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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

DEM Particle Fracture Model

An adaptive particle fracture model in poly-ellipsoidal Discrete Element Method is developed. The poly-ellipsoidal particle will break into several sub-poly-ellipsoids by Hoek-Brown fracture criterion based on continuum stress and the maximum tensile stress in contacts. Also Weibull theory is introduced to consider the statistics and size effects on particle strength. Finally, high strain-rate split Hopkinson pressure bar experiment of silica sand is simulated using this newly developed model. Comparisons with experiments show that our particle fracture model can capture the mechanical behavior of this experiment very well, both in stress-strain response and particle size redistribution. The effects of density and packings o the samples are also studied in numerical examples.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Incorporating the Min-Max Mesh Optimization Method within the Target-Matrix Paradigm

The Target-Matrix Optimization Paradigm (TMOP) is a method for improving mesh quality via node movement. Through the use of appropriate pre-defined quality metrics and Target-matrices, TMOP provides the ability to define mesh quality in terms of element shape, volume, and edge orientation as a function of position within the mesh, thus facilitating high-level goals such as size-adapted meshing. The Paradigm is developed further in this paper by showing how it can be applied to the problem of improving the mesh in locations where the quality is the worst. Improving the worst quality portions of a mesh was investigated by Freitag, Amenta, and others, who showed that the problem can be formulated as a min-max optimization problem. The Target-paradigm is used to extend the previous work in two important respects. First, by using quality metrics from the Target-paradigm, quality can be user-specified via Target-matrices instead of the quality definition being hard-wired into the quality metric. Second, by making use of the sample point concept in TMOP, one can extend min-max mesh optimization to non-simplicial element types such as quadrilaterals. Numerical experiments were performed to illustrate these extensions and to investigate their utility. A non-gradient solver known as the amoeba was used to numerically compute the optimal solutions. This derivative-free method, in conjunction with the use of barrier metrics from TMOP, enables the solution of the min-max problem without the use of explicit constraints to guarantee that the optimal mesh is non-inverted. The experiments showed that the use of Target-metrics in min-max with triangle (or tetrahedral) element meshes is able to effectively improve the worst quality elements in terms of shape or in terms of size+shape. The experiments also showed that the mesh min-max extension to quadrilateral element meshes can lead to acceptable meshes using barrier metrics from the Target-paradigm, provided that inter-element mesh smoothness is not important. Poor behavior was observed when using non-barrier Target-metrics in min-max with quadrilateral element meshes. For both simplicial and quadrilateral meshes, the min-sum method can be competitive with min-max, however.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Viral shift and drift, report part 1

The ability for RNA viruses to evolve at a high rate has the potential to confound existing medical technology by making it more difficult to accurately diagnosis and treat RNA based infectious disease. The rapid mutation rates of RNA viruses give a virus the ability to adapt to novel selective pressures, which can potentially support zoonosis, sustained outbreaks in a novel host, and resistance to anti-retroviral treatments. A key contributor to an RNA virus’ mutation rate is the lack of a proof reading enzyme to correct for mis-incorporated bases when transcribing a daughter RNA particle. Thus, there are potentially many opportunities for new mutations to be randomly introduced and subsequently fixed in a key subset of the viral population. This is a feature, which we refer to in this report as genetic drift. One of the hurdles to understanding the role of genetic drift in the spread of RNA virus outbreaks is the need to analyze a densely sampled outbreak using whole genome sequencing in order to measure the amount of mutation occurring on a small time scale. The recent advances in sequencing technology have now lowered the data collection cost barriers to allow the measure of evolution not just among the consensus virus sequences on a shorter time scale, but potentially capture all the distinct genetic variants that are circulating within a single infected host. Tracking the distinct genetic variants within an infected individual provides additional information on genetic drift within the host, and can help determine whether mutations that are important for emerging disease are able to persist at the sub consensus level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Limited‐memory adaptive snapshot selection for proper orthogonal decomposition

Summary Reduced order models are useful for accelerating simulations in many‐query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models (ROMs) can have prohibitively expensive memory and floating‐point operation costs in high‐performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time‐stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition‐based ROMs, and memory usage is minimized by computing the singular value decomposition using a single‐pass incremental algorithm. Results for a viscous Burgers' test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full‐order model is recovered to within discretization error. A parallel version of the resulting method can be used on supercomputers to generate proper orthogonal decomposition‐based ROMs, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space. Copyright © 2016 John Wiley & Sons, Ltd.

