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The purpose of this paper is to identify the strengths and weaknesses associated with physical and virtual prototyping and propose an approach that utilises a real‐time integration of both methods through an automated process.

Following a literature review, the paper presents the results of a survey investigating the current use of prototyping. It then discusses a series of trials that were developed for the proposed tool.

Physical and virtual prototypes are not competitive but rather complementary. An integrated real‐time system would reduce cost and shorten the product design process.

This paper provides recommendations on how real‐time integration of both physical and virtual prototypes could potentially streamline the new product development process.

Corrosion is one of the common damage mechanisms in many engineering structures such as marine structures, petroleum pipelines, aerospace and nuclear reactor. However, the service performance of metal materials and structures is gradually degenerating with the increase of service life due to the rapid growth of corrosion damages. Thus, the coupled effects for corrosion damage in reliability analysis should be considered urgently. Then, the purpose of this paper is to develop the corrosion damage physical model and the corresponding reliability analysis methods, which consider the coupled effect of corrosion damage.

A failure physical model, considering the coupled effect of pitting growth, crack and crack propagation, is presented in this paper. Sequentially, the corrosion reliability with respect to pitting physical damage can be investigated. The presented pitting damage physical model is formulated as time-variant performance limit state functions, which include the crack transition, crack growth and fracture failure mechanics. The first-passage failure criterion is used to construct the corrosion reliability framework, involving in the pitting damage model with the increase of service life.

Results demonstrate that the multiplicative dimensional reduction (MDR) method behaves much better than FORM no matter in accuracy or efficiency. The proposed corrosion reliability method is applicable for dealing with the damage failure model of the structural pitting corrosion.

The MDR method is used to calculate the corrosion reliability index of a given structure with fewer function calls. Finally, an aeronautical metal material is used to demonstrate the efficiency and precision of the proposed corrosion reliability method when the failure physical model considering the coupled effects of mechanical stresses and corrosion environment is adopted.

This paper aims to study, experimentally validate and select the main physical and numerical parameters of influence in computational numerical simulations to evaluate mean heat flux by natural convection on square flat plates.

Several numerical models were built to study the influence of physical and numerical parameters about the predictions of the natural convection heat transfer rates on the surface of a flat plate with aspect ratio = 1, in isothermal conditions, turbulent regime and using the free and open-source software OpenFOAM®. The studied parameters were: boundary conditions (using or not using wall functions in properties ε, κ, ν_t and ω), degree of mesh refinement, refinement layers and turbulence models [κ – ε and κ – ω Shear Stress Transport (SST)]. From the comparison of the values of the mean Nusselt number, obtained from numerical simulations and literature experimental results, the authors evaluated the precision of the studied parameters, validating and selecting the most appropriate to the analyzed problem situation.

The validation and agreement of the numerical results could be proven with excellent precision from experimental references of the technical scientific literature. More refined meshes with refinement layers were not suitable for the studies developed. The κ – ε and κ – ω SST turbulence models, in meshes without refinement layers, proved to be equivalent. Whether or not to use wall functions in turbulent boundary conditions proved to be irrelevant as to the accuracy of results for the problem situation studied.

Use of the physical and numerical parameters is studied and validated for various applications in natural convection heat transfer of technology and industry areas.

Use of free and open-source software as a research tool in the Computational Fluid Dynamics (CFD) area, especially in conditions without large financial resources or state-of-the-art infrastructure.

To the best of the authors’ knowledge, this work is yet not available in existing literature.

We extend the Jones (1971) analysis of the effects of distortions in 2×2 trade models to the case of a two-sector dynamic general equilibrium model of a small open economy with capital accumulation. We do a comparative steady state analysis for the effect of policy changes on factor prices and the capital stock, and examine the dynamics of the system in the neighborhood of the steady state. We also show that the system will have multiple equilibria when value and physical factor intensity rankings of the sectors do not agree.

Recent research supports the role of productive government spending as an important determinant of economic growth. Previous analyses have focused on the separate effects of public investment in infrastructure and on investment in education. This paper aims to introduce both types of public investment simultaneously, enabling the authors to address the trade‐offs that resource constraints may impose on their choice.

The authors employ a two‐sector endogenous growth model, with physical and human capital. Physical capital is produced in the final output sector, using human capital, physical capital, and government spending on infrastructure. Human capital is produced in the education sector using human capital, physical capital, and government spending on public education. The introduction of productive government spending in both sectors yields an important structural difference from the traditional two‐sector growth models in that the relative price of human to physical capital dynamics does not evolve independently of the quantity dynamics.

The model yields both a long‐run growth‐maximizing and welfare‐maximizing expenditure rate and allocation of expenditure on productive capital. The welfare‐maximizing rate of expenditure is less than the growth‐maximizing rate, with the opposite being the case with regard to their allocation. Moreover, the growth‐maximizing value of the expenditure rate is independent of the composition of government spending, and vice versa. Because of the complexity of the model, the analysis of its dynamics requires the use of numerical simulations the specific shocks analyzed being productivity increases. During the transition, the growth rates of the two forms of capital approach their common equilibrium from opposite directions, this depending upon both the sector in which the shock occurs and the relative sectoral capital intensities.

These findings confirm that the form in which the government carries out its productive expenditures is important. The authors have retained the simpler, but widely employed, assumption that government expenditure influences private productivity as a flow. But given the importance of public investment suggests that extending this analysis to focus on public capital would be useful.

Two‐sector models of economic growth have proven to be a powerful tool for analyzing a wide range of issues in economic growth. The originality of this paper is to consider the relative impact of government spending on infrastructure and government spending on human capital and the trade‐offs that they entail, both in the long run and over time.

