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DOE OSTI2012

LCLS-II New Instruments Workshops Report

The LCLS-II New Instruments workshops chaired by Phil Heimann and Jerry Hastings were held on March 19-22, 2012 at the SLAC National Accelerator Laboratory. The goal of the workshops was to identify the most exciting science and corresponding parameters which will help define the LCLS-II instrumentation. This report gives a synopsis of the proposed investigations and an account of the workshop. Scientists from around the world have provided short descriptions of the scientific opportunities they envision at LCLS-II. The workshops focused on four broadly defined science areas: biology, materials sciences, chemistry and atomic, molecular and optical physics (AMO). Below we summarize the identified science opportunities in the four areas. The frontiers of structural biology lie in solving the structures of large macromolecular biological systems. Most large protein assemblies are inherently difficult to crystallize due to their numerous degrees of freedom. Serial femtosecond protein nanocrystallography, using the 'diffraction-before-destruction' approach to outrun radiation damage has been very successfully pioneered at LCLS and diffraction patterns were obtained from some of the smallest protein crystals ever. The combination of femtosecond x-ray pulses of high intensity and nanosized protein crystals avoids the radiation damage encountered by conventional x-ray crystallography with focused beams and opens the door for atomic structure determinations of the previously largely inaccessible class of membrane proteins that are notoriously difficult to crystallize. The obtained structures will allow the identification of key protein functions and help in understanding the origin and control of diseases. Three dimensional coherent x-ray imaging at somewhat lower resolution may be used for larger objects such as viruses. The chemistry research areas of primary focus are the predictive understanding of catalytic mechanisms, with particular emphasis on photo- and heterogeneous catalysis. Of particular interest is the efficient conversion of light to electrical or chemical energy, which requires understanding the non-adiabatic dynamics of electronic excited states. Ultrafast x-ray scattering presents an excellent opportunity to investigate structural dynamics of molecular systems with atomic resolution, and x-ray scattering and spectroscopy present an excellent opportunity to investigating the dynamics of the electronic charge distribution. Harnessing solar energy to generate fuels, either indirectly with photovoltaics and electrochemical catalysis or directly with photocatalysts, presents a critical technological challenge that will require the use of forefront scientific tools such as ultrafast x-rays. At the center of this technical challenge is the rational design of efficient and cost effective catalysts. Important materials science opportunities relate to information technology applications, in particular the transport and storage of information on increasingly smaller length- and faster time-scales. Of interest are the understanding of the intrinsic size limits associated with the storage of information bits and the speed limits of information or bit processing. Key questions revolve about how electronic charges and spins of materials can be manipulated by electric and magnetic fields. This requires the exploration of speed limits subject to the fundamental conservation laws of energy and linear and angular momentum and the different coupling of polar electric and axial magnetic fields to charge and spin. Of interest are novel composite materials, including molecular systems combining multi electric and magnetic functionality. Ultrafast x-rays offer the required probing speed, can probe either the charge or spin properties through polarization control and through scattering and spectroscopy cover the entire energy-time-momentum-distance phase space. In the field of atomic and molecular science, LCLS II promises to elucidate the fundamental interactions among electrons and between electrons and nuclei, and to explore the frontiers of light-matter interactions. The high x-ray intensities unique to LCLS II will allow for highly localized electron excitation and probing at different positions inside a molecule, thereby interrogating the fundamental electron correlations. At the ultimate intensities, a breakdown of our established model of x-ray - matter interaction is predicted, leading to possibly new regimes of plasma physics.

