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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Bounding the states of systems with unknown-but-bounded disturbances

Control systems with hard constraints on certain variables are characterized, in an analytical review of recent investigations based on an unknown-but-bounded description of magnitude uncertainties. Hard-constraint problems typically arise in the design of controllers for potentially hazardous systems such as nuclear power plants. Consideration is given to norm bounds based on matrix measures, extensions of Schweppe's (1968) ellipsoid bounds, and set-theoretic regulator design. The performance of these approaches is evaluated by means of numerical simulations involving a third-order nonlinear steam-boiler model; the results are presented in graphs, and it is found that ellipsoid bounds are tightest in the general case, but that box bounds are even tighter for linear systems with Metzler system matrices.

Tsai, Wei K.↗
NASA NTRS1993

Visual and somesthetic influences on postural orientation in the median plane

We investigated optic and somesthetic contributions to perceived body orientation in the pitch dimension. In a within-subject factorial design, each of 12 subjects attempted to set his/her body erect or 45 degrees back from erect while restrained in a movable bed surrounded by an adjustable box. The box provided a visual environment consisting of either a grid pattern, two luminous lines, or complete darkness. Both the grid pattern and the luminous lines were effective at biasing settings of body position when the box was pitched; the pitched grid was more effective than the pitched lines. Although the pitch of the box influenced orientation to both goals, the effect was greater for the diagonal goal than for the erect goal. We present a model of postural orientation in the median plane that involves vestibular, somatosensory, and visual inputs.

Nemire, K.↗
NASA NTRS1993

Large eddy simulation and direct numerical simulation of high speed turbulent reacting flows

The objective of this research is to make use of Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for the computational analyses of high speed reacting flows. Our efforts in the first phase of this research conducted within the past three years have been directed in several issues pertaining to intricate physics of turbulent reacting flows. In our previous 5 semi-annual reports submitted to NASA LaRC, as well as several technical papers in archival journals, the results of our investigations have been fully described. In this progress report which is different in format as compared to our previous documents, we focus only on the issue of LES. The reason for doing so is that LES is the primary issue of interest to our Technical Monitor and that our other findings were needed to support the activities conducted under this prime issue. The outcomes of our related investigations, nevertheless, are included in the appendices accompanying this report. The relevance of the materials in these appendices are, therefore, discussed only briefly within the body of the report. Here, results are presented of a priori and a posterior analyses for validity assessments of assumed Probability Density Function (PDF) methods as potential subgrid scale (SGS) closures for LES of turbulent reacting flows. Simple non-premixed reacting systems involving an isothermal reaction of the type A + B yields Products under both chemical equilibrium and non-equilibrium conditions are considered. A priori analyses are conducted of a homogeneous box flow, and a spatially developing planar mixing layer to investigate the performance of the Pearson Family of PDF's as SGS models. A posteriori analyses are conducted of the mixing layer using a hybrid one-equation Smagorinsky/PDF SGS closure. The Smagorinsky closure augmented by the solution of the subgrid turbulent kinetic energy (TKE) equation is employed to account for hydrodynamic fluctuations, and the PDF is employed for modeling the effects of scalar fluctuations. The implementation of the model requires the knowledge of the local values of the first two SGS moments. These are provided by additional modeled transport equations. In both a priori and a posteriori analyses, the predicted results are appraised by comparison with subgrid averaged results generated by DNS. Based on these results, the paths to be followed in future investigations are identified.

Adumitroaie, V.↗
NASA NTRS2024

Orbital Debris Quarterly News, October 2024

- Three New On-orbit Fragmentations - NASA’s ODPO Wins Software of the Year Award - Aerodynamic Demise Model for Carbon Fiber Polymer Fiber - DebriSat: 10 years and Growing - Meeting Reports - Upcoming Meetings - NASA ODPO Abstracts - Space Missions, and Satellite Box Score

