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To enhance the reuse of construction waste in structural materials and improve the interfacial transition zone (ITZ) in recycled concrete (RC), this study employed two modification strategies and conducted a multiscale analysis to compare the effects of combined Nano-SiO2 (NS)/ethylene-vinyl acetate copolymer (EVA) modification and EVA-only modification on the mechanical properties, hydration characteristics, and microstructure of RC. The aim was to better overcome the interface defects in recycled concrete through synergistic modification. Experimental results show that the incorporation of EVA and NS significantly improves the mechanical properties of RC, with the combined modification outperforming the single modification. Specifically, when EVA content is 5% and NS is 2%, the 28-day compressive, shear, and flexural strengths of concrete increased by 15.7%, 17.6%, and 18.5%, respectively. Microscopic tests, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR), revealed that the cement matrix became denser, the porosity decreased, and the content of hydrated calcium silicate (C-S-H) increased. Molecular dynamics (MD) simulations indicate that EVA-only modification enhances interfacial bonding through hydrogen and ionic bonds, while the combined modification further strengthens the interface by forming additional Si-O-Si bonds, thereby improving the overall cohesion between the new and old concrete. [ABSTRACT FROM AUTHOR]

This study presents a methodology for characterizing the constituent properties of composite materials by back-calculating from the laminate behavior under fatigue loading. Composite materials consist of fiber reinforcements and a polymer matrix, with the fatigue performance of the laminate governed by the interaction between these constituents. Due to the challenges in directly measuring the properties of individual fibers and the polymer matrix, a reverse-engineering approach was employed. Using the micro-mechanics of fatigue (MMFatigue), we predicted the laminate's fatigue behavior based on assumed constituent properties and compared these predictions with experimental data from fatigue tests. The properties of the fiber and polymer matrix were iteratively adjusted to minimize the differences between predictions and experimental results, enabling accurate fatigue characterization. To ensure robustness, three laminate angles—0°, 30°, and 60°—were evaluated at three temperatures: low temperature (LT: −40 °C), room temperature (RT: 25 °C), and high temperature (HT: 85 °C). The error, defined as the fatigue life difference between the prediction and the experimental results, were obtained as 2.48% at LT, 7.18% at RT, and 1.25% at HT for a laminate angle of 45°. Finally, the applicability of the multiscale-based fatigue life prediction method was demonstrated through studies on laminates with various angles under tension–compression, and compression–compression cyclic loads, as well as composite pressure vessels under cyclic loading. [ABSTRACT FROM AUTHOR]

Finding the relevant scale to observe the influence of a process is one of the most important purposes of multiscale surface characterization. This study investigates various methods to determine a pertinent scale for evaluating the relationship between the relative area and grit blasting pressure. Several media types were tested alongside two different methods for calculating the relative area and three bootstrapping approaches for scale determination through regression. Comparison with the existing literature highlights innovations in roughness parameter characterization, particularly the advantages of relative area over traditional parameters like Sa. This study also discusses the relevance of different media types in influencing surface topography. Additionally, insights from a similar study on the multiscale Sdq parameter and blasting pressure correlation are integrated, emphasizing a scale relevance akin to our Sdr method's 120 µm cut-off length. Overall, our findings suggest a pertinent scale of 10,000 µm2 for the Patchwork method and a 120 µm cut-off length for the Sdr method, derived from bootstrapping on residual regression across all media. At the relevant scale, every value of R2 inferior to 0.83 is not significant with the threshold of 5% for the two methods of calculation of the relative area. This study enhances the understanding of how media types and blasting pressures impact surface topography, offering insights for refining material processing and surface treatment strategies. [ABSTRACT FROM AUTHOR]