Oxberry, Geoffrey M.↗
DOE OSTI2012

Tradeoffs in the Evolution of Caste and Body Size in the Hyperdiverse Ant Genus Pheidole

The efficient investment of resources is often the route to ecological success, and the adaptability of resource investment may play a critical role in promoting biodiversity. The ants of the “hyperdiverse” genus Pheidole produce two discrete sterile castes, soldiers and minor workers. Within Pheidole, there is tremendous interspecific variation in proportion of soldiers. The causes and correlates of caste ratio variation among species of Pheidole remain enigmatic. Here we test whether a body size threshold model accounts for interspecific variation in caste ratio in Pheidole, such that species with larger body sizes produce relatively fewer soldiers within their colonies. We evaluated the caste ratio of 26 species of Pheidole and found that the body size of workers accounts for interspecific variation in the production of soldiers as we predicted. Twelve species sampled from one forest in Costa Rica yielded the same relationship as found in previously published data from many localities. We conclude that production of soldiers in the most species-rich group of ants is regulated by a body size threshold mechanism, and that the great variation in body size and caste ratio in Pheidole plays a role in niche divergence in this rapidly evolving taxon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

An agentic artificially intelligent X-ray scientist

Executing experimental tasks in both normal research laboratories and large-scale scientific facilities often requires extensive human supervision and remains a key challenge on the path to fully autonomous, artificial intelligence (AI)-driven science. Here we demonstrate a large language model-driven agent that autonomously performs X-ray sample alignment on a synchrotron beamline by planning actions, executing instrumental commands, interpreting observations and iterating towards experimental goals. Based on existing large language models with structured tool-use via the model context protocol, our AI X-ray scientist was guided and tested using an in-house-built virtual experimental setup that mirrors a six-circle diffractometer at an operational synchrotron beamline. The agentic workflow developed in the virtual environment was directly deployed on a real beamline, where it correctly identified reference reflections and determined the orientation matrix, an essential first step in any type of single-crystal scattering experiment. Our AI X-ray scientist responded effectively to unexpected experimental conditions, demonstrating adaptive problem-solving and readiness for addressing practical experimental situations. Our study provides a step towards autonomous operation across diverse experimental environments at large-scale scattering facilities.

Chen, Zhantao (ORCID:0000000319543868)↗
DOE OSTI2021

The sol–gel autocombustion as a route towards highly CO 2 -selective, active and long-term stable Cu/ZrO 2 methanol steam reforming catalysts

The adaption of the sol-gel autocombustion method to the Cu/ZrO 2 system opens new pathways for the specific optimisation of the activity, long-term stability and CO 2 selectivity of methanol steam reforming (MSR) catalysts. Calcination of the same post-combustion precursor at 400 °C, 600 °C or 800 °C allows accessing Cu/ZrO 2 interfaces of metallic Cu with either amorphous, tetragonal or monoclinic ZrO 2 , influencing the CO 2 selectivity and the MSR activity distinctly different. While the CO 2 selectivity is less affected, the impact of the post-combustion calcination temperature on the Cu and ZrO 2 catalyst morphology is more pronounced. A porous and largely amorphous ZrO 2 structure in the sample, characteristic for sol-gel autocombustion processes, is obtained at 400 °C. This directly translates into superior activity and long-term stability in MSR compared to Cu/tetragonal ZrO 2 and Cu/monoclinic ZrO 2 obtained by calcination at 600 °C and 800 °C. The morphology of the latter Cu/ZrO 2 catalysts consists of much larger, agglomerated and non-porous crystalline particles. Based on aberration-corrected electron microscopy, we attribute the beneficial catalytic properties of the Cu/amorphous ZrO 2 material partially to the enhanced sintering resistance of copper particles provided by the porous support morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2015

High resolution imaging of very low mass spectral binaries: Three resolved systems and detection of orbital motion in an L/T transition binary

We present high resolution Laser Guide Star Adaptive Optics imaging of 43 late-M, L and T dwarf systems with Keck/NIRC2. These include 17 spectral binary candidates, systems whose spectra suggest the presence of a T dwarf secondary. We resolve three systems: 2MASS J1341–3052, SDSS J1511+0607 and SDSS J2052–1609; the first two are resolved for the first time. All three have projected separations <8 AU and estimated periods of 14–80 years. We also report a preliminary orbit determination for SDSS J2052–1609 based on six epochs of resolved astrometry between 2005 and 2010. Among the 14 unresolved spectral binaries, 5 systems were confirmed binaries but remained unresolved, implying a minimum binary fraction of 47{sub −11}{sup +12}% for this sample. Our inability to resolve most of the spectral binaries, including the confirmed binaries, supports the hypothesis that a large fraction of very low mass systems have relatively small separations and are missed with direct imaging.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Future Vision for Autonomous Ocean Observations

