Nonlinear Composites Research Articles

A Non-Linear Multi-Objective Service Composition Optimization for Smart Agriculture with Lagrange’s Interpolation-based Evolutionary Algorithm

A Non-Linear Multi-Objective Service Composition Optimization for Smart Agriculture with Lagrange’s Interpolation-based Evolutionary Algorithm

Novel rate-based modeling and mass transfer performance of CO2 absorption in rotating spiral contactor

For the process of CO2 absorption, existing gas-liquid contactors suffer from low mass transfer performance and low gas-liquid ratios. In this study, a rotating spiral contactor was developed to overcome these drawbacks and a novel rate-based model was developed to predict the CO2 absorption performance. The effective interfacial area (ae), overall volumetric mass transfer coefficient (KGae) and CO2 absorption efficiency (η) were investigated. The results showed that the ae was 913–1125 m2/m3 superior to the conventional contactor. In the range of gas–liquid ratio of 200–1800, the KGae and η were 1.4–10.1 kmol.m-3.h-1.kPa-1 and 40.5–99.6 %, respectively. The rate-based model predicted the KGae and η with the AARD of 6.71 % and 1.90 %, respectively. Also, it has better robustness even in highly nonlinear temperature and composition distributions. This study provides a potential contactor and a new modeling tool for CO2 capture and other gas-liquid separation.

A statistical high-order reduced model for nonlinear random heterogeneous materials with three-scale micro-configurations

An effective statistical higher-order three-scale reduced homogenization (SHTRH) method is established to analyze the nonlinear random heterogeneous materials with multiple micro-configurations. Firstly, the various unit cell functions based on the microscale and mescoscale regions are given, and two expected homogenization coefficients are computed through Kolmogorov's strong laws of large number. Further, the nonlinear homogenized equations are formulated, and the corresponding reduced-order multiscale systems for displacement and stress solutions are derived by using the high-order unit cell solutions and homogenized solutions. The key features of the new statistical multiscale methods are (i) the novel reduced models established to solve the inelastic problems of random composites at a fraction of cost, (ii) the high-order homogenized solutions which do not need high-order continuity for the macro solutions of the random problems and (iii) the statistical high-order multiscale algorithms developed for analyzing the nonlinear random composites with three-scale structures. Finally, the effectiveness and correctness of the algorithm are confirmed according to several hyperelastic, plasticity and damage periodic/random composites with multiple-scale configurations. The computation shows that the proposed SHTRH methods are useful for analyzing the macroscopic nonlinear performance, and can efficiently catch the microscopic and mesoscopic information for the random heterogeneous composites.

Nonlinear composition dependence of hydrogen bond lifetime in water-DMSO binary mixtures: The role of hydrophobic interaction.

The lifetime of a hydrogen bond between water and dimethyl sulfoxide (DMSO) is found to be considerably longer than that between two water molecules in neat water. This is counter-intuitive because the charge on the oxygen in DMSO is considerably less than that in water. Additionally, the strength of the water-dimethyl sulfoxide (w-D) hydrogen bond is found to be strongly composition dependent; the lifetime of the hydrogen bond is ten times larger at 30% than at very low concentrations. Using computer simulations, we perform microscopic structural and dynamic analysis to find that these anomalies arise at least partly from an "action-at-a-distance" effect where the attraction between the hydrophobic methyl groups results in the self-aggregation of DMSO molecules that "cages" both the rotational and linear motions of the molecules involved. This is reflected in the observed strong correlation of the lifetime with the local coordination number of the associated methyl groups. The elongated w-D h-bond lifetime causes a slowdown of collective dynamics and affects the lifetime of the w-w h-bond. This nonlinear feedback mechanism explains the strong composition dependence of viscosity and is anticipated to play a dominant role in many self-assemblies. Furthermore, the w-D hydrogen bond breaking mechanism changes from low to high DMSO concentration, a phenomenon not anticipated a priori. We introduce a new order parameter-based free energy surface of the bond breaking pathway. A two-dimensional transition state rate theory calculation is performed for the lifetime of the w-D h-bond that is found to be semi-quantitatively accurate.

