Multiscale Behavior Research Articles

Experimental Study on Macroscopic Mechanical Characteristics and Microscopic Pore Structure Evolution of Soil–Rock Mixture under Repeated Freeze–Thaw Cycles

The response characteristics of the mesostructure and macro-characteristics of the soil–rock mixture under repeated freeze–thaw action have an important influence on the safety and stability of the dump slope in low-temperature environments. In order to further understand the multi-scale response behavior of a soil–rock mixture under freeze–thaw cycles, this paper carried out indoor freeze–thaw cycles, uniaxial compression, and electrochemical impedance spectroscopy tests on a soil–rock mixture taken from a graphite mine dump in Jixi City, Heilongjiang Province, China. Combined with the simulation calculation of discrete element numerical software (PFC2D 7.0), the effects of freeze–thaw cycling on electrochemical impedance spectrometry (EIS) mesoscopic parameters, uniaxial compressive strength, and crack propagation of soil–rock mixtures were analyzed. The intrinsic relationship between mesoparameters and macroscopic mechanical properties was established. The results showed that as the number of freeze–thaw cycles increases from 0 to 15, the mesopores inside the soil–rock mixture gradually increase, and the angular similarity of distribution characteristics increases by 5.25%. The uniaxial compressive strength and the peak secant modulus increase exponentially with the increase in the number of freeze–thaw cycles, the uniaxial compressive strength decreases by 47.62%, and the peak secant modulus decreases by 75.87%. The peak strain and pore compaction stage showed an exponential increase and an increasing trend, respectively, and the peak strain increased from 2.115% to 4.608%. The failure mode was basically similar in different cycles; the failure cracks extended from the corners to the middle and lower parts before the failure finally occurred. The types of failure cracks were mainly tensile cracks, followed by tensile shear cracks and the fewest compression shear cracks. The similarity and uniaxial compressive strength conformed to a good linear relationship with the number of freeze–thaw cycles, with the uniaxial compressive strength decreasing linearly with the increase in similarity.

Guided Deep Learning Manifold Linearization of Porous Media Flow Equations

Summary Integrated reservoir studies for performance prediction and decision-making processes are computationally expensive. In this paper, we develop a novel linearization approach to reduce the computational burden of intensive reservoir simulation execution. We achieve this by introducing two novel components: (1) augmention of the state-space to yield a bilinear system and (2) an autoencoder based on a deep neural network to linearize physics reservoir equations in a reduced manifold using a Koopman operator. Recognizing that reservoir simulators execute expensive Newton-Raphson iterations after each timestep to solve the nonlinearities of the physical model, we propose “lifting” the physics to a more amenable manifold where the model behaves close to a linear system, similar to the Koopman theory, thus avoiding the iteration step. We use autoencoder deep neural networks with specific loss functions and structure to transform the nonlinear equation and frame it as a bilinear system with constant matrices over time. In such a way, it forces the states (pressures and saturations) to evolve in time by simple matrix multiplications in the lifted manifold. We also adopt a “guided” training approach, which is performed in three steps: (1) We initially train the autoencoder, (2) then we use a “conventional” model order reduction (MOR) as an initializer for the final (3) full training, when we use reservoir knowledge to improve and to lead the results to physically meaningful output. Many simulation studies exhibit extremely nonlinear and multiscale behavior, which can be difficult to model and control. Koopman operators can be shown to represent any dynamical system through linear dynamics. We applied this new framework to a 2D two-phase (oil and water) reservoir subject to a waterflooding plan with three wells (one injector and two producers) with speedups around 100 times faster and accuracy in the order of 1% to 3% on the pressure and saturation predictions. It is worthwhile noting that this method is a nonintrusive data-driven method because it does not need access to the reservoir simulation internal structure; thus, it is easily applied to commercial reservoir simulators and is also extendable to other studies. In addition, an extra benefit of this framework is to enable the plethora of well-developed tools for MOR of linear systems. To the authors’ knowledge, this is the first work that uses the Koopman operator for linearizing the system with controls. As with any MOR method, this can be directly applied to a well-control optimization problem and well-placement studies with low computational cost in the prediction step and good accuracy.

