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

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At least 307 records · Page 17

Developing Near Optimal Control Sequences for Chiller Plants with Water-side Economizers: A Case Study in a Warm and Marine Climate

Various advanced control sequences for chiller plants with water-side economizers (WSE) have been proposed in literature, but the optimization of those controls is limited. It is possible to maximize energy savings by developing near-optimal control sequences, which are dependent on several factors such as the load profile. To address these gaps, we first identify an advanced control sequence and three key control parameters for chiller plants with WSE. Next, optimizations are performed to minimize energy consumption for seven combinations of control parameters. A chiller plant with WSE system in a warm and marine climate is studied and two load profiles are considered. The system and controls are modeled using the Modelica Buildings library. The results show optimizing the selected control parameters can reduce energy consumption by up to 11% depending on the load profile. Specifically, optimizing the cooling tower efficiency threshold in the condenser water reset control can significantly reduce energy savings for the variable load profile by efficiently shifting the load from the cooling tower to the chiller. This paper provides practical guidance for developing near-optimal control sequences for chiller plant with WSE systems considering impacts such as the load profile.

chiller plant↗

Comparative Analysis of HEATNETS for Geothermal Network Performance

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification and validation process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study focuses on a validation of HEATNETS using results from TRNSYS. HEATNETS is not intended to replace other modeling tools, but this work demonstrates, via a comparison with an industry standard code, that HEATNETS can be a unique, high-level and rapid modeling tool for estimating the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗

Freestream turbulence effects on unsteady wind turbine loads and wakes: An IDDES study

We investigate numerically the effects of freestream turbulence on the unsteady aerodynamics and wakes of the National Renewable Energy Laboratory Phase VI wind turbine rotor for increasing wind speed. Turbulence is modeled using the Improved Delayed Detached-Eddy Simulation (IDDES) method. As a first step, a detailed mesh resolution study is conducted with the decaying freestream turbulence model at turbulence intensity of 0.5%. Our blade-resolved IDDES simulations show that grid-independent average torque and thrust results can be achieved with relatively coarse meshes, whereas dramatically higher mesh resolution is required for grid-independent results for power spectral densities of thrust force, especially in the deep-stall regime. Comparing the loads with the Shear-Stress Transport model demonstrates the superiority of IDDES in predicting massively separated flows. The aerodynamic performance and wake predictions with the decaying freestream turbulence model are compared with the synthetic freestream turbulence model. Both models predict nearly the same loads, spectral energy content, and wake characteristics. The properties of both the near- and far-wake regions are then examined. Furthermore, we show that separated boundary layers accelerate turbulent mixing and entrainment of the external flow, which results in faster wake recovery. The effect of increasing turbulence intensity to 6% is investigated using the synthetic freestream turbulence model. In contrast with the fully attached boundary layer, higher freestream turbulence in deep stall does not significantly affect the loads and vortex-shedding characteristics. However, the turbulent mixing in the wake is enhanced, which further hastens the recovery of the self-similar velocity profile. In general, increasing the wind speed at high turbulence intensity shifts the recovery farther upstream and increases the wake width.

17 WIND ENERGY↗

Crack Identification and Characterization in Deformed Nb3Sn Rutherford Cable Stacks Using Machine Learning

An investigation of instance segmentation of cracks in Nb3Sn 4-stack 40-strand Rutherford cables using machine learning is presented. Three samples were uniaxially and biaxially loaded before metallographic inspections were performed. The Mask R-CNN model was used in the Detectron2 framework with pre-trained weights but fine-tuned to detect and segment cracks. The model detected cracks with bounding box and mask average precisions (AP) of 42.8 and 27.9, respectively, and was used for instance segmentation of all cracks in the three samples. More cracks were found in the sample pre-loaded along the z-axis (i.e., along the cable length). Pre-loading along the x-axis (i.e., on the cables edges) reduced the number of cracks and changed the crack orientation distribution, away from being highly aligned with the y-axis (i.e., normal to the cables broad faces), i.e., the direction with the highest applied load. Fine-tuning of the Segment Anything Model (SAM) was also studied but performed poorly without human-provided prompts. However, the zero-shot capability of SAM showed high promises to accelerate the image annotation process for applications beyond this study.

