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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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NASA NTRSDate not supplied

Series Bosch Carbon Formation Reactor Trade Study and Down-Select

Human exploration missions to Mars and other destinations beyond low Earth orbit require highly robust, reliable, and maintainable life support systems that maximize the recovery of oxygen (O2). One process in development and under consideration is the Series-Bosch System (S-Bosch). This system is a two stage reactor process that reduces carbon dioxide (CO2) with hydrogen (H2) to produce water and solid carbon. Theoretically, the Bosch process can recover 100% of the O2 from CO2 in the form of water, making it an attractive option for long duration missions. The Series Bosch system includes a reverse water gas shift (RWGS) reactor, a carbon formation reactor (CFR), a H2 extraction membrane, and a CO2extraction membrane. To further the development of oxygen recovery systems, NASA awarded Phase I contracts to several entities under the Game Changing Development Program addressing Spacecraft Oxygen Recovery (SCOR). Two of the hardware deliverables were integrated into the Carbon Dioxide Reduction Test Stand (CORTS) as carbon formation reactors and performance evaluations were executed at Marshall Space Flight Center. A trade study was performed between these two reactors along with one developed at MSFC. This paper provided the necessary information for the Advanced Exploration Systems/Life Support Systems Project (AES/LSS) managers to select a CFR for further development and discusses the process of selection.

Bosch↗
DOE OSTI2022

Performance and Economic Analysis of Organosolv Softwood and Herbaceous Lignins to Activated Carbons as Electrode Materials in Supercapacitors

In this work, yellow pine (YP, softwood) and switchgrass (SG, grass) lignins were extracted as a coproduct of an organosolv γ-valerolactone (GVL) biorefinery that also produces biofuels and furfural. The extracted lignins were converted to carbon precursors for synthesizing porous activated carbon electrodes for high energy-density supercapacitors. This research details the impact of lignin composition on the derived porous structures and electrochemical properties of activated carbons. Lignin precursors with various syringyl (S) to guaiacyl (G) contents were characterized using 31 P nuclear magnetic resonance (NMR) and two-dimensional 1 H‒ 13 C NMR. A two-step activation process, using steam and carbon dioxide as the activating agents, enabled the formation of porous carbons structures with high surface area. The capacitive behavior of supercapacitors was systematically characterized by cyclic voltammetry, charge-discharge cycling, and electrochemical impedance spectroscopy. The specific capacitance of YP and SG capacitors reached 367 and 221 F g −1 , respectively. Both types of capacitors demonstrated remarkably stable capacitance (capacitance retention >90%) along with excellent Coulombic efficiency (>99%) over 10,000 cycles. Compared to SG electrode, the better electrochemical performance achieved with YP electrodes was mainly due to shorter diffusion path, improved ionic mobility, and increased active surface area. The inexpensive lignin-based porous electrodes synthesized in this work can be used for various electrochemical devices for improved performance, decreased cost, and enhanced durability. This work also demonstrates that the selection of feedstock and appropriate processing conditions can tailor the structure of carbon composites for targeted applications. Techno-economic analysis indicates that YP and SG activated carbons can be produced at a minimum selling price of $8,493 and $6,670 per ton, respectively, which is competitive with the commercially available supercapacitor-grade activated carbons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Self-Disinfecting PPE Fabric [Factsheet]

Green Theme Technologies Inc. developed a chemical finishing technology that uses a high pressure, water-free, thermally triggered polymerization process to produce a thin conformal polymer coating around fabric fibers. This process can be used to embed selective, disinfectant chemicals to provide an anti-microbial, anti-viral finish to fabrics. In the face of COVID-19, the company hopes this process produces a permanent, laundry-durable, anti-pathogenic finish. Essentially, creating regenerative and reusable PPE.

