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• A Goal Programming model to optimize a waste paper recycling network was elaborated. • The model considers objectives related to sustainability, multiple products and periods. • Vehicle routing, different-capacity vehicles and multiple trips are highlights. • The possibility of storing material at the collection points is considered. • The formulation provides relevant solutions to assist decision-makers. Organization and planning of reverse logistics networks make sustainable processes more efficient. Thus, an important sector for connecting the collection and waste paper recycling echelons is the intermediate center. In this study, a Mixed Integer Linear Programming model, which is multi-objective, multi-product, multi-level and multi-period, was developed to optimize the waste paper logistics processes of intermediate centers. The formulation includes the following echelons: collection, considering vehicle routing with different capacities; inventory of non-baling materials; baling sorted waste and inventory of bales; selling bales; disposal of non-recyclable waste. The aims of the model include: maximizing the collected waste; minimizing distances; maximizing both the production and sale of bales, and minimizing costs. According to research carried out in the literature, the developed model is a new proposal and to implement it, the Weighted Goal Programming and Revised Multi-Choice Goal Programming approaches were used to deal with multiple objectives and incorporate uncertainty into the quantity of waste available for collection. To analyze the proposed model, computational tests were executed with instances based on real data from a Brazilian company in the sector. For all performed tests, General Algebraic Modeling System 23.6.5 modeling language and CPLEX 12.2.0.2 solver were used for modeling and optimization. The results show that this study presents formulation and technological approaches that represent real situations and provide competitive solutions to the problem. [ABSTRACT FROM AUTHOR]

• This research proposes a new formulation for the integrated lot-sizing and cutting-stock problem. • It is also presented analytical and numerical comparisons of the proposed model against the model from the literature. • A column generation approach and a relax-and-fix heuristic were applied to solve the proposed model. The integrated lot-sizing and cutting-stock problem has become a trend in the last decades for its applicability and advantage. Consequently, different approaches and formulations have been developed. One of them, which is widespread and related to the production and cutting process of paper, is the research subject of this paper. Fundamental considerations about the literature model are discussed and an alternative formulation is proposed, which consists of a simplified version that can provide better solutions. The upgrade modifications are proved analytically and an instance is analyzed to exemplify the discussed improvement. Moreover, computational tests are performed to compare both formulations. The novelty of the proposed formulation is the possibility of finding better solutions through the reduction of a constraint set, which guarantees the flexibility given by item and object inventories in meeting demand and it also enables a reduction in the total amount of produced paper. The proposed formulation has a significant impact on future research since the addressed model is the target of many scientific researches and practical applications. [ABSTRACT FROM AUTHOR]

In this short communication the solution of a steady state model of a sextuple evaporator system used in a paper industry has been presented. With the help of the residual values of model equations (a set of 12 nonlinear algebraic equations) it has been shown that the presently obtained results are superior to the previously published results. The importance of the number of significant digits in calculation are also briefly discussed. [ABSTRACT FROM AUTHOR]

• Semi-analytical solution of damping fluid-conveying pipe systems are obtained. • The concepts of the original system and the adjoint system are introduced for research. • The eigenvalues and eigenfunctions of the original system and the adjoint system are obtained. • The orthogonality condition of damped gyroscopic system is obtained in state space. • It is proved that the original system and the adjoint system of the system with free boundary are not orthogonal. In this paper, the response solutions of the damped fluid-conveying pipe system with elastic torsion constraints at both ends are analyzed. The pipe system considering gyroscopic effect induced by internal flow and damping effect is a typical damped gyroscopic system. This system cannot be decoupled in the modal space by the traditional modal analysis, and then the semi-analytical response solutions cannot be obtained by the classical modal superposition method. In order to remedy this problem, this paper proposes a new method based on complex modal superposition method and state-space method to give the semi-analytical response solutions of the damped fluid-conveying pipe system. The adjoint system is introduced through the concept of adjoint operator, and the orthogonality conditions of the damped fluid-conveying pipe system are derived in the state-space by using the eigenvalue relationship between the original system and the adjoint system. The Laplace transformation method is used to solve the eigenvalue problems of the original system and the adjoint system, and the implicit function equations about the eigenvalues and analytical eigenfunctions are obtained. According to the obtained orthogonality conditions, the semi-analytical response solutions of the system under arbitrary initial conditions and excitations are given, and the obtained solutions include transient and steady-state response solutions. In the numerical discussion part, the reliability and accuracy of the present method are verified. This research has positive significance for the dynamic analysis of fluid-conveying pipe systems, and the obtained orthogonality conditions have potential value for the nonlinear dynamics research. [ABSTRACT FROM AUTHOR]

• Improved lorenz chaotic systems with higher complexity. • Pixel permutation method based on the image pyramid structure. • Secure and efficient image encryption method. • Galois field multiplication for efficient diffusion of pixels. This paper proposes an improved Lorenz chaotic system and a secure and efficient image encryption method to enhance encryption effectiveness in encrypted images. The proposed improved Lorenz chaotic system addresses the problem of applying the Lorenz chaotic system to image encryption, resulting in weak chaotic characteristics and susceptibility to reconstruction. Dynamic analysis, sensitivity analysis, and randomness testing demonstrate that the improved Lorenz chaotic system exhibits hyperchaotic characteristics, with a maximum Lyapunov exponent of 2.9897. Based on the improved Lorenz chaotic system, this paper proposes an image encryption method that combines image pyramid structure permutation and Galois field diffusion. Unlike most of the current permutation methods limited to a single image layer, this paper proposes a multilayer permutation method based on the image pyramid structure to enhance the permutation effect of image encryption. Although diffusion based on Galois field multiplication operation is efficient and secure, it is less effective in encrypting pixel points with a pixel value of '0′. To address this issue, this paper incorporates DNA computing into diffusion based on Galois field operations, enabling even pure black images to achieve better encryption effectiveness. Experimental results demonstrate that the encryption method proposed in this paper effectively conceals information contained in the plain image. The global Shannon entropy of the encrypted Lena image can reach 7.9975, indicating a high level of randomness and complexity. Notably, even a slight alteration, such as changing a single pixel, results in a significant divergence, with 99.6307 % of the cipher image's pixels being distinct. Moreover, it effectively withstands analysis from various attacks. Therefore, the encryption method proposed in this paper can be effectively applied to grayscale image encryption scenarios requiring relatively high security and encryption efficiency, such as remote sensing image encryption and personal privacy image encryption. [ABSTRACT FROM AUTHOR]

• The elastic instability phenomenon in hyperelastic layered materials with the phases exhibiting stiffening behavior is studied • A closed-form expression for the critical stretch of macroscopic instability is derived • An analytical prediction based on Bloch-Floquet analysis for the microscopic instability is exhibited • The critical parameters and transition of instability modes are found to be highly tunable with phase stiffening This paper investigates the elastic instability behavior in soft periodic laminates subjected to finite strains, with a focus on both macroscopic and microscopic instabilities. Considering the deformation-induced phase stiffening, the Gent model with a high bulk-to-shear modulus ratio describes the behavior of incompressible phases. This non-Gaussian statistics-based model captures the non-linear constitutive results from the limited extensibility of polymeric molecular chains. This paper derives an analytical prediction for the onset of macroscopic (or longwave) instability and microscopic instability as functions of material parameters. Moreover, a numerical Bloch-Floquet analysis is imposed on identifying the instability behavior under compression. We consider a wide range of phase combinations and find that the relatively rapid stiffening of the matrix compared to the stiff layer increases the stability of laminates by decreasing the critical stretch ratio. Essentially, properly manipulating the stiffening parameters can produce an absolutely stable region without observed instability. This paper also systematically illustrates the changes in instability and the transition between macro and micro instability in fully Gent laminates, which show higher stability than fully neo-Hookean laminates with larger critical stretch ratios. The critical characteristics of instabilities, such as critical stretch ratios and critical wavenumbers, can be controlled by the choice of stiffening parameters and other material properties, enlarging the tuning of soft laminates for desired buckling patterns in practical applications. [ABSTRACT FROM AUTHOR]

