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DOE OSTI2025

Temperature sensitivity of the equilibrium neutronics and accident analysis of the HTR-10

Pebble-Bed High-Temperature Gas-cooled Reactors (PB-HTGR) are moderated by the graphite in the fuel pebbles and the graphite reflector surrounding the pebble-bed. Because graphite is by far the most abundant material in PB-HTGRs and the primary moderator, accurate modeling of the graphite material, including density, impurities, and temperatures, is crucial for accurate computational modeling and simulation of these reactors. While main characteristics of the graphite components are often known, the local temperature is less well known and often averaged over all components. Here, this work studies the impact of considering accurate temperature profiles in the graphite material on the generation of a small PB-HTGR model at the state of equilibrium operation and on short-term accident progression. The fuel compositions for the PB-HTGR were determined using a jump-in equilibrium modeling method, the Axial Radial Zone Equilibrium Modeling (AR-ZEM) method. In contrast to previous work, the AR-ZEM method was used considering thermal-hydraulic feedback from the MELCOR code to determine temperatures of the fuel pebbles and the surrounding graphite reflector. The consideration of an axial and radial temperature profile in the core and reflector, as opposed to uniform material temperatures, had an impact of almost 1,300 pcm on the equilibrium core eigenvalue and caused significant differences in the discharged plutonium fuel inventory with up to 4.9% and 11.0% for Pu-239 and Pu-242, respectively. To assess the impact on short-term accident progression, two Anticipated Transient Without SCRAM (ATWS) events, a Pressurized Loss of Forced Coolant (PLOFC) and a Control Rod Withdrawal (CRW) with loss of flow, were simulated with MELCOR. The use of temperature profiles in the equilibrium core models did not reveal a significant impact on the temperature, power, or reactivity responses during the transients. In conclusion, a need for consideration of accurate temperature profiles, in particular for the graphite reflector, was found for the generation of equilibrium PB-HTGRs core models using jump-in methods, but detailed temperature profiles may not be necessary when performing conservative transient analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Practical Start-Up Process of Multiple Grid-Tied Voltage-Sourced Inverters in Laboratory

Starting up inverter-based resources (IBRs) and integrating them into a grid are important in real-world engineering and there are many challenges to be tackled. Using a laboratory-scale hardware test bed (50 Watt and 20 V), this paper demonstrates the challenges and provides a practical start-up process that can smoothly energize two grid-tied voltage-sourced inverters (VSI) and synchronize the VSIs into a 60-Hz grid. The hardware test bed consists of two SiC VSIs and a 45-kW Chroma grid simulator to act as the grid. The inverter controls are implemented in OPAL-RT OP5600, which has the measurements sensed, control algorithms processed, and gate signals generated and sent to the VSI switches. This research focuses on examining how to energize VSIs and how to synchronize the VSIs into the grid. The best energizing approach is summarized based on comparison and analysis of the experiment results. The presented approach can prevent large transients during the start-up process.

Wang, Zhengyu↗

DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗

DOE OSTI2021

Fast Grid Frequency Support from Distributed Energy Resources

This report describes research related to electric power system frequency support from inverter-coupled distributed energy resources (DERs). This research was initiated under the U.S. Department of Energy’s Grid Modernization Laboratory Consortium (GMLC) and also contains work funded through a Cooperative Research and Development Agreement with Hawaiian Electric. The purpose of this report is to summarize the findings of simulations, hardware testing, power hardware-in-the-loop (PHIL) simulation, and analysis examining the effects of DER frequency support on the Oahu power system. This report also includes recommendations for consideration in the use of DER grid frequency support functionality, and related topics. Note that a previous GMLC Technical Report from this project also provided specific recommendations for the activation of one specific grid frequency support function, frequency-watt control, for overfrequency events in Hawaii. Those recommendations included recommended frequency-watt control settings, which have since been approved by the Hawaii Public Utilities Commission on October 20, 2017, for system-wide activation. This report builds on the previous report by considering not only overfrequency events but also underfrequency events, and by considering distributed energy storage systems in addition to photovoltaic (PV) systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Performance Evaluation of an Occupancy-Based HVAC Control System in an Office Building

