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At least 1,081 records · Page 60

Uncertainty Quantification for Capacity Expansion Planning

This report quantifies the uncertainty in output decisions from a Capacity Expansion Planning (CEP) model. The need to understand how uncertainties within CEP models and modeling assumptions affect Quantities of Interest (QoIs) such as expansion and operating costs, as well as expansion decisions remains an ongoing challenge in scientific research and industrial operations. This area of research is particularly important for models which seek to capture how large networks will evolve and operate under increased sources of variable generation, i.e., higher penetration of renewable technologies such as solar and wind generators. Uncertainty quantification (UQ) of CEP models which estimate expansion costs and decisions, and production cost models which estimate operating costs and dispatch decisions, is a key focus of research at NREL. The Regional Energy Deployment System (ReEDS) represents a state-of-the-art CEP model and considers a range of possible grid evolutions in an attempt to identify key drivers, ramifications, and decisions which contribute to better informed investment and policy decisions. However, research to quantify how uncertainties and model assumptions, such as unit commitment (UC), within ReEDS may be affecting its outputs remains challenging due to to size and complexity of the model

24 POWER TRANSMISSION AND DISTRIBUTION↗

Voltammetric Measurement of Rates and Energetics for Surface Methoxylation of Si(100) in Methanol with Dissolved Electron Acceptors Using Si Ultramicroelectrodes

The steady-state voltammetric responses of n-type Si(100) semiconductor ultramicroelectrodes (SUMEs) immersed in air- and water-free methanolic electrolytes have been measured. The response characteristics of these SUMEs in the absence of illumination were modeled and understood through a framework that describes the distribution of the applied potential across the semiconductor/electrolyte contact using four discrete regions: the semiconductor space charge, surface, Helmholtz, and diffuse layers. The latter region was described by the full Gouy–Chapman model. This framework afforded insight on how relevant parameters such as the semiconductor band edge potentials, the reorganization energies for charge transfer, the standard potential of redox species in solution, the density and energy of surface state populations, and the presence of an insulating (tunneling) layer individually and collectively dictate the observable current–potential responses. With this information, the methoxylation of Si surfaces was evaluated by analysis of the change in voltammetric responses during the course of prolonged immersion in methanol. Here, the electrochemical data were consistent with a surface methoxylation mechanism that depended on the standard potential of redox species dissolved in solution. Estimates of the enthalpies of adsorption as well as the potential-dependent rate constant for surface methoxylation were obtained. Collectively, these measurements supported the contention that the rates of Si surface reactions can be systematically tuned by exposure to dissolved outer-sphere electron acceptors. Moreover, the data represent the quantitative utility of voltammetry with SUMEs for the measurement of semiconductor/liquid contacts.

14 SOLAR ENERGY↗

A biokinetic model for trivalent or hexavalent chromium in adult humans

Chromium exists in several oxidation states, with the trivalent state (Cr(III)) being the dominant naturally occurring form. Chromium in other oxidation states tends to be converted to the trivalent oxide in the natural environment and in biological systems. Chromium(III) has been shown to be an essential nutrient for humans and several non-human species. Chromium(VI), the second most stable form of chromium, is an important environmental contaminant that is mostly of industrial origin and is associated with lung cancer and nose tumours in chromium workers. This paper proposes a biokinetic model for chromium that addresses the distinctive behaviours of Cr(III) and Cr(VI) following uptake to blood of an adult human. Additionally, the model is based on biokinetic data derived from relatively short-term studies involving administration of chromium tracers to adult human subjects or laboratory animals, supplemented with data on the long-term distribution of chromium in adult humans as estimated from autopsy measurements. The model is part of a comprehensive update of biokinetic models of the International Commission on Radiological Protection, used to project or evaluate radiation doses from occupational intake of radionuclides.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Battery Energy Storage System (BESS) End-of-Performance and Decommissioning Considerations [Slides]

This presentation provides a comprehensive overview of end-of-performance and decommissioning considerations for large-scale Battery Energy Storage Systems (BESS). It outlines expected system lifespans, midterm assessment needs, and pathways for extending operational life through augmentation or repowering. The presentation details regulatory requirements that govern decommissioning plans, cost estimates, financial assurance mechanisms, and performance obligations across multiple jurisdictions. It further examines end-of-life equipment management, including recycling, waste handling, transportation, and environmental compliance. Designed to support Malawi's electricity-sector institutions, the presentation highlights how planning for decommissioning and environmental stewardship can be integrated early in project development to ensure safe, financially accountable, and environmentally responsible BESS system retirement.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simplified Model and Approach to Transform Infrared Surface Temperature to Film Effectiveness in a Conjugate Heat Transfer Experiment

