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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 1,099 records · Page 61

Early Impacts of a Human-in-the-Loop Evaluation in a Space Vehicle Mock-up Facility

The development of a new space vehicle, the Orion Crew Exploration Vehicle (CEV), provides Human Factors engineers an excellent opportunity to have an impact early in the design process. This case study highlights a Human-in-the-Loop (HITL) evaluation conducted in a Space Vehicle Mock-Up Facility and will describe the human-centered approach and how the findings are impacting design and operational concepts early in space vehicle design. The focus of this HITL evaluation centered on the activities that astronaut crewmembers would be expected to perform within the functional internal volume of the Crew Module (CM) of the space vehicle. The primary objective was to determine if there are aspects of a baseline vehicle configuration that would limit or prevent the performance of dynamically volume-driving activities (e.g. six crewmembers donning their suits in an evacuation scenario). A second objective was to step through concepts of operations for known systems and evaluate them in integrated scenarios. The functional volume for crewmember activities is closely tied to every aspect of system design (e.g. avionics, safety, stowage, seats, suits, and structural support placement). As this evaluation took place before the Preliminary Design Review of the space vehicle with some designs very early in the development, it was not meant to determine definitely that the crewmembers could complete every activity, but rather to provide inputs that could improve developing designs and concepts of operations definition refinement.

Byrne, Vicky↗

A Physics-Based Work-Energy Formulation for Real-Time Trajectory Guidance of A Lunar Lander

Throughout the years, many researchers have calculated and optimized trajectory solutions for lunar landing systems by employing sophisticated mathematical methods, that include: Hamilton’s Principle of Variation, Pontryagin’s maximum principle, and well known convex-optimization techniques among others. Many of these approaches typically require expensive computational resources to achieve convergence in the solution. In an effort to reduce complexity and the computational load required to obtain real-time guidance commands, a simple physics-based work-energy approach has been formulated. This approach is based on the dissipation of the mechanical energy of the vehicle to its final desired energy state required to achieve a safe landing. The rocket engine(s) employed during landing (among other maneuvers) dissipates mechanical energy by both doing work against the velocity vector of the vehicle (thus defining the trajectory path), and by jettisoning mass. Therefore, by solving the energy dissipation problem at every step of the maneuver, a much simpler formulation that naturally and quickly attains convergence is obtained. This formulation is not limited to approach, landing, and divert maneuvers, but in principle it can be employed during de-orbiting, braking burn, ascent, as well as orbit insertion.

Guidance↗

A Physics-Based Work-Energy Formulation for Real-Time Trajectory Guidance of a Lunar Lander

Throughout the years, many researchers have calculated and optimized trajectory solutions for lunar landing systems by employing sophisticated mathematical methods, that include: Hamilton’s Principle of Variation, Pontryagin’s maximum principle, and well known convex-optimization techniques among others. Many of these approaches typically require expensive computational resources to achieve convergence in the solution. In an effort to reduce complexity and the computational load required to obtain real-time guidance commands, a simple physics-based work-energy approach has been formulated. This approach is based on the dissipation of the mechanical energy of the vehicle to its final desired energy state required to achieve a safe landing. The rocket engine(s) employed during landing (among other maneuvers) dissipates mechanical energy by both doing work against the velocity vector of the vehicle (thus defining the trajectory path), and by jettisoning mass. Therefore, by solving the energy dissipation problem at every step of the maneuver, a much simpler formulation that naturally and quickly attains convergence is obtained. This formulation is not limited to approach, landing, and divert maneuvers, but in principle it can be employed during de-orbiting, braking burn, ascent, as well as orbit insertion.

Guidance↗

Algae-based sorbents for removal of gallium from semiconductor manufacturing wastewater

Gallium is increasingly used in industry, and particularly as a component of new materials that have entered semiconductor manufacturing. The release of gallium in factory’s wastewater is potentially an environmental issue and a human health concern. Utilization of algae-based sorbents in the treatment of wastewater polluted by heavy metals has been regarded as a potentially efficient and environmentally-friendly technology. Removal of gallium from simulated wastewater using dead freshwater green algae, ( Chlorella sorokiniana ), as a sorbent was studied. Both batch and continuous flow operations were investigated. Mass balance-based process models were developed and validated for both batch and flow systems. These models were found to be valuable for both understanding the process steps as well as for analyzing the experimental data and determining the fundamental kinetics and thermodynamic parameters. Adsorption capacity was found to be 14.1 mg/g at pH of 2.3, increasing to 38.5 mg/g when the pH is raised to 2.8. The effect of pH is attributed to the surface charge interactions between biomass and gallium and indicates that gallium can be acid-washed and desorbed from the biomass. This property allows for capture followed by recovery of gallium from wastewater using algae based biosorbents.

