Engineering Computations最新文献

Purpose

The objective of this work is to analyze the necessary conditions for chaotic behavior with fractional order and fractal dimension values of the fractal-fractional operator.

Design/methodology/approach

The numerical technique based on the fractal-fractional derivative is implemented over the fractional model and analyzes the condition at the distinct values of fractional order and fractal dimension.

Findings

The obtained numerical solution from the numerical technique is analyzed at distinct fractional order and fractal dimension values, and it has been figured out that the behavior of the solution either chaotic or non-chaotic agrees with the condition.

Originality/value

The necessary condition is associated with the fractional order only. So, our work not only studies the condition with fractional order but also examines the model by simultaneously adjusting fractal dimension values. It is found that the model still has chaotic or non-chaotic behavior at certain fractal dimension values and fractional order values corresponding to the condition.

Purpose

In order to include the non-negligible lag relaxation time feature that is characteristic of heat transfer in biological bodies, the classical Fourier's law of heat conduction has to be generalized as the Maxwell–Cattaneo law resulting in the thermal-wave model of bio-heat transfer. The purpose of the paper is to retrieve the unknown time-dependent blood perfusion coefficient in such a thermal-wave model of bio-heat transfer from (non-intrusive) measurements of the temperature on an accessible sub-portion of the boundary that may be taken with an infrared scanner.

Design/methodology/approach

The nonlinear and ill-posed problem is reformulated as a nonlinear minimization problem of a Tikhonov regularization functional subject to lower and upper simple bounds on the unknown coefficient. For the numerical discretization, an unconditionally stable direct solver based on the Crank–Nicolson finite-difference scheme is developed. The Tikhonov regularization functional is minimized iteratively by the built-in routine lsqnonlin from the MATLAB optimization toolbox. Numerical results for a benchmark test example are presented and thoroughly discussed, shedding light on the performance and effectiveness of the proposed methodology.

Findings

The inverse problem of obtaining the time-dependent blood perfusion coefficient and the temperature in the thermal-wave model of bio-heat transfer from extra boundary temperature measurement has been solved. In particular, the uniqueness of the solution to this inverse problem has been established. Furthermore, our proposed computational method demonstrated successful attainment of the perfusion coefficient and temperature, even when dealing with noisy data.

Originality/value

The originalities of the present paper are to account for such a more representative thermal-wave model of heat transfer in biological bodies and to investigate the possibility of determining its time-dependent blood perfusion coefficient from non-intrusive boundary temperature measurements.

Purpose

The purpose of this study is to simulate the tensile and shear types of fractures using the mixed fracture criteria considering the energy evolution based on the dual bilinear cohesive zone model and investigate the dynamic propagation of tensile and shear fractures induced by an impact load in rock. The propagation of tension and shear at different scales induced by the impact load is also an important aspect of this study.

Design/methodology/approach

In this study, based on the well-developed dual bilinear cohesive zone model and combined finite element-discrete element method, the dynamic propagation of tensile and shear fractures induced by the impact load in rock is investigated. Some key technologies, such as the governing partial differential equations, fracture criteria, numerical discretisation and detection and separation, are introduced to form the global algorithm and procedure. By comparing with the tensile and shear fractures induced by the impact load in rock disc in typical experiments, the effectiveness and reliability of the proposed method are well verified.

Findings

The dynamic propagation of tensile and shear fractures in the laboratory- and engineering-scale rock disc and rock strata are derived. The influence of mesh sensitivity, impact load velocities and load positions are investigated. The larger load velocities may induce larger fracture width and entire failure. When the impact load is applied near the left support constraint boundary, concentrated shear fractures appear around the loading region, as well as induced shear fracture band, which may induce local instability. The proposed method shows good applicability in studying the propagation of tensile and shear fractures under impact loads.

Originality/value

The proposed method can identify fracture propagation via the stress and energy evolution of rock masses under the impact load, which has potential to be extended into the investigation of the mixed fractures and disturbance of in-situ stresses during dynamic strata mining in deep energy development.

Purpose

Elastic rings served as the elastic supporting elements which have been extensively used in the aeroengines for maneuverable planes with high overloading. However, under extreme conditions, the elastic ring contacts the bearing seat, causing elastic ring failure. Therefore, it is necessary to optimize the matching parameters of the elastic ring in order to suppress the occurrence of elastic ring failure under harsh working conditions.

Design/methodology/approach

In this paper, a rotor system supported by elastic rings is researched and a multi-objective parameter matching method of elastic ring is proposed, considering the elastic ring failure, rotor system’s frequency forbidden zone and rotor system’s dynamic response. Then, the particle swarm optimization algorithm is used to dynamically constrain the parameter matching space and obtain the ideal solution for the elastic ring parameter matching.

Findings

By analyzing the elastic ring’s matching results (different unbalanced forces and disk masses), the relationship between the trend of Pareto front changes and rotor system parameters is studied. In addition, the rotor system’s dynamic characteristics before and after parameter matching are analyzed.

Originality/value

This article provides guidance for the design of elastic rings by matching the parameters of elastic rings.

Purpose

The paper aims to propose a generation approach for unstructured surface mesh to speed up mesh generation.

Design/methodology/approach

The paper proposes a lightweight interactive generation approach for unstructured surface mesh and presents several key technologies to support this approach.

Findings

The experimental results show that the proposed approach is feasible for unstructured meshes and it can accelerate the mesh generation process.