14 SOLAR ENERGY↗

DOE OSTI2017

Molecular Diversity of Sea Spray Aerosol Particles: Impact of Ocean Biology on Particle Composition and Hygroscopicity

The impact of sea spray aerosol (SSA) on climate depends on the size and chemical composition of individual particles that make-up the total SSA ensemble. While the organic fraction of SSA has been characterized from a bulk perspective, there remains a lack of understanding as to the composition of individual particles within the SSA ensemble. To better understand the molecular components within SSA particles and how SSA composition changes with ocean biology, simultaneous measurements of seawater and SSA were made during a month-long mesocosm experiment performed in an ocean-atmosphere facility. Herein, we deconvolute the composition of freshly emitted SSA devoid of anthropogenic and terrestrial influences by characterizing classes of organic compounds as well as specific molecules within individual SSA particles. Analysis of SSA particles show that the diversity of molecules within the organic fraction varies between two size fractions (submicron and supermicron) with contributions from fatty acids, monosaccharides, polysaccharides and siliceous material. Significant changes in the distribution of these compounds within individual particles are observed to coincide with the rise and fall of phytoplankton and bacterial populations within the seawater. Furthermore, water uptake is impacted as shown by hygroscopicity measurements of model systems composed of representative organic compounds. Thus, the how changes in the hygroscopic growth of SSA evolves with composition can be elucidated. Overall, this study provides an important connection between biological processes that control the composition of seawater and changes in single particle composition which will enhances our ability to predict the impact of SSA on climate.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2022

Pulsed power to control growth of silicon nanoparticles in low temperature flowing plasmas

Low-temperature plasmas have seen increasing use for synthesizing high-quality, mono-disperse nanoparticles (NPs). Recent work has highlighted that an important process in NP growth in plasmas is particle trapping—small, negatively charged nanoparticles become trapped by the positive electrostatic potential in the plasma, even if only momentarily charged. In this article, results are discussed from a computational investigation into how pulsing the power applied to an inductively coupled plasma (ICP) reactor may be used for controlling the size of NPs synthesized in the plasma. The model system is an ICP at 1 Torr to grow silicon NPs from an Ar/SiH 4 gas mixture. This system was simulated using a two-dimensional plasma hydrodynamics model coupled to a three-dimensional kinetic NP growth and trajectory tracking model. The effects of pulse frequency and pulse duty cycle are discussed. We identified separate regimes of pulsing where particles become trapped for one pulsed cycle, a few cycles, and many cycles—each having noticeable effects on particle size distributions. For the same average power, pulsing can produce a stronger trapping potential for particles when compared to continuous wave power, potentially increasing particle mono-dispersity. Pulsing may also offer a larger degree of control over particle size for the same average power. Experimental confirmation of predicted trends is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Continuous soil temperature measurements from 2019-10-4 to 2020-10-4, Teller road Mile 27, Seward Peninsula, Alaska

The dataset contains depth-resolved soil temperature measured at 45 discrete locations in a watershed located along the Nome-Teller road at Mile 27 in Seward Peninsula, Alaska. The dataset was generated to understand the local heterogeneity of soil thermal dynamics and their controls in a discontinuous permafrost region. At each location, temperatures were measured by a distributed temperature profiling probe designed based on Dafflon et al (2022). The dataset includes a description of the probe locations in the "Probe_locations.csv" file and the 45 data files (Soil_temperatures_*.csv). Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in NGA513_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

The “High Fidelity, Faster than RealTime Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of largescale power system dynamics simulation, including (1) a validated faster than real time simulation of both stable and unstable transient dynamics in a largescale positive sequence transmission grid model, (2) a threephase unbalanced simulation platform for modeling new grid devices, such as independently controlled singlephase static var compensators (SVCs), (3) the world’s first high fidelity threephase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a firstofits kind implementation of a singlephase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the longterm, the simulator will form the backbone of the newly conceived hybrid realtime protection and control architecture that will coordinate local controls, widearea measurements, widearea controls and advanced realtime prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the fasterthanrealtime simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three phase unbalanced simulator’s ability to model threephase and single phase networks and devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Investigation of the impact of supplemental reflective films to improve micro-light climate within tomato plant canopy in solar greenhouses

