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Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.

In the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.

This paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.

The authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.

The purpose of this paper is to study the controller design of flexible manipulator. Flexible manipulator system is a nonlinear, strong coupling, time-varying system, which is introduced elastodynamics in the study and complicated to control. However, due to the flexible manipulator, system has a significant advantage in response speed, control accuracy and load weight ratio to attract a lot of researchers.

Since the order of flexible manipulator system is high, designing controller process will be complex, and have a large amount of calculation, but this paper will use the dynamic surface control method to solve this problem.

Dynamic surface control method as a controller design method which can effectively solve the problem with the system contains nonlinear and reduced design complexity.

The authors assume that the dynamic parameters of flexible manipulator system are unknown, and use Radial Basis Function neural network to approach the unknown system, combined with the dynamic surface control method to design the controller.

As an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex engineering systems, not only because of the accurate evaluation of the impact of uncertain factors but also the relatively good balance between economy and safety of performance. However, with the increasing complexity of engineering technology, the proposed RBMDO method gradually cannot effectively solve the higher nonlinear coupled multidisciplinary uncertainty design optimization problems, which limits the engineering application of RBMDO. Many valuable works have been done in the RBMDO field in recent decades to tackle the above challenges. This study is to review these studies systematically, highlight the research opportunities and challenges, and attempt to guide future research efforts.

This study presents a comprehensive review of the RBMDO theory, mainly including the reliability analysis methods of different uncertainties and the decoupling strategies of RBMDO.

First, the multidisciplinary design optimization (MDO) preliminaries are given. The basic MDO concepts and the corresponding mathematical formulas are illustrated. Then, the procedures of three RBMDO methods with different reliability analysis strategies are introduced in detail. These RBMDO methods were proposed for the design optimization problems under different uncertainty types. Furtherly, an optimization problem for a certain operating condition of a turbine runner blade is introduced to illustrate the engineering application of the above method. Finally, three aspects of future challenges for RBMDO, namely, time-varying uncertainty analysis; high-precision surrogate models, and verification, validation and accreditation (VVA) for the model, are discussed followed by the conclusion.

The scope of this study is to introduce the RBMDO theory systematically. Three commonly used RBMDO-SORA methods are reviewed comprehensively, including the methods' general procedures and mathematical models.

The heat transfer properties play significant roles in the thermal comfort of the clothing products. The purpose of this paper is to find the relationship between heat transfer properties and fabrics' structure, yarn properties and predict the effective thermal conductivity of single layer woven fabrics by a parametric mathematical model.

First, the weave unit was divided into four types of element regions, including yarn overlap regions, yarn crossing regions, yarn floating regions and pore regions. Second, the number and area proportion of each region were calculated respectively. Some formulas were created to calculate the effective thermal conductivity of each element region based on serial model, parallel model or series–parallel mixing model. Finally, according to the number and area proportion of each region in weave unit, the formulas were established to calculate the fabric overall effective thermal conductivity in thickness direction based on the parallel models.

The influences of yarn spacing, yarn width, fabric thickness, the compressing coefficients of air layers and weave type on the effective thermal conductivity were further discussed respectively. In this model, the relationships between the effective thermal conductivity and each parameter are some polynomial fitting curves with different orders. Weave type affects the change of effective thermal conductivity mainly through the numbers of different elements and their area ratios.

In this model, the formulas were created respectively to calculate the effective thermal conductivity of each element region and whole weave unit. The serial–parallel mixing characteristics of yarn and surrounding air are considered, as well as the compression coefficients of air layers. The results of this study can be further applied to the optimal design of mixture fabrics with different warp and filling yarn densities or different yarn thermal properties.

The purpose of this paper is to present a numerical methodology for the solution of non-Fourier conduction in two-dimensional (2-D) heterogeneous materials with contact resistance.

Energy and heat flux equations with time lagging constant are combined to form a 2-D hyperbolic conduction equation in conservational form, and the resulting equation is solved by finite volume method.

The magnitude of contact resistance is inversely proportional to the temperature jump at the contact surface and phonon transmission coefficient between heterogeneous medium. Numerical results show that higher the contact resistance, lower the heat flux through the interface, lower the strength of transmitted wave and higher the strength of reflected wave at the interface. These results are in agreement with physical expectations. Temperature profiles show expected discontinuity at the interface while the heat fluxes are continuous, demonstrating the accuracy of the proposed methodology.

In most available numerical methods for hyperbolic conduction with contact resistance, contact resistances are treated as internal boundaries at which boundary conditions are specified. In the present formulation, contact resistance between two heterogeneous materials is treated as a part of interface transport properties not as an added boundary condition. This approach makes the formulation much simpler and straightforward for multidimensional applications. This approach is never used previously and is original.

The emergence of the Software-as-a-service (SaaS) licensing model dramatically changes how enterprise software is released. Especially, it is favored by small and medium enterprises (SMEs) because of the cost-friendly feature. In contrast, many large enterprises (LEs) own relatively abundant budgets and prefer the on-premise software to fulfill demands through customization. Considering the differentiated cost-acceptance level among customers, this study aims to address the versioning problem of the enterprise software faced by software firms.

