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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Two-dimensional equations of the surface harmonics method for solving problems of spatial neutron kinetics in square-lattice reactors

Two-dimensional time-dependent finite-difference equations of the surface harmonics method (SHM) for the description of the neutron transport are derived for square-lattice reactors. These equations are implemented in the SUHAM-TD code. Verification of the derived equations and the developed code are performed by the example of known test problems, and the potential and efficiency of the SHM as applied to the solution of the time-dependent neutron transport equation in the diffusion approximation in two-dimensional geometry are demonstrated. These results show the substantial advantage of SHM over direct finite-difference modeling in computational costs.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Online peak-aware energy scheduling with untrusted advice

This paper studies the online energy scheduling problem in a hybrid model where the cost of energy is proportional to both the volume and peak usage, and where energy can be either locally generated or drawn from the grid. Inspired by recent advances in online algorithms with Machine Learned (ML) advice, we develop parameterized deterministic and randomized algorithms for this problem such that the level of reliance on the advice can be adjusted by a trust parameter. We then analyze the performance of the proposed algorithms using two performance metrics: robustness that measures the competitive ratio as a function of the trust parameter when the advice is inaccurate, and consistency for competitive ratio when the advice is accurate. Since the competitive ratio is analyzed in two different regimes, we further investigate the Pareto optimality of the proposed algorithms. Our results show that the proposed deterministic algorithm is Pareto-optimal, in the sense that no other online deterministic algorithms can dominate the robustness and consistency of our algorithm. Furthermore, we show that the proposed randomized algorithm dominates the Pareto-optimal deterministic algorithm. Our large-scale empirical evaluations using real traces of energy demand, energy prices, and renewable energy generations highlight that the proposed algorithms outperform worst-case optimized algorithms and fully data-driven algorithms.

Lee, Russell↗
DOE OSTI2022

Modular Adaptive Packing for Integrally Cooled Absorbers

Process intensification is one cornerstone in ION Clean Energy’s (ION) efforts to lowering CO2 capture cost. ION has modeled, designed, and fabricated an innovative gas-liquid contactor known as Modular Adaptive Packing (MAP). During two successful SBIR Phase I and II projects entitled: “Rapid Design and Testing of Novel Gas-Liquid Contacting Devices for Post-Combustion CO2 Capture via 3D-printing”, ION developed and proved this new technology at bench scale. MAP, a 3D-printed lattice-structured packing, combines the absorber gas/liquid contactor with an innovative in-situ heat-exchanger. Thanks to the capabilities of 3D-printing, the lattice structure of MAP contains hollow channels through which coolant water can be pumped to remove the heat of reaction from CO2 absorption. ION refers to this novel method of heat exchange as intracooling. After 25.4 cm (10 in) diameter MAP modules were fabricated, ION built and tested a packing characterization rig at its pilot facility in Boulder, Colorado, U.S.A. To provide baseline results for the characterization rig, ION tested Sulzer’s Mellapak™ 250Y (MP250Y) as a standard structured packing. ION’s MAP was then compared directly to the baseline MP250Y packing to evaluate key indicators including pressure drop, liquid hold-up, and effective area. MAP has a higher pressure drop than MP250Y at the same gas velocities in addition to greater liquid holdup. However, ION found that MAP displays a higher wetting coverage of 93% compared to 65% for MP250Y and reduces shearing forces that result in undesirable droplet formation. Using Optimized Gas Treating’s (OGT) rate-based simulation software ProTreat®, a conceptual evaluation of MAP was modeled for a CO2 absorber using 30 wt% MEA solvent over a range of lean loadings at 90% CO2 capture from a coal-fired power plant. ION modeled a 25-meter column absorber for both the standard MP250Y packing and a hybrid column. The hybrid absorber contained 10 m of MP250Y packing at the top and bottom with the middle 5 meters comprised of MAP. Compared to a traditional intercooled absorber, MAP can remove 22% more heat and increase overall MEA carrying capacity by 4% without increasing overall pressure drop.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Staged, High-Pressure Oxy-Combustion Technology: Development and Scale-Up

The immediate need for a high efficiency, low cost carbon capture process has prompted the recent development of pressurized oxy-combustion. With a greater combustion pressure the dew point of the flue gas is increased, allowing for effective integration of the latent heat of flue gas moisture into the Rankine cycle. This increases the net plant efficiency and reduces costs. A novel, transformational process, named Staged, Pressurized Oxy-Combustion (SPOC), achieves additional step changes in efficiency and cost reduction by significantly reducing the recycle of flue gas. The research and development activities conducted under Phases I and II of this project (FE0009702) include: SPOC power plant cost and performance modeling, CFD-assisted design of pressurized SPOC boilers, theoretical analysis of radiant heat transfer and ash deposition, boiler materials corrosion testing, construction of a 100 kWth POC test facility, and experimental testing. The results of this project have advanced the technology readiness level (TRL) of the SPOC technology from 1 to 5.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Risk Evaluation for Identification and Intervention in Dual Use Research of Concern (DURC) for International Biological R&D Activity