The non-uniform growth and development of crops within Chinese Solar Greenhouses (CSG) is directly related to the micro-light climate within canopy. In practice, reflective films are used to improve micro-light climate within plant canopy by homogenizing light distribution and so increasing total plant light interception. However, as to our knowledge, the contributions to light distribution within canopy have not been investigated for passive reflector like reflective films. Field experiments dealing with light conditions and growth behavior over time, are complicated to carry out, time-consuming and hard to control, while however, accurate measurements of how reflective films influence the micro-light climate of canopy are an essential step to improve the growth conditions for any crop. Here, we propose a supplementary light strategy using reflective films to improve light distribution within plant canopy. Based on the example of CSG, a 3D greenhouse model including a detailed 3D tomato canopy structure was constructed to simulate the influence of supplementary reflective films to improve micro-light climate. Comparison of measured solar radiation intensity with predicted model data demonstrated that the model could precisely predict light radiation intensity over time with different time points and positions in the greenhouse. A series of reflective film configurations were investigated based on features analysis of light distribution in the tomato canopy on sunny days using the proposed model. The reflective film configuration scheme with the highest impact significantly improved the evenness of horizontal and vertical light distribution in tomato canopy. The strategy provided here can be used to configure reflective films that will enhance light conditions in CSG, which can be applied and extended in different scenarios.

Liu, Anhua↗

DOE OSTI2017

A Multiple Flux-tube Solar Wind Model

We present a new model, MULTI-VP, which computes the three-dimensional structure of the solar wind and includes the chromosphere, the transition region, and the corona and low heliosphere. MULTI-VP calculates a large ensemble of wind profiles flowing along open magnetic field lines that sample the entire three-dimensional atmosphere or, alternatively, a given region of interest. The radial domain starts from the photosphere and typically extends to about 30 R{sub ⊙}. The elementary uni-dimensional wind solutions are based on a mature numerical scheme that was adapted in order to accept any flux-tube geometry. We discuss here the first results obtained with this model. We use Potential Field Source-surface extrapolations of magnetograms from the Wilcox Solar Observatory to determine the structure of the background magnetic field. Our results support the hypothesis that the geometry of the magnetic flux-tubes in the lower corona controls the distribution of slow and fast wind flows. The inverse correlation between density and speed far away from the Sun is a global effect resulting from small readjustments of the flux-tube cross-sections in the high corona (necessary to achieve global pressure balance and a uniform open flux distribution). In comparison to current global MHD models, MULTI-VP performs much faster and does not suffer from spurious cross-field diffusion effects. We show that MULTI-VP has the capability to predict correctly the dynamical and thermal properties of the background solar wind (wind speed, density, temperature, magnetic field amplitude, and other derived quantities) and to approach real-time operation requirements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

VADER: A Tool for Criticality Safety Validation

The purpose of criticality safety is to prevent any inadvertent criticality from occurring during the handling or storage of fissile material. Calculations are frequently used to demonstrate that a sufficient subcritical margin exists. Validation is a key aspect of the evaluation process, establishing the suitability, accuracy, and associated uncertainty of the computational method and data to be used for the intended application. The validation process is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 in order to investigate the parameters at which such a critical condition is achieved. The validation parameters that are traditionally applied to safety analysis calculations are the bias and the bias uncertainty . The bias is the deviation of the average k eff of the validation suite from unity. The bias uncertainty accounts for the statistical uncertainty in the bias based on the standard deviation, sample size, and distribution of k eff values of the validation suite. The values of bias and bias uncertainty ensure that the systems predicted to be subcritical by the computational method will indeed be subcritical. The bias and bias uncertainty are often combined to determine an upper subcritical limit (USL) or computational margin that can then be applied to safety analysis calculations. Many methods have been developed by different organizations to calculate the bias and bias uncertainty for various types of criticality analyses. Each of these methods typically requires that the validity of various underpinning statistical assumptions be confirmed to demonstrate that the method is appropriate for the analysis of a given validation suite. An example of the validation decision making flow is shown in Fig.1. As shown in Fig. 1, the analyst performing the validation fits a trend line to the data and performs a test to determine if the trend was a statistically better representation of the data than if it were treated as an uncorrelated sample. If the trend line is a better representation of the data, then the analyst uses any one of a number of trending techniques to determine the bias and bias uncertainty. If a trend is not an appropriate representation of the data, then the analyst proceeds to perform a normality assessment for the data. If the normal assumption can be shown to be acceptable, then the analyst calculates the bias and bias uncertainty with the parametric technique. If the assumption of normality cannot be justified, then the nonparametric technique is used. Once the decision flow has been followed and the appropriate technique has been selected, the bias and bias uncertainty is typically combined with an administrative margin to determine a USL below which calculated values of k eff for safety analysis models can be considered subcritical. The calculations used in each decision are often performed with spreadsheets or with small programs available at various sites performing criticality analyses. Expertise in understanding and interpreting the results must be maintained to perform these calculations. This can often be an error-prone process. Oak Ridge National Laboratory (ORNL) is currently developing the Validation and Data Evaluation Resource (VADER) to simplify and automate the criticality safety validation process and to provide a software quality assurance pedigree to the calculational methods used. This paper discusses the use of the Fulcrum user interface with VADER, the anticipated initial capabilities of VADER to perform validation analyses, and the output from the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Generic Photovoltaic Inverter Model in an Electromagnetic Transients Simulator for Transmission Connected Plants