Heather Cowardin↗
DOE OSTI2021

Designing for Supply and Return Air System Interaction in Residential Buildings

Standard practice for HVAC return design has evolved from running a dedicated return to each room with a supply, to systems with returns in more centrally located areas of the home with jump ducts, transfer grilles, or simply door undercuts used as return air pathways from isolated rooms . In these latter systems, hallways and stairwells act as large open ducts for conveying air back to a single (or sometimes multiple) central return. When partition doors to an isolated room are closed, the return airflow resistance goes up, significantly impacting airflow balance if an adequate relief pathway is not installed. Airflow imbalances can lead to comfort and building durability issues and increased envelope leakage. To combat this, some jurisdictions have requirements for return air pathways. The supply system topology – or layout - impacts the airflow balance stability in response to adjustments of return pathway resistances. Branching supply topologies typically have reduced static pressure after each split. The static pressure at the final split will be lower than the primary supply plenum. Because of this, if there is a restriction in a room’s return path, supply airflow will tend to redistribute to adjacent ducts at the end of the branch. A properly designed trunk and branch supply system can effectively equalize static pressure by reducing the cross sectional area after each takeoff . Maintaining static pressure within the trunk will reduce the system’s sensitivity to changes in return paths. However, in practice, it is difficult to design and time consuming to install a complex supply plenum. Velocity effects and poor takeoff placement also impact airflow balance. This fact sheet considers return systems in three main categories: distributed, with a return duct to each room; multiple central, with one return grille on each floor of a home; and single central, with a single return grille located near the air handling unit. Three supply categories are also considered: radial splitter box, trunk and branch, and home-run with all ducts connecting directly to a central manifold. A complete description of the modeling work and results can be found in the companion technical report.

buildings↗
NASA NTRS2019

Design of an Automated Ultrasonic Scanning System for In-Situ Composite Cure Monitoring and Defect Detection

The preliminary design and development of an automated ultrasonic scanning system for in-situ composite cure monitoring and defect detection in the high temperature environment of an oven was completed. This preliminary design is a stepping stone to deployment in the high temperature and high pressure environment of an autoclave, the primary cure method of aerospace grade thermoset composites. Cure monitoring with real-time defect detection during the process could determine when defects form and how they move. In addition, real-time defect detection during cure could assist validating physics-based process models for predicting defects at all stages of the cure cycle. A physics-based process model for predicting porosity and fiber waviness originating during cure is currently under development by the NASA Advanced Composites Project (ACP). For the design, an ultrasonic contact scanner is enclosed in an insulating box that is placed inside an oven during cure. Throughout the cure cycle, the box is nitrogen-cooled to approximately room temperature to maintain a standard operating environment for the scanner. The composite part is mounted on the outside of the box in a vacuum bag on the build/tool plate. The build plate is attached to the bottom surface of the box. The scanner inspects the composite panel through the build plate, tracking the movement of defects introduced during layup and searching for new defects that may form during cure. The focus of this paper is the evaluation and selection of the build plate material and thickness. The selection was based on the required operating temperature of the scanner, the cure temperature of the composite material, thermal conductivity models of the candidate build plates, and a series of ultrasonic attenuation tests. This analysis led to the determination that a 63.5 mm thick build plate of borosilicate glass would be utilized for the system. The borosilicate glass plate was selected as the build plate material due to the low ultrasonic attenuation it demonstrated, its ability to efficiently insulate the scanner while supporting an elevated temperature on the part side of the plate, and the availability of a 63.5 mm thick plate without the need for lamination.

Hudson, Tyler B.↗
NASA NTRS2007

Algorithm Plans Collision-Free Path for Robotic Manipulator

An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps between the corresponding OBB and OBP models. For computational efficiency, the process is started at the coarsest resolution and stopped as soon as possible, preferably before reaching the finest resolution. At the coarsest resolution, there is a single OBB enclosing all relevant external objects and a single OBB enclosing the entire robot. At the next finer level of resolution, the coarsest-resolution OBB is divided into two OBBs, and so forth. If no collision is detected at the coarsest resolution, then there is no need for further computation to detect collisions. If a collision is detected at the coarsest resolution, then tests for collisions are performed at the next finer level of resolution. This process is continued to successively finer resolutions until either no more collisions are detected or the finest resolution is reached.