Design engineering of non-linear graded InAlAs metamorphic buffer layers for efficient reduction of misfit dislocation density

Metamorphic InxAl1-xAs (xmax > 0.75) buffer layer (MBL) grown on GaAs with an optimized non-linear graded composition profile along the growth direction is proposed for enhanced reduction of misfit dislocation (MD) density in highly mismatched III-V/GaAs metamorphic heterostructures. The equilibrium distributions of MD density throughout such InxAl1-xAs/GaAs MBLs are calculated. The influence of the initial composition (xmin) of MBL and the elastically strained thin GaAs layer embedded into the InxAl1-xAs MBL on the MD density distribution was studied. An optimum value of the inverse step (Δ), representing the difference between the top In content of the InxAl1-xAs MBL and that of a In0.75Al0.25As virtual substrate (VS) grown atop is determined. It was theoretically shown that Δ above 0.04 results in relaxation of the elastic stresses in VS via formation of the MDs, while the lower Δ values allow growing the VS completely free of MDs. Finally, the metamorphic In0.75Al0.25As/graded-InAlAs/GaAs heterostructures differing from each other by only the composition profile of the graded-InAlAs MBL were grown by MBE on GaAs(001) and studied by atomic force microscopy. The structure with proposed optimized non-linear graded (x = 0.05–0.77) MBL demonstrated the ∼ 1.5 times less MD density as compared to that with the convex-graded (x = 0.05–0.81) MBL, which was estimated to be at the level of ∼ 2·107 cm−2.

Information geometric bound on general chemical reaction networks.

We investigate the convergence of chemical reaction networks (CRNs), aiming to establish an upper bound on their reaction rates. The nonlinear characteristics and discrete composition of CRNs pose significant challenges in this endeavor. To circumvent these complexities, we adopt an information geometric perspective, utilizing the natural gradient to formulate a nonlinear system. This system effectively determines an upper bound for the dynamics of CRNs. We corroborate our methodology through numerical simulations, which reveal that our constructed system converges more rapidly than CRNs within a particular class of reactions. This class is defined by the count of chemicals, the highest stoichiometric coefficients in the reactions, and the total number of reactions involved. Further, we juxtapose our approach with traditional methods, illustrating that the latter falls short in providing an upper bound for CRN reaction rates. Although our investigation centers on CRNs, the widespread presence of hypergraphs across various disciplines, ranging from natural sciences to engineering, indicates potential wider applications of our method, including in the realm of information science.

High aspect ratio Na–Co-oxide ceramic filler composites with novel electrical and dielectric properties

Polymer composites with high aspect ratio Na–Co oxide ceramic filler – polymer matrix was investigated in this study. They demonstrate high dielectric permittivity, low dielectric loss tangent values which is useful for capacitive field grading and reversible voltage dependent electrical conductivity properties under an applied electric field which can be utilized for resistive field grading. These unique properties are useful for electrical stress control applications in power components. This study employs novel ceramic platelets as the varistor filler component in a polymer composite form, introducing a new class of materials to the world of electrical stress control technology. By minimizing the amount of varistor filler material required to very low levels (15 wt%), it is possible to develop lightweight non-linear dielectric composites that not only exhibit improved electrical characteristics but also make processing easier and open up new design space for making various components for electrical power applications. By utilizing novel NaxCoO2 (x < 1) ceramic fillers in composite form, we aim to contribute to the development of innovative nonlinear dielectric composites that can enhance the performance and processibility of various power system components under various working environments.

Modelling of hybrid biocomposites for automotive structural applications

The demand for environmentally friendly materials is at its peak, and government legislations have become stricter and no longer tolerate violations. With biocomposites emerging as structural components instead of being hidden as non-structural applications and interiors, the automotive and motorsport sector started considering them for structural body parts. Natural fibres abundance, commercial availability, renewability, low density, low cost, and high tensile strength make biocomposite materials excellent candidates for eco-friendly vehicles. Several studies reported the utilisation of biocomposites as high-performance components and structural applications. However, current computer-aided engineering and modelling tools are insufficient to explore the vast field of possibilities during biocomposite materials selection to accurately predict the components' behaviour and analyses. Therefore, this study focuses on creating a material model to predict the behaviour of biocomposite materials. Additionally, the model is numerically implemented to illustrate the deformation and bending stiffness capabilities of a motorsport monocoque chassis structure application. A micromechanics modelling combining rate-dependant constitutive laws and multi-site interactions of inclusions is developed for studying the nonlinear response of composite materials. To avoid numerical instabilities when increments of time become very small, a regulation procedure concerning the visco-plastic function is adopted in the computation of the consistent tangent modulus. Based on the Generalised Mori–Tanaka (GMT) scheme, the effective properties are obtained for the nonlinear composite. The accuracy of the model is evaluated and validated by comparison results from the open literature. Finally, the developed constitutive equations are implemented as a user-defined material UMAT in a Finite Element code, leading to an application on a bio-based composite for the bamboo/flax fibre-reinforced epoxy hybrid composite materials.

