Dynamic modelling of flexible dispatch in a novel nuclear-solar integrated energy system with thermal energy storage
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Previous work has proposed and characterized the structural and electrical performance of Multifunctional Energy Storage Composite (MESC) structures: structural elements with embedded lithium-ion batteries which were developed by the Structures and Composite Laboratory (SACL) at Stanford University. This work conducts a comprehensive parametric study over the design variables in the manufacturing process to determine the root cause of increased DC impedance compared to commercial pouch cell batteries. Several MESC samples were assembled under various controlled environmental temperatures and pressures. The samples underwent Hybrid Peak Pulse Characterization (HPPC) to approximate the DC impedance as a function of state of charge (SOC). Failure limits of the battery with respect to assembly temperature and pressure were tested, and an MESC manufacturing simulation model was constructed in Abaqus to validate the manufacturing limits. Samples assembled without enough temperature or pressure failed due to a lack of structural integrity or hermetic seal. Conversely, samples which underwent elevated temperatures and pressures resulted in high DC impedance due to nonuniform electrolyte wetting. This work resolves the primary concern of MESC by achieving comparable DC impedance to commercial pouch cells of the same chemistry and testing procedure.
Concentrating Solar Power (CSP) molten-salt central receivers are subject to high, transient incident flux during daily operation. The resulting creep-fatigue damage impacts the receiver’s reliability and restricts the permissible incident flux distribution for a given receiver. This paper aims to reduce CSP plants’ levelized cost of electricity by developing a methodology to predict lifetime and identifies the primary damage mechanism (creep vs fatigue) for any given fluid temperature and temperature gradient. Results are presented in the form of a damage map that serves as a valuable operation guide and design tool. Damage maps can be used to reduce maintenance costs by improving reliability and reduce receiver capital costs by better utilizing the receiver area. FEA simulation and damage modeling of tubes subject to asymmetrical flux conditions is performed in the open-source receiver design tool srlife. Parametric studies are performed over a range of inner tube temperatures and thermal gradients for A230, 316H, 740H, A282, A617, and 800H high temperature alloys. Damage maps are presented for each alloy. A parametric, FEA-based methodology is presented for comparison of fatigue-creep ratios and prediction of tube lifetime based on the critical thermal operating conditions. Fatigue is found to be negligible compared to creep for almost every case. Here, this finding suggests that fatigue effects associated with cloud events are insignificant compared to creep at these high temperature operating conditions. Additionally, lifetime predictions identify thermal conditions where small changes in operating conditions can result in large changes in predicted lifetime.
Low-cost, high performance proton exchange membrane fuel cells (PEMFCs) have been difficult to develop due to limited understanding of coupled processes in the cathode catalyst layer (CCL). Low-Pt-loaded PEMFCs suffer losses beyond those predicted solely due to reduced catalyst area. Although consensus links these losses to thin ionomer films in the CCL, a precise mechanistic explanation remains elusive. In this publication, we present a physically based PEMFC model with novel structure-property relationships for thin-film Nafion, validated against PEMFC data with low Pt loading. Results suggest that flooding exacerbates kinetic limitations in low-loaded PEMFCs, shifting the Faradaic current distribution. As current density increases, protons travel further into the CCL, resulting in higher Ohmic overpotentials. We also present a parametric study of CCL design parameters. We find that graded Pt and ionomer loadings reduce Ohmic losses and flooding, but individually do not provide significant improvements. However, a dual-graded CCL (i.e., graded Pt and ionomer) is predicted to significantly improve the maximum power density and limiting current compared to uniformly loaded CCLs. This work highlights the importance of accurate transport parameters for thin-film Nafion and provides a pathway to low-cost PEMFCs via precise control of CCL microstructures.