This report summarizes the work performed as part of a Laboratory Directed Research and Development project focused on evaluating and mitigating risk associated with biological dual use research of concern. The academic and scientific community has identified the funding stage as the appropriate place to intervene and mitigate risk, so the framework developed here uses a portfolio-level approach and balances biosafety and biosecurity risks, anticipated project benefits, and available mitigations to identify the best available investment strategies subject to cost constraints. The modeling toolkit was designed for decision analysis for dual use research of concern, but is flexible enough to support a wide variety of portfolio-level funding decisions where risk/benefit tradeoffs are involved. Two mathematical optimization models with two solution methods are included to accommodate stakeholders with varying levels of certainty about priorities between metrics. An example case study is presented.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

CRADA Final Report: Weld Predictor App

Welding is an important manufacturing process used in a broad range of industries and market sectors, including automotive, aerospace, heavy manufacturing, medical, and defense. During welded fabrication, high localized heat input and subsequent rapid cooling result in the creation of residual stresses and distortion. These residual stresses can significantly affect the fatigue resistance, cracking behavior, and load-carrying capacity of welded structures during service. Further, additional fitting and tacking time is often required to fit distorted subassemblies together, resulting in non-value added cost. Using trial-and-error methods to determine which welding parameters, welding sequences, and fixture designs will most effectively reduce distortion is a time-consuming and expensive process. For complex structures with many welds, this approach can take several months. For this reason, efficient and accurate methods of mitigating distortion are in-demand across all industries where welding is used. Analytical and computational methods and commercial software tools have been developed to predict welding-induced residual stresses and distortion. Welding process parameters, fixtures, and tooling can be optimized to reduce the HAZ softening and minimize weld residual stress and distortion, improving performance and reducing design, fabrication and testing costs. However, weld modeling technology tools are currently accessible only to engineers and designers with a background in finite element analysis (FEA) who work with large manufacturers, research institutes, and universities with access to high-performance computing (HPC) resources. Small and medium enterprises (SMEs) in the US do not typically have the human and computational resources needed to adopt and utilize weld modeling technology. To allow an engineer with no background in FEA and SMEs to gain access to this important design tool, EWI and the Ohio Supercomputer Center (OSC) developed the online weld application software tool “WeldPredictor” ( https://eweldpredictor.ewi.org ). About 1400 users have tested this application. This project marked the beginning of development on the next version of WeldPredictor that addresses many outstanding features of the original, including 3D models, allow more material hardening laws, model material phase transformation, and uses open source finite element solvers to quickly solve problems (as opposed to expensive commercial tools).

42 ENGINEERING↗
DOE OSTI2021

International Collaboration Activities in Geologic Disposal Research: FY2021 Progress

This report describes the FY21 status of international collaboration regarding geologic disposal research in the Spent Fuel and Waste Disposition (SFWD) Campaign. Since 2012, in an effort coordinated by Lawrence Berkeley National Laboratory, SFWD has advanced active collaboration with several international geologic disposal programs across the world. Such collaboration has allowed the SFWD Campaign to benefit from a deep knowledge base in regards to alternative repository environments developed over decades and has provided a framework for active peer-to-peer research participation in international groups which conduct, analyze, and model performance-relevant processes. Via international collaboration, the SFWD Campaign also benefits from substantial international investments in research facilities (such as underground research laboratory testing and modeling) and achieves cost savings via joint funding of expensive field experiments. To date, SFWD’s International Disposal R&D Program has established formal collaboration agreements with multiple international initiatives and various international partners, and national lab scientists associated with SFWD have conducted a large number of specific collaborative R&D activities that align well with its R&D priorities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Distribution Grid Impacts of Community Solar [Slides]

