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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 1,549 records · Page 86

All sources NASA NTRS DOE OSTI

NASA NTRS2012

Friction Pull Plug Welding in Aluminum Alloys

NASA's Marshall Space Flight Center (MSFC) has recently invested much time and effort into the process development of Friction Pull Plug Welding (FPPW). FPPW, is a welding process similar to Friction Push Plug Welding in that, there is a small rotating part (plug) being spun and simultaneously pulled (forged) into a larger part. These two processes differ, in that push plug welding requires an internal reaction support, while pull plug welding reacts to the load externally. FPPW was originally conceived as a post proof repair technique for the Space Shuttle fs External Tank. FPPW was easily selected as the primary weld process used to close out the termination hole on the Constellation Program's ARES I Upper Stage circumferential Self-Reacting Friction Stir Welds (SR-FSW). The versatility of FPPW allows it to also be used as a repair technique for both SR-FSW and Conventional Friction Stir Welds. To date, all MSFC led development has been concentrated on aluminum alloys (2195, 2219, and 2014). Much work has been done to fully understand and characterize the process's limitations. A heavy emphasis has been spent on plug design, to match the various weldland thicknesses and alloy combinations. This presentation will summarize these development efforts including weld parameter development, process control, parameter sensitivity studies, plug repair techniques, material properties including tensile, fracture and failure analysis.

Brooke, Shane A.↗

NASA NTRS2007

The Buffer-Gas Positron Accumulator and Resonances in Positron-Molecule Interactions

This is a personal account of the development of our buffer-gas positron trap and the new generation of cold beams that these traps enabled. Dick Drachman provided much appreciated advice to us from the time we started the project. The physics underlying trap operation is related to resonances (or apparent resonances) in positron-molecule interactions. Amusingly, experiments enabled by the trap allowed us to understand these processes. The positron-resonance "box score" to date is one resounding "yes," namely vibrational Feshbach resonances in positron annihilation on hydrocarbons; a "probably" for positron-impact electronic excitation of CO and NZ;an d a "maybe" for vibrational excitation of selected molecules. Two of these processes enabled the efficient operation of the trap, and one almost killed it in infancy. We conclude with a brief overview of further applications of the trapping technology discussed here, such as "massive" positron storage and beams with meV energy resolution.

Surko, C.M.↗

NASA NTRSDate not supplied

Adaptive Learning for Reliability Analysis using Support Vector Machines

A novel algorithm is presented for adaptive learning of an unknown function that separates two regions of a domain.In the context of reliability analysis these two regions represent the failure domain, where a set of constraints or requirements are violated, and a safe domain where they are satisfied. The Limit State Function (LSF) separates these two regions. Evaluating the constraints for a given parameter point requires the evaluation of a computational model that may well be expensive. For this reason we wish to construct a meta-model that can estimate the LSFas accurately as possible, using only a limited amount of training data. This work presents an adaptive strategy employing a Support Vector Machine (SVM) as a meta-model to provide a semi-algebraic approximation of the LSF.We describe an optimization process that is used to select informative parameter points to add to training data at each iteration to improve the accuracy of this approximation. A formulation is introduced for bounding the predictions of the meta-model; in this way we seek to incorporate this aspect of Gaussian Process Models (GPMs) within anSVM meta-model. Finally, we apply our algorithm to two benchmark test cases, demonstrating performance that is comparable with, if not superior, to a standard technique for reliability analysis that employs GPMs

Adaptive learning↗

DOE OSTI2022

A review study of rare Earth, Cobalt, Lithium, and Manganese in Coal-based sources and process development for their recovery