The rising interest in nuclear microreactors has highlighted the need for comprehensive technoeconomic assessments. However, the scarcity of publicly available designs and cost data has posed significant challenges. To address this issue, the Microreactor Optimization Using Simulation and Economics (MOUSE) tool is developed. MOUSE is a tool that integrates nuclear microreactor design with reactor economics. The design calculations encompass core simulations using the OpenMC Monte Carlo Particle Transport Code [romano2015], along with simplified balance of plant calculations. On the economic side, MOUSE provides detailed bottom-up cost estimates, calculating both the total capital cost and the levelized cost of energy for first-of-a-kind and nth-of-a-kind microreactors. The cost estimation correlations are developed using data from the MARVEL project and additional literature sources. MOUSE has released as an open-source tool on GitHub (MOUSE Tool). By combining design calculations with cost equations, MOUSE enables users to evaluate the impact of various technological consideration, advanced moderators, design changes, material/fuel changes, and geometry modifications—as well as economic parameters like interest rates and construction duration. This comprehensive framework can guide stakeholders towards technological solutions that enhance microreactor competitiveness. Additionally, powered by the WATTS toolkit [romano2022], MOUSE supports optimization studies, parametric analyses, and uncertainty calculations/propagation. Currently, preconceptual designs of three microreactor types are included in MOUSE: a liquid metal thermal microreactor (LTMR), gas cooled TRISO-fueled microreactor (GCMR) and heat-pipe TRISO fueled microreactor (HPMR). To showcase its ability, MOUSE was used to conduct detailed bottom-up cost estimates for the first of a kind (FOAK) and Nth of a kind (NOAK) of the following microreactors • A 20MWt LTMR that is built on the ongoing MARVEL demonstration at Idaho National Laboratory (INL) • A 15 MWt GCMR that was designed to be more representative of the typical commercial microreactor • A 7 MWt HPMR that was built on previous work (Choi 2024) The The reader should note that these three designs and corresponding cost estimates are examples to demonstrate the MOUSE capability. The designs are pre-conceptual, the reactor designs were not optimized, and the cost estimates were developed with incomplete information. Additionally, stakeholders might be interested in a variety of designs that may differ from the examples provided in this report. The MOUSE tool can also be used to study how design choices affect economics. To demonstrate its capability, MOUSE was used conduct parametric studies such as examining the economic impact of the reflector's material and thickness, the moderator's booster material and dimensions, fuel composition and enrichment, core size, and power level. Several insights were gained from these parametric studies.
Safety is always the primary concern for designing and analyzing nuclear reactor systems. The requirements for the safety margin for advanced small modular reactor (SMR) systems are targeted even higher than the conventional commercial large-scale nuclear reactors incorporating the passive and inherent safety systems. The SMR systems are designed with the condensation passive containment cooling system (PCCS), which plays a critical role in removing reactor heat during a steam release accident case. However, the presence of non-condensable gas (NCG), like air, reduces the heat transfer performance. This physics phenomenon becomes multifactorial for nuclear reactor containment during a fuel failure accident case that releases hydrogen gas. Besides, the mixture component of steam-air-hydrogen varies in reactor accident cases, which need simulation and validation keeping parameters of importance. Reviews showed that previous studies for SMR’s PCCCS did not cover the condensation heat transfer (CHT) in the presence of multicomponent NCG mixture parametric computational fluid dynamics (CFD) simulation and validation, making a research gap in the SMR design safety. A comprehensive CHT parametric CFD study was performed for SMR PCCS to fill this research gap. This study used experimental data as simulation 3D physics domain inlet and outlet boundary conditions. However, the wall boundary conditions were constant temperature, curve-fit, and annular coolant for verifying the turbulence models. Parametric simulations were performed, verified, and optimized for steam-NCGs mixtures. The multicomponent gases, multiphase mixtures, and fluid film condensation models were applied with associated turbulence models. The results of the parametric study were evaluated for realistic reactor conditions. Results showed that parametric study provided critical insight about the dependency of multicomponent gas mixture parameters that supports reactor safety design, analysis, and licensing.
Solid desiccant dehumidification systems are an alternative to vapor-compression-based air dehumidification systems. They use solid desiccant materials to adsorb air moisture in space cooling. DCHE can integrate the cooling component in the heat exchanger to achieve higher dehumidification capacity. Comprehensive numeric modeling would be necessary to assist in the design and operation of the DCHE under development to achieve maximum performance. Here, we provide the details of a heat and mass transfer model developed for this purpose. The model aims to cover a gap in existing models by independently modeling heat transfer on the solid desiccant, fin, and tube. The model results were compared with an experimental reference for validation. The air outlet humidity and temperature results for dehumidification and regeneration showed a deviation lower than 15% from the experiment. The validated model was used to perform a parametric study for a series of design and operating conditions. The parametric analysis showed that an increase of 25% in desiccant layer thickness and thermal contact resistance between solid elements reduces moisture removal by 9.1% and 1%, respectively. These results indicate the need to independently model the desiccant layer.