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

Enabling Real-time Scattering Data Analysis with Scalable Optimization [Slides]

Diffraction experiments produce datasets with rich multidimensional physics information such as microstructure, equations of state, crystal structure, elastoplastic properties, and other key inputs to LANL mission-essential multiphysics models. This information is typically extracted through a process called Rietveld refinement, which involves selecting appropriate models of the instrument, crystal structure, and microstructure, identifying suitable starting values, and then fitting often hundreds of model parameters using a sequence of empirical parameter turnon/off sequences within a non-global gradient-based optimization. Extensive user expertise is required to properly setup a refinement, identify appropriate models, and select initial parameter values close to truth, such that the refinement will yield parameter values that are optimally predictive. This is a very tedious manual process performed far after the beamline campaign has ended. As facilities have become capable of generating larger volumes of data, the limitation in throughput due to Rietveld refinement has led to a dramatic increase in unanalyzed data as opposed to an intended increase in new science. In our FY22 TED, we demonstrated an integrated toolset providing near real-time automated Rietveld analysis. If this toolset can be optimized to provide automated Rietveld analysis in real-time, this could alleviate the bottleneck in unanalyzed diffraction data, aid in decision-making during experiments, and increase efficiency of the facility.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1992

State-selected chemical reaction dynamics at the S matrix level - Final-state specificities of near-threshold processes at low and high energies

State-to-state reaction probabilities are found to be highly final-state specific at state-selected threshold energies for the reactions O + H2 yield OH + H and H + H2 yield H2 + H. The study includes initial rotational states with quantum numbers 0-15, and the specificity is especially dramatic for the more highly rotationally excited reactants. The analysis is based on accurate quantum mechanical reactive scattering calculations. Final-state specificity is shown in general to increase with the rotational quantum number of the reactant diatom, and the trends are confirmed for both zero and nonzero values of the total angular momentum.

Chatfield, David C.↗
NASA NTRS1977

Processing on high efficiency solar collector coatings

Wavelength selective coatings for solar collectors are considered. Substrates with good infrared reflectivity were examined along with their susceptibility to physical and environmental damage. Improvements of reflective surfaces were accomplished through buffing, chemical polishing and other surface processing methods.

Roberts, M.↗
NASA NTRS2000

The Effect of Radiation on Selected Photographic Film

We conducted this film test to evaluate several manufacturers' photographic films for their ability to acquire imagery on the International Space Station. We selected 25 motion picture, photographic slide, and negative films from three different film manufacturers. We based this selection on the fact that their films ranked highest in other similar film tests, and on their general acceptance by the international community. This test differed from previous tests because the entire evaluation process leading up to the final selection was based on information derived after the original flight film was scanned to a digital file. Previously conducted tests were evaluated entirely based on 8 x 10s that were produced from the film either directly or through the internegative process. This new evaluation procedure provided accurate quantitative data on granularity and contrast from the digital data. This test did not try to define which film was best visually. This is too often based on personal preference. However, the test results did group the films by good, marginal, and unacceptable. We developed, and included in this report, a template containing quantitative, graphical, and visual information for each film. These templates should be sufficient for comparing the different films tested and subsequently selecting a film or films to be used for experiments and general documentation on the International Space Station.

Slater, Richard↗
DOE OSTI2023

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

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

Geology↗
NASA NTRS1988

Space-borne computing for the year 2000 and beyond

The influence and utilization of computers in space science investigations greatly enhances the ability to address difficult and complicated questions about the Universe. Space Science is wholly dependent on computers because the data acquired from instruments on the spacecraft are not only complicated in form but also voluminous. Athough a great deal of attention has been paid to develop efficient and powerful computing systems on-ground, research in the area of spaceborne computing is far from satisfactory. On-board processing of data will be important in future planetary missions where telemetry rates constrain the total amount of data which can be returned and decisions may have to be made in real time. Little thought has been given to a dynamic man-machine interface with regard to scientific real-time interactive control of flight experiments. Careful thinking is therefore essential to define appropriate spaceborne computing requirements for the future. It is imperative that powerful multiprocessing systems for on-board processing be experimentally impleneted and evaluated in selected application missions. The presentation addresses key issues and attempts to define the requirements for such processing with some of NASA's future missions in perspective. The resulting architectural and performance issues and possible developments are also addressed.

