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At least 1,027 records · Page 57

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

Understanding the potential impacts of climate change is complicated by mismatched spatial representations between gridded Earth System Models (ESMs) and Integrated Assessment Models (IAMs), whose regions are typically larger and defined by geopolitical and biophysical criteria. In this study we address uncertainty stemming from the construction of land use regions in an IAM, the Global Change Assessment Model (GCAM), whose regions are currently based on historical climatic conditions (1961-1990). We re-define GCAM’s regions according to projected climatic conditions (2070-2099), and investigate how this changes model outcomes for land use, agriculture, and forestry. By 2100, we find potentially large differences in projected global and regional area of biomass energy crops, fodder crops, harvested forest, and intensive pasture. These land area differences correspond with changes in agricultural commodity prices and production. These results have broader implications for understanding policy scenarios and potential impacts, and for evaluating and comparing IAM and ESM simulations.

54 ENVIRONMENTAL SCIENCES↗

Assessment of Transition Modeling Capability in OVERFLOW with Emphasis on Swept-Wing Configurations

In preparation for comparisons with data obtained from the recently concluded experiments in the National Transonic Facility at the NASA Langley Research Center on the new common research model with natural laminar flow (CRM-NLF), an assessment of the current transition modeling capability in the NASA OVERFLOW 2.2o code has been carried out. A combination of the available experimental data and linear stability analysis is used to evaluate the accuracy and robustness of these models for selected swept-wing type configurations, with significant crossflow. An additional goal for this work involves providing a comparative assessment of the relevant transition models in the context of a single flow solver and identifying model limitations as well as the potential for future improvements that would help strengthen the physical basis of such transition models. Included in this investigation is an assessment of the sensitivities of the underlying transition models to grid resolution (wall-normal, as well as streamwise and spanwise) and the values of extra input parameters such as the level of surface roughness and freestream turbulence variables. The flow configurations targeted in this assessment include the NASA NLF(2)-0415 swept-wing configuration, the sickle-shaped wing introduced by the Technical University of Braunschweig, and the wing-body configuration of the CRM model from the fourth and fifth AIAA CFD Drag Prediction Workshops.

Freestream velocity↗

Ultraviolet line profiles of slowly rotating massive star winds using the ‘analytic dynamical magnetosphere’ formalism

Recent large-scale spectropolarimetric surveys have established that a small but significant percentage of massive stars host stable, surface dipolar magnetic fields with strengths on the order of kG. These fields channel the dense, radiatively driven stellar wind into circumstellar magnetospheres, whose density and velocity structure can be probed using ultraviolet (UV) spectroscopy of wind-sensitive resonance lines. Coupled with appropriate magnetosphere models, UV spectroscopy provides a valuable way to investigate the wind–field interaction, and can yield quantitative estimates of the wind parameters of magnetic massive stars. We report a systematic investigation of the formation of UV resonance lines in slowly rotating magnetic massive stars with dynamical magnetospheres. We pair the analytic dynamical magnetosphere (ADM) formalism with a simplified radiative transfer technique to produce synthetic UV line profiles. Using a grid of models, we examine the effect of magnetosphere size, the line strength parameter, and the cooling parameter on the structure and modulation of the line profile. We find that magnetic massive stars uniquely exhibit redshifted absorption at most viewing angles and magnetosphere sizes, and that significant changes to the shape and variation of the line profile with varying line strengths can be explained by examining the individual wind components described in the ADM formalism. Finally, we show that the cooling parameter has a negligible effect on the line profiles.