Croteau, Jean-Francois↗

Impact of Limited Degree of Freedom Drag Coefficients on a Floating Offshore Wind Turbine Simulation

The worldwide effort to design and commission floating offshore wind turbines (FOWT) is motivating the need for reliable numerical models that adequately represent their physical behavior under realistic sea states. However, properly representing the hydrodynamic quadratic damping for FOWT remains uncertain, because of its dependency on the choice of drag coefficients (dimensionless or not). It is hypothesized that the limited degree of freedom (DoF) drag coefficient formulation that uses only translational drag coefficients causes mischaracterization of the rotational DoF drag, leading to underestimation of FOWT global loads, such as tower base fore-aft shear. To address these hydrodynamic modeling uncertainties, different quadratic drag models implemented in the open-source mid-fidelity simulation tool, OpenFAST, were investigated and compared with the experimental data from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project. The tower base fore-aft shear and up-wave mooring line tension were compared under an irregular wave loading condition to demonstrate the effects of the different damping models. Two types of hydrodynamic quadratic drag formulations were considered: (1) member-based dimensionless drag coefficients applied only at the translational DoF (namely limited-DoF drag model) and (2) quadratic drag matrix model (in dimensional form). Based on the results, the former consistently underestimated the 95th percentile peak loads and spectral responses when compared to the OC5 experimental data. In contrast, the drag matrix models reduced errors in estimates of the tower base shear peak load by 7–10% compared to the limited-DoF drag model. The underestimation in the tower base fore-aft shear was thus inferred be related to mischaracterization of the rotational pitch drag and the heave motion/drag by the limited-DoF model.

17 WIND ENERGY↗

Assessing plasma face component thermal response to rotating 3D magnetic fields for SPARC tokamak

Thermal response simulations of plasma-facing components (PFCs) in the SPARC tokamak, performed with the HEAT code, show that three-dimensional (3D) heat loads resulting from stationary n=1 perturbations require highly radiative scenarios, with up to 95% of the power crossing the separatrix (P SOL ) being radiated, to maintain PFC temperatures within acceptable operational limits, whereas the application of slowly rotating 3D fields substantially reduces the thermal loads. The HEAT module, developed to predict heat loads from non-axisymmetric plasmas, is extended to model time-dependent heat flux patterns generated by rotating 3D fields, and a comprehensive thermal analysis is performed on PFCs subjected to both the maximum and minimum power loads, as well as to rotating heat flux distributions, to evaluate the temperature evolution for varying perturbation amplitudes and rotation frequencies. The extension of this analysis to 3D fields with toroidal mode number n=2 shows that this configuration leads to weaker localized heat flux peaks relative to the n=1 case, enabling safe operation with less than 80% of the power radiated when static 3D fields of low amplitude are applied, while using slowly rotating fields at higher amplitudes. These results indicate that n=2 perturbations are generally less detrimental to divertor power exhaust, emphasizing the strong dependence of divertor power exhaust on the characteristics of the applied 3D fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training

Large Language Models (LLMs) have demonstrated remarkable performance in various natural language processing tasks. However, the training of these models is computationally intensive and susceptible to faults, particularly in the attention mechanism, which is a critical component of transformer-based LLMs. In this paper, we investigate the impact of faults on LLM training, focusing on INF, NaN, and near-INF values in the computation results with systematic fault injection experiments. We observe the propagation patterns of these errors, which can trigger non-trainable states in the model and disrupt training, forcing the procedure to load from checkpoints. To mitigate the impact of these faults, we propose ATTNChecker, the first Algorithm-Based Fault Tolerance (ABFT) technique tailored for the attention mechanism in LLMs. ATTNChecker is designed based on fault propagation patterns of LLM and incorporates performance optimization to adapt to both system reliability and model vulnerability while providing lightweight protection for fast LLM training. Evaluations on four LLMs show that ATTNChecker on average incurs on average 7% overhead on training while detecting and correcting all extreme errors. Compared with the state-of-the-art checkpoint/restore approach, ATTNChecker reduces recovery overhead by up to 49×.

