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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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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

The quiet short-haul research aircraft

The design concepts, performance capabilities, and projected applications of the Quiet Short-Haul Research Aircraft (QSRA) are discussed. The propulsive lift system of the QSRA provides the lift required for short field operations at low community noise levels. This system consists of four high bipass ratio, geared turbofan engines mounted so that the engine exhaust flows across the upper surface of the wing (upper surface blowing). Large specially shaped flaps behind each engine control the direction of the flow for each phase of flight. A 95 passenger short haul transport based on this technology could operate out of a 2500 foot runway with a combined takeoff and landing 90 EPNdB footprint area of 2.7 sq mi.

Cochrane, J. A.↗
NASA NTRS2017

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.↗
NASA NTRSDate not supplied

HemoCue ISS Tech Demo - Results and Lessons Learned

During long duration space missions, astronauts experience immune system dysregulation [1], and white blood cell (WBC) count can give vital information about the body’s immune response. The ability to measure WBC count is currently an unmet need on the International Space Station (ISS) and for future exploration missions. To address this need, the Human Research Program’s (HRP) Exploration Medical Capability (ExMC) Element, along with the Research Operations and Integration (ROI) Element and the NASA Johnson Space Center Immunology Lab, flew HemoCue®, a commercial-off-the-shelf analyzer with the ability to measure whole blood WBC count with 5-part differential to ISS in December 2020.

Exploration Medical Capability↗
DOE OSTI2026

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2023

Identifying and Closing Medical Capability Gaps for Human Spaceflight Missions Beyond Low Earth Orbit

BACKGROUND: Features of human space missions beyond low Earth orbit such as increasing distance from Earth, lack of real-time communication, and limited or no evacuation or resupply capability are expected to drive an increase in medical risk and require crews to operate in an increasingly autonomous fashion. A diverse set of stakeholders at NASA are seeking to fund the development of concepts of operations, medical requirements, and medical capabilities for such missions. However, a systematic approach to identification of current medical capability gaps and a strategic framework to gap closure is needed. OVERVIEW: The Exploration Medical Integrated Product Team (XMIPT) has developed a list of nine high-level medical capability gaps and associated activities required for gap closure. The list was derived based on inputs from subject matter experts at NASA including flight surgeons, other clinical providers, as well as operational and research communities regarding medical capabilities required to support human missions to the Moon and the Mars surface. Responses were reviewed and distilled to identify common themes across capabilities. To ensure alignment with established human system risks, the gap list was further refined based on inputs from NASA’s Human System Risk Board. Relevant medical gap closure activities outside of those funded by the XMIPT were identified through solicitation of inputs from Elements of NASA’s Human Research Program (particularly Exploration Medical Capability), the broader medical operations community, and other stakeholders. This medical capability gap list is reviewed and updated regularly as new information becomes available or new stakeholders are identified. DISCUSSION: The medical capability gap list has matured to include a large group of NASA stakeholders and development activities. This has enabled articulation of priorities to funding entities and programmatic stakeholders, while serving as an accessible resource summarizing gap closure activities, relevant programmatic infusion points, and opportunities for collaboration between stakeholders. This presentation will provide an overview of the nine NASA medical capability gaps and their associated gap closure activities.

Moriah Thompson↗
NASA NTRS2011

Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model that does not contain AIRS profiles.

Kozlowski, Danielle↗
DOE OSTI2021

Absolute quantitation of propranolol from 200-μm regions of mouse brain and liver thin tissues using laser ablation-dropletProbe-mass spectrometry

Rationale: The ability to quantify drugs and metabolites in tissue with sub-mm resolution is a challenging but much needed capability in pharmaceutical research. To fill this void, a novel surface sampling approach combining laser ablation with the commercial dropletProbe automated liquid surface sampling system (LA-dropletProbe) was developed and presented here.Methods: Parylene C-coated 200 × 200 μm tissue regions of mouse brain and kidney thin tissue sections were analyzed for propranolol by laser ablation of tissue directly into a preformed liquid junction. Propranolol was detected by high performance liquid chromatography with positive ion mode electrospray ionization tandem mass spectrometry. Quantitation was achieved via application of a stable isotope-labeled internal standard and an external calibration curve.Results: Absolute concentration of propranolol determined from 200 × 200 µm tissue regions were compared to propranolol concentrations obtained from 2.3-mm-diameter tissue punches of adjacent, non-coated sections using standard bulk tissue extraction protocols followed by regular HPLC-MS/MS analysis. Average concentration of propranolol in both organs determined by the two employed methods agreed within ±12%. Furthermore, the relative abundance of phase II hydroxypropranolol glucuronide metabolites were recorded and found to be consistent with previous results.Conclusions: This work illustrates that depositing a thin parylene C layer onto thin tissue prior to analysis, which seals the surface and prevents direct liquid extraction of the drug from the tissue, coupled to the novel LA-dropletProbe surface sampling system is a viable approach for sub-mm resolution quantitative drug distribution analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Utilizing plant synthetic biology to accelerate plant-microbe interactions research

