We present an \(hr\)-adaptivity framework for optimization of high-order meshes. This work extends the r-adaptivity method by Dobrev et al. (Comput Fluids, 2020), where we utilized the Target-Matrix Optimization Paradigm (TMOP) to minimize a functional that depends on each element’s current and target geometric parameters: element aspect-ratio, size, skew, and rotation. Since fixed mesh topology limits

The blood flow with heat transportation has prominent clinical importance during the levels where the blood flow needs to be checked (surgery) and the heat transportation rate must be controlled (therapy). This work presents an analysis of the melting heat transport of blood, which consists of iron nanoparticles along free convection with cross-model and solution of the partial differential equation

Variable-fidelity surrogate-based efficient global optimization (EGO) method with the ability to adaptively select low-fidelity (LF) and high-fidelity (HF) infill point has emerged as an alternative to further save the computational cost of the single-fidelity EGO method. However, in terms of the variable-fidelity surrogate-assisted multi-objective optimization methods, existing methods rely on empirical

Via the nonlocal stress–strain gradient continuum mechanics, the microscale-dependent linear and nonlinear large deflections of transversely loaded composite sector microplates with different thickness variation schemes are investigated. Microplates are assumed to be prepared from functionally graded materials (FGMs) the characteristics of which are changed along the thickness direction. A quasi-3D

Over the past few decades, it has been observed a remarkable progression in the development of computer aid models in the field of civil engineering. Machine learning models provide a reliable and robust alternative modeling design for solving complex engineering issues. The current study introduced three versions of newly explored ensemble machine learning models [extreme gradient boosting (XGBoost)

This paper is devoted to numerical investigations on mechanical behavior of cracked composite functionally graded (FG) plates. We thus develop an efficient adaptive approach in terms of the extended isogeometric analysis (XIGA) enhanced by locally refined non-uniform rational B-spline (LR NURBS) for natural frequency and buckling analysis of cracked FG Mindlin–Reissner plates. In this setting, the

Failure-probability-based global sensitivity (FP-GS) analysis can measure the effect of the input uncertainty on the failure probability. The state-of-the-art for estimating the FP-GS are less efficient for the rare failure event and the implicit performance function case. Thus, an adaptive Kriging nested Importance Sampling (AK-IS) method is proposed in this work to efficiently estimate the FP-GS

Liquefaction has caused many catastrophes during earthquakes in the past. When an earthquake is occurring, saturated granular soils may be subjected to the liquefaction phenomenon that can result in significant hazards. Therefore, a valid and reliable prediction of soil liquefaction potential is of high importance, especially when designing civil engineering projects. This study developed the least

This paper presents two distinct model updating strategies for dynamical systems with local nonlinearities based on acceleration time history responses measured spatially across the vibrating structure. Both linear and nonlinear parameters are calibrated by minimizing the selected metric based on measured and predicted response using the newly proposed variant of differential search algorithm named

Plate structures are the integral parts of any maritime engineering platform. With the recent focus on composite structures, the need for optimizing their design and functionality has now been tremendously realized. In this paper, a comprehensive study is carried out on the effectiveness and optimization performance of three metaheuristic algorithms in designing skew composite laminates under dynamic

Recent work trend is to hybridize two and more variants in order to recognize better quality of functional and remedies to the global challenges of optimisation. The newly formed Slime Mould Algorithm (SMA) is premised upon naturally occurring slime mould oscillation feature. There is an effort to build a more effective way to accomplish exploration through process of exploitation. In a comprehensive

The safety and health monitoring of dams has attracted increasing attention. In this paper, a novel prediction model based on variational autoencoder (VAE) and temporal attention-based long short-term memory (TALSTM) network is proposed for the long-term deformation of arch dams. In the proposed model, the convolutional neural network-based VAE is applied to extracting the features of environmental

Accurate prediction of ground vibration caused by blasting has always been a significant issue in the mining industry. Ground vibration caused by blasting is a harmful phenomenon to nearby buildings and should be prevented. In this regard, a new intelligent method for predicting peak particle velocity (PPV) induced by blasting had been developed. Accordingly, 150 sets of data composed of thirteen uncontrollable

In this study, a new fractal-fractional (FF) derivative is defined by coupling the local conformable derivative and non-local Caputo fractional derivative. Using the defined derivative, a space–time FF version of the modified Benjamin–Bona–Mahony type equations is introduced. A collocation technique based on the orthonormal Bernoulli polynomials and their derivative matrices (including the ordinary

Due to the increasing usage of nanostructures in nanotechnology and nanodevice, the following article aims to investigate the free vibration and buckling behaviours of a Timoshenko functionally graded nanobeam under to thermal and magnetic environment. The nanoscale and microstructure effects of FG nanobeam are included to classical mechanics using nonlocal strain gradient theory. The gradation of