Backes, Paul↗
NASA NTRS1990

Estimation of area-averaged rainfall over tropical oceans from microwave radiometry - A single channel approach

This paper presents a new simple retrieval algorithm for estimating area-time averaged rain rates over tropical oceans by using single channel microwave measurements from satellites. The algorithm was tested by using the Nimbus-5 Electrically Scanning Microwave Radiometer and a simple microwave radiative transfer model to retrieve seasonal 5-deg x 5-deg area averaged rainrate over the tropical Atlantic and Pacific from December 1973 to November 1974. The brightness temperatures were collected and analyzed into histograms for each season and in each grid box from December 1973 to November 1974. The histograms suggest a normal distribution of background noise plus a skewed rain distribution at the higher brightness temperatures. By using a statistical estimation procedure based upon normally distributed background noise, the rain distribution was separated from the raw histogram. The radiative transfer model was applied to the rain-only distribution to retrieve area-time averaged rainrates throughout the tropics. Despite limitations of single channel information, the retrieved seasonal rain rates agree well in the open ocean with expectations based upon previous estimates of tropical rainfall over the oceans.

Shin, Kyung-Sup↗
DOE OSTI2024

Probabilistic neural networks for improved analyses with phenomenological R -matrix

Here we present a method for measurement analyses based on probabilistic deep neural networks that provide several advantages over conventional analyses with phenomenological models. These include predicting physical quantities directly from data, the rapid generation of statistically robust uncertainties, and the ability to bypass some parameters that may induce ambiguities and complications in data analysis. As deep learning methods make predictions through “black boxes,” the uncertainty quantification is typically challenging. We use a probabilistic framework that provides thorough uncertainty quantification and is straightforward to follow in practice. With the network architecture based on the Transformer, we demonstrate the current method for predicting nuclear resonance parameters from scattering data using the phenomenological R-matrix model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Systematic Process Intensification involving Zeotropic Distillation

Distillation is commonly used for separating homogeneous fluid mixtures. While it is based on a simple thermally driven vapor-liquid equilibrium phenomenon at the two-phase region, different variants of distillation systems exist. These include simple distillation, dividing wall columns, pressure swing distillation, thermally coupled distillation and reactive distillation. Complex separation may also involve multiple distillation in a sequence to achieve the desired products. These sequences can be constructed as direct sequence, indirect sequence or thermally coupled columns. Even when a sequence is fixed, each column in the sequence can have a plethora of design alternatives to consider. All these make the design and intensification of distillation systems a challenging task. The large number of plausible design alternatives increases the combinatorial complexity for screening. Although significant efforts have been made in the past, we still lack a method for systematic identification of novel pathways for process intensification of distillation system. This is due to the lack of a generalized representation of all plausible alternatives in a single modeling and optimization framework. In this work, we first present a general representation of thermally driven vapor-equilibrium phenomenon using abstract building blocks. Specifically, each tray in a distillation column is represented by a liquid block and a vapor block with a shared semi-restricted boundary representing the interface. The arrangement of these building blocks in a two-dimensional grid gives rise to all plausible variants of distillation systems. These systems range from simple distillation, dividing wall columns to task-integrated columns. This enables us to systematically identify both classic and out-of-the-box intensified designs at the column and flowsheet levels. The overall distillation-based separation process synthesis problem is formulated as a single mixed-integer nonlinear programming (MINLP) model. In conclusion, the proposed approach is applied to multi-component zeotropic systems to show the capability of identifying promising intensified alternatives.

42 ENGINEERING↗
NASA NTRS2003

Analysis and Test Correlation of Proof of Concept Box for Blended Wing Body-Low Speed Vehicle

The Low Speed Vehicle (LSV) is a 14.2% scale remotely piloted vehicle of the revolutionary Blended Wing Body concept. The design of the LSV includes an all composite airframe. Due to internal manufacturing capability restrictions, room temperature layups were necessary. An extensive materials testing and manufacturing process development effort was underwent to establish a process that would achieve the high modulus/low weight properties required to meet the design requirements. The analysis process involved a loads development effort that incorporated aero loads to determine internal forces that could be applied to a traditional FEM of the vehicle and to conduct detailed component analyses. A new tool, Hypersizer, was added to the design process to address various composite failure modes and to optimize the skin panel thickness of the upper and lower skins for the vehicle. The analysis required an iterative approach as material properties were continually changing. As a part of the material characterization effort, test articles, including a proof of concept wing box and a full-scale wing, were fabricated. The proof of concept box was fabricated based on very preliminary material studies and tested in bending, torsion, and shear. The box was then tested to failure under shear. The proof of concept box was also analyzed using Nastran and Hypersizer. The results of both analyses were scaled to determine the predicted failure load. The test results were compared to both the Nastran and Hypersizer analytical predictions. The actual failure occurred at 899 lbs. The failure was predicted at 1167 lbs based on the Nastran analysis. The Hypersizer analysis predicted a lower failure load of 960 lbs. The Nastran analysis alone was not sufficient to predict the failure load because it does not identify local composite failure modes. This analysis has traditionally been done using closed form solutions. Although Hypersizer is typically used as an optimizer for the design process, the failure prediction was used to help gain acceptance and confidence in this new tool. The correlated models and process were to be used to analyze the full BWB-LSV airframe design. The analysis and correlation with test results of the proof of concept box is presented here, including the comparison of the Nastran and Hypersizer results.