The dynamic behaviour of wildfires is mainly influenced by weather, fuel, and topography. Based on fundamental conservation laws involving numerous physical processes and large scales, atmospheric models require substantial computational resources. Therefore, coupling wildfire and atmospheric models is impractical for high resolutions. Instead, a static atmospheric wind field is typically input into the wildfire model, either as boundary conditions on the control surface or distributed over the control volume. Wildfire propagation models may be (i) data-driven ; (i i) theoretical ; or (i i i) mechanistic surrogates. Data-driven models are beyond the scope of this paper. Theoretical models are based on conservation laws (species, energy, mass, momentum) and are, therefore, computationally intensive; e.g. the Fire Dynamics Simulator (FDS). Mechanistic surrogate models do not closely follow fire dynamics laws, but related laws observed to make predictions more efficiently with sufficient accuracy; e.g. FARSITE, and FDS with the Level Set model (FDS-LS). Whether theoretical or mechanistic surrogate, these wildfire models may be coupled with or decoupled from wind models (e.g. Navier-Stokes equations). Only coupled models account for the effect of the fire on the wind field. In this paper, a series of simulations of wildfire propagation on grassland are performed using FDS-LS to study the impact of the fire-induced wind on the fire propagation dynamics. Results show that coupling leads to higher Rates of Spread (RoS), closer to those reported from field experiments, with increasing wind speeds and higher terrain slopes strengthening this trend. Aiming to capture the fire–wind interaction without the hefty cost of solving Navier-Stokes equations, a conceptual framework is proposed: 1) a swarm of unmanned aerial vehicles measure wind velocities at flight height; 2) the wind field is constructed with the acquired data; 3) the high-altitude wind field is mapped to near-surface, and 4) the near-surface wind field is fed into the wildfire model periodically. A series of simulations are performed using an in-house decoupled physics-based reduced-order fire propagation model (FireProM-F) enhanced by wind field "measurements". In this proof of concept, wind velocities are not measured but extracted from physics-based Large Eddy Simulations taken as ground truth. Unsurprisingly, higher measurement frequencies lead to more accurate and realistic predictions of the propagating fire front. An initial attempt is made to study the effect of wind measurement uncertainty on the model predictions by adding Gaussian noise. Preliminary results show that higher noise leads to the fire front displaying more irregular shapes and slower propagation. • Higher wildfire model prediction accuracy normally achieved by coupling it with wind model such as Navier-Stokes equations. • Coupled fire-wind models often too computationally expensive for real-time use in operational contexts. • Prediction accuracy of wildfire model uncoupled from wind model enhanced by periodic inputs of updated wind field. • Wind field to be constructed from UAV swarm measurements, surrogated here to velocities obtained from full CFD simulations. • Proposed method to enhance wildfire model predictions robust to Gaussian noise added to represent measurement uncertainty. [ABSTRACT FROM AUTHOR]

A new enhanced multi-strategy bottlenose dolphin optimizer is proposed. • The superiority of the proposed algorithm is verified by comparing with efficient intelligent algorithms. • A three-dimensional path planning model for unmanned aerial vehicles with time, threat, height and smooth cost is studied. • The proposed algorithm is applied to solve the three-dimensional path planning problem for unmanned aerial vehicles. • The quality of the proposed algorithm based path planning results is better than other approaches. The path planning of unmanned aerial vehicle is a complex practical optimization problem, which is an important part of unmanned aerial vehicle technology. For constrained path planning problem, the traditional path planning methods can not deal with the complex constraint conditions well, and the classical nature-inspired algorithms will find the local optimal solution due to the lack of optimization ability. In this paper, an enhanced multi-strategy bottlenose dolphin optimizer is proposed to solve the unmanned aerial vehicle path planning problem under threat environments. Firstly, the introduction of fish aggregating device strategy that simulates the living habits of sharks enriches the behavioral diversity of the population. Secondly, random mixed mutation strategy and chaotic opposition-based learning strategy expand the exploration range of the algorithm in the solution space by disturbing the positions of some individuals and generating the opposite population respectively. Finally, after balancing the exploration and exploitation ability of the algorithm more reasonably through the mutation factor and energy factor, this paper proposes a new swarm intelligence algorithm. After verifying the adaptability and efficiency of the proposed algorithm through different types of test functions, this paper further highlights the advantages of the proposed algorithm in finding the optimal feasible path in the unmanned aerial vehicle path planning model based on four constraints. [ABSTRACT FROM AUTHOR]

This paper presents a case study on condition monitoring of power generators at offshore wind turbines. Two fault detection models are proposed for detecting sudden changes in the sensed value of metallic debris at the generator. The first model uses an exponentially weighted moving average, while the second monitors first-order derivatives using a fixed threshold. This is expected to improve the maintenance activities by avoiding late or early part replacement. The economic impact of the proposed approach is also provided with a realistic depiction of the cost structure associated with the corresponding maintenance plan. While the specifics of the case study are supported by real-life data, considering the prevalence of the use of generators not only in offshore wind turbines but also in other production environments, we believe the case study covered in this paper can be used as a blueprint for similar studies in other applications. • Large scale condition monitoring demonstrates economic benefits. • Case study from real wind turbine population with economic impact assessment. • Sensor for monitoring fault mode results in lead time for maintenance planning. • Sensitivity analysis assesses results despite downtime and power price uncertainty. [ABSTRACT FROM AUTHOR]

• A model to explore the multiphysics characteristic of semiconductors is presented. • The model determines the thermal and mechanical properties of complex patterns. • Results show a strong correlation between thermal and mechanical properties. • Dielectric bands asymmetrically affect thermal and mechanical behavior. • Machine learning can predict one property from another. As semiconductor performance improves through advanced package designs, it becomes important to consider both thermal and mechanical properties. Better understanding their relationship enhances system design and optimization. This study has introduced a numerical method that takes into account both thermal and mechanical fluxes to construct thermal and mechanical property maps for practical application in semiconductor engineering. Furthermore, this paper investigated the relationship between the two properties using the constructed property maps in commercially available semiconductor packages. Owing to the complexity of packaging design patterns, a coupled isoparametric mapping and machine learning (ML) method was introduced to investigate their effects. The model then determines and investigates the anisotropic equivalent thermal and mechanical properties of the commercialized semiconductor packages with complex pattern designs, according to the package materials, volume fractions of each material, and design patterns. This approach pursues more sophistication and practicality compared to simplified composite structure property evaluation models. Additionally, all processes in the algorithm are automated based on ML methods, making them practically applicable in the semiconductor industry. The study shows that there is a strong correlation between the thermal and mechanical characteristics in the complex package patterns. This relationship was able to form a fairly clear category based on the shape of the dielectric band because the dielectric band had significantly different effects on the thermal and mechanical fluxes. The study discussed the physical implications of the similarities and differences between the two behaviors and validated the results of the equivalent properties through finite element (FE) analysis. Finally, the study cross-validates the relationship by showing that information from one flux behavior can be used to predict the other based on the ML method. Based on the results, this paper can provide a better understanding of thermal and mechanical fluxes in semiconductor package patterns for package design and optimization. [ABSTRACT FROM AUTHOR]

• A dynamic model of L-shaped fluid-conveying pipes based on ANCF method is established. • Effects of the radius of the arc section and the fluid velocity on the natural frequency are discovered. • Results of the ANCF method are verified by results obtained by the experiment and simulation. In this study of fluid-conveying pipe dynamics, it is usually assumed that the shape of the pipe is straight. This paper establishes a flow-induced vibration model of an L-shaped pipe based on the absolute nodal coordinate formulation (ANCF), and mainly studies the effects of fluid velocity, structural parameters, and boundary conditions on the vibration characteristics of the pipe. The results show that the fluid velocity will reduce the natural frequency and affect the modal shapes on the basis of causing static deformation of the pipe. After reaching the critical fluid velocity, the modal combination will occur when the fluid velocity continues to increase. Notably, alterations in pipe length, arc radius, wall thickness, eccentricity and boundary conditions exert diverse effects on the natural frequencies of the pipe. In particular, the arc radius is not involved in the previous study of straight and curved pipe dynamics, so it is analyzed emphatically. Among these variables, the fluid velocity is always a key factor affecting the dynamic characteristics. Finally, experiments and finite element software were used to compare the ANCF method, verifying the effectiveness of the method. Therefore, this paper has developed an effective analytical method to study the flow-induced vibration of complex shaped conveying fluid pipes. [ABSTRACT FROM AUTHOR]

Urbanization and the release of carbon emission are two significant features of contemporary economic and social progress in China. However, there are few studies that consider how urbanization policy goals affect carbon emission. This paper aims to study the nonlinear effects of urbanization policy goals on carbon emission in 13 cities of the Beijing-Tianjin-Hebei region. In this paper, a multi-dimensional spatial disturbance grey model is proposed. Based on matrix perturbation theory, this paper explores the spatial perturbation bounds of the novel model and verifies that the spatial property of the model is consistent with the viewpoint of the First Law of Geography. Then, the novel model is used to predict the urban carbon emission under different urbanization policy goal scenarios. The results showed that the novel model has spatial regional correlation in spatial region prediction. With the development of urbanization level, carbon emissions show a downward trend in more than 50% of cities from 2022 to 2025. In addition, the improvement of urbanization policy goals will promote the carbon peak time of most cities. The carbon emission intensity will exhibit an inverted U-shaped trend distribution in space. The research results are conducive to providing scientific guidance for the formulation of new-type urbanization policies and helping to achieve the dual carbon goals. • A multi-dimensional spatial disturbance grey model is proposed. • The novel grey model is consistent with the viewpoint of the First Law of Geography. • The spatial distribution of carbon intensity showed an inverted U-shaped pattern. [ABSTRACT FROM AUTHOR]