C Erba↗

A unified framework of stabilized finite element method for solving the Boltzmann transport equation

This paper presents a unified framework of stabilized finite element method for solving the Boltzmann transport equation. Unlike the traditional Petrov-Galerkin finite element method which modifies the test function to construct the stabilization term, we derive the stabilization methods from the standard Galerkin weak form with Sub-grid scale model. The basic idea of this method is to decompose the unknowns into its numerical solution and residual, with an approximation for the residual and embeds it in the Galerkin weak form to yield a stabilized variational formula. Different approximations of the residual lead to different stabilization methods, all the frequently used stabilized methods, including the Streamline Upwinding Petrov-Galerkin (SUPG) method, Galerkin/Least-Square (GLS) method, and Algebraic Sub-Grid Scale (ASGS) method can be obtained from this framework. The similarities and differences of the different approximations are compared in this paper. The numerical results show that the behaviors of the different methods area similar with the same stabilization parameter, and all these stabilized techniques can obtain a correct and stable solution. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Gaining insight into lithium-ion battery degradation by a calorimetric approach

With the growing demand for lithium-ion batteries (LIBs) in transportation and renewable energy sectors, ensuring reliability and mitigating degradation are crucial challenges for their widespread deployment. Here this study investigates the relationship between thermal characteristics and degradation/reliability by developing an in-situ heat measurement methodology for LIBs operating under grid services. Using adiabatic mode-based calorimetry, we examine the thermal behavior of two commercial cells with different cathode chemistries (Ni-rich layered oxide and olivine) before and after two years of grid service (peak shaving) and demonstrate a strong correlation between thermal characteristics and electrochemical performance and its degradation. By further analyzing the heat sources separation (differentiating between irreversible and reversible heat), we disclose the underlying degradation mechanisms of LIBs. These findings emphasize the critical role of thermal characteristics in determining LIB reliability and deterioration, while the obtained heat data can aid in the development and calibration of LIB state-of-health models for grid applications.

25 ENERGY STORAGE↗

Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)

Abstract. We describe the development of a block-structured, equal-CPU-load (central processing unit), multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Fully Nonlinear Boussinesq Wave Model with Total Variation Diminishing Solver). The new model framework does not interfere with the core solver, and thus the core program, FUNWAVE-TVD, is still a standalone model used for a single grid. The nesting interface manages the time sequencing and two-way nesting processes between the parent grid and child grid with grid refinement in a hierarchical manner. Workload balance in the MPI-based (message passing interface) parallelization is handled by an equal-load scheme. A strategy of shared array allocation is applied for data management that allows for a large number of nested grids without creating additional memory allocations. Four model tests are conducted to verify the nesting algorithm with assessments of model accuracy and the robustness in the application in modeling transoceanic tsunamis and coastal effects.

Choi, Young-Kwang↗

Analyzing inference workloads for spatiotemporal modeling

Ensuring power grid resiliency, forecasting climate conditions, and optimization of transportation infrastructure are some of the many application areas where data is collected in both space and time. Spatiotemporal modeling is about modeling those patterns for forecasting future trends and carrying out critical decision-making by leveraging machine learning/deep learning. Once trained offline, field deployment of trained models for near real-time inference could be challenging because performance can vary significantly depending on the environment, available compute resources and tolerance to ambiguity in results. Users deploying spatiotemporal models for solving complex problems can benefit from analytical studies considering a plethora of system adaptations to understand the associated performance-quality trade-offs. To facilitate the co-design of next-generation hardware architectures for field deployment of trained models, it is critical to characterize the workloads of these deep learning (DL) applications during inference and assess their computational patterns at different levels of the execution stack. In this paper, we develop several variants of deep learning applications that use spatiotemporal data from dynamical systems. We study the associated computational patterns for inference workloads at different levels, considering relevant models (Long short-term Memory, Convolutional Neural Network and Spatio-Temporal Graph Convolution Network), DL frameworks (Tensorflow and PyTorch), precision (FP16, FP32, AMP, INT16 and INT8), inference runtime (ONNX and AI Template), post-training quantization (TensorRT) and platforms (Nvidia DGX A100 and Sambanova SN10 RDU). Overall, our findings indicate that although there is potential in mixed-precision models and post-training quantization for spatiotemporal modeling, extracting efficiency from contemporary GPU systems might be challenging. Instead, co-designing custom accelerators by leveraging optimized High Level Synthesis frameworks (such as SODA High-Level Synthesizer for customized FPGA/ASIC targets) can make workload-specific adjustments to enhance the efficiency.

