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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A New Subfamily of Glycoside Hydrolase Family 30 with Strict Xylobiohydrolase Function

The Acetivibrioclariflavus (basonym: Clostridium clariflavum) glycoside hydrolase family 30 cellulosomal protein encoded by the Clocl_1795 gene was highly represented during growth on cellulosic substrates. In this report, the recombinantly expressed protein has been characterized and shown to be a non-reducing terminal (NRT)-specific xylobiohydrolase (AcXbh30A). Biochemical function, optimal biophysical parameters, and phylogeny were investigated. The findings indicate that AcXbh30A strictly cleaves xylobiose from the NRT up until an α-1,2-linked glucuronic acid (GA)-decorated xylose if the number of xyloses is even or otherwise a single xylose will remain resulting in a penultimate GA-substituted xylose. Unlike recently reported xylobiohydrolases, AcXbh30A has no other detectable hydrolysis products under our optimized reaction conditions. Sequence analysis indicates that AcXbh30A represents a new GH30 subfamily. This new xylobiohydrolase may be useful for commercial production of industrial quantities of xylobiose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗
DOE OSTI2024

A high fidelity and user-friendly equation-oriented optimization model for carbon capture using a novel water-lean solvent

Research Triangle Institute (RTI) International and SLB have developed a novel water-lean solvent technology for carbon capture, demonstrating low specific reboiler duty (SRD) values at capture rates exceeding 90%. At the Technology Centre Mongstad (TCM) pilot plant, the technology achieved an SRD of 2.55 GJ/t-CO2 at 95% capture, utilizing an intercooler and a 5°C temperature approach in the lean/rich solvent cross exchanger. To meet varying carbon capture targets for Front End Engineering and Design (FEED) studies and to enable real-time optimization and advanced process control, an efficient optimization model is required. This model needs to minimize energy demand for a given capture rate and determine optimal operating parameters in response to fluctuating flue gas conditions. While an existing Aspen Plus simulation model, developed by RTI and SLB, accurately matches TCM plant data, its sequential modular (SM) strategy is too slow for real-time applications due to recycle streams and tight heat integration inherent in solvent-based carbon capture processes. Although an equation-oriented (EO) modeling strategy is more suitable for optimizing these processes, its adoption has been limited by several factors: feature limitations in Aspen Plus EO mode (e.g., lack of balance block support), a less user-friendly interface for variable identification and loop solving, complex troubleshooting of convergence issues, and the necessity for accurate initial values.

carbon capture↗
DOE OSTI2023

Aero‐servo‐elastic co‐optimization of large wind turbine blades with distributed aerodynamic control devices

Abstract This work introduces automated wind turbine optimization techniques based on full aero‐servo‐elastic models and investigates the potential of trailing edge flaps to reduce the levelized cost of energy (LCOE) of wind turbines. The Wind Energy with Integrated Servo‐control (WEIS) framework is improved to conduct the presented research. Novel methods for the generic implementation and tuning of trailing edge flap devices and their controller are also introduced. Primary flap and controller parameters are optimized to demonstrate potential maximum blade tip deflection reductions of 21 % . Concurrent design optimization (i.e., co‐design) of a novel segmented wind turbine blade with trailing edge flaps and its controller is then conducted to demonstrate blade cost savings of 5 % . Additionally, rotor diameter co‐design optimization is demonstrated to reduce the LCOE by 1.3 % without significant load increases to the tower. These results demonstrate the efficacy of control co‐design optimization using trailing edge flaps, and the entirety of this work provides a foundation for numerous control co‐design‐oriented studies for distributed aerodynamic control devices.