We present a general methodology to evaluate the mass moments of two-dimensional domains and axisymmetric solids made of functionally graded materials. The approach developed in the paper is based on the sequence of two steps. First, the original domain integrals are converted to integrals extended to the relevant boundary by exploiting Gauss theorem. Second, for domains having a polygonal or circular shape, the boundary integrals are evaluated analytically by providing algebraic expressions that depend upon the parameters defining the density distribution, the position vectors of the vertices of the polygonal domain or the initial and ending points of an arbitrary circular sector, respectively. While the first step refers to moments of arbitrary order, the second step is limited to the most useful quantities for engineering applications, i.e. generalised mass, static moment and inertia tensor. The formulas derived in the paper are validated by means of examples retrieved from the specialised literature for which analytical results are available or have been specifically derived by the authors. Finally, in order to ascertain the computational savings entailed by the use of the proposed analytical formulas with respect to numerical techniques, the mass moments of a longitudinal section of a human femure, made of a functionally graded material and characterised by a linear density distribution, have been computed. • Mass moments for functionally graded domains expressed by boundary integrals. • Polynomial, exponential and polynomial quadratic density distributions. • General methodology for computing mass moments of order greater than 2. • Analytical evaluation of mass moments for polygonal or circular domains. • Accuracy and computational efficiency of the analytical formulas. [ABSTRACT FROM AUTHOR]

We investigate the one-dimensional cutting-stock problem integrated with the lot-sizing problem in the context of paper industries. The production process in paper mill industries consists of producing raw materials characterized by rolls of paper and cutting them into smaller rolls according to customer requirements. Typically, both problems are dealt with in sequence, but if the decisions concerning the cutting patterns and the production of rolls are made together, it can result in better resource management. We investigate Dantzig–Wolfe decompositions and develop column generation techniques to obtain upper and lower bounds for the integrated problem. First, we analyze the classical column generation method for the cutting-stock problem embedded in the integrated problem. Second, we propose the machine decomposition that is compared with the classical period decomposition for the lot-sizing problem. The machine decomposition model and the period decomposition model provide the same lower bound, which is recognized as being better than the linear relaxation of the classical lot-sizing model. To obtain feasible solutions, a rounding heuristic is applied after the column generation method. In addition, we propose a method that combines an adaptive large neighborhood search and column generation method, which is performed on the machine decomposition model. We carried out computational experiments on instances from the literature and on instances adapted from real-world data. The rounding heuristic applied to the first column generation method and the adaptive large neighborhood search combined with the column generation method are efficient and competitive. [ABSTRACT FROM AUTHOR]

This paper introduces link information value obtained by the traffic sensors and presents a traffic sensor location and flow estimation joint optimization model in an urban road network. In contrast to most previous studies, this paper adds new traffic sensors into the existing sensor network and proposes a data-driven path flow measurement method based on Wasserstein metric, which is utilized to measure the distance between the estimated traffic flow distribution and the actual distribution. Furthermore, this paper develops a customized greedy algorithm by combining a search strategy for the link information value to obtain the optimal sensor location scheme and perform traffic flow estimation under different budget conditions. Numerical experiments are conducted on Sioux-Falls test network and Eastern Massachusetts interstate highway subnetwork to verify the accuracy and effectiveness of the proposed model based on Wasserstein metric and the developed solution method. Computational results show that the sensor location scheme generated by the model based on Wasserstein metric can reduce the estimation error of the traffic flow compared with KL divergence model under the same deployment cost. Additionally, the customized greedy algorithm can achieve the better performance than the Brute force algorithm in terms of computing time and solution quality. • A traffic sensor location and path flow estimation joint optimization model is formulated. • A data-driven path flow measurement method based on Wasserstein metric is proposed. • A customized greedy algorithm by combining a search strategy is developed. • Numerical experiments are conducted based on the real-word transportation network. [ABSTRACT FROM AUTHOR]

• Nonlinear model for a bended piezoelectric semiconductor beam is established. • Differential quadrature method based iteration procedure is developed. • Nonlinearity of constitutive relation and non-uniformity of structure are focused. • Potential barriers and wells are realized through designing structures. In this paper, the effects of nonlinear constitutive relation on the electro-elastic coupling behaviors in non-uniform piezoelectric semiconductor beams are investigated. On the basis of three-dimensional theory for piezoelectric semiconductor and double power series, one-dimensional bending model is developed. In order to deal with the nonlinear problem, a differential quadrature method based iteration procedure is proposed. Comparing with the results from finite element method, the proposed method has good convergence and high accuracy. In numerical analysis, the effects of nonlinearity and non-uniformity in piezoelectric semiconductor are discussed thoroughly. It is found the introduction of nonlinearity induces the loss of symmetric for all electrical field quantities but little changes the mechanical quantities. While the reduction of width along the length direction produces larger mechanical and electrical responses. Importantly, the effects of nonlinearity on the electrical field quantities are more evident in a piezoelectric semiconductor beam with rapidly varied cross section. Besides, we designed the piezoelectric semiconductor beams subject to double shear forces and a beam with locally varied cross section. In the designed structures, the potential barriers and wells are realized, which provide new approaches adjusting the electro-elastic behaviors in piezoelectric semiconductors. The study in this paper could be the guidance designing high performance electronic devices. [ABSTRACT FROM AUTHOR]

This paper takes a reaction-diffusion predator-prey system with ratio-dependent Holling III functional response function and Leslie-Gower term into consideration. First of all, the system model is proposed on the basis of basic biological assumptions and previous work, and the existence conditions of the equilibrium point of the system are discussed. Secondly, under the assumption of the existence of equilibrium point, the Turing instability necessary conditions induced by diffusion are investigated. Thirdly, optimal control theory is derived, and the adjoint system and the first-order optimization condition are established. Fourthly, parameter identification based on optimal control is studied, and the technique is extended to network structure. Finally, extensive numerical simulations, including Turing pattern, Normalized Population High Distribution Area (NPHDA) diagram and parameter identification, are carried out to illustrate and validate the analytical results. For the system dynamics phenomena, the results from different perspectives effectively demonstrate that the theoretical findings, numerical simulations and natural reality are identical. In terms of the parameter identification of continuous model and network model, the efficiency and accuracy of various algorithms are fully tested. • This paper proposes and investigates index normalized population height distribution area. • The optimal control problem of reaction-diffusion predator-prey system is formally derived. • The parameter identification research is extended to population network structure space. [ABSTRACT FROM AUTHOR]

• Derivatives of Dirac delta function were introduced to describe the action of joint parts in dynamic analysis. • Analytical solutions were provided to study dynamic responses of joints in infinite beams under time-lag loads. • Connection between joints and standard beams induces great differences in dynamic responses. This paper investigates the analytical method for the infinite beam with joint parts resting on a foundation under time-lag loads. The ground is simulated as a viscoelastic foundation. The existence of joint parts in beams is explained by introducing virtual forces expressed through the Dirac delta function. Integral transformation simplifies the dynamic governing equations for standard beam sections and joint parts into an algebraic equation. The convolution theorem converts the solutions into the time domain. The analytical solutions for dynamic analysis of standard beam sections and joint parts are obtained conveniently in the frequency domain. The proposed analytical method is verified by comparing it with the traditional methods and also validated by numerical examples with time-lag loads. Parametric discussions study the effects on the dynamic response of joint parts and standard beam sections, such as the amplitude and frequency of time-lag loads and coefficient of bending stiffness reduction of joint parts. The parametric analyses emphasize the dramatic effect of critical parameters on the discontinuous deformation of beams. The damage caused by critical values of some factors is emphasized. The severe effects of discontinuous deformation induced by dynamic loads in the safety of beam structures are revealed in this paper. The differences in dynamic responses between the beam and joint part must be monitored to ensure the safety of whole beam structures. [ABSTRACT FROM AUTHOR]