09 BIOMASS FUELS↗

Characterization of laboratory-scale hydraulic fracturing for EGS

To investigate the impact of reservoir stimulation by hydraulic fracturing, a series of advanced lab-scale block tests were conducted with multiple measurement methods to characterize the fracture and to assess the operation and the performance of an enhanced or engineered geothermal system (EGS). The stimulation test samples were 330-mm cubic blocks of Sierra White granite with one injection well and four producers drilled into it. Acoustic emissions generated during the fracture initiation and propagation were monitored with twenty AE sensors mounted on all sides of the block to help characterize the fracture initiation and propagation process. The recorded AE signals were analyzed to obtain the event location and the failure mechanism. The localized AE events shows that due to the low viscosity of the fracturing fluid (water), the fracture propagated rapidly and took only about 1.4 s to reach near the block surface. During the fracturing phase, about 47 percent of the events were determined to be shear/mixed mode failure events, 28 percent tensile failure events, and 25 percent compressional failure events. Just after the simulation, a step-rate (constant flowrate) injection test was carried out to investigate the reservoir injectivity enhancement. During this phase additional compressional failure events were observed and the percentages of tensile failure and shear/mixed mode failure decreased. The dramatic increase of the injection rate with small increments of the injection pressure demonstrates the nonlinear response of the fracture to effective normal stress variation with much higher fracture opening increase during the low effective normal stress interval. Hydraulic fracturing tests under different stress levels show that more AE hits/events are recorded when the rock block is under higher applied stress. The reconstructed 3D fracture geometry shows good agreement with the AE monitoring results. After fracturing, a tracer test was carried out and the fracture aperture was estimated to be around 139 μm. The tracer recovery curve shows two linear portions of the tracer tail on a semi-log plot similar to that observed in some field data and predicted by numerical modeling. Laser scanning of the fracture surfaces indicates that the induced fracture has a rough surface with a joint roughness coefficient (JRC) of 12.98 and tortuosity of 1.10, both of which are slightly larger than that from the Brazilian test fracture on the same rock. The thin section and SEM observations show that the fracture follows the weak boundaries between the Quartz and Albite grains or the weak beddings in the grains.

58 GEOSCIENCES↗

Towards the development of a hybrid-integrated chip interferometer for online surface profile measurements

Non-destructive testing and online measurement of surface features are pressing demands in manufacturing. Thus optical techniques are gaining importance for characterization of complex engineering surfaces. Harnessing integrated optics for miniaturization of interferometry systems onto a silicon wafer and incorporating a compact optical probe would enable the development of a handheld sensor for embedded metrology applications. In this work, we present the progress in the development of a hybrid photonics based metrology sensor device for online surface profile measurements. The measurement principle along with test and measurement results of individual components has been presented. For non-contact measurement, a spectrally encoded lateral scanning probe based on the laser scanning microscopy has been developed to provide fast measurement with lateral resolution limited to the diffraction limit. The probe demonstrates a lateral resolution of ∼3.6 μm while high axial resolution (sub-nanometre) is inherently achieved by interferometry. Further the performance of the hybrid tuneable laser and the scanning probe was evaluated by measuring a standard step height sample of 100 nm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advanced Data Science Model for Detecting Intelligent Malware

This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.