In the presented research, vibrational, and amplitude behaviors of a sandwich spinning disk made of two laminated layers and graphene nanoplatelets reinforced composite (GPLRC) core has been reported. The Coriolis and centrifugal impacts have been taken into account due to its rotational feature. The stresses and strains have been obtained through the high-order shear deformable theory (HSDT). The

Automated logistic systems are commonly applied in the enterprise logistic processes while allowing to improve the reliability and efficiency of logistics procedures with computer simulation. The logistics system focuses on realizing the space and time efficiency of material and understanding the links of logistics to achieve the optimum economic effect. Therefore, in this study, 150 data were collected

As a first attempt, Fourier series expansion (FSE), particle swarm optimization (PSO), and genetic algorithm (GA) methods are coupled for analysis of the static–dynamic performance and propagated waves in the magneto-electro-elastic (MEE) nanoplate. The FSE method is presented for solving the motion equations of the MEE nanoplate. For increasing the performance of genetic algorithms for solving the

In this paper, to improve the vibrational response of microstructures, the impact of the nonlinear modal analysis of axially functionally graded (AFG) truncated conical micro-scale tube including the thermal loading for the different type of cross sections such as uniform section, linear tapered section, convex section, the exponential section are studied that are applicable for various application

Carbon nanotube (CNT)-reinforced polymer nanocomposites possess marvelous stiffness and strength as well as viscoelastic nature due to the time-dependent properties of the polymers. Hence, adequate knowledge about their rheological behavior is required if it is aimed at using such nanomaterials in design of aerospace structures. Present manuscript is arranged to account for the time-dependency of the

Predator–prey models appear in various fields of bio-mathematics used for the analysis of interactions of biological systems. Due to the complexities of the physical context for the real-world problems of food chain dynamics, introducing new models compatible with experimental results stays ongoing research. Many models have been proposed and analyzed for these systems in recent years. In this paper

Motivated by progressive sandwich structures’ usage due to their high strength to weight ratio in different industries, the current paper aimed at evaluating static and dynamic behaviors of three-layered cylinders including FG porous core and two graphene nanoplatelet (GPLs)-reinforced composite as face sheets. The whole sandwich cylinder rests on Pasternak substrate and it is also exposed to a longitudinal

The dynamic mechanical properties of ore rock are important in blast designs and support designs for underground mines. However, few studies have focused on ore rock with varying grade, and the application of such studies to production in underground mines is rather limited. In this study, Split Hopkinson pressure bar (SHPB) tests were conducted on ore rock with varying grades. Images were recorded

In this article, critical angular velocity, critical velocity of fluid flow and vibration control analysis of a rotating multi-hybrid nanocomposite reinforced (MHCR) cylindrical microshell covered with a piezoelectric layer as sensor and actuator (PLSA) are presented. The current non-classical model is capable of capturing the size dependency in the microshells using only one material length scale

In the present article, delay and system of delay differential equations are treated using feed-forward artificial neural networks. We have solved multiple problems using neural network architectures with different depths. The neural networks are trained using the extreme learning machine algorithm for the satisfaction of delay differential equations and associated initial/boundary conditions. Further

This study proposes Chebyshev wavelet collocation method for partial differential equation and applies to solve magnetohydrodynamic (MHD) flow equations in a rectangular duct in the presence of transverse external oblique magnetic field. Approximate solutions of velocity and induced magnetic field are obtained for steady‐state, fully developed, incompressible flow for a conducting fluid inside the

Evolutionary polynomial regression (EPR) is extensively used in engineering for soil properties modeling. This grey-box technique uses evolutionary computing to produce simple, transparent and well-structured models in the form of polynomial equations that best explain the observed data. A key task is then to determine mathematical structures for modeling physical phenomena and to select the optimal

The Analytic hierarchy process is one of the most commonly used Multicriteria decision-making methods. The biggest drawback of this method is that it does not produce good results if some of the criteria are undesirable. There are many ways to overcome this problem, which are either too complex or too limited. This paper presents the application and results of one aspect of the general BOCR method

Most of the multiscale topology optimization (TO) approaches, which have been proposed for multi-material designs, are based on the assumption of deterministic loads and the exclusion of uncertain quantities like positions, directions, and magnitudes of loads. This contribution deals with: (1) multiscale design; (2) multi-materials; (3) loading uncertainties; and (4) incompressible materials such as

