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DOE OSTI2023

Load Profile Inpainting for Missing Load Data Restoration and Baseline Estimation

This paper introduces a Generative Adversarial Nets (GAN) based, Load Profile Inpainting Network (Load-PIN) for restoring missing load data segments and estimating the baseline for a demand response event. The inputs are time series load data before and after the inpainting period together with explanatory variables (e.g., weather data). Here, we propose a Generator structure consisting of a coarse network and a fine-tuning network. The coarse network provides an initial estimation of the data segment in the inpainting period. The fine-tuning network consists of self-attention blocks and gated convolution layers for adjusting the initial estimations. Loss functions are specially designed for the fine-tuning and the discriminator networks to enhance both the point-to-point accuracy and realisticness of the results. We test the Load-PIN on three real-world data sets for two applications: patching missing data and deriving baselines of conservation voltage reduction (CVR) events. We benchmark the performance of Load-PIN with five existing deep-learning methods. Our simulation results show that, compared with the state-of-the-art methods, Load-PIN can handle varying-length missing data events and achieve 15-30% accuracy improvement.

14 SOLAR ENERGY↗

DOE OSTI2022

Spectral Radiative Properties of Polydispersed SiO 2 Particle Beds

The focus of this work is on the measurement and analysis of the radiative properties of polycrystalline SiO 2 particle beds with various layer thicknesses. The particles are polydispersed with average diameters of 222, 150, and 40 μm . The spectral, directional–hemispherical reflectance and transmittance of the particle bed are measured at wavelengths from 0.4 to 1.8 μm using a monochromator, and the reflectance measurement is extended to 15 μm using a Fourier-transform infrared spectrometer. Particles are closely packed between two transparent windows for measuring the radiative properties. In the visible and near-infrared region up to 1.8 μm, the inverse adding–doubling method yields the effective absorption and scattering coefficients. The results suggest that short wavelength absorption needs to be included in modeling the behavior of particle beds due to multiple scattering. A discrete-scale Monte Carlo ray-tracing method is developed to model the radiative properties by assuming monodispersed spherical particles, and the simulated results compare well with measurements. The effective absorption and scattering coefficients of the particle beds obtained from the independent scattering theory are compared to those from the inverse method. As a result, the impact of dependent scattering on the packed beds is observed for smaller-sized particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids: Preprint

Increase in the proliferation of DERs requires real-time situational awareness for efficient grid operations. State estimation plays an important role for real time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hierarchical spectral clustering-based network partition algorithm followed by a decentralized compressive sensing (DCS) based state estimation. The applicability of the proposed network partitioning algorithm is tested on IEEE-123 bus, IEEE-8500 node, and a 6204-node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6204-node distribution network after dividing the network into 18 optimal partitions. Simulation results show that DCS-based state estimation recovers the system states with high accuracy and low complexity.

ADMM↗

DOE OSTI2025

Effects of midplane density gradient in the propagation of high-harmonic fast waves considering high temperature anisotropy in the scrape-off layer of NSTX-U

High-Harmonic Fast Wave (HHFW) heating experiments in NSTX have shown that up to 60% of the injected power can be lost in the Scrape-Off Layer (SOL) when the density is above the fast wave cutoff density in front of the antenna, for which the fast wave is able to propagate into the plasma. This work models HHFW propagation in the SOL plasmas of NSTX-U using a 2D divertor SOL profile derived from the pressure assumption and the finite element temperature solution, which accounts for the high anisotropy of heat conduction in a 2D axisymmetric geometry. In this work, the two-dimensional axisymmetric SOL temperature profile is first evaluated by solving the steady-state non-linear heat conduction equation, in which thermal conductivity depends on temperature, using a finite element approach in the Petra-M workbench. A 2D density profile is then obtained from a prescribed density profile at the outer midplane assuming pressure is uniform along a flux tube in the SOL. This approach results in density and temperature profiles in which the strong asymmetric nature of heat conduction between the parallel and perpendicular background magnetic field is successfully captured. Furthermore, this work focuses on investigating the effect of the SOL plasma density profile on parasitic HHFW propagation in the SOL. The simulation results show that the radial gradient of the density profile affects the wavefield propagation in the SOL. As the density profile broadens, the wavefield intensity and its poloidal extent are reduced in the SOL, and the core coupling increases. Similarly, as shown by collisional power deposition, a proxy for power absorption, the fraction of power deposited in the SOL decreases with a broadening profile.

