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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Savannah River Remediation Liquid Waste Operations Making the Workplace Safer - Lean and Human Performance Improvement Initiatives - 17244

The Savannah River Site, a U.S. Department of Energy facility, contracted Savannah River Remediation (SRR) to manage its liquid waste project, which is a unique, high hazard nuclear waste treatment and disposal facility consisting of 51, one million gallon underground waste tanks, a solvent extraction processing unit, a vitrification facility for the highest radioactive waste, and a grout solidification and disposal facility for a decontaminated salt solution. Our Project mission is to treat the nuclear waste and close the associated storage and treatment facilities, of which, 8 of the 51 tanks have been closed to date. Over the past three years, SRR implemented a Lean Business Management System to address site inefficiencies, aging infrastructure concerns and budget constraints. The Lean philosophy started with the work of W. Edwards Deming and his contemporaries. In more recent years the process has matured in the Toyota Production System and migrated into fields as diverse as services industries, health-care, and now the DOE complex. Like safety, continuous improvement is a fundamental core business value that starts at the top. The Lean Business System, led by our executive management team, drives quality, production and waste elimination by focusing on People using a structured Process that allows the workforce to identify and fix problems in their workplace. Many inefficiencies and quality related issues start with the desire to make systems fail-safe without defining the core requirements for which that process or program was created. This leads to added complexity and latent or inherent human performance issues embedded within our processes. While Lean can't fix all problems, a combination of strong nuclear safety culture, robust conduct of operations, active human performance improvement process, and a business practice of continuously looking for improvements leads to excellence across our industry and creates a culture that is worthy of promoting. Without strong management, our systems fail because no one sponsors or encourages those attributes we covet. Leadership starts at the top with our customer defining what provides 'value' to them, and filters down through to the organization and ultimately the workforce in day to day conduct of operations. It is imperative that our customer drives these desirable ideals through recognition and contractual requirements to encourage and support those behavioral traits that are critical to our ongoing success.This paper focuses on how the Lean Business Management System supports those attributes that we value: a strong nuclear safety culture; disciplined conduct of operations; and a culture of robust human performance and continuous improvement. These attributes in our daily work environment propel a safer, more consistent, more efficient workplace. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
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 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 OSTI2021

Tailoring renewable materials via plant biotechnology

Plants inherently display a rich diversity in cell wall chemistry, as they synthesize an array of polysaccharides along with lignin, a polyphenolic that can vary dramatically in subunit composition and interunit linkage complexity. These same cell wall chemical constituents play essential roles in our society, having been isolated by a variety of evolving industrial processes and employed in the production of an array of commodity products to which humans are reliant. However, these polymers are inherently synthesized and intricately packaged into complex structures that facilitate plant survival and adaptation to local biogeoclimatic regions and stresses, not for ease of deconstruction and commercial product development. Herein, we describe evolving techniques and strategies for altering the metabolic pathways related to plant cell wall biosynthesis, and highlight the resulting impact on chemistry, architecture, and polymer interactions. Furthermore, this review illustrates how these unique targeted cell wall modifications could significantly extend the number, diversity, and value of products generated in existing and emerging biorefineries. These modifications can further target the ability for processing of engineered wood into advanced high performance materials. In doing so, we attempt to illuminate the complex connection on how polymer chemistry and structure can be tailored to advance renewable material applications, using all the chemical constituents of plant-derived biopolymers, including pectins, hemicelluloses, cellulose, and lignins.

09 BIOMASS FUELS↗
DOE OSTI2019

Transcriptome analysis of Aspergillus niger xlnR and xkiA mutants grown on corn Stover and soybean hulls reveals a highly complex regulatory network