Iyer, Ravi K.↗
NASA NTRS2004

Specification, Design, and Analysis of Advanced HUMS Architectures

During the two-year project period, we have worked on several aspects of domain-specific architectures for HUMS. In particular, we looked at using scenario-based approach for the design and designed a language for describing such architectures. The language is now being used in all aspects of our HUMS design. In particular, we have made contributions in the following areas. 1) We have employed scenarios in the development of HUMS in three main areas. They are: (a) To improve reusability by using scenarios as a library indexing tool and as a domain analysis tool; (b) To improve maintainability by recording design rationales from two perspectives - problem domain and solution domain; (c) To evaluate the software architecture. 2) We have defined a new architectural language called HADL or HUMS Architectural Definition Language. It is a customized version of xArch/xADL. It is based on XML and, hence, is easily portable from domain to domain, application to application, and machine to machine. Specifications written in HADL can be easily read and parsed using the currently available XML parsers. Thus, there is no need to develop a plethora of software to support HADL. 3) We have developed an automated design process that involves two main techniques: (a) Selection of solutions from a large space of designs; (b) Synthesis of designs. However, the automation process is not an absolute Artificial Intelligence (AI) approach though it uses a knowledge-based system that epitomizes a specific HUMS domain. The process uses a database of solutions as an aid to solve the problems rather than creating a new design in the literal sense. Since searching is adopted as the main technique, the challenges involved are: (a) To minimize the effort in searching the database where a very large number of possibilities exist; (b) To develop representations that could conveniently allow us to depict design knowledge evolved over many years; (c) To capture the required information that aid the automation process.

Mukkamala, Ravi↗
NASA NTRS2006

Vapor Hydrogen Peroxide as Alternative to Dry Heat Microbial Reduction

The Jet Propulsion Laboratory, in conjunction with the NASA Planetary Protection Officer, has selected vapor phase hydrogen peroxide (VHP) sterilization process for continued development as a NASA approved sterilization technique for spacecraft subsystems and systems. The goal is to include this technique, with appropriate specification, in NPG8020.12C as a low temperature complementary technique to the dry heat sterilization process. A series of experiments were conducted in vacuum to determine VHP process parameters that provided significant reductions in spore viability while allowing survival of sufficient spores for statistically significant enumeration. With this knowledge of D values, sensible margins can be applied in a planetary protection specification. The outcome of this study provided an optimization of test sterilizer process conditions: VHP concentration, process duration, a process temperature range for which the worst case D value may be imposed, a process humidity range for which the worst case D value may be imposed, and robustness to selected spacecraft material substrates.

vapor hydrogen peroxide↗
NASA NTRS2018

Impact of Powder Variability on the Microstructure and Mechanical Behavior of Selective Laser Melted Alloy 718