This paper presents an approach for analytically solving gradient-enhanced damage (GED) models. The proposed approach provides rigorous proofs for essential phenomena observed in the traditional GED model, including damage widening, characteristic length sensitivity, and stress-locking. The derived cohesive law is a useful technique for accurately determining the material parameters of the GED model, significantly reducing the sensitivity to characteristic length. Furthermore, this study presents an isotropic damage model that considers both tensile and shear failures and can capture complex crack paths. Finally, a series of numerical examples is shown to demonstrate the efficacy of the suggested method. • This paper introduces a mathematical approach for the analytical solution of gradient-enhanced damage (GED) models. • The analytic solution alleviates the characteristic length sensitivity in the GED model. • The proposed damage evolution method can effectively capture complex crack paths. [ABSTRACT FROM AUTHOR]

Snake robots have redundant kinematic structure which predetermines them for motion in rough and unstructured terrain with obstacles, narrow spaces or environments with different ground levels. Dynamic modeling of snake robots is an important element in the development of control strategies for them. This paper, deals with the dynamic model of a snake robot moving in a pipeline. The model is based on Newton's mechanics with consideration of the viscous as well as Coulomb friction model. The paper uses Hertz theory for modeling of contact between a snake robot and side walls of a pipeline. Based on optimization process results, the friction effects as well as analyses of snake robot propulsive force are investigated. The main contributions of the paper are the developed dynamic model for snake robot motion in a pipeline, open source code of the developed model in MATLAB, and analyses of individual parameters of snake robot motion. • Propulsive force of snake robot moving in a pipeline is significantly affected by friction of the side walls. • One full sine wave formed by snake robot links ensures maximum average velocity. • Considering Coulomb friction the snake robot performs more jerked motion in comparison with viscous friction. [ABSTRACT FROM AUTHOR]

In this paper, we develop a method for the estimation of airgap spatial variation from the harmonics that appear in the stator's current under static eccentricity conditions. We move beyond the detection of the eccentricity fault and endeavour to quantify the severity of this fault. To achieve this, we formulate the problem as a mathematical inverse problem and attempt to solve it in the Bayesian framework using the so-called Bayesian approximation error approach. The solution takes the form of an algorithm capable of estimating the parameter(s) that characterize the spatial variation of the airgap length from noisy and limited data. Furthermore, it can quantify the uncertainty associated with the results as a byproduct of the Bayesian analysis approach employed in this paper. The results demonstrate that with each iteration of the algorithm, estimation accuracy improves, and the uncertainty of the estimated results reduces. • Bayesian approximation error analysis shows promise in monitoring electrical machines with eccentric rotors. • The paper applies Bayesian inversion for online estimation of airgap length in induction machines with eccentric rotors. • The study estimates static eccentricity ratio from limited data on harmonics of the machine line currents. • This paper gives an analytical method for calculating all inductances of induction machines under static eccentricity. [ABSTRACT FROM AUTHOR]

This paper discusses the challenging issues that reliability practitioners face in conducting destructive tests that lead to completely censored lifetimes, especially in estimating the defect rate of products. Manufacturers need to measure the defect rate for quality control purposes, but obtaining enough defective devices for accurate estimation is not easy when the defect rate is relatively low. To address the issues, a Bayesian approach for estimating the defect rate is proposed in this paper. The proposed method is devised to make up for the heavy computational burdens of the Metropolis-Hastings algorithm. To quantify the uncertainty in the Bayesian estimation, a nonparametric bootstrap technique is employed to construct a credible interval for the defect rate. The performance of the proposed method is evaluated through a variety of Monte Carlo simulation studies. The efficiency of the proposed Bayesian estimation procedure is validated using a real-world dataset of return-springs in DC motor systems under an accelerated destructive degradation test. • Estimate the defect rate of products in conducting destructive tests with completely censored lifetime data. • Propose a computationally efficient Bayesian estimator of an analytical form for the defect rate with masking. • Propose a nonparametric bootstrap technique to construct a credible interval for the defect rate. • The proposed method is validated using accelerated destructive degradation testing data of return-springs. [ABSTRACT FROM AUTHOR]

• Proposing and establishing a dynamic model for the combined rotor that accounts for rub-impact. • Increasing the stiffness of the stator advances the speed at which the system enters the quasi-periodic period. • The Stribeck friction model reduces the speed range of the system's period three motion compared to Coulomb friction. • The magnitude and phase angle of the imbalance significantly alters the state of motion of the system. • Analyzing the basic mechanism that governs the variation of friction and its impact on the stability of the system. This paper aims to analyze the dynamic behavior of the rod-fastening combined rotor(RFCR) system in a rub-impact state and proposes a rod-fastening rotor dynamics model based on the Stribeck friction model. This model offers advantages such as generating frictional forces based on relative velocities and considering the coupling effects of rub-impact under complex excitations, providing greater flexibility in studying rotor systems. The Lagrange equation is utilized to deduce the RFCR formula, and the balance equation of the combined rotor is presented under friction, oil-film, and unbalanced conditions. This paper investigates the dynamic response of the RFCR system under rub-impact using the 4th-order Runge–Kutta method. The effects of parameter variations on the nonlinear dynamics of the combined rotor are systematically analyzed by means of bifurcation diagrams, motion trajectory, time domain waveform, frequency spectrum, and Poincaré maps. The results show that the dynamic characteristics of the rotor system show a regular variation with the variation of the system parameters. Different forms of periodic motions, namely Periodic 1 motion (P1), Periodic 2 motion (P2), and Periodic 3 motion (P3) motions, along with quasi-periodic motions, are observed in response to varying system parameters. The results show that the higher the stator stiffness, the earlier the rotor enters the quasi-periodic speed. The velocity effect of friction reduces the speed range of the P3 motion of the rotor system and enhances the nonlinearity of the system. The magnitude and phase of the unbalance force change the frequency component of the system, which has a more substantial effect on the rotor system. These findings can help engineers and researchers in comprehending system behavior and designing more dependable and effective gas turbine rotor systems. [ABSTRACT FROM AUTHOR]

· This paper presents a multi-stage mechanical deformation mode with complex loading surfaces. · All multi-stage contact mechanical models involved in the actual loading deformation process are established. · APSD can describe and analyze the characteristics of fractal surfaces. The contact mechanical behavior of rough surfaces is related to the friction and wear of mechanical components, and also has an important impact on the dynamic performance and force transfer characteristics of assembly surfaces. This paper aims to solve the complex multi-stage mechanical deformation mode of the loading surface, and establishes all multi-stage contact mechanical models involved in the actual loading deformation process from the perspective of the actual deformation and critical deformation of the asperity. Firstly, based on the three-dimensional fractal contact theory, the force deformation relationship of a single asperity during the full deformation stage of loading is constructed. Then, six critical contact areas and four critical deformation quantities of a multi scale asperity are derived. Finally, the complex multi-stage deformation contact mechanical models of three-dimensional fractal surfaces under actual loading are established. The area power spectral density (APSD) function spectrum of rough surface under different fractal parameters, as well as the variation of contact load, contact stiffness, and contact area are analyzed numerically. Compared with several classical models, the rationality of the proposed model is verified. This study can be used as the basis for constructing the overall dynamic model of an assembly system [Display omitted] [ABSTRACT FROM AUTHOR]

• Eringen's nonlocal and strain gradient theories are used for wave propagation. • Symmetric wave propagation and scattering are modelled using the two theories. • The study is carried out for layered piezoelectric media at nanoscale. • Length scale effect on the propagation of polarized guided waves is investig. • Changes in mechanical displacement and electrical potential are plotted and analyzed. This paper investigates the dynamic propagation behavior of guided waves in nanoscale media composed of alternating layers of piezoelectric phases. The study employs Eringen's nonlocal and strain gradient theories to derive equations for symmetric wave propagation and the scattering relations of guided waves perpendicular to these structures. Dispersion curves are calculated and plotted to compare these theories, considering the influence of nanoscale size-effect, volume ratio of constituent layers, and material length scale. Using the strain gradient theory, the paper explores the impact of length scale parameters on the propagation behavior of horizontally polarized guided waves in an alternating layer structure of nanoscale piezoelectric material, specifically nanoscale piezoelectric laminates. The analysis involves calculating localization factors and dispersion curves to analyze the effects of size-effect and length scale parameters on wave propagation and band structures. Additionally, the study plots and analyzes changes in mechanical displacement and electrical potential, followed by an investigation and discussion of nanoscale size effects and the effects of the material's length scale parameter on dispersion curves and conversion modes within specific regions. The results highlight that the length scale effect parameter significantly impacts the mode conversion zones and band gap structures, more so than the NLPE continuum theory suggests. As the strain gradient parameter increases, these zones shift towards higher wavenumbers and to the right. Furthermore, introducing the length scale factor results in a substantial decrease in both the formation of conversion zones and the density of dispersion curves. [ABSTRACT FROM AUTHOR]

