Search results

Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This study aims to offer a comparative evaluation of GSCA and PLSPM in a predictive modeling framework.

A simulation study compares the predictive performance of GSCA and PLSPM under various simulation conditions and different prediction types of correctly specified and misspecified models.

The results suggest that GSCA with reflective composite indicators (GSCA_R) is the most versatile approach. For observed prediction, which uses the component scores to generate prediction for the indicators, GSCA_R performs slightly better than PLSPM with mode A. For operative prediction, which considers all parameter estimates to generate predictions, both methods perform equally well. GSCA with formative composite indicators and PLSPM with mode B generally lag behind the other methods.

Future research may further assess the methods’ prediction precision, considering more experimental factors with a wider range of levels, including more extreme ones.

When prediction is the primary study aim, researchers should generally revert to GSCA_R, considering its performance for observed and operative prediction together.

This research is the first to compare the relative efficacy of GSCA and PLSPM in terms of predictive power.

The purpose of this paper is to find the pattern with minimal deformation energy while developing from 3D designed garments. Moreover, darts are generated to further reduce deformation energy. The aims of the energy-based flattening method are to reduce the difference between 3D designed garments and 2D flattened patterns in an accurate and efficient way.

This study uses a mass spring method and iterative optimization to analyze pattern contours with minimal contour deformation while flattening three dimensional draping designs into a plane. Darts are generated to further reduce distortion during surface flattening and the energy method is introduced to verify that the analysis results obtained match the garment darts provided by the Bunka formula which is currently widely used in East Asia.

An efficient method for generating optimal darted pattern is presented. It compares the important factors of darts, including position, length and amount. After iterative optimization and darts generation, the maximum energy reduction is about 30 percent.

This study provides an aggregate to analyze and compare the differences between different patterns and conduct a verification comparison with traditional pattern formula.

This paper attempts to deal with the presentation of a numerical investigation of the laminar‐free convective heat transfer in a square enclosure containing a solid cylinder located at an arbitrary position. Effects of the cylinder position on the heat transfer and the flow structures inside the cavity are to be studied and highlighted.

The numerical code is based on the hybrid scheme with the lattice Boltzmann and the alternating‐directional implicit (ADI) splitting scheme. The energy equation is solved by ADI scheme and the flow field velocities have been computed using the lattice Boltzmann method (LBM). The bounce‐back condition combined with quadratic interpolation is used at solid boundaries.

The predicted results show that the cylinder location has a significant effect on the heat transfer. It is observed that: when the inner body does not generate heat, most of the heat transfer takes place if the body is located at the center of the enclosure. When the cylinder generates heat and is displaced from the left towards the right and from the lower part towards the upper part of the cavity, the heat transfer rate decreases on the hot wall and increases on the cold wall.

The fluid flow (air) is assumed to be incompressible, laminar and 2D. The viscous heat dissipation is neglected in the energy equation and all physical proprieties are constant except for the density, whose variation with temperature is allowed for in the buoyancy term.

Natural convection in heated enclosures, housing inner bodies has received significant attention because of its interest and importance in industrial applications. Some applications are solar collectors, fire research, electronic cooling, aeronautics, chemical apparatus, building constructions, nuclear engineering, etc.

The paper contributes to the development of the LBM. In particular, it was found that the inherent numerical instabilities of this LBE are not modified by coupling with temperature. This is a good improvement compared to what is observed in the simulations of thermal systems using the full LBE formulation where the energy conservation is taken into account.

In order to more accurately predict the dynamics of the e-commerce market and increase the comprehensive value of the circular e-commerce industry, proposes to use Grey system theory to analyze the circular economy of the e-commerce market.

Construct a Grey system theory model, analyze the big data of e-commerce and circular economy of the e-commerce market and predict the development potential of China's e-commerce market.

The results show that the Grey system theory model can play an important role in the data analysis of circular economy of the e-commerce market.

Use Grey model to analyze e-commerce data, discover e-commerce market rules and problems and then optimize e-commerce market.

The purpose of this paper is to propose a methodology that determines vehicle-level specifications for new-car program by balancing market environments and engineering feasibility in the early stages of the vehicle development processes using statistical analysis of historical data.

The proposed methodology effectively captures the interplay among key factors in preliminary vehicle planning: engineering feasibility constraints, market demands, and economic conditions. Engineering design constraints, derived by statistical analysis of historical data, define the strategic feasible space. Within the defined design space, the methodology determines a set of specifications that maximize the customer utility which is built as a function of preferences on each attribute of a vehicle.

The present paper develops an “extrapolation” approach using historical vehicle data, rather than attempt to model a complex system with limited information. In doing so, the proposed approach avoids the difficulties of understanding an entire complex system by determining only the moderate level of specifications. Moreover, its quantification of revealed customer preferences as expressed in sales data resolves the confusions in vehicle planning arising from the translation of customer requirements to engineering specification.

The proposed methodology can provide feasible prediction values with a new, historical-data-based statistical approach that effectively surmounts the difficulty of mechanically understanding complex systems. Moreover, through quantification of the target market's customer requirements as well as effects of market-environmental changes, the methodology enables designers to plan complex products for new concept in objective and reasonable manner.

The purpose of this paper is to numerically examine the conjugate natural convection in an inclined enclosure with a conducting centred block. This enclosure is filled with an Ethylene Glycol‐copper nanofluid. This study utilises numerical simulations to quantify the effects of pertinent parameters such as the Rayleigh number, the solid volume fraction, the length and the thermal conductivity of the centred block and the inclination angle of the enclosure on the conjugate natural convection characteristics.

The SIMPLE algorithm is utilised to solve the governing equations with the corresponding boundary conditions. The convection‐diffusion terms are discretised by a power‐law scheme and the system is numerically modelled in FORTRAN.

The results show that the utilisation of the nanofluid enhances the thermal performance of the enclosure and that the length of the centred block affects the heat transfer rate. The results also show that the higher block thermal conductivity results in a better heat transfer that is most noticeable at low Rayleigh numbers, and that increasing the inclination angle improves the heat transfer, especially at high Rayleigh numbers.

This paper presents an original research on conjugate natural convection in nanofluid‐filled enclosures.

The purpose of this paper is to investigate electrokinetic and mixed convection (pressure gradient and buoyancy) effects on reverse flow formation at the channel walls.

The electrical potential distribution was modelled using the Poisson–Boltzmann equation while the governing momentum and energy equations are modelled from the Navier–Stokes equations and solved exactly.

It is found that flow reversal at the walls is enhanced by electrokinetic parameter whereas increasing degree of asymmetric parameter up to symmetric heating eliminates reverse flow formation at the walls no matter the electric charge distribution.

The results of this paper indicate that degree of asymmetric heating, mixed convection parameter and electrokinetic parameter regulate fluid velocity, rate of heat transfer, skin friction and reverse flow formation at the walls.

A computer model based on the fractional step method is presented for modelling density coupled mass transport in groundwater. Although several models utilising the fractional step method had been developed previously, all were based on the Eulerian solution approach. The model developed by the authors uses the Langrangian approach which has some inherent advantages and disadvantages. The problems associated with the implementation of the fractional step method and techniques by which they were overcome are discussed. The performance of the model is examined and results obtained for standard problems are compared with those from other computer packages.