The sandwich structures contain three or more layers attached to the core. In the current research, a three-layered sandwich microplate containing functionally graded (FG) porous materials as core and piezoelectric nanocomposite materials as face sheets subjected to electric field resting on Pasternak foundation is chosen as a model to investigate its vibrational behavior. To make the face sheets stiffer

In the present study, damage initiation and growth in a polycrystalline aggregate are investigated. In this regard, an anisotropic continuum damage mechanics coupled with rate-dependent crystal plasticity theory is employed. Using a thermodynamically consistent procedure, a finite deformation formulation is derived. For this purpose, the damage tensor is incorporated in the crystal plasticity formulation

This paper aims to address the problem of poor diversity and convergence for traditional evolutionary algorithms in solving multi-objective optimization problems and proposes a cellular differential evolutionary algorithm with double-stage external population-leading. This algorithm divides the maintenance of external population diversity into double stages and introduces new disturbance in the mutation

Air overpressure (AOp) is a hazardous effect induced by the blasting method in surface mines. Therefore, it needs to be predicted to reduce the potential risk of damage. The aim of this study is to offer an efficient method to predict AOp using a cascaded forward neural network (CFNN) trained by Levenberg–Marquardt (LM) algorithm, called the CFNN-LM model. Additionally, a generalized regression neural

Composite beams (CBs) include concrete slabs jointed to the steel parts by the shear connectors, which highly popular in modern structures such as high rise buildings and bridges. This study has investigated the structural behavior of simply supported CBs in which a concrete slab is jointed to a steel beam by headed stud shear connector. Determining the behavior of CB through empirical study except

When choosing a path for a linear infrastructure between two terminals, several types of constraints apply for installation and operational criteria. For offshore pipelines or cables, curvature constraints are typically important not only due to the flexural rigidity but also the maneuverability of the laying vessels. Roads are subject to similar curvature constraints to ensure the safety of users

A numerical scheme based on polynomials and finite difference method is developed for numerical solutions of two-dimensional linear and nonlinear Sobolev equations. In this approach, finite difference method is applied for the discretization of time derivative whereas space derivatives are approximated by two-dimensional Lucas polynomials. Applying the procedure and utilizing finite Fibonacci sequence

The paper presents a novel nonlocal strain gradient isogeometric model for functionally graded carbon nanotube-reinforced composite (FG-CNTRC) nanoplates. To observe the length scale and size-dependency effects of nanostructures, the nonlocal strain gradient theory (NSGT) is considered. The present model is efficient to capture both nonlocal effects and strain gradient effects in nanoplate structures

Clustering is an exploratory data analysis technique that organize the data objects into clusters with optimal distance efficacy. In this work, a bat algorithm is considered to obtain optimal set of clusters. The bat algorithm is based on the echolocation feature of micro bats. Moreover, some improvements are proposed to overcome the shortcoming associated with bat algorithm like local optima, slow

The multi-objective efficient global optimization (MOEGO), an extension of the single-objective efficient global optimization algorithm with the intention to handle multiple objectives, is one of the most frequently studied surrogate model-based optimization algorithms. However, the evaluation of the infill point obtained in each MOEGO update iteration using simulation tool may fail. Such evaluation

In this work, a fast numerical method is considered to solve the space-fractional semilinear parabolic equations on closed surfaces. It is a challenge in that how to define the space fractional operator and corresponding semilinear parabolic equation with the energy functional defined on surface. To overcome it, using the local tangential space, we construct the spectral approximation for the space

Engineering design is a complex process to find a suitable trade-off among different, and sometimes conflicting, design specifications. In reality, these requirements can be often considered as constraints of the design problem, that can be defined in terms of performance measures or geometrical characteristics of the device under study. In this paper, a new design space exploration methodology is

This paper updates a method for generating small, accurate kinetic models for applications in computational fluid dynamics programs. This particular method first uses a time-integrated flux-based algorithm to generate the smallest possible skeletal model based on the detailed kinetic model. Then, it uses a multi-stage optimization process in which multiple runs of a genetic algorithm are used to optimize

The Guadalquivir bridge is a large-scale twin steel truss bridge located in Spain that opened to traffic in 1929. Since the bridge has come into operation for a long time, structural health monitoring (SHM) is strictly necessary to guarantee safety and avoid serious incidents. This paper proposes a novel approach to model updating for the Guadalquivir bridge based on the vibration measurements combined

Feature selection (FS) is a critical step in data mining, and machine learning algorithms play a crucial role in algorithms performance. It reduces the processing time and accuracy of the categories. In this paper, three different solutions are proposed to FS. In the first solution, the Harris Hawks Optimization (HHO) algorithm has been multiplied, and in the second solution, the Fruitfly Optimization