Spellman, Regina L.↗
DOE OSTI2026

Gradient-informed Hamiltonian Monte Carlo for multicomponent CALPHAD model optimization and uncertainty quantification

CALPHAD model parameter optimization is inherently challenging due to non-smooth objective functions, high-dimensional parameter spaces, and the need for uncertainty quantification (UQ). Traditional weighted nonlinear least squares approaches are computationally efficient but local, whereas black-box global optimizers and ensemble Markov Chain Monte Carlo (MCMC) methods provide broader exploration at substantial computational cost. The objective of this work is to combine the global exploration capability of gradient-informed Hamiltonian Monte Carlo – specifically the No-U-Turn Sampler (NUTS) – with local deterministic refinement using BFGS to efficiently optimize multicomponent CALPHAD models with minimal manual intervention. Analytic gradients are computed via the Jansson derivative framework. The methodology is demonstrated on the Cr—Fe binary system and extended to the Cr—Fe—Ni ternary system with 32 degrees of freedom. For Cr—Fe, NUTS achieves comparable or superior optimality relative to ensemble MCMC while requiring over an order-of-magnitude fewer likelihood evaluations. Parameter uncertainties are quantified through NUTS sampling and propagated to thermodynamic observables using local expansion, demonstrating a novel modular approach that combines binary and ternary parameter subsets without requiring global relaxation. These results establish gradient-informed exploration as a scalable strategy for multicomponent CALPHAD optimization and provide a practical route towards efficient higher-order database development with quantified uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Exploring Gradient-Based Multi-directional Controls in GANs

Generative Adversarial Networks (GANs) have been widely applied in modeling diverse image distributions. However, despite its impressive applications, the structure of the latent space in GANs largely remains as a black-box, leaving its controllable generation an open problem, especially when spurious correlations between different semantic attributes exist in the image distributions. To address this problem, previous methods typically learn linear directions or individual channels that control semantic attributes in the image space. However, they often suffer from imperfect disentanglement, or are unable to obtain multi-directional controls. Furthermore, in this work, in light of the above challenges, we propose a novel approach that discovers nonlinear controls, which enables multi-directional manipulation as well as effective disentanglement, based on gradient information in the learned GAN latent space. More specifically, we first learn interpolation directions by following the gradients from classification networks trained separately on the attributes, and then navigate the latent space by exclusively controlling channels activated for the target attribute in the learned directions. Empirically, with small training data, our approach is able to gain fine-grained controls over a diverse set of bi-directional and multi-directional attributes, and we showcase its ability to achieve disentanglement significantly better than state-of-the-art methods both qualitatively and quantitatively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

In this paper, we developed a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of multiphase computational fluid dynamics (MCFD) simulations for bubbly flows. The proposed approach is supported by high-resolution two-phase flow measurements, including those by double-sensor conductivity probes, high-speed imaging, and particle image velocimetry. Local distributions of key physical quantities of interest (QoIs), including the void fraction and phasic velocities, are obtained to support the Bayesian inference. In the process, the epistemic uncertainties of the closure relations are inversely quantified while the aleatory uncertainties from stochastic fluctuations of the system are evaluated based on experimental uncertainty analysis. The combined uncertainties are then propagated through the MCFD solver to obtain uncertainties of the QoIs, based on which probability-boxes are constructed for validation. The proposed approach relies on three machine learning methods: feedforward neural networks and principal component analysis for surrogate modeling, and Gaussian processes for model form uncertainty modeling. The whole process is implemented within the framework of an open-source deep learning library PyTorch with graphics processing unit (GPU) acceleration, thus ensuring the efficiency of the computation. The results demonstrate that with the support of high-resolution data, the uncertainties of MCFD simulations can be significantly reduced. The proposed approach has the potential for other applications that involve numerical models with empirical parameters.