BACKGROUND: Enzymatic plant biomass degradation by fungi is a highly complex process and one of the leading challenges in developing a biobased economy. Some industrial fungi (e.g. Aspergillus niger) have a long history of use with respect to plant biomass degradation and for that reason have become 'model' species for this topic. A. niger is a major industrial enzyme producer that has a broad ability to degrade plant based polysaccharides. A. niger wild-type, the (hemi-)cellulolytic regulator (xlnR) and xylulokinase (xkiA1) mutant strains were grown on a monocot (corn stover, CS) and dicot (soybean hulls, SBH) substrate. The xkiA1 mutant is unable to utilize the pentoses D-xylose and L-arabinose and the polysaccharide xylan, and was previously shown to accumulate inducers for the (hemi-)cellulolytic transcriptional activator XlnR and the arabinanolytic transcriptional activator AraR in the presence of pentoses, resulting in overexpression of their target genes. The xlnR mutant has reduced growth on xylan and down-regulation of its target genes. The mutants therefore have a similar phenotype on xylan, but an opposite transcriptional effect. D-xylose and L-arabinose are the most abundant monosaccharides after D-glucose in nearly all plant-derived biomass materials. In this study we evaluated the effect of the xlnR and xkiA1 mutation during growth on two pentose-rich substrates by transcriptome analysis. RESULTS: Particular attention was given to CAZymes, metabolic pathways and transcription factors related to the plant biomass degradation. Genes coding for the main enzymes involved in plant biomass degradation were down-regulated at the beginning of the growth on CS and SBH. However, at a later time point, significant differences were found in the expression profiles of both mutants on CS compared to SBH. CONCLUSION: This study demonstrates the high complexity of the plant biomass degradation process by fungi, by showing that mutant strains with fairly straightforward phenotypes on pure mono- and polysaccharides, have much less clear-cut phenotypes and transcriptomes on crude plant biomass.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Modeling of the Heat-Affected and Thermomechanically Affected Zones in a Ti-6Al-4V Inertia Friction Weld

Inertia friction welding has been used across the aerospace, automotive, and power-generation industries for the fabrication of complex axisymmetric components for over forty years. The process involves one axisymmetric piece being held stationary and another piece being brought into contact set to rotate about its axis of symmetry by a flywheel with the system under an applied load across the joint. Plasticization at the joint interface through the frictional heating sees the two pieces bond together. The titanium alloy Ti-6Al-4V has been widely studied for inertia welding applications. A successful selection of processing parameters (flywheel energy and mass, applied load) allows an inertia welding process which produces a very high-integrity weld, with a minimal heat-affected zone (HAZ) and thermomechanically affected zone (TMAZ), formed as a narrow band at the interface and extending further into the material. The width of this narrow band of heated material is dependent upon the process parameters used. A series of experimental inertia friction welds were performed using Ti-6Al-4V, and a finite element (FE) modeling framework was developed using the FE code Deform in order to predict the widths of the HAZ and TMAZ at the weld interface. The experimentally observed HAZ boundaries were correlated with the thermal fields from the FE model, while TMAZ boundaries were correlated with the Von Mises plastic strain fields.

42 ENGINEERING↗
DOE OSTI2018

Multi-scale and multi-technic microstructure analysis of a linear friction weld of the metastable-β titanium alloy Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti17) towards a new Post-Weld Heat Treatment

Highlights: • Soft joint showing sharp macro-zones and marked by asymmetrical process effects • Gradient of thermomechanical loads identified through progressive stages of transformation • Highly textured recrystallized β grains at the joint core with distorted β lattice • Lattices, phase fractions, microstructures and hardness homogenized after heat treatment - Abstract: Linear Friction Welding (LFW) is a solid-state joining process producing narrow joints mainly developed for the aircraft industry. The Thermo-Mechanical Processing (TMP) loads imposed on the material cause complex microstructure transformations. This study aimed at characterizing the local microstructures and crystallographic configurations to identify the mechanisms impacting the stability and the mechanical properties of a Ti17 LFW joint with the objective of establishing an innovative homogenizing Post-Weld Heat Treatment (PWHT). The process caused a narrow zone of ±2 mm from the friction interface to reach the isothermal α → β transformation temperature under a heating rate of 500 K/s followed by quenching (−100 K/s). The TMP resulted in the formation a ±3 mm wide soft Process Affected Zone (PAZ) delimited by three characteristic zones: the Welding Line (WL width ≈ 400 μm), The Thermo-Mechanically Affected Zone (TMAZ width ≈ 1 mm) and the Heat Affected Zone (HAZ). β TMP resulted in the total dissolution of the α phase in the joint core (WL + TMAZ) and formed strongly textured {110}<111> β recrystallized grains in the WL by continuous dynamic recrystallization of squeezed prior-β grains in the TMAZ. α + β TMP led to a gradual loss of hardness in the HAZ whose microstructure is similar to the one of the base material (BM) but is subject to gradual α laths dissolution due to the local temperatures experienced during LFW. A PWHT consisting in a β annealing followed by an α + β ageing resulted in a uniformly hardened weld with a homogenized Widmanstätten microstructure in the whole assembly.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PUMA:POWDER UTILIZATION MODELING APPLICATION

SF-25-084 PUMA a high performance modeling framework to simulate powder processing. It provides a scalable tool for manufacturers to simulate powder pre- and post-processing. The tool can predict the distortion, residual stress, and (for reactive processes) reaction completion fraction of complex parts after curing/debinding, sintering, and infiltration processes. These predictions are key metrics industry uses to optimize these processes to produce dense, defect-free, stable components.