Multifractal analysis on CT soil images: Fluctuation analysis versus mass distribution

The combined action of physical, chemical and biological processes at different scales creates a highly complex soil architecture. At the same time, this soil pores' complexity is crucial in maintaining soil biogeochemical and biophysical processes. The development of digital image processing and a multiscaling analysis allow a better study to quantify pore complexity and evaluate pore spatial variability. This study took saline soils from coastal reclamation areas as an example and aimed to compare the multifractality of porosity series using different methods on sample cubes of 512 pixels in length extracted at different soil depths. Two measures were selected to represent the porosity series: the average grey values (AVG) of each slice and the CT-porosity (CTP) of binarized slices. The mass distribution (MD), detrended fluctuation analysis (DFA), and the moments function (K) were the methods applied in the multiscaling study. Shuffled and surrogated series were used to analyze the two possible multifractality sources, the probability distribution density function (PDF) and long-range correlations, respectively.The results showed that MD gave the minimum multifractal spectrum, which appeared as a point in AGV and a narrow concave parabola in CTP. On the other hand, both AGV and CTP showed a higher complexity, a clear and significant multifractal behaviour when DFA and K were used. The shuffled and surrogated series pointed out that the long-range correlations were the main factor of the multifractal sources of the porosity series. Both long-range correlations and PDF influenced more heavily on the multifractality of porosity in topsoil (0– 20 cm) than in the deeper soil (20– 60 cm), implying that the porosity series in topsoil had stronger multifractality. In addition, the DFA and K, combined with shuffled and surrogated series analysis, can distinguish between different factors in the multiscaling behaviour of different soil textures and time reclamation.

Multiscale dynamics in streamwise-rotating channel turbulence

In this paper the multiscale dynamics of streamwise-rotating channel turbulence is studied through direct numerical simulations. Using the generalized Kolmogorov equation, we find that as rotation becomes stronger, the turbulence in the buffer layer is obviously reduced by the intense spatial turbulent convection. On the contrary, in other layers, the turbulence is strengthened mainly by the modified production peak, the intense spatial turbulent convection and the suppressed forward energy cascades. It is also discovered that under a system rotation, small- and large-scale inclined structures have different angles with the streamwise direction, and the difference is strengthened with increasing rotation rates. The multiscale inclined structures are further confirmed quantitatively through a newly defined angle based on the velocity vector. Through the budget balance of Reynolds stresses and the hairpin vortex model, it is discovered that the Coriolis force and the pressure–velocity correlation are responsible for sustaining the inclined structures. The Coriolis force directly decreases the inclination angles but indirectly induces inclined structures in a more predominant way. The pressure–velocity correlation term is related to the strain rate tensor. Finally, the anisotropic generalized Kolmogorov equation is used to validate the above findings and reveals that the multiscale behaviours of the inclined structures are mainly induced by the mean spanwise velocity gradients.

A multiscale elastoplastic tensive behavior of quasi-continuous network structured (Ti3AlC2-Al3Ti)/2024Al composite

A multiscale elastoplastic damage model to predict mechanical response and fracture behavior of quasi-continuous network structured (Ti3AlC2-Al3Ti)/2024Al composites under uniaxial tension, along with the flexible program for structure reconstruction is proposed. Microscale constituents consist of dispersed in-situ Al3Ti and matrix, while the mesoscale constituents include Ti3AlC2, the matrix, and the interface. The brittle damage model is employed to degrade the stiffness of Ti3AlC2, and a modified Johnson-Cook model is applied to the matrix to accommodate the effect of grain size on the yield strength of the material. The period boundary condition is adopted to the bilinear constitutive relation in microscale analysis, and the output is calculated and transferred to mesoscale as the interface property of Ti3AlC2 and matrix. The numerical simulation results agree well with that of the corresponding quasi-static tension experiment and the deformation response of quasi-continuous network structured (Ti3AlC2-Al3Ti)/2024Al composites is discussed.