This study employs polyvinyl alcohol (PVA) fibers and silane coupling agent (SCA) to augment rubberized concrete mechanical prowess. A multiscale investigation delves into the synergistic enhancement mechanism of SCA on the interfaces of PVA/cement and rubber/cement, considering macroscopic mechanical properties, microscopic structural characteristics, and nanoscale interface interactions. Initially, fundamental mechanical performance tests reveal a notable enhancement in compressive and flexural strength with the inclusion of SCA and PVA fibers in rubberized concrete. Subsequently, observations of corresponding composite concrete slices are conducted using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FT-IR). The results manifest gel and polymer filling interface gaps, with SCA fostering a tighter amalgamation of the two interfaces, effectively rectifying interface defects and elucidating its bonding effects at the microscopic interface. Molecular dynamics (MD) modeling and simulation analyses of PVA/C-S-H and rubber/C-S-H, pre- and post-SCA modification, demonstrate that SCA mitigates interface effects, reinforcing hydrogen bonding, van der Waals interactions, Ca-H coordination bonds, and stability. This augmentation enhances interface adhesion energy, fortifying the weak interface bonding between PVA fibers, rubber, and inorganic silicate (C-S-H). Ultimately, portal frame experiments substantiate that incorporating fiber rubberized concrete into structures not only fails to diminish but marginally enhances the load-bearing capacity of the framework. This research furnishes concrete and innovative solutions for sustainable development while providing a valuable reference for the future application of PVA fiber rubberized concrete materials in practical engineering endeavors. [ABSTRACT FROM AUTHOR]

Health monitoring has garnered significant and increasing attention from the research community and industrial practices thanks to its critical role in ensuring the safe operation of machinery and maintenance schedule. With regard to this, this paper introduces a novel diagnostic approach called fluctuation-based symbolic dynamic entropy (FSDE), which can enhance noise immunity and computational efficiency by utilizing fluctuation-based entropy algorithm and symbolic dynamic filtering. Moreover, the noise immunity and computational efficiency of FSDE, permutation entropy, fuzzy entropy, and sample entropy are compared by simulation signals. The simulation results show that FSDE has a more robust anti-noise performance and higher computational efficiency than the other three entropy methods. In order to extract fault features more thoroughly, multiscale analysis is applied to the entropy method, and multiscale FSDE (MFSDE) is proposed. MFSDE divides the measurement data into several scale series by coarse-grained technology, and then, FSDE is used to process each scale series separately. A series of experiments verify the effectiveness of MFSDE in fault feature extraction of fault diagnosis. Furthermore, the experimental results substantiate that MFSDE outperforms the other three currently used entropy-based approaches in terms of accuracy in classifying different health conditions of transmission systems. [ABSTRACT FROM AUTHOR]

In this research, a 3D multiscale model was applied for the analysis of long-term deformation of mudstone under high stress. Firstly, Voronoi tessellation generating and cohesive elements inserting programs were developed by Python-driven ABAQUS to establish a multiscale numerical analysis platform. In addition, creep damage effects for high stress were investigated through tests. Extended Drucker–Pranger model with strain hardening creep was developed for the calculation of mudstone viscoelastic plasticity. Finally, the creep damage model was integrated with multiscale analysis platform to evaluate the creep process of samples. The results verified that the developed model was effective in multiscale numerical analysis. [ABSTRACT FROM AUTHOR]