Today, medical models can be made by the use of medical imaging systems through modern image processing methods and rapid prototyping (RP) technology. In ultrasound imaging systems, as images are not layered and are of lower quality as compared to those of computerized tomography (CT) and magnetic resonance imaging (MRI), the process for making physical models requires a series of intermediate processes and it is a challenge to fabricate a model using ultrasound images due to the inherent limitations of the ultrasound imaging process. The purpose of this paper is to make high quality, physical models from medical ultrasound images by combining modern image processing methods and RP technology.

A novel and effective semi‐automatic method was developed to improve the quality of 2D image segmentation process. In this new method, a partial histogram of 2D images was used and ideal boundaries were obtained. A 3D model was achieved using the exact boundaries and then the 3D model was converted into the stereolithography (STL) format, suitable for RP fabrication. As a case study, the foetus was chosen for this application since ultrasonic imaging is commonly used for foetus imaging so as not to harm the baby. Finally, the 3D Printing (3DP) and PolyJet processes, two types of RP technique, were used to fabricate the 3D physical models.

The physical models made in this way proved to have sufficient quality and shortened the process time considerably.

It is still a challenge to fabricate an exact physical model using ultrasound images. Current commercial histogram‐based segmentation method is time‐consuming and results in a less than optimum 3D model quality. In this research work, a novel and effective semi‐automatic method was developed to select the threshold optimum value easily.

The purpose of this paper is to propose a comprehensive framework for integrating big data analytics (BDA) into cyber-physical system (CPS) solutions. This framework provides a wide range of functions, including data collection, smart data preprocessing, smart data mining and smart data visualization.

The architecture of CPS was designed with cyber layer, physical layer and communication layer from the perspective of big data processing. The BDA model was integrated into a CPS that enables managers to make sound decisions.

The effectiveness of the proposed BDA model has been demonstrated by two practical cases − the prediction of energy output of the power grid and the estimate of the remaining useful life of the aero-engine. The method can be used to control the power supply system and help engineers to maintain or replace the aero-engine to maintain the safety of the aircraft.

The communication layer, which connects the cyber layer and physical layer, was designed in CPS. From the communication layer, the redundant raw data can be converted into smart data. All the necessary functions of data collection, data preprocessing, data storage, data mining and data visualization can be effectively integrated into the BDA model for CPS applications. These findings show that the proposed BDA model in CPS can be used in different environments and applications.

As the physical dimensions of the devices are reduced to the submicrometer regime, the hot‐carrier reliability has become an important issue in the scaling of the p‐MOSFET as well as the n‐MOSFET. In this paper, we present a unified approach for p‐MOSFET degradation due to the trapping of the hot electrons in the gate oxide layers. A physical analytical model, based on the pseudo two‐dimensional model, is derived for the first time to describe the linear and saturation drain current degradation. The model has been verified by comparing the calculation and the measurement from submicron p‐MOSFET's with different channel lengths and oxide thickness. There are no empirical parameters in the model. Two physical parameters: the capture cross section and the density of states of electron traps, which can be determined independently from the measured degradation characteristics, are valid for both the linear current and the saturation current degradation. The simple expression is very suitable for the predicting of the circuit reliability.

In recent years it has been often claimed that quality is one of most critical success factors for organizations. Managers introduced quality‐based programmes – such as total quality management – assuming that performances would improve. However, many quality‐based initiatives failed. There are several reasons that could explain the failure of quality‐based strategies in a number of firms; suggests two causes: the lack of effective decisional tools for evaluating the most effective investment(s) among a set of potential programmes; and the lack of specific goals to be assigned to each investment in order to monitor the actual results of the programmes on time. In small firms these problems are greater because of the limited availability of financial and managerial resources which make more difficult the identification of the most effective decisional solutions. Identifies a conceptual framework aimed at supporting the choice of most effective models for evaluating quality‐related investments in small firms, particularly an approach which balances different decisional needs such as completeness, urgency of evaluation, measurability of output and structural characteristics.

Owing to the excellent performance, giant magnetostrictive materials (GMMs) are widely used in many engineering fields. The dynamic Jiles–Atherton (J-A) model, derived from physical mechanism, is often used to describe the hysteresis characteristics of GMM. However, this model, despite cited by many different literature studies, seems not to possess unique expressions, which may cause great trouble to the subsequent application. This paper aims to provide the rational expressions of the dynamic J-A model and propose a numerical computation scheme to obtain the model results with high accuracy and fast speed.

This paper analyzes different published papers and provides a reasonable form of the dynamic J-A model based on functional properties and physical explanations. Then, a numerical computation scheme, combining the Newton method and the explicit Adams method, is designed to solve the modified model. In addition, the error source and transmission path of the numerical solution are investigated, and the influence of model parameters on the calculation error is explored. Finally, some attempts are made to study the influence of numerical scheme parameters on the accuracy and time of the computation process. Subsequently, an optimization procedure is proposed.

A rational form of the dynamic J-A model is concluded in this paper. Using the proposed numerical calculation scheme, the maximum calculation error, while computing the modified model, can remain below 2 A/m under different model parameter combinations, and the computation time is always less than 0.5 s. After optimization, the calculation speed can be enhanced with the computation accuracy guaranteed.

To the best of the authors’ knowledge, this paper is the first one trying to provide a rational form of the dynamic J-A model among different citations. No other research studies focus on designing a detailed computation scheme targeting the fast and accurate calculation of this model as well. And the performance of the proposed calculation method is validated in different conditions.