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At least 37 records · Page 2

Forecasting high-dimensional spatio-temporal systems from sparse measurements

This paper introduces a new neural network architecture designed to forecast high-dimensional spatio-temporal data using only sparse measurements. The architecture uses a two-stage end-to-end framework that combines neural ordinary differential equations (NODEs) with vision transformers. Initially, our approach models the underlying dynamics of complex systems within a low-dimensional space; and then it reconstructs the corresponding high-dimensional spatial fields. Many traditional methods involve decoding high-dimensional spatial fields before modeling the dynamics, while some other methods use an encoder to transition from high-dimensional observations to a latent space for dynamic modeling. In contrast, our approach directly uses sparse measurements to model the dynamics, bypassing the need for an encoder. This direct approach simplifies the modeling process, reduces computational complexity, and enhances the efficiency and scalability of the method for large datasets. We demonstrate the effectiveness of our framework through applications to various spatio-temporal systems, including fluid flows and global weather patterns. Although sparse measurements have limitations, our experiments reveal that they are sufficient to forecast system dynamics accurately over long time horizons. Our results also indicate that the performance of our proposed method remains robust across different sensor placement strategies, with further improvements as the number of sensors increases. This robustness underscores the flexibility of our architecture, particularly in real-world scenarios where sensor data is often sparse and unevenly distributed.

97 MATHEMATICS AND COMPUTING↗

Steam generator model design parameter sensitivity study for small modular reactor system

Here, this study focuses on design parameter sensitivity studies pertaining to several Once-Through Steam Generator (OTSG) model cases both with and without a riser using python and advanced risk assessment and optimization tool, i.e. Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), to support a Small Modular Reactor (SMR) system. The presented Steam Generator (SG) python-based model is a mathematical representation of a steam-generating unit for a Pressurized Water Reactor (PWR)-type SMR system, including fluid flow and heat transfer equations, models, and correlations. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system, such as the Heat Transfer Coefficient (HTC), Reynolds number, Nusselt number, and heat transfer performance. Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in the input parameters. By using RAVEN, detailed design parametric sensitivity studies. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10 % relative changes) for 600 samples. The analysis results give valuable insights into SG system performance, and provide justification for further research and development such as optimized sensor placement, design verification, validation, and optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles

Off-road vehicles, such as wheel loaders, excavators, and harvesters, are extensively utilized across a wide range of industries, including construction, agriculture, and mining. These machines have become indispensable in supporting the day-to-day operational needs of a nation, playing a critical role in various sectors' infrastructure and productivity. However, despite their utility, off-road vehicles are significant consumers of fossil fuels, resulting in substantial emissions that contribute to environmental degradation. This highlights the pressing need for research and technological advancements aimed at improving their energy efficiency and reducing their carbon footprint. There are, however, two primary challenges that must be addressed to achieve these goals. First, off-road vehicles typically perform both driving and working tasks simultaneously, which introduces a high level of complexity into their overall dynamic systems. Analysis the interactions between these functions is challenging. Second, research into off-road vehicles is inherently interdisciplinary, demanding expertise across several domains such as fluid power systems, vehicle dynamics, control theory, optimization techniques, and real-world implementation. Recognizing these challenges, we proposed the project titled "Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles" as a comprehensive solution to enhance fuel efficiency while simultaneously improving productivity. This project specifically focuses on autonomous off-road vehicles, with particular attention to wheel loaders, and seeks to develop novel methods to optimize energy consumption without sacrificing operational performance. The project integrates real-time control algorithms, vehicle dynamics modeling, and co-optimization of powertrain system and vehicle system to achieve these goals. Our optimization strategy dynamically co-optimizes critical parameters at both the powertrain and vehicle levels, including vehicle speed, working tool movements, powertrain dynamics, and engine operations in real-time. To streamline this optimization process, we developed a vehicle model that captures the key dynamics while significantly enhancing computational efficiency. This allows the system to intelligently minimize fuel consumption, all while maintaining or even improving productivity through real-time calculations during various off-road operations. To validate the effectiveness of this energy optimization method, we introduced a state-of-the-art Hardware-in-the-Loop (HIL) testbed. This reconfigurable testbed seamlessly integrates the actual engine with virtual models of the wheel loader's subsystems, allowing for accurate emulation of real-world operational loads and environments. By simulating these conditions, the HIL testbed enables us to evaluate the wheel loader’s performance under diverse working scenarios, ensuring the developed solution is applicable in real-world operations. This testbed proved to be instrumental in validating the optimization algorithms and demonstrating the system's practical effectiveness. During the evaluation and testing phase, we employed the HIL testbed to rigorously assess the energy savings and productivity improvements generated by the optimized system. The results were highly encouraging, revealing that the automated wheel loader achieved over 30% fuel savings compared to traditional, human-operated cycles, with comparable or even enhanced levels of productivity. The insights gained from this HIL-based testing provided critical validation of our approach and highlighted the potential for deploying these optimized autonomous technologies in real-world off-road vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Development of an Improved RELAP5-3D Model for the High Temperature Test Facility

