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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 775 records · Page 43

All sources NASA NTRS DOE OSTI

NASA NTRS2004

Effect of Surface Impulsive Thermal Loads on Fatigue Behavior of Constant Volume Propulsion Engine Combustor Materials

The development of advanced high performance constant-volume-combustion-cycle engines (CVCCE) requires robust design of the engine components that are capable of enduring harsh combustion environments under high frequency thermal and mechanical fatigue conditions. In this study, a simulated engine test rig has been established to evaluate thermal fatigue behavior of a candidate engine combustor material, Haynes 188, under superimposed CO2 laser surface impulsive thermal loads (30 to 100 Hz) in conjunction with the mechanical fatigue loads (10 Hz). The mechanical high cycle fatigue (HCF) testing of some laser pre-exposed specimens has also been conducted under a frequency of 100 Hz to determine the laser surface damage effect. The test results have indicated that material surface oxidation and creep-enhanced fatigue is an important mechanism for the surface crack initiation and propagation under the simulated CVCCE engine conditions.

Zhu, Dongming↗

NASA NTRS2013

Development of the Orion Crew-Service Module Umbilical Retention and Release Mechanism

The Orion Crew-Service Module umbilical retention and release mechanism supports, protects and disconnects all of the cross-module commodities between the spacecraft's crew and service modules. These commodities include explosive transfer lines, wiring for power and data, and flexible hoses for ground purge and life support systems. Initial development testing of the mechanism's separation interface resulted in binding failures due to connector misalignments. The separation interface was redesigned with a robust linear guide system, and the connector separation and boom deployment were separated into two discretely sequenced events. Subsequent analysis and testing verified that the design changes corrected the binding. This umbilical separation design will be used on Exploration Flight Test 1 (EFT-1) as well as all future Orion flights. The design is highly modular and can easily be adapted to other vehicles/modules and alternate commodity sets.

Delap, Damon↗

NASA NTRS2011

Low-Thermal Conductivity Suspensions Used in the Isolation of the Salt Pills Aboard the Astro-H Adiabatic Demagnetization Refrigerator

An adiabatic demagnetization refrigerator (ADR) utilizes the magnetocholoric effect in a paramagnetic salt to produce sub-Kelvin temperatures. It is a solid-state device that has no moving parts and does not rely upon a density gradient in a working fluid. This makes it ideal for cooling space-based instruments. ·Typically the salt is enclosed in a cylindrical pill that is suspended within the bore of a magnet. The suspension between the salt pill and magnet must be robust enough to survive a launch yet have a thermal conductance that minimizes heat from the magnet that is mechanically, and thermally, anchored to a stage at a higher temperature. Here we detail such a design that uses Kevlar(Trade Mark) as the supporting media in a system that limits motion of the salt pill axial as well as laterally with respect to the magnet bore.

Kimball, Mark O.↗

NASA NTRSDate not supplied

A Method for Validating Causal Diagrams of Human Health Risk in Space Flight

The complexity of cause-and-effect relationships between spaceflight hazards and resulting health conditions clouds understanding of the totality of human system risk in space. In response, NASA has introduced Directed Acyclic Graphs (causal diagrams) into the human systems risk management process. These diagrams allow for a common understanding of the mechanisms that lead from unique hazards of spaceflight to the health outcomes important to agencies and astronauts. However, the paucity of available biomedical data from spaceflight creates a need for methods of validating causal models that can accommodate data from spaceflight model analogs. Here we outline one approach utilizing open-access rodent bone datasets from the Ames Life Sciences Data Archive. The properties of directed acyclic graphs themselves can provide an epistemological and statistical framework for validation of a priori causal representations of human system risk in space flight. The assumed causal connections on the graph creates sets of logical implications: variables that – if the causal diagram is correct – should be correlated, as well as sets that should be conditionally independent. By testing these implied correlations and conditional independencies both statistically and heuristically, we can provide evidence for or against specific causal pathways on the causal diagram. In addition to validation of expert-generated causal diagrams, machine learning techniques can learn the most likely structure of a causal diagram from a given dataset. Comparison with and reconciliation between machine-learned causal diagrams and expert-generated diagrams is another technique for challenging assumptions and improving our understanding of causal mechanisms. Accurately representing complex causation is essential to systemic understanding of human health risks in space travel. Having a robust system of validating causal diagrams helps us arrive at more accurate representations of causal systems. This process will be integral to developing the countermeasures necessary for extended exploration of the moon and Mars.