This work presents a homogenization damage approach for brittle composites based on the concept of Representative Volume Element (RVE) performing complex numerical analysis of the mechanical behavior of materials with individual characteristics of constituent phases. Focusing on concrete material, cement paste and transition zone are modeled as damaged materials using the Mazars' model, while the aggregates are modeled as linear elastic material. A based homogenization damage model technique is obtained and it is applied to describe the damage in the macrostructure. Results for concrete microstructures are presented and the homogenized responses demonstrate the expected behavior, including comparison with experimental test. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) empowers the creation of high‐performance cellular materials, underscoring the increasing need for programmable and predictable energy absorption capabilities. This study evaluates the impact of a precisely tuned fused filament fabrication (FFF) process on the energy absorption and failure characteristics of 2D‐thermoplastic lattice materials through multiscale experiments and predictive modeling. Macroscale in‐plane compression testing of both thick‐ and thin‐walled lattices, along with their µ‐CT imaging, reveal relative density‐dependent damage mechanisms and failure modes, prompting the development of a robust predictive modeling framework to capture process‐induced performance variation and damage. For lower relative density lattices, an FE model based on the extended Drucker–Prager material model, incorporating Bridgman's correction with crazing failure criteria, accurately captures the crushing response. As lattice density increases, interfacial damage along bead‐bead interfaces becomes predominant, necessitating the enrichment of the model with a microscale cohesive zone model to capture interfacial debonding. The predictive modeling introduces an enhancement factor, offering a straightforward method to assess the impact of the AM process on energy absorption performance, thereby facilitating the inverse design of FFF‐printed lattices. This approach provides a critical evaluation of how FFF processes can be optimized to achieve the highest attainable performance and mitigate failures in architected materials. [ABSTRACT FROM AUTHOR]

Accurate landslide susceptibility assessment is vital for disaster prevention, but current mapping lacks systematic analysis of the underlying mechanisms between multi-scale factors and model performance. Taking Zhenxiong County as an example, this paper combines the IV, WOE, LR models, and PCA to reveal the impact of methodological differences and scale selection on mapping results, and quantitatively evaluates them using ROC curves and landslide density statistics. Results show that: 1) The scale effect of influencing factors is significant. Natural factors such as topography, geological conditions, and rainfall play dominant roles at the regional scale, while the impacts of human activities, geological features, and soil erosion intensity are more pronounced at local and moderate scales. 2) The landslide susceptibility mapping results of the three models at different spatial scales show similar spatial distribution trends. As the spatial scale increases, high/very high susceptibility areas and low/very low susceptibility areas spread outward, while the spatial distribution of medium susceptibility areas shows a fragmented expansion outward first and then agglomeration and contraction inward. 3) Scale selection significantly affects the accuracy of landslide susceptibility mapping, and expanding the spatial scale appropriately improves mapping precision. The IV and WOE models show the highest AUC at the 600-m buffer, while the LR model peaks at 400 m. In terms of landslide identification accuracy, the IV model performs best at 400-m buffer, WOE at 600-m buffer, and LR at 100 -meter buffer. 4) Different methods have different mapping performances. Overall, the IV model performs best, followed by the WOE model, with the LR model lagging behind. In terms of high-risk area recognition, the LR model excels, followed by the IV model, while the WOE model performs relatively poorly. 5) Scale and method selection significantly impact landslide susceptibility mapping outcomes. The IV model excelled in global prediction at the 600-m buffer, whereas the LR model was effective in pinpointing high-risk areas at the 100-m buffer. This paper proposes a landslide susceptibility evaluation method that integrates model performance and scale effects, enhancing disaster assessment and prevention capabilities. [ABSTRACT FROM AUTHOR]

In the damage analysis of material with complex microstructures, a full‐scale direct numerical simulation (DNS) could produce huge computational costs. Alternatively, multiscale modeling is a more effective method by using less degrees of freedom to balance the calculation accuracy and cost. In this paper, a new multiscale damage modeling method is proposed based on the framework of the variational effective model originally presented by Jezdan et al. and the relaxation damage model presented by Junker et al. A variational statement for the free energy and the dissipation potential for a coarse scale model is constructed by relating the free energy and dissipation potential of the fine scale model. In this way, the coarse scale damage variable is defined instead of directly solving in the fine scale model; therefore, the computational efficiency can be increased. Besides, the relaxation damage model can effectively avoid ill‐posed boundary value problems in damage analysis without use of gradients or integration techniques. Two numerical examples are provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study implements the permutation Jensen–Shannon distance as a metric for discerning ordinal patterns and similarities across multiple temporal scales in time series data. Initially, we present a numerically controlled analysis to validate the multiscale capabilities of this method. Subsequently, we apply our methodology to a complex photonic system, showcasing its practical utility in a real-world scenario. Our findings suggest that this approach is a powerful tool for identifying the precise temporal scales at which two distinct time series exhibit ordinal similarity. Given its robustness, we anticipate that this method could be widely applicable across various scientific disciplines, offering a new lens through which to analyze time series data. [ABSTRACT FROM AUTHOR]