Plant-microbe interactions are critical to ecosystem resilience and substantially influence crop production. From the perspective of plant science, two important focus areas concerning plant-microbe interactions include: 1) understanding plant molecular mechanisms involved in plant-microbe interfaces and 2) engineering plants for increasing plant disease resistance or enhancing beneficial interactions with microbes to increase their resilience to biotic and abiotic stress conditions. Molecular biology and genetics approaches have been used to investigate the molecular mechanisms underlying plant responses to various beneficial and pathogenic microbes. While these approaches are valuable for elucidating the functions of individual genes and pathways, they fall short of unraveling the complex cross-talk across pathways or systems that plants employ to respond and adapt to environmental stresses. Also, genetic engineering of plants to increase disease resistance or enhance symbiosis with microbes has mainly been attempted or conducted through targeted manipulation of single genes/pathways of plants. Recent advancements in synthetic biology tool development are paving the way for multi-gene characterization and engineering in plants in relation to plant-microbe interactions. Here, we briefly summarize the current understanding of plant molecular pathways involved in plant interactions with beneficial and pathogenic microorganisms. Then, we highlight the progress in applying plant synthetic biology to elucidate the molecular basis of plant responses to microbes, enhance plant disease resistance, engineer synthetic symbiosis, and conduct in situ microbiome engineering. Lastly, we discuss the challenges, opportunities, and future directions for advancing plant-microbe interactions research using the capabilities of plant synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deep learning approaches to semantic segmentation of fatigue cracking within cyclically loaded nickel superalloy

Improvements to synchrotron-based micro-computed tomography scanning capabilities have gifted researchers the ability to characterize 4D material thermomechanical responses more thoroughly than ever before. These advancements, however, have brought about new challenges in analyzing the resulting deluge of data. We report on a nickel-based superalloy specimen imaged 26 times in-situ during cyclic loading at Argonne National Laboratory Advanced Photon Source beamline 1ID, in order to monitor crack growth within the microstructure. Therefore, several deep learning approaches which utilize convolutional neural networks are implemented to segment crack features from reconstructed tomography scans. U-Net architecture implementations are found to be especially effective, achieving IoU = 0.995 +/- 0.004 and Matthews correlation coefficient scores of Φ = 0.826 +/- 0.085. These advancements broaden possibilities for scientists seeking to automate segmentation analyses of similar large datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Long cycle and calendar life of Si-based Li-ion batteries enabled by localized high-concentration electrolytes and their surprising water tolerance

Silicon-based anodes promise an increase in energy density for Li-ion batteries, yet they suffer from a poor calendar life. Researchers have posited that fluorinated lithium salt forms reactive side products that destroy the solid electrolyte interphase (SEI), even without cycling. HF is one such reactive side product formed from trace water contamination in the electrolyte. Some electrolytes, such as localized high concentration electrolytes (LHCEs) may improve cell stability in highly reactive systems, such as Li metal and Si. In the present study, LHCEs containing 200-300 ppm of water retained up to 8% greater capacity (1200-1300 mAh/g Si) in calendar life tests over 200 days compared to dried electrolytes (< 20 ppm water). Calendar aging took place at 100% state of charge. Cells with 200-300 ppm water performed comparably to cells with 20 ppm water in cycle life tests (900-1000 mAh/g Si) . Even adding 1000 ppm water did not lead to rapid capacity fade in cells undergoing cycle life tests. Nano-FTIR spectroscopy revealed chemical and structural differences in the SEI for cells with 1000 ppm water compared to 200-300 ppm water. The SEI differences, including increased Li2O concentration, may have contributed to improved calendar life. This research reveals the capabilities of LHCEs to improve the calendar and cycle life of Si-based Li-ion batteries, despite the presence of a highly reactive contaminant.