Robert Reynolds↗

DOE OSTI2021

Process Robustness of Friction Stir Dovetailing of AA7099 to Steel with In Situ AA6061 Interlayer Linking

Rolled homogeneous armor (RHA) steel was joined to aluminum alloy AA7099-T7451 with an interlayer of AA6061-T651 by single-pass friction stir dovetailing (FSD). The evolution of the AA7099/AA6061 and AA6061/steel interfacial microstructures and mechanical properties of the joints were examined. The AA6061 interlayer prevented Zn migration from the AA7099 to the steel during FSD and inhibited formation of brittle, Zn-rich, Fe-Al intermetallic compounds within the joint. The flow of the dissimilar aluminum alloys at the interface was controlled with a partially threaded friction stir welding pin and a dovetail geometric configuration optimized in previous work. The process robustness was explored to establish parameter windows by elucidating parametric effects on the relationship between process conditions and the joint’s microstructure and mechanical properties. Ranges of process forge force (50–70 kN) and interface temperature (475°C–515°C) consistently yielded joints with adequate performance. The load-carrying capacity in lap shear tensile tests was 2025 ? 100 N/mm.

Friction Stir Dovetailing, FSW, AA7099, AA6061, Ro↗

DOE OSTI2021

Multiscale Modeling Meets Machine Learning: What Can We Learn?

Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where we have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. This is a field where classical physics-based simulation seems to remain irreplaceable. In this review, we identify areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another: Machine learning can integrate physics-based knowledge in the form of governing equations, boundary conditions, or constraints to manage ill-posted problems and robustly handle sparse and noisy data; multiscale modeling can integrate machine learn- ing to create surrogate models, identify system dynamics and parameters, analyze sensitivities, and quantify uncertainty to bridge the scales and understand the emergence of function. With a view towards applications in the life sciences, we discuss the state of the art of combining machine learning and multiscale modeling, identify applications and opportunities, raise open questions, and address potential challenges and limitations. We anticipate that it will stimulate discussion within the community of computational mechanics and reach out to other disciplines including mathematics, statistics, computer science, artificial intelligence, biomedicine, systems biology, and precision medicine to join forces towards creating robust and efficient models for biological systems.

machine learning, multiscale modeling, physics-bas↗

NASA NTRS1999

Thermal and Mechanical Microspacecraft Technologies for Deep Space Systems Program X2000 Future Deliveries

Thermal and mechanical technologies are an important part of the Deep Space Systems Technology (DSST) Program X2000 Future Deliveries (FD) microspacecraft. A wide range of future space missions are expected to utilize the technologies and the architecture developed by DSST FD. These technologies, besides being small in physical size, make the tiny spacecraft robust and flexible. The DSST FD architecture is designed to be highly reliable and suitable for a wide range of missions such as planetary landers/orbiters/flybys, earth orbiters, cometary flybys/landers/sample returns, etc. Two of the key ideas used in the development of thermal and mechanical technologies and architectures are: 1) to include several of the thermal and mechanical functions in any given single spacecraft element and 2) the architecture be modular so that it can easily be adapted to any of the future missions. One of the thermal architectures being explored for the DSST FD microspacecraft is the integrated thermal energy management of the complete spacecraft using a fluid loop. The robustness and the simplicity of the loop and the flexibility with which it can be integrated in the spacecraft have made it attractive for applications to DSST FD. Some of the thermal technologies to be developed as a part of this architecture are passive and active cooling loops, electrically variable emittance surfaces, miniature thermal switches, and specific high density electronic cooling technologies. In the mechanical area, multifunction architecture for the structural elements will be developed. The multifunction aspect is expected to substantially reduce the mass and volume of the spacecraft. Some of the technologies that will be developed are composite material panels incorporating electronics, cabling, and thermal elements in them. The paper describes the current state of the technologies and progress to be made in the thermal and mechanical technologies and approaches for the DSST Future Deliveries microspacecraft.

Birur, Gajanana C.↗

DOE OSTI2022

Kinetics-Informed Neural Networks

Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize feed-forward artificial neural networks as basis functions to solve ordinary differential equations (ODEs) constrained by differential algebraic equations (DAEs) that describe microkinetic models (MKMs). We present an algebraic framework for the mathematical description and classification of reaction networks, types of elementary reaction, and chemical species. Under this framework, we demonstrate that the simultaneous training of neural nets and kinetic model parameters in a regularized multi-objective optimization setting leads to the solution of the inverse problem through the estimation of kinetic parameters from synthetic experimental data. We analyze a set of scenarios to establish the extent to which kinetic parameters can be retrieved from transient kinetic data, and assess the robustness of the methodology with respect to statistical noise. Furthermore, this approach to inverse kinetic ODEs can assist in the elucidation of reaction mechanisms based on transient data.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Enhanced Mechanical Properties and Wear Resistance of FeCrAl Alloys at ~ 300°C and Higher Temperatures