High-temperature gas-cooled reactors (HTGRs) are rapidly approaching deployment. Confidence in transient analysis of these systems for design, optimization, and licensing calculations requires modeling and simulation tools that have been validated against data relevant to HTGR conditions. The High Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility for prismatic HTGRs. In spring and summer of 2019, HTTF was used for a series of experiments that now serve as the basis for the OECD/NEA Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data (HTGR T/H Benchmark). This benchmark contains problems for systems code, computational fluid dynamics (CFD), and coupled systems code/CFD modeling representing lower plenum mixing and both the depressurized and pressurized conduction cooldown (DCC and PCC respectively) transients. Benchmark problems include exercises for code-to-code and code-to-data comparisons as well as an exercise for error scaling between HTTF and the Modular High Temperature Gas-Cooled Reactor, which serves as the basis for the HTTF design. Previous analysis as part of the HTGR T/H benchmark used a RELAP5-3D model developed at Idaho National Laboratory (INL) and demonstrated an ability to reproduce trends in the measured data but difficulties reproducing experimental values within their uncertainty. These difficulties were largely attributed to assumptions made during the development of the initial RELAP5-3D model, which predated the HTTF experiments. A significant cause of difficulty reproducing the measured temperatures may be the radial nodalization of the previous RELAP5-3D model. The new model provides a finer nodalization to assess the impact of radial nodalization and allows for asymmetric heating within the core, which was a feature of multiple HTTF experiments. In this paper, we present the new RELAP5-3D model of HTTF. In addition to describing the new model, this paper compares the new and old models and provides results for a full-power steady state, a DCC, and a PCC in HTTF. These analyses are based on the code-to-code comparison exercises for the DCC and PCC problems of the HTGR T/H benchmark. We present the results of these exercises from the new model and compare them to the results of the old model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nanopore Confinement of C-H-O Mixed-Volatile Fluids Relevant to Subsurface Energy Systems

The overarching goal of OU’s contribution to the project was to use novel computational approaches to quantify the effect of variable nanopore features (pore size, volume, topology, and chemistry) and the presence of water or salt solutions on the sorption and transport of carbon-bearing fluids. To achieve this goal OU collaborators tested test two related hypotheses: • The transport of water and aqueous electrolytes in nanopores is controlled by pore size, pore wall composition, and the type of salt – structure-maker (e.g., CaCl 2 ) versus structure-breaker (e.g., NaCl) that affect the hydrogen-bonding network. • The structure, solubility, and transport of carbon-bearing molecules in water or aqueous electrolyte-filled nanopores are controlled by the substrate type including degree of hydration, and pore features, and regulated by the hydration structure of the guest molecules.

58 GEOSCIENCES↗

Development of Hydrogen-Fueled, Highly Energy-Efficient, Electro-Hydraulic Excavator

Regulations for CO2 emissions reduction are driving increasing demand for “zero emissions” off-road vehicles (ORVs). Hydrogen internal combustion engines (H2 ICEs) are closer to commercial viability, and less expensive than fuel cells. The major challenge is the slow torque response of H2 ICEs, that makes it difficult to sustain the harsh torque requirements typical of ORVs. The goal of this paper is to overcome this challenge by proposing an electro-hydraulic hybrid technology with hybrid powertrain and multi-pressure rail technology as fluid power system for an excavator, to enable the use of the H2 ICE, while improving efficiency. The study is based on simulation in MATLAB/Simulink environment, using duty cycle data from a 24-ton excavator. Simulation results show that in respect to the diesel-powered baseline, the proposed electro-hydraulic hybrid allows the use of a H2 ICE, eliminates CO2 emissions and ensures a 52% fuel consumption reduction.