17 WIND ENERGY↗
DOE OSTI2021

Revisions of ORNL 188 W Process Based on Nonradiological Experiments

Tungsten-188 is in widespread use in the 188 W(t 1/2 = 69 d)/ 188 Re(t 1/2 =16.9 h) biomedical generator. Oak Ridge National Laboratory (ORNL) has been providing this product to the world since 1999. At ORNL, 188 W is produced via irradiation in ORNL’s High Flux Isotope Reactor (HFIR). Enriched 186 W targets in the form of sintered metallic pellets or rings achieve a compact loading in the irradiation vessel, providing a high yield per unit target. The enrichment of the target is >90% 186 W and this isotope undergoes double neutron capture to produce the desired 188W product. While 188 W is produced by neutron bombardment, 191 Os(t 1/2 = 15.4 d) is simultaneously produced as a byproduct requiring separation from 188 W by post irradiation treatment. In the current processing pathway, the irradiated W metal pellets or rings are first converted into an oxide form of WO 3 by heating the irradiated W metal target at 750°C in a quartz reaction vessel inside a vertical furnace under a constant flow of air. During heating, W metal reacts with oxygen in the air to produce WO 3 , which is soluble in 6 M NaOH for later purification process. This oxidation process also converts 188 Os (the decay daughter of 188 W) and 191 Os (the irradiation produced byproduct) into OsO 4 , a highly volatile and toxic gas. The gaseous effluents driven from the quartz reaction vessel are passed through a scrubbing array to remove OsO 4 before the air is discharged from the process. This heterogeneous oxidation method simultaneously achieves two goals: 1). converting metal target to a soluble oxide form and 2). separating volatile OsO 4 away from the solid WO 3 product, although harmful 191 OsO 4 is unfavorable but being taken care of by the down road scrubbing array. In the past twenty years the existing OsO 4 scrubbing array served well in preventing OsO 4 from being released into the environment, until July of 2020 when a minor amount of 191 Os was found to have been released into the environment which resulted in a standby of building 4501 from July 2020 to February 2021.Since October 20 of 2020 a team of researchers from groups of RSTD and NEFD were organized to work for the following tasks: (1) Fully understand the root causes of the July incident of 191 Os release and create a redesigned 191 Os scrubbing array to eliminate the possibility of 191 Os release in future 188 W processes; (2) In Phase-1 tests, select a correct air (O 2 ) flow rate in 188 W process, that provides sufficient oxygen for the oxidation of tungsten metal, while still allowing sufficient resonance time for 191 Os removal by the scrubbers; (3) In Phase-2 tests, confirm the efficiency of the redesigned scrubbing array to absorb excessive amount of non-rad OsO 4 (generated from Os metal powder) at the selected air flow; (4) In Phase-3 tests, simulate the hot cell 188 W process by heating pressed non-rad W-Os pellets in a quartz vessel of new design and the new array under operation parameters selected in Phase-1 and -2; (5) Complete a new operation procedure for 188 W process in hot cell and a TM report as a summary of the Os Mitigation Project. This TM report summarizes the investigation on root causes from technical aspects in July 191 Os release and the correspondent improvement towards the redesigned 191 Os scrubbing system. The report presents the efforts made on selection of optimal operational parameter with the new scrubbing array and the quartz vessel of new design, based on experiment data obtained in Phase-1, -2 and -3 tests. Further renovations for 188 W process and additional improvement of W target treatment will also be discussed.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Study on Electropolishing of N-Doped Niobium Surfaces and 650 MHz Cavity for High-Gradient Performance

This presentation provides an overview of the latest studies on electropolishing (EP) of nitrogen-doped niobium surfaces and 650 MHz cavities. The first study focuses on optimizing EP parameters to achieve a pit-free surface on N-doped niobium, highlighting the effects of process conditions on surface pitting and suggesting strategies for mitigation. The second study investigates the EP of 650 MHz cavities to achieve high-gradient performance comparable to that of 1.3 GHz niobium SRF cavities. Additionally, an example of a 650 MHz single-cell cavity is presented, demonstrating its record-high gradient achieved through optimized EP conditions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Catalytic resonance theory for parametric uncertainty of programmable catalysis

Microkinetic models are useful tools for screening catalytic materials; however, errors in their input parameters can lead to significant uncertainty in model predictions of catalyst performance. Here, in this work, we investigate the impact of linear scaling and Brønsted-Evans-Polanyi relation parametric uncertainty on microkinetic predictions of programmable-catalyst performance. Two case studies are considered: a generic A-to-B prototype reaction and the oxygen evolution reaction (OER). The results show that error-unaware models can accurately predict trends and, for the prototype reaction, values of optimal waveform parameters. The specific model parameters driving output uncertainty are identified via variance-based global sensitivity analysis. However, predictions of dynamic rate enhancement can decrease when uncertainty is propagated into the models. In both cases, we identify operating conditions where the programmable catalyst achieves a rate enhancement of at least one order of magnitude despite parametric uncertainty in the model, supporting programmable catalysis as a viable strategy for exceeding the Sabatier limit.