Surface microgeometry created by the energy of electric discharges is related to surface wetting behavior. These relationships change depending on the scale of observation. In this work, contact angles correlated with the surface complexity of AA 6060 after electro-discharge machining were analyzed at different observation scales. This research focuses on the methodology of selecting the best scales for observing wetting phenomena on irregular surfaces, as well as indicating the topographic characterization parameters of the surface in relation to the scales. Additionally, the geometric features of the surface that determine the contact angle were identified. In this study, the surfaces of an aluminum alloy are rendered using focus variation 3D microscopy and described by standardized ISO, area-scale, and length-scale parameters. The research also confirms that it is possible to design surface wettability, including its hydrophilicity and hydrophobicity, using electrical discharge machining parameters. The static and dynamic behavior of liquids on surfaces relevant to contact mechanics was also determined. [ABSTRACT FROM AUTHOR]

Here, we propose a method for the semantic segmentation of 3D point clouds based on functional data analysis. For each point of a training set, a number of handcrafted features representing the local geometry around it are calculated at different scales, that is, varying the spatial extension of the local analysis. Calculating the scales at small intervals allows each feature to be accurately approximated using a smooth function and, for the problem of semantic segmentation, to be tackled using functional data analysis. We also present a step-wise method to select the optimal features to include in the model based on the calculation of the distance correlation between each feature and the response variable. The algorithm showed promising results when applied to simulated data. When applied to the semantic segmentation of a point cloud of a forested plot, the results proved better than when using a standard multiscale semantic segmentation method. The comparison with two popular deep learning models showed that our proposal requires smaller training samples sizes and that it can compete with these methods in terms of prediction. [ABSTRACT FROM AUTHOR]

We consider a class of infinite weighted metric trees obtained as perturbations of self‐similar regular trees. Possible definitions of the boundary traces of functions in the Sobolev space on such a structure are discussed by using identifications of the tree boundary with a surface. Our approach unifies some constructions proposed by Maury, Salort, and Vannier for discrete weighted dyadic trees (expansion in orthogonal bases of harmonic functions on the graph and using Haar‐type bases on the domain representing the boundary), and by Nicaise and Semin and Joly, Kachanovska, and Semin for fractal metric trees (approximation by finite sections and identification of the boundary with a interval): We show that both machineries give the same trace map, and for a range of parameters we establish the precise Sobolev regularity of the traces. In addition, we introduce new geometric ingredients by proposing an identification with arbitrary Riemannian manifolds. It is shown that any compact manifold admits a suitable multiscale decomposition and, therefore, can be identified with a metric tree boundary in the context of trace theorems. [ABSTRACT FROM AUTHOR]

Experimental observations have revealed a change in the concavity of the resultant force-displacement plot in the extension test for pantographic sheets. In this paper, we aim to relate these macroscopically observed mechanical properties with the microscale properties of the hinges (or pivots) connecting the pantographic fibers. The material constituting the hinges is modeled at the microscale as an isotropic elastoplastic 3D Cauchy continuum. The elastic regime is assumed to be linear, while the plastic regime exhibits either saturating or non-saturating hardening. In the case of circular homogeneous cylindrical hinges, monotonic loading is considered to derive a mesoscale constitutive relation linking the torsional angle to the total applied torque. It is demonstrated that (non-)saturating hardening at the microscale results in (non-)saturating hardening of the twist angle/torque plot at the mesoscale, which itself is responsible for the change of concavity in bias extensional test of pantographic sheets. [ABSTRACT FROM AUTHOR]