08 HYDROGEN↗

R&D with NREL's Davison Circulating Riser System

The Davison circulating riser (DCR) is the National Renewable Energy Laboratory's (NREL's) pilot-scale recirculating riser reactor system. Coupled with an upstream fluid-bed pyrolysis system, it permits evaluation of catalytic cracking of biogenic feedstocks, as well as coprocessing of biogenic and fossil feedstocks in a commercially relevant pilot fluid catalytic cracker.

09 BIOMASS FUELS↗

Effect of Surface Roughness on Dynamic Stall in Pitching Motion

Dynamic stall plays a critical role in determining the performance and stability of a wide range of fluid-dynamics systems in various engineering applications. This unsteady aerodynamic phenomenon is particularly significant for maneuvering aircraft wings, jet aircraft subjected to gust encounters, helicopter rotor blades, and wind turbine blades [1–3]. The prediction of the dynamic stall vortex (DSV) is challenging due to factors such as unsteady aerodynamics, three-dimensional (3-D) effects, turbulence and flow separation, incoming gust, and surface impact effects [4–6]. Hence, advanced computational techniques and modeling approaches in computational fluid dynamics (CFD) would be required to enhance the accuracy and reliability of DSV predictions in dynamic stall scenarios. In the past, Batther and Lee [7] employed delayed detached eddy simulations (DDES) to understand the flow physics associated with the onset of dynamic stall. Their approach demonstrated that DDES achieves results comparable to those obtained from large-eddy simulations at a reduced computational cost. In another study, Khalifa et al. [8] examined the 3-D aspects of dynamic stall on a NACA 0012 airfoil using DES solvers. In conclusion, the findings underlined the superiority of 3-D simulations over two-dimensional approaches, particularly in predicting the lift coefficient values and capturing dynamic stall stages more precisely.

97 MATHEMATICS AND COMPUTING↗

Development and experimental evaluation of an acoustic flow meter prototype for measuring air flow

Here, this study outlines the development and testing of a flow meter prototype specifically designed for use in nuclear reactor environments. The meter uses flow-induced vibration to measure flow rates and is designed for remote monitoring in harsh environments where radiation can damage electronics. The device generates a vibration signal produced by a feedback system when fluid flows out of an orifice and interacts with a downstream wedge. The frequency of the vibration signal corresponds directly to flow rate and velocity. The study investigates geometric parameters intrinsic to the prototype, such as orifice height, width, edge distance, and chamber length. Different configurations were also tested, including a bypass loop with variable cross-sections around the device. The investigation results reveal the impact of these geometric parameters on the vibration signal output, providing valuable insights for future design improvements and enhancing the effectiveness of flow metering systems used in nuclear reactor applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Decadal-Scale Hydrothermal Alteration of Basalt: Implications for Long-Term Reactivity in Subsurface Technologies

Global demands to secure critical mineral supply chains and managing water resources require innovative resource management strategies. Subsurface basalt reservoirs offer a dual-purpose application, where CO2 enhanced critical metal recovery can be coupled with water remediation strategies for the extraction of economically important and environmentally relevant elements. This study utilizes static batch experiments conducted on Columbia River Basalt Group samples to evaluate long-term fluid–rock interactions relevant to coupled subsurface applications. Samples were reacted under elevated temperature and pressure conditions, for 296 and 4,061 days, providing a unique dataset to assess geochemical evolution, element partitioning, and aqueous chemistry over decadal timescales. The alteration was dominated by silicate, aluminosilicate, and oxide phases. Progressive hydrothermal alteration increased the cation exchange capacity through the formation of secondary minerals (e.g. clays and zeolites), influencing solute retention, ion exchange behavior, and aqueous chemistry. Grain-scale and bulk analyses revealed selective cation release and retention patterns, establishing a mechanistic baseline for predicting element mobility. These geochemical constraints inform the prospective use of CO2-enhanced metal recovery for critical resources (e.g. Co, Ni, Mn, Mg, Ti, Fe) and associated water-quality impacts, providing a foundation for the design and management of engineered fluid–rock systems in basalt reservoirs.