Research limitations/implications

More geometric defects should be covered, and more convenient and efficient interactive means need to be provided.

Practical implications

The proposed approach and key technologies are implemented in NNW-GridStar.UG, which is the unstructured version of the mesh generation software of National Numerical Windtunnel (NNW).

Originality/value

This paper proposes a lightweight interactive approach for unstructured surface mesh generation, which can speed up mesh generation.

Purpose

Deep-learning techniques are recently gaining a lot of importance in the field of turbulence. This study focuses on addressing the problem of data imbalance to improve the performance of an existing deep learning neural network to infer the Reynolds-averaged Navier–Stokes solution, proposed by Thuerey et al. (2020), in the cases of airfoils with high wake formation behind them. The model is based on a U-Net architecture, which calculates pressure and velocity solutions for fluid flow around an airfoil.

Design/methodology/approach

In this work, we propose various methods for training the model on selectively generated data with different distributions, which would be representative of the under-performing test samples. The property we chose for selectively generating data was the fraction of negative x-velocity in the domain. We have used Grad-CAM to compare the layer activations of different models trained using the proposed methods.

Findings

We observed that using our methods, the average performance on the samples with high wake formation (i.e. flow over airfoils at high angle of attack) has improved. Using one of the proposed methods, an average performance improvement of 15.65% was observed for samples of unknown airfoils compared to a similar model trained using the original method.

Originality/value

This work demonstrates the use of imbalanced learning in the field of fluid mechanics. The performance of the model is improved by giving significance to the distribution of the training data without changes to the model architecture.

Purpose

Multilayer composite liner structures are the primary structural form of hydraulic tunnels. However, the bearing mechanism of multilayer composite liners has not been investigated thoroughly. Many existing design schemes do not properly achieve a balance between structural safety, anti-seepage capacity, and cost effectiveness. Thus, a new composite liner structure type and its theoretical model was proposed.

Design/methodology/approach

A novel hydraulic tunnel composite liner structure with a polyurea spray coating interlayer was proposed in this study. A theoretical model based on the state-space method was developed and verified using FEM models and existing theoretical models. Parametric analysis was conducted based on the theoretical model to investigate the influence of various variables, including interfacial shear stiffness, inner liner thickness, and outer liner elastic modulus.

Findings

It was concluded that the proposed theoretical model can be used successfully to calculate multilayer composite liner structures with high calculation efficiency. The overall deformation stiffness of the composite liner system increased with the interfacial shear stiffness. The sprayed coating interlayer significantly affects the residual force distribution between the outer and inner liners, which can also be affected by the adjustment of the thickness of the outer and inner liners. Thus, attention should be paid to these factors in the rational design of the proposed composite liner system.

Originality/value

With the development of China’s water conservancy projects, complex geological conditions, high surrounding rock stress, high internal and external water pressures, and other unique application scenarios have gradually increased. This places higher requirements on the bearing performance and impermeability of hydraulic tunnel lining structures. On the other hand, conventional hydraulic tunnel lining structures can hardly achieve a satisfactory balance between economy, structural safety, and impermeability. Thus, the proposed structure has the potential to be used in a wide range of applications.

Purpose

The constitutive models determine the mechanical response to the defined loading based on model parameters. In this paper, the inverse problem is researched, i.e. the identification of the model parameters based on the loading and responses of the material. The conventional methods for determining the parameters of constitutive models often demand significant computational time or extensive model knowledge for manual calibration. The aim of this paper is to introduce an alternative method, based on artificial neural networks, for determining the parameters of a viscoplastic model.

Design/methodology/approach

An artificial neural network was proposed to determine nine material parameters of a viscoplastic model using data from three half-life hysteresis loops. The proposed network was used to determine the material parameters from uniaxial low-cycle fatigue experimental data of an aluminium alloy obtained at elevated temperatures and three different mechanical strain rates.

Findings

A reasonable correlation between experimental and numerical data was achieved using the determined material parameters.

Originality/value

This paper fulfils a need to research alternative methods of identifying material parameters.

Purpose

The purpose of this research is to establish a robust numerical framework for the calibration of macroscopic constitutive parameters, based on the analysis of polycrystalline RVEs with computational homogenisation.

Design/methodology/approach

This framework is composed of four building-blocks: (1) the multi-scale model, consisting of polycrystalline RVEs, where the grains are modelled with anisotropic crystal plasticity, and computational homogenisation to link the scales, (2) a set of loading cases to generate the reference responses, (3) the von Mises elasto-plastic model to be calibrated, and (4) the optimisation algorithms to solve the inverse identification problem. Several optimisation algorithms are assessed through a reference identification problem. Thereafter, different calibration strategies are tested. The accuracy of the calibrated models is evaluated by comparing their results against an FE2 model and experimental data.

Findings

In the initial tests, the LIPO optimiser performs the best. Good results accuracy is obtained with the calibrated constitutive models. The computing time needed by the FE2 simulations is 5 orders of magnitude larger, compared to the standard macroscopic simulations, demonstrating how this framework is suitable to obtain efficient micro-mechanics-informed constitutive models.

Originality/value

This contribution proposes a numerical framework, based on FE2 and macro-scale single element simulations, where the calibration of constitutive laws is informed by multi-scale analysis. The most efficient combination of optimisation algorithm and definition of the objective function is studied, and the robustness of the proposed approach is demonstrated by validation with both numerical and experimental data.