As new algorithms incorporate occupancy count information into more sophisticated HVAC control, these technologies offer great potential for reductions in energy costs while enhancing flexibility. This study presents results from a two-year field evaluation of an occupancy-based HVAC control system installed in an office building. Two wings on each of the building’s 2–11 floors were equipped with occupancy counters to learn occupancy patterns. In combination with proprietary machine learning algorithms and thermal modeling, the occupancy data were leveraged to implement optimized start, early closure, and adjustments to fan operation at the air handling unit (AHU) level. This study conducted a holistic evaluation of technical performance, cost-effectiveness analysis, and user satisfaction. Results show the platform reduced weekday AHU run times by 2 h and 35 min per AHU per day during the pandemic time period. Simulation shows that 6.1% annual whole-building savings can be achieved when the building is fully occupied. The results are compared with prior studies, and potential drivers are discussed for future opportunities. The assessment results shed light on the expected in-the-field performance for researchers and industry stakeholders and enabled practical considerations as the technology strives to move beyond research-grade pilot trials into product-grade deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution

Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.

17 WIND ENERGY↗

DOE OSTI2025

Hardware-Efficient Quantum Phase Estimation via Local Control

Quantum phase estimation plays a central role in quantum simulation as it enables the study of spectral properties of many-body quantum systems. Most variants of the phase estimation algorithm require the application of the global unitary evolution conditioned on the state of one or more auxiliary qubits, posing a significant challenge for current quantum devices. In this work, we present an approach to quantum phase estimation that uses only locally controlled operations, resulting in a significantly reduced circuit depth. At the heart of our approach are efficient routines to measure the complex phase of the expectation value of the time-evolution operator, the so-called Loschmidt echo, for both circuit dynamics and Hamiltonian dynamics. By tracking changes in the phase during the dynamics, the routines trade circuit depth for increased sampling cost and classical postprocessing. Our approach does not rely on reference states and is applicable to any efficiently preparable state, regardless of its correlations. We provide a comprehensive analysis of the sample complexity and illustrate the results with numerical simulations. Our methods offer a practical pathway for measuring spectral properties in large many-body quantum systems using current quantum devices.

Schiffer, Benjamin F. [Max Planck Institute of Qua↗

DOE OSTI2024

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Measuring and unbiasing the BAO shift in the Ly α forest with AbacusSummit

ABSTRACT The Dark Energy Spectroscopic Instrument (DESI) places sub- per cent constraints on measurements of the Baryon Acoustic Oscillation (BAO) scaling parameters from the Ly $\alpha$ forest. However, no systematic error budget stemming from non-linearities in the three-dimensional clustering of the Ly $\alpha$ forest is included in the DESI-Ly $\alpha$ analysis. In this work, we measure the size of the shift of the BAO peak using large Ly $\alpha$ forest mocks produced on the N-body simulation suite AbacusSummit, which adopt the Fluctuating–Gunn–Peterson Approximation (FGPA). Specifically, we measure the Ly $\alpha$ autocorrelation and the Ly $\alpha$-quasar cross-correlation functions. To mitigate the noise, we adopt a linear control variates technique, reducing the error bars by a factor of up to $\sim \sqrt{50}$ on large scales. From the autocorrelation, we detect a small positive shift in radial direction of $\Delta \alpha _{\parallel }= 0.35~{{\ \rm per\ cent}}$ at the 3$\sigma$ level and virtually no shift in the transverse direction, $\alpha _\perp$. From the cross-correlation, we see a similar shift to $\Delta \alpha _\parallel$, albeit with larger error bars, and a small negative shift, $\Delta \alpha _{\perp }=\sim$0.25 per cent, at the 2$\sigma$ level. We also make a connection with the Ly $\alpha$ forest effective field theory (EFT) framework and find that the one-loop EFT power spectrum yields unbiased measurements of the BAO shift parameters in radial and transverse direction for Ly $\alpha$ auto- and the Ly $\alpha$-quasar cross-correlation measurements. When using the one-loop EFT framework, we find that we can recover the BAO parameters without a shift, which has important implications for future Ly $\alpha$ forest analyses based on EFT. This work paves the way for novel full-shape analyses of the currently observing DESI and future surveys such as the PFS, WEAVE-QSO, and 4MOST.

Hadzhiyska, Boryana↗

DOE OSTI2026

The Extended Embedded Self-Shielding Method in SCALE 6.3/Polaris

The SCALE transport lattice code, Polaris, has been previously developed to generate few-group homogenized cross sections for whole-core nodal diffusion simulators in which the embedded self-shielding method (ESSM) is used for resonance self-shielding calculations to process cross sections. Although the ESSM capability has been very successful in light-water reactor analysis, it may require enhancements in computational efficiency; treatment of spatially dependent resonance self-shielding effects; and handling of interrelated resonance effects among fuel, cladding, and control rod materials. Therefore, this study focuses on improving computational efficiency by using a Dancoff-based Wigner–Seitz approximation combined with a material-based resonance categorization, through which a spatially dependent ESSM capability is developed to accurately estimate self-shielded cross sections inside the fuel. Benchmark results show that the new capability significantly enhances computational efficiency and accuracy for spatially dependent local zones within the fuel and through depletion.