Rainstorm is one of the most severe and frequent meteorological disasters. The rainstorm event brings considerable risks to the natural ecosystem and human life. There is a limited body of research on applying the grey prediction model for predicting rainstorm-related data. Based on the extreme precipitation index defined by the Expert Team on Climate Change Detection and Indices, this paper uses the data of rainstorm days from 493 weather stations in the middle and lower reaches of the Yangtze River to establish a prediction model. Improving the accuracy of rainstorm days prediction can bring valuable results to decision-makers in a specific region. The annual rainstorm days series exhibits randomness, irregular nonlinearity, fluctuations, etc.; however, the traditional grey prediction model can only identify the trend of a series but not its fluctuations, making its prediction extremely challenging. Therefore, this paper introduces a new dynamic grey action quantity based on the traditional grey model, and the parameters are solved by the hybrid technique of the genetic algorithm and the constrained fmincon function. The prediction results of the new model are compared with those of the traditional grey model, the seasonal grey model, the neural network, and the seasonal autoregressive integrated moving average. In terms of prediction accuracy and similarity of fluctuations, the results demonstrate that the new model outperforms these models. • A fluctuation data grey model is proposed to predict the rainstorm days. • A novel dynamic grey action quantity is introduced into the traditional grey model. • The nonlinear parameters are determined based on hybrid optimization algorithm. • The new model has better simulation and prediction accuracy than the traditional models. [ABSTRACT FROM AUTHOR]

• A model-based approach is proposed for the design synthesis of autonomous articulated vehicles. • The dynamically coupled subsystems of an autonomous vehicle are devised and evaluated simultaneously. • A prediction vehicle model for articulated vehicles is developed. • The effectiveness of the proposed approached is demonstrated by numerical simulations. • The results presented in the paper may be used as guidelines for devising autonomous articulated vehicles. In conventional autonomous vehicle designs, the mechanical system is first devised, and the automated driving systems are subsequently added. The conventional method can be categorized as a sequential design approach. An autonomous vehicle consists of the subsystems of mechanical assembles, automated driving, etc. There exist dynamic couplings among these subsystems, and the sequential design method may not be the most effective. This observation initiates the motivation of this research, and the objective of this paper is thus to explore a more effective design method for autonomous vehicles and, in particular, autonomous articulated vehicles. To this end, this paper proposes a model-based design synthesis method, i.e., a concurrent design method, for autonomous articulated vehicles. The autonomous articulated vehicle assumes to be composed of the subsystems of a mechanical unit, a trajectory tracking-controller based on a model predictive control technique, and a motion-planner. The design synthesis of the autonomous articulated vehicle is constructed as a bi-level optimization problem. With the proposed concurrent design approach, the subsystems are optimally devised simultaneously. To examine the proposed approach, it is applied to the design of a car-trailer combination with automated steering. The insightful findings attained from the study may be used as guidelines for developing autonomous articulated vehicles. [ABSTRACT FROM AUTHOR]

• A learning algorithm for human-robot skill transfer based on dynamic movement primitive was proposed. • The impedance control system was investigated to improve the compliance and robustness. • Two-dimensional writing tasks were extended to three-dimensions space. • Constraints on the inverse solutions of redundant robots were ensured by adding constraint equations. • The proposed algorithm had been validated on a ROKAE xMate robot platform. This paper proposed a learning algorithm for human-robot skill transfer based on dynamic movement primitive. Through the establishment of Transmission Control Protocol communication, the position trajectory and force characteristic of the human demonstrator while demonstrating the robot were recorded as the training data of the dynamic movement primitive model. The demonstrated skill/motion reproduction and generalization were successfully achieved through adjusting the parameters of the dynamic movement primitive model. The impedance control system investigated in this paper improved the compliance of the robot trajectory reproduction and skill generalization, and improved the robustness of robot control system in different environments. In addition, for the problem of inverse solution of redundant robots, this paper improved the dimension of constraint equations in the inverse solution of robots by training multiple dynamic movement primitive models, which guaranteed the constraints of inverse solutions of redundant robots. The proposed algorithm had been validated on a simulated robot platform using MATLAB and a ROKAE xMate robot platform, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we consider a nonlinear switched dynamical system (NSDS) with unknown system parameters in the context of uncertain experimental data. This system is employed to model the continuous fermentation for the production of 1,3-propanediol through glycerol bioconversion. The uncertain experimental data points are regarded as stochastic variables and only their first-order moment information of the probability distributions is available. The target of this paper is to optimize these system parameters under the environment of uncertain experimental data. Taking these factors into account, we propose a distributionally robust system identification (DRSI) problem (i.e., a bi-level system identification problem) governed by the NSDS. The objective functional comprises two level objectives: (i) the inner-level objective aims to maximize the expectation of the relative error between the solution of the NSDS and the uncertain experimental data with respect to their probability distributions at approximately stable time; and (ii) the outer-level objective is to minimize the expectation with respect to these system parameters. The DRSI problem is equivalently transformed into a single-level system identification (SLSI) problem with non-smooth term through the application of the duality theory in the probability space. A smoothing technique is employed to approximate the non-smooth term in the SLSI problem. Subsequently, an error analysis of the employed smoothing technique is derived. The gradients of the objective functional in the SLSI with respect to these system parameters are obtained. An optimization algorithm is designed to solve the SLSI problem. Finally, the paper concludes with simulation results. • The DRSI problem lies between RSI problem and SSI problem. • An optimization algorithm with the duality theory is proposed to solve the DRSI problem. • A smoothing technique is employed to approximate the non-smooth term in the objective functional. [ABSTRACT FROM AUTHOR]

• Small scale analysis of functionally graded triply periodic minimal surface (FG-TPMS) nanoplates. • The generalized weak form formulation for the FG-TPMS nanoplate is proposed. • A fitting technique based on a two-phase piece-wise function for porous structures of TPMS. • The length scale parameters can high-efficiently predict size effects. • Novel benchmark numerical results are illustrated and introduced. In recent years, the triply periodic minimal surface (TPMS) has emerged as a remarkable solution for constructing structures, drawing inspiration from natural architectures. TPMS offers several outstanding features, including porous architectures with high interconnectivity, smooth surfaces and the ability to achieve mathematically controllable geometry features. However, it is evident that the current research has not fully harnessed the extensive potential and benefits of TPMS structures. In this paper, a groundbreaking approach for analyzing functionally graded triply periodic minimal surface (FG-TPMS) nanoplate, which is utilized a novel nonlocal strain gradient isogeometric analysis, is provided. Three patterns of the FG-TPMS nanoplate, namely Primitive (P), Gyroid (G) and I-gragh and Wrapped Package-graph (IWP), are utilized in this study. The primary focus is to investigate size dependent problems with two types of density distributions. The proposed model successfully incorporates both nonlocal effects and strain gradient effects into nanoplate structures. The paper demonstrates how the mechanisms responsible for both reducing and enhancing stiffness in the nanoplate can be understood by fine-tuning the nonlocal and strain gradient parameters. The findings of this study offer promising prospects for future design and optimization as they provide a robust approach to address the complex mechanical behavior observed in the FG-TPMS nanoplate. The proposed model not only captures the behavior accurately but also opens up new avenues for exploring the capabilities of FG-TPMS structures. [ABSTRACT FROM AUTHOR]

• A fractional-order viscoelastic model is used to simulate soil. • The time variation of engineering load is considered. • The layered property of soil is considered. • The influence of the bottom rock on the soil is considered. • The recovery of settlement after unloading is analyzed. Time-varying loading is a frequently encountered loading type in geotechnical engineering. As the deformation of viscoelastic soil is related to its loading history, studying the viscoelastic problems under time-varying loads has important practical engineering significance. In this paper, the stress and displacement of a layered soil with fractional-order viscoelastic model under time-varying loads were solved using the complex variable method and the corresponding principle. Under the assumption of quasi-static and linear elasticity, this paper derives the quasi-static elastic solutions of a layered soil under time-varying strip loads. By introducing the fractional-order viscoelastic model and using the corresponding principle, the Laplace-domain analytical solutions are obtained. Finally, numerical methods are utilized to perform the Laplace inverse transform and obtain the solutions in the physical domain. The correctness of this paper is validated by comparing the numerical results with the ANSYS software, as well as by comparison with previous literature. Based on the experimental data, the material parameters of frozen soil at two temperatures are fitted. The settlement patterns of soil under two engineering loads were analyzed through case studies. By controlling variables, the influence of parameters of the fractional viscoelastic model on elastic aftereffect was investigated. [ABSTRACT FROM AUTHOR]