42 ENGINEERING↗

Aerogel Projects Ongoing in MSFC's Engineering Directorate

When we speak of an aerogel material, we are referring more to process and structure am to a specific substance. Aerogel, considered the lightest solid material, has been made from silica for seventy years. Resorcinol-formaldehyde, organic aerogels have been developed more recently. However, aerogel can be made from almost any type of substance, even lead. Because an aerogel is mostly air (about 99 %), the solid substance used will affect the weight very little. The term "aerogel" connotes the sol-gel process used to manufacture the material. The aerogel begins as a liquid "sol," becomes a solid "alcogel," and is then dried to become an "aerogel." The final product has a unique structure, useful for exploitation. It is an "open pore" system with nano-sized particles and pores, has very high surface area, and is highly interconnected. Besides low weight, aerogels have ultimate (lowest) values in other properties: thermal conductivity, refractive index, sound speed, and dielectric constant. Aerogels were first prepared in 1931 by Steven Kistler, who used a supercritical drying step to replace the liquid in a gel with air, preserving the structure (1). Kistler's procedure involved a water-to-alcohol exchange step; in the 1970's, this step was eliminated when a French investigator introduced the use of tetramethylorthosilicate. Still, alcohol drying involved dangerously high temperatures and pressures. In the 1980's, the Microstructured Materials Group at Berkeley Laboratory found that the alcohol in the gel could be replaced with liquid carbon dioxide before supercritical drying, which greatly improved safety (2). 'Me most recent major contribution has been that of Deshpande, Smith and Brinker in New Mexico, who are working to eliminate the supercritical drying step (3). When aerogels were first being developed, they were evaporatively dried. However, the wet gel, when dried, underwent severe shrinkage and cracking; this product was termed "xerogel." When the autoclave drying step was introduced, the final product was without cracks and showed only minimal shrinkage; this product was termed "aerogel." In the 1990's, Deshpande, Smith and Brinker developed an evaporative drying procedure in which the wet gel is chemically "capped" so that the material, which undergoes shrinkage, springs back to its original size when evaporatively dried. This new type of xerogel, while uncracked and almost the same size as the wet gel, differs from the autoclave-dried product in that it is less porous (approximately 70%, as compared to 99% for aerogels).

Shular, David A.↗

Engineering Second Sphere Interactions in a Host–Guest Multicomponent Catalyst System for the Hydrogenation of Carbon Dioxide to Methanol

Many enzymes utilize interactions extending beyond the primary coordination sphere to enhance catalyst activity and/or selectivity. Such interactions could improve the efficacy of synthetic catalyst systems, but the supramolecular assemblies employed by biology to incorporate second sphere interactions are challenging to replicate in synthetic catalysts. Herein, a strategy is reported for efficiently manipulating outer sphere influence on catalyst reactivity by modulating host–guest interactions between a noncovalently encapsulated transitionmetal-based catalyst guest and a metal–organic framework (MOF) host. This composite consists of a ruthenium PNP pincer complex encapsulated in the MOF UiO-66 that is used in tandem with the zirconium oxide nodes of UiO-66 and a ruthenium PNN pincer complex to hydrogenate carbon dioxide to methanol. Due to the method used to incorporate the complexes in UiO-66, structure–activity relationships could be efficiently determined using a variety of functionalized UiO-66-X hosts. These investigations uncovered the beneficial effects of the ammonium functional group (i.e., UiO-66-NH 3 + ). Mechanistic experiments revealed that the ammonium functionality improved efficiency in the hydrogenation of carbon dioxide to formic acid, the first step in the cascade. Isotope effects and structure–activity relationships suggested that the primary role of the ammonium functionality is to serve as a general Brønsted acid. Importantly, the cooperative influence from the host was effective only with the functional group in close proximity to the encapsulated catalyst. Here, reactions carried out in the presence of molecular sieves to remove water highlighted the beneficial effects of the ammonium functional group in UiO-66-NH 3 + and resulted in a 4-fold increase in activity. As a result of the modular nature of the catalyst system, the highest reported turnover number (TON) (19 000) and turnover frequency (TOF) (9100 h –1 ) for the hydrogenation of carbon dioxide to methanol are obtained. Moreover, the reaction was readily recyclable, leading to a cumulative TON of 100 000 after 10 reaction cycles.

08 HYDROGEN↗

How ExMC Communicates a System Model to Non-Modelers

NASA’s Human Research Program (HRP) Exploration Medical Capability (ExMC) Element adopted Systems Engineering (SE) principles and Model Based Systems Engineering (MBSE) tools to capture the system functions, system architecture, requirements, interfaces, and clinical capabilities for a future exploration medical system. There are many different stakeholders who may use the information in the model: systems engineers, clinicians (physicians, nurses, and pharmacists), scientists, and mission planners. Many of these stakeholders have neither access to MBSE modeling tools nor experience with SE modeling techniques. The challenge faced by ExMC SE team was how to present the content in the model to non-modelers in a way they would understand the content with limited training in MBSE and without using the modeling tool. ExMC SE team created a Hypertext Markup Language (HTML) report that shows key model content and is accessible to anyone with a browser. When creating the HTML report, the ExMC SE received stakeholder feedback on what content they wanted and how to display this content. Incorporating this feedback, the report arranges the content in a way that directs readers through the SE process taken to derive the requirements and helps them to understand the fundamental steps in an SE approach. The report includes links to source information (e.g., NASA documentation that describes levels of care) and other SE products (e.g., Concept of Operations). These links were provided to aid in the understanding of how the team created this content through a methodical SE approach. This presentation outlines the process used to develop the model, the data chosen to share with stakeholders, many of the model elements used in the report, the review process stakeholders followed, the comments received from the stakeholders, and the lessons ExMC learned through producing this HTML report.

