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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Acoustic emission analysis of cyclically loaded superelastic shape memory alloy fiber reinforced mortar beams

Superelastic shape memory alloys (SMAs) are metallic alloys that can recover their nonlinear deformations upon unloading. The use of SMAs in cementitious composites as fibers can enable crack recovery and re-centering capabilities. In this study, the crack recovery characteristics of SMA fiber reinforced mortar specimens subjected to flexural cyclic loading are studied through acoustic emission analysis. SMA fiber reinforced mortar specimens with fiber volume ratios of 0.3%, 0.5% and 1.0% are tested under cyclic flexural loads. Acoustic emissions (AE) signals are captured and analyzed to characterize the crack formation and crack width development at each cycle of loading. In addition, the crack width propagation of the specimens is monitored by Digital Image Correlation measurement system and is used as a basis in AE analyses. Results show that the SMA fiber reinforced mortars exhibit considerable re-centering and crack recovery characteristics at large deformation amplitudes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Processing and mechanical characterization of short carbon fiber-reinforced epoxy composites for material extrusion additive manufacturing

Fiber-reinforced polymer composites have been extensively utilized in recent years as feedstock materials for material extrusion additive manufacturing (AM) processes to improve strength, stiffness, and functionality of printed parts over unfilled printed polymers. However, the widespread adoption of AM of fiber-reinforced polymer composites requires a deeper understanding of the process-structure-property relationships in printed components, and such relationships are not well understood yet. Fiber length is critically important to the mechanical performance of short fiber composites, but very few studies to-date have focused on how the fiber length distribution (FLD) evolves during processing of composite feedstocks and how this evolution affects printing behavior and mechanical properties in 3D-printed composites. Here, FLD is measured for carbon fiber reinforced epoxy composites over a wide range of ink compositions and shear mixing times, and the distributions are fit with a Weibull-type distribution function. The effects of FLD on the tradeoff between ink processability, ink rheology, printing behavior and mechanical properties are investigated. Furthermore, the effects of printing parameters (nozzle size and print speed) on mechanical anisotropy and fiber orientation distribution (FOD) in printed composites are explored. Mechanical properties of printed composites are characterized via 3 pt-flexural testing, and microstructure is investigated using optical and scanning electron microscopy (SEM), and x-ray computed tomography. Finally, the fitted Weibull parameters are fed into a composite model that incorporates FLD and FOD, and model predictions are found to be in excellent agreement with experimental observations.

3D printing↗
DOE OSTI2024

Long coir and glass fiber reinforced polypropylene hybrid composites prepared via wet-laid technique

Natural fiber composites offer an advantage in terms of weight saving for many automotive applications; however, many natural fiber composites lack properties to justify substitution for synthetic composites. Hybridizing the natural fiber composites by adding a fraction of synthetic fibers is an innovative approach to provide a balance between composite's performance and weight savings. In this study, coir fiber (40 wt%)-reinforced polypropylene (PP) composites were hybridized by substituting a fraction of coir fiber with glass fiber (0–30 wt%). The composites were prepared using a novel wet-laid technique followed by compression molding, where the fiber length is preserved. The composites prepared by hybridizing PP/coir fibers with glass fibers were light in weight (6–20% lighter compared to 40 wt% glass fiber reinforced PP) with significantly enhanced tensile (strength – 49–182%, modulus – 54–130%), flexural (strength – 41–104%, modulus – 64–193%), and impact properties (157 - 474%) compared to 40 wt% coir fiber reinforced PP composites. Furthermore, the addition of glass fiber (10–30 wt%) to coir fiber reduced the water-absorbing tendency (by 18–74%) of PP/coir fiber composites. All in all, this work has potential applications in automotive, mass transit, and truck applications where natural fiber composites are being investigated as alternatives to metal and/or fully synthetic composites.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Microstructural study and densification analysis of hot work tool steel matrix composites reinforced with TiB{sub 2} particles

