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The authors consider the problem of optimizing temporary fastener patterns in aircraft assembly. Minimizing the number of fasteners while maintaining final product quality is one of the key enablers for intensifying production in the aerospace industry. The purpose of this study is to formulate the fastener pattern optimization problem and compare different solving approaches on both test benchmarks and rear wing-to-fuselage assembly of an Airbus A350-900.

The first considered algorithm is based on a local exhaustive search. It is proved to be efficient and reliable but requires much computational effort. Secondly, the Mesh Adaptive Direct Search (MADS) implemented in NOMAD software (Nonlinear Optimization by Mesh Adaptive Direct Search) is used to apply the powerful mathematical machinery of surrogate modeling and associated optimization strategy. In addition, another popular optimization algorithm called simulated annealing (SA) was implemented. Since a single fastener pattern must be used for the entire aircraft series, cross-validation of obtained results was applied. The available measured initial gaps from 340 different aircraft of the A350-900 series were used.

The results indicated that SA cannot be applicable as its random character does not provide repeatable results and requires tens of runs for any optimization analysis. Both local variations (LV) method and MADS have proved to be appropriate as they improved the existing fastener pattern for all available gaps. The modification of the MADS' search step was performed to exploit all the information the authors have about the problem.

The paper presents deterministic and probabilistic optimization problem formulations and considers three different approaches for their solution. The existing fastener pattern was improved.

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.

An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine design optimization algorithms which can find optimal designs at a low computational cost.

Several optimization approaches and algorithms are compared and contrasted for the design of DRWTs. More specifically, parametric sweeps, direct optimization using pattern search, surrogate-based optimization (SBO) using approximation-based models and SBO using kriging interpolation models with infill criteria are investigated for the DRWT design problem.

The approaches are applied to two example design cases where the DRWT fluid flow is simulated using the Reynolds-averaged Navier−Stokes (RANS) equations with a two-equation turbulence model on an axisymmetric computational grid. The main rotor geometry is kept fixed and the secondary rotor characteristics, using up to three variables, are optimized. The results show that the automated numerical optimization techniques were able to accurately find the optimal designs at a low cost. In particular, SBO algorithm with infill criteria configured for design space exploitation required the least computational cost. The widely adopted parametric sweep approach required more model evaluations than the optimization algorithms, as well as not being able to accurately find the optimal designs.

For low-dimensional PDE-constrained design of DRWTs, automated optimization algorithms are essential to find accurately and efficiently the optimal designs. More specifically, surrogate-based approaches seem to offer a computationally efficient way of solving such problems.

The aim of this paper is to achieve a reasonable microclimate between clothing and the human body and optimize the custom dress pattern.

An interactive design method of 3D modeling, virtual try-on and heat transfer simulation are used. First, a 3D dress is designed with nonuniform rational B-splines curves and tried on virtually. After that, the heat transfer in the body-air-clothing microclimate and temperature distributions on the clothing surface are obtained. Based on the heat transfer in the body-air-clothing system, we design a method to improve the thermal comfort by optimizing the garment pattern digitally. Then, this paper utilized two heat transfer validating indexes to quantify the improvement of thermal comfort, and evaluate the modified model of dress.

The microclimate under the clothing is varied with the air gap distance, and the heat transfer on the area of the clavicle, bust point and front abandon are higher than other parts due to the narrow air gaps. In view of thermal comfort, the pattern optimization changes the distance ease and reforms the air circulating efficiency. The mean heat transfer and its standard variance are changing by about 10% and more than 20%. Thus, the heat transfer evaluation indexes are suitable to represent the heat transfer and thermal comfort in the microclimate system.

It can be concluded that the methodology proposed in this paper has the advantage of interactive design, 3D visualization and local heat transfer simulation. This technology meets the need of personalized customization and well-considered garment and has broad application prospects.

This study demonstrates that modifying the distance ease on body key girths based on heat transfer is a reliable way to improve thermal comfort. This method meets the consumers’ demand of the comfort of body-fit clothing under the condition of daily activities.

• 3D air gap distributions.

• Heat transfer varies with air gap distance.

• Thermal comfort can be improved by optimizing garment pattern.

3D air gap distributions.

Heat transfer varies with air gap distance.

Thermal comfort can be improved by optimizing garment pattern.

This paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations.

The authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals.

The study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou.

The authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area.

The authors propose a zoning method based on the optimization of land use towards low-carbon development by combining “top-down” and “bottom-up” strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the “double carbon” target in urban agglomerations in China.

The purpose of this paper is to present a method of digital twins of female bodies and the optimization of wetsuit patterns with the help of virtual technologies.

First, the new anthropometrical grouping of female torsos has been developed with 3D body scanning technology. Second, soft tissue deformation under the influence of typical diving postures and hydraulic pressure has been explored. Through real experiments, the relationship between textile material strain and body measurement changing has been applied to establish deformed digital twins of female bodies. Finally, during the evaluation of the virtual wetsuit test on digital twins through material strain and pressure values in CLO 3D, the optimized pattern of the wetsuit has been designed.

The experimental results show that the digital twins based on real data transformation are feasible and practical, and the process of establishing digital twins with 3D body scanning technology is valid and accurate.

The researches on the wetsuit of structure and body dynamic measurements still have many gaps existing in the real and virtual experiments. Thus the manuscript addresses these issues and provides the deformed digital twin for wetsuit pattern design for the first time. This study can be used for designing and optimizing the wetsuit and further improving the efficiency of manufacture and evaluation.