Gibson, Marie N.↗

Decomposing causality into its synergistic, unique, and redundant components

Causality lies at the heart of scientific inquiry, serving as the fundamental basis for understanding interactions among variables in physical systems. Despite its central role, current methods for causal inference face significant challenges due to nonlinear dependencies, stochastic interactions, self-causation, collider effects, and influences from exogenous factors, among others. While existing methods can effectively address some of these challenges, no single approach has successfully integrated all these aspects. Here, we address these challenges with SURD: Synergistic-Unique-Redundant Decomposition of causality. SURD quantifies causality as the increments of redundant, unique, and synergistic information gained about future events from past observations. The formulation is non-intrusive and applicable to both computational and experimental investigations, even when samples are scarce. We benchmark SURD in scenarios that pose significant challenges for causal inference and demonstrate that it offers a more reliable quantification of causality compared to previous methods.

applied mathematics↗

A multiphysics coupling framework for exascale simulation of fracture evolution in subsurface energy applications

Predicting the evolution of fractured media is challenging due to coupled thermal, hydrological, chemical and mechanical processes that occur over a broad range of spatial scales, from the microscopic pore scale to field scale. We present a software framework and scientific workflow that couples the pore scale flow and reactive transport simulator Chombo-Crunch with the field scale geomechanics solver in GEOS to simulate fracture evolution in subsurface fluid-rock systems. This new multiphysics coupling capability comprises several novel features. An HDF5 data schema for coupling fracture positions between the two codes is employed and leverages the coarse resolution of the GEOS mechanics solver which limits the size of data coupled, and is, thus, not taxed by data resulting from the high resolution pore scale Chombo-Crunch solver. The coupling framework requires tracking of both before and after coarse nodal positions in GEOS as well as the resolved embedded boundary in Chombo-Crunch. We accomplished this by developing an approach to geometry generation that tracks the fracture interface between the two different methodologies. The GEOS quadrilateral mesh is converted to triangles which are organized into bins and an accessible tree structure; the nodes are then mapped to the Chombo representation using a continuous signed distance function that determines locations inside, on and outside of the fracture boundary. The GEOS positions are retained in memory on the Chombo-Crunch side of the coupling. The time stepping cadence for coupled multiphysics processes of flow, transport, reactions and mechanics is stable and demonstrates temporal reach to experimental time scales. The approach is validated by demonstration of 9 days of simulated time of a core flood experiment with fracture aperture evolution due to invasion of carbonated brine in wellbore-cement and sandstone. We also demonstrate usage of exascale computing resources by simulating a high resolution version of the validation problem on OLCF Frontier.

97 MATHEMATICS AND COMPUTING↗

Scalable foundation models for numerical simulations on HPC platforms

In recent years, foundation models (FMs) have begun to reshape numerical simulations on high-performance computing (HPC) platforms. These large, pre-trained AI models enable rapid predictions across a broad range of physical domains, including Earth system modeling, fluid dynamics, materials science, as well as complex multi-modal simulations in aerospace engineering and fusion research. By training on diverse datasets, FMs learn intricate relationships and underlying physical behavior while also enabling the quantification of uncertainty in their predictions. This capability allows simulations that once required days of numerical calculation to be completed in minutes (FM inference), supporting real-time design optimization, uncertainty-aware decision making, and more comprehensive exploration of complex scenarios.

AI↗

NiCrMoNb age hardenable alloy for creep-resistant high temperature applications, and methods of making

Nickel alloys, methods of making nickel alloys, articles including the nickel alloys, uses of the alloys, and methods of treating nickel alloys are described. The inventive heat resistant structural materials are suitable for applications requiring high yield stress at room temperature and good creep strength at high temperatures, such as in gas turbines, steam turbines, fossil energy boilers, aero engines, power generation systems using fluids such as supercritical carbon dioxide (e.g., advanced ultra-supercritical power plants), concentrated solar power plants, nuclear power plants, molten salt reactors: turbine blades, casings, valves, heat exchangers and recuperators.