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

MODELING AND OPTIMIZATION OF A PCM-BASED OCEAN THERMAL ENERGY HARVESTER FOR POWERING UNMANNED UNDERWATER VEHICLES

As oceans cover over 70% of the planet’s surface, they represent a large reservoir of resources that remained vastly untapped. Uncrewed Underwater Vehicles (UUVs) are becoming key technology for ocean exploration. Ocean thermal gradient is a permanent and reliable energy source that can be used to power UUVs using phase change material (PCM)-based thermal engines. However, the main drawback of this technology is its low conversion efficiency. When using PCM-based thermal engines to power UUVs, there are different energy conversion stages, thermal-hydraulic, hydraulic-kinetic, kinetic-electrical, dependent of a wide variety of parameters. Thus, optimization of the overall energy conversion is still a challenge for powering the increasing energy demanding UUVs for long missions. The goal of this study is to propose a PCM-based ocean thermal energy harvesting system for powering the Solo II float. Using the ocean thermal energy reduces the cost for battery replacement and expands the float’s mission time. For this purpose, we developed a multiphysics model for a system consisting of thermal material, hydraulic, and electrical systems. This system is designed to provide the electrical power needed for the instruments aboard the underwater vehicle. The models of the hydraulic and the electric systems are implemented in MATLAB-Simulink/Simscape environment. The final model developed can provide 13.66 kJ of electrical energy, which is more than 1.5 times the energy requirement per cycle for the SOLO II float.

Ouro-Koura, Habilou↗
DOE OSTI2023

Development of a Reactive Force Field for Simulating Photoinitiated Acrylate Polymerization

Light-driven and photo-curable polymer based additive manufacturing (AM) has enormous potential due to its excellent resolution and precision. Acrylated radical chain-growth polymerized resins are widely used in photopolymer AM due to their fast kinetics, and often serve as a departure point for developing other resin materials for photopolymer-based AM technologies. For successful control of the photopolymer resins, the molecular basis of the acrylate free-radical polymerization has to be understood in detail. We present an optimized reactive force field (ReaxFF) for molecular dynamics (MD) simulations of acrylate polymer resins that captures radical polymerization thermodynamics and kinetics. The force field is trained against an extensive training set including density functional theory (DFT) calculations of reaction pathways along the radical polymerization from methyl acrylate to methyl butyrate, bond dissociation energies, and structures and partial charges of several molecules and radicals. We also found that it was critical to train the force field against an incorrect, nonphysical reaction pathway observed in simulations that used parameters not optimized for acrylate polymerization. As a result, the parameterization process utilizes a parallelized search algorithm, and the resulting model can describe polymer resin formation, crosslinking density, conversion rate, and residual monomers of the complex acrylate mixtures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Case for Reducing Emissions from Heavy-Duty Off-Road Applications via Ducted Fuel Injection

Designers of heavy-duty diesel engines use a variety of techniques to improve efficiency and reduce pollutant emissions. Ducted fuel injection (DFI), high fuel injection pressures, optimized injection orifices, multiple injection sites, and oxygenated fuels are a few techniques used by designers to improve fuel/charge-gas mixtures within the combustion chamber to improve efficiency and emissions results. Ducted fuel injection (DFI) has been proven to substantially reduce soot for low- and mid-load conditions in heavy duty engines, without significantly increasing nitrogen oxides (NO x ). This study investigates the performance of DFI utilizing conventional diesel fuel and the potential the technique has for future research utilizing varieties of test fuels and operating parameter values. Optimization for high engine efficiency and low emissions will help facilitate DFI deployment for substantial environmental benefits in heavy-duty sectors where electrification and/or carbon-free fuels aren’t feasible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Studies on Printability Methodologies and Directed-Energy-Deposition-Fabricated Iron Alloys for Nuclear Applications

