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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Optimized AC/DC Dual Active Bridge Converter using Monolithic SiC Bidirectional FET (BiDFET) for Solar PV Applications

Grid interface power conversion systems for commercial, industrial and residential solar power generation are becoming ubiquitous due to the competitive cost of solar energy. The AC/DC dual active bridge (DAB) converter is an upcoming topology in industrial PV energy and energy storage applications, providing bidirectional power transfer and galvanic isolation. In this paper, the properties of a DAB-type converter are leveraged to propose a design optimization process. It can optimize the high-frequency RMS current, size of magnetic elements and zero-voltage-switching (ZVS) region of the converter. The resulting design is compared against that derived from a conventional approach. In addition, an algorithm to compute the harmonic currents at the DC and line frequency AC ports of the system is proposed, and the respective filter designs are presented. The optimized design of the AC/DC DAB converter is implemented using the newly developed, 1200 V, 46 mΩ, four quadrant, SiC-based monolithic bidirectional FETs (BiDFET). Experimental results from the 2.3 kW, 400V/277VRMS hardware prototype are finally presented to verify the design process.

Bidirectional isolated AC-DC conversion, solar ene↗
DOE OSTI2025

PrOMMiS Tutorial

This is a tutorial on using parameter estimation and process optimization in PrOMMiS. The tutorials are publicly available in the GitHub repository. The presentation attached guides through the flow of the three different tutorials. The tutorials are presented as follows: i) Parameter estimation of oxalate precipitation, ii) Optimization of precipitation model, and iii) Optimization of full process.

critical minerals and materials↗
DOE OSTI2021

Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli.

Here, we report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

High-Power Impulse Magnetron Sputter Deposition of Boron Carbide with Full-Face Erosion Magnetron and Mixed Ar-Ne Plasma

Boron carbide (B 4 C) is an attractive inertial confinement fusion ablator material. The fabrication of B4C ablators by magnetron sputtering requires process optimization. To increase process flexibility, here we explore high-power impulse magnetron sputter (HiPIMS) deposition of B 4 C in pure Ar and mixed Ar-Ne plasmas. Here, the results show that higher plasma discharge currents can be reached with a mixed Ar-Ne plasma in the entire working pressure range studied (5 𝑡𝑜 50 mTorr). At 45 mTorr with 10% of Ne in the Ar-Ne mix, high peak target current densities of ~1 A cm −2 were demonstrated. Films deposited with such a mixed Ar-Ne plasma with a full-face erosion magnetron source on substrates biased at −25 V exhibited higher density and improved mechanical properties, albeit with higher compressive residual stresses compared to the case of HiPIMS deposition in a pure Ar plasma. This work demonstrates additional process flexibility of the HiPIMS discharge mode for the deposition of B 4 C coatings.

Ablator capsule↗
DOE OSTI2024

DeepOpt

DeepOpt is a simple and easy-to-use library for performing Bayesian optimization, leveraging the powerful capabilities of BoTorch. Its key feature is the ability to use neural networks as surrogate functions during the optimization process, allowing Bayesian optimization to work smoothly even on large datasets and in many dimensions. DeepOpt also provides simplified wrappers for BoTorch fitting and optimization routines.

Kur, Eugene↗
DOE OSTI2024

Production of Carbon Nanomaterials and Sorbents from Domestic U.S. Coal (Final Report)