Autonomous platforms already make observations over a wide range of temporal and spatial scales, measuring salinity, temperature, nitrate, pressure, oxygen, biomass; and many other parameters. However, the observations are not comprehensive. Future autonomous systems need to be more affordable, more modular, more capable and easier to operate. Creative new types of platforms and new compact, low power, calibrated and stable sensors are under development to expand autonomous observations. Communications and recharging need bandwidth and power which can be supplied by standardized docking stations. In situ power generation will also extend endurance for many types of autonomous platforms, particularly autonomous surface vehicles. Standardized communications will improve ease of use, interoperability, and enable coordinated behaviors. Improved autonomy and communications will enable adaptive networks of autonomous platforms. Improvements in autonomy will have three aspects: hardware, control, and operations. As sensors and platforms have more onboard processing capability and energy capacity, more measurements become possible. Control systems and software will have the capability to address more complex states and sophisticated reactions to sensor inputs, which allows the platform to handle a wider variety of circumstances without direct operator control. Operational autonomy is increased by reducing operating costs. To maximize the potential of autonomous observations new standards and best practices are needed. In some applications, focus on common platforms and volume purchases could lead to significant cost reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as EGO for the emerging glider operations should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Rapid detection of Ebola virus with a reagent-free, point-of-care biosensor

Surface acoustic wave (SAW) sensors can rapidly detect Ebola antigens at the point-of-care without the need for added reagents, sample processing, or specialized personnel. This preliminary study demonstrates SAW biosensor detection of the Ebola virus in a concentration-dependent manner. The detection limit with this methodology is below the average level of viremia detected on the first day of symptoms by PCR. We observe a log-linear sensor response for highly fragmented Ebola viral particles, with a detection limit corresponding to 1.9 × 10⁴ PFU/mL prior to virus inactivation. We predict greatly improved sensitivity for intact, infectious Ebola virus. This point-of-care methodology has the potential to detect Ebola viremia prior to symptom onset, greatly enabling infection control and rapid treatment. This biosensor platform is powered by disposable AA batteries and can be rapidly adapted to detect other emerging diseases in austere conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

THE BLACK HOLE MASSES AND STAR FORMATION RATES OF z>1 DUST OBSCURED GALAXIES: RESULTS FROM KECK OSIRIS INTEGRAL FIELD SPECTROSCOPY

We have obtained high spatial resolution Keck OSIRIS integral field spectroscopy of four z {approx} 1.5 ultra-luminous infrared galaxies that exhibit broad H{alpha} emission lines indicative of strong active galactic nucleus (AGN) activity. The observations were made with the Keck laser guide star adaptive optics system giving a spatial resolution of 0.''1 or <1 kpc at these redshifts. These high spatial resolution observations help to spatially separate the extended narrow-line regions-possibly powered by star formation-from the nuclear regions, which may be powered by both star formation and AGN activity. There is no evidence for extended, rotating gas disks in these four galaxies. Assuming dust correction factors as high as A(H{alpha}) = 4.8 mag, the observations suggest lower limits on the black hole masses of (1-9) x 10{sup 8} M{sub sun} and star formation rates <100 M{sub sun} yr{sup -1}. The black hole masses and star formation rates of the sample galaxies appear low in comparison to other high-z galaxies with similar host luminosities. We explore possible explanations for these observations, including host galaxy fading, black hole growth, and the shut down of star formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Uranium and strontium fate in waste-weathered sediments: Scaling of molecular processes to predict reactive transport