Detrois, Martin↗

Insights into the hydro-mechanical behavior of a decimeter-scale fracture using the mini-SIMFIP probe

ABSTRACT: Understanding hydro-mechanical couplings in fractured rocks is essential for predicting the rock mass response during high-pressure fluid injection, including the stimulation of enhanced geothermal systems. However, fluid-driven fracture dislocations are challenging to measure due to the need for local displacement data at high fluid pressures. In this study, fluid-driven displacement across a decimeter-scale laboratory fracture was investigated using the mini-SIMFIP (step rate injection method for fracture in-situ properties) probe, which is a smaller version of the SIMFIP tool (Guglielmi et al., 2014). The mini-SIMFIP probe is able to resolve the full 3D displacement vector of a fracture. The probe was installed in one of two boreholes across a decimeter-scale saw-cut granite fracture. Two pressure step injection tests were conducted under the same isotropic stress conditions. By varying injection between the boreholes, we estimated the aperture profile across the fracture. The results show a consistent pressure-dependent opening as long as steady-state flow was maintained. At a certain pressure step, steady-state conditions were no longer achievable and the fracture opened rapidly. The pressure-opening relationship diverged between the two tests and indicated a homogenization of the aperture profile and an increase in the non-linearity of the flow regime.

Osten, J↗

Performance Investigation of High-temperature Latent Heat Storage for Integration with Advanced Nuclear Reactors

Integrating thermal energy storage (TES) with advanced nuclear reactors enhances the flexible use of nuclear energy, facilitating its expansion beyond conventional electricity generation. High-temperature TES, capable of storing heat above 400 degree C, emerges as a vital carbon-free energy solution for decarbonizing industrial sector, especially when combined with low-emission energy sources like advanced nuclear reactors. Idaho National Laboratory (INL) has recently developed a novel design for high-temperature latent heat storage system, called Heat pipe Integrated Thermal Battery (HITB), and efforts are underway to experimentally demonstrate the concept. HITB employs liquid-metal heat pipes to establish thermal linkage between TES and nuclear systems without direct fluid exchange, minimizing the potential risk of the integrated systems such as cross-contamination. HITB is designed to achieve high charging and discharging efficiency as well as high energy storage density by employing metal alloys as Phase Change Material (PCM). Initial proof-of-concept experiments are being undertaken using an aluminum alloy (Al59%-Mg35%-Zn6%). This paper discusses current progress of the HITB project at INL, seeking to develop high-temperature TES for versatile integration with advanced nuclear reactors, and shares insights from the performance evaluations via numerical modeling and analysis.

25 ENERGY STORAGE↗

SiC Receiver/Reactor by Additive Manufacturing for Concentrated Solar Thermocatalysis with Thermal Energy Storage (Final Technical Report - Public)

The direct use of solar thermal energy provides opportunities for low-cost heating sources for a variety of applications. Ultra-high temperatures around 1000°C are high value and highly useful for energy-demanding industries. Many materials cannot withstand these conditions. In the area of Sustainable Chemicals, further limitations on material stability exist. Combining state-of-the-art materials with new designs provides a promising pathway for harvesting solar thermal energy and performing high temperature chemical processes. However, conventional manufacturing limits the potential for design flexibility. In this project, Additive Manufacturing was combined with advanced materials and new chemical reactor designs. In addition, 24/7 energy is necessary for chemical processing, and designs for ultra-high temperature thermal storage were devised. Specifically, preliminary design of a novel solar thermal receiver was developed in this project and designed to work with thermocatalytic reactors for producing sustainable chemicals and fuels. An ultra-high temperature particle storage system and heat exchangers were proposed to transport ultra-hot air as thermal fluid for the system. On a broader scale, this system could be used to tap solar thermal energy for a centralized facility with capability of transferring that heat to various segments at a full range of temperatures to 1000°C. The project pushed the temperature boundaries past those in current use, and Additive Manufacturing was envisaged for fabricating the receiver to meet requirements of extreme environments. An extensive analysis of silicon carbide additive manufacturing was performed to compare the thermal and mechanical properties of complex geometries compared to conventional material and those manufactured via other methods. The Additive Manufacturing via Binder-Jet printing was optimized and characterized to provide high quality and reproducible components capable of withstanding the proposed extreme environments. The designs for the concentrating solar thermal cavity with ultra-hot air thermal fluid showed high performance in simulations, attributable to the complex optimized geometries of the 3D printed systems. The bright future of Additive Manufacturing with advanced materials developments should provide more options and even higher quality as the technology further develops. Current costs for Additive Manufacturing of advanced ceramics is relatively low, however post-processing of the materials for extreme environments is currently high. There is little industrial-scale infrastructure for these, but it is growing as niche applications become more mainstream. The results of the project can be translated into similar extreme environments for concentrating solar thermal energy as well as its integration with ultra-hot air thermal fluids. A number of industries that require ultra-high temperatures need to electrify or otherwise decarbonize for climate goals, and this project showed that theoretically there is a pathway to do so with direct concentrated solar thermal power.