97 MATHEMATICS AND COMPUTING↗

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dust masses of disks around 8 brown dwarfs and very low-mass stars in upper SCO OB1 and Ophiuchus

We present the results of ALMA band 7 observations of dust and CO gas in the disks around 7 objects with spectral types ranging between M5.5 and M7.5 in Upper Scorpius OB1, and one M3 star in Ophiuchus. We detect unresolved continuum emission in all but one source, and the {sup 12}CO J = 3 − 2 line in two sources. We constrain the dust and gas content of these systems using a grid of models calculated with the radiative transfer code MCFOST, and find disk dust masses between 0.1 and 1 M{sub ⊕}, suggesting that the stellar mass/disk mass correlation can be extrapolated for brown dwarfs (BDs) with masses as low as 0.05 M{sub ⊙}. The one disk in Upper Sco in which we detect CO emission, 2MASS J15555600, is also the disk with the warmest inner disk, as traced by its H–[4.5] photometric color. Using our radiative transfer grid, we extend the correlation between stellar luminosity and mass-averaged disk dust temperature, originally derived for stellar mass objects, to the BD regime to 〈T{sub dust}〉≈22(L{sub ∗}/L{sub ⊙}){sup 0.16} K, applicable to spectral types of M5 and later. This is slightly shallower than the relation for earlier spectral type objects and yields warmer low-mass disks. The two prescriptions cross at 0.27 L{sub ⊙}, corresponding to masses between 0.1 and 0.2 M{sub ⊙} depending on age.

79 ASTRONOMY AND ASTROPHYSICS↗

MAGIC: A Tool for Combining, Interpolating, and Processing Magnetograms

Transients in the solar coronal magnetic field are ultimately the source of space weather. Models which seek to track the evolution of the coronal field require magnetogram images to be used as boundary conditions. These magnetograms are obtained by numerous instruments with different cadences and resolutions. A tool is required which allows modelers to fmd all available data and use them to craft accurate and physically consistent boundary conditions for their models. We have developed a software tool, MAGIC (MAGnetogram Interpolation and Composition), to perform exactly this function. MAGIC can manage the acquisition of magneto gram data, cast it into a source-independent format, and then perform the necessary spatial and temporal interpolation to provide magnetic field values as requested onto model-defined grids. MAGIC has the ability to patch magneto grams from different sources together providing a more complete picture of the Sun's field than is possible from single magneto grams. In doing this, care must be taken so as not to introduce nonphysical current densities along the seam between magnetograms. We have designed a method which minimizes these spurious current densities. MAGIC also includes a number of post-processing tools which can provide additional information to models. For example, MAGIC includes an interface to the DA VE4VM tool which derives surface flow velocities from the time evolution of surface magnetic field. MAGIC has been developed as an application of the KAMELEON data formatting toolkit which has been developed by the CCMC.

Allred, Joel↗

Modeling tracers of young stellar population age in star-forming galaxies

The young stellar population of a star-forming galaxy is the primary engine driving its radiative properties. As a result, the age of a galaxy's youngest generation of stars is critical for a detailed understanding of its star formation history, stellar content, and evolutionary state. Here we present predicted equivalent widths for the Hβ, Hα, and Brγ recombination lines as a function of stellar population age. The equivalent widths are produced by the latest generations of stellar evolutionary tracks and the Starburst99 stellar population synthesis code, and are the first to fully account for the combined effects of both nebular emission and continuum absorption produced by the synthetic stellar population. Our grid of model stellar populations spans six metallicities (0.001 < Z < 0.04), two treatments of star formation history (a 10{sup 6} M {sub ☉} instantaneous burst and a continuous star formation rate of 1 M {sub ☉} yr{sup –1}), and two different treatments of initial rotation rate (v {sub rot} = 0.0v {sub crit} and 0.4v {sub crit}). We also investigate the effects of varying the initial mass function. Given constraints on galaxy metallicity, our predicted equivalent widths can be applied to observations of star-forming galaxies to approximate the age of their young stellar populations.