This report proposes a generic model specification of a photovoltaic inverter applied in transmission-connected plants for implementation in an electromagnetic transients simulator. The model specification contains the necessary control loops to meet the fault ride-through performance requirements in the IEEE 2800-2022 standard. The report details the implementation and example parameterization of the model in PSCAD™. Simulation results verify the model meets the performance requirements. Comparisons of the model’s response to laboratory test measurements of a commercial 2.2 MVA storage inverter show the model can reasonably predict the response of commercial equipment.

14 SOLAR ENERGY↗

DOE OSTI2016

A Comparison of Modeling Strategies for Additively Manufactured HFIR Control Elements

The High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory is a flux-trap type research reactor that is used for a range of research applications, including neutron scattering experiments, materials irradiation tests, and isotope production. The HFIR core comprises several concentric cylindrical regions; starting from the core centerline and moving radially outwards, these are the flux trap target (FTT) region, the inner and outer fuel elements (IFE and OFE), the inner and outer control elements (ICE and OCE), and the reflector region. The control elements (CEs) are axially zoned into regions of differing absorption strength: the white regions contain only structural aluminum and do not significantly contribute to reactivity control; the gray regions contain tantalum as the primary absorber with a concentration of 38% by volume, and the black regions contain europia (Eu{sub 2}O{sub 3}) as the primary absorber with a concentration of 31% by volume. During operation, the CEs are withdrawn symmetrically in opposite directions from the core to remove the neutron absorbers from the core and maintain criticality. The current approach to fabrication of the HFIR CEs is tedious, outdated, and expensive. In an effort to improve the operational economics of HFIR and to demonstrate the feasibility of advanced manufacturing techniques for production of nuclear reactor components, novel methods for production of neutron-poison bearing aluminum structures have been initiated at ORNL. For this application, the ultrasonic additive manufacturing (UAM) process involves the use of 3D printing technology to construct small cylindrical compacts (0.559 cm in diameter and 0.171 cm in height) of aluminum mixed with neutron-absorbing material. The compacts contain 60% poison (Ta or Eu{sub 2}O{sub 3}) by volume. These compacts are then embedded into an aluminum matrix before formation into the cylindrical shape appropriate for use in HFIR. The CEs produced in this process therefore contain discrete regions of absorbing material, in contrast to the traditional design with homogeneously distributed absorbers. It is therefore of interest to investigate how the HFIR core behavior with discrete CEs differs from the case with homogeneous CEs with respect to some key reactor physics parameters. The primary objective of this study is to compare modeling strategies for the discrete CE design and examine differences in the core physics between the discrete and homogeneous CE designs as predicted by each model. Lessons learned from this investigation may then be used to inform the design process in future endeavors. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Forecasting Commercial Building Electricity Consumption, Zone Airflow and Zone Temperature: Update - Development of a Generalized Machine Learning Approach