Abstract Worldwide, light water reactors (LWRs) have been using zirconium (Zr)-based alloys for the cladding of the uranium dioxide fuel for more than 6 decades. Zr alloys oxidize rapidly in the presence of water and steam at temperatures > 450°C; therefore, they do not respond well to scenarios of loss of coolant accidents. There is a global effort by nuclear materials technologists to find more robust or stronger cladding materials for LWRs. One option is to use an iron-chromium-aluminum (FeCrAl) alloy since they have excellent resistance to high temperature oxidation and superior mechanical properties at LWR operation temperatures. Results show that (1) FeCrAl alloys have better mechanical properties than Zr alloy and are orders of magnitude more resistant to creep at temperatures higher than LWR normal operation conditions. (2) FeCrAl alloys have better resistance to fretting wear than Zr alloys at the normal operation conditions of LWRs.

Materials Science↗

DOE OSTI2023

Towards Quantum Computing Phase Diagrams of Gauge Theories with Thermal Pure Quantum States

The phase diagram of strong interactions in nature at finite temperature and chemical potential remains largely theoretically unexplored due to inadequacy of Monte-Carlo–based computational techniques in overcoming a sign problem. Quantum computing offers a sign-problem-free approach, but evaluating thermal expectation values is generally resource intensive on quantum computers. To facilitate thermodynamic studies of gauge theories, we propose a generalization of the thermal-pure-quantum-state formulation of statistical mechanics applied to constrained gauge-theory dynamics, and numerically demonstrate that the phase diagram of a simple low-dimensional gauge theory is robustly determined using this approach, including mapping a chiral phase transition in the model at finite temperature and chemical potential. Quantum algorithms, resource requirements, and algorithmic and hardware error analysis are further discussed to motivate future implementations. Thermal pure quantum states, therefore, may present a suitable candidate for efficient thermal simulations of gauge theories in the era of quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRSDate not supplied

Trends in Asian Summer Monsoon Anticyclone Dynamical Diagnostics in Reanalyses

The area of the Asian summer monsoon anticyclone (ASMA), as defined by contours of Montgomery stream function (MSF) on isentropic surfaces, has been increasing over at least the last four decades. Here we analyze the relationship of the trend in ASMA area to trends in dynamical diagnostics in the ASM region, both inside and outside the ASMA, for 1979 through 2020 in the MERRA-2, JRA-55, and ERA5 reanalyses. Trends in geopotential height (GPH) and temperature (from which MSF is calculated) indicate that MSF increases are dominated by increasing temperature (GPH) at levels that are primarily in the troposphere (stratosphere). Trends in MSF, GPH, and temperature are much less clear within the ASMA circulation than those for the entire ASM region, suggesting that other mechanisms, besides the direct effects of increasing tropospheric temperatures, are at play. To further explore these results, we present trends in lapse rate and dynamical tropopause altitudes, easterly and westerly windspeeds bounding the ASMA, and potential vorticity. Overall, weak or inconsistent trends inside the ASMA in most diagnostics likely arise from a complex interplay of mechanisms in this region (which spans tropospheric/stratospheric and tropical/midlatitude conditions), and suggest that the previously reported area trends do not necessarily indicate an increase in “intensity" of the ASMA. In regions both with and without robust trends in dynamical diagnostics, trend results are typically consistent between the three reanalyses studied even when there are biases in the magnitudes of those diagnostics. This generally good agreement indicates that these reanalyses are suitable for more detailed studies needed to fully understand the mechanisms for trends in the ASMA.

Gloria Manney↗

DOE OSTI2020

Polyester functional graphenic materials as a mechanically enhanced scaffold for tissue regeneration