Liang, Yuhang [University of Alabama - Birmingham]↗

Enhancing power grid resilience to winter storms via generator winterization with equity considerations

Here we develop two-stage stochastic programming models for generator winterization that enhance power grid resilience while incorporating social equity. The first stage in our models captures the investment decisions for generator winterization, and the second stage captures the operation of a degraded power grid, with the objective of minimizing load shed and social inequity. To incorporate equity into our models, we propose a concept called adverse effect probability that captures the disproportionate effects of power outages on communities with varying vulnerability levels. Grid operations are modeled using DC power flow, and equity is captured through mean or maximum adverse effects experienced by communities. We apply our models to a synthetic Texas power grid, using winter storm scenarios created from the generator outage data from the 2021 Texas winter storm. Our extensive numerical experiments show that more equitable outcomes, in the sense of reducing adverse effects experienced by vulnerable communities during power outages, are achievable with no impact on total load shed through investing in winterization of generators in different locations and capacities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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↗

Nuclear microreactor transient and load-following control with deep reinforcement learning

The economic feasibility of nuclear microreactors will depend on minimizing operating costs through advancements in autonomous control, especially when these microreactors are operating alongside other types of energy systems (e.g., renewable energy). This study explores the application of deep reinforcement learning (RL) for real-time drum control in microreactors, exploring performance in regard to load-following scenarios. By leveraging a point kinetics model with thermal and xenon feedback, we first establish a baseline using a single-output RL agent, then compare it against a traditional proportional–integral–derivative (PID) controller. This study demonstrates that RL controllers, including both single- and multi-agent RL (MARL) frameworks, can achieve similar or even superior load-following performance as traditional PID control across a range of load-following scenarios. In short transients, the RL agent was able to reduce the tracking error rate in comparison to PID by one half to one third. Over extended 300-minute load-following scenarios in which xenon feedback becomes a dominant factor, PID maintained better accuracy, but RL still remained within a 1% error margin despite being trained only on short-duration scenarios. This highlights RL’s strong ability to generalize and extrapolate to longer, more complex transients, affording substantial reductions in training costs and reduced overfitting. Furthermore, when control was extended to multiple drums, MARL enabled independent drum control as well as maintained reactor symmetry constraints without sacrificing performance---an objective that standard single-agent RL could not learn. We also found that, as increasing levels of Gaussian noise were added to the power measurements, the RL controllers were able to maintain lower error rates than PID, and to do so with at least 10% and upwards of 150% less control effort. These findings illustrate RL's potential for autonomous nuclear reactor control, laying the groundwork for future integration into high-fidelity simulations and experimental validation efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Environmentally Assisted Fatigue in Light Water Reactor Environment

This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Constraining Black Carbon Aging in Global Models to Reflect Timescales for Internal Mixing

The radiative effects of black carbon depend critically on its atmospheric lifetime, which is controlled by the rate at which freshly emitted combustion particles become internally mixed with other aerosol components. Global aerosol models strive to represent this process, but the timescale for aerosol mixing is not easily constrained using observations. In this study, we apply a timescale parameterization derived from particle‐resolved simulations to quantify, in a global aerosol model, the timescale for internal mixing. We show that, while highly variable, the average timescale for internal mixing is approximately 3 hr, which is much shorter than the 24‐hr aging timescale traditionally applied in bulk aerosol models. We then use the mixing timescale to constrain the aging criterion in the Modal Aerosol Module. Our analysis reveals that, to best reflect timescales for internal mixing, modal models should assume that particles transition from the hydrophobic (fresh) to the hydrophilic (aged) class once they accumulate a coating thickness equal to four monolayers of sulfuric acid, as opposed to the model's current aging criterion of eight monolayers. We show that, in remote regions like the Arctic and Antarctic, predictions of black carbon loading and its seasonal variation are particularly sensitive to the model representation of aging. By constraining aging in global models to reflect mixing timescales simulated by the particle‐resolved model, we eliminate one of the free parameters governing black carbon's long‐range transport and spatiotemporal distribution.

