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At least 721 records · Page 40

Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector

To support the government of Rajasthan and inform state policy makers, regulators, planners, and system operators on power system trends, NREL undertook a long-term capacity expansion planning study. We used NREL's flagship capacity expansion planning tool for the power sector called the Regional Energy Deployment System India (ReEDS-India) to understand the generation and transmission needs of Rajasthan through 2050. NREL's modeling framework includes co-optimized decisions about generation, energy storage, transmission, and reserves investments needed to meet future demand while maintaining reliable electricity supply. Scenario analysis was conducted to assess a range of potential future scenarios, providing insight for planning agencies, utilities, and local stakeholders about key trends and sources of uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

LYNM PE1 Pre-Experiment A Site Characterization Report

Underground chemical explosive experiments such as LYNM PE1 generate large multiphenomenological datasets, require complex site preparation and build out, and utilize cutting edge models and analysis techniques to analyze and simulate the explosion-induced signals. This wide range of outcomes makes it a necessity to thoroughly characterize the testbed in advance of experiments in a way that complements the wide suite of data being generated. Here, we present a broad overview of the site characterization work and data collection that was conducted before Experiment A, which is the first in a series of three PE1 experiments. This work includes, but is not limited to, geologic mapping, physical sample collection, analysis of material properties, geophysical borehole logging, and in-situ measurements. This information was collected by a large, dedicated team and was used to inform site construction, finalize instrumentation placement, generate Geologic Framework Models, feed pre-experiment predictions, and facilitate post-experiment data analysis

58 GEOSCIENCES↗

LYNM PE1 Pre-Experiment A Site Characterization Report

Underground chemical explosive experiments such as LYNM PE1 generate large multi-phenomenological datasets, require complex site preparation and build out, and utilize cutting edge models and analysis techniques to analyze and simulate the explosion-induced signals. This wide range of outcomes makes it a necessity to thoroughly characterize the testbed in advance of experiments in a way that complements the wide suite of data being generated. Here, we present a broad overview of the site characterization work and data collection that was conducted before Experiment A, which is the first in a series of three PE1 experiments. This work includes, but is not limited to, geologic mapping, physical sample collection, analysis of material properties, geophysical borehole logging, and in-situ measurements. This information was collected by a large, dedicated team and was used to inform site construction, finalize instrumentation placement, generate Geologic Framework Models, feed pre-experiment predictions, and facilitate post-experiment data analysis.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Continuum Damage Mechanics Modeling of High-Temperature Flaw Propagation: Application to Creep Crack Growth In 316H Standardized Specimens and Nuclear Reactor Components

Predicting creep crack growth (CCG) of flaws found during operation in high-temperature alloy components is essential for assessing the remaining lifetime of those components. While defect assessment procedures are available for this purpose in design codes, these are limited in their range of applicability. This study assesses the application of a local damage-based finite-element methodology as a more general technique for the prediction of CCG at high temperatures on a variety of structural configurations. Numerical results for stainless steel 316H, which are validated against experimental data, show the promise of this approach. This integration of continuum damage mechanics (CDM) based methodologies, together with adequate inelastic models, into assessment procedures can therefore inform the characterization of CCG under complex operating conditions, while avoiding excessive conservatism. This article shows that such modeling frameworks can be calibrated to experimental data and used to demonstrate that the degree of tri-axiality ahead of a growing creep crack affects its rate of growth. The framework is also successfully employed in characterizing CCG in a realistic reactor pressure vessel geometry under an arbitrary loading condition. These results are particularly relevant to the nuclear power industry for defect assessment and inspections as part of codified practices of structural components with flaws in high-temperature reactors.

42 ENGINEERING↗

A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes

Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.

Chemical engineering↗

Phase-field modeling and experiments of dynamic fracture in single crystal quartz

Predicting the onset and characteristics of brittle fracture is important for a wide range of engineering and geological material applications. In this paper, we study important aspects of brittle fracture in α-quartz by phase-field modeling and experiments using a top-down approach. In the modeling framework, the work term in the Griffith energy balance is replaced with internal energy contributions that represent surface energy, thermal energy, and elastic strain energy stored in defects. This allows parametrization of individual energy contributions in terms of internal state variables and keeps track of energy partitioning after the onset of fracture. The path and history dependence of fracture is included in evolution laws for internal state variables, e.g., entropy evolution, while the energy remains a true potential. In the experimental part, dynamic compression experiments coupled with X-ray phase contrast imaging are performed on cube-like samples with a hole. In the top-down analysis, dynamic compression and three point bending experiments from the literature are simulated with the developed phase-field damage model. In conclusion, the fitted model highlights the strain rate, size, and stress state dependence of damage nucleation and evolution in single crystal α-quartz.