Multi-view and multi-scale behavior recognition algorithm based on attention mechanism.

Human behavior recognition plays a crucial role in the field of smart education. It offers a nuanced understanding of teaching and learning dynamics by revealing the behaviors of both teachers and students. In this study, to address the exigencies of teaching behavior analysis in smart education, we first constructed a teaching behavior analysis dataset called EuClass. EuClass contains 13 types of teacher/student behavior categories and provides multi-view, multi-scale video data for the research and practical applications of teacher/student behavior recognition. We also provide a teaching behavior analysis network containing an attention-based network and an intra-class differential representation learning module. The attention mechanism uses a two-level attention module encompassing spatial and channel dimensions. The intra-class differential representation learning module utilized a unified loss function to reduce the distance between features. Experiments conducted on the EuClass dataset and a widely used action/gesture recognition dataset, IsoGD, demonstrate the effectiveness of our method in comparison to current state-of-the-art methods, with the recognition accuracy increased by 1-2% on average.

Using the Intrinsic Geometry of Binodal Curves to Simplify the Computation of Ternary Liquid-Liquid Phase Diagrams.

Phase diagrams are powerful tools to understand the multi-scale behaviour of complex systems. Yet, their determination requires in practice both experiments and computations, which quickly becomes a daunting task. Here, we propose a geometrical approach to simplify the numerical computation of liquid-liquid ternary phase diagrams. We show that using the intrinsic geometry of the binodal curve, it is possible to formulate the problem as a simple set of ordinary differential equations in an extended 4D space. Consequently, if the thermodynamic potential, such as Gibbs free energy, is known from an experimental data set, the whole phase diagram, including the spinodal curve, can be easily computed. We showcase this approach on four ternary liquid-liquid diagrams, with different topological properties, using a modified Flory-Huggins model. We demonstrate that our method leads to similar or better results comparing those obtained with other methods, but with a much simpler procedure. Acknowledging and using the intrinsic geometry of phase diagrams thus appears as a promising way to further develop the computation of multiphase diagrams.

An interpretable LSTM deep learning model predicts the time-dependent swelling behavior in CERCER composite fuels

The study proposes a reliable and trustworthy data-driven approach with high precision and low computational cost, to predict the multiscale irradiation swelling behavior within CERCER composite fuels. A Long Short-Term Memory (LSTM) deep learning model is utilized to process the sequential data obtained from high-fidelity multiscale simulations. The model is evaluated using the metrics of accuracy, efficiency, interpretability, and generalizability. Compared to the feedforward and recurrent neural network models, the results indicate that the LSTM is superior at capturing the time-dependent character of the swelling progression and accurately catching the initiation of the critical recrystallization phenomena. The global and local interpretations via Shapley additive explanation theory (SHAP) agree with the mechanism analysis in simulations and experimental findings. The former identifies that the loading parameters of fission rate and density are the primary determinants in modulating the swelling deformation, while the latter uncovers the competing mechanism between temperature and hydrostatic pressure. The proposed model showcases its capacity to generalize on a time-consuming simulation involving a time-discrete algorithm. It guarantees a rapid swelling prediction in 36.4 secs that greatly reduces the time needed for 20.7 h in FE simulations.

