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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Computational Modeling of Photovoltaic Mini-Modules Undergoing Accelerated Stress Testing

A finite element model of a four-cell photovoltaic mini-module was developed and compared to experimental results from an accelerated stress test protocol in order to validate that computational models can accurately represent their physical counterparts when subjected to mechanical loading and to assess mini-module representativeness against full scale photovoltaic modules. Deflected shapes across the simulated mini-modules were compared to measured mini-module shapes when subjected to various pressure loads. Displaced mini-module shape results constrained to the experimental protocols of 0.4 mm and 1.1 mm of displacement at the mini-module center were compared to experimental results of full-size modules subjected to module qualification test load levels of 1.0 kPa and 2.4 kPa, to assess if the bending of mini-modules was representative of full-sized modules under the load. Temperature cycling was incorporated into the model to simulate the impacts of stress due to thermal expansion of the backsheet and cells. A preliminary uncertainty analysis was performed to show how variations in material properties and geometric parameters change the simulation results.

computational modeling↗
DOE OSTI2025

Cooling outweighs warming across phenological transitions in the Northern Hemisphere

Vegetation phenology, i.e., seasonal biological events such as leaf-out and leaf-fall, regulates local climate through biophysical processes like evapotranspiration (ET) and albedo. However, the net surface temperature impact of these processes—whether ET cooling or albedo-induced warming predominates—and how the dominance changes across phenological transitions and regions remains poorly understood. Here, we investigated the effects of vegetation foliage on daytime land surface temperature (LST) following six phenological transitions, spanning from the start of season to end of season, in deciduous and mixed forests across the mid- to high-latitude Northern Hemisphere during 2013–2021 using multiple satellite products and ground observations. We quantified vegetation effect as the difference between observed LST and LST estimates from the Annual Temperature Cycle (ATC) model, representing a no-foliage scenario. We found that vegetation-induced cooling consistently outweighs warming following all phenological transitions except for the end of the season. Cooling intensity increased with vegetation greenness, ranging from 1.0 ± 0.5 °C (mean ± 0.15 SD) in 59% of forests after the start of the season (SOS) to 6.1 ± 0.8 °C in 89% of forests following the onset of maturity, before declining toward the end of the season. Over half of the regions experiencing cooling showed intensification of surface cooling with climate warming, suggesting an amplified vegetation-mediated cooling under future climate change. The findings provide a more precise understanding of the role of vegetation in modulating climate at the intraseasonal scale, highlighting the importance of integrating phenological impacts into climate adaptation strategies and Earth system modeling.

albedo↗
DOE OSTI2021

Techno-economic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

A techno-economic analysis is underway examining the cost and performance of future large-scale photovoltaic (PV) plant components, including bifacial modules, tandem modules, increased plant voltage architectures, and module-level power electronics. Integration of these components into PV plant designs is compared with current PV technologies based on levelized cost of electricity (LCOE). Baseline models are developed and validated against recorded PV plant performance data. Expected cost and performance data of future PV technologies are incorporated into the baseline models. An evolutionary algorithm is utilized to optimize PV plant configuration, technology combination, and LCOE. This paper focuses on the bifacial module analysis.

14 SOLAR ENERGY↗
DOE OSTI2021

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. Furthermore, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Technoeconomic Analysis of High-Value, Crystalline Silicon Photovoltaic Module Recycling Processes

Recycling is an important circular economy strategy, and for photovoltaics (PV), the one that has received the greatest research attention. Recycling of PV modules is required in Europe; everywhere else it competes in the market of end-of-life options, where cost is a primary decision factor. The vast majority of PV modules sold globally are crystalline-silicon (c-Si); most of the rest of the market are cadmium telluride thin film modules whose primary manufacturer runs its own commercial-scale recycling program. While many different c-Si recycling approaches and technologies have been proposed, they generally lack accompanying cost estimates or enough process information to model costs. Herein we develop detailed estimates of seven categories of capital and operating costs along with estimates of revenue from recovered materials for each step in two proposed recycling processes for c-Si PV modules. Using these results, we develop a hypothetical third recycling process merging process steps from the original two, estimate surcharges required to achieve minimum sustainable prices for each recycling process, as well as consider how economies of scale could reduce costs. Increasing the purity of and identifying higher-value markets for recovered materials are approaches to reducing costs and increasing recycling rates in voluntary markets.