HU, TIANCHEN (GARY)↗
NASA NTRS1980

Stitch-bond parallel-gap welding for IC circuits

Stitch-bonded flatpacks are superior to soldered dual-in-lines where size, weight, and reliability are important. Results should interest designers of packaging for complex high-reliability electronics, such as that used in security systems, industrial process control, and vehicle electronics.

Chvostal, P.↗
NASA NTRS1979

The evaluation of ceramic turbine stators

A ceramic turbine stator evaluation program administered by the NASA Lewis Research Center and supported by the Department of Energy is outlined. The objectives of the program are to evaluate the durability of ceramic stators over a highly dynamic automotive gas turbine duty cycle and to assess the capability of current ceramic design methodology to predict the durability of the stators over the selected duty cycle for times in excess of 200 hours. The program also provides an assessment of the ability of the ceramic industry to fabricate complex geometry monolithic stators by near-net-shape forming processes. A summary of results obtained to date is presented and future plans are discussed.

Fisher, E. A.↗
NASA NTRS2009

Collaborative Systems Thinking: A Response to the Problems Faced by Systems Engineering's 'Middle Tier'

Experienced systems engineers are adept at more than implementing systems engineering processes: they utilize systems thinking to solve complex engineering problems. Within the space industry demographics and economic pressures are reducing the number of experienced systems engineers that will be available in the future. Collaborative systems thinking within systems engineering teams is proposed as a way to integrate systems engineers of various experience levels to handle complex systems engineering challenges. This paper uses the GOES-R Program Systems Engineering team to illustrate the enablers and barriers to team level systems thinking and to identify ways in which performance could be improved. Ways NASA could expand its engineering training to promote team-level systems thinking are proposed.

Phfarr, Barbara B.↗
DOE OSTI2019

Calculation Accuracy and Efficiency of a Transient Model for Submerged Entry Nozzle Clogging

A transient numerical model was proposed and validated by the current authors for nozzle clogging (Barati et al. in Powder Technol 329:181-98, 2018). The model can reproduce the experiment in pilot scale satisfactorily. In the present article, the main objective is to validate the model for application in industry process continuous casting of steel, referring to the model accuracy and calculation efficiency. The results have shown that for the complex geometry of submerged entry nozzle (SEN), where it is difficult to create hexahedron mesh in the entire domain, a mixed mesh type is recommended, i.e., the wedge mesh for regions adjacent to SEN walls and the tetrahedron mesh for inner regions. Another challenge to the calculation of real SEN clogging is the huge number of particles involved in the industry process. An artificial factor, the N-factor, has to be introduced to reduce the calculation cost. A dimensionless number (α) is defined to limit the N-factor and ensure the modeling accuracy. Simulation of a test case has indicated that by an appropriate N-factor (1000, corresponding to α = 6 × 10{sup −5}), the calculation time would be reduced significantly to a reasonable time.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗
DOE OSTI2019

Electrochemical Machining Technology for Surface Improvements of Ni-base Superalloy Additively Manufactured Components

Additive Manufacturing’s (AM) promise and potential is of growing interest to US industries such as the energy sector. However, to move AM from prototyping to full-scale production a number of key risk areas must still be overcome, particularly the enhancing the surface finish of AM parts. Due to the industry’s desire for components fabricated from difficult to machine alloys and highly complex geometries, advanced finishing technologies are needed. This project focused on the ability to enhance the surface finish of material from the crack prone Ni-base superalloy Inconel 738 fabricated using the Arcam electron beam melting (EBM) process using the Pulsed Electrochemical Machining (PECM) process for surface enhancements. To evaluate the suitability of the PECM process, several artifacts were experimented with, each of which had increasing levels of complexity and relevancy to the industrial gas turbine sector. Ultimately, it was shown that the finish of as-built relevant EBM gas turbine airfoil surfaces could be enhanced by an average of 4x to approach an average roughness of a surface (Ra) equivalent of 1 um.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Single Pass Laser Process for Super-Hydrophobic Flexible Surfaces with Micro/Nano Hierarchical Structures