The world’s majority predominantly relies on foreign sources for supplying critical minerals. This renders the countries susceptible to supply chain disruption and urges them to develop alternative sources to compete in technological advancements. Among many proven newly identified sources, coal and coal-based materials present their opportunities. Due to the complex structure of coal, many mineral forms can be found in coal-related sources, including critical element-containing minerals. Among the fifty critical elements and minerals defined by the USGS, the rare earth elements, cobalt, lithium, and manganese, are particularly significant as they have enormous importance in high-technology product development. These critical metals can be found in high concentrations in coal-derived sources, such as coal refuse, coal combustion products, and coal acid mine drainage, and be recovered through various separation techniques. Further, this study aims to advance the understanding of these elements' extraction and commercial potential from coal and coal-related sources and help address the world's challenges in the critical mineral supply chain. The concentrations and occurrences of these four commodities in coal-related sources were first reviewed. Later, their recovery processes were discussed, and a conceptual process flowsheet was proposed to selectively recover the rare earth elements, lithium, cobalt, and manganese from coal-based sources.

58 GEOSCIENCES↗

DOE OSTI2025

Development of a bench-scale dissolution concept for the direct extraction of nuclear fuel

Current used nuclear fuel reprocessing efforts utilize a hydrometallurgical approach in which the UNF is dissolved in hot nitric acid followed by solvent extraction into an organic solvent to harvest target nuclides. Previous studies have shown that the dissolution and loading process could be combined into a single organic dissolution/extraction step, producing loaded organic in a single step process. This single step process also includes the advantage of selectively targeting key nuclides in the dissolution while leaving undesirable constituents as part of the undissolved solids. This process is referred to hereafter as direct extraction. Ongoing research from multiple national labs has proven the effectiveness of this technique at research scale. Therefore, potential methods to implement direct extraction at both bench and industrial scale have been developed. The key features of potential dissolver system designs were identified via the team at Pacific Northwest National Laboratory and several designs based on industrial counterparts were assessed for feasibility. This report summarizes the advantages and disadvantages of multiple methods, concluding with a path forward to create multiple unique dissolver designs. The first design will be a single stage recirculating eductor mixer. The second design recommendation is a stator rotor static mixing flow loop design. Each dissolver could be utilized separately, simultaneously, or in series to answer questions surrounding reaction kinetics including residence time, provide a proof of concept for targeted extractions of specific nuclides, and inform needs for industrial scale implementation

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1991

Application of a design-build-team approach to low cost and weight composite fuselage structure

Relationships between manufacturing costs and design details must be understood to promote the application of advanced composite technologies to transport fuselage structures. A team approach, integrating the disciplines responsible for aircraft structural design and manufacturing, was developed to perform cost and weight trade studies for a twenty-foot diameter aft fuselage section. Baseline composite design and manufacturing concepts were selected for large quadrant panels in crown, side, and keel areas of the fuselage section. The associated technical issues were also identified. Detailed evaluation of crown panels indicated the potential for large weight savings and costs competitive with aluminum technology in the 1995 timeframe. Different processes and material forms were selected for the various elements that comprise the fuselage structure. Additional cost and weight savings potential was estimated for future advancements.

Ilcewicz, L. B.↗

NASA NTRSDate not supplied

Effect of Boundary Conditions on Process-Induced Stresses in a Plain Weave Unit Cell

Woven polymer matrix composites (PMCs) are leveraged in aerospace applications for their desirable specific properties, yet they are vulnerable to high residual stresses during manufacturing and their complex geometry makes experimental results difficult to observe. Process modeling is needed to characterize the effects of the curing and predict end stress states. Finite element software can be used to model woven architectures, however accurate representation of processing conditions remains a challenge when it comes to selecting boundary conditions. The effect of BCs on process-induced stress within woven PMCs is studied. The commercial Finite Element Analysis (FEA) software Abaqus is coupled with user-written subroutines in a process modeling framework. A two-dimensionally (2D) woven PMC repeating unit cell (RUC) is modeled with TexGen and Abaqus. Virtual curing is imposed on the bulk matrix. The BC study is conducted with Free, Periodic, Flat, and Flat-Free configurations. Results show that the end stress state is sensitive to the boundary condition assumptions. Flat BC results show great agreement with Periodic BCs. Residual stress results from process modeling are then compared with a linear-elastic thermal cooldown analysis in Abaqus. Cooldown results indicate an overestimation in matrix stresses compared with process modeling.