This paper proposes a novel nature-inspired meta-heuristic algorithm, named Snow Geese Algorithm. It is inspired by the migratory behavior of snow geese and emulates the distinctive "Herringbone" and "Straight Line" shaped flight patterns observed during their migration. The algorithm is structured into three main phases for benchmark testing. In the first phase, the Snow Geese Algorithm's numerical results are compared with those of several classical meta-heuristic algorithms using the same test functions and original data from these algorithms. In the second phase, in order to minimize potential variations during the comparison, all algorithms undergo evaluation on a standardized testing platform. In the third phase, this paper applies the Snow Geese Algorithm to solve four widely recognized engineering optimization problems: the tubular column design, piston lever optimization design, reinforced concrete beam design and car side impact design. These real-world engineering problems serve as test cases to assess Snow Geese Algorithm problem-solving capabilities. The primary objective of the Snow Geese Algorithm is to provide an alternative perspective for tackling complex optimization problems. Please note that the complete source code for the Snow Geese Algorithm is publicly available at https://github.com/stones3421/SGA-project. • Snow Geese Algorithm: A novel meta-heuristic approach inspired by snow geese flight behavior, tackling optimization problems. • Two-stage Strategy: Mimics snow geese exploration and exploitation patterns, setting it apart from traditional methods. • Performance Evaluation: Multiple algorithms are assessed on different problems. • Algorithm Features: Experimental results validate the effectiveness of the Snow Geese Algorithm. • Practical Applications: Snow Geese Algorithm shows potential in engineering optimization, aiding accurate decision-making. [ABSTRACT FROM AUTHOR]

We propose a new concept which is a generalization of fuzzy soft subset and fuzzy soft equal. Using such notions, we will be able to consider the distributive law of fuzzy soft sets. Using the distributive law of fuzzy soft sets, we point out that the distributive law of trapezoidal fuzzy soft sets as proposed by Xiao et al. (2012) is not true. The correction will further improve further extensions of the results of Xiao et al. (2012). We will also establish the generalized distributive law of trapezoidal fuzzy soft sets along with illustrative examples. [ABSTRACT FROM AUTHOR]

• Develop an original FE-analytical model of bolt tightening with elastic of bearing cap. • Propose a new assembly accuracy prediction method of planetary gear train. • Consider gear-shaft-bearing-bolt coupling effects on assembly accuracy. • Explore bolt tightening effects on shaft error motion and assembly accuracy. • Carry out the assembly accuracy and vibration tests to verify the proposed method. Planetary gear train (PGT) is a complex transmission system composed of gears, shafts, bearings and bolted joints, of which the assembly accuracy affects the transmission accuracy and dynamic behavior. In this paper, a new assembly accuracy prediction method is proposed for PGT considering gear-shaft-bearing-bolt coupling effects. The new method is formulated by establishing three models for bolt assembly, shaft error motion and assembly accuracy (transmission error) of PGT. The model for bolt assembly is an original FE-analytical model to analyze the bolt assembly effect on elastic deformation of bearing cap, which is developed by finite element (FE) method and analytical method for addressing the elastic effect of bearing cap and elastic interaction between bolts. The models for shaft error motion and assembly accuracy are performed by the three-dimensional contact analysis with errors and preload of bearing cap based on analytical method and kinematic geometry relationship. Combining the three models, the assembly accuracy can be predicted by simulations. The simulations indicate that the proper bolt assembly parameters can alleviate the influence of manufacturing errors on assembly accuracy. The assembly accuracy tests of PGT are conducted. The results well agree with the simulations', and the assembly accuracy is improved by the proper bolt assembly parameters. [ABSTRACT FROM AUTHOR]

• A new Weibull log-logistic mixture distribution accumulation generation operator is established. • A novel grey model with multiple interaction effects is established. • The robustness and stability of the proposed method is proved and validated. • A new parameter estimation method is designed. • The proposed method is superior to other seven benchmark models in four case studies. Forecasting the failure of hard disk drives is important in server operation and has attracted increasing attention. However, current disk drive warning systems suffer from high false positive rates and high resource consumption when dealing with hard disk drive overall failure. Therefore, to accurately and stably predict hard disk drive overall failure, this paper develops a new Weibull Log-Logistic grey forecasting model with multiple interaction effects. Firstly, to capture and fit the trend of hard disk failure data flexibly and reduce the volatility, a new accumulation generation operator is established by introducing the Weibull Log-Logistic mixture distribution. Secondly, the proposed model constructs a multiple interaction term to describe the nonlinear relationship of the dependent variables on the system behavior series and the multiple interaction effects between the independent variables. Then, the parameter estimation method is designed to improve the fitting accuracy of the new model, in which linear estimation method, nonlinear estimation method, and meta-heuristic optimization algorithm are used to calculate the parameter values according to their categories. Finally, four varieties of hard disk drive data sets from BackBlaze are selected as study cases to validate the effectiveness of the proposed model. The results show that the mean MAPE of the proposed method is 2.1181 %, 2.2306 %, 8.1712 %, and 4.3417 %, respectively, corresponding to (hard disk drives ST8000NM0055, ST12000NM0007, ST10000NM0086, and ST14000NM0138), and the average value of the evaluation metrics are optimal in all competing models. Furthermore, it is observed that the number of reallocated sectors has the greatest influence in causing the failure of hard disk drives. [ABSTRACT FROM AUTHOR]

• An exact matrix-form solution is proposed for analyzing multiple non-circular tunnels in layered media. • Generalized complex variable theory, conformal mapping and fast Fourier transform are used in derivation. • The proposed solution avoids complicated coefficient determinations and iterative algorithm. • Effects of elastic properties, tunnels' position, equivalent layer and the layer thickness surrounding tunnels are discussed. This paper presents a matrix-form complex variable method that can predict the stress and displacement field around multiple tunnels in layered media. The proposed matrix-form method avoids complicated coefficient determinations and iterative algorithm, which effectively improves the computation efficiency. Firstly, the expressions for the stress and displacement field are given under the generalized complex variable theory. The conformal mapping technique and fast Fourier transform algorithm are used to formulate the matrix-form expressions of boundary conditions. Considering the boundary conditions of the tunnels and soil interfaces, the global matrix solution for multiple tunnels in layered media are obtained by assembling the matrix solutions of all single layers. The present theory is verified by comparison with the existing literature, finite element analysis and field data in engineering practices, and several numerical examples are given to reveal the effects of elastic properties, tunnels' position, equivalent layer and the layer thickness surrounding tunnels. [ABSTRACT FROM AUTHOR]

• A hybrid method by integrating the advantages of frequency-wavenumber method and finite element method. • The entire process simulation from the source to the local terrain has been achieved. • Seismic response of mountains due to point dislocation source. • The crustal velocity structure and source parameters influence the seismic response. This paper proposes a hybrid method to analyze seismic responses from the source to complex terrain. The hybrid method is based on the domain reduction idea, dividing the overall model into global domain (including the source and propagation path) and local domain (including complex terrain). For the propagation of seismic wave fields in the global domain, a frequency-wavenumber method based on the exact dynamic stiffness matrix is adopted. For the local domain, the finite element method combined with the artificial boundary substructure method is used to analyze the seismic response of complex terrain. The advantage of this hybrid method is that the frequency-wavenumber method can accurately and efficiently calculate the three-component ground motion of the global large-scale model, while the finite element method has a variety of elements and constitutive models, which can finely simulate the local complex terrain. We take the Zigong Xishan Park site as the research object, and verify the correctness of the hybrid method. Based on this, we use the hybrid method to simulate the seismic response of the site, focusing on the propagation process of seismic waves on the mountain surface, the spatial distribution of peak ground displacement, and the effects of crustal velocity structure and source parameters on the seismic response of the mountain. The results show that the propagation of seismic waves and the distribution of peak ground displacement are closely related to changes in terrain, and the crustal velocity structure and source parameters have significant effects on the seismic response of the mountain. [ABSTRACT FROM AUTHOR]

In this paper, we formulate mean and dispersion submodels for the class of Bell-Touchard regression models, and so we introduce the Bell-Touchard regression model with varying precision for count response variables. This regression model is, in some aspects, similar to the double generalized linear model framework, allowing for parameter interpretation in terms of the response variable in its original scale. We also provide an iterative process to estimate the regression coefficients in the mean and dispersion submodels, and develop diagnostic measures for this class of regression models. The methods developed are applied in a real data set for illustrative purposes. • Univariate count data modeling. • Two-parameter Bell-Touchard family of distributions. • Regression model for count variables with varying precision. • Overdispersion. [ABSTRACT FROM AUTHOR]