Multiscale Computational and Artificial Intelligence Models of Linear and Nonlinear Composites: A Review

Herein, state‐of‐the‐art multiscale modeling methods have been described. This research includes notable molecular, micro‐, meso‐, and macroscale models for hard (polymer, metal, yarn, fiber, fiber‐reinforced polymer, and polymer matrix composites) and soft (biological tissues such as brain white matter [BWM]) composite materials. These numerical models vary from molecular dynamics simulations to finite‐element (FE) analyses and machine learning/deep learning surrogate models. Constitutive material models are summarized, such as viscoelastic hyperelastic, and emerging models like fractional viscoelastic. Key challenges such as meshing, data variability and material nonlinearity‐driven uncertainty, limitations in terms of computational resources availability, model fidelity, and repeatability are outlined with state‐of‐the‐art models. Latest advancements in FE modeling involving meshless methods, hybrid ML and FE models, and nonlinear constitutive material (linear and nonlinear) models aim to provide readers with a clear outlook on futuristic trends in composite multiscale modeling research and development. The data‐driven models presented here are of varying length and time scales, developed using advanced mathematical, numerical, and huge volumes of experimental results as data for digital models. An in‐depth discussion on data‐driven models would provide researchers with the necessary tools to build real‐time composite structure monitoring and lifecycle prediction models.

A data-driven model based on the numerical solution of the equivalent inclusion problem for the analysis of nonlinear short-fibre composites

The paper introduces a novel data-driven homogenization model developed for the computation of stress-strain curves for composites featuring arbitrary orientation distributions, aspect ratios, and volume fractions of fibres. The objective of the proposed model is to deliver both time-efficient and accurate results while taking into account a relatively small database. The database is generated through numerical solutions of the equivalent inclusion problem, encompassing results for predefined orientations and aspect ratios of the single inclusion (fibre). The database created for a specific matrix-fibre system can be employed by the surrogate model to predict outcomes for various cases involving different fibre configurations. The surrogate model comprises four key modules: aspect ratio interpolation, a discrete orientation averaging procedure involving a genetic algorithm, a spatial transformation procedure, and an iterative Mori-Tanaka scheme. The validity of the proposed data-driven model has been confirmed by comparing the obtained results with those acquired through analysis of the complex representative volume element (RVE) using Fast Fourier Transform (FFT)-based homogenization, as well as through comparisons with experimental results from the existing literature.

The use of generative music in nonlinear music composition for video games

The use of generative music in nonlinear music composition for video games

Retracted: Nonlinear Matrix Ferroelectric Composites on Construction Quality and Safety Measures

Retracted: Nonlinear Matrix Ferroelectric Composites on Construction Quality and Safety Measures

Mathematical micro–macro modeling of fully coupled nonlinear magneto-elastic reinforced composites

In this paper, integral equation formulations and field-dependent micromechanical modeling of global nonlinear magneto-mechanical behavior of magneto-elastic composites under high strain and magnetic field are elaborated. The modeling is obtained based on an extension of micro–macro transition inclusion problem to nonlinear behavior using field-dependent and highly nonlinear localization tensors. A methodological procedure is elaborated based on newly introduced strain and magnetic field-dependent Green tensors, strain and magnetic field-dependent integral equations linked to tensors of Eshelby and micromechanical approaches. The field-dependent global moduli are predicted based on the Mori–Tanaka approach and self-consistent method. Iterative incremental schemes based on the Newton–Raphson and fixed-point algorithms are examined and established precise semi-analytic equations of the effective magneto-elastic properties of composites that are dependent on the magnetic-strain field for different types of inclusions. A numerical code is elaborated for numerical predictions and the obtained field-dependent effective magneto-elastic coefficients are obtained and presented for various volume fractions of inclusion, types and shapes of the reinforced nonlinear composites.