micromechanics↗

NASA NTRS2021

Automated Data Accountability for Missions in Mars Rover Data

As the Mars Curiosity Rover transmits data to the JPL Ground Data System (GDS), it frequently observes data loss and corruption, requiring re-transmits from the rover and Ground Data System Analysts (GDSA) to monitor the downlink process. As new missions are launched, the GDSA team redistributes analysts to these new missions, causing shortages in previous missions. The GDSA team can significantly benefit from the automation and optimization of the downlink process of telemetry data. In fact, there is a need for a better understanding of why the data is corrupted, so that the GDSA team can best determine the root cause of the issues in the GDS. This paper presents machine learning and deep learning based approaches to automate and optimize the detection of data loss. We first created a pipeline to automatically accumulate data from the telemetry databases (MAROS, Telemetry Data Storage, and GDS Elastic Search Database) in the downlink process. With our newly created datasets, we perform feature selection to supplement the GDSA understanding of the downlink process and provide supplemental analysis on the importance of different features. We implement various machine learning and deep learning based models, including support vector machines, ensemble methods, and deep neural networks and evaluate their accuracies in identifying whether a downlink process is complete or incomplete. We utilize fast hyperparameter optimization methods that allow our models to quickly be re-trained, allowing them to quickly be tuned and optimized on daily incoming data in real time. This hyperparameter optimization also allows our methods to be quickly integrated into other JPL missions. Our results show that our best-performing machine learning and deep learning based models outperform the existing GDSA detection software by 6 accuracy points and can aid analysts by providing insights into the data accountability problem. Since these various machine learning and deep learning approaches vary significantly in interpretability, we provide a discussion on the tradeoffs between their performance and trustworthiness in helping detect issues in data transmission.

Divsalar, Dariush↗

DOE OSTI2026

Microstructure prediction for Ti-22Al-25Nb in laser powder bed fusion

This work presents a physics-informed framework for predicting solidification morphology and defect susceptibility in additively manufactured Ti–22Al–25Nb across a broad processing space. The framework integrates solidification microstructure selection (SMS) analysis with a single-track defect-based printability map to establish a unified methodology linking processing parameters to both interfacial morphology and manufacturability. Thermal gradients G and solidification rates R are first computed using the Thermo-Calc Additive Manufacturing (TC-AM) module, a finite-interface-dissipation (FID) phase-field (PF) model coupled with CALPHAD method is then employed to systematically distinguish planar and dendritic regimes as functions of $G$ and $R$. By superimposing the printability map onto the morphology projections, a comprehensive process–structure framework is obtained. Across most processing conditions, the predicted microstructure is predominantly dendritic, while planar growth emerges only under selected laser power $P$ and scan speed $v$ combinations. In addition to morphology classification, the framework quantifies the dendritic area fraction and introduces a width-based morphology descriptor to characterize the spatial extent of planar/dendritic regions within the melt pool. It provides mechanistic insight into the interplay between solidification physics and defect formation, offering practical guidance for parameter selection and microstructural control in Ti–22Al–25Nb additive manufacturing (AM).

36 MATERIALS SCIENCE↗

NASA NTRS1986

Noise-driven sidebranching in the boundary-layer model of dendritic solidification

In the context of local models of solidification, it is suggested that the sidebranching which appears to be a characteristic feature of dendritic processes may be generated by selective amplification of noise near the tip and that, under some circumstances, thermal fluctuations may be strong enough to explain the observed effects. This proposal is discussed based on the two-dimensional boundary-layer model with kinetic crystalline anisotropy. Experimental methods to distinguish this stochastic process from a deterministic, dynamical sidebranching mechanism are suggested, including the possibility of space-based experiments.