Rotating algal biofilm reactors (RABRs) are innovative systems designed to cultivate microalgae biofilms efficiently. In this paper, we have developed a novel mathematical model to accurately capture the growth dynamics of algae biofilms within RABR. By considering the spatial heterogeneity of the RABR, we introduce a PDE-based model that addresses the spatial variations across the substratum, enabling a more accurate simulation of biofilm growth in RABRs. The photosynthesis process is modeled through reactive kinetics, driving the growth of the algae biofilm. To analyze the system's behavior, we employ finite difference numerical methods to solve the complex PDE model. We then conduct extensive numerical simulations to understand algae biofilm growth in the RABR environment under various operational factors and environmental conditions. One primary focus in these simulations is to investigate the impact of various harvesting strategies, harvesting frequencies, light intensity, and light exposure on the overall biomass productivity of the algae biofilm. The numerical results provide valuable insights into optimizing algae biofilm growth and designing harvesting techniques in RABR systems. Our proposed novel mathematical model provides an effective platform for the theoretical investigation and design of RABRs for wastewater treatment. • New mathematical model simulates algae biofilm growth in RABRs accurately. • Incorporates photosynthesis and substratum surface heterogeneity. • Advances RABR efficiency in wastewater treatment and bioproducts. [ABSTRACT FROM AUTHOR]

• A numerical approach for obtaining gas-liquid flow parameters utilizing one-dimensional two-fluid model was proposed. • The two-fluid model was discretized by implicit FEM techniques utilizing the proposed algorithm in this paper. • Four cases utilizing different meshes were utilized to illustrate the gas puffing effect on the momentum exchange process. • The transient numerical trends indicate that the gas puffing manifests in two physical forms between different flow regions. The accumulation of liquid condensate in the wet gas pipelines gives negative effects on the piping efficiency and flow managements. Accurate prediction of the condensate behavior is of crucial importance in the pipeline engineering. In this study, the one-dimensional two-fluid model with the stratified modeling in its source term is used to describe the gas-liquid kinetic motion along the pipe and the flow fields obtained from the newly proposed numerical approach are utilized to analyze the flow characteristics. Firstly, four cases with varying inlet liquid fractions, outlet pressures, and different meshes are utilized to investigate the gas-liquid steady-state variations along the pipe. The numerical results indicate that the outlet pressure influences the working pressure of the inlet gas-liquid, subsequently altering the equilibrium state and momentum exchange direction near the inlet, resulting in different condensate distributions in the pipeline. In the transient analysis with initial empty pipe, the inlet gas-liquid mainly impacts the pressure wave propagations in pressure spread stage, the gas kinetic motion in gas filling stage and the motion of the dividing interface between different regions in liquid filling stage, which is validated by the proposed numerical approach through comparison with the simulation tool OLGA designed by Schlumberger. Furthermore, when the liquid condensates appear in the initial state, the transition zones have two physical forms between different flow regions, which include the sudden dividing interface due to the high liquid amount carried by the inlet gas and the transition region resulted from the liquid accumulations. [ABSTRACT FROM AUTHOR]

In this paper, a novel non-convex fractional-order image denoising model is proposed to suppress the staircase effect produced by the TV model while maintaining a neat contour. The model combines ℓ q (0 < q < 1) quasi-norm and fractional-order regularization, and employs a diffusion coefficient with a faster convergence rate to preserve more image edges and details. Additionally, an adaptive regularization parameter is designed to adjust the denoising performance of the algorithm. To obtain the optimal approximate solution of the model, an enhanced primal-dual algorithm is adopted and the complexity and convergence of the algorithm are theoretically analyzed. Finally, the effectiveness of the proposed method is demonstrated through numerical experiments. • A new non-convex FOTV model is proposed. • A new diffusion coefficient is introduced to retain more edge details of the image. • The existing primal-dual algorithm is improved, and the convergence of this algorithm is analyzed. • An adaptive regularization parameter is designed. [ABSTRACT FROM AUTHOR]

• Thermomechanical problem of FGMs sphere with material uncertainties is analyzed. • The interval random uncertainty model is recommended for material parameters. • A data-driven ANN fast calculation for FGMs sphere uncertainties analysis is established. • The volume fraction distribution is optimized for the safety design of the FGMs sphere. Mechanical analysis and optimal design for functionally graded materials (FGMs) structures are significant. The present paper analyzes the parameter uncertainties problem for the thermomechanical response of the FGMs spherical shells with volume fraction power distribution. Here, the interval random uncertainty model is recommended to describe the uncertainties of each component of material parameters in FGMs, and a data-driven artificial neural network (ANN) fast calculation for FGMs spherical shells thermomechanical problems with uncertainties analysis is established and trained. The thermomechanical coupling response analysis and volume fraction optimization analysis of the FGMs spherical shell with material uncertainties are realized for zirconia-titanium FGMs, with the maximum normalized Von Mises stress as the structural safety index and the ANN as the fast calculation method. In addition, the Von Mises stress of the FGMs spherical shell and a ZrO 2 -Ti alloy double-layer spherical shell under different loads is compared. The results show that material parameter uncertainties, especially those in Young's modulus, thermal expansion coefficient, and uniaxial yield limit significantly affect structural safety. The structural safety index λ calculated based on the volume fraction optimization design of FGMs spherical shell is significantly lower than that of the ZrO 2 -Ti alloy double-layer. The ANN method greatly improves the computational efficiency for uncertain problems and maintains high accuracy, compared with the statistical analysis after many calculations by randomly selecting material parameters. This study provides a path for the safety design of FGMs structures with uncertain parameters. [ABSTRACT FROM AUTHOR]

This paper incorporates the shortest passenger travel paths into the first train timetabling problem in urban rail transit networks. We first propose a path-based first train timetabling problem, which is formulated as a mixed-integer nonlinear programming model to reduce the travel time for passengers. To solve this model, we present a tailored branch-and-bound combined with the timetable-based Dijkstra algorithm. To further enhance the efficiency of the exact algorithm, we design a rolling time heuristic algorithm as a substitute for the branch-and-bound algorithm. Then, we proved that the rolling time heuristic combined with the timetable-based Dijkstra algorithm achieves 97.86% and 99.39% reductions in CPU time while sacrificing only 0.007% and 0.057% of optimality gap by two numerical experiments. Finally, the results based on two test networks with different structures demonstrate that the path-based first train timetabling model effectively improves passenger travel efficiency. Specifically, the travel times are reduced by 744 mins and 761 mins, while the transfer waiting times are reduced by 37.87% and 58.91% compared to the existing timetables. Moreover, the results also demonstrate that loop line networks will increase the difficulty of timetabling and lead to many passengers taking detours. To further enhance the efficiency of commuting for passengers who take the first train, URT operators may consider relaxing the limitations on the departure time of the depot stations. • A path-based first train timetabling model to minimize the total travel time in urban rail transit networks. • A tailored branch-and-bound combined with a timetable-based Dijkstra algorithm. • A rolling time heuristic algorithm to solve large-scale networks cases. [ABSTRACT FROM AUTHOR]

• The reflection/transmission of seismoelectric waves propagating through a sandwiched structure are studied. • A new fractional order viscoelastic model with two attenuation peaks at seismic and sonic frequencies is established. • The seismoelectric effects have noticeable influences on EM wave while negligible influences on seismic waves. • The porosity and the viscoelasticity of solid frame have evident influences on both elastic waves and EM waves The seismoelectric waves generated in a fluid-saturated porous interlayer and the reflection/transmission characteristics at the interfaces of sandwiched structure are studied in this paper. Aiming to describe the strong attenuation and dispersion simultaneously at seismic and sonic frequencies, a new fractional viscoelastic model for the solid skeleton is introduced to the Pride's seismoelectric coupling theory. Using the interfacial continuity of stress, displacements, magnetic and electric fields, the reflection/transmission coefficients are determined. The numerical results are provided and shown graphically. The effects of seismoelectric coupling and the viscoelastic characteristics of solid skeleton on the reflection and transmission of seismoelectric waves are mainly studied. It is observed that the thickness, porosity and the viscoelastic characteristics of solid skeleton have evident effects not only on the electromagnetic waves but also on the seismic waves. [ABSTRACT FROM AUTHOR]