crystalline silicon↗
DOE OSTI2022

Dynamic Material Flow Analysis of Silicon Photovoltaic Modules to Support a Circular Economy Transition

Solar photovoltaics (PV) are the fastest growing renewable energy technologies for clean, cheap, and sustainable electricity generation. To prepare for rapid scale-up, the PV industry needs to project material requirements to build out all aspects of the supply chain appropriately and plan to handle large volumes of module waste. Impacts of deploying different material circularity strategies to reduce waste and conserve primary resources need to be quantified to inform sustainable material management. Here, we introduce the photovoltaic dynamic material flow analysis (PV DMFA) model based on PV electricity generation. The model quantifies material flows and stocks in the cradle-to-cradle life cycles of utility-scale c-Si PV systems in the United States through 2100. We present case studies for solar flat glass and aluminum frame materials under various scenarios to project the impacts of PV performance, reliability, and processing parameters, material circularity strategies, and module design shifts. In the absence of circularity measures, ~100 million MT of flat glass and ~12 million MT of aluminum would be needed for PV installations by 2100 to meet projected growth in domestic utility PV demand to nearly 1000 TWh in 2100. With optimistic but feasible improvements in efficiency, reliability, and circularity, material intensity and waste could be reduced by nearly 50%. Efficient module collection, minimally intrusive recycling, and careful scrap handling and cleaning could improve material circularity in the PV value chain. This model serves as a sustainability data support tool that may aid in the circular economy transition for PV systems.

circular economy↗
DOE OSTI2026

Entity—Hardware-agnostic Particle-in-cell Code for Plasma Astrophysics. I. Curvilinear Special Relativistic Module

Entity is a new-generation, fully open-source particle-in-cell (PIC) code developed to overcome key limitations in astrophysical plasma modeling, particularly the extreme separation of scales and the performance challenges associated with evolving, GPU-centric computing infrastructures. It achieves hardware-agnostic performance portability across various GPU and CPU architectures using the Kokkos library. Crucially, Entity maintains a high standard for usability, clarity, and customizability, offering a robust and easy-to-use framework for developing new algorithms and grid geometries, which allows extensive control without requiring edits to the core source code. This paper details the core general-coordinate special relativistic module. Entity is the first PIC code designed to solve the Vlasov–Maxwell system in general coordinates, enabling a coordinate-agnostic framework that provides the foundational structure for straightforward extension to arbitrary coordinate geometries. The core methodology achieves numerical stability by solving particle equations of motion in the global orthonormal Cartesian basis, despite using generalized coordinates like Cartesian, axisymmetric spherical, and quasi-spherical grids. Charge conservation is ensured via a specialized current deposition technique using conformal currents. The code exhibits robust scalability and performance portability on major GPU platforms (AMD MI250X, NVIDIA A100, and Intel Max Series), with the 3D particle pusher and the current deposition operating efficiently at about 2 ns per particle per time step. Functionality is validated through a comprehensive suite of standard Cartesian plasma tests and the accurate modeling of relativistic magnetospheres in curvilinear axisymmetric geometries.

Hakobyan, Hayk [Flatiron Institute, New York, NY (↗
DOE OSTI2024

Membrane-based carbon capture process optimization using CFD modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗
DOE OSTI2024

Membrane-based Carbon Capture Process Optimization using CFD Modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity re-quires a multi-stage membrane process, where the optimal network configuration of the mem-brane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules.