Pieters, R.↗

DOE OSTI2024

Reductive catalytic fractionation of cotton stalks: catalytic strategy for tuning the selectivity of phenolic monomers

Pretreatment of lignocellulosic biomass is a primary step to delink lignin from the lignin-carbohydrate complex for bioethanol production and other value-added products. Presently, these processes yield lignin (technical) with significant structural changes compared to native lignin and make it difficult to valorize. Reductive catalytic fractionation (RCF) is an advanced pretreatment process to valorize native lignin to selective phenolic monomers before capitalizing on carbohydrates. Herein, cotton stalks (CS) were pretreated with ethanol: water mixture catalyzed by bimetallic, Ru-Ni/HY (RNY) and Ru-Fe/HY (RFY), and trimetallic, Ru-Fe-Ni/HY (RFNY), catalysts using the endogenously produced H 2 . The favorable catalytic properties of the RFNY catalyst, including high reducibility, acidity, metal dispersion, the synergistic effect of all the metals, and appropriate pore and particle size resulted in the highest catalytic activity. Maximum 92% delignification efficiency was achieved with 91% holocellulose retention. The extracted lignin after depolymerization in the same step produced a 19 wt.% yield of phenolic monomers. Increasing the duration of the reaction from 2 to 6 h increased the selectivity to saturated alkyl chain phenolics (1 to 16 wt.%) at the expense of hemicellulose (50 to 9%). The fate of carbohydrates left behind after the RCF (CS-RCF) process was analyzed through enzymatic saccharification and compared with raw CS and acid-pretreated CS. In conclusion, CS-RCF yielded maximum glucose yield (45 g/L) within an incubation period of 72 h.

09 BIOMASS FUELS↗

DOE OSTI2022

Variant selection in laser powder bed fusion of non-spherical Ti-6Al-4V powder

The presence of α/α' on prior β/β grain boundaries directly impacts the final mechanical properties of the titanium alloys. The β/β grain boundary variant selection of titanium alloys has been assumed to be unlikely owing to the high cooling rates in laser powder bed fusion (L-PBF). However, we hypothesize that powder characteristics such as morphology (non-spherical) and particle size (50–120 µm) could affect the initial variant selection in L-PBF processed Ti-6Al-4V alloy by locally altering the cooling rates. Despite the high cooling rate found in L-PBF, the results showed the presence of β/β grain boundary α' lath growth inside two adjacent prior β grains. Electron backscatter diffraction micrographs confirmed the presence of β/β grain boundary variant selection, and synchrotron X-ray high-speed imaging observation revealed the role of the “shadowing effect” on the locally decreased cooling rate because of keyhole depth reduction and the consequent β/β grain boundary α' lath growth. The self-accommodation mechanism was the main variant selection driving force, and the most abundant α/α boundary variant was type 4 (63.26°//[ $\bar{10}$ 5 5 $\bar{3}$ ]). The dominance of Category II α lath clusters associated with the type 4 α/α boundary variant was validated using the phenomenological theory of martensite transformations and analytical calculations, from which the stress needed for the β→α' transformation was calculated.

36 MATERIALS SCIENCE↗

NASA NTRS2003

Sleep deprivation influences some but not all processes of supervisory attention

Does one night of sleep deprivation alter processes of supervisory attention in general or only a specific subset of such processes? Twenty college-aged volunteers, half female, performed a choice reaction time task. A cue indicated that compatible (e.g., right button, right-pointing arrow) or incompatible (e.g., left button, right-pointing arrow) responses were to be given to a stimulus that followed 50 or 500 ms later. The paradigm assessed response inhibition, task-shifting skill, and task strategy-processes inherent in supervisory attention. Performance, along with heart rate, was assessed for 12 hr following normal sleep or a night of complete sleep deprivation. Sleep deprivation altered neither preparation for task shifting nor response inhibition. The ability to use preparatory bias to speed performance did decrease with sleep deprivation. Sleep deprivation appears to selectively affect this supervisory attention process, which is perceived as an active effort to cope with a challenging task.