Modeling Brain Representations of Words' Concreteness in Context Using GPT-2 and Human Ratings.

The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented opportunities to study the human brain in action as language is read and understood. Recent contextualized language models seem to be able to capture homonymic meaning variation ("bat", in a baseball vs. a vampire context), as well as more nuanced differences of meaning-for example, polysemous words such as "book", which can be interpreted in distinct but related senses ("explain a book", information, vs. "open a book", object) whose differences are fine-grained. We study these subtle differences in lexical meaning along the concrete/abstract dimension, as they are triggered by verb-noun semantic composition. We analyze functional magnetic resonance imaging (fMRI) activations elicited by Italian verb phrases containing nouns whose interpretation is affected by the verb to different degrees. By using a contextualized language model and human concreteness ratings, we shed light on where in the brain such fine-grained meaning variation takes place and how it is coded. Our results show that phrase concreteness judgments and the contextualized model can predict BOLD activation associated with semantic composition within the language network. Importantly, representations derived from a complex, nonlinear composition process consistently outperform simpler composition approaches. This is compatible with a holistic view of semantic composition in the brain, where semantic representations are modified by the process of composition itself. When looking at individual brain areas, we find that encoding performance is statistically significant, although with differing patterns of results, suggesting differential involvement, in the posterior superior temporal sulcus, inferior frontal gyrus and anterior temporal lobe, and in motor areas previously associated with processing of concreteness/abstractness.

A Perturbation Framework for Convex Minimization and Monotone Inclusion Problems with Nonlinear Compositions

We introduce a framework based on Rockafellar’s perturbation theory to analyze and solve general nonsmooth convex minimization and monotone inclusion problems involving nonlinearly composed functions as well as linear compositions. Such problems have been investigated only from a primal perspective and only for nonlinear compositions of smooth functions in finite-dimensional spaces in the absence of linear compositions. In the context of Banach spaces, the proposed perturbation analysis serves as a foundation for the construction of a dual problem and of a maximally monotone Kuhn–Tucker operator, which is decomposable as the sum of simpler monotone operators. In the Hilbertian setting, this decomposition leads to a block-iterative primal-dual algorithm that fully splits all the components of the problem and appears to be the first proximal splitting algorithm for handling nonlinear composite problems. Various applications are discussed. Funding: The work of L. M. Briceño-Arias was supported by Agencia Nacional de Investigación y Desarrollo-Chile [Grant Fondo Nacional de Desarrollo Científico y Tecnológico 1190871, Grant Centro de Modelamiento Matemático ACE210010, Grant Centro de Modelamiento Matemático FB210005, and basal Funds for Centers of Excellence], and the work of P. L. Combettes was supported by the National Science Foundation [Grant DMS-1818946].

The response of microbial compositions and functions to chronic single and multiple antibiotic exposure by batch experiment

Understanding the response of the microbial community to external disturbances such as micropollutants is vital for ecological risk evaluation. In this study, the effect of chronic antibiotic exposure on community compositions and functions was investigated by two batch experiments. The first experiment investigated the effect of chronic sulfamethoxazole (SMX) exposure, while the second investigated the combined effect of dissolved organic matter (DOM) sources and multi-antibiotic exposure. The results showed that the community responses to chronic antibiotic exposure depended on the dynamic balance among community resistance, adaptation, recovery, and selection, leading to nonlinear composition diversity variations. The disturbance strength of chronic SMX exposure increased with concentration (0.5–50 μg/L). However, complex sources and structures of coexisting organic matter might delay the disturbance by elevating metabolic activity and generating functional redundancy. Especially, when nutrient was a limiting factor, the disturbance strength by DOM source was greater than that by chronic antibiotic exposure. The resistance of abundant taxa to external distributions resulted in a low explanation of community diversity, while rare taxa played key roles in response to community variation and thereby affected community assembly. Long-term SMX exposure reduced the number of key species and favored the deterministic assembly process by 21%. However, elevated community adaptability might weaken the influence of antibiotic selection. Chronic SMX exposure elevated the relative abundance of sulfonamide resistance genes (sul1, sul2) by a factor of 1.2–4.3, while that of nitrogen-fixing genes (nifH, nifK) and the metabolic pathways related to the toluene, ethylbenzene, and dioxin degradation decreased. However, the combined influence of DOM sources and multi-antibiotic exposure barely caused the difference in the genes linking to element metabolism and drug resistance of microbial communities between blank and exposed groups. This study suggested that more concern should be given to the chronic environmental effect of organic micropollutants.