The main goal of this project was to produce high-value carbon nanomaterials and carbon sorbents from domestic coal resources in a cost-effective manner. Four types of domestic coal samples were processed through a combination of deashing, devolatilization, oxidation, reduction, and activation treatments to produce graphene oxide (GO), reduced graphene oxide (RGO), and activated carbon (AC). The precursors and developed materials were extensively characterized by various methods to investigate the impact of the coal feedstock type on the yield and quality of each product. A commercial graphite-based GO sample was included in the experimental work as the baseline material for comparison with the coal-based materials developed in this work. The performed work also included a technoeconomic analysis and cost estimation for a plant processing 20 tons/day coal, a market evaluation for the graphene materials, and a technology gap analysis. A simple process by concentrated nitric acid oxidation is used to oxidize coal precursors for the production of GO. Fine oxidized coal particles that were separated from larger oxidized coal particles had significantly higher oxygen contents and were identified as coal-based GO samples. Coarse oxidized coal particles were used as precursors for production of AC. Based on the Raman spectroscopy results, coal-based GO samples exhibited G and D bands similar to those of graphite-based GO samples. X-ray photoelectron spectroscopy revealed that coal-based GO samples had surface oxygen contents of ~26-35% that were higher than the oxygen contents of graphite-based GO samples. Larger particles of oxidized coal samples were activated under different conditions to produce high surface area functionalized AC. Prepared materials had surface areas exceeding 1,500 m 2 /g and pore volumes more than 1 cm 3 /g with different pore size distributions. Reduced graphene oxide samples were prepared by thermal reduction of both coal-based and graphite-based GO samples at 170-2800 ºC. Coal-based and graphite-based RGO samples exhibited similar carbon contents, Raman spectra, and XRD profiles. Heat treatment above 1500 ºC shifted RGO to synthetic graphite. Among anthracite, bituminous, subbituminous, and lignite coals tested, anthracite was the best precursor to produce carbon nanomaterials exhibiting properties similar to those of graphite-based materials. Anthracite-based carbon nanomaterials also had the highest production yields. Technoeconomic analysis estimated the production cost of GO and RGO for anthracite-based samples at about 2,600 and 4,200 $/ton, respectively, which is about two orders of magnitude lower than the current estimated price of graphite-based materials. Several gaps to further develop the proposed technology were identified and discussed that include process and equipment optimization, process integration, need for additional bench- and pilot-scale experiments, and other items to reduce the scale up risk. Market analysis reports suggested a compound annual growth rate of 40% for graphene and related materials. Short-term applications include composites, inks, and coatings. However, energy storage applications appear to be the dominant potential long-term applications. Different applications of coal-based GO and RGO need to be explored and clear metrics and standards for each application need to be developed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Study of the Printability, Microstructures, and Mechanical Performances of Laser Powder Bed Fusion Built Haynes 230

The nickel-based superalloy, Haynes 230 (H230), is widely used in high-temperature applications, e.g., heat exchangers, because of its excellent high-temperature mechanical properties and corrosion resistance. As of today, H230 is not yet in common use for 3D printing, i.e., metal additive manufacturing (AM), primarily because of its hot cracking tendency under fast solidification. The ability to additively fabricate components in H230 attracts many applications that require the additional advantages leveraged by adopting AM, e.g., higher design complexity and faster prototyping. In this study, we fabricated nearly fully dense H230 in a laser powder bed fusion (L-PBF) process through parameter optimization. The efforts revealed the optimal process space which could guide future fabrication of H230 in various metal powder bed fusion processes. The metallurgical analysis identified the cracking problem, which was resolved by increasing the pre-heat temperature from 80 °C to 200 °C. A finite element simulation suggested that the pre-heat temperature has limited impacts on the maximum stress experienced by each location during solidification. Additionally, the crack morphology and the microstructural features imply that solidification and liquation cracking are the more probable mechanisms. Both the room temperature tensile test and the creep tests under two conditions, (a) 760 °C and 100 MPa and (b) 816 °C and 121 MPa, confirmed that the AM H230 has properties comparable to its wrought counterpart. The fractography showed that the heat treatment (anneal at 1200 °C for 2 h, followed by water quench) balances the strength and the ductility, while the printing defects did not appreciably accelerate part failure.

14 SOLAR ENERGY↗
NASA NTRS1984

Evaluation of LANDSAT-4 Thematic Mapper Data as Applied to Geologic Exploration: Summary of Results

As with any tool applied to geologic exploration, maximum value results from the innovative integration of optimally processed LANDSAT-4 data with existing pertinent information and perceptive geologic thinking. The synoptic view of the satellite images and the relatively high resolution of the data permits recognization of regional tectonic patterns and their detailed mapping. The refined spatial and spectral characteristics and digital nature surface alterations associated with hydrothermal activity and microseepage of hydrocarbons. In general, as vegetation and soil cover increase, the value of spectral components of TM data decreases with respect to the value of the spatial component of the data. This observation reinforces the experience from working with MSS data that digital processing must be optimized both for the area and for the application.