HHFW↗

DOE OSTI2025

Turbulence-Resolving Simulations of Hurricane Laura (2020): Insights Into Extreme Winds and Eyewall Turbulence

Extreme weather events pose significant risks to coastal and offshore energy infrastructure. In this work, we investigate the structure of mean winds and turbulence near the surface ( z < 300 m) that occurred during Hurricane Laura in 2020 on the US Gulf Coast. To this end, we perform turbulence-resolving simulations (..delta..x = 33.33 m) that encompass the entire eyewall of Hurricane Laura by introducing a novel method that we will refer to as Moving-Mesoscale to Static-LES Integrated Coupling (MOSAIC). The simulation results are validated against surface, boundary-layer, and mid-tropospheric observations. Our analysis of the extreme wind conditions near the surface indicates that the mean wind and turbulence profiles vary greatly at and near the eyewall, resulting in extreme values of mean wind speed (U > 50 m * s-1) and turbulence kinetic energy (k ~ 50 m2 * s-2) at altitudes above 50 m . To investigate in detail the nature of turbulence within the eyewall of the storm, we conduct higher-resolution simulations (..delta..x = 11.11 m) of a portion of the hurricane. We provide a comprehensive statistical description of turbulence in the eyewall region, highlighting the need to employ ..delta..x ~ 10 m grid spacing to capture the integral length-scales near the surface, second- and higher-order central moments (i.e., skewness and kurtosis), and spectral coherence in the flow accurately. These numerical simulations provide the most detailed description of mean winds and turbulent conditions within the eyewall of a historical tropical cyclone to date, illustrating how high-resolution simulations can enhance limited turbulence measurements in hurricanes and giving insight into the extreme conditions threatening offshore and coastal infrastructure.

17 WIND ENERGY↗

DOE OSTI2021

Microturbulence in edge of a tokamak plasma with medium density and steep temperature gradient

Gyrokinetic simulations of electrostatic micro-turbulence have been carried out for transport barriers (TBs) in tokamak plasmas. It is found that the ion temperature gradient (ITG) mode is dominant in the pedestal with medium density gradient and steep temperature gradient. The mode width shrinks with increase of the ratio of the density and temperature gradients, which is in good agreement with the analytic theory. Unstable mode with herringbone-like structure is excited in the simulation annulus. The simulation results also indicate that multiple ITG modes are induced by a high temperature gradient. Radial electric field shear decreases the mode growth rate while increases the real frequency. Lastly, the generation of the GAM and its interaction with the turbulence are also observed in the nonlinear simulation.

tokamak↗

DOE OSTI2024

Improving Cost and Efficiency of the Scalable Solid Oxide Fuel Cells Power System