Powder-bed additive manufacturing processes use fine powders to build parts layer-by-layer. Alloy 718 powder feedstocks for selective laser melting (SLM) additive manufacturing are produced commercially by both gas and rotary atomization and are available typically in the 10-45 or 15-45 microns size ranges. A comprehensive investigation was conducted to understand the impact of powder variability on the microstructure and mechanical behavior of SLM 718 heat treated to Aerospace Material Specification (AMS) 5664. This study included sixteen virgin powders and three once-recycled powders within the 10-45 and 15-45 microns size ranges that were obtained from seven direct source suppliers and one reseller. Although alike as highly regular spheroids, these powders showed distinct differences in composition (especially Al, C and N contents), particle size distributions, and powder features such as degree of agglomeration, fusion and surface roughness. Compositional differences expectedly had the strongest impact on microstructure. High N and C contents formed TiN-nitrides and/or (Nb,Ti,Mo)-C carbides on the grain boundaries, prevented recrystallization during heat treatment, and resulted in retained (001)-scalloped shaped grains that ranged from 19 to 41 microns in average size. In the absence of this particle pinning, the average grain size of the heat treated SLM 718 ranged from 51 microns to 90 microns. Room temperature tensile and high cycle fatigue (HCF) testing compared as-fabricated (AF) and low stress ground (LSG) surface conditions. Tensile testing revealed consistent behavior between the two surface conditions and amongst the powder lots. The finer grained SLM 718 builds displayed the lowest tensile properties. A SLM 718 build fabricated from a powder with eight times lower C content showed statistically better tensile properties presumably due to enhanced coarsening of (delta)-Ni3Nb precipitates. The specimens from once-recycled powders had slightly higher tensile strengths and slightly higher ductility compared to their virgin equivalents; once-recycling also did not substantially degrade the mean HCF life. The LSG fatigue lives agreed with conventionally manufactured 718 data, while AF lives exhibited a knock-down due to surface roughness. The fatigue lives of AF specimens were statistically equivalent across powder lots except for one and failures typically initiated at stress concentrators associated with SLM surface asperities. Fatigue testing of low stress ground specimens result in both transgranular and within facet crack initiations. More than half of the cracks initiated from these facets for the machined condition; however, these facets appeared to be within grains that were larger-than-average in size. A nitrogen-atomized powder with fine prior particles of TiN-nitrides and M(Ti,Nb,Mo)C carbides from atomization on powder surfaces resulted in the best fatigue performance with segregation of these particles to the SLM 718 grain boundaries leading to higher resistance to early-stage crack propagation. Typically the fine-grained builds with minor phases along the grain boundaries did not perform well in fatigue, whereas a larger-grain build with lower carbon content and coarser delta-Ni3Nb precipitates showed the next best HCF response. Further details of the build microstructure and its impact on tensile and fatigue behavior was considered.

laser deposition↗
NASA NTRS2019

Investigating Additively Manufactured 17-4 PH for Structural Applications

17-4 is used regularly to manufacture force transducers particularly for wind tunnel testing. Such applications place demanding structural requirements on the transducers with static safety factors of 1.5 common and the potential for additional dynamic loads. Additive manufacturing (AM) of transducers is very appealing because of significant potential cost and time savings as well as increased design flexibility. This study looks at the processing of 17-4 powder using selective laser melting by two different facilities using their own best practices. Hot isostatic pressing (HIP) is used by both facilities as part of the thermomechanical processing following printing to explore whether it can improve the consistency of mechanical properties. Results revealed that HIP reduced average porosity of 17-4 parts and that the yield strength of parts following solutionization and aging met wrought material property targets. Strain to failure of one of the facilities parts was less than 5% compared to greater than 9% for the other facility. Inspection of failure surfaces revealed this discrepancy could be attributed to pores (2-4% area fraction) on the failure surface of the low ductility parts. Phase content varied between the facilities with one facility producing fully martensitic parts and the other containing some retained austenite. The phase content of the starting powder and a slower than air cooling rate following the final heat treatment above the austenite eutectoid temperature are likely sources of the retained austenite. Taken together these results suggest that the current state of the art in AM 17-4 processing is sufficient for many NASA force measurement applications, but that attention is required at each stage of processing to assure desired mechanical properties.