Assembly and Characterization of Length-Sorted, Aligned Boron Nitride/Carbon Nanotube Thin Film Composites Via Slow Vacuum Filtration

Globally aligned single-wall carbon nanotubes (SWCNTs) are a promising, scalable platform for studying fundamental physical phenomena and an important vehicle for optoelectronic device applications. Recent work by Rust et al. [1] has identified nanotube length as an important mediating factor in the degree and scale of SWCNT alignment via slow vacuum filtration (SVF).Building on this work and that of Walker et al. [2,3], we explore the co-assembly of length-sorted SWCNTs and boron nitride nanotubes (BNNTs) atop polycarbonate track-etched membranes. BNNTs have recently gained interest as a chirality-agnostic, wide-bandgap material for encapsulation, insulation, thermal/mechanical robustness, and visible-light transparency, while also having a similar high aspect ratio morphology, making them an exceptional and alignable host matrix for individualized CNT species. To prepare such hybrid assemblies, a polymer-assisted, depletion-based method was first used to length-sort different diameter SWCNT (alkane filled electric-arc, CoMoCAT, metallic-sorted Tuball), and BNNT nanotube populations. Thereafter, we investigated the impacts of tube lengths, relative BN/C fraction, mass loading, and presence of a global director force on the multi-scale assembly behavior. A combination of birefringence microscopy and polarized Raman spectroscopy probed and identified trends in global and local ordering under these conditions.[1] Rust, C., Shapturenka, P., Spari, M., Jin, Q., Li, H., Bacher, A., Guttmann, M., Zheng, M., Adel, T., Hight Walker, A. R., Fagan, J. A., & Flavel, B. S. (2022). The Impact of Carbon Nanotube Length and Diameter on their Global Alignment by Dead-End Filtration. Small (forthcoming).[2] Walker, J. S., Fagan, J. A., Biacchi, A. J., Kuehl, V. A., Searles, T. A., Hight Walker, A. R., & Rice, W. D. (2019). Global Alignment of Solution-Based Single-Wall Carbon Nanotube Films via Machine-Vision Controlled Filtration. Nano Letters, 19(10), 7256–7264.[3] Walker, J. S., Macdermid, Z. J., Fagan, J. A., Kolmakov, A., Biacchi, A. J., Searles, T. A., Walker, A. R. H., & Rice, W. D. (2022). Dependence of Single‐Wall Carbon Nanotube Alignment on the Filter Membrane Interface in Slow Vacuum Filtration. Small, 18, 2105619.

Exploring the responses of smallscale poultry keepers to avian influenza regulations and guidance in the United Kingdom, with recommendations for improved biosecurity messaging

Understanding how smallscale (‘backyard’) poultry keepers interpret and respond to governmental directives designed to reduce the transmission of highly pathogenic avian influenza (HPAI) is of paramount importance in preparing for future HPAI outbreaks. Qualitative insights from open questions in an online survey conducted during the 2021–22 HPAI season (1,559 responses) shed light on smallscale poultry keepers' understanding of, and responses to, governmental directives to control HPAI exposure and onwards transmission. A follow-up participatory workshop (21 participants) explored the HPAI-related information sources used by smallscale poultry keepers, their trust in these sources, perceptions of HPAI-related risk, and interpretation of, opinions on and adherence to government regulations and communications regarding biosecurity and housing measures. This paper draws on a multi-scale behaviour change model to explore barriers to compliance with HPAI-related regulations. Insights from behaviour settings theory reveal how poultry-keeping settings and routines might be ‘disrupted’ and ‘re-configured’ to improve long-term biosecurity and reduce the risk of HPAI exposure. The findings highlight the need for HPAI-related guidance that is tailored to smallscale poultry keepers. This guidance should include clear action points and simple, practical, affordable and sustainable suggestions for improving compliance with biosecurity measures.

Low-cost table-top experiments for teaching multi-scale geophysical fluid dynamics

Multi-scale instabilities are ubiquitous in atmospheric and oceanic flows and are essential topics in teaching geophysical fluid dynamics. Yet these topics are often difficult to teach and counter-intuitive to new learners. In this paper, we introduce our state-of-the-art Do-It Yourself Dynamics (DIYnamics) LEGO® robotics kit that allows users to create table-top models of geophysical flows. Deep ocean convection processes are simulated via three experiments – upright convection, thermal wind flows, and baroclinic instability – in order to demonstrate the robust multi-scale modeling capabilities of our kit. Detailed recipes are provided to allow users to reproduce these experiments. Further, dye-visualization measurements show that the table-top experimental results adequately agree with theory. In sum, our DIYnamics setup provides students and educators with an accessible table-top framework by which to model the multi-scale behaviors, inherent in canonical geophysical flows, such as deep ocean convection.