ESSM↗

DOE OSTI2020

DeepGrid: Robust Deep Reinforcement Learning-based Contingency Management

Increasing uncertainty raised by the integration of renewable energy resources requires an enormous number of simulations to be carried out for the security assessment of the power grid. However, it is challenging to assess the steady-state and dynamic security indices for different system contingency events by doing an exhaustive analysis in real-time due to the computational and communication constraints. One promising solution is using data-driven techniques along with the system models to train an intelligent contingency management framework to better handle the contingencies in real-time. Nevertheless, implementing a data-driven technique to obtain the best remedial actions necessitates to account for the effect of the measurement noise on the performance of the contingency management. To tackle these challenges, we leverage a robust deep reinforcement learning (DRL) algorithm called Double Deep Q-Network (DDQN) to design a recommender system capable of prescribing optimal control actions with the help of the real-time digital simulator (RTDS). The use of RTDS system in combination with the advanced DRL algorithm allows to explore a wide variety of system contingencies in order to derive better remedial actions. The performance of the proposed algorithm is evaluated in IEEE 9-bus system under different loading conditions, and different network configurations in presence of noisy measurements.

Ghasemkhani, Amir↗

DOE OSTI2025

Ice storage model-predictive control in an office building with PV: scenario, error and sensitivity analysis

Thermal energy storage (TES) can enable more building-sited renewable electricity generation and lower utility bill costs for buildings owners and occupants, especially when there are high demand and variable time-of-use (TOU) charges. A model predictive control (MPC) strategy can offer additional savings over a schedule-based control with added complexity and reliance on forecasts. Here, this study examines savings for medium office buildings with chiller plants in three locations with building-installed solar photovoltaics (PV) to understand the impact of MPC. Control setpoints are fixed by a schedule-based control or optimized by nonlinear MPC. These control setpoints are actuated within EnergyPlus building models to simulate the utility cost of the chiller plant. NLP solutions can be unstable or unrealistic, but our results show that by regularizing the NLP, the solutions can be reasonably followed by the building model. MPC models make simplifications that lead to errors once the controller is participating in and changing the operation of the building. These errors average 9 % across the cases, showing that the most important parts of the system are represented. The no-thermal load costs are computed to show that the optimization can in some cases achieve both the minimum TOU and minimum monthly demand costs by demand management while reducing TOU energy costs by energy arbitrage. The MPC saves 35–66 % in the annual chiller plant operating costs, which is an additional savings above the schedule by 1–33 %. PV and TES are complementary and mostly independent, but a load with PV often results in better performance for the schedule. Our case study and sensitivity analysis show the importance of modeling and optimization for complex rates, but also the circumstances wherein a simpler strategy achieves the same performance with less potential for error.

14 SOLAR ENERGY↗

DOE OSTI2026

Thiol post-translational modifications modulate allosteric regulation of the OpcA–G6PDH complex through conformational gate control

In cyanobacteria, the redox-sensitive protein OpcA acts as a metabolic switch for G6PDH, enabling rapid adjustment of reducing power generation from glycogen catabolism and thereby precisely regulating carbon flux between anabolic and catabolic pathways. Although redox-sensitive cysteines in OpcA are known to regulate G6PDH, the mechanisms by which redox post-translational modifications (PTMs) on OpcA control G6PDH structure and activity remain unclear. Here, we combine computational modeling with experimental redox proteomics in Synechococcus elongatus PCC 7942 to dissect this mechanism. Experimentally, redox proteome analysis revealed differential redox PTM patterns, particularly on cysteines within the G6PDH-binding site of OpcA. These environmentally sensitive PTM changes at the interface suggest that thiol modifications in this region form a key regulatory node. More broadly, redox proteomics identified site-specific cysteine modifications under light/dark transitions and circadian cycling, linking distinct redox regimes to discrete PTM states. We employed PTM-Psi simulations to show that thiol PTMs near the OpcA–G6PDH interface are critical for allosteric regulation of G6PDH. The thiol PTMs on OpcA affect a putative gate region in G6PDH for substrate ingress and product egress as well as key hydrogen-bond networks within the active site. We infer that PTMs on OpcA tune the conformational landscapes of individual G6PDH subunits toward functionally relevant configurations according to environmental gradients, biasing the enzyme toward catalytically favorable states. Together, our results reveal a molecular mechanism in which thiol PTMs on OpcA modulate G6PDH structure and function through PTM-induced reorganization of conformational dynamics and allosteric communication. These findings demonstrate that PTM-level regulation provides a critical control layer from genotypes to phenotypes that enables cyanobacteria to rapidly adapt to environmental fluctuations through precise metabolic fine-tuning.