Traditional metal implants such as titanium, cobalt, and chromium have found wide utility in medicine; however, these come with a risk of toxicity. To overcome metal-related toxicity and enable degradability, polyesters including polycaprolactone (PCL), polylactic acid (PLA), and polyglycolic acid (PGA) show promise for the replacement of various biomedical applications of metals due to their accepted biocompatibility and FDA approval. However, polyesters are less stiff than their metallic counterparts, limiting their application to non-load bearing injury sites, such as fixation hardware for fingers. To improve mechanical properties, graphene oxide (GO)-polyester composites are a promising class of biodegradable scaffolds. Initial reports of these composites are encouraging, but mechanical properties still fall short. Traditional composites rely on non-covalent association between GO and the polyesters, which often leads to failure at the interface and weakens the overall strength of the material. Herein, we present a strategy for attachment of these FDA-approved polyesters onto a derivative of GO using a robust covalent bond. By covalently functionalizing the graphenic backbone with polyesters and without metal catalysts, we create functional graphenic materials (FGMs) to not only simultaneously retain biodegradability and compatibility, but also mechanically strengthen PCL, PLA, and PGA; we observed an average increase in the Young's modulus of over 140% compared to the graphenic backbone. These polyester-functionalized FGMs are a promising platform technology for tissue implants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Enabling Ultra-Compact, Lightweight, Efficient, and Reliable 6.6 kW On-Board Bi-Directional Electric Vehicle Charger with Advanced Topology and Control

The research explored new topologies, control methods, mechanical integration, and thermal management methods for electric vehicle (EV) on-board chargers. The team investigated capacitor-based power conversion, leveraging the high energy densities inherent to capacitive energy storage compared to inductive methods. The proposed topologies simultaneously enabled high power density and high efficiency of the design. The proposed architecture was demonstrated in a 6.6 kW bi-directional charger prototype. The research pursued several directions to improve system performance. Innovative topologies were studied for both the main power conversion stage as well as the single-phase twice-line-frequency energy buffer. To ensure robust and efficient operation, new control methods were developed to integrate these two subsystems. To achieve high power density in the full system solution, the mechanical structure of the charger is highly optimized to maximally fill the converter box volume. In parallel with the mechanical design effort, the converter was packaged with high-performance cooling methods which removed heat from key areas of power dissipation in the converter. The thermal management system was optimized to minimize its weight and volume, ultimately motivating the design of a custom additively manufactured cold-plate. The full system achieves a peak power of 7 kW with less than 0.3% total harmonic distortion (THD) and greater than 0.994 power factor in power factor correction (PFC) operation, corresponding to a total box-volume power density of 47.9 kW/L and gravimetric power density of 24.6 W/g. The system achieves a peak efficiency of 98.9%, with 97.9% efficiency at maximum power.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Understanding the origin of softness in structurally tailored and engineered macromolecular (STEM) gels: A DPD study

Structurally tailored and engineered macromolecular (STEM) gels are polymer networks containing a primary network (the “STEM-0” gel) and side chains that are anchored to this network (forming the “STEM-1” gel). The ability to vary the features of the side chains provides a robust means of tailoring the macroscopic properties of the material. We use dissipative particle dynamics (DPD) simulations to determine the mechanical response of STEM-1 gels to uniaxial compression for various values of the side chain length, n sc . While the Young’s modulus of the material is significantly decreased with increasing n sc (at a fixed density of grafted side chains), above a certain saturation value, increasing n sc does not lead to any further softening of the sample. Using the simulations, we calculate the relevant stresses, which are related to the Young’s modulus and the number of entanglements in the network. We show that the backbone chains become more spread out upon addition of sidechains, leading to a decrease in the physical entanglements between backbone segments. This observation accounts for the decrease of stress in the backbone network and the softening of the networks through the addition of sidechains. For long chains, however, the number density of physical crosslinks between side chains is independent of side chain length; this observation explains the observed stress saturation in the STEM-1 gels. Our approach allows us to correlate the molecular architecture of the gels to the resultant macroscopic mechanical behavior and provide guidelines for fabricating STEM gels with well-defined mechanical properties, which allow the materials to be used for a variety of applications.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Bimetallic Ir x Pb nanowire networks with enhanced electrocatalytic activity for the oxygen evolution reaction

Metallic nanowire networks (MNNs) have attracted increasing attention due to their high surface area and tunable compositions. Although enormous efforts have been devoted to preparing noble metal MNNs with different compositions, the composition optimization and the formation mechanism of Ir-based MNNs have not been thoroughly investigated. Here, this work presents a facile method for synthesizing robust Ir-based bimetallic MNNs by chemical reduction. As unveiled by our characterization, the network structure is constructed by ultrafine nanowires evolved from aggregated nanoparticles. The element analysis confirms the even distribution of Pb and Ir elements. The introduction of Pb is found to be beneficial to the stable formation of Ir x Pb MNNs in the sol–gel process. By tuning the precursor ratio of Ir and Pb, the optimized Ir x Pb catalyst delivers an enhanced oxygen evolution reaction (OER) performance in acid media (307 mV at 10 mA cm −2 ), which is superior to that of the commercial IrO 2 catalyst. Besides, due to the robust structure of the Ir x Pb MNNs, excellent OER durability is observed in the accelerated durability test (ADT) (2000 cycles).