This report provides results from a printability study of laser directed energy deposition (DED)-based additive manufacturing of nuclear-grade stainless steels as well as DED process parameter development for austenitic Alloy 709 (A709) and ferritic/martensitic Grade 91 (G91) and Grade 92 (G92) steels. The printability study includes the use of machine learning and physics-based modeling via commercial software such as FLOW-3D for insights into the impact of the alloy composition, particularly the carbon content, on the printability of stainless steels during the DED process. In the DED process development work, 1 cm 3 alloy blocks were deposited with broad ranges of laser powers, scan speeds, and hatch spacings to optimize the build quality, resulting in densities of more than 99.8% for all three alloys. The microstructure and mechanical properties were characterized using electron microscopy, X-ray diffraction, and Vickers hardness measurements. Further, tensile samples were extracted from DED-fabricated alloys utilizing the optimized process parameters. The present work provides guidance and progress towards the successful deployment of the DED process for the fabrication of structural components of nuclear reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Constitutive model development of aluminum alloy 1100 for elevated temperature forming process

Commercially pure aluminum alloy, AA1100, presents good electrical and thermal conductivity, high formability, and low cost. Those favorable characteristics have the potential to enable bipolar plates with improved economics and enhanced performance compared to current stainless steel bipolar plates for proton exchange membrane fuel cells. An accurate constitutive model is essential to develop and optimize processing parameters and effectively control the forming process. Here, the objective of this work is to develop a constitutive model of AA1100 that is able to simulate stress-strain relation, formed geometry, and predict the onset of fracture strain to avoid forming failure. Initially, a set of tensile tests at temperature between 300 and 500°C and strain rate between 0.005 and 1.0/s were conducted to examine the deformation behavior. Then, a set of damage-based unified visco-plastic constitutive equations is proposed and calibrated based on the results of stress-strain data. A genetic algorithm optimization method is applied to search for best fitting material constants in constitutive equations. The proposed model shows good predictability of both the stress-strain relation and fracture strain at low strain rate and high temperature conditions. The accuracy of proposed model is also evaluated statistically. A comparison of the proposed model with three popular models (Arrhenius-type mode, Johnson-Cook model and Zerilli-Armstrong model) was made. The proposed model shows the best experimental agreement with correlation coefficient of 0.96 in contrast to 0.25, 0.38 and 0.75 for the popular models, respectively. The proposed model can help to optimize the elevated temperature forming process and guide die design to enable optimal geometric features in the formed components.

08 HYDROGEN↗
DOE OSTI2025

Role of Computational Parameters on Predicting Self-Consistent Residual Stress and Distortion during Wire Arc Additive Manufacturing

Production of three-dimensional metallic parts through integration of an articulated robot and gas metal arc welding, also known as wire arc additive manufacturing (WAAM), can produce large-scale components with moderate geometrical complexity. This technology is particularly appealing due to its high deposition rates, scalability, and cost-effective feedstock compared to other AM processes. Despite its advantages, WAAM adoption is hindered by challenges in ensuring geometric conformity without extensive distortion, defect-free structures, and consistent mechanical properties. Finite element analysis (FEA) is often used to address the challenge of geometrical conformity. As the size of parts increases, the best practices for mesh size and temporal resolution known in the literature become computationally unviable. This research examined the effects of mesh and time-step resolutions during transient FEA of a large-scale (248 layers) metallic part. The impact of computational parameters on the thermal history, displacement, and residual stress distributions were evaluated. The results showed that predicted distortion was consistent across resolutions, while time-step length significantly affected predicted thermal history, and mesh size influenced residual stress distributions. To investigate this relationship further, directionally biased meshes were considered and analyzed. The results indicated that increasing mesh resolution perpendicular to the welding path yielded stress predictions that aligned closely with higher-resolution models while offering substantial computational savings. In conclusion, the significances of this research are related to verification and validation of WAAM models for widespread industrial adoption and pragmatic guidelines for optimizing computation parameters for balancing computational efficiency and predictive accuracy of residual stress and distortion.