This study extends the Deep Material Network (DMN), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (Cosserat-type) constitutive behavior. This extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. While traditional, direct numerical simulation micropolar models effectively capture size effects by introducing extra local degrees of freedom, they bring significant computational challenges, particularly for multiscale analyses relevant to engineering applications. The micropolar DMN developed in this paper achieves high accuracy while significantly reducing computation time compared to micropolar direct numerical simulations. This advancement enables multiscale analyses and parameter studies that were previously impractical, such as high-cycle fatigue simulations and comprehensive investigations of internal length scale effects notably in size-dependent plastic response and the optimization of lattice structures. By uniting microstructure-sensitive modeling, physics-driven learning, and scalable surrogate modeling, the micropolar DMN paves the way for accelerated material design, large-scale parametric studies, and the reliable incorporation of size-dependent effects across a wide range of engineering applications, including optimization and next-generation composite design.
We report integrating thermal energy storage with building energy systems can enable flexible building electric demands at buildings to help mitigate the mismatch between electricity supply and demand. A novel building heating and cooling system that integrates a dual-source heat pump with hybrid thermal storage named dual-purpose underground thermal battery (DPUTB) has been developed for reshaping building electric demands. The proposed DPUTB integrated geothermal heat pump system is an original innovation that enables Grid-interactive Energy Efficient buildings. This paper focuses on the study of the novel DPUTB. The DPUTB works as both a thermal storage tank (an inner tank) and a ground heat exchanger (an outer tank separated from the inner tank by the insulation material). High fidelity and computationally effective models are needed to predict the performance of the novel DPUTB. This study has developed a simplified dynamic model for the DPUTB according to heat transfer and energy conservation principles and validated it by using experimental data obtained from testing a small-scale DPUTB apparatus. A parametric study was conducted to identify a design that can achieve the target thermal storage performance of load shift and energy efficiency. The parametric study results show that the inner tank shell thermal conductivity and the phase change material's melting point are the two most influencing factors on the performance of the DPUTB. One single full-size DPUTB with the identified design could provide 1-ton cooling (3.51 kW) with the supply temperature lower than 11 °C for 4 hours in summer after being fully charged in 8 hours. The inner tank filled with phase change material is for cooling thermal storage as a latent tank in the design. However, its capacity can be as high as 60 MJ as a sensible water tank for heating storage in winter. In the future study, the DPUTB model will be incorporated into the dual-source heat pump system for evaluating the overall system performance of demand side management in the long term.
During the past decade, the US Department of Energy (DOE)/National Nuclear Security Administration (NNSA) Nuclear Criticality Safety Program (NCSP) has been coordinating nuclear criticality safety (NCS) courses to provide training and qualification to new staff, supervisors, managers, regulators, and other professionals involved with NCS. To address the growing need for more NCS training possibilities, a subcritical assembly was designed at Oak Ridge National Laboratory (ORNL). The Oak Ridge Subcritical Assembly (ORSA), operated at ORNL, could be used in a new course for fissile material handlers/operators or as a backup training facility for currently existing NCSP hands-on NCS training. This paper describes some of the design steps necessary for obtaining a final ORSA design, beginning with a successful feasibility study performed in 2020. Numerous parameters within each main element of the assembly were considered, such as the reflector used, the type of fuel coating or plating used, and the number of fuel plates used. The design choices related to each parametric study described in this paper are detailed and justified at the end of each subsection. An overview of the current final design characteristics of ORSA and the experiments’ possibilities is also provided. ORSA will be built with fuel plates from legacy Aerojet General Nucleonics (AGN)-201M research reactors currently stored at the Y-12 National Security Complex (Y-12). The cylindrical fuel plates comprise UO 2 particles embedded in polyethylene and have a nominal enrichment of 19.5 ± 0.5 wt % 235 U. The basis for the final design was the feasibility study from 2020. In the feasibility study, ORSA achieved k eff = 0.95, corresponding to a multiplication factor of 20, with approximately 620 g of 235 U (four 4 cm plates, three 2 cm plates, and two 1 cm plates) and an 8.5 cm thick graphite reflector radially and on top of the assembly. The bottom of the assembly has a graphite thickness of 5 cm, and the chosen graphite density was 2.3 g/cm 3 . All design calculations were performed using SCALE 6.2.4 KENO-VI and with the ENDF/B VII.1 Continuous Energy cross-section library.