On the creep mechanisms and macroscopic creep rate modeling of high-uranium-density composite fuels

UN-U3Si2 composite fuel is a promising candidate of Accident Tolerant Fuels (ATFs). Its in-pile creep performance will have an important impact on the irradiation-induced thermo-mechanical coupling behavior and safety of fuel elements. Based on the existing mechanism-based creep models of UN and U3Si2, the finite element analysis was performed for the multi-scale creep behaviors of various UN-U3Si2 composite fuels, and the influences of the U3Si2 volume fraction, applied stress, temperature, fission rate, and grain size were investigated. The dominant creep mechanisms under different conditions were proposed, and the mechanism-based macroscopic creep rate model for the UN-U3Si2 composite fuels were correspondingly developed, quantitatively correlating with the macroscopic creep rate with the U3Si2 vol fraction, temperature, fission rate and equivalent stress. The creep rate predictions obtained by this model were in good agreement with the results of the finite element simulation. The research results indicate that: (1) the irradiation or thermal diffusion creep contributions from the UN and U3Si2 phases were dominated under various conditions; (2) the dislocation creep contributions from the dispersed-phase of U3Si2 were appreciable at the temperatures ranged from 500 K to 1300 K, while those of the matrix-phase of UN appeared only at an extremely high temperature of 1300 K; (3) different from the ordinary inert-matrix dispersion fuels, the macroscopic creep rates of UN-U3Si2 composite fuels were predicted to be almost independent of burnup, due to the slight difference in the irradiation swelling of UN and U3Si2; (4) the total creep contribution proportions of the U3Si2 or UN phase were almost equal to the initial volume fractions, while the creep contribution ratios within the UN or U3Si2 phase vary under different conditions. The evolutions of various creep contributions with the fission density were attributed to the fuel-swelling induced additional stresses.

Manipulating near-wall flow instability and transport characteristics by the airfoil probe: Investigation on a transonic compressor cascade

The flow field exhibits complex features, such as shock waves, wakes, and end wall vortices in a transonic cascade. Installation of airfoil probes exacerbates the multi-scale and unsteady behavior of the internal passage flow. Apart from inducing measurement errors, it also generates extra flow loss inevitably and further affects the measuring accuracy. This paper investigates the impact of airfoil probes on a transonic compressor cascade's unsteady behavior and transport characteristics. Using high-fidelity numerical simulations, the influence of pipe layouts on the flow field of instrumented blades is visualized, revealing highly radial asymmetry. Loss analysis uncovers entropy transport induced by the streamwise vortices, primarily manifested by large-scale angular deformation at the outlet. The vortex structures in the wake region are dominated by momentum transport, displaying regional evolution and momentary equilibrium. The vortex expansion plays a leading role in the global vortex transport process, which is strengthened by the presence of the probes. Spatiotemporal analysis of the unsteady flow field can reveal some features overlooked by conventional fluid mechanics analysis. Using proper orthogonal decomposition, wake vortex pairs' high-frequency oscillations and shedding behaviors are captured in adjacent modes for the first time. The proposed approach can provide a theoretical basis for in-depth investigations of instrumented blade flow fields at the transonic regime. Furthermore, corresponding research can promote the refinement of instrument design by enabling experimentalists to understand the effects of intrusive instruments on transonic flow fields.