The U.S. power grid is being transformed to make it smarter, more efficient, and cleaner. This transformation is leading to the addition of a significant of energy generated by distributed, variable, and renewable resources. Because of the variable nature of renewable generation, the short- and long-term supply and demand imbalances are less predictable, and conventional approaches to mitigating the imbalances will be less efficient or cost effective. To address this challenge and to support the mission and the vision of the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) Building Technologies Office has developed a Grid-Interactive Efficient Building Strategy. The strategy focuses on simultaneously improving building energy efficiency and supporting reliability and resilience of the electric grid more efficiently and at a lower cost. In addition, EERE and DOE’s Office of Electricity created an initiative led by DOE and supported by the national laboratories under the Grid Modernization Lab Consortium structure to enhance grid modernization. The work reported in this document is part of the first set of projects funded under the initiative to design, develop, and validate scalable transactive control technologies for the commercial buildings sector. Transactive controls requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical grey- and black-box models have been widely used to express flexibility. Although this approach is generally easy to construct and simple to use, it does not capture non-linear behavior that some end-use loads represent. Therefore, Pacific Northwest National Laboratory (PNNL) with support from Western Washington University conducted this research to explore the use of deep machine learning (ML) techniques. The work reported in this document is limited to forecasting whole building electricity consumption, the zone airflow and the zone temperature predictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Multi-scenario modelling of uncertainty in stochastic chemical systems

Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Predicting Radiation-Induced Plutonium Redox Chemistry using Multi-scale Modeling Methods

Over the the last 70 years plutonium (Pu) has been integral in the development of several technologies that have changed the world, yet our fundamental understanding of its chemistry is still far from complete. This is a testament to this element’s unique and complex properties, such as its ability to coexist as multiple oxidation states in aqueous solution. Careful manipulation of plutonium oxidation states is essential in the study and utilization of its rich chemistry. To achieve this level of control, a comprehensive mechanistic understanding of radiation-induced plutonium redox chemistry is critical due to the unavoidable exposure of plutonium to ionizing radiation fields, both inherent and from in-process applications. For this reason, we have developed an experimentally evaluated multi-scale computer model for the prediction of gamma radiation-induced Pu(IV) redox chemistry in concentrated nitric acid solutions (1.0, 3.0, and 6.0 M). Under these acidic, aqueous solution conditions, cobalt-60 gamma irradiation afforded negligible net change in the steady-state oxidation state distribution of Pu(IV). Multi-scale calculations, which are in excellent agreement with experimental data, indicate that this observation is due to radiation-induced redox cycling between Pu(IV) and Pu(III), as achieved by the reduction of Pu(IV) by radiolytic nitrous acid and hydrogen peroxide, and the oxidation of Pu(III) by nitrate and hydroxyl radicals. These radiation-induced redox processes are augmented by plutonium’s inherent disproportionation reactions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2020

Towards Robustness Guarantees for Feedback-Based Optimization

Feedback-based online optimization algorithms have gained traction in recent years because of their simple implementation, their ability to reject disturbances in real time, and their increased robustness to model mismatch. While the robustness properties have been observed both in simulation and experimental results, the theoretical analysis in the literature is mostly limited to nominal conditions. In this work, we propose a framework to systematically assess the robust stability of feedback-based online optimization algorithms. We leverage tools from monotone operator theory, variational inequalities and classical robust control to obtain tractable numerical tests that guarantee robust convergence properties of online algorithms in feedback with a physical system, even in the presence of disturbances and model uncertainty. The results are illustrated via an academic example and a case study of a power distribution system.

approximation algorithms↗

DOE OSTI2023

Creation of Synthetic Electric Grids (SPP/MISO) Supporting PERFORM (Final Report)