The objective of this project was to design and develop a 20kW range small-scale solid oxide fuel cells (SOFC) power system for applications such as data centers and commercial buildings. The original plan included a 5,000 hours demonstration and a Techno-Economic Analysis (TEA) which were dropped as part of project termination. The original project plan was to use a stack with a cross-flow cell design which had previously been tested for 500 hours at a community college in Malta, NY. However, it was decided to move to the advanced R-SOFC co-flow cell developed under Department of Energy Award DE-FE0031971. The advanced cell design has the advantage of a larger active area for the same manufacturing footprint which results in fewer required cells for the same stack power, hence a higher volumetric power density (kW/L) and lower cost per kW than the original cross-flow cell design. A full SOFC system Simulink model was developed and calibrated with testing data from a fuel cell stack and BOP (balance of plant) components. The simulation results from the calibrated model showed an acceptable match with the experimental data. A structural analysis conducted for various load scenarios indicated no high stress areas for all spatial directions. Major electrical system components were acquired, built and successfully tested. System sensors were verified and validated against controls. Safety checks, a diagnostic check, PID tuning, and control software commissioning tasks were also conducted. The power electronics prototype was delivered and trial testing completed. Balance of Plant component testing and simulation work was conducted to characterize Reformer-Heat Exchanger heat transfer and backpressure and reformer catalyst methane conversion and product selectivity. Simulations were conducted to design the Anode and Cathode fluid passages and size the air-air and fuel-fuel heat exchangers. A Burner operation map was created from test data and the Anode Gas Recirculation blower was tested to evaluate its durability. The SOFC system used a horizontal style design where components sit directly on a casting with a direct connection to the skid. This design has efficient packaging and a small footprint with approximate dimensions of 750 mm x 700 mm x 1700 mm. An SOFC system was built and successfully tested at the Malta, NY facility The system for over 500 hours under load of which over 300 hours was at full load of 20 kW.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Numerical Studies of the On-Line Reactivity Monitoring Techniques in Subcritical Systems: Revisit of the Area-Ratio Method, the Neutron Source-Modulation Method, and the Flux-to-Current Ratio Method

In the subcritical systems, the subcriticality level must be monitored continuously to ensure the safe operation of the systems. Techniques such as the neutron source-modulation method and the flux-to-current ratio method have been proposed for on-line reactivity measurements of the subcritical systems. However, the accuracy of these methods is unknown in the actual applications. In this report, the fundamental concepts of these techniques are visited, with numerical simulation techniques developed to validate these on-line reactivity monitoring methodologies. Specifically, the Monte Carlo numerical simulation results show that the neutron source-modulation method is not accurate in determining the reactivity of the subcritical systems. The flux-to-current ratio method can provide on-line reactivity measurements, and its spatial effects have been studied and well understood through the numerical simulations of the fuel loading of the neutron source facility of Ukraine. In addition, a modified version of the area-ratio method is proposed for the on-line measurements of the absolute reactivity of the subcritical systems. Monte Carlo numerical simulations showed that this method can provide the absolute reactivity of the subcritical systems within ~5% error, if the neutron detectors are placed close to the fuel assembly interface with the reflector zone or in the reflector zones away from the neutron source.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

How sheath properties change with gas pressure: modeling and simulation

Abstract Particle-in-cell simulations are used to study how neutral pressure influences plasma properties at the sheath edge. The high rate of ion–neutral collisions at pressures above several mTorr are found to cause a decrease in the ion velocity at the sheath edge (collisional Bohm criterion), a decrease in the edge-to-center density ratio ( h l factor), and an increase in the sheath width and sheath potential drop. A comparison with existing analytic models generally indicates favorable agreement, but with some distinctions. One is that models for the h l factor need to be made consistent with the collisional Bohm criterion. With this and similar corrections, a comprehensive fluid-based model of the plasma boundary transition is constructed that compares well with the simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

On the importance of excited state species in low pressure capacitively coupled plasma argon discharges

In the past three decades, first principles-based fully kinetic particle-in-cell Monte Carlo collision (PIC/MCC) simulations have been proven to be an important tool for the understanding of the physics of low pressure capacitive discharges. However, there is a long-standing issue that the plasma density determined by PIC/MCC simulations shows quantitative deviations from experimental measurements, even in argon discharges, indicating that certain physics may be missing in previous modeling of the low pressure radio frequency (rf) driven capacitive discharges. In this work, we report that the energetic electron-induced secondary electron emission (SEE) and excited state atoms play an important role in low pressure rf capacitive argon plasma discharges. The ion-induced secondary electrons are accelerated by the high sheath field to strike the opposite electrode and produce a considerable number of secondary electrons that lead to additional ionizing impacts and further increase of the plasma density. Importantly, the presence of excited state species even further enhances the plasma density via excited state neutral and resonant state photon-induced SEE on the electrode surface. The PIC/MCC simulation results show good agreement with the recent experimental measurements in the low pressure range (1–10 Pa) that is commonly used for etching in the semiconductor industry. At the highest pressure (20 Pa) and driving voltage amplitudes 250 and 350 V explored here, the plasma densities from PIC/MCC simulations considering excited state neutrals and resonant photon-induced SEE are quantitatively higher than observed in the experiments, requiring further investigation on high pressure discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids

Increase in the proliferation of distributed energy resources require real-time situational awareness for efficient grid operations. State estimation plays an important role for the real-time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hier-archical spectral clustering-based network partitioning algorithm followed by a decentralized compressive sensing (DCS)-based state estimation. The applicability of the proposed network partitioning algorithm is tested on an IEEE 123-bus network, an IEEE 8,500-node system, and a 6,000+ node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum number of edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6,000+ node distribution network after dividing the network into 18 optimal partitions. Simulation results show that the DCS-based state estimation recovers the system states with high accuracy and low complexity.

alternating direction method of multipliers↗

DOE OSTI2024

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗

DOE OSTI2022

Network Uncertainty Quantification for Analysis of Multi-Component Systems

To impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

42 ENGINEERING↗

DOE OSTI2023

Computing dissipation for molecular-level turbulence simulations

A major difficulty in the analysis of molecular-level simulations is that macroscopic flow quantities are inherently noisy due to molecular fluctuations. An important example for turbulent flows is the kinetic energy dissipation rate. Traditionally, this quantity is calculated from gradients of the macroscopic velocity field, which exacerbates the noise problem. The inability to accurately compute the dissipation rate makes meaningful comparison of molecular-level and continuum simulation results a serious challenge. Herein, we extend previously developed coarse-graining theories to derive an exact molecular-level expression for the dissipation rate, which would circumvent the need to compute gradients of noisy fields. Although the exact expression cannot feasibly be implemented in Sandia’s direct simulation Monte Carlo (DSMC) code SPARTA, we utilize an approximate “hybrid” approach and compare it to the conventional gradient-based approach for planar Couette flow and the two-dimensional Taylor-Green vortex, demonstrating that the hybrid approach is significantly more accurate. Finally, we explore the possibility of adopting a Lagrangian approach to calculate the energy dissipation rate.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Modeling Green Roof Potential to Mitigate Urban Flooding in a Chinese City

The Middle and Lower Reaches of the Yangtze River (MLRYR) region, which has humid subtropical climate conditions and unique plum rain season, is characterized by a simultaneous high-frequency urban flooding and reduction in groundwater levels. Retrofitting the existing buildings into green roofs is a promising approach to combat urban flooding, especially for a densely developed city. Here, the application potential of the Green Roof System (GRS) and the Improved Green Roof System (IGRS) designed to divert overflowing water from green roofs to recharge groundwater were analyzed in a densely developed city, Nanchang, China. For the first time, the influence of GRS on the hydraulic condition of Combined Sewage System/Storm Water System (CSS/SWS) is analyzed, which is a direct reflection of the effect of GRS on alleviating urban flooding. The simulation results show that GRS can retain about 41–75% of precipitation in a 2-hour timescale and the flooding volumes in the GRS/IGRS region are 82% and 28% less than those of the Traditional Roof System (TRS) in 10- and 100-yr precipitation events, respectively. In the continuous simulations, GRS also enhances Evapotranspiration (ET), which accounts for 39% of annual precipitation, so that reduces the cumulative surface runoff. Considering the IGRS can provide more hydrological benefits than the GRS under the same climate conditions, we may conclude that the widespread implementation of both the GRS and the IGRS in Nanchang and other densely developed cities in the MLRYR region could significantly reduce surface and peak runoff rates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Relationship between microporous structure and light gas transport through glassy polymeric membranes revealed by molecular simulations