Steam piping networks are essential for optimizing performance in industrial processes and district heating systems. However, dynamic models that balance thermo-hydraulic accuracy with computational efficiency remain limited. In response, this paper presents a new discretized steam pipe model based on the plug flow approach, capturing key thermo-hydraulic behaviors while simplifying steam phase change processes. Implemented in Modelica, the model accurately calculates temperature and pressure distributions along steam pipelines. To improve computational efficiency for district-scale simulations, five model simplifications are introduced: lumped thermo-hydraulic functions, empirical correlations, fluid state approximations, steady-state dynamics and inclusion of flow derivatives. These simplified models achieve 85%-98% accuracy in predicting pressure drop and condensation losses, including dynamic condensate behavior during pipe warm-up—a factor often overlooked in existing models. The models support diverse network configurations, scaling effectively to systems with multiple distribution pipes and connected building loads. Discrete models provide detailed insights but exhibit a cubic increase in simulation time as the network scales by N connected building O(N 2.42 ). In contrast, lumped models simulate 10–28 times faster than discrete, offering quadratic scaling of simulation time O(N 1.73 ). However, they still require 6 times more computation time than a lossless network, highlighting the inherent computational challenges of modeling compressible fluid flow. In conclusion, the steady-state lumped variant, with its near-linear scalability in computational time O(N 1.01 ), emerges as an efficient solution for preliminary design evaluations and extensive parametric studies.
The design and techno-economic performance of a compact additively manufactured (AM) molten salt (MS)-to-supercritical carbon di-oxide (sCO2) primary heat exchanger (PHE) for solar thermal application is described. The PHE design consists of sCO2 flow through an array of microscale pin fins while the MS flows through mm-scale rectangular channels. Constraints imposed by AM using laser powder bed fusion method are considered in the design. Structural and fluid flow simulations are performed to arrive at a viable design of the core and headers. A simplified one-dimensional steady state model for the PHE is developed including the impact of surface roughness from the AM process. A process-based cost model is used to determine the tradeoff between thermofluidic design and manufacturing cost. A parametric study is performed using the thermo-fluidic and cost models to determine the set of geometrical and flow variables that result in high power density and low cost, while restricting the pressure drop on the sCO2 side to less than 2% of line pressure. Flow rates of MS and sCO2 were varied over heat capacity rate ratios ranging from 0.2 to 1. Results indicate that it is possible to design a low-pressure drop AM PHE with an effectiveness of 90% and a power density in excess of 10 MW/m3 (including headers). Fabrication of representative nickel superalloy specimens are shown to demonstrate that low-porosity parts with the requisite dimensional tolerance of PHE core can be generated.
This keynote presentation explores the behavior of headers—essential components of pipeline systems—using ANSYS simulation software and machine learning techniques. The study aims to predict the thermal and mechanical performance of headers under diverse conditions through both steady-state and transient simulations. We investigate critical parameters such as heat transfer coefficient, fluid velocity, and temperature to optimize header design. Conducted as part of a DOE project led by NCAT in collaboration with UNC Charlotte, this research encompasses multiple key topics. The initial section focuses on the behavior of header systems under steady-state conditions using ANSYS simulation. It underscores the importance of headers in industrial infrastructure, especially in the energy sector, and examines the implications of material selection and flow direction on heat transfer dynamics. Methodologically, we employ Computational Fluid Dynamics (CFD) analysis through ANSYS, detailing the development of models, material properties, geometry specifications, boundary conditions, and meshing strategies. Our simulations explore various operational parameters, including temperature and mass flow rates, crucial for predicting heat transfer coefficients and enhancing header design. Results from the study include parametric investigations into mesh sensitivity, viscosity model evaluations, and the effects of heat transfer locations, all validated against theoretical calculations. We conclude with insights on mesh optimization, the suitability of viscosity models, and recommendations for future research aimed at improving header system efficiency and sustainability in industrial applications.