Allosteric regulation↗

DOE OSTI2023

Detailed Simulation Study to Evaluate Future Transportation Decarbonization Potential

This report is the ninth revision of a continuous-improvement, scenario-based study on program benefits from the U.S. Department of Energy’s Vehicle Technologies Office and Hydrogen and Fuel Cell Technologies Office. With each revision of the study, Argonne made improvements to the assumptions, control strategies at the vehicle level, methodologies, powertrain selections, and the number of vehicles analyzed. In 2019, separate reports were published on the analysis of light-duty and heavy-duty vehicles. From 2020 onwards, summaries for both light- and heavy-duty vehicles are consolidated into one report. The first part of the report covers the impact of technology progress on light-duty vehicles and the second part of the report is devoted to the technology progress assumed for medium- and heavy-duty trucks.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Locally Engineering and Interrogating the Photoelectrochemical Behavior of Defects in Transition Metal Dichalcogenides

Transition metal dichalcogenides (TMDs) are attractive materials for a variety of applications in solar energy conversion and electrocatalysis, due to their favorable optical and electrical properties and their unique two-dimensional structures which facilitate the fabrication of wide-area, ultrathin layers. Unfortunately, the basal planes which make up the majority of these materials are relatively inert, and thus a great deal of effort has been directed to engineering favorable, catalytically active defects into these materials. In this paper, we demonstrate how probe-based electrochemical techniques can be employed as multifunctional tools for locally modifying TMD materials and probing the electrochemical behavior of the resulting defects. Scanning Electrochemical Cell Microscopy (SECCM) was employed to locally anodize exfoliated p-type WSe 2 nanosheets, creating hole-like defects within individual basal planes in a highly controllable fashion. Photoelectrochemical SECCM imaging was then employed to characterize the chemical behavior of these engineered defects, revealing significantly enhanced activity toward the Hydrogen Evolution Reaction (HER). Atomic force microscopy studies are presented which suggest these enhancements result from an increased density of monolayer-high step features within the anodized defects. Analysis of the SECCM data in the context of finite element simulations revealed that these enhancements increased with increasing anodization time, with local kinetic rates over 2 orders of magnitude higher than unaltered basal planes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

The Shortwave Cloud-SST Feedback Amplifies Multi-Decadal Pacific Sea Surface Temperature Trends: Implications for Observed Cooling

Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud-SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi-decadal SST variability. A heat-budget analysis reveals coupling between cloud-radiative effects, circulation, and SST gradients in driving multi-decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ~56% on average. If models underestimate climate “noise,” as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate.

58 GEOSCIENCES↗

DOE OSTI2021

Transition of a network of nonlinear interactions into a regime of strong nonlinear fluctuations: A paradigm for the edge localized mode onset

We study how a network of nonlinear oscillators transits into a regime of strong nonlinear fluctuations when perturbed by a triad. In this regime, most of the potential energy contained in the waves is made available to the system through strong nonlinear fluctuations. This analysis is motivated by recent experimental observations [Dominski and Diallo, Plasma Phys. Control. Fusion 62, 095011 (2020)] where it was found that magnetic fluctuations trigger the onset of edge localized modes by suddenly exciting a network of nonlinear interactions. In our study, we consider the simplest system of many harmonic oscillators that are organized in a network of nonlinear triads. We model and simulate the sudden transition of this network of triads into a regime of strong nonlinear fluctuations—reminiscent of the onset of edge localized modes in tokamaks. This transition is triggered by the activation of a nonlinear perturbation. An abrupt rise of the system's disorder (an entropy-like quantity) is measured during the transition. This transition from weak to strong nonlinear fluctuations is even more abrupt when these fluctuations are chaotic, i.e., when the timescale of the nonlinear interaction is comparable to the timescale of the wave oscillations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

We report a sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