Community solar (CS) projects often face uncertain interconnection costs and fees associated with distribution grid infrastructure upgrades required to connect the project. These costs can determine the economic viability of a CS project, but they are difficult to assess. Cost uncertainty can discourage new projects and prevent communities from accessing the benefits of community solar projects. At the same time, CS deployment strategies hold potential to defer or avoid some distribution costs due to new loads. To mitigate CS interconnection costs, it is important to find least-cost combinations of distribution system infrastructure solutions (transformer upgrades, reconductoring, voltage regulators, storage), and to understand how location of CS projects within a feeder impact distribution grid upgrade costs. This study aims to quantify CS impacts on the distribution grid and provide policy and regulatory insights and CS deployment strategies to address them. It is the first analysis that has systematically studied the technical impacts of community solar projects on a wide range of distribution feeders using state-of-the-art optimization and power flow tools. The analysis employs Berkeley Lab’s novel Least-cost Optimal Distribution Grid Expansion (LODGE) model, a deterministic version of the REPAIR model, that optimally upgrades hundreds or even thousands of distribution circuits or feeders. This is the first application of the LODGE model. LODGE finds the least-cost portfolio of traditional distribution system upgrades to integrate CS in combination with alternative solutions, such as utility-owned storage and downsizing CS capacity. Working with a set of least-cost solutions per feeder allows us to benchmark, compare and find techno-economic trends in CS interconnection.

14 SOLAR ENERGY↗
DOE OSTI2025

Estimates of the Economic Impacts of Long-Duration, Widespread Power Disruptions in Puerto Rico

A typical electricity customer in Puerto Rico experienced nearly 27 hours of power interruptions in 2023–with many customers experiencing extremely long duration outages during a single event (i.e., greater than one month). This project involved conducting state-of-the-art surveying to assess the direct costs of power outages occurring across Puerto Rico, developing customer-specific models to estimate future costs over varying outage durations, and comparing these estimates to FEMA’s Value of Unit Service for Electricity. We estimate that a territory-wide power outage may cost customers $\$1$, $\$5$ and $\$29$ billion during one-, 14-, and 30-day interruptions, respectively. However, these are lower-bound estimates because our study focused on direct economic costs and, by necessity, did not fully incorporate (1) indirect impacts to the economy; (2) costs to repair or replace damaged utility infrastructure; and (3) the broader societal consequences including increased morbidity- and mortality-related costs. The information contained in this study can be used to estimate the direct economic value of past or proposed investments in power system resilience. We conclude with a discussion of this study’s limitations and suggest additional research to improve stakeholder understanding of the impacts of power outages across Puerto Rico.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Electric Vehicles as Flexibility Management Strategy for the Electricity System—A Comparison between Different Regions of Europe

This study considers whether electric vehicles (EVs) can be exploited as a flexibility management strategy to stimulate investments in and operation of renewable electricity under stringent CO 2 constraints in four regions with different conditions for renewable electricity (Sweden, Germany, the UK, and Spain). The study applies a cost-minimisation investment model and an electricity dispatch model of the European electricity system, assuming three types of charging strategies for EVs. The results show that vehicle-to-grid (V2G), i.e., the possibility to discharging the EV batteries back to grid, facilitates an increase in investments and generation from solar photovoltaics (PVs) compare to the scenario without EVs, in all regions except Sweden. Without the possibility to store electricity in EV batteries across different days, which is a technical limitation of this type of model, EVs increase the share of wind power by only a few percentage points in Sweden, even if Sweden is a region with good conditions for wind power. Full electrification of the road transport sector, including also dynamic power transfer for trucks and buses, would decrease the need for investments in peak power in all four regions by at least 50%, as compared to a scenario without EVs or with uncontrolled charging of EVs, provided that an optimal charging strategy and V2G are implemented for the passenger vehicles.

25 ENERGY STORAGE↗
DOE OSTI2025

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗
DOE OSTI2021

Direct Recycling R&D at the ReCell Center

The expected rapid growth in electric vehicle deployment will inevitably be followed by a corresponding rise in the supply of end-of-life vehicles and their lithium-ion batteries (LIBs). The batteries may be reused, but will eventually be spent and provide a potential domestic resource that can help supply materials for future battery production. However, commercial recycling processes depend on profits from recovery of cobalt, use of which is being reduced in new cathode chemistries. The U.S. Department of Energy, therefore, established the ReCell Center in early 2019 to develop robust LIB recycling technology that would be economical even for batteries that contain no cobalt. The central feature of the technology is recovery of the cathode material with its unique crystalline cathode morphology intact in order to retain its value and functionality. Other materials are recovered as well in order to maximize revenues and minimize waste-handling costs. Analysis and modeling serve to evaluate and compare process options so that we can identify those that will be most economical while still minimizing energy use and environmental impacts. This paper provides background and describes highlights of the center’s first 2 years of operation.