Pedrozo, Hector A.↗
DOE OSTI2025

Unsteady aerodynamics of large-scale floating offshore wind turbines in surge motion

Unsteady aerodynamic loads significantly influence the design and wake flow field of floating offshore wind turbines, especially due to wave- or vibration-induced tower top motions triggering various unsteady phenomena. Recent studies show that increasing turbine sizes amplify unsteady aerodynamic effects, as their impact typically grows with rotor diameter. This work combines recent findings from experiments and simulations on model-scale FOWT aerodynamics with new numerical analyses of large-scale rotors, providing a comprehensive understanding of unsteady phenomena occurrence and impact. Numerical analyses of the IEA 15-MW and 22-MW rotors undergoing surge motions characterise the combined influence of motion-induced unsteady phenomena on rotor thrust. Results indicate that unsteady effects can reduce thrust force variations by up to 40% at realistic surge periods. These findings contrast with prior model-scale rotor investigations, attributed to the specialised design of the model rotors. Comparisons between numerical methods - the dynamic blade element momentum method in OpenFAST and free vortex wake modules in panMARE and OpenFAST - reveal persistent differences in thrust predictions under both idealised and realistic conditions. This highlights that classical blade element momentum approaches require enhancement to accurately capture unsteady loads on large-scale floating offshore wind turbines at low wind speeds.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Quantifying pH buffering capacity in acidic, organic-rich Arctic soils: Measurable proxies and implications for soil carbon degradation

Dynamic pH change promoted by biogeochemical reactions in Arctic tundra soils can be a major control on the production and release of CO 2 and CH 4 , which contribute to rising global temperatures. Large quantities of soil organic matter (SOM) in these soils are susceptible to microbial decomposition, leading to pH changes during permafrost thaw. Soil pH buffering capacity (β) modulates the extent of pH change but has not been thoroughly studied and represented in predictive ecosystem scale biogeochemical models in Arctic tundra soils. In this study, we generated titration curves for 21 acidic tundra soils from three Arctic sites across northern Alaska, United States of America. Geochemical and hydrological soil properties were evaluated, and correlations with β were developed. Strong correlations between β and both gravimetric water content (Θ g ) (R 2 = 0.847, p < 0.001) and soil water retention (SWR) (R 2 = 0.849, p = 0.001) indicate that the ability of soil to retain water could be associated with its buffering properties. Correlations between β and soil organic carbon (SOC) and cation exchange capacity (CEC) were also explored, and relationships to SWR are discussed. These correlations were then used with existing soil databases reporting SOC, CEC, and SWR to estimate β across Alaska soils. We further demonstrated the quantitative relationships between β and the simulated rates of biogeochemical reactions and show that lower β leads to higher soil pH and more CH 4 production. Overall, our study provides simple proxies for β in Arctic soils and highlights the importance and implications of representing soil buffering in predictive models, thereby enabling quantitative coupling between pH dynamics associated with biogeochemical reactions. Integrating β into predictive models of Arctic biogeochemical cycling may reduce model uncertainty and further our understanding of permafrost SOM degradation accelerated by warming.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

SAM Enhancements and Model Developments for Molten-Salt-Fueled Reactors

To support the development and utilization of the SAM code for molten-salt-fueled reactor (MSR) safety analysis and licensing, an effort was devoted to enhancing code capabilities and developing reference models for the MSR primary loop. A reference standard problem of a prototypical reactor design is foundational to NRC to verify the adequacy of computer codes and evaluation models for a specific reactor type. A thermo-fluid model of the Molten Salt Reactor Experiment (MSRE) has been developed. The MSRE primary loop model consists of a 2-D core region and external core components in 1-D or 0-D. Both the steady-state and a transient scenario are simulated. The porous medium model is utilized for both the molten salt fluid channels and the moderator matrix in the MSRE core. The use of the porous medium model for the MSRE core is verified with the higher-fidelity simulation results using 1-D representations of the fluid channels and 3-D modeling of core structures. To further enhance SAM multi-scale simulation capabilities for MSRs, a mass transport model is developed and implemented in SAM multi-dimension flow module for modeling of species transport such as delayed neutron precursors in MSRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling

The Renewable Energy Potential (reV) model is a platform for detailed assessment of renewable energy (RE) resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP) and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for assessment of resource potential, technical potential and supply curves at varying levels of detail. The platform runs on NREL's High Performance Computing system, providing scalable and efficient performance from a single location all the way up to continental scales, for a single year or decades of time series resource data. Coupled with NREL's System Advisor Model (SAM), reV supports resource assessment from 5-minute to hourly temporal resolution and provides for analysis of long-term (i.e., year-on-year) variability of RE generation (e.g., interannual variability and exceedance probabilities). Technical potential is measured as a function of resource potential and limitations put on developable land area defined by the user. For example, the user can limit development by land ownership, terrain, land use/cover, and urban areas, as well as custom inputs. Technology, grid interconnection and operation costs, based on the latest market data and future projections, are also embedded in the model. The supply curve module is a spatial sorting algorithm based on plant siting, grid interconnection cost, and regional competition, which provides a geographically discrete estimate of levelized cost of electricity (LCOE) and supply (i.e., capacity) for specific renewable technologies. The reV model currently provides broad coverage across North America, South and Central Asia, South America and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.

13 HYDRO ENERGY↗
DOE OSTI2022

A Realistic Full-Scale 3D Modeling of Turning Using Coupled Smoothed Particle Hydrodynamics and Finite Element Method for Predicting Cutting Forces

Computational modelling is an effective technique for understanding the complex physics of machining. Large deformations, material separation, and high computational requirements are the key challenges faced while simulating machining. This work introduces a full-scale three-dimensional model of turning operations using a combined approach based on the Smoothed Particle Hydrodynamics (SPH) and Finite Element (FE) methods. By exploiting the advantages of each method, this approach leads to high-fidelity coupled SPH-FE machining models. Cutting forces and chip morphology are the primary results of interest. The machining models are validated with the results of turning experiments. Two-dimensional machining model underpredicts the cutting force and feed force by approximately 49% and 70%, respectively. Moreover, passive force cannot be predicted using the two-dimensional model. On the other hand, with the three-dimensional models developed in this manuscript, the difference between the total simulated force and experimentally measured force is ∼17%. The chip morphologies correlate with experiments in terms of the direction of the chip movement and the “long” continuous chips observed while turning Al 6061. This work expands the realm of machining simulations from two-dimensional orthogonal machining or sectional three-dimensional model to a full-scale realistic simulation. The encouraging simulation results show the potential to study more complex phenomena, such as machining stability and tool path modulation.

42 ENGINEERING↗
DOE OSTI2021

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

On the influence of ENSO complexity on Pan-Pacific coastal wave extremes

Significance This study demonstrates how the main wave regimes in the Pacific, in particular related to tropical and extratropical storm activity, are activated by different El Niño/Southern Oscillation (ENSO) teleconnections patterns. By combining these robust relationships with the latest theoretical advances in ENSO research, a mathematical model of wave energy modulation is derived. It allows a better representation of wave extremes over a range of time scales wider than previously possible with the previous baseline understanding of ENSO’s influence on coastal impacts. This paves the way for unprecedented seasonal to monthly forecasts of coastal hazards around the densely populated Pacific basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

MAT 332: Recyclable-By-Design Carbon Fiber Composites for Battery Enclosures

This work aims to fabricate a small-scale battery module with the baseline RBD-CFRC and conduct mechanical crush test to develop an initial thermal runaway model. Test the adhesive properties of the RBD-CFRCs using their resin constituent, ultrasonic welding, and other resins employed today. Recommend a future direction for resin development to enable the welding of RBDCFRCs to dissimilar materials. Time and Cost Permitting. Iterate on resin development for flame resistance and adhesive properties, demonstrating how thermal runaway can be reduced or joining properties can be improved.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

ECAR-6076 Rev 0 MARVEL Reactor End of Life Enveloping Radiological Source Term

As part of the Microreactor Applications Research Validation and Evaluation Project (MARVEL) design effort, an enveloping end of life radiological source term for the reactor fuel and sodiumpotassium (NaK) eutectic coolant is calculated in support of the MARVEL preliminary hazard evaluation. The source term calculation assumes slightly more than two-years of uninterrupted operations at a power of about 120 kW for a total energy of 7,600,000 MJ which exceeds the planned two-year operation at 100 kW. The Reactor modeling was performed with MCNP6 Version 1.0 and the depletion was performed using the COUPLE and ORIGEN modules from the SCALE Version 6.2 code package.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