Wetting has been studied in various fields: chemical industry, automobile manufacturing, food companies, and even life sciences. In these studies, super-hydrophobic surfaces have been achieved through complex steps and processes. To realize super-hydrophobicity, however, we demonstrated a simple and single pass laser process for the fabrication of micro/nano hierarchical structures on the flexible polytetrafluoroethylene (PTFE, Teflon) surface. The fabricated hierarchical structures helped increase the hydrophobicity by augmenting the surface roughness and promoting air-trapping. In addition, we employed a low-cost and high-throughput replication process producing numerous polydimethylsiloxane (PDMS) replicas from the laser-processed PTFE film. Thanks to the anti-adhesive characteristics of PTFE and the elasticity of PDMS, the structure perfectly transferred to the replica without any mechanical failure. Moreover, our designed mesh patterns offered the possibility of large area applications through varying the process parameters (pitch, beam spot size, laser fluence, and scan speed). Even though mesh patterns had relatively large pitch (190 μm), we were able to achieve high contact angle (>150°). Through pneumatically deformed structure, we clearly showed that the shape of the droplets on our laser-processed super-hydrophobic surface was spherical. Based on these outcomes, we can expect our single laser pulse exposure process can overcome many drawbacks and offer opportunities for advancing applications of the wetting phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Coordination Chemistry and Stoichiometry of Extracted Diglycolamide Complexes of Lanthanides in Extraction Chromatography Materials

Industrial rare earth element (REE) separations predominantly utilize solvent extraction processes tailored toward conventional resources such as bastnäsite, monazite, and ion adsorption clays. Advances in diglycolamide (DGA) chemistry have shown effective extraction characteristics for REE separations. However, limitations associated with traditional DGA solvent extraction techniques, such as third-phase formation and gelling, have hindered commercial viability. By supporting DGA extractants on porous resins such as polystyrene divinyl benzene (PS-DVB), the desirable combination of solvent extraction selectivity and ease of operation of sorbent columns can be achieved. To design a low-cost model for such solid-supported DGAs, extraction characteristics as influenced by the underlying coordination chemistry must be explored to achieve efficient functional systems. Within this study, we report novel DGA resin materials, each incorporating one of the DGAs N,N,N’,N’-tetra-(1-octyl)-3-oxapentane-1,5-diamide (TODGA), N,N'-dimethyl-N,N'-dioctyl-3-oxapentane-1,5-diamide (DMDODGA), and 2,2'-oxybis(1-(3-(((2-ethylhexyl)thio)methyl)-4-methylpyrrolidin-1-yl)ethan-1-one) (DEHPDGA). The affinity of DGAs across the lanthanide (Ln) series was evaluated for both hydrochloric acid and nitric acid media with varying Ln feed concentrations to study distribution ratios and loading characteristics. Focusing on dysprosium, extended X-Ray Absorption Fine Structure (EXAFS) and density functional theory (DFT) calculations were also utilized to explore coordination chemistry and their effects on ligand performance. The general trend for both acid media resulted in DMDODGA having the highest extraction strength of all three DGAs at varying acid concentrations. Coordination-chemistry analysis supported by loading data, DFT calculations, and EXAFS results under forced loading conditions posited less than the expected 3:1 ligand-to-metal coordination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Extrusion‐Spheronization of Energetic Materials

The prevailing method to produce plastic‐bonded explosive (PBX) molding powder, or “prills”, is a complex, multiphase, and bespoke process that was developed by the high explosives (HEs) manufacturing industry several decades ago. This work demonstrates the utility of a simpler, widely‐used mechanical process—extrusion‐spheronization—to produce PBX prills. We begin by detailing precautions taken to enable safe remote operation of extrusion‐spheronization equipment with HE. We then perform a study investigating the effect of lacquer solvent composition on the particle packing, pressed density, and compressive strength properties of a 95 wt.% TATB/5 wt.% polymer binder formulation akin to PBX 9502. It was found that increased composition of low vapor pressure solvents caused prolonged retention of the solvent, resulting in tackier materials that would agglomerate and form larger prills. The larger prills also led to lower poured density and tapped density of HE prills and compressive strength of pressed PBX articles. The samples prepared with a 75% propyl acetate/25% butyl acetate lacquer solvent composition exhibited the highest compressive strength. However, it is believed that the prill packing and compressive strength properties are primarily driven by the prill size rather than the chemical composition of the lacquer itself. Extrusion‐spheronization remains a promising method to reliably and repeatably produce HE prills that is less sensitive to feedstock or process variation than traditional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