Gaines, Linda (ORCID:0000000237263387)↗
DOE OSTI2023

Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations

Abstract. Deep learning (DL) and machine learning (ML) are widely used in hydrological modelling, which plays a critical role in improving the accuracy of hydrological predictions. However, the trade-off between model performance and computational cost has always been a challenge for hydrologists when selecting a suitable model, particularly for probabilistic post-processing with large ensemble members. This study aims to systematically compare the quantile regression forest (QRF) model and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) model as hydrological probabilistic post-processors. Specifically, we evaluate their ability in dealing with biased streamflow simulations driven by three satellite precipitation products across 522 nested sub-basins of the Yalong River basin in China. Model performance is comprehensively assessed using a series of scoring metrics from both probabilistic and deterministic perspectives. Our results show that the QRF model and the CMAL-LSTM model are comparable in terms of probabilistic prediction, and their performances are closely related to the flow accumulation area (FAA) of the sub-basin. The QRF model outperforms the CMAL-LSTM model in most sub-basins with smaller FAA, while the CMAL-LSTM model has an undebatable advantage in sub-basins with FAA larger than 60 000 km2 in the Yalong River basin. In terms of deterministic predictions, the CMAL-LSTM model is preferred, especially when the raw streamflow is poorly simulated and used as input. However, setting aside the differences in model performance, the QRF model with 100-member quantiles demonstrates a noteworthy advantage by exhibiting a 50 % reduction in computation time compared to the CMAL-LSTM model with the same ensemble members in all experiments. As a result, this study provides insights into model selection in hydrological post-processing and the trade-offs between model performance and computational efficiency. The findings highlight the importance of considering the specific application scenario, such as the catchment size and the required accuracy level, when selecting a suitable model for hydrological post-processing.

Geology↗
DOE OSTI2026

West Africa Battery Energy Storage Systems (BESS) Capacity Building - Discussion of BESS Tariffs: Payment Structures and Case Studies [Slides]

Battery Energy Storage Systems (BESS) are emerging as critical assets for enhancing grid reliability, integrating renewable energy, and enabling system flexibility. Yet, the regulatory and financial frameworks that determine how BESS projects are compensated vary widely across jurisdictions. This presentation explores international case studies - from Honduras, Costa Rica, Chile, South Africa, Mexico, and Brazil - to illustrate how tariff design and payment structures are evolving to support large-scale BESS deployment. The cases highlight a range of ownership and revenue models, including cost-of-service mechanisms, energy and capacity payments, and market-based arbitrage, as well as hybrid approaches under development. The discussion will examine key challenges such as defining remuneration for ancillary services, addressing double charging, and accounting for efficiency losses and degradation over time. By comparing experiences across markets, the presentation identifies emerging best practices for valuing BESS and designing tariffs that align technical performance with economic incentives, providing insights for regulators, utilities, and policymakers pursuing storage integration.

25 ENERGY STORAGE↗
NASA NTRS1973

Structural analysis of light aircraft using NASTRAN

An application of NASTRAN to the structural analysis of light aircraft was conducted to determine the cost effectiveness. A model of the Baby Ace D model homebuilt aircraft was used. The NASTRAN model of the aircraft consists of 193 grid points connected by 352 structural members. All members are either rod or beam elements, including bending of unsymmetrical cross sections and torsion of noncircular cross sections. The aerodynamic loads applied to the aircraft were in accordance with FAA regulations governing the utility category aircraft.

Wilkinson, M. T.↗
NASA NTRS1974

Control system design using frequency domain models and parameter optimization, with application to supersonic inlet controls

A technique is described for designing feedback control systems using frequency domain models, a quadratic cost function, and a parameter optimization computer program. FORTRAN listings for the computer program are included. The approach is applied to the design of shock position controllers for a supersonic inlet. Deterministic or random system disturbances, and the presence of random measurement noise are considered. The cost function minimization is formulated in the time domain, but the problem solution is obtained using a frequency domain system description. A scaled and constrained conjugate gradient algorithm is used for the minimization. The approach to a supersonic inlet included the calculations of the optimal proportional-plus integral (PI) and proportional-plus-integral-plus-derivative controllers. A single-loop PI controller was the most desirable of the designs considered.

Seidel, R. C.↗
NASA NTRS1977

An application of interactive computer graphics technology to the design of dispersal mechanisms

Interactive computer graphics technology is combined with a general purpose mechanisms computer code to study the operational behavior of three guided bomb dispersal mechanism designs. These studies illustrate the use of computer graphics techniques to discover operational anomalies, to assess the effectiveness of design improvements, to reduce the time and cost of the modeling effort, and to provide the mechanism designer with a visual understanding of the physical operation of such systems.

Richter, B. J.↗