Objectives of the project: 1. Determine the process coupling that occurs between mineral transformation and contaminant (U and Sr) speciation in acid-uranium waste weathered Hanford sediments. 2. Establish linkages between molecular-scale contaminant speciation and meso-scale contaminant lability, release and reactive transport. 3. Make conjunctive use of molecular- to bench-scale data to constrain the development of a mechanistic, reactive transport model that includes coupling of contaminant sorption-desorption and mineral transformation reactions. Hypotheses tested: - Uranium and strontium speciation in legacy sediments from the U-8 and U-12 Crib sites can be reproduced in bench-scale weathering experiments conducted on unimpacted Hanford sediments from the same formations. - Reactive transport modeling of future uranium and strontium releases from the vadose zone of acid-waste weathered sediments can be effectively constrained by combining molecular-scale information on contaminant bonding environment with grain-scale information on contaminant phase partitioning, and meso-scale kinetic data on contaminant release from the waste-weathered porous media. - Although field contamination and laboratory experiments differ in their diagenetic time scales (decades for field vs. months to years for lab), sediment dissolution, neophase nucleation, and crystal growth reactions that occur during the initial disequilibrium induced by waste-sediment interaction leave a strong imprint that persists over subsequent longer-term equilibration time scales and, therefore, give rise to long-term memory effects. Enabling capabilities developed: Our team developed an iterative measure-model approach that is broadly applicable to elucidate the mechanistic underpinnings of reactive contaminant transport in geomedia subject to active weathering. Experimental design: Hypotheses were tested by comparing (with a similar set of techniques) the geochemical transformations and transport behaviors that occured in bench-scale studies of waste-sediment interaction with parallel model systems studies of homogeneous nucleation and neo-phase dissolution. Initial plans were to compare results with core sample extractions from the acid uranium waste impacted U-8 and U-12 Cribs at Hanford (see original proposal and letter of collaboration from J. Zachara). However, this part of the project was impossible because funding for core extractions were eliminated from the DoE budget. Three distinct crib waste aqueous simulants (whose composition is based on the most up-to-date information from field site investigations) were reacted with Hanford sediments in batch and column systems. Coupling of contaminant uptake to mineral weathering was monitored using a suite of methods both during waste-sediment interaction, and after, when waste-weathered sediments were subjected to infusion with circumneutral background pore water solutions. Our research was designed to adapt as needed to maintain a strong dialogue between laboratory and modeling investigations so that model development was increasingly constrained by emergent data and understanding. Potential impact of the project to DOE: Better prediction of contaminant uranium transport was achieved by employing multi-faceted lines of inquiry to build a strong bridge between molecular- and field-scale information. By focusing multiple lines and scales of observation on a common experimental design, our collaborative team revealed non-linear and emergent behavior in contaminated weathering systems. A goal of the current project was to expand our modeling capabilities, originally focused on hyperalkaline legacy waste streams, to include acidic weathering reactions that, as described above, were expected to result in profoundly different products. We were able to achieve this goal, and showed that these products nonetheless undergo analogous silicate and non-silicate transformation, ripening and aging processes. Our prediction that these weathering reactions would vary with waste stimulant chemistry resulted in data that was incorporated directly into a reactive transport model structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary

Recent advancements in scientific equipment and the adaptation of electronics and the Internet of Things (IoT) in our everyday lives resulted in large and complex data production at a high rate. Making meaningful and timely knowledge discovery at a modest cost from this big data is difficult for computing power and storage limitations. Training deep learning models incrementally in a streaming setting can help us with overcoming these limitations. However, in a well-known phenomenon named catastrophic forgetting, incrementally trained models increasingly perform poorly on the past data. To mitigate catastrophic forgetting in training in a streaming setting, we propose constructing a historical summary over time and use the summary with newly arrived data during incremental training. We propose various data summarization techniques such as random sampling, micro clustering, coreset computation, and Auto Encoders to counteract catastrophic forgetting. We built a pipeline for incremental training with a historical summary for training deep learning models for streaming data. We demonstrate the effectiveness of historical summary in mitigating catastrophic forgetting using three case studies involving three different deep learning applications: an Artificial Neural Network (ANN) for classification task on MNIST dataset, a language model (RNN-LM) on the WikiText2 dataset, and a Convolutional Neural Network (CNN), ResNet50 to classify the ImageNet dataset. Through the training of the models, we observe that catastrophic forgetting is evident in ANN and CNN but not in an RNN. For the first task, our method recovers up to 47.9% lost accuracy due to catastrophic forgetting. For the third task, the historical summary recovers classification accuracy by up to 25%. For the second task, though there is not proof of catastrophic forgetting, the training performance (PPL) improves by up to 26% with historical summary.