The paper presents a new Lyapunov-type predefined-time stabilization control algorithm for stochastic high-order nonlinear systems with asymmetric output constraints. In contrast to stochastic finite-time and fixed-time stabilization, the average value of the settling-time function for stochastic predefined-time stabilization control is independent of both the initial value and the control factors. To mitigate the significant uncertainties arising from the asymmetric output constraint, a tan-type barrier Lyapunov function is formulated. Furthermore, by harnessing the previously mentioned barrier Lyapunov function and integrating the power integrator technique, a controller design strategy is formulated based on the backstepping method. The rigorous analysis in this study proves that the designed controller ensures both the attainment of predefined-time convergence of the system states to the origin in probability and the satisfaction of the output constraint. Finally, an example of a roll angle subsystem for quadrotor UAVs and a numerical illustration are presented to corroborate the theoretical analysis. • A novel Lyapunov-type stochastic predefined-time stable control algorithm is presented in Theorem 1. • Controller design based on the backstepping method is formulated through the power integrator technique. • The tan-type barrier Lyapunov function extends the order range and absorbs the inherent properties of the nonlinear terms. [ABSTRACT FROM AUTHOR]

• This manuscript firstly establishes a half vehicle-pavement-continuous beam bridge (VPCB) coupled system analytical model. • It is innovatively that the bridge and vehicle initial conditions are considered into analytical model. • The pavement road surface local deterioration is simulated by increasing the local roughness level of the road surface. At present, the highway bridge field is in a period of vigorous development, and the application of continuous beam bridges is becoming more extensive, so the related safety research is particularly important. However, there are few studies on the vehicle-bridge coupled interaction of continuous beam bridges, and the influence of pavement is not considered. In order to ensure that the theoretical research can better serve the engineering practice, it is urgent to establish a more refined and more complex vehicle-bridge coupled model. In this paper, a vehicle-pavement-continuous beam bridge (VPCB) coupled system model is established. A half-vehicle model is adopted, the pavement is simulated by a continuous and uniform spring damper, and the bridge is a three-span continuous beam bridge. The motion equation of VPCB system is established and deduced using D 'Alembert principle and modal superposition method. The dynamic responses of VPCB system are calculated by Newmark- β method. Here, the continuous beam bridge mode functions are fitted based on the modal vector of the continuous beam calculated by the finite element model. The correctness of the method is verified by existing literatures. The effects of bridge pavement, vehicle speed, bridge second span length, the pavement equivalent spring stiffness coefficient k p and damping coefficient c p , road roughness on VPCB system are studied. The results show that the pavement can reduce the bridge dynamic amplification factor (DAF) and the vehicle acceleration to improve the ride comfort. The dynamic responses of the vehicle and the bridge contain each other's natural frequencies. The responses of VPCB system increase with the vehicle velocity, the vehicle responses are more affected than the bridge responses. The pavement equivalent stiffness and damping coefficient has little effect on the system. The responses of vehicle and bridge increase with the increase of the bridge second span length. When the vehicle travels each span of the three-span continuous beam bridge, the time history curve of the pavement deformation under the tire resembles a sine wave. When the local roughness level of the road surface increases, the system responses at the deteriorated position suddenly increases, and the responses of the subsequent position will also be affected. The larger the roughness grade, the more obvious the responses increase. The effect on the system responses of the whole pavement damage is more significant than the local pavement damage. [ABSTRACT FROM AUTHOR]

Intensity inhomogeneity (IIH) and noise are ubiquitous in images acquired by a variety of imaging modalities, which pose an ongoing challenge for segmentation methods used in many applications. This paper proposes a level set evolution equation based on fractional derivative to address the IIH and noise issues in image segmentation, which integrates the information from the input and guidance images. The proposed model is a linear diffusion equation of level set function with nonlinear edge-stopping and guidance sources, in which the edge-stopping source is derived from the input image and a local statistical model (Bayesian formulation) in the level set framework, whereas the guidance source is derived from the guidance image and the fitting term of the popular Chan-Vese model. The guidance source ensures swift contour movement toward the boundary of the objects and enhances the robustness to noise and contour initialization, while the edge-stopping source is used to stop the evolving contour on the boundary of the objects later in the evolution. To tackle the challenge of obtaining accurate guidance images for many applications, an adaptive variable-order of fractional derivative robust to IIH and noise is introduced to generate the desired guidance image from the input image. The proposed diffusion equation with sources is solved numerically by the series splitting method and finite difference scheme. Experimental results on synthetic and real images show that the proposed model has higher performance in terms of accuracy and efficiency of segmentation, compared to several state-of-the-art level set models. • Propose guided active contours via level set evolution for noisy images with intensity inhomogeneity (IIH). • Design an adaptive order of fractional derivative that is basically not affected by IIH and noise. • Present a fractional derivative based method for generating guidance image from the input image. • Our model is experimentally very effective and efficient in segmenting images with IIH and noise. [ABSTRACT FROM AUTHOR]

Closed-form models are important because they offer more design insights, require less computing time and prevent convergence problems in modeling compliant mechanisms. However, most of the available closed-form models, e.g., beam constraint models, are only appropriate for beam flexures within the intermediate deflection range. In this paper, a method for developing closed-form models based on the chained beam constraint model through the combined use of strain energy and Castigliano's first theorem is proposed. A closed-form model for beam flexures with a large prediction range is derived using this method. By modeling simple beams and compliant mechanisms using the proposed closed-form model, it is shown that the model has a significantly broader prediction range than the beam constraint model and is more efficient than the chained beam constraint model. The large prediction range and high efficiency of the proposed closed-form model make it potentially useful for optimizing compliant mechanisms. • A method to develop closed-form models for beam flexures is proposed. • A closed-form model for CBCM with 3 discretized elements is obtained. • Closed-form load-displacement relations for beam flexures are obtained. • The proposed molded is demonstrated to reduce the computational time. [ABSTRACT FROM AUTHOR]

In this paper, the most probable exit path is applied to understand the switching of a bistable synthetic gene network with genetic toggle in Escherichia coli from a new perspective. It is worth mentioning that the most probable exit path is a deterministic indicator for researching stochastic system, and its role is analogous to the phase diagram and time history diagram of deterministic system. Firstly, the large deviation theory proves that when a dynamic system has a stable equilibrium point, the cumulative effect of its long-term action can make its sample trajectory reach another region with a probability of 1 from the attractive region under weak random disturbance. The concept of the most probable exit path is given by defining Freidlin-Wentzell action functional. Moreover, considering the noise intensity, Onsager-Machlup action functional is defined to obtain the most probable exit path of the system subject to random disturbance. Based on the Onsager-Machlup action functional, it can be observed that the impact of two types of noise intensities on the most probable exit path for the transition of the system. In addition, based on vector field decomposition, energy landscape is used to analyze the global stability of the system. Finally, this article intuitively demonstrates the switching process of the system with genetic toggle. The analysis of Onsager-Machlup action functional reveals that two independent noises have opposite effects on the system switching. The increase in the intensity of the second Gaussian noise is conductive to more accurately observing the most probable exit path of the system. According to the energy landscape, the reduction of noise intensity is not conductive to switching of the system with genetic toggle. • Most probable exit path intuitively illustrates the process of stochastic gene regulation. • Most probable exit path is obtained using FW and OM functional respectively by large deviation theory. • Analyze the effects of noise intensity and final time, provide guidance for gene expression cell differentiation process. • Based on vector field decomposition, energy landscape is used for global stability analysis of the system. [ABSTRACT FROM AUTHOR]

• Analyzed the stochastic resonance and stochastic P-bifurcation of an axially moving shape-memory alloy laminate. • A change in the volume fraction of the SMA shifted the formant of the SNR (signal-to-noise ratio) curve up and down. • Variation in axial velocity, temperature, and stochastic intensity induced stochastic P-bifurcation. This paper investigates the transverse vibration of an axially moving shape-memory alloy (SMA) fiber hybrid laminations under the combined action of transverse harmonic excitation and stochastic disturbance. Considering the shape memory alloy (SMA) fiber volume fraction random field, the kinetic energy and strain potential energy of SMA laminates are solved, and the axial motion equation of SMA laminates is derived according to Hamilton principle, a non-dimensional differential equation of the transverse vibration of the axially moving SMA laminated plates is obtained by adopting the Galerkin integral method. Considering the volume-fraction stochastic field, the stochastic natural vibration of a SMA laminate is analyzed. Considering the stochastic resonance of the SMA laminate under the action of Gaussian white noise and harmonic excitation, the effects of geometric parameters, physical parameters of materials, and temperature on the stochastic resonance behavior of the SMA laminate is analyzed. Finally, the effect of the stochastic P-bifurcation phenomenon of the parameters on the steady-state response of the SMA laminate is analyzed. [ABSTRACT FROM AUTHOR]