COVID-19 PREVENTION SIGNS IN THE INDONESIA'S SUPER PRIORITY TOURIST DESTINATION

After a long struggle against Covid-19 for more than a year, the spread of COVID-19 in Indonesia gradually decreased and was considerably under control. Several public places, including some tourist destinations, were allowed to re-open. The Ministry of Tourism and Creative Economy made 20 tourist attractions for trial, including the Borobudur temple, the world’s largest Buddhist temple. It is carried out cautiously and under strict health protocols procedure. Implementing health protocol regulations was encouraged by making and placing many protocol signs in strategic places. The aim of this study was to identify and investigate the compositions meaning of the COVID-19 prevention sign at Borobudur Temple. The data were collected through the documentation method with photographic technique. The result showed that all signs have real and ideal information value. Salience signs appear as a result of a variety of fascinating text and images. The framing of the sign is presented in centered/circular with a linear and nonlinear composition. Overall, the signs proved the management of Borobudur temple’s strong commitment to opening the site with strict protocols to prevent the spread of COVID-19 in the Borobudur area.

Numerical estimation via remeshing and analytical modeling of nonlinear elastic composites comprising a large volume fraction of randomly distributed spherical particles or voids

We investigate numerically via finite element (FE) simulations and analytically the nonlinear behavior of a soft matrix comprising a large volume fraction (up to 55%) of monodisperse spherical inclusions, which can be either rigid particles or voids. To address the issue of severe mesh distortion at large strains, we employ a successive remeshing and solution mapping technique that allows us to achieve a large macroscopic deformation, with the maximum attained stretch being at least two to three times when compared to that without remeshing. A general algorithm allowing to read complex arbitrary particle geometries is proposed and implemented allowing to remesh a finitely strained domain with randomly distributed inclusions of arbitrary shape. The present simulation results for a neo-Hookean elastic matrix filled with rigid particles show that the nonlinear stress–stretch uniaxial tension response can be well approximated by a neo-Hookean material with an effective shear modulus that depends on the volume fraction of the inclusions. Additionally, a study of the number of particles demonstrates that sixty four monodisperse spheres is a good compromise to reach accurate results for large deformations and maintain a reasonable CPU-time. The FE data serve as a powerful assessment tool for analytical homogenization models. Newly developed and existing models for small and large strains are proposed and assessed, respectively, for both rigid particles and voids. These results fill the gap for large volume fractions of inclusions and serve as a reference for the homogenization of the microstructures of interest.

Failure analysis of field-aged polymeric outdoor insulators and performance enhancement for electric stress using nonlinear field grading composites

Failure analysis of field-aged polymeric outdoor insulators and performance enhancement for electric stress using nonlinear field grading composites

Effective Properties of Homogenised Nonlinear Viscoelastic Composites.

We develop a general approach for the computation of the effective properties of nonlinear viscoelastic composites. For this purpose, we employ the asymptotic homogenisation technique to decouple the equilibrium equation into a set of local problems. The theoretical framework is then specialised to the case of a strain energy density of the Saint-Venant type, with the second Piola-Kirchhoff stress tensor also featuring a memory contribution. Within this setting, we frame our mathematical model in the case of infinitesimal displacements and employ the correspondence principle which results from the use of the Laplace transform. In doing this, we obtain the classical cell problems in asymptotic homogenisation theory for linear viscoelastic composites and look for analytical solutions of the associated anti-plane cell problems for fibre-reinforced composites. Finally, we compute the effective coefficients by specifying different types of constitutive laws for the memory terms and compare our results with available data in the scientific literature.