Dykstra, J. D.↗
DOE OSTI2025

Process-Microstructure-Property Relationships in Low Heat Input Wire-Arc Additive Manufacturing (WAAM) of Ni-Based Superalloy Haynes 282

Conference presentation on WAAM process optimization on Ni-based superalloy Haynes® 282®. This alloy is targeted for advanced power generation systems for its superior high temperature mechanical properties. Wire-arc additive manufacturing (WAAM) offers attractive cost and materials savings with high deposition rates. Based on initial build process optimization, WAAM blocks were made, and screened for defects using high-throughput CT scanning. The microstructural evolution in arc energy range of 250-700 J/mm was characterized in the as-built and aged conditions, using electron microscopy. Results showed self-consistent microstructure across conditions, with grain size dependence on arc energy, MC and M6C carbides in as-built, and blocky grain boundary M23C6 in as-heat-treated condition. Further reductions in as-built porosity were explored through 20+ combinations of H2 and CO2 additions to shielding gas. Initial results show improved wetting behavior, and bead overlap with up to 1% H2 and up to 0.25% CO2. Combination of experimentally determined datasets provided comprehensive understanding of process-structure-property relationships in WAAM Haynes 282.

Haynes 282↗
NASA NTRS1993

An investigation of squeeze-cast alloy 718

Alloy 718 billets produced by the squeeze-cast process have been evaluated for use as potential replacements for propulsion engine components which are normally produced from forgings. Alloy 718 billets were produced using various processing conditions. Structural characterizations were performed on 'as-cast' billets. As-cast billets were then homogenized and solution treated and aged according to conventional heat-treatment practices for this alloy. Mechanical property evaluations were performed on heat-treated billets. As-cast macrostructures and microstructures varied with squeeze-cast processing parameters. Mechanical properties varied with squeeze-cast processing parameters and heat treatments. One billet exhibited a defect free, refined microstructure, with mechanical properties approaching those of wrought alloy 718 bar, confirming the feasibility of squeeze-casting alloy 718. However, further process optimization is required, and further structural and mechanical property improvements are expected with process optimization.

Gamwell, W. R.↗
DOE OSTI2024

Recent Advances of PyROS: A Pyomo Solver for Nonconvex Two-Stage Robust Optimization in Process Systems Engineering

This poster highlights uncertainty and technical risk reduction capabilities in CCSI2, with a focus on robust optimization. It presents recent advances of the two-stage robust optimization (RO) solver PyROS and applications to advanced energy systems optimization. To demonstrate the computational performance and reliability of PyROS, a benchmarking study on a library of over 8,500 small-scale RO problems is presented. Further, PyROS is used to obtain robust system designs of a MEA-based CO2 absorber under uncertainty in the thermodynamic property models for a variety of CO2 capture rate threshold requirements. Overall, the results demonstrate that the PyROS solver, including recent extensions to multi-stage RO settings, provides a reliable avenue to optimize the design and operation of advanced energy systems subject to various sources of parametric uncertainty.

Sherman, Jason↗
DOE OSTI2024

Recent Advances of PyROS: A Pyomo Solver for Nonconvex Two-Stage Robust Optimization in Process Systems Engineering

This poster highlights uncertainty and technical risk reduction capabilities in CCSI2, with a focus on robust optimization. It presents recent advances of the two-stage robust optimization (RO) solver PyROS and applications to advanced energy systems optimization. To demonstrate the computational performance and reliability of PyROS, a benchmarking study on a library of over 8,500 small-scale RO problems is presented. Further, PyROS is used to obtain robust system designs of a MEA-based CO2 absorber under uncertainty in the thermodynamic property models for a variety of CO2 capture rate threshold requirements. Overall, the results demonstrate that the PyROS solver, including recent extensions to multi-stage RO settings, provides a reliable avenue to optimize the design and operation of advanced energy systems subject to various sources of parametric uncertainty.