Hot work tool steels are characterized by good toughness and high hot hardness but are less wear resistant than other tooling materials, such as high speed steel. Metal matrix composites show improved tribological behavior, but not much work has been done in the field of hot work tool steels. In this paper TiB{sub 2}-reinforced hot work tool steel matrix composites were produced by spark plasma sintering (SPS). Mechanical alloying (MA) was proposed as a suited process to improve the composite microstructure. Density measurements and microstructure confirmed that MA promotes sintering and produces a fine and homogeneous dispersion of reinforcing particles. X-ray diffraction patterns of the sintered composites highlighted the formation of equilibrium Fe{sub 2}B and TiC, as predicted by thermodynamic calculations using Thermo-Calc® software. Scanning electron microscopy as well as scanning Kelvin probe force microscopy highlighted the reaction of the steel matrix with TiB{sub 2} particles, showing the formation of a reaction layer at the TiB{sub 2}-steel interface. Phase investigations pointed out that TiB{sub 2} is not chemically stable in steel matrix because of the presence of carbon even during short time SPS. - Highlights: • TiB{sub 2} reinforced steel matrix composites were produced by spark plasma sintering. • TiB{sub 2} was successfully dispersed in the steel matrix by mechanical alloying. • Steel and TiB{sub 2} react during sintering forming equilibrium Fe{sub 2}B and TiC. • The new phases were investigated by means of AFM, Volta potential and XRD analyses.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Interfacial analysis of the ex-situ reinforced phase of a laser spot welded Zr-based bulk metallic glass composite

To study the interfacial reaction of the ex-situ reinforced phase (Ta) of a Zr-based ((Zr{sub 48}Cu{sub 36}Al{sub 8}Ag{sub 8})Si{sub 0.75} + Ta{sub 5}) bulk metallic glass composite after laser spot welding, the interfacial regions of the reinforced phases located at specific zones in the welds including the parent material, weld fusion zone and heat affected zone were investigated. Specimen preparation from the specific zones for transmission electron microscopy analysis was performed using the focused ion beam technique. The test results showed that the reinforced phases in the parent material, weld fusion zone and heat affected zone were all covered by an interfacial layer. From microstructure analysis, and referring to the phase diagram, it was clear that the thin layers are an intermetallic compound ZrCu phase. However, due to their different formation processes, those layers show the different morphologies or thicknesses. - Highlights: • An ex-situ Zr-based BMG composite was laser spot welded. • The interfacial regions of the RPs located at PM, WFZ and HAZ were investigated. • The RPs in the PM, WFZ and HAZ were all covered by a ZrCu interfacial layer. • Due to different formation processes, those layers show the different morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Effect of in-situ (TiC-TiB2) reinforcement on aging and mechanical behavior of AZ91 magnesium matrix composite

Highlights: • Effect of TiC-TiB{sub 2} particles on precipitation behavior of in-situ composite was studied. • The age-hardening rate of in-situ composites is faster than that of alloy. • Faster age hardening rate is due to the presence of high dislocation density in composite. • Post aging treatment improved the mechanical properties of both base and composite. - Abstract: In the present work, influence of in-situ TiC-TiB{sub 2} reinforcement on age hardening behavior and mechanical properties of TiC-TiB{sub 2}/AZ91 composite was investigated. The base and in-situ composite materials were solution treated at 400 °C for 24 h and then aged at different temperatures up to 100 h. The kinetics of age hardening results revealed that the addition of in-situ TiC-TiB{sub 2} reinforcement increase the age hardening kinetics of the composite as compared to AZ91 magnesium alloy. The improvement in age hardening kinetics is attributed to the presence of high dislocation density resulted from the mismatch of coefficients of thermal expansion between in-situ TiC-TiB{sub 2} reinforcement and magnesium matrix. The precipitation behavior of Mg{sub 17}Al{sub 12} phase in both AZ91 alloy and TiC-TiB{sub 2}/AZ91 composites were established. After age hardening, base and in-situ composite materials show significant improvement in ultimate tensile strength by 47.72% and 66.49% respectively as compared with the base monolithic alloy. The enhancement of mechanical properties in the base and in-situ composites is explained in detail by analyzing their fractographs and microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phosphonic-Acid-Reinforced Polymer Hole Transport Layers for Deployable p-i-n Perovskite Photovoltaics