This paper presents the results of studies aimed at assessing the impact of the molding process on the variability of surface irregularities of casting models. This research was conducted using a selected multiscale method, i.e., wavelet transformation, in both discrete and continuous perspective. The test samples were made both based on traditional methods of manufacturing casting models, i.e., machining of aluminum and wood, as well as using three additive technologies. The impact of the forming process on the variability of the topography of the produced models was evaluated. This research comprehensively relates to the assessment of the applicability of additive technologies, which are increasingly used in various industrial areas, as well as the impact of the process on surface topography in relation to scale. The statistical assessment based on the ANOVA analysis demonstrated that it is possible to distinguish between the surfaces before and after a specific number of forming cycles. Studies have shown that the impact of the forming process is relatively small, mainly affecting the long-term irregularity components, and there are no functional dependencies in terms of the impact of the forming process on the variation in surface topography in relation to the manufacturing method or its parameters. [ABSTRACT FROM AUTHOR]

A three-dimensional (3D) multiscale modelling approach was developed in this study, which considers a two-way coupling of material properties and mechanical responses between macroscale (pavement level) and mesoscale (mixture level) finite element (FE) models. Both thermal and mechanical properties at the two scales were linked through a homogenisation method, and the boundary response was transferred from the macroscopic target element to the mesoscale model using a mapping procedure. The results show that seasonal temperature variations have a significant effect on the coupled thermo-mechanical response within bridge deck pavement. In winter, the deck pavement is subject to tensile stresses, the maximum values of which mainly occur at the tire edges and the dual-tire clearance centre; while the deck pavement experiences compressive stresses in summer, and the stress difference within the asphalt concrete layer increases with the temperature. [ABSTRACT FROM AUTHOR]

In the past decade, topological data analysis has emerged as a powerful algebraic topology approach in data science. Although knot theory and related subjects are a focus of study in mathematics, their success in practical applications is quite limited due to the lack of localization and quantization. We address these challenges by introducing knot data analysis (KDA), a paradigm that incorporates curve segmentation and multiscale analysis into the Gauss link integral. The resulting multiscale Gauss link integral (mGLI) recovers the global topological properties of knots and links at an appropriate scale and offers a multiscale geometric topology approach to capture the local structures and connectivities in data. By integration with machine learning or deep learning, the proposed mGLI significantly outperforms other state-of-the-art methods across various benchmark problems in 13 intricately complex biological datasets, including protein flexibility analysis, protein-ligand interactions, human Ether-à-go-go-Related Gene potassium channel blockade screening, and quantitative toxicity assessment. Our KDA opens a research area--knot deep learning--in data science. [ABSTRACT FROM AUTHOR]

Auroral field‐aligned currents (FACs) have an intrinsic complexity caused by the superposition of contributions from a broad spectrum of scales and diversity of locations. The complex FAC systems are investigated by using the multiscale minimum variance analysis. This technique provides a scale based decomposition of the FAC systems by identifying the constituting FAC elements as well as their structure. At the basis, the analysis exploits the scale dependence of the eigenvalues of the magnetic field variance matrix. The scale decomposition along the transversal (latitudinal) direction results from the scale derivative of the maximum eigenvalue. The complementary information from the scale derivative of the minimum eigenvalue helps to infer the full structure of each FAC element by providing estimates of the FAC length (longitudinal) scale. The scale derivative of minimum and maximum eigenvalues are used to identify FAC signatures associated to different types of aurora (e.g., highly extended, finite arcs, gradient regions) as well as to characterize the influence of the crossing location with respect to the FAC structures (e.g., near edge crossings). The multiscale analysis is applied to simulated FACs and to spacecraft observations made by the Swarm mission. The use with real world data illustrates the power of this analysis, whose full benefits for magnetosphere‐ionosphere coupling investigations are yet to be explored. Plain Language Summary: The analysis in this work applies to magnetic field observations from satellites crossing above the aurora. The complexity of auroral displays relates to complex currents that flow along the Earth main magnetic field. These currents are observed as a perturbation magnetic field. The added contributions from currents of different spatial scales, locations and life‐times lead to complex signatures of the field‐aligned currents. The analysis here traces this complexity by a decomposition of the measured magnetic field perturbation into discrete current elements. The aim is to decompose the magnetic field observations into the constituent discrete elements and to characterize their respective structures. The analysis is applied to Swarm observations whereas the ground optical observations provide a qualitative cross‐check to the analysis. Key Points: Single‐spacecraft decomposition of complex field‐aligned current (FAC) systems associated to finite length (east‐west) auroral structuresEstimation of the geometric structure of finite FACs by the transversal and longitudinal scalesIdentification of FAC signatures associated to finite FACs like the crossings near the eastward/westward edges of longitudinally extended FACs [ABSTRACT FROM AUTHOR]