J. Cohen↗

Single-Step Shear-Based Deformation Processing of Electrical Conductor Wires

Commercial electrical conductor wires are currently produced from aluminum alloys by multi-step deformation processing involving rolling and drawing. These processes typically require 10 to 20 steps of deformation, since the plastic strain or reduction that can be imposed in a single step is limited by material workability and process mechanics. Here, we demonstrate a fundamentally different, single-step approach to produce flat wire aluminum products using machining-based deformation that also ensures adequate material workability in the formed product. Two process routes are proposed: (1) chip formation by free-machining (FM), with a post-machining, light drawing reduction (<20%) to achieve desired finish and (2) constrained chip formation by large strain extrusion machining (LSEM). Using commercially pure aluminum conductor alloys (Al 1100 and EC1350) as representative material systems, we demonstrate key features of the machining-based processing, including (a) single-step processing to achieve flat wire geometries, (b) surface finish (Ra = 0.2 to 1.0 μm) comparable to that of commercial wire products made by drawing/rolling, (c) deformation control independent of wire size, and (d) hardness increases of 50–150% over that of annealed wires, while retaining high electrical conductivity (>56% IACS). Here, the wire microstructure, which can also be varied via the large-strain deformation parameters, is correlated with mechanical and electrical properties. Implications for commercial manufacture of flat wire products are discussed.

36 MATERIALS SCIENCE↗

Fuel Stratification Effects on Gasoline Compression Ignition with a Regular-Grade Gasoline on a Single-Cylinder Medium-Duty Diesel Engine at Low Load

Prior research studies have investigated a wide variety of gasoline compression ignition (GCI) injection strategies and the resulting fuel stratification levels to maintain control over the combustion phasing, duration, and heat release rate. Previous GCI research at the US Department of Energy’s Oak Ridge National Laboratory has shown that for a combustion mode with a low degree of fuel stratification, called “partial fuel stratification” (PFS), gasoline range fuels with anti-knock index values in the range of regular-grade gasoline (~87 anti-knock index or higher) provides very little controllability over the timing of combustion without significant boost pressures. On the contrary, heavy fuel stratification (HFS) provides control over combustion phasing but has challenges achieving low temperature combustion operation, which has the benefits of low NOX and soot emissions, because of the air handling burdens associated with the required high exhaust gas recirculation rates. Furthermore, this work investigates HFS and PFS combustion, efficiency, and emissions performance on a single-cylinder, medium-duty engine with a regular-grade gasoline (91 research octane number) at 1,200 rpm, 4.3 bar, and 3.0 nominal gross indicated mean effective pressure operating points with boost levels similar to those in a medium-duty diesel application. Authority of combustion phasing with main injection timing sweeps for HFS and second injection timing sweeps and fuel split sweeps for PFS are shown. In addition, this work is discussed in the context of previous findings with a light-duty diesel platform, and next steps and future direction for this work are presented.

33 ADVANCED PROPULSION SYSTEMS↗

Compact liquid nitrogen pump

The invention provides a cryogenic liquid pump system, having a first end with at least an insulating lid and motor; a second end, wherein the second end is a pump, said pump comprising an impeller; and a gas release plate upstream of the impeller; and a shaft disposed between the first end and the second end, wherein the motor imparts mechanical energy to the pump through the shaft. Also provided is a method for preventing cavitation of a cryogenic liquid in a cryogenic pump, the method having the steps of constantly maintaining pressure on the liquid in the pump and evacuating gas bubbles that form within the pump.