Burns, Devin E.↗
NASA NTRS2021

Development and Characterization of Lightweight Durable Composite Conductor for Cables

Sustainable aviation in the form of electrified propulsion is likely to lead to an increase in the electrical assets contained within a single aircraft. As a result, it is desirable to design light weight conductor materials, thus reducing the payload of components like motor windings, low voltage signal cables, and transmission cables for data and power. One approach involves replacing pure Cu wiring with metalized CNT composites. This paper evaluates a framework for modeling overall conductivity and current sharing within such composites. Processing methods and parameters were refined. Select electroplated samples outperformed pure Cu in conductivity and had comparable ultimate tensile strengths. Tensile strengths are expected to improve with an additional densification step during processing. Acoustic emission data was used to predict the failure mechanism of the composite. Theories explaining improved intrinsic conductivity are discussed, with a focus on chemical and mechanical interactions at the Cu-CNT interface. These include Cu infiltration of CNT crevices, CNT oxidation, activity at defects in CNT walls, and the release of carbide-forming metals from CNT walls. Validating any or all these theories will require further work replicating data, collecting electron micrographs and conducting chemical analyses.

Metalized CNT↗
NASA NTRSDate not supplied

Behavioral Health and Performance Operations and Research in Human Spaceflight

There are two distinct functions of the Behavioral Health and Performance (BHP) specialists at NASA Johnson Space Center (JSC), with a shared goal of promoting optimal performance during all mission phases, beginning with selection to the NASA Astronaut Corps through training for and completing a spaceflight mission. The BHP Operations team is active in areas such as selection, training, routine behavioral healthcare services, and work-rest schedule. The BHP Laboratory is engaged in research in space and analog platforms to address the risks and other challenges associated with future deep space missions. Their research focuses on topics that align with the NASA Human Research Program’s Human Factors Behavioral Performance Element goals. This panel will provide details of recent work by BHP Operations and the BHP Laboratory at NASA JSC, and will demonstrate their shared goals, and contributions toward, optimizing performance and maintaining the behavioral health and well-being of astronauts during all mission phases.In 2020-2021, NASA engaged another astronaut applicant screening process to identify its 23rd group of astronaut candidates. The BHP Operations team completed a significant amount of work to evaluate applicants and provide valuable input to the Astronaut Selection Board and the Aerospace Medical Board. One presentation will provide an overview of the work completed by BHP; and one presentation will discuss a critical competency important for successful job performance of the astronauts – Team Orientation. The former will summarize aspects of BHP’s Select-in and Select-out process and provide lessons learned for future selection cycles; the latter will briefly discuss the competencies of BHP’s applicant screening work, with focus on the importance of Team Orientation and the challenges of its measure. A third presentation will provide an overview of BHP’s current fatigue management work with astronauts and mission-critical operators at JSC (e.g., flight directors, pilots), and provide a look at the direction these fatigue management services may take in future exploration missions. Two other presentations will focus on the research completed by the BHP Lab to measure in a standardized way the critical aspects of behavioral health and well-being. One of the presentations will provide an overview of the Exploration Measures being collected during all space and analog missions, and the importance these objective measures have for future research and operations. The final presentation will summarize analyses completed with these measures, as they have been harmonized across both ISS and Analog missions.

Gary Beven↗
DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗
DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A review of microwave-assisted process intensified multiphase reactors

Microwaves provide alternative heating and allow process intensification due to their rapid, volumetric, and selective nature. Recognizing the central role of multiphase reactors in chemical industry, a recent surge in employing microwaves is observed. We review the recent experimental and modeling investigations of microwave heating of multiphase reactors with emphasis on chemical engineering applications. Here we demonstrate that there is accumulated evidence for improved performance via microwave heating and a clear opportunity for further process intensification. In most of the cases, this improved performance stems from a temperature gradient between two phases. We discuss the ongoing debate on the mechanism by which microwaves affect chemical processes exacerbated by the inability of measuring the temperature distribution in a microwave cavity. We outline recent progress in this direction in monolith reactors and needs for future work. We underscore the lack of detailed modeling and simulation tools even for single-phase systems and emphasize the imperative for multiscale predictive modeling to bridge the experimental-modeling gap. Promising results are shown by a few recently published modeling studies that can predict the experimental measurements in complex multiphase reactors. A combination of experimental and modeling tools can provide a comprehensive picture of the microwave multiphase reactors as well as a means toward scale-up and optimization.

42 ENGINEERING↗