NASA Discipline Regulatory Physiology↗

NASA NTRS1979

Very high speed processing: Applicability of peripheral devices to pixel-dependent tasks

Early options studied in the satisfaction of LACIE implementation computational demands are described as well as the ultimate selection and development of an array processing solution to the problem. The economic justification, as a function of required LANDSAT analysis, is provided. The suitability of such processors for LACIE and other applications is discussed.

Lyon, J. C.↗

NASA NTRSDate not supplied

Additive Manufacturing for Rocket Propulsion Applications

Metal Additive manufacturing (AM) is changing how components are being fabricated for current and next generation spaceflights. AM provides many advantages including cost and schedule reduction, enhanced complexity for light-weighting, consolidation of parts, and improved performance using novel alloys and improved designs. This presentation will highlight some of the use cases of AM in rocket propulsion applications, the various processes and attributes for proper selection, and the integrated lifecycle for proper AM use. As AM evolves, there is a need to better understand these lifecycle design constraints such as geometry, microstructure and resulting properties, and surface texture for proper implementation. Ongoing research is being conducted on integral channel heat exchangers, such as combustion chambers and nozzles, using some of the AM processes. The presentation will conclude with a focus on this AM heat exchanger research and how it may be applied for future spaceflight.

Additive Manufacturing↗

DOE OSTI2024

Sustainable valorization of waste tires: Selective hydrotreating for renewable p-cymene production

The escalating global concern over waste tire management driven by the surge in automobiles necessitates sustainable and innovative solutions. Here, this study posits a novel approach by introducing a selective catalytic hydrogenation and dehydrogenation process using a tandem two-stage pressurized fixed-bed reactor, aiming to convert waste tires into valuable sulfur-free p-cymene. The experimental results indicate that among the studied catalysts including Pt/C, Pd/C, Ru/C, and Ni/Al 2 O 3 -SiO 2 , the Pd/C exhibits concomitant hydrogenation and dehydrogenation functionalities, achieving full conversion and displaying 100 % selectivity towards p-cymene from limonene model compound. Furthermore, the Pd/C catalyst demonstrates remarkable efficiency in converting real-world waste tires into p-cymene, yielding up to 134.8 mg/g at optimal conditions. Importantly, this catalyst also facilitates complete hydrodesulfurization activity, addressing environmental concerns by producing sulfur-free liquid products. This innovative method not only optimizes p-cymene synthesis from waste tires but also contributes to environmental sustainability, showcasing both economic and ecological viability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1981

Coal conversion systems design and process modeling. Volume 1: Application of MPPR and Aspen computer models

The development of a coal gasification system design and mass and energy balance simulation program for the TVA and other similar facilities is described. The materials-process-product model (MPPM) and the advanced system for process engineering (ASPEN) computer program were selected from available steady state and dynamic models. The MPPM was selected to serve as the basis for development of system level design model structure because it provided the capability for process block material and energy balance and high-level systems sizing and costing. The ASPEN simulation serves as the basis for assessing detailed component models for the system design modeling program. The ASPEN components were analyzed to identify particular process blocks and data packages (physical properties) which could be extracted and used in the system design modeling program. While ASPEN physical properties calculation routines are capable of generating physical properties required for process simulation, not all required physical property data are available, and must be user-entered.

Source record↗

NASA NTRS1994

Facility design consideration for continuous mix production of class 1.3 propellant

In November of 1989, NASA awarded the Advanced Solid Rocket Motor (ASRM) contract to Lockheed Missiles and Space Company (LMSC) for production of advanced solid rocket motors using the continuous mix process. Aerojet ASRM division (AAD) was selected as the facility operator and RUST International Corporation provided the engineering, procurement, and construction management services. The continuous mix process mandates that the mix and cast facilities be 'close-coupled' along with the premix facilities, creating unique and challenging requirements for the facility designer. The classical approach to handling energetic materials-division into manageable quantities, segregation, and isolation-was not available due to these process requirements and quantities involved. This paper provides a description of the physical facilities, the continuous mix process, and discusses the monitoring and detection techniques used to mitigate hazards and prevent an incident.

Williamson, K. L.↗