Characterization of the L4/L5 rat facet capsular ligament macromechanical and microstructural responses to tensile failure loading

Low back pain is a prevalent condition that affects the global population. The lumbar facet capsular ligament is a source of pain since the collagenous tissue of the ligament is innervated with sensory neurons that deform with the capsule’s stretch. Regional differences in the microstructural and macrostructural anatomy of the spinal facets affect its capsule’s mechanical behavior. Although there are many studies of the cervical facet in human and rodent models, the lumbar capsular ligament’s multiscale behavior is less well-defined. This study characterizes the macroscale and fiber-scale changes of the rat lumbar facet capsule during tensile failure loading. An integrated polarized light imaging setup captured local fiber alignment during 0.08 mm/s distraction of 7 lumbar facets. Force, displacement, strain, and circular variance were measured at several points along the failure curve: the first instance when the local collagen fiber network realigns differentially (anomalous realignment), yield, the first peak in force corresponding to the capsule’s first failure, and peak force, defined as ultimate rupture. Those outcomes were compared across events. While each of force, displacement, and average maximum principal strain increased with applied tension, so did the circular variance of the collagen, suggesting that the fibers were becoming more disorganized. From the fiber alignment maps collected at each mechanical event, the number of anomalous realignment events were counted and found to increase dramatically with loading. The increased collagen disorganization and increasing regions of such disorganization in the facet capsule during loading can provide insights about how loading to the ligament afferent nerves may be activated and thereby produce pain.

Multi-scale dynamic behaviors of oxygen entering carbon fiber/epoxy resin interfaces under thermal environment

Understanding the thermo-oxidative ageing behavior of carbon fiber/epoxy resin interfaces at multiple scales is crucial for structural optimization and durable design of composites. Here we report the effects of oxygen entering the interface on the 3D ageing crack evolutions, interface spatial structures, and multi-scale dynamic mechanisms for carbon fiber/epoxy composites under a thermal environment using experiments and molecular dynamics (MD) simulations. The dynamic behaviors under ambient temperature environments were studied for comparison. Ageing cracks first appear at the interface and then spread to the surrounding resin-rich region as the ageing time increases. Interface cracks provide channels for oxygen to enter the interior of the composite. The MD results show that interface systems with fewer oxygen molecules have serious interface cracks, weaker interaction energies and stronger diffusion capabilities than those with more oxygen molecules. The oxygen amounts entered the interface and the intermolecular interactions affect the interface dynamic behaviors. High temperature promotes the molecular movement, accelerates the interface cracking, weakens the interaction energy, and improves the diffusion capability. The diffusion of oxygen molecule from the interface to the epoxy matrix is a gradual process and is affected by the interface cracks.

Multifractal Features and Dynamical Thresholds of Temperature Extremes in Bangladesh

Multifractal detrended fluctuation analysis (DFA) can extract multi-scaling behavior and measure long-range correlations in climatic time series. In this study, with the help of multifractal DFA, we investigated the scaling behavior of daily minimum/maximum temperatures during the years 1989–2019 from 34 meteorological stations in Bangladesh. We revealed spatial patterns, topographic impacts and global warming impacts of long-range correlations embedded in small and large fluctuations in temperature time series. Meanwhile, we developed a multifractal DFA-based algorithm to dynamically determine thresholds to discriminate extreme and non-extreme events in climate systems and applied it to analyze the frequency and trends of temperature extremes in Bangladesh. Compared with widely-used percentile thresholds, the extreme climate events captured in our algorithm are more reliable since they are determined dynamically by the climate system itself.

Multiscale investigation on bitumen-aggregate interfacial debonding using molecular dynamics and finite element method

Adhesive failure between bitumen and aggregates is the primary cause of cracking in asphalt mixtures and pavement moisture damage. The resulting pavement distress poses a significant challenge to the service durability of the road infrastructure. Previous studies have validated that aggregate mineralogy has a significant influence on the adhesion properties between bitumen and aggregates; however, there is still a lack of a mechanistic understanding of the influence of the mineral constitution and distribution on the interfacial debonding behavior. This study aims to fill this knowledge gap by proposing a multiscale approach based on molecular dynamics (MD) simulations and the finite element method (FEM). First, the MD method was employed to extract the traction-separation curve of the interface between bitumen and minerals at a molecular scale. The obtained traction-separation relationship was then utilized as the input parameter for the zero-thickness cohesive element in the microscale bitumen-aggregate finite element model. The combined simulation results indicate that quartz with bitumen has the best cracking resistance at the molecular scale, followed by albite, mica, pyroxene, and anorthite. Among the three selected aggregates, the greywacke aggregate exhibited the best cracking resistance at the microscale level. Moreover, the distribution microstructure of the minerals was found to affect the cracking path of the bitumen-aggregate interface, and the bitumen-mica interface elements at the junction area with quartz have a late debonding. The proposed research method spearheads the prediction of multiscale bitumen-aggregate interfacial behavior by considering the aggregate mineralogical heterogeneity.