42 ENGINEERING↗

Understanding the stability of a plastic‐degrading Rieske iron oxidoreductase system

Abstract Rieske oxygenases (ROs) are a diverse metalloenzyme class with growing potential in bioconversion and synthetic applications. We postulated that ROs are nonetheless underutilized because they are unstable. Terephthalate dioxygenase (TPA DO PDB ID 7Q05 ) is a structurally characterized heterohexameric α 3 β 3 RO that, with its cognate reductase (TPA RED ), catalyzes the first intracellular step of bacterial polyethylene terephthalate plastic bioconversion. Here, we showed that the heterologously expressed TPA DO /TPA RED system exhibits only ~300 total turnovers at its optimal pH and temperature. We investigated the thermal stability of the system and the unfolding pathway of TPA DO through a combination of biochemical and biophysical approaches. The system's activity is thermally limited by a melting temperature ( T m ) of 39.9°C for the monomeric TPA RED , while the independent T m of TPA DO is 50.8°C. Differential scanning calorimetry revealed a two‐step thermal decomposition pathway for TPA DO with T m values of 47.6 and 58.0°C (Δ H = 210 and 509 kcal mol −1 , respectively) for each step. Temperature‐dependent small‐angle x‐ray scattering and dynamic light scattering both detected heat‐induced dissociation of TPA DO subunits at 53.8°C, followed by higher‐temperature loss of tertiary structure that coincided with protein aggregation. The computed enthalpies of dissociation for the monomer interfaces were most congruent with a decomposition pathway initiated by β‐β interface dissociation, a pattern predicted to be widespread in ROs. As a strategy for enhancing TPA DO stability, we propose prioritizing the re‐engineering of the β subunit interfaces, with subsequent targeted improvements of the subunits.

59 BASIC BIOLOGICAL SCIENCES↗

Validation and Verification for INL Modelica-based TEDS models Via Experimental Results

This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Practical Application of Model-based Programming and State-based Architecture to Space Missions

A viewgraph presentation to develop models from systems engineers that accomplish mission objectives and manage the health of the system is shown. The topics include: 1) Overview; 2) Motivation; 3) Objective/Vision; 4) Approach; 5) Background: The Mission Data System; 6) Background: State-based Control Architecture System; 7) Background: State Analysis; 8) Overview of State Analysis; 9) Background: MDS Software Frameworks; 10) Background: Model-based Programming; 10) Background: Titan Model-based Executive; 11) Model-based Execution Architecture; 12) Compatibility Analysis of MDS and Titan Architectures; 13) Integrating Model-based Programming and Execution into the Architecture; 14) State Analysis and Modeling; 15) IMU Subsystem State Effects Diagram; 16) Titan Subsystem Model: IMU Health; 17) Integrating Model-based Programming and Execution into the Software IMU; 18) Testing Program; 19) Computationally Tractable State Estimation & Fault Diagnosis; 20) Diagnostic Algorithm Performance; 21) Integration and Test Issues; 22) Demonstrated Benefits; and 23) Next Steps

Mission Data System (MDS)↗

Trends in Field and Laboratory Performance of Photovoltaic Modules and Materials

This DuraMAT project intends to identify bill of materials (BOM) and/or process control measures for photovoltaic modules with representative failure modes as informed by accelerated and field tests to guide next steps in module and material design. We have begun work to identify correlation between module field performance and accelerated testing results by cross-comparing a module database of accelerated test results with a module database of fielded systems. We have identified fielded systems with degraded performance, and intend to compare this to the results observed in certification and qualification testing. We also intend to apply lessons and observations from accelerated tests to the field, where it may be possible to mitigate or avoid degradation in the field.

DuraMAT↗

Directed Energy Deposition Process Modeling, Validation, and Process-Informed Optimization

The directed energy deposition (DED) process, one of the most popular additive manufacturing techniques in use today, involves various complex physical mechanisms that are not yet well understood. In this regard, computational tools show promise for elucidating the manufacturing process and enabling nondestructive performance evaluations of manufactured parts. To better control and optimize the DED process?thereby improving the manufactured product? the present work develops and demonstrates a novel artificial intelligence (AI)-based process control and optimization technique. Specifically, a geometry-free thermo-mechanical model with adaptive subdomain construction is developed to accurately capture the material?s thermo-mechanical response under cyclical reheating and high cooling rates [1]. The model is demonstrated and validated with experimental measurements, in light of various geometries and processing parameters. Moreover, based on this thermo-mechanical model, a physics-informed reduced-order model is developed to enable quick predictions of the temperature field at every time step. Furthermore, an AI-based controller is developed that can adapt to the ever-changing system states by automatically adjusting the manufacturing process parameters. This entire work is based on the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) [2] and its recent integration with Libtorch (the C++ frontend of PyTorch [3]). The combined development of the adaptive material deposition scheme, thermo-mechanical model, associated reduced-order model, and AI-based process controller carries great potential for improving advanced manufacturing processes.

36 MATERIALS SCIENCE↗