Understanding the impacts of habitat conversion on species assemblages across multiple biodiversity dimensions (taxonomic, functional, and phylogenetic) and spatial scales is pivotal for implementing effective conservation strategies. Here, we surveyed phyllostomid bats using mist nets in riparian and unflooded forests, flooded savannahs, and conventional rice fields to investigate how changes in habitat quality affect multifaceted diversity from two Colombian farming systems in the Orinoco Llanos: traditional farmlands with high‐intensity agriculture (mainly rice production) and Civil Society Nature Reserves with greater ecosystem protection. We used a unified framework based on Hill numbers for quantifying bat taxonomic, functional, and phylogenetic diversity and modeled the relationship of these diversity facets with landscape variables (habitat cover and patch density) across three spatial scales (0.5, 1.5, 3 km) using Bayesian generalized linear mixed‐effect models. Our results indicate that increasing human activity toward rice monocultures representative of traditional farmlands negatively affected all diversity facets. In contrast, forested habitats associated mainly with riparian forests within private reserves contained higher taxonomic, functional, and phylogenetic diversity than savannahs and rice fields. However, the differences between riparian forests and rice crops were significant only for phylogenetic diversity, indicating loss of evolutionary history after habitat conversion. At the landscape scale, forest cover was a significant predictor for functional (0.5‐ and 3‐km scale) and phylogenetic diversity (0.5 km), and bats responded negatively at the 3‐km scale to rice patch density from a functional diversity perspective. Increasing habitat quality through preserving forest cover and patches should minimize the harmful effects of habitat conversion on multidimensional bat biodiversity. Furthermore, the conservation of riparian forests and the creation of more wildlife‐friendly farming, as practiced in the reserves, should be prioritized to ensure high levels of bat taxonomic, functional, and phylogenetic diversity across Orinoco countryside landscapes. [ABSTRACT FROM AUTHOR]

A multiscale model is developed for stress analysis and burst speed prediction of a titanium matrix composite (TMC) ring. The proposed multiscale model is based on finite-volume directly averaging micromechanics (FVDAM) to connect the TMC ring and the composite microstructure. Moreover, Bodner-Partom's constitutive model is adopted to characterise the viscoplasticity of the titanium cladding and the matrix. The effects of viscoplasticity on the mechanical behaviour and burst speed of the TMC ring are presented and discussed for the first time via macromechanical and micromechanical analysis. The results suggest that considering the viscoplasticity of the titanium matrix and cladding leads to a decrease in the burst speed of the TMC ring, especially at elevated temperatures such as 315 ℃ and 482 ℃. Burst rupture of the TMC ring also occurs after a certain time in the load-holding stage at these elevated temperatures and a low, constant angular speed, even though no burst rupture is predicted in the loading stage. Hence, the newly defined load-holding burst speed, which is relative to the load-holding time, is predicted at elevated temperatures. The results of the load-holding burst speed provide more comprehensive information on the safety assessment of a TMC ring at elevated temperatures. [ABSTRACT FROM AUTHOR]