Microporous glassy polymers are attractive materials for gas separation membranes, due to their high permeability and tailorable selectivity, provided physical aging can be delayed. The archetypal microporous glassy polymer, PTMSP, can be blended with a hyper-crosslinked isatin–triptycene porous polymer network (PPN) to delay physical aging. However, while PPN is effective at reducing physical aging, it also affects the permeability of light gases through PTMSP. Molecular dynamics simulations were used here to shed fundamental light on the mechanisms responsible for these effects. Atomistic models are developed that satisfactorily reproduce experimental observations such as matrix density and cavity size distributions for neat PTMSP as well as for PTMSP–PPN blends. Analysis of the simulation results suggests that physical aging is delayed because the PPN inclusions slow down PTMSP relaxation while reducing the connectivity between free volume pockets. To understand how PPN inclusions affect light gas permeability, the atomistic models developed are used to probe CO 2 and CH 4 diffusion and sorption. These simulations are conducted for PTMSP matrices exhibiting varying density, towards reproducing experimental permeability data. Interrogating the simulation trajectories, it is discovered that while CH 4 travels preferentially through the free volume cavities, CO 2 preferentially interacts with the available surfaces, especially in the presence of PPN. These differences help interpret experimental observations. The transport of C 2 H 6 and H 2 S through PTMSP matrices was also investigated. These gases, and in particular H 2 S, were found to absorb within PTMSP, yielding very low diffusion coefficients. The ability to predict differences in diffusion pathways for various natural gas components unveils the possibility of engineering membranes to control permeability and selectivity towards large-scale applications.

Bao Le, Tran Thi [Univ. of Oklahoma, Norman, OK (U↗

DOE OSTI2022

Evaluation of 3D Simulation Capabilities within xRAGE using a Suite of Test Problems

This presentation describes a 3D verification and validation suite for xRAGE. Three verification test problems for hydrodynamics are presented: the Kidder ball problem, the Verney shell problem, and a 5-material compression problem. There is excellent agreement between 2D and 3D XRAGE simulation results for these problems, and between the xRAGE results and the benchmark solutions. In addition, two 3D ICF test problems are presented, based on an OMEGA direct drive capsule experiment, and on a NIF indirect drive capsule experiment. These two ICF test problems are used to evaluate two hydrodynamic methods within xRAGE. In addition to hydrodynamics the simulations also include three temperature plasma physics, thermal conduction and radiation diffusion. When simulating either capsule in 3D the newer unsplit hydrodynamic method in xRAGE produces more vorticity relative to the older default method. For the indirect drive capsule the 3D simulations are in reasonable agreement with the experimental values of ion temperature and neutron production. Unstable 3D vortex rings are present near the DT ice/carbon interface which enhance the confinement of the DT ice.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Particle charge distributions in the effluent of a flow-through atmospheric pressure low temperature plasma

Atmospheric pressure low-temperature plasmas are often utilized to perform particle synthesis, treatment, and removal. It is well-known that dust particles are highly negatively charged in these plasmas; however, little is known about dust particle charging behavior as particles leave the plasma volume and pass through the spatial afterglow region. In this work, monodisperse particles of various sizes and work functions were introduced into an atmospheric pressure radiofrequency capacitively coupled flow-through plasma. Dust particle electrical mobility distributions downstream of the flow-through plasma were measured utilizing a differential mobility analyzer in conjunction with a condensation particle counter at various gas flow velocities. Charge distributions were determined from the measured electrical mobility distributions. Experiments confirm that particles become less negatively charged, and even net-positively charged after leaving the plasma volume, with a distribution that follows a shifted Boltzmann charge distribution. Additionally, particle charge in the effluent of the flow-through plasma is negligibly dependent on work function but highly size and flow velocity dependent. Larger particles were shown to have a higher magnitude of charge under all studied conditions; however, particle polarity was switchable by varying gas flow velocity. The charging dynamics were simulated utilizing a constant number Monte Carlo model that accounts for electron temperature decay and the transition from ambipolar to free diffusion of electrons and ions in the spatial afterglow. Simulation results also suggest that, at the same flow velocity, larger particles obtain a greater magnitude of charge, negative or positive. Furthermore, the decrease in electron mobility and the difference between ion and electron convective loss rates create an ion-rich region in the plasma effluent that promotes ion–particle collisions and drives particle charge removal and even reversal of polarity. Larger particles more favorably collide with energetic species in these environments, which results in higher charge states.

atmospheric pressure low temperature plasma↗