10 SYNTHETIC FUELS↗

Nuclear Thermal Energy Storage Configurations for Industrial Combined Heat and Power Supply: Conceptual Study and Engineering Designs

The industries examined in this report primarily rely on moderate-temperature heat provided by gas- or coal-fired boilers and combined heat and power (CHP) plants, delivered through standard process steam systems. High-temperature energy demands are often industry-specific and typically exceed the capabilities of high-temperature gas-cooled reactors (HTGRs). While it is technically feasible to replace process steam from fossil-based heat sources with nuclear energy, certain industries, such as methanol production and pulp and paper, face technoeconomic challenges in integrating nuclear energy without major changes or a technological shift. This is mainly due to the limited external energy demand remaining after the use of internal byproducts, waste heat recovery, and simple efficiency improvements. Achieving full decarbonization of these processes with nuclear energy would require significant technological advancements, involving experimental technology and substantial investments, making widespread adoption in existing industrial plants unlikely in the near term. This study reviews TES options in the context of enabling a flexible CHP supply while maintaining a steady nuclear heat input. Heat storage systems that interface between the reactor primary fluid and the CHP system offer superior performance and flexibility. Specifically, steam extraction downstream of the reheater with a two-tank molten-salt TES appears as the best solution regarding thermodynamic system benefits and system drawbacks. Using selected system configurations, a conceptual design of an industrial energy park was developed for industries with varying energy demands, such as steel production plants utilizing electric arc furnaces (EAFs) and chemical plants, as well as for those with constant energy demands, like petroleum refineries. This design highlights the capabilities of TES and explores its potential business cases. The study also conceptually develops the potential for integrating additional energy sources with nuclear systems through the implementation of TES. The potential of the HTGR-TES-CHP system was also evaluated considering key uncertainties such as industrial demand profiles, external grid access availability, and eligible tax credit levels, using the Holistic Energy Resource Optimization Network. Sensitivity of net present value to these uncertainties was analyzed to determine the optimal number of nuclear reactors (and CHP systems) and the suitable TES capacity. The results were interpreted from a decision-maker’s perspective, focusing on three key areas: deployment strategy (oversized units vs. undersized units with TES support), industrial process characteristics (thermal-intensive single profiles vs. electricity-intensive combined profiles), and operational goals (maximizing profits vs. minimizing natural gas (NG) consumption or external grid dependence). The optimization results indicate that the HTGR-TES-CHP system significantly reduces reliance on NG boilers for individual industrial processes by 9-60% (in NG capacity factor), with an average reduction of 38%, compared to standalone NG boiler operation case (Business As Usual [BAU]). For combined industrial processes, the reduction ranges from 37-77%, with an average of 60%. Additionally, the system greatly reduces dependence on external grids. In meeting industrial electrical demands, a 33-100% self-sufficient internal electricity supply is achieved for single industrial process, with an average of 74%, compared to the BAU scenario, where 100% of electricity is imported. For combined processes, 35-100% of internal electricity demands are met by the reactor, with an average of 73%. At last, the relative NG price levels at which the proposed HTGR-TES-CHP system can cost-effectively enter the market currently dominated by existing NG boilers were estimated. For a moderate HTGR CAPEX level ($\$$2500/kWth, $\$$6329/kWe), the analysis suggests that NG prices must be 2.5 to 7 times higher than HTGR variable operating and maintenance costs for single industrial process, and 5.5 to 9.5 times higher for a combined process scenario. Tax credit modeling shows that the Investment Tax Credit significantly reduces the price threshold needed to break even, making the system competitive with NG boilers in certain cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