Sherman, Jason↗
DOE OSTI2025

Performance Evaluation of LPBF Manufactured 316H Components

This work represents the continuation of a benchmark study that includes modeling, fabrication and characterization as demonstration to support industry’s adoption of advanced manufacturing processes in a variety of structures. This comprehensive study investigated the feasibility of using additive manufacturing (AM) technologies, specifically Laser Powder Direct Energy Deposition (LP-DED) and Laser Powder Bed Fusion (LPBF), to produce complex nuclear microreactor components using 316H stainless steel. The research focused on manufacturing an expanded elbow pipe component with transitioning sections, which are traditionally difficult and costly to produce through conventional manufacturing methods. The overall study’s primary objectives are therefore demonstrating AM viability for nuclear applications, optimizing process parameters, developing comprehensive material characterization protocols, validating computational modeling approaches, and establishing manufacturing guidelines for complex geometries. Although the initial work included the phased approach of cubical, upscaled cylindrical components, it is to enable to obtain more knowledge for the printing of the expanded elbow structure. The project achieved significant progress in process development by successfully optimizing LP-DED parameters to achieve 99.16-99.97% relative density in 316H stainless steel components. Through systematic evaluation of sixteen cube samples with varied laser powers (400-700W) and scan speeds (600-900 mm/min), optimal processing windows were identified at 500-550W with 600-700 mm/min or 650-700W with 650-900 mm/min scan speeds. The DED manufactured 316H demonstrated mechanical properties comparable or superior to wrought materials, with Young's modulus ranging from 153-208 GPa and controlled microstructural characteristics including greater than 95% face-centered cubic (FCC) phases and engineered cellular structures with sizes between 3.23-6.17 µm.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Design Process for High Speed Civil Transport Aircraft Improved by Neural Network and Regression Methods

A key challenge in designing the new High Speed Civil Transport (HSCT) aircraft is determining a good match between the airframe and engine. Multidisciplinary design optimization can be used to solve the problem by adjusting parameters of both the engine and the airframe. Earlier, an example problem was presented of an HSCT aircraft with four mixed-flow turbofan engines and a baseline mission to carry 305 passengers 5000 nautical miles at a cruise speed of Mach 2.4. The problem was solved by coupling NASA Lewis Research Center's design optimization testbed (COMETBOARDS) with NASA Langley Research Center's Flight Optimization System (FLOPS). The computing time expended in solving the problem was substantial, and the instability of the FLOPS analyzer at certain design points caused difficulties. In an attempt to alleviate both of these limitations, we explored the use of two approximation concepts in the design optimization process. The two concepts, which are based on neural network and linear regression approximation, provide the reanalysis capability and design sensitivity analysis information required for the optimization process. The HSCT aircraft optimization problem was solved by using three alternate approaches; that is, the original FLOPS analyzer and two approximate (derived) analyzers. The approximate analyzers were calibrated and used in three different ranges of the design variables; narrow (interpolated), standard, and wide (extrapolated).

Hopkins, Dale A.↗
DOE OSTI2021

Laser-based Adhesion Strength Measurements for Advanced Manufactured Sensor Adhesion Characterization