This paper presents an application of the economics-by-design approach to the Radiant Integrated Thermo-photovoltaic Microreactor System (RITMS). The RITMS design is unique in that it directly couples a critical fission reactor with thermo-photovoltaic (TPV) panels for high efficiency energy conversion. This significant shift from electric conversion using traditional dynamic heat pumps leads to a simpler and more reliable system without turbomachinery and high pressurization. In working towards wrapping up the early design work, the economics-by-design approach, which centers economic competitiveness as the optimization parameter, is well suited in making a final determination on viability. This paper describes the computational sequence that was developed to couple the radiative and conductive heat transfer and feed operational performance to cost estimation. The framework was applied to maximize the power of the system, while minimizing the fuel enrichment. This method is applied to a reference RITMS design as part of a parametric sensitivity study, which revealed that the system is under moderated and that single unit plants could produce power as low as 300 dollar/MWh. This price point supports the notion that early in the RITMS design implementation, adoption into niche markets as a first-of-a-kind technology is possible. (authors)
In this work, we devised a new WEC (wave energy converter) called SR-WEC (Surface Riding WEC). The SR-WEC consists of two bodies: the outer cylinder with an armature assembly (body #1) and a magnet assembly (body #2) sliding inside the armature. For the SR-WEC, the relative sliding displacement and velocity are caused by gravity acceleration and the outer cylinder's motions, and they lead to electrical power generation. To evaluate its performance, a numerical simulation tool was developed, which solves the fully-coupled floater-mooring-generator dynamics. During the developing stage, the appropriate hydrodynamics model, sliding mechanics model, mooring dynamics model, and LEG (linear electric generator) electro-magnetic model were independently developed and then fully coupled in time domain to account for the cross-coupling interactions among them. Then, the developed simulation tool was verified component by component against various laboratory tests. Subsequently, systematic parametric studies were conducted with several important design parameters under various wave conditions to enhance power generation. After that, the average output power was evaluated in enlarged operational wave conditions. The present SR-WEC is particularly designed to be efficient at low sea states, which is good since they cover the majority of typical annual sea states.
Buildings’ thermal energy systems for providing space heating/cooling consume a considerable amount of electricity nationwide. Integrating thermal energy storage with buildings’ thermal systems has the potential to shave the peak electric demand and to overcome the mismatch between the intermittent renewable power and the fluctuating daily demand for electricity. A novel dual-purpose underground thermal battery (DPUTB) has been developed to provide diurnal thermal energy storage in conjunction with a dual-source heat pump (DSHP)system. A two-dimensional numerical model is developed to simulate the transient performance of the DPUTB. This model has similar accuracy as a detailed three-dimensional model developed with commercial heat transfer and fluid dynamics simulation program but with 1000 times faster computational speed. A parametric study is performed to identify a design of the DPUTB that can provide 14 kWh thermal storage capacity for each charging and discharging cycle. A system simulation has been developed to assess the performance of the designed DPUTB when it is integrated with a DSHP for conditioning a typical residential building in summer and winter. Simulation results indicate that the DPUTB can meet all the design requirements in both summer and winter with the simple rule-based control strategy and the overall integrated DPUTB and DSHP system can shift the electric load for meeting the thermal demand from the peak hours to off-peak hours during a day, which would result in considerable energy cost savings if a Time of Use electricity tariff is applicable.
To further the development of low-enriched uranium fuels, precedence has been placed on delivering the same amount of power while lowering the fuel temperature and radial temperature gradient. To address this, modeling efforts have resulted in a novel design featuring conductive fins of varying thermal conductivities and geometries inserted into the fuel matrix. These conductive inserts were not allowed to exceed 6% of the original fuel volume. This constraint was imposed due to other designs displacing 10% of fuel volume. A parametric study was performed that consisted of 2.56 million BISON simulations involving varying fin characteristics (i.e., fin thermal conductivity, number, and geometry) to determine the optimal geometric configuration for a desired amount of fuel volume displaced. The results from this study show that the thickness and length of each fin affect the fuel temperature and temperature gradient more than varying the number and thermal conductivity of the fins. The parametric study resulted in the development of an optimized combination to produce the lowest peak fuel temperature, lowest radial temperature gradient, and highest temperature reduction for the amount of original fuel volume displaced. The simulations presented in this work will eventually be compared with irradiation experiments of similar fuel designs at Idaho National Laboratory’s Advanced Test Reactor.
Abstract The design optimization of a diesel exhaust-coupled heat and mass exchanger that drives a 2.71 kW cooling capacity absorption heat pump is presented in this study. Fouling layer thermal resistance and pressure drops from single-tube experiments are used to develop a thermodynamic, heat transfer, and pressure drop model for the exhaust-coupled desorber. A parametric study is performed to select a desorber design that meets system performance while minimizing footprint. Experimental heat duties and pressure drops are within 10% and 3%, respectively, of the model predictions. Thus, large data sets from single-tube experiments with representative geometries are successful in accounting for fouling effects at the component level. Desorber design optimization based on this approach ensures continued heat pump performance after fouling. This study, along with the single-tube experiments, presents a systematic approach to design exhaust-coupled heat exchangers while considering the effects of fouling. These results are applicable for a wide range of waste-heat recovery applications, and this method can be extended to different geometries and operating conditions.