A two-point distribution model is formulated to calculate the maximal profits software firm earned from both LEs and SMEs under three strategies (On-premise, SaaS and Hybrid). Then through profit comparison, this paper obtains the optimal versioning strategy and corresponding feasible conditions. Finally, the optimal solutions are derived concerning social welfare.

A significant finding is that moving to SaaS becomes necessary for the software firms in product releases since the on-premise strategy will not be optimal. Based on this, this paper discovers that when LEs own a cost-acceptance level close to that of SMEs, the hybrid strategy is the only optimal choice. When LEs become less sensitive to costs, the hybrid strategy is suggested if the customization cost falls below the threshold. Otherwise, the SaaS strategy becomes the optimal option. The conclusions explain why some software vendors transit to “cloud companies” thoroughly and provide practical insights for software firms’ future decisions.

To the best of the authors’ knowledge, this paper is the first information economics study to consider consumer cost sensitivity in discussing enterprise software versioning. The differentiated cost-acceptance level is introduced to describe the customer utilities, and the results uncover the necessity of moving to SaaS under diversified customer composition. This work provides significant theoretical value and practical insights.

Numerous finite elements are proposed based on analytical solutions. However, it is difficult to find the solutions for complicated governing equations. This paper aims to present a novel formulation in the framework of assumed stress quasi-conforming method for the static and free vibration analysis of anisotropic and symmetric laminated plates.

Firstly, an initial stress approximation ruled by 17 parameters, which satisfies the equilibrium equations is derived to improve the performance of the constructed element. Then the stress matrix is treated as the weighted function to weaken the strain-displacement equations. Finally, the Timoshenko’s laminated composite beam functions are adopted as boundary string-net functions for strain integration.

Several numerical examples are presented to show the performance of the new element, and the results obtained are compared with other available ones. Numerical results have proved that the new element is free from shear locking and possesses high accuracy for the analysis of anisotropic and symmetric laminated plates.

This paper proposes a new QC element for the static and free vibration analysis of anisotropic and symmetric laminated plates. In contrast with the complicated analytical solutions of the equilibrium equations, an initial stress approximation ruled by 17 parameters is adopted here. The Timoshenkos laminated composite beam functions are introduced as boundary string-net functions for strain integration. Numerical results demonstrate the new element is free from shear locking and possesses high accuracy for the analysis of anisotropic and symmetric laminated plates.

This paper aims to investigate an identification strategy for the nonlinear state-space model (SSM) in the presence of an unknown output time-delay. The equations to estimate the unknown model parameters and output time-delay are derived simultaneously in the proposed strategy.

The unknown integer-valued time-delay is processed as a latent variable which is uniformly distributed in a priori known range. The estimations of the unknown time-delay and model parameters are both realized using the Expectation-Maximization (EM) algorithm, which has a good performance in dealing with latent variable issues. Moreover, the particle filter (PF) with an unknown time-delay is introduced to calculated the Q-function of the EM algorithm.

Although amounts of effective approaches for nonlinear SSM identification have been developed in the literature, the problem of time-delay is not considered in most of them. The time-delay is commonly existed in industrial scenario and it could cause extra difficulties for industrial process modeling. The problem of unknown output time-delay is considered in this paper, and the validity of the proposed approach is demonstrated through the numerical example and a two-link manipulator system.

The novel approach to identify the nonlinear SSM in the presence of an unknown output time-delay with EM algorithm is put forward in this work.

To solve problems of low intelligence and poor robustness of traditional navigation systems, the purpose of this paper is to propose a brain-inspired localization method of the unmanned aerial vehicle (UAV).

First, the yaw angle of the UAV is obtained by modeling head direction cells with one-dimension continuous attractor neural network (1 D-CANN) and then inputs into 3D grid cells. After that, the motion information of the UAV is encoded as the firing of 3 D grid cells using 3 D-CANN. Finally, the current position of the UAV can be decoded from the neuron firing through the period-adic method.

Simulation results suggest that continuous yaw and position information can be generated from the conjunctive model of head direction cells and grid cells.

The proposed period-adic cell decoding method can provide a UAV with the 3 D position, which is more intelligent and robust than traditional navigation methods.

The objectives of this study are to assess the utility of the high‐Tc superconductor, yttrium barium copper oxide (YBCO), as a gate material in two‐ and three‐terminal superconductor‐insulator‐semiconductor (SulS) devices, and to study the electrical properties of the insulator and the insulator/Si interface. The YBCO and yttria‐stabilised‐zirconia (YSZ) layers were epitaxially grown on Si by pulsed‐laser deposition. The SulS diodes were fabricated using standard lithographic techniques, with evaporated gold providing the gate and substrate contacts. Electrical characterisation of these superconducting devices is performed using current vs. voltage and capacitance vs. voltage (C‐V) measurements under bias‐temperature cycling. It is found that deposition of thicker YBCO films (≥ 1500 A) minimises the leakage current of the devices, resulting in electrically stable capacitors, especially at superconducting temperatures. A thermally activated process in the temperature range 80–295 K, as determined from flat‐band shifts of C‐V curves, is attributed to trapping/detrapping mechanisms in the SiOx interfacial layer between YSZ and Si. The mobile ions present in YSZ, which affect the room‐temperature C‐V behaviour, give rise to adjustable threshold voltages at superconducting temperatures. These findings will have a significant impact on future transistors using this capacitor as the gate structure.