The long-term durability prospects of halide perovskite solar cells are rapidly improving; however, the interface between the hole transport layer (HTL) and the perovskite remains a source of degradation. Alone, polymer- or carbazole-based HTLs suffer from incomplete coverage of the underlying indium tin oxide glass, leading to degradation and compromised performance. Here, we show a multi-HTL approach whereby a polymer HTL is reinforced using a phosphonic acid modification leading to better protection of the buried perovskite interface and more columnar growth of perovskite film, resulting in an ~40-mV open-circuit voltage (VOC) improvement indicative of suppressed interfacial recombination across multiple p-i-n device architectures. Solar cells with this reinforced HTL show higher tolerance to several accelerated stress tests. We report, among the best durabilities for unencapsulated cells, a T90 ~3,000 h (T80 ~5,900 h) at 65 degrees C under continuous 1.2 sun AM 1.5G illumination and maximum power point tracking, representing a nearly 4-fold increase compared with [2-(9H-carbazol-9-yl)ethyl]phosphonic acid (2PACz)-only devices. Furthermore, we deployed a device with this reinforced HTL on a cube satellite, with long-duration operational space testing results exceeding T80 for the complete mission duration of ~100 days in low Earth orbit.

14 SOLAR ENERGY↗
DOE OSTI2021

Reinforcement Learning Configuration Interaction

Selected configuration interaction (sCI) methods exploit the sparsity of the full configuration interaction (FCI) wave function, yielding significant computational savings and wave function compression without sacrificing the accuracy. Despite recent advances in sCI methods, the selection of important determinants remains an open problem. Furthermore, we explore the possibility of utilizing reinforcement learning approaches to solve the sCI problem. By mapping the configuration interaction problem onto a sequential decision-making process, the agent learns on-the-fly which determinants to include and which to ignore, yielding a compressed wave function at near-FCI accuracy. This method, which we call reinforcement-learned configuration interaction, adds another weapon to the sCI arsenal and highlights how reinforcement learning approaches can potentially help solve challenging problems in electronic structure theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Enhancing the Mechanical Toughness of Epoxy-Resin Composites Using Natural Silk Reinforcements

Strong and tough epoxy composites are developed using a less-studied fibre reinforcement, that of natural silk. Two common but structurally distinct silks from the domestic B. mori/Bm and the wild A. pernyi/Ap silkworms are selected in fabric forms. We show that the toughening effects on silk-epoxy composites or SFRPs are dependent on the silk species and the volume fraction of silk. Both silks enhance the room-temperature tensile and flexural mechanical properties of the composite, whereas the more resilient Ap silk shows a more pronounced toughening effect and a lower critical reinforcement volume for the brittle-ductile transition. Specifically, our 60 vol.% Ap-SFRP displays a three-fold elevation in tensile and flexural strength, as compared to pure epoxy resin, with an order of magnitude higher breaking energy via a distinct, ductile failure mode. Importantly, the 60 vol.% Ap-SFRP remains ductile with 7% flexural elongation at lower temperatures (-50 °C). Under impact, these SFRPs show significantly improved energy absorption, and the 60 vol.% Ap-SFRP has an impact strength some eight times that of pure epoxy resin. Lastly, the findings demonstrate both marked toughening and strengthening effects for epoxy composites from natural silk reinforcements, which presents opportunities for mechanically superior and "green" structural composites.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Efficient and assured reinforcement learning-based building HVAC control with heterogeneous expert-guided training