In the pursuit of more efficient gas turbines, film cooling is a critical technology. This article describes a simplified engineering model based on a one-dimensional thermal resistance network. The model is used to relate film-cooling effectiveness and heat transfer augmentation to local overall cooling effectiveness in a conjugate flat plate experiment. Here, this article presents experimental proof-of-concept data to demonstrate the potential for this model. In contrast to previous approaches, neither the wall heat flux nor the adiabatic wall temperature is required to estimate the local film-cooling performance parameters. The model predicts surface temperatures that are within the experimental uncertainties over the range for which the model is trained and to within five percent when the model is extrapolated to higher coolant channel Reynolds numbers. This article is relevant to conjugate test rigs that can measure the hot-surface temperature distribution with and without film cooling. This information may also be relevant to designers as a method to approximate surface temperatures or used as an approximate heat transfer model for optimization studies.

advanced turbines↗

Rigorous constraints on three-nucleon forces in chiral effective field theory from fast and accurate calculations of few-body observables

We explore the constraints on the three-nucleon force (3NF) of chiral effective field theory (χ EFT) that are provided by bound-state observables in the A = 3 and A = 4 sectors. Our statistically rigorous analysis incorporates experimental error, computational method uncertainty, and the uncertainty due to truncation of the χ EFT expansion at next-to-next-to-leading order. A consistent solution for the 3 H binding energy, the 4 He binding energy and radius, and the 3 H β-decay rate can only be obtained if χ EFT truncation errors are included in the analysis. Here, the β-decay rate is the only one of these that yields a nondegenerate constraint on the 3NF low-energy constants, which makes it crucial for the parameter estimation. We use eigenvector continuation for fast and accurate emulation of no-core shell model calculations of the few-nucleon observables. This facilitates sampling of the posterior probability distribution, allowing us to also determine the distributions of the parameters that quantify the truncation error. We find a χ EFT expansion parameter of Q = 0.33 ± 0.06 for these observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Overview of Nuclear Integration Activities for Mitigation of Radiation Loads to ITER Superconducting Magnets

The Nuclear Integration Unit (NIU) is a trans-departmental team from the ITER Organization and Domestic Agencies, responsible for all nuclear integration aspects of the facility and for ensuring that systems and components are suitable for their radiation environment and satisfy all related performance requirements. This is a very challenging task namely due to the large number of systems, their still evolving designs, the intricate and far-reaching impacts of these in nuclear responses everywhere, and the complex world-wide distribution of procurement responsibilities. A sound systems engineering approach that involves all relevant experts and stakeholders, and trades-off between different performance requirements in an optimum way, needs to be taken and sustained during design evolution and construction, always with the objective of final overall project success. One of the most important current occupations of the NIU is the evaluation of, and protection from, radiation conditions to superconducting magnets during plasma operations, and particularly nuclear heating. This requires neutronic analyses in massive computer resources, with state-of-the-art methods and complex, extensive computer models. The main ITER superconducting magnet systems subject to significant nuclear loads are the toroidal field coils (TFCs) and the poloidal field coils (PFCs). These are illustrated in Fig. 1. Nuclear responses in these depend mostly on the design of all in-vessel (blankets, manifolds, divertor, in-vessel coils, port plugs), vessel and thermal shield components. Sources to consider are the 500 MW DT burning plasma (14.1 MeV neutrons) and the activated water in the in-vessel cooling system (photons up to 7 MeV from N-16 and neutrons up to 3.5 MeV from N-17). This paper discusses a snapshot of the present understanding of nuclear heat conditions in both the TFC and PFC magnets. This includes integral values and distributions, as well as best estimates from computations and conservative upper estimates by consideration of systematic effects and random uncertainties. The computer models, methods and assumptions used for evaluation of these responses are described. Nuclear integration aspects and ongoing efforts to study and implement additional shielding and other mitigating measures are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimization of process models for determining volatility distribution and viscosity of organic aerosols from isothermal particle evaporation data