As part of the advanced manufacturing (AM) focus of the Nuclear Energy Enabling Technologies (NEET) Advanced Sensors and Instrumentation (ASI) Program, new in-house capabilities to fabricate and test novel active and passive in-pile sensors are being developed at the Idaho National Laboratory (INL). These advanced-manufactured sensors, such as peak temperature monitors and strain gauges, must be miniaturized and be able to provide real-time feedback, all while withstanding the coupled extremes of temperature and radiation typically observed in the environment of a nuclear test reactor. Fabricating durable and robust in-pile sensors with high fidelity requires a fundamental understanding of the optimal process parameters required in the AM technique, as well as the effect of deviations from optimal process parameters on the sensor-substrate adhesion and the ultimate robustness of the sensor. This report presents the use of a laser-based, non-contact approach for characterizing the adhesion of sensors manufactured using aerosol jet printing (AJP) that comprise of silver nanoparticle inks deposited and sintered on austenitic stainless steel (SS) 316L substrates. The effect of substrate surface roughness, surface energy, ink sintering time and sintering temperature on the printed sensor topography and the sensor-substrate adhesion has been systematically investigated. The sensor-substrate interfacial adhesion strength was determined from the critical laser pulse energy required to ablate/ detach the printed sensor from the substrate. Measurements of the sensor topography using optical profilometry revealed that post-deposition sintering at 400°C for 60 minutes resulted in a reduced sensor thickness, while plasma treating the substrate prior to printing yielded sensors with uniform thickness profiles transverse to the print direction. Sintering temperature and time were found to be the dominant parameters that affected sensor-substrate adhesion, followed by substrate surface roughness. The laser-based and locally-destructive approach for adhesion strength measurements shows promise in overcoming the challenges and limitations of current standardized peel tests and can be developed into a post-fabrication process control protocol for evaluating the durability of AM printed sensors in a high throughput fashion. Future studies will investigate the use of laser-induced spallation techniques as well as non-destructive laser ultrasonic methods for sensor-substrate adhesion characterization on sensors manufactured using AJP and other AM techniques such as plasma jet printing (PJP).

42 ENGINEERING↗
DOE OSTI2025

Using Separation-Enhanced Isotope Ratio Mass Spectrometry to Enable Increased Renewable Carbon Content in Transportation Fuels (CRADA 525)

Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.

09 BIOMASS FUELS↗
DOE OSTI2023

Modeling of Reactor Design and Optimization for Scale-Up of the Catalyxx Process for Ethanol Conversion to Higher Alcohol Biofuels

This report summarizes the results of a collaborative efforts between Oak Ridge National Laboratory (ORNL) and Catalyxx Inc. to investigate scale-up of Catalyxx’s Ethanol upgrading to higher alcohols process. The study was funded by the U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) under CRADA (Cooperative Research and Development Agreement) No: NFE-20-08396. The project is part of the Direct Funding Opportunity (DFO) for Computational Science to Enable Bioenergy program which utilized computational toolsets developed by the Consortium for Computational Physics and Chemistry, a multi-laboratory consortium in BETO. The report here summarizes a packed-bed reactor modeling effort spanning the range from lab to industrial scale (from 4 gram to 5-ton catalyst beds), and examining reactor design, process optimization strategies, and suggested design and operating conditions for Catalyxx’s ethanol upgrading plants. The results in this report have been shared in monthly steering meetings and presentations are available in the shared data house owned by Catalyxx. The modeling effort helped to define optimum operation conditions for maximum alcohol selectivity and yield: i.e., temperature control scenarios ranging from adiabatic to isothermal, feed rate, pressure, and inlet H 2 /Ethanol ratio. The modeling results were verified at lab-(4 gram) and pre-pilot (4 kg) scales and has been used to evaluate a 5-ton packed-bed reactor and identify operating conditions to maximize the butanol yield. Special focus was given to understanding mass-transfer effects in the pre-pilot and pilot-scale reactors, over the domain of flow rate, pressure, feed composition, pellet size, shape, porosity, bed voidage, and reactor dimensions (i.e., length/diameter). Modeling was also used to evaluate innovative reactor design concepts such as water removal to improve alcohol selectivity and yield, and a reactor with an additional side inlet to facilitate quenching. These concepts were thoroughly explored, and potential benefits were disclosed. The results in this report are summarized and described qualitatively to protect the IP rights of Catalyxx. The details have been shared with the Catalyxx team in the regular steering meetings. At the end of the project, Catalyxx Inc. announced a successful demonstration of pilot scale operation in Seville, Spain.

02 PETROLEUM↗