Bimetallic↗

DOE OSTI2020

A sensitive and robust thin-film x-ray detector using 2D layered perovskite diodes

Solid-state radiation detectors, using crystalline semiconductors to convert radiation photons to electrical charges, outperform other technologies with high detectivity and sensitivity. Here, we demonstrate a thin-film x-ray detector comprised with highly crystalline two-dimensional Ruddlesden-Popper phase layered perovskites fabricated in a fully depleted p-i-n architecture. It shows high diode resistivity of 10 12 ohm·cm in reverse-bias regime leading to a high x-ray detecting sensitivity up to 0.276 C Gy air –1 cm –3 . Such high signal is collected by the built-in potential underpinning operation of primary photocurrent device with robust operation. The detectors generate substantial x-ray photon–induced open-circuit voltages that offer an alternative detecting mechanism. Furthermore, our findings suggest a new generation of x-ray detectors based on low-cost layered perovskite thin films for future x-ray imaging technologies.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Charged skyrmions and topological origin of superconductivity in magic-angle graphene

Topological solitons, a class of stable nonlinear excitations, appear in diverse domains as in the Skyrme model of nuclear forces. Here, we argue that similar excitations play an important role in a remarkable material obtained on stacking and twisting two sheets of graphene. Close to a magic twist angle, insulating behavior is observed, which gives way to superconductivity on doping. Here, we propose a unifying description of both observations. A symmetry breaking condensate leads to the ordered insulator, while topological solitons in the condensate—skyrmions—are shown to be charge 2 e bosons. Condensation of skyrmions leads to a superconductor, whose physical properties we calculate. More generally, we show how topological textures can mitigate Coulomb repulsion and provide a previously unexplored route to superconductivity. Our mechanism not only clarifies why several other moiré materials do not show superconductivity but also points to unexplored platforms where robust superconductivity is anticipated.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Unlocking the distinctive enzymatic functions of the early plant biomass deconstructive genes in a brown rot fungus by cell-free protein expression

ABSTRACT Saprotrophic fungi that cause brown rot of woody biomass evolved a distinctive mechanism that relies on reactive oxygen species (ROS) to kick-start lignocellulosic polymers’ deconstruction. These ROS agents are generated at incipient decay stages through a series of redox relays that shuttle electrons from fungus’s central metabolism to extracellular Fenton chemistry. A list of genes has been suggested encoding the enzyme catalysts of the redox processes involved in ROS’s function. However, navigating the functions of the encoded enzymes has been challenging due to the lack of a rapid method for protein synthesis. Here, we employed cell-free expression system to synthesize four redox or degradative enzymes, which were identified, by transcriptomic data, as conserved players of the ROS oxidation phase across brown rot fungal species. All four enzymes were successfully expressed and showed activities that enable confident assignment of function, namely, benzoquinone reductase (BQR), ferric reductase, α-L-arabinofuranosidase (ABF), and heme-thiolate peroxidase (HTP). Detailed analysis of their catalytic features within the context of brown rot environments allowed us to interpret their roles during ROS-driven wood decomposition. Specifically, we validated the functions of BQR as the driver redox enzyme of Fenton cycles and reconstructed its interactions with the co-occurring HTP or laccase and ABF. Taken together, this research demonstrated that the cell-free expression platform is adequate for synthesizing functional fungal enzymes and provided an alternative route for the rapid characterization of fungal proteins, escalating our understanding of the distinctive biocatalyst system for plant biomass conversion. IMPORTANCE Brown rot fungi are efficient wood decomposers in nature, and their unique degradative systems harbor untapped catalysts pursued by the biorefinery and bioremediation industries. While the use of “omics” platforms has recently uncovered the key “oxidative-hydrolytic” mechanisms that allow these fungi to attack lignocellulose, individual protein characterization is lagging behind due to the lack of a robust method for rapid synthesis of crucial fungal enzymes. This work delves into the studies of biochemical functions of brown rot enzymes using a rapid, cell-free expression platform, which allowed the successful depictions of enzymes’ catalytic features, their interactions with Fenton chemistry, and their roles played during the incipient stage of brown rot when fungus sets off the reactive oxygen species for oxidative degradation. We expect this research could illuminate cell-free protein expression system’s use to fulfill the increasing need for functional studies of fungal enzymes, advancing the discoveries of novel biomass-converting catalysts.

60 APPLIED LIFE SCIENCES↗