54 ENVIRONMENTAL SCIENCES↗

Influence of thermal treatment on structure and catalytic performance of ceria-zirconia supported copper oxide (CuO x /Ce y Zr 1-y O 2 ) catalysts for CO oxidation

Copper oxide (CuO x ) supported on ceria-zirconia (Ce y Zr 1-y O 2 , y = 1.0, 0.5, 0.0) catalysts were investigated to elucidate the effects of thermal treatment on their physicochemical properties and catalytic performance in carbon monoxide (CO) oxidation. Here, the catalysts were synthesized via a one-pot chemical vapor deposition (OP-CVD) method at 700˚C and 900˚C with controlled Cu loading. Characterization techniques, including synchrotron X-ray diffraction (S-XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), inductively coupled plasma spectroscopy (ICP), and N 2 adsorption-desorption, were implemented to probe the crystalline structure, molecular and electronic structure, oxygen vacancies, specific surface area (SSA) and metal loading. CO oxidation was chosen as a model reaction to explore the structure-catalytic performance relationship. A ∼100% CO conversion was achieved at < 150˚C, particularly with the CuO x /CeO 2 catalyst calcined at 700˚C. In contrast, calcination at 900˚C caused a ∼90% decrease in SSA and a ∼24% increase in T 50 . Activity tests revealed that increasing ZrO 2 content lowered CO oxidation activity despite generating more defect sites. In-situ measurement of the 700 °C calcined samples revealed the presence of stable and unstable defects in CuO x /Ce 0.5 Zr 0.5 O 2 and CeO 2 respectively, which play a key role in the activity of the catalysts. The results highlight that catalytic performance is closely related to the SSA. Furthermore, an optimum calcination temperature favor significant oxygen vacancy formation with required CuO x -support interactions, enhancing redox properties and catalytic performance.

36 MATERIALS SCIENCE↗

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enhancing heat pump water heater performance with embedded phase change materials thermal energy storage: First hour rating improvement and demand response operation

The increasing global emphasis on energy efficiency and sustainability has put heat pump water heaters (HPWHs) in the spotlight as an energy-efficient alternative to traditional water heating systems. However, their widespread adoption is limited by challenges such as insufficient First Hour Rating (FHR), suboptimal control mechanisms, and limited flexibility for demand response operations. Here, to address these limitations, this study proposes an innovative HPWH system integrated with embedded phase change material (PCM)-based thermal energy storage (TES). The research introduces a novel design and control strategy that leverages optimized PCM integration to enhance thermal storage capacity, improve hot water delivery during peak demand, and increase load-shifting potential. A combination of system modeling, performance simulation, and demand response control strategy evaluation was employed to quantify the benefits of PCM integration. Results demonstrate that the proposed PCM-TES HPWH system significantly enhances FHR, with an optimal 7.0 lb. of PCM increasing FHR by over 26 %—from 62 to 78 gal—for a standard 50-gal HPWH. Additionally, under advanced demand response operation using a preheat strategy, the system reduces the percentage of control temperature out-of-band time from 65 % (conventional HPWH) to just 11.6 %, enabling a more stable and efficient hot water supply. This research contributes a novel PCM-embedded HPWH design and control framework that addresses both performance and grid-interactivity challenges. The findings offer a viable pathway to enhancing the operational efficiency, flexibility, and grid responsiveness of residential water heating systems.