36 MATERIALS SCIENCE↗

Understanding local plant extinctions before it is too late: bridging evolutionary genomics with global ecology

Understanding evolutionary genomic and population processes within a species range is key to anticipating the extinction of plant species before it is too late. However, most models of biodiversity risk under global change do not account for the genetic variation and local adaptation of different populations. Population diversity is critical to understanding extinction because different populations may be more or less susceptible to global change and, if lost, would reduce the total diversity within a species. Here, two new modeling frameworks advance our understanding of extinction from a population and evolutionary angle: Rapid climate change-driven disruptions in population adaptation are predicted from associations between genomes and local climates. Furthermore, losses of population diversity from global land-use transformations are estimated by scaling relationships of species' genomic diversity with habitat area. Overall, these global eco-evolutionary methods advance the predictability – and possibly the preventability – of the ongoing extinction of plant species.

60 APPLIED LIFE SCIENCES↗

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

Elevating zero dimensional global scaling predictions to self-consistent theory-based simulations

In this work, we have developed an innovative workflow, Stability, Transport, Equilibrium, and Pedestal (STEP)-zero-dimensional (0D), within the OMFIT integrated modeling framework. Through systematic validation against the International Tokamak Physics Activity global H-mode confinement database, we demonstrated that STEP-0D, on average, predicts the energy confinement time with a mean relative error of less than 19%. Moreover, this workflow showed promising potential in predicting plasmas for proposed fusion reactors such as the affordable, robust, compact (ARC) reactor, the European demonstration power plant (EU-DEMO), and the China fusion engineering test reactor (CFETR) indicating moderate H-factors between 0.9 and 1.2. STEP-0D allows theory-based prediction of tokamak scenarios, beginning with 0D quantities. The workflow initiates with the PRO-create module, generating physically consistent plasma profiles and equilibrium using the same 0D quantities as the IPB98(y,2) confinement scaling. This sets the starting point for the STEP module, which further iterates between theory-based physics models of equilibrium, core transport, and pedestal to yield a self-consistent solution. Given these attributes, STEP-0D not only improves the accuracy of predicting plasma performance but also provides a path toward a novel fusion power plant design workflow. When integrated with engineering and costing models within an optimization, this new approach could eliminate the iterative reconciliation between plasma models of varying fidelity. This potential for a more efficient design process underpins STEP-0D's significant contribution to future fusion power plant development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future

Electrification and renewables deployment efforts are amplifying the interdependence of the climate and energy systems. Increases in climate model resolution, which is now approaching that of reanalysis datasets and operational weather forecast models, present a unique opportunity to use future climate projections for energy infrastructure planning. In this Perspective, we review recent developments in high-resolution climate modeling, which have been driven by increased computing power and advanced software tools. We then look ahead to discuss how high-resolution climate data can be used to plan for a renewable-dependent future, and envision a unified climate-energy model framework that captures the two-way feedbacks between these interdependent systems.

climate change↗

A Triple-Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme

In the original Predicted Particle Properties (P3) bulk microphysics scheme, all ice-phase hydrometeors are represented by one or more “free” ice categories, where the physical properties evolve smoothly through changes to the four prognostic variables (per category), and with a two-moment representation of the particle size distribution. As such, the spectral dispersion cannot evolve independently, which thus results in limitations in representation of ice—in particular, hail—due to necessary constraints in the scheme to prevent excessive gravitational size sorting. To overcome this, P3 has been modified to include a three-moment representation of the size distribution of each ice category through the addition of a fifth prognostic variable, the sixth moment of the size distribution. The details of the three-moment ice parameterization in P3 are provided. The behavior of the modified scheme, with the single-ice-category configuration, is illustrated through simulations in a simple 1D kinematic model framework as well as with near large-eddy-resolving (250-m grid spacing) 3D simulations of a hail-producing supercell. It is shown that the three-moment ice configuration controls size sorting in a physically based way and leads to an improved capacity to simulate large, heavily rimed ice (hail), including mean and maximum sizes and reflectivity, and thus an overall improvement in the representation of ice-phase particles in the P3 scheme.

54 ENVIRONMENTAL SCIENCES↗

The Relative Importance of Antarctic Sea Ice Loss within the Response to Greenhouse Warming

Abstract The response to Antarctic sea ice loss within a coupled modeling framework is examined in comparison to the response to Arctic sea ice loss and within the context of general greenhouse warming. Sea ice loss responses are found to be linear (particularly in response to Antarctic or global sea ice loss) with respect to the degree of imposed perturbation and additive when perturbations are applied in hemispheres separately and concurrently. Globally, and in the tropical Pacific in particular, Antarctic sea ice loss plays a relatively larger role than Arctic sea ice loss in both the atmosphere and the ocean, within the parameters of our experiments. The pattern of response to Antarctic sea ice loss is also found to more closely resemble that of greenhouse warming, again particularly in the tropics. An extension to multiparameter pattern scaling is developed to include a scaling factor for Antarctic change in addition to those for tropical warming and Arctic sea ice loss. The decomposition is applied to the modeled response to Antarctic sea ice loss to break it down into component partial responses that scale with Antarctic, tropical, and Arctic changes. This reveals the aspects of the response that are directly related to Antarctic change, such as an equatorward intensification of tropical precipitation in the Northern Hemisphere, and those that are modified via the induced changes in the tropics and Arctic, such as Northern Hemisphere temperature change. With this, we hope to gain a deeper understanding of the role of each of these changes for the development of physical mechanisms of the response.