Abstract Building heating, ventilation, and air conditioning (HVAC) systems account for nearly half of building energy consumption and $$20\%$$ of total energy consumption in the US. Their operation is also crucial for ensuring the physical and mental health of building occupants. Compared with traditional model-based HVAC control methods, the recent model-free deep reinforcement learning (DRL) based methods have shown good performance while do not require the development of detailed and costly physical models. However, these model-free DRL approaches often suffer from long training time to reach a good performance, which is a major obstacle for their practical deployment. In this work, we present a systematic approach to accelerate online reinforcement learning for HVAC control by taking full advantage of the knowledge from domain experts in various forms . Specifically, the algorithm stages include learning expert functions from existing abstract physical models and from historical data via offline reinforcement learning, integrating the expert functions with rule-based guidelines, conducting training guided by the integrated expert function and performing policy initialization from distilled expert function. Moreover, to ensure that the learned DRL-based HVAC controller can effectively keep room temperature within the comfortable range for occupants, we design a runtime shielding framework to reduce the temperature violation rate and incorporate the learned controller into it. Experimental results demonstrate up to 8.8 X speedup in DRL training from our approach over previous methods, with low temperature violation rate.

Xu, Shichao↗
DOE OSTI2016

Molecular dynamics study of mechanical properties of carbon nanotube reinforced aluminum composites

Atomistic simulations were conducted to estimate the effect of the carbon nanotube (CNT) reinforcement on the mechanical behavior of CNT-reinforced aluminum (Al) nanocomposite. The periodic system of CNT-Al nanocomposite was built and simulated using molecular dynamics (MD) software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). The mechanical properties of the nanocomposite were investigated by the application of uniaxial load on one end of the representative volume element (RVE) and fixing the other end. The interactions between the atoms of Al were modeled using embedded atom method (EAM) potentials, whereas Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential was used for the interactions among carbon atoms and these pair potentials are coupled with the Lennard-Jones (LJ) potential. The results show that the incorporation of CNT into the Al matrix can increase the Young’s modulus of the nanocomposite substantially. In the present case, i.e. for approximately 9 with % reinforcement of CNT can increase the axial Young’s modulus of the Al matrix up to 77 % as compared to pure Al.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Deep reinforcement learning of cell movement in the early stage of C.elegans embryogenesis

Motivation: Cell movement in the early phase of Caenorhabditis elegans development is regulated by a highly complex process in which a set of rules and connections are formulated at distinct scales. Previous efforts have demonstrated that agent-based, multi-scale modeling systems can integrate physical and biological rules and provide new avenues to study developmental systems. However, the application of these systems to model cell movement is still challenging and requires a comprehensive understanding of regulatory networks at the right scales. Recent developments in deep learning and reinforcement learning provide an unprecedented opportunity to explore cell movement using 3D time-lapse microscopy images. Results: We present a deep reinforcement learning approach within an agent-based modeling system to characterize cell movement in the embryonic development of C.elegans. Our modeling system captures the complexity of cell movement patterns in the embryo and overcomes the local optimization problem encountered by traditional rule-based, agent-based modeling that uses greedy algorithms. Here, we tested our model with two real developmental processes: the anterior movement of the Cpaaa cell via intercalation and the rearrangement of the superficial left-right asymmetry. In the first case, the model results suggested that Cpaaa’s intercalation is an active directional cell movement caused by the continuous effects from a longer distance (farther than the length of two adjacent cells), as opposed to a passive movement caused by neighbor cell movements. In the second case, a leader-follower mechanism well explained the collective cell movement pattern in the asymmetry rearrangement. These results showed that our approach to introduce deep reinforcement learning into agent-based modeling can test regulatory mechanisms by exploring cell migration paths in a reverse engineering perspective. Lastly, this model opens new doors to explore the large datasets generated by live imaging. Availability and implementation: Source code is available at https://github.com/zwang84/drl4cellmovement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

MOLLER Spectrometer Magnet Design With Measured Mechanical Properties of Irradiated S2-Glass Reinforced Cyanate Ester Resin at Elevated Temperature