The composition of organic aerosol under different ambient conditions as well as their phase state have been a subject of intense study in recent years. One way to study particle properties is to measure the particle size shrinkage in a diluted environment at isothermal conditions. From these measurements it is possible to separate the fraction of low-volatility compounds from high-volatility compounds. In this work, we analyse and evaluate a method for obtaining particle composition and viscosity from measurements using process models coupled with input optimization algorithms. Two optimization methods, the Monte Carlo genetic algorithm and Bayesian inference, are used together with process models describing the dynamics of particle evaporation. The process model optimization scheme in inferring particle composition in a volatility-basis-set sense and composition-dependent particle viscosity is tested with artificially generated data sets and real experimental data. Optimizing model input so that the output matches these data yields a good match for the estimated quantities. Both optimization methods give equally good results when they are used to estimate particle composition to artificially test data. Finally, the timescale of the experiments and the initial particle size are found to be important in defining the range of values that can be identified for the properties from the optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plant, microbial and ecosystem carbon use efficiencies interact to stabilize microbial growth as a fraction of gross primary production

Summary The carbon use efficiency of plants ( CUE a ) and microorganisms ( CUE h ) determines rates of biomass turnover and soil carbon sequestration. We evaluated the hypothesis that CUE a and CUE h counterbalance at a large scale, stabilizing microbial growth (μ) as a fraction of gross primary production ( GPP ). Collating data from published studies, we correlated annual CUE a , estimated from satellite imagery, with locally determined soil CUE h for 100 globally distributed sites. Ecosystem CUE e , the ratio of net ecosystem production ( NEP ) to GPP , was estimated for each site using published models. At the ecosystem scale, CUE a and CUE h were inversely related. At the global scale, the apparent temperature sensitivity of CUE h with respect to mean annual temperature ( MAT ) was similar for organic and mineral soils (0.029°C −1 ). CUE a and CUE e were inversely related to MAT , with apparent sensitivities of −0.009 and −0.032°C −1 , respectively. These trends constrain the ratio μ : GPP (= (CUE a × CUE h )/(1 − CUE e )) with respect to MAT by counterbalancing the apparent temperature sensitivities of the component processes. At the ecosystem scale, the counterbalance is effected by modulating soil organic matter stocks. The results suggest that a μ : GPP value of c . 0.13 is a homeostatic steady state for ecosystem carbon fluxes at a large scale.

Sinsabaugh, Robert L.↗

Electrical properties and the determination of interface state density from I–V, C–f and G–f measurements in Ir/Ru/n-InGaN Schottky barrier diode

The electrical properties of the Ir/Ru Schottky contacts on n-InGaN have been investigated by current-voltage (I–V), capacitance-voltage (C–V), capacitance-frequency (C–f) and conductance-frequency (G–f) measurements. The obtained mean barrier height and ideality factor from I–V are 0.61 eV and 1.89. The built-in potential, doping concentration and barrier height values are also estimated from the C–V measurements and the corresponding values are 0.62 V, 1.20 × 1017 cm{sup –3} and 0.79 eV, respectively. The interface state density (N{sub SS}) obtained from forward bias I–V characteristics by considering the series resistance (R{sub S}) values are lower without considering the series resistance (R{sub S}). Furthermore, the interface state density (N{sub SS}) and relaxation time (τ) are also calculated from the experimental C–f and G–f measurements. The N{sub SS} values obtained from the I–V characteristics are almost three orders higher than the N{sub SS} values obtained from the C–f and G–f measurements. The experimental results depict that N{sub SS} and τ are decreased with bias voltage. The frequency dependence of the series resistance (R{sub S}) is attributed to the particular distribution density of interface states.

36 MATERIALS SCIENCE↗

ANALYZING METEOROID FLIGHTS USING PARTICLE FILTERS

Fireball observations from camera networks provide position and time information along the trajectory of a meteoroid that is transiting our atmosphere. The complete dynamical state of the meteoroid at each measured time can be estimated using Bayesian filtering techniques. A particle filter is a novel approach to modeling the uncertainty in meteoroid trajectories and incorporates errors in initial parameters, the dynamical model used, and observed position measurements. Unlike other stochastic approaches, a particle filter does not require predefined values for initial conditions or unobservable trajectory parameters. The Bunburra Rockhole fireball, observed by the Australian Desert Fireball Network (DFN) in 2007, is used to determine the effectiveness of a particle filter for use in fireball trajectory modeling. The final mass is determined to be 2.16±1.33 kg with a final velocity of 6030±216 m s{sup −1}, similar to previously calculated values. The full automatability of this approach will allow an unbiased evaluation of all events observed by the DFN and lead to a better understanding of the dynamical state and size frequency distribution of asteroid and cometary debris in the inner solar system.