Dash, Sajal↗
DOE OSTI2015

Limited-memory adaptive snapshot selection for proper orthogonal decomposition

Reduced order models are useful for accelerating simulations in many-query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models can have prohibitively expensive memory and floating-point operation costs in high-performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time-stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition-based reduced order models, and memory usage is minimized by computing the singular value decomposition using a single-pass incremental algorithm. Results for a viscous Burgers’ test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full order model is recovered to within discretization error. The resulting method can be used on supercomputers to generate proper orthogonal decomposition-based reduced order models, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km 2 of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. Here, we employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We discover a difference in species abundance within a 130 m radius of the center of the test site.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Dynamic structure of the full-length scaffolding protein NHERF1 influences signaling complex assembly

The Na+/H+ exchange regulatory cofactor 1 (NHERF1) protein modulates the assembly and intracellular trafficking of several transmembrane G protein–coupled receptors (GPCRs) and ion transport proteins with the membrane–cytoskeleton adapter protein ezrin. We applied in this report solution NMR and small-angle neutron scattering (SANS) to structurally characterize full-length NHERF1 and disease-associated variants that are implicated in impaired phosphate homeostasis. Using NMR, we mapped the modular architecture of NHERF1, which is composed of two structurally-independent PDZ domains that are connected by a flexible, disordered linker. We observed that the ultra-long and disordered C-terminal tail of NHERF1 has a type 1 PDZ-binding motif that interacts weakly with the proximal, second PDZ domain to form a dynamically autoinhibited structure. Using ensemble-optimized analysis of SANS data, we extracted the molecular size distribution of structures from the extensive conformational space sampled by the flexible chain. Our results revealed that NHERF1 is a diffuse ensemble of variable PDZ domain configurations and a disordered C-terminal tail. The joint NMR/SANS data analyses of three disease variants (L110V, R153Q, and E225K) revealed significant differences in the local PDZ domain structures and in the global conformations compared with the WT protein. Furthermore, we show that the substitutions affect the affinity and kinetics of NHERF1 binding to ezrin and to a C-terminal peptide from G protein–coupled receptor kinase 6A (GRK6A). Significant insight into the modulation of the intrinsic flexibility of NHERF1 by disease-associated point mutations that alter the dynamic assembly of signaling complexes are provided in this work.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Isolation of Histone from Sorghum Leaf Tissue for Top Down Mass Spectrometry Profiling of Potential Epigenetic Markers

Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. Post-translational modifications (PTMs) of histones, which are highly dynamic and can be added or removed by enzymes, play critical roles in regulating gene expression. In plants, epigenetic factors including histone PTMs are related to their adaptive responses to the environment. Understanding the molecular mechanisms of epigenetic control can bring unprecedented opportunities for engineering solutions to increase the resilience of crops to climate change. Herein, we describe a protocol to isolate the nuclei and purify histones from sorghum leaf tissue. The extracted histones can be analyzed as their intact forms by top-down mass spectrometry (MS) coupled to online reversed-phase (RP) liquid chromatography (LC). Combinations and stoichiometry of multiple PTMs on the same histone proteoform can be readily identified. In addition, histone tail clipping can be detected using the top-down LC-MS workflow thus yielding the global PTM profile of core histones (H4, H2A, H2B, H3). By comparing the PTM profile among samples corresponding to different conditions (e.g. drought vs. control), potential epigenetic marks can be discovered as targets for further characterization using approaches such as chromatin immunoprecipitation – sequencing (ChIP-seq).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Atomistic modeling of tensile deformation and fracture of carbon fibers: Nanoscale stress redistribution, effect of local structural characteristics and nanovoids

The mechanisms of tensile deformation and fracture of carbon fibers are investigated in large-scale molecular dynamics simulations. The simulations performed for computational samples with different structural characteristics enable analysis of the structural sensitivity of the mechanical properties. It is found that the carbon fiber nanostructure can be represented by a fine (nanoscale) mixture of stiff and soft regions. Despite the nanoscale structural heterogeneity of the computational fibers, their fracture strain and tensile strength exceed the experimental values by almost an order of magnitude. Here, this observation is explained by the ability of the carbon fiber nanostructure, largely consisting of curved and folded layers of turbostratic carbon, to exhibit continuous nanoscale load redistribution during the deformation. The transient, fluid nature of a percolating cluster of stress-holding structural elements prevents stress localization at the early stage of the deformation and enables the fiber nanostructure to adapt to the increasing load. Overall, the results of the simulations suggest that the design of advanced carbon fiber manufacturing and post-processing methods focused on the elimination of critical mesoscopic structural defects (internal voids, foreign inclusions, and surface flaws) can yield a substantial increase in the strength and fracture strain of carbon fibers.

36 MATERIALS SCIENCE↗