site. Applications that require cooling towers or additional equipment are likely to experience higher parasitic loads. Therefore, the study’s estimates are most applicable to scenarios with similar parasitic load configurations—namely, access to a high-pressure cold sink. Applicability to other locations may be limited, as differing conditions could necessitate additional pumps and cooling systems, potentially impacting performance significantly.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