25 ENERGY STORAGE↗
DOE OSTI2022

Machine learning with knowledge constraints for process optimization of open-air perovskite solar cell manufacturing

Perovskite photovoltaics (PV) have achieved rapid development in the past decade in terms of power conversion efficiency of small-area lab-scale devices; however, successful commercialization still requires further development of low-cost, scalable, and high-throughput manufacturing techniques. One of the critical challenges of developing a new fabrication technique is the high-dimensional parameter space for optimization, but machine learning (ML) can readily be used to accelerate perovskite PV scaling. Herein, we present an ML-guided framework of sequential learning for manufacturing process optimization. We apply our methodology to the Rapid Spray Plasma Processing (RSPP) technique for perovskite thin films in ambient conditions. With a limited experimental budget of screening 100 process conditions, we demonstrated an efficiency improvement to 18.5% as the best-in-our-lab device fabricated by RSPP, and we also experimentally found 10 unique process conditions to produce the top-performing devices of more than 17% efficiency, which is 5 times higher rate of success than the control experiments with pseudo-random Latin hypercube sampling. Our model is enabled by three innovations: (a) flexible knowledge transfer between experimental processes by incorporating data from prior experimental data as a probabilistic constraint; (b) incorporation of both subjective human observations and ML insights when selecting next experiments; (c) adaptive strategy of locating the region of interest using Bayesian optimization first, and then conducting local exploration for high-efficiency devices. Furthermore, in virtual benchmarking, our framework achieves faster improvements with limited experimental budgets than traditional design-of-experiments methods (e.g., one-variable-at-a-time sampling). This framework shows the capability of incorporating researchers’ domain knowledge into the ML-guided optimization loop; therefore, it has the potential to facilitate the wider adoption of ML in scaling to perovskite PV manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2021

Physicochemical Gas–Solid Sorption Properties of Geologic Materials Using Inverse Gas Chromatography

The goal of this study was to determine the physicochemical properties of a variety of geologic materials using inverse gas chromatography (IGC) by varying probe gas selection, temperature, carrier gas flow rate, and humidity. This is accomplished by measuring the level of interaction between the materials of interest and known probe gases. Identifying a material’s physicochemical characteristics can help provide a better understanding of the transport of gaseous compounds in different geologic materials or between different geological layers under various conditions. Our research in this study focused on measuring the enthalpy (heat) of adsorption, Henry’s constant, and diffusion coefficients of a suite of geologic materials, including two soil types (sandy clay-loam and loam), quartz sand, salt, and bentonite clay, with various particle sizes. The reproducibility of IGC measurements for geologic materials, which are inherently heterogeneous, was also assessed in comparison to the reproducibility for more homogeneous synthetic materials. This involved determining the variability of physicochemical measurements obtained from different IGC approaches, instruments, and researchers. For the investigated IGC-determined parameters, the need for standardization became apparent, including the need for application-relevant reference materials. The inherent physical and chemical heterogeneities of soil and many geologic materials can make the prediction of sorption properties difficult. Characterizing the properties of individual organic and inorganic components can help elucidate the primary factors influencing sorption interactions in more complex mixtures. This research examined the capabilities and potential challenges of characterizing the gas sorption properties of geologic materials using IGC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Operando Electrochemical Liquid-Cell Scanning Transmission Electron Microscopy (EC-STEM) Studies of Evolving Cu Nanocatalysts for CO 2 Electroreduction

The design and synthesis of nanocatalysts with well-defined sizes, compositions, and structures have revolutionized our accessibility to tunable catalyst activity and selectivity for a variety of energy-related electrochemical reactions. Nonetheless, establishing structure-(re)activity correlations requires the understanding of the dynamic evolution of pristine nanocatalysts and the identification of their active states under operating conditions. We previously communicated the operando observation of Cu nanocatalysts evolving into active metallic Cu nanograins for CO 2 electroreduction (Yang et al. Nature 2023, 614, 262–269). Here, we expand our discussion to the technical capabilities and further research applications of operando electrochemical liquid-cell scanning transmission electron microscopy (EC-STEM), which enables quantitative electrochemistry while tracking dynamic structural evolution of sub-10 nm Cu nanocatalysts. The coexistent H 2 bubbles, often disruptive to operando spectroscopy, are an effective approach to create a thin-liquid layer that significantly improves spatial resolution while remaining electrochemically accessible to Cu nanocatalysts. Operando four-dimensional (4D) STEM in liquids provides insights into the complex structure of active polycrystalline metallic Cu nanograins. With continuous technical developments, we anticipate that operando EC-STEM will evolve into a powerful electroanalytical method to advance our understanding of a variety of nanoscale electrocatalysts at solid/liquid interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control