Multiscale Relaxation Behavior of Amorphous Plasticized Poly(vinyl butyral).

As a key component in laminated glass, plasticized polyvinyl butyral (PVB) interlayer is a kind of impact resistant polymer material with high toughness. Recently, by using ultra-small angle X-ray scattering (USAXS) technique, we have reported that stretch-induced phase separated structure on the scale of hundreds of nanometers formed in plasticized PVB for the first time. In this work, the multiscale relaxation behavior of plasticized PVB was further investigated. The relaxation behavior of deformed plasticized PVB was studied from macroscopic stress, mesoscopic phase separated structure and microscopic chain segment by combining USAXS, birefringence with in-situ stretching device. The contributions of chain segments and hydrogen bonding clusters for the multiscale relaxation behavior are discussed. This article is protected by copyright. All rights reserved.

Enhanced multi-scale nanomechanical deformation behavior in reactive plasma sprayed Fe-based amorphous/TiNx composite coating

Creep performance plays a pivotal role in evaluating the stability of materials during application. In particular, creep in amorphous alloys exhibits nonlinear and outburst characteristics. This work attempted to strengthen the Fe-based amorphous coating under loading by introducing TiNx ceramic material with high stability to the amorphous interlamellar. The results revealed that the creep resistance and indentation size effect of the composite coating were improved, compared with the monolithic Fe-based amorphous coating. The creep curves of both coatings can be well fitted by the Kelvin-Voigt formula composed of two relaxation processes. Moreover, the diffusion-mediated creep ratio of the composite coating was higher than that of the amorphous coating. And the composite coating had less free volume. Accordingly, more shear transition regions were activated synergistically during the deformation process, so the atom rearrangement effect was enhanced, which was well proved by the time relaxation spectrum and deformation characteristics. The expansion caused by excessive free volume in the amorphous shear band region caused plastic flow and strain softening. While the less free volume in the composite coating improved this situation, showing a less obvious indentation size effect. Ceramic phase doping appears to be a very effective and promising way to wield the plastic flow, accordingly to modify the amorphous coating.

A multi-scale damage model and mechanical behavior for novel light-weight C/C honeycomb sandwich structure

The high-resolution spacecraft poses an urgent need for opto-mechanical structure with ultra-high stability and light-weight. Owing to the advantages of both carbon fiber-reinforced carbon-based composites (C/C composites) and honeycomb sandwich structure, a novel C/C honeycomb sandwich structure strategy is proposed in this study. It was fabricated by using weaving fabrics and Chemical Vapor Infiltration (CVI) process, then was tested under out-of-plane compression. Taking the weave structure of honeycomb wall, anisotropy characteristics and damage mechanism of C/C composites, as well as the parameters of core size, a multi-scale damage model is established and validated to investigate mechanical behavior of the novel structure. The effects of influence factors (side length, thickness and height of core) on mechanical properties and damage mode of the novel sandwich structure are investigated. The results demonstrate that the optimal honeycomb core sizes for improving the light-weight and high load-bearing integration performance are l = 5 mm–7.5 mm and t = 0.3 mm–0.4 mm. The matrix damage occurs in the middle region of core, while fiber damage occurs at the end of core when its height reaches 15 mm. This study is helpful for design and optimization for opto-mechanical structure of high-resolution spacecraft.