Here, the aim of this study was to retire the risk of maintaining the integrity of S2-glass reinforced CTD-403 (a cyanate ester resin) that is exposed to radiation and elevated temperature over the life of the measurement of a lepton–lepton electroweak reaction (MOLLER) experiment in experimental Hall A at Jefferson Lab, Newport News, VA. In this article, the shear strength and flexural modulus of irradiated S2-glass reinforced CTD-403 specimens were measured at 65 °C (the magnets are to operate at less than 65 °C) under two scenarios: vacuum and gaseous nitrogen. The testing method is the short-beam shear (SBS) test according to ASTM D2344. The specimens were exposed to neutrons and gamma rays up to 124 MGy. The results show that specimens have excellent resistance against radiation, only 23% degradation of apparent shear strength with 124 MGy at 65 °C under vacuum. At the highest dose areas of the coils, tungsten plates are used to reduce the radiation dose to the resin system. The conclusion is that S2-glass reinforced CTD-403 is well-suited for electrical insulation of MOLLER magnets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Three-Dimensional Permeability of Thick-Section Glass Fabric Reinforced Polymer Composite by Vacuum-Assisted Resin Infusion Molding

Abstract Determination of permeability of thick-section glass fabric preforms with fabric layers of different architectures is critical for manufacturing large, thick composite structures with complex geometry, such as wind turbine blades. The thick-section reinforcement permeability is inherently three-dimensional and needs to be obtained for accurate composite processing modeling and analysis. Numerical simulation of the liquid stage of vacuum-assisted resin infusion molding (VARIM) is important to advance the composite manufacturing process and reduce processing-induced defects. In this research, the 3D permeability of thick-section E-glass fabric reinforcement preforms is determined, and the results are validated by a comparison between flow front progressions from experiments and from numerical simulations using ansys fluent software. The orientation of the principal permeability axes were unknown prior to experiments. The approach used in this research differs from those in literature in that the through-thickness permeability is determined as a function of flow front positions along the principal axes and the in-plane permeabilities and is not dependent on the inlet radius. The approach was tested on reinforcements with fabric architectures which vary through-the-thickness direction, such as those in a spar cap of a wind turbine blade. The computational simulations of the flow-front progression through-the-thickness were consistent with experimental observations.

Engineering↗
DOE OSTI2025

Black-box optimization of CT acquisition and reconstruction parameters: a reinforcement learning approach

Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exhaustive combinations of these parameters. This poses a notable limitation due to the impracticality of exhaustive parameter testing. This study introduces a novel methodology leveraging Virtual Imaging Trials (VITs) and reinforcement learning to more efficiently optimize CT protocols. Computational phantoms with liver lesions were imaged using a validated CT simulator and reconstructed with a novel CT reconstruction Toolkit. The optimization parameter space included tube voltage, tube current, reconstruction kernel, slice thickness, and pixel size. The optimization process was done using a Proximal Policy Optimization (PPO) agent which was trained to maximize the Detectability Index (d’) of the liver lesion for each reconstructed image. Results showed that our reinforcement learning approach found the absolute maximum d’ across the test cases while requiring 79.7% fewer steps compared to an exhaustive search, demonstrating both accuracy and computational efficiency, offering a efficient and robust framework for CT protocol optimization. The flexibility of the proposed technique allows for use of varying image quality metrics as the objective metric to maximize for. Our findings highlight the advantages of combining VIT and reinforcement learning for CT protocol management.

Fenwick, David [Duke University Medical Center]↗
DOE OSTI2023

Low-velocity repeated impact behaviors of Polymer Fiber Reinforced Plastics (PFRPs)