Over the course of the project, two “realistic but not real” synthetic transmission-level grid models over the SPP-MISO and ERCOT footprints were created to provide more realistic data and increase the reliability and resiliency of the grids under a variety of scenarios. The synthetic ERCOT transmission grid is compatible with the distribution grid developed in collaboration with NREL. All generators are based on the EIA 860 data and a column with EIA plant code and Gen ID is added to generators of both grids so that they can be easily mapped. The improvements are also made to electric grids including N-1 contingencies with some remedial actions, improving the transmission lines to avoid lines in lakes, including an HVDC line to the SPP-MISO case, providing several generator parameters and their temporal constraints that were not included in EIA 860 form, generators’ cost curves, load offer curves, adding phase shifters and tap changers with impedance correction tables, adding reactive power control and partitioning the grids into active and reactive reserve zones and determine different types of the required reserve for each zone. Hourly load time series at the bus level were generated to create scenarios for solving power flow in different loading conditions. Weather measurement information and the models of renewable generators are used to directly include the impact of weather on the grids. Based on a variety of load and weather conditions the grids are improved to accommodate different conditions. The ERCOT 7k-bus grids were also modeled for the year 2030 with predicted improvements in renewable resources. The renewable generation model was also improved with historic weather data included. The impact of electric vehicles on the ERCOT grid is also modeled.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2012

A Comparison of TWP-ICE Observational Data with Cloud-Resolving Model Results

Observations made during the TWP-ICE campaign are used to drive and evaluate thirteen cloud-resolving model simulations with periodic lateral boundary conditions. The simulations employ 2D and 3D dynamics, one- and two-moment microphysics, several variations on large-scale forcing, and the use of observationally derived aerosol properties to prognose droplet numbers. When domain means are averaged over a 6-day active monsoon period, all simulations reproduce observed surface precipitation rate but not its structural distribution. Simulated fractional areas covered by convective and stratiform rain are uncorrelated with one another, and are both variably overpredicted by up to a factor of {approx}2. Stratiform area fractions are strongly anticorrelated with outgoing longwave radiation (OLR) but are negligibly correlated with ice water path (IWP), indicating that ice spatial distribution controls OLR more than mean IWP. Overpredictions of OLR tend to be accompanied by underpredictions of reflected shortwave radiation (RSR). When there are two simulations differing only in microphysics scheme or large-scale forcing, the one with smaller stratiform area tends to exhibit greater OLR and lesser RSR by similar amounts. After {approx}10 days, simulations reach a suppressed monsoon period with a wide range of mean precipitable water vapor, attributable in part to varying overprediction of cloud-modulated radiative flux divergence compared with observationally derived values. Differences across the simulation ensemble arise from multiple sources, including dynamics, microphysics, and radiation treatments. Close agreement of spatial and temporal averages with observations may not be expected, but the wide spreads of predicted stratiform fraction and anticorrelated OLR indicate a need for more rigorous observation-based evaluation of the underlying micro- and macrophysical properties of convective and stratiform structures.

58 GEOSCIENCES↗

DOE OSTI2022

Predicted Impacts of Pt and Ionomer Distributions on Low-Pt-Loaded PEMFC Performance

Low-cost, high performance proton exchange membrane fuel cells (PEMFCs) have been difficult to develop due to limited understanding of coupled processes in the cathode catalyst layer (CCL). Low-Pt-loaded PEMFCs suffer losses beyond those predicted solely due to reduced catalyst area. Although consensus links these losses to thin ionomer films in the CCL, a precise mechanistic explanation remains elusive. In this publication, we present a physically based PEMFC model with novel structure-property relationships for thin-film Nafion, validated against PEMFC data with low Pt loading. Results suggest that flooding exacerbates kinetic limitations in low-loaded PEMFCs, shifting the Faradaic current distribution. As current density increases, protons travel further into the CCL, resulting in higher Ohmic overpotentials. We also present a parametric study of CCL design parameters. We find that graded Pt and ionomer loadings reduce Ohmic losses and flooding, but individually do not provide significant improvements. However, a dual-graded CCL (i.e., graded Pt and ionomer) is predicted to significantly improve the maximum power density and limiting current compared to uniformly loaded CCLs. This work highlights the importance of accurate transport parameters for thin-film Nafion and provides a pathway to low-cost PEMFCs via precise control of CCL microstructures.

08 HYDROGEN↗