Meteorology & Atmospheric Sciences↗

Preparing Distribution Utilities for the Future - Unlocking Demand-Side Management Potential: A Novel Analytical Framework

The balance of supply and demand in the power systems has traditionally been served solely through generation and network capacity planning and operations. However, with increased requirements for flexibility due to the uptake in variable renewable generation sources such as wind and solar there is a need to increased demand-side flexibility. In addition, there are increased communications and flexibility capabilities emerging on the demand-side from the adoption of advanced metering infrastructures and smart meter deployment and intelligent loads such as smart thermostats and schedulable white goods (e.g. dishwashers and washing machines). Unlocking demand-side flexibility can bring system benefits from peak load reduction bringing about generation capacity and network upgrade deferral, to reducing demand and more efficient utilization of generation and network capacity. Unlocking demand-side flexibility is an evolving process for utilities and solutions must be tailored to each specific customer group. Demand-side management (DSM) is a broad set of tools that can include demand response (both dispatchable and non-dispatchable), energy efficiency and distributed energy resources and demand-side technologies. The National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL) and Deloitte, examined the potential of DSM in BRPL’s service territory, developing detailed information on customer classes and willingness to participate in DSM. The study developed modeling frameworks for load analysis and the analysis tools to assess the potential of time-of-use tariffs in motivating customers to reduce their peak period energy consumption. The study shows that BRPL customers, specifically their domestic customers, are willing to participate in DSM programs and that time-of-use pricing can help BRPL reduce their peak demand and help unlock demand-side flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks

The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Incorporating Heterogeneity into 3D Geologic Models for the Alluvial Basin Reference Case

The unsaturated zone alluvium reference case is one of several geologic systems under consideration by the U.S. Department of Energy Office of Nuclear Energy for hosting repositories for spent nuclear fuel and associated waste (Sevougian et al., 2019). As noted by Mariner et al. (2018), the generic alluvial basin offers positive attributes that merit its consideration as a reference case by the Spent Fuel and Waste Science and Technology (SFWST) campaign. Hundreds of alluvial basins and sub-basins are scattered across the arid western United States (Figure 1-1). Precipitation and infiltration rates are relatively low with high evapotranspiration, resulting in deep regional water tables. Deep regional water tables allow for significant vertical separation between proposed repository depths and groundwater and thus longer transport paths from a hypothetical repository to an aquifer. Accumulations of alluvial sediments within these basins are typically on the order of hundreds of meters, and locally may exceed 1,000 m in thickness, as is the case for the Deming sub-basin in southern New Mexico. In alluvial basins, alluvium creates a thick geologic host medium that serves as the natural barrier system (NBS) in the conceptual model framework of a geologic disposal system and isolates the waste packages from receptors in the biosphere. Further, alluvial basin fill is typically comprised of stacked playa and lacustrine deposits along the basin axis (Perry et al., 2018). Characterized by low permeability, these layers protect the biosphere above the repository and the groundwater resources below the repository by limiting flow and transport of radionuclides.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Rock Valley Dense Gravity Acquisition

Characterizing the shallow structure of the Rock Valley region of the Nevada National Security Site is a critical component of the Rock Valley Direct Comparison project. Geophysical data of the region is needed for operational decisions, to constrain geologic models used for simulation, and to facilitate the analysis of future explosive source data. Local measurements of gravity are a key piece of geophysical information that helps to resolve the underlying geologic composition, fault structure, and density characteristics, yet, in the Rock Valley region these measurements are sparse on the scale of the testbed. In this report, we present the details of a recent gravity data acquisition survey designed to collect a dense dataset in the region of interest that complements the existing gravity work but greatly enhances our resolution. This dataset will be integrated with a complementary Los Alamos National Laboratory gravity collection and combined with the existing seismic data in a joint inversion. These measurements were conducted over two weeks with a portable gravimeter and high-resolution GPS and include repeat measurements at a USGS base station as well as reoccupation of gravity sites in the regional dataset. This collection of over 100 new dense gravity measurements will facilitate refinement of the existing Geologic Framework Model and directly complement newly acquired dense seismic data, ultimately improving the project’s ability to investigate the direct comparison of shallow earthquake and explosive sources.

58 GEOSCIENCES↗

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.

Earth Systems↗

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.

Earth Systems↗