Demand response control↗

Fuel Behavior Implications of Reactor Design Choices in Pressurized Water SMRs

Small pressurized water reactors (PWRs) can feature boron free operation, natural circulation mode, reduced height assemblies and/or long refueling cycles. This paper attempts to explore core design optimization for each of these design evolutions. In consequence, five core design layouts are developed incorporating boron free operation with continuous control rods insertion, natural circulation with low burnup/low power density design, natural circulation with high burnup/low power density design, forced circulation with standard core power density design, and forced circulation with high power density design. These cores’ performance is compared to a standard 4-loop PWR. The design process aims to improve the fuel cycle cost under safety constraints through core design optimization using CASMO4E/SIMULATE3 reactor physics codes and FRAPCON4.1 fuel performance assessment tool. Core modeling assumes standard 17x17 PWR fuel assemblies loaded with low enriched uranium (LEU) up to 5wt% or LEU+ (i.e., below 10wt% enrichment) pellets with gadolinium oxide (Gd2O3) as the burnable poison. Satisfactory core and fuel performances are obtained for all the designed cores under steady state and considered overpower transients. For low power density operation, long cycle lengths are achieved reaching a 2.5- and a 5-year cycles and peak rod-average burnup is pushed to 83 MWd/kgU. Other cycle lengths are maintained at 18 months. Boron free operation exhibits the ability to achieve longer cycle lengths at the cost of higher peaking factors leading to high local power and fuel temperatures which prevents sizable power uprates and is deemed uneconomical. Fuel assembly height reduction allows coolant velocity retrofit which enables higher core power density without violating structural integrity of the fuel assembly. As a result, a core power density of 123 kW/l is reached where total cladding hoop strain becomes the limiting parameter.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Multi-Agent Hierarchical Deep Reinforcement Learning for HVAC Control With Flexible DERs

As electricity consumption in commercial and residential buildings continues to rise, reducing energy costs presents an increasing challenge. Heating, ventilating, and air-conditioning (HVAC) systems, which typically account for 40%-50% of a building's energy use, are prime targets for energy savings. Intelligent control of HVAC temperature through the exploitation of HVAC load flexibility brings significant potential to reduce energy consumption and electricity expenses. The nonlinear models of HVAC systems challenge traditional control methods, while the uncertainty introduced by HVAC load flexibility complicates distributed energy resource (DER) management using conventional optimal dispatch techniques. In response to these challenges, we propose a hierarchical multi-agent deep reinforcement learning (DRL) approach. The lower-level agents focus on balancing comfort and energy conservation, while the upper-level DRL agents optimize the use of DERs to reduce peak demand based on the control outcomes of the HVAC by the lower-level agents. Here, in the upper-level agents, we incorporate a multi-agent structure based on ensemble learning, which acts based on historical and current data without relying on precise load forecasting to address the delayed rewarding issue in DRL. This allows for the effective reduction of energy costs. The proposed method is tested using a real-world microgrid comprising 413 buildings in Southern California, and the results demonstrate that our approach can significantly reduce overall electricity bills while ensuring the comfort of consumers and residents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CalTestBed - Delphire - Testing and Evaluation of Delphire Sentinel System (CRADA Final Report)

The Delphire Sentinel is a modular fire detection and communications system operating as a mobile field unit, with low voltage DC power supplied by onboard photovoltaics (PV) and batteries. The Sentinel addresses several aspects of fire detection, communications and data analysis. The Sentinel's mobility enables it to be rapidly deployed and operate independently of existing power and communications networks. The duration of independent operation depends critically on the energy consumption of the systems and performance of the onboard PV and battery. The purpose of this testing is to ascertain the power draw and energy consumption of the Delphire Sentinel prototype system under several operational states, including various data transfer packet sizes, transmission time and frequencies, and communication pathways (Wi-Fi, cellular, satellite) expected to be encountered in field deployments. It will also include procedures to test the ability of the Sentinel to operate for extended periods without loss of functionality. Based on results from energy and power measurements, and anticipated duty cycles in field deployments, we will model annual system autonomy (e.g. loss of load probability) for off-grid operation in representative locations.

47 OTHER INSTRUMENTATION↗