42 ENGINEERING↗
DOE OSTI2021

Protoplanetary Disk Rings as Sites for Planetesimal Formation

Axisymmetric dust rings are a ubiquitous feature of young protoplanetary disks. These rings are likely caused by pressure bumps in the gas profile; a small bump can induce a traffic-jam-like pattern in the dust density, while a large bump may halt radial dust drift entirely. The resulting increase in dust concentration may trigger planetesimal formation by the streaming instability (SI), as the SI itself requires some initial concentration of dust. Here we present the first 3D simulations of planetesimal formation in the presence of a pressure bump modeled specifically after those seen by Atacama Large Millimeter/submillimeter Array. We place a pressure bump at the center of a large 3D shearing box, along with an initial solid-to-gas ratio of Z = 0.01, and we include both particle back-reaction and particle self-gravity. We consider millimeter-sized and centimeter-sized particles separately. For simulations with centimeter-sized particles, we find that even a small pressure bump leads to the formation of planetesimals via the SI; a pressure bump does not need to fully halt radial particle drift for the SI to become efficient. Furthermore, pure gravitational collapse via concentration in pressure bumps (such as would occur at sufficiently high concentrations and without the SI) is not responsible for planetesimal formation. For millimeter-sized particles, we find tentative evidence that planetesimal formation does not occur. If this result is confirmed at higher resolution, it could put strong constraints on where planetesimals can form. Ultimately, our results show that for centimeter-sized particles planetesimal formation in pressure bumps is extremely robust.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1984

Finite-amplitude models of convection in the early mantle

Models of finite-amplitude, time-dependent mantle convection at Reynolds number ten million are calculated. The models are based on the Boussinesq approximation for convection at infinite Prandtl number and treat convection in a two-dimensional, Cartesian coordinate box with an aspect ratio of 1.4. The initial conditions consist of a static fluid with a purely conductive temperature profile, while the boundary conditions are taken to be free slip, with impenetrable insulating side walls. The initial conditions are found to result in an initial burst of convection that reverses the horizontally averaged temperature gradient, making the middle layers stable with respect to convection. With bottom heating and cooling of the top, two distinct layers of convective cells occur; with top cooling only, the upper layer alone convects.

Boss, A. P.↗
NASA NTRS1997

Demonstration of Oxygen and Carbon Monoxide Propellants for Mars Missions

Currently, proposed planetary exploration missions must be small, with low costs and a short development time. Relatively high-risk technologies are being accepted for such missions if they meet these guidelines. For a Mars sample-return mission, one of the higher risk technologies is the use of return propellants produced from indigenous materials such as the Martian atmosphere. This consists of 96 percent carbon dioxide, which can be processed into oxygen and carbon monoxide. This year, the NASA Lewis Research Center completed the experimental evaluation and subscale technology development of an oxygen/carbon monoxide propellant combination. Previous research included ignition characterization, combustion performance, and heat transfer characterization with gaseous propellants at room temperature. In this year s tests, we studied the ignition characteristics and combustion of oxygen and carbon monoxide at near liquid temperatures. The mixture ratio boundaries for oxygen and carbon monoxide were determined as a function of propellant temperature in a spark torch igniter. With both propellants at room temperature, the ignition range was between 0.50 and 1.44; and with both propellants chilled to near-liquid temperatures, it was between 2.4 and 3.1. Statistical analysis of the mean value of the ignition boundaries provided models that describe the combination of oxygen temperature, carbon monoxide temperature, and mixture ratio that resulted in ignition. This range is the larger boxed area shown in the figure. The smaller boxed area indicates the range at which there is a 90-percent confidence that ignition will occur. The relatively small range at only 90-percent confidence indicates that using the oxygen/carbon monoxide combination as its own ignition source may not be the best design for a remote engine operating on Mars. Tests also were performed in a simulated small rocket engine that used oxygen/hydrogen combustion gases as the ignition source for oxygen/carbon monoxide. In these experiments, the oxygen/carbon monoxide was successfully ignited in eight of eight tests at a mixture ratio of 0.52. In addition, the oxygen/carbon monoxide maintained steady combustion after the oxygen/hydrogen ignition source was removed, verifying that the oxygen/carbon monoxide rocket engine should continue to be included in mission plans as return propulsion from Mars.

Linne, Diane L.↗
DOE OSTI2025

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↗