79 ASTRONOMY AND ASTROPHYSICS↗

UV SURFACE ENVIRONMENT OF EARTH-LIKE PLANETS ORBITING FGKM STARS THROUGH GEOLOGICAL EVOLUTION

The UV environment of a host star affects the photochemistry in the atmosphere, and ultimately the surface UV environment for terrestrial planets and therefore the conditions for the origin and evolution of life. We model the surface UV radiation environment for Earth-sized planets orbiting FGKM stars in the circumstellar Habitable Zone for Earth through its geological evolution. We explore four different types of atmospheres corresponding to an early-Earth atmosphere at 3.9 Gyr ago and three atmospheres covering the rise of oxygen to present-day levels at 2.0 Gyr ago, 0.8 Gyr ago, and modern Earth. In addition to calculating the UV flux on the surface of the planet, we model the biologically effective irradiance, using DNA damage as a proxy for biological damage. We find that a pre-biotic Earth (3.9 Gyr ago) orbiting an F0V star receives 6 times the biologically effective radiation as around the early Sun and 3520 times the modern Earth–Sun levels. A pre-biotic Earth orbiting GJ 581 (M3.5 V) receives 300 times less biologically effective radiation, about 2 times modern Earth–Sun levels. The UV fluxes calculated here provide a grid of model UV environments during the evolution of an Earth-like planet orbiting a range of stars. These models can be used as inputs into photo-biological experiments and for pre-biotic chemistry and early life evolution experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

iiasa/emissions_downscaling

This software tool, written in R, performs manipulations necessary to translate Human-Earth system model regional/sector emission outputs, such as those from PNNL's Global Change Assessment Model (GCAM), to gridded form needed by Earth System Models, such as DOEs E3SM (Energy Exascale Earth System Model) model. The tool takes as its primary input emissions in a standard community format, and produces CF-compliant netCDF gridded emission as its primary output. As intermediate output the tool produces downscaled emissions at the country level.

Feng, Leyang↗

2.1.3.404 - WEC Array Power Management and Output Simulation Tool

An array of wave energy converter (WEC) devices has variations in power output due to the chaotic nature of the waves. Eliminating or mitigating the power fluctuations is important for reducing the integration impacts of WEC plants in both distribution and transmission grids, and in standalone isolated power systems. Reduced variability of WEC-generated power in combination with energy storage or power management control at each WEC and at the array level will help increasing hosting capacity of distribution feeders for this type of variable renewable generation, and minimization of electric losses. To reduce risks and risk perception, gain key stakeholder acceptance, and enable developers to design effective and compatible energy plants with arrays of WEC devices, it requires the use of modeling tools to simulate the resource environment, device dynamics, utility power system response, as well as the development of an interface for an array controller. The project will create a publicly accessible numerical modeling framework to empower the wave energy sector to design projects of various scales (kW-100s MW), which are optimized on a plant performance basis and are compatible with different power systems and wave conditions. The framework will integrate with WEC-Sim, a wave environment model (SWAN-FUNWAVE), as well as established relevant electrical analysis tools, to model the grid system and interconnection, and optimize power output and power management for the WEC array.

POWER TRANSMISSION AND DISTRIBUTION,TIDAL AND WAVE↗

Security Analysis of Smart Grid Cyber Physical Infrastructures Using Modeling and Game Theoretic Simulation

Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.

Availability↗

Cambium Documentation: Version 2020

This is the documentation for the 2020 version of Cambium. Cambium is a tool that assembles structured data sets of simulated hourly cost and operational data for modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision-making. In this documentation, we define the metrics reported in Cambium databases and document the Cambium-specific methods for calculating those metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Accelerating Computation of the Unit Commitment Problem (Presentation)

Production cost models (PCMs) simulate power system operation at hourly (or higher) resolution. While computation times often extend into multiple days, the sequential nature of PCM's makes parallelism difficult. We exploit the persistence of unit commitment decisions to select partition boundaries for simulation horizon decomposition and parallel computation. Partitioned simulations are benchmarked against sequential solutions for optimality and computation time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mass‐Conserving Downscaling of Climate Model Precipitation Over Mountainous Terrain for Water Resource Applications

Abstract A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined.

Geology↗