Solsbee, Brandon [Univ. of Tennessee, Knoxville, T↗
DOE OSTI2024

Referenceless, grating-based, single shot X-ray phase contrast imaging with optimized laser-driven K-α sources

With its ability to efficiently probe low-Z materials, X-ray phase imaging methods have recently raised high interest in multiple fields from biology and medical applications to high energy density (HED) physics. Initially developed with synchrotron light and X-ray tubes, we present a novel grating based Talbot X-ray deflectometer (TXD) diagnostic that was coupled with laser-generated K-α X-ray sources. The multi-terawatt laser (I > 1 × 10 14 W cm -2 ) was used as a testbed for diagnostic development. It was found that X-ray source chromaticity plays an important role in TXD. Indeed, the broadband spectrum of laser-generated X-ray sources may strongly impact image quality and thus diagnostic performance. We qualified X-ray emission from different laser-produced sources and determined laser, target, and deflectometer parameters that optimize TXD performance. We present the first results of referenceless grating-based X-ray imaging at high-power laser facilities and discuss the implications of this new development in HED research.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

High-Throughput Microfluidic Electroporation (HTME): A Scalable, 384-Well Platform for Multiplexed Cell Engineering

Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. These challenges ultimately increase the time and cost per transformation. As a result, rapidly screening genetic libraries, exploring combinatorial designs, or optimizing electroporation parameters requires extensive iterations, consuming large quantities of expensive custom-made DNA and cell lines or primary cells. To address these limitations, we have developed a High-Throughput Microfluidic Electroporation (HTME) platform that includes a 384-well electroporation plate (E-Plate) and control electronics capable of rapidly electroporating all wells in under a minute with individual control of each well. Fabricated using scalable and cost-effective printed-circuit-board (PCB) technology, the E-Plate significantly reduces consumable costs and reagent consumption by operating on nano to microliter volumes. Furthermore, individually addressable wells facilitate rapid exploration of large sets of experimental conditions to optimize electroporation for different cell types and plasmid concentrations/types. Use of the standard 384-well footprint makes the platform easily integrable into automated workflows, thereby enabling end-to-end automation. We demonstrate transformation of E. coli with pUC19 to validate the HTME's core functionality, achieving at least a single colony forming unit in more than 99% of wells and confirming the platform's ability to rapidly perform hundreds of electroporations with customizable conditions. This work highlights the HTME's potential to significantly accelerate synthetic biology Design-Build-Test-Learn (DBTL) cycles by mitigating the transformation/transfection bottleneck.

Gaillard, William R↗
DOE OSTI2026

Test cavity and Iris-to-Coax transition for tuning and high-power verification of SNS DTL iris couplers

The Spallation Neutron Source (SNS) Drift Tube Linac (DTL) employs iris couplers to efficiently deliver RF power into the accelerating structure. To support the development, tuning, and high‑power conditioning of these couplers prior to installation in the actual DTLs, a dedicated test cavity and an iris‑to‑coaxial transition structure have been designed. This work presents the electromagnetic design, simulation, and optimization of the test setup, enabling precise characterization of the iris coupler’s performance. The transition structure allows for tuning of the iris opening dimensions without requiring a waveguide taper or full‑size waveguide transitions, while maintaining impedance matching between the coaxial feed and the iris geometry to minimize reflection and power loss. During low‑power tests, the iris opening di-mensions can be evaluated using the iris‑to‑coax transi-tion attached to the test cavity. For high‑power condi-tioning, full‑size waveguides with ceramic vacuum win-dows are connected to the test cavity to replicate opera-tional conditions. Key design parameters were optimized using computer-aided simulation, and sensitivity studies were conducted to assess the impact of mechanical toler-ances on RF performance. The resulting test platform provides a reliable and efficient means for tuning and validating iris couplers, contributing to improved opera-tional stability in the SNS DTL.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