The present paper focuses on designing an artificial neural network (ANN) model and a multiple regression analysis (MRA) that could be used to predict factor of safety of dragline dump slope. To implement these two models, the dataset was utilized from the numerical simulation results of dragline dump slopes, wherein 216 dragline dump slope models were simulated using a numerical modeling technique

The present work fills a gap on the postbuckling behavior of multilayer functionally graded graphene platelet reinforced composite (FG-GPLRC) cylindrical and spherical shell panels resting on elastic foundations subjected to central pinching forces and pressure loadings. Based on a higher-order shear deformation theory and the von Kármán’s nonlinear strain–displacement relations, the governing equations

This study investigates the effects of fluid–structure and soil–structure interaction on the free vibration response of functionally graded sandwich plates. To this aim, an exemplary problem is analyzed, whereas a metal/ceramic sandwich plate is placed at the bottom of a tank filled in with fluid. Two cases are considered: (i) soft core, i.e., a sandwich plate with metal core and ceramic skins, and

Circular failure can be seen in weak rocks, the slope of soil, mine dump, and highly jointed rock mass. The challenging issue is to accurately predict the safety factor (SF) and the behavior of slopes. The aim of this study is to offer advanced and accurate models to predict the SF of slopes through machine learning methods improved by optimization algorithms. To this view, three different methods

High accurate wind speed forecasting plays an important role in ensuring the sustainability of wind power utilization. Although deep neural networks (DNNs) have been recently applied to wind time-series datasets, their maximum performance largely leans on their designed architecture. By the current state-of-the-art DNNs, their architectures are mainly configured in manual way, which is a time-consuming

Reliability analysis with multiple failure modes is needed because more than one failure mode exists in many engineering applications. Kriging-based surrogate model is widely adopted for component reliability analysis because of its high computational efficiency. Compared with Kriging-based component reliability analysis, selecting the sample points that affect the system performance is more difficult

Optimization to optimization (OtoO) approach is proposed in this study. It aims to increase an optimization algorithm performance. OtoO approach has two types of optimization methods. First is essential algorithm, which is used for solution of the basic problem. Second is auxiliary algorithm that adjusted the parameters of the essential algorithm. In this study, the monarchy butterfly optimization

A nonlocal strain gradient model is developed in this research to analyse the nonlinear frequencies of functionally graded porous curved nanotubes. It is assumed that the curved nanotube is in contact with a two-parameter nonlinear elastic foundation and is also subjected to the uniform temperature rise. The non-classical theory presented for curved nanotubes contains a nonlocal parameter and a material

Prediction of the scour depth around non-uniformly spaced pile groups (PGs) is one of the most complex problems is hydraulic engineering. Different types of empirical methods have been developed for estimating the scour depth around the PGs. However, the majority of the existing methods are based on simple regression methods and have serious limitations in modelling the highly nonlinear and complex

Naked mole-rat algorithm (NMRA) is a new swarm intelligence technique based on the mating patterns of NMRs present in nature. The algorithm though is very simple and linear in nature but suffers from poor exploration during the initial stages and poor exploitation towards the end. Thus to overcome these problems and estimate the effect of basic parameters of NMRA, six new inertia weight strategies

We propose an efficient formulation using the framework of Generalized Finite Element Method (GFEM) for the solutions of transient heat diffusion problems having multiple heat sources in the solution domain. The purpose here is to use minimal computational resources and rely on coarse mesh grids to capture the sharp variations of temperature field. We use Gaussian functions of global nature to enrich

In this paper, we will focus on adaptive meshing and re-meshing. We present an original approach, based on Quadtree and Octree, to construct the initial mesh and refine it using mixed-elements. We propose a fast algorithm using a determined set of Patterns to handle transitions between fine and coarse regions, and to closely approximate surface boundaries. An optimized structure for storing edges permits

For the reliability analysis with imprecise probability distributions, the failure probability and its sensitivity are always denoted as the functions of distribution parameters. The computation of those functional relationships remains a challenging task due to the intensive computational burden. To further improve the computational efficiency, this work proposes a new computational method based on

Blast-induced ground vibration is considered as one of the most hazardous phenomena of mine blasting, which can even cause casualties and severe damages to the adjacent properties. Measuring peak particle velocity (PPV) is helpful to know the actual vibration level but prediction of blast vibration prior to the blast is a tedious job due to involvement of blast design, explosive and rock parameters

The range of applications of artificial intelligence (AI) that is based on nature-inspired metaheuristics is rapidly increasing across various scientific fields as it is used to solve complex engineering problems. This work develops a cloud evolutionary machine learning system, called the nature-inspired metaheuristic optimization and prediction system (NiMOPS) that is composed of metaheuristic AI