Considering two-dimensional features in the body shape classification system cannot fully reflect the three-dimensional (3D) morphological characteristics of human body. The purpose of this paper is to propose a 3D feature based method to characterize and classify the upper body shape of women, and then obtained the corresponding garment block and improved the fitness of clothing.

In this study, the [TC]² 3D scanner was used to obtain human data, and 15 layers of cross-sections of young females’ upper body were extracted. In total, 240 space vectors were obtained with the center of the bust cross-section as the original point. By using the principal component analysis and K-means clustering analysis, the body shape classification based on the space vectors length was realized. The garment block corresponding to three body types was obtained using the 3D scanning data and the cross-section convex hull, and compared with existing garment block and evaluated fitness of the blocks.

In total, 11 main components used to characterize the 3D morphological features of young women were obtained, which could explain 95.28 percent features of young women’s upper body. By cluster analysis, the body shape of women was divided into three categories. The block of three body types was obtained by the construction of the convex hull model.

This paper investigates a classification method of the body shape based on space vector length, which can effectively reflect the difference of surface shape of human body and further improve the matching degree of human body and clothing.

The purpose of this study is to find a new design that can increase the sensitivity of the sensor without sacrificing the linearity. A novel and very efficient method for increasing the sensitivity of MEMS pressure sensor has been proposed for the first time. Rather than perforation, we propose patterned thinning of the diaphragm so that specific regions on it are thinner. This method allows the diaphragm to deflect more in response with regard to the pressure. The best excavation depth has been calculated and a pressure sensor with an optimal pattern for thinned regions has been designed. Compared to the perforated diaphragm with the same pattern, larger output voltage is achieved for the proposed sensor. Unlike the perforations that have to be near the edges of the diaphragm, it is possible for the thin regions to be placed around the center of the diaphragm. This significantly increases the sensitivity of the sensor. In our designation, we have reached a 60 per cent thinning (of the diaphragm area) while perforations larger than 40 per cent degrade the operation of the sensor. The proposed method is applicable to other MEMS sensors and actuators and improves their ultimate performance.

Instead of perforating the diaphragm, we propose a patterned thinning scheme which improves the sensor performance.

By using thinned regions on the diaphragm rather than perforations, the sensitivity of the sensor was improved. The simulation results show that the proposed design provides larger membrane deflections and higher output voltages compared to the pressure sensors with a normal or perforated diaphragm.

The proposed MEMS piezoelectric pressure sensor for the first time takes advantage of thinned diaphragm with optimum pattern of thinned regions, larger outputs and larger sensitivity compared with the simple or perforated diaphragm pressure sensors.

The purpose of this paper investigates dynamic ease distributions of clothes at bust and waist lines with different body surface angle by using a Qualisys three-dimensional motion capture system (3DMCS).

The current method first obtain the specific markers of participants and their clothes along the bust and waist lines through 3DMCS, then using the least square method and four piecewise polynomial fitting participants and their clothes' bust and waist curves. The coordinates of the markers were tracked by the 3DMCS, while the participants under different body surface angle walked on a treadmill calculated the distances of markers coordinates to the participants' bust and waist curves. Finally, the data of samples were analyzed. It was found that the dynamic ease distributions showed different patterns at different body surface angle.

The results revealed the bust convex angle is 26.53 degrees (Specification:X3) and back slope angle is 13.96 degrees (Specification: Y1), the fluctuation of participant ease distributions on bust section was most obvious, and the maximum fluctuation value was ±20 mm and ±25 mm. The ease distributions of participant waist section fluctuated most obviously when the bust convex angle is 28.10 degrees (Specification: X5) and the back slope angle is 13.96 degrees (Specification: Y1), and the maximum fluctuation was ±30 mm and ±20 mm. The bust convex angle has the greatest influence on 1# garment, and the back slope angle has the greatest influence on 2# garment.

Currently, there is little information in the literature about dynamic ease distributions of garment on a different body types. This paper takes different body surface angles as the research objects to analyze the ease distributions of different clothes, the conclusion can provide reference data for 3D garment modeling and improve the authenticity of virtual garment fitting.

The inbound event tourists drawn to an Australian destination to participate in one of 14 annual international auto racing (AR) events can be sectioned to release each group’s behavioural perspectives around their tourism-related impacts on the destination. The paper aims to discuss these issues.

Inbound event tourists attending the destination are surveyed during the three-day major event. Each respondent displays non-uniform, personally driven agendas and varying degrees of local tourism acceptance.

Inbound event tourists self-select into one of six psychologically framed AR sport groupings, and exhibit micro-differences that can then be used to align local tourism around future.

The authors do not consider locals attending this international series AR event, but project their destination tourism and event impacts to be less than those of inbound event tourists. Totally, 90 per cent of inbound AR event tourists each fit one of six motive groups and each group exhibits behaviours, decision-making and spending patterns which can be later optimized in preparation for the destination’s next major event.

AR attendees self-select into just one behavioural attendance motive. Group approaches unlock new understanding of event attendees and their behaviours. Inbound event tourists spend 2 to 1 on the destination’s tourism vs its major event. Destinations targeting inbound event tourists should grow their spend ratio by bundling local tourism offerings into short length-of-stay requirements offering conservatively priced (under $100/activity), adventure focused, tourism options.

This study links inbound event tourist groupings; acquisitions; stay patterns and spending. It captures the economic components and their relative impact on the destination. By combining all the sub-groups of inbound (and local) AR event attendees, a better representation of their economic impact on the destination can be determined.