Modern fiber-reinforced composites have become ubiquitous across multiple industries due to their excellent weight-to-strength ratio. Typically glass or carbon fibers are widely used. While Glass or Carbon Fiber-Reinforced Plastics (GFPRs or CFPRs) have good stiffness, strength, and fatigue life, they are expensive and difficult to recycle. Researchers are exploring Polymer Fiber-Reinforced Plastics (PFRPs) as an alternative solution. PFRPs utilize polymer fibers and a polymer matrix. A wide range of materials options is available, including low-cost thermoplastics such as polyethylene or polypropylene. These thermoplastics are easy to handle and recyclable without special methods. Manufacturing parts using thermoplastics are well-established as well. However, their mechanical performances have not been extensively studied compared to GFRPs or CFRPs. This study examines the low-velocity impact resistance of PFRPs made of different thermoplastics. The low-velocity impacts are applied through a drop-weight tower. The experiment is divided into two cases: a single perforation impact and low-energy repeated impacts. Energy absorption and the number of impacts to failure are measured. The results are compared to traditional CFRPs which have a thermoset matrix. The PFRPs demonstrate energy absorption capabilities comparable to or greater than those of CFRPs with respect to specimen thickness and density. Additionally, the PFRPs show significantly higher impacts-to-failure than the CFRPs in low-energy repeated impact tests. This is particularly noteworthy considering that the PFRPs are much simpler and more economical to manufacture than CFRPs. To further

Ko, Seunghyun↗
DOE OSTI2023

Recyclable Cellulose Fiber Reinforced Vitrimer Composite

Vitrimer is an innovative class of polymeric materials which demonstrates traditional thermoset-like mechanical and chemical resilience while still being able to flow on demand like a traditional thermoplastic through covalently adaptive dynamic linkages. Herein, high-performance cellulose fiber reinforced vitrimer composites are developed using an epoxy-based vitrimer and natural cellulose paper. The reinforced vitrimer composite was fabricated by impregnating the porous structure of cellulose paper with two curable monomers, followed by in-situ polymerization of the monomers inside the fibrous scaffold. The introduction of hydroxyl group present on the cellulosic framework assisted in a faster topological rearrangement of the crosslinked matrix through transesterification exchange reaction, thus imparting various sought-after properties like shape recovery and recyclability via simple thermal reprocessing. Moreover, the reinforced vitrimer composite exhibits superior tensile properties as high as 90 MPa with 15-25 volume% vitrimer loading due to the interfacial adhesion via ester exchange reaction between the epoxy matrix and functionalities on the cellulosic fibers. Noteworthily, the key ingredients of the resulting composite (i.e., epoxy-based vitrimer and cellulose fibers) can be comfortably recycled without using aggressive chemical treatment, enabling composite to be easily recycled or disposed of at the end of service life and assist in reducing the subsequent manufacturing cost. This study would shed light on the development of a recyclable polymer composite with exceptional mechanical properties while simultaneously demonstrating self-healing and shape memory capabilities.

Rohewal, Sargun Singh↗
DOE OSTI2017

Mutual reinforcement of pathophysiological host-microbe interactions in intestinal stasis models

Chronic diseases arise when there is mutual reinforcement of pathophysiological processes that cause an aberrant steady state. Such a sequence of events may underlie chronic constipation, which has been associated with dysbiosis of the gut. In this study we hypothesized that assemblage of microbial communities, directed by slow gastrointestinal transit, affects host function in a way that reinforces constipation and further maintains selection on microbial communities. In our study, we used two models – an opioid-induced consti- pation model in mice, and a humanized mouse model where germ-free mice were colonized with stool from a patient with constipation-predominant irritable bowel syndrome (IBS-C) in humans. We examined the impact of pharmacologically (loperamide)-induced constipation (PIC) and IBS-C on the structural and functional profile of the gut microbiota. Germ-free (GF) mice were colonized with microbiota from PIC donor mice and IBS-C patients to determine how the microbiota affects the host. PIC and IBS-C promoted changes in the gut microbiota, characterized by increased relative abundance of Bacteroides ovatus and Parabacteroides distasonis in both models. PIC mice exhibited decreased luminal concentrations of butyrate in the cecum and altered metabolic profiles of the gut microbiota. Colonization of GF mice with PIC-associated mice cecal or human IBS-C fecal microbiota significantly increased GI transit time when compared to control microbiota recipients. IBS-C-associated gut microbiota also impacted colonic contractile properties. Lastly, our findings support the concept that constipation is characterized by dis- ease-associated steady states caused by reinforcement of pathophysiological factors in host-microbe interactions.

60 APPLIED LIFE SCIENCES↗