Abstract Algal cultivations are strongly influenced by light and dark cycles. In this study, genome-scale metabolic models were applied to optimize nutrient supply during alternating light and dark cycles of Chlorella vulgaris . This approach lowered the glucose requirement by 75% and nitrate requirement by 23%, respectively, while maintaining high final biomass densities that were more than 80% of glucose-fed heterotrophic culture. Furthermore, by strictly controlling glucose feeding during the alternating cycles based on model-input, yields of biomass, lutein, and fatty acids per gram of glucose were more than threefold higher with cycling compared to heterotrophic cultivation. Next, the model was incorporated into open-loop and closed-loop control systems and compared with traditional fed-batch systems. Closed-loop systems which incorporated a feed-optimizing algorithm increased biomass yield on glucose more than twofold compared to standard fed-batch cultures for cycling cultures. Finally, the performance was compared to conventional proportional-integral-derivative (PID) controllers. Both simulation and experimental results exhibited superior performance for genome-scale model process control (GMPC) compared to traditional PID systems, reducing the overall measured value and setpoint error by 80% over 8 h. Overall, this approach provides researchers with the capability to enhance nutrient utilization and productivity of cell factories systematically by combining genome-scale models and controllers into an integrated platform with superior performance to conventional fed-batch and PID methodologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Population inversion X-ray laser oscillator

Oscillators are at the heart of optical lasers, providing stable, transform-limited pulses. Until now, laser oscillators have been available only in the infrared to visible and near-ultraviolet (UV) spectral region. In this paper, we present a study of an oscillator operating in the 5- to 12-keV photon-energy range. We show that, using the Kα 1 line of transition metal compounds as the gain medium, an X-ray free-electron laser as a periodic pump, and a Bragg crystal optical cavity, it is possible to build X-ray oscillators producing intense, fully coherent, transform-limited pulses. As an example, we consider the case of a copper nitrate gain medium generating ~ 5 × 10 10 photons per pulse with 37-fs pulse length and 48-meV spectral resolution at 8-keV photon energy. Our theoretical study and simulation of this system show that, because of the very large gain per pass, the oscillator saturates and reaches full coherence in four to six optical-cavity transits. We discuss the feasibility and design of the X-ray optical cavity and other parts of the oscillator needed for its realization, opening the way to extend X-ray–based research beyond current capabilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A design of resonant inelastic X-ray scattering (RIXS) spectrometer for spatial- and time-resolved spectroscopy

The optical design of a Hettrick–Underwood-style soft X-ray spectrometer with Wolter type 1 mirrors is presented. The spectrometer with a nominal length of 3.1 m can achieve a high resolving power (resolving power higher than 10000) in the soft X-ray regime when a small source beam (<3 µm in the grating dispersion direction) and small pixel detector (5 µm effective pixel size) are used. Adding Wolter mirrors to the spectrometer before its dispersive elements can realize the spatial imaging capability, which finds applications in the spectroscopic studies of spatially dependent electronic structures in tandem catalysts, heterostructures, etc . In the pump–probe experiments where the pump beam perturbs the materials followed by the time-delayed probe beam to reveal the transient evolution of electronic structures, the imaging capability of the Wolter mirrors can offer the pixel-equivalent femtosecond time delay between the pump and probe beams when their wavefronts are not collinear. In combination with some special sample handing systems, such as liquid jets and droplets, the imaging capability can also be used to study the time-dependent electronic structure of chemical transformation spanning multiple time domains from microseconds to nanoseconds. The proposed Wolter mirrors can also be adopted to the existing soft X-ray spectrometers that use the Hettrick–Underwood optical scheme, expanding their capabilities in materials research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Integrated Modeling and Optimal Operation of Multi-Energy System for Coastal Community

Focusing on remote, isolated, and underserved communities, a multi-energy system is designed in this research which is capable of utilizing different energy sources in a more coordinated and energy-efficient way to support various demands, such as fresh water, electricity, hydrogen, thermal demand, etc. The energy sources considered are renewables (wind, solar, marine) and natural gas. The energy conversion process includes water desalination, gas combustion, water electrolyzation, and different types of storage (hydrogen tank, electricity, thermal, etc.) are designed to serve as buffers in supply-demand balancing. Sets of experiments are designed to demonstrate the effectiveness of the proposed operating model and investigate the impact of uncertainties from renewable generations and demands.

Chen, Yang↗
DOE OSTI2023

ExoToComsol v.0.1

SAND2024-08641O ExoToComsol models capability-sharing. For example, the software can develop a multiphysics modeling chain using physics modeling capabilities from different research institutions using either SIERRA or COMSOL. The converter program allows exporting user-defined, region-of-interest from a large FE model, which results in a finer mesh of the submodel that can be used for subsequent analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rahman, Farhan↗