79 ASTRONOMY AND ASTROPHYSICS↗

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗

Electronic spectra of DyF studied by four-component relativistic configuration interaction methods

The electronic states of the DyF molecule below 3.0 eV are studied using 4-component relativistic CI methods. Spinors generated by the average-of-configuration Hartree-Fock method with the Dirac-Coulomb Hamiltonian were used in CI calculations by the KRCI (Kramers-restricted configuration interaction) program. The CI reference space was generated by distributing 11 electrons among the 11 Kramers pairs composed mainly of Dy [4f], [6s], [6p] atomic spinors, and double excitations are allowed from this space to the virtual molecular spinors. The CI calculations indicate that the ground state has the dominant configuration (4f{sup 9})(6s{sup 2})(Ω = 7.5). Above this ground state, 4 low-lying excited states (Ω = 8.5, 7.5, 7.5, 7.5) are found with dominant configurations (4f{sup 10})(6s). These results are consistent with the experimental studies of McCarthy et al. Above these 5 states, 2 states were observed at T{sub 0} = 2.39 eV, 2.52 eV by McCarthy et al. and were named as [19.3]8.5 and [20.3]8.5. McCarthy et al. proposed that both states have dominant configurations (4f{sup 9})(6s)(6p), but these configurations are not consistent with the large R{sub e}’s (∼3.9 a.u.) estimated from the observed rotational constants. The present CI calculations provide near-degenerate states of (4f{sup 10})(6p{sub 3/2,1/2}), (4f{sup 10})(6p{sub 3/2,3/2}), and (4f{sup 9})(6s)(6p{sub 3/2,1/2}) at around 3 eV. The former two states have larger R{sub e} (3.88 a.u.) than the third, so that it is reasonable to assign (4f{sup 10})(6p{sub 3/2,1/2}) to [19.3]8.5 and (4f{sup 10})(6p{sub 3/2,3/2}) to [20.3]8.5.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A SIMPLE METHOD FOR MODELING COLLISION PROCESSES IN PLASMAS WITH A KAPPA ENERGY DISTRIBUTION

We demonstrate that a nonthermal distribution of particles described by a kappa distribution can be accurately approximated by a weighted sum of Maxwell–Boltzmann distributions. We apply this method to modeling collision processes in kappa-distribution plasmas, with a particular focus on atomic processes important for solar physics. The relevant collision process rate coefficients are generated by summing appropriately weighted Maxwellian rate coefficients. This method reproduces the rate coefficients for a kappa distribution to an estimated accuracy of better than 3%. This is equal to or better than the accuracy of rate coefficients generated using “reverse-engineering” methods, which attempt to extract the needed cross sections from the published Maxwellian rate coefficient data and then reconvolve the extracted cross sections with the desired kappa distribution. Our approach of summing Maxwellian rate coefficients is easy to implement using existing spectral analysis software. Moreover, the weights in the sum of the Maxwell–Boltzmann distribution rate coefficients can be found for any value of the parameter κ, thereby enabling one to model plasmas with a time-varying κ. Tabulated Maxwellian fitting parameters are given for specific values of κ from 1.7 to 100. We also provide polynomial fits to these parameters over this entire range. Several applications of our technique are presented, including the plasma equilibrium charge state distribution (CSD), predicting line ratios, modeling the influence of electron impact multiple ionization on the equilibrium CSD of kappa-distribution plasmas, and calculating the time-varying CSD of plasmas during a solar flare.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantum secret sharing using weak coherent states

Secret sharing allows a trusted party (the dealer) to distribute a secret to a group of players, who can only access the secret cooperatively. Quantum secret sharing (QSS) protocols could provide unconditional security based on fundamental laws in physics. While the general security proof has been established recently in an entanglement-based QSS protocol, the tolerable channel loss is unfortunately rather small. Here we propose a continuous variable QSS protocol using conventional laser sources and homodyne detectors. In this protocol, a Gaussian-modulated coherent state (GMCS) prepared by one player passes through the secure stations of the other players sequentially, and each of the other players injects a locally prepared, independent GMCS into the circulating optical mode. Finally, the dealer measures both the amplitude and the phase quadratures of the receiving optical mode using double homodyne detectors. Collectively, the players can use their encoded random numbers to estimate the measurement results of the dealer and further generate a shared key. We prove the unconditional security of the proposed protocol against both eavesdroppers and dishonest players in the presence of high channel loss, and discuss various practical issues.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate

Characterizing the properties of groundwater aquifers is essential for predicting aquifer response and managing groundwater resources. In this work, we develop a high-dimensional scalable Bayesian inversion framework governed by a three-dimensional quasi-static linear poroelastic model to characterize lateral permeability variations in groundwater aquifers. In this work, we determine the maximum a posteriori (MAP) point of the posterior permeability distribution from centimeter-level surface deformation measurements obtained from Interferometric Synthetic Aperture Radar (InSAR). The scalability of our method to high parameter dimension is achieved through the use of adjoint-based derivatives, inexact Newton methods to determine the MAP point, and a Mat´ern class sparse prior precision operator. Together, these guarantee that the MAP point is found at a cost, measured in number of forward/adjoint poroelasticity solves, that is independent of the parameter dimension. We apply our methodology to a test case for a municipal well in Mesquite, Nevada, in which InSAR and GPS surface deformation data are available. We solve problems with up to 320,824 state variable degrees of freedom (DOFs) and 16,896 parameter DOFs. A consistent treatment of noise level is employed so that the aquifer characterization result does not depend on the pixel spacing of surface deformation data. Our results show that the use of InSAR data significantly improves characterization of lateral aquifer heterogeneity, and the InSAR-based aquifer characterization recovers complex lateral displacement trends observed by independent daily GPS measurements.

54 ENVIRONMENTAL SCIENCES↗

ML-Based Pebble Power Reconstruction for Pebble Bed Reactor Analysis

Pebble power reconstruction has been explored to complement the conventional homogenized modeling approach in pebble bed reactor (PBR) analysis, as detailed heterogeneous geometry calculations are computationally expensive. The random distribution of pebble fuels within the core challenges the application of conventional pin power reconstruction methods. To address this, we introduce a machine learning approach based on the transformer model, composed of encoder and decoder layers, to estimate the flux and power form functions for reconstructing individual pebble neutron fluxes and powers. The homogeneous neutron flux distribution within each spectral zone (SZ) is obtained from finite element solutions of global diffusion or transport calculations. Verification tests demonstrate that the trained transformer model accurately predicts power form functions over a range of conditions, including variations in pebble enrichment, location, type, SZ size, and burnup. In particular, verification using a three-dimensional PBR benchmark with burned pebbles shows good agreement in heterogeneous pebble power distributions between Griffin and Serpent. These results highlight the potential of applying conventional pin power reconstruction approaches to PBR cores with randomly distributed pebbles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios

Abstract Climate change and increasing water demand due to population growth pose serious threats to surface water availability. The biggest challenge in addressing these threats is the gap between climate science and water management practices. Local water planning often lacks the integration of climate change information, especially with regard to its impacts on surface water storage and evaporation as well as the associated uncertainties. Using Texas as an example, state and regional water planning relies on the use of reservoir “Firm Yield” (FY)—an important metric that quantifies surface water availability. However, this existing planning methodology does not account for the impacts of climate change on future inflows and on reservoir evaporation. To bridge this knowledge gap, an integrated climate‐hydrology‐management (CHM) modeling framework was developed, which is generally applicable to river basins with geographical, hydrological, and water right settings similar to those in Texas. The framework leverages the advantages of two modeling approaches—the Distributed Hydrology Soil Vegetation Model (DHSVM) and Water Availability Modeling (WAM). Additionally, the Double Bias Correction Constructed Analogues method is utilized to downscale and incorporate Coupled Model Intercomparison Project Phase 6 GCMs. Finally, the DHSVM simulated naturalized streamflow and reservoir evaporation rate are input to WAM to simulate reservoir FY. A new term—“Ratio of Firm Yield” (RFY)—is created to compare how much FY changes under different climate scenarios. The results indicate that climate change has a significant impact on surface water availability by increasing reservoir evaporation, altering the seasonal pattern of naturalized streamflow, and reducing FY.

54 ENVIRONMENTAL SCIENCES↗