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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 propose a structural sizing approach of an unmanned aerial vehicle (UAV) wing that takes into account the aeroelasticity effects through a fluid–structure interaction analysis.

The sizing approach proposed in this study is an iterative process, each iteration of which consists of two sub-loops, a multidisciplinary analysis (MDA) loop followed by a structural optimization loop. The MDA loop seeks the aeroelastic equilibrium between aerodynamic forces and structural displacements using a fixed-point iteration scheme. Once the equilibrium is reached, the converged pressure loads are used for the structural optimization, which aims to find the structural thicknesses that minimize the wing weight under failure criteria. The two sub-loops are run sequentially in an iterative process until the mass is converged. The analysis models are implemented in open-source software, namely, PANUKL for aerodynamics and MYSTRAN for structures, while the whole process is automated with Python and integrated in the open-source optimization framework OpenMDAO.

The approach was applied to the design of the Predator MQ-1 wing. The results of the MDAs show the convergence of the wing deformations to the flight shape after few iterations. At the end of the aeroelastic sizing loop, the result is a structurally sized wing with minimal weight considering the aeroelasticity effects.

The approach proposed takes into account the wing aero-structural coupling effects while sizing its structure instead of a fixed load distribution. In addition, the approach is fully based on open-source codes, which are freely available for public use and can be fully reproducible.

While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains.

To handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm.

The initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability.

In this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.

The purpose of this study is to introduce a dedicated simulator to automatically generate and simulate a balanced apparel assembly line, which is critical to the digital twin concept in apparel manufacturing. Given the low automation level in apparel manufacturing, this is a first step toward the implementation of a smart factory based on cyber-physical systems.

The mixed task assignment algorithm was implemented to automatically generate a module-based apparel assembly line in the developed simulator. To validate the developed simulator, a case study was conducted using process analysis data of technical jackets obtained from an apparel manufacturer. The case study included three scenarios: calculating the number of workers, selecting orders based on factory capacity and managing unexpected worker absences.

The developed simulator is approximately 97.2% accurate in assigning appropriate tasks to workstations using the mixed task assignment algorithm. The simulator was also found to be effective in supporting decision-making for production planning, order selection and apparel assembly line management. In addition, the module-based line generation algorithm made it easy to modify the assembly line.

This study contributes a novel approach to address the challenge of low automation levels in apparel manufacturing by introducing a dedicated simulator. This dedicated simulator improves the efficiency of virtual apparel assembly line generation and simulation, which distinguishes it from existing commercial simulation software.

The purpose of this study is to evaluate the effectiveness of nanocontainer solutions in removing deteriorated and aged polymers commonly used in coating and consolidating archaeological glass.

This study focused on characterizing glass surfaces coated with two commonly used polymeric materials in archaeological glass preservation. Furthermore, the study evaluates the elimination of these coatings from the surfaces by using innovative aqueous systems composed of micellar solutions (MS) and oil-in-water (O/W) Texapon-P microemulsions (TEX). Glass samples coated with selected polymers were subjected to thermal and photochemical aging to simulate natural degradation conditions. This study aimed to evaluate the effectiveness of nanocontainer aqueous systems compared to acetone (Ac), a conventional solvent commonly used for removal procedures. The characterization procedures involved transmission electron microscopy, USB digital microscopy, scanning electron microscopy, color alteration and gravimetric measurement.

The findings indicate that the effectiveness of novel techniques using aqueous nanocontainer systems is quite promising when considering a “green approach” to preserving cultural heritage. Microscopic examination demonstrated the efficacy of MS in effectively removing acrylic and vinyl polymers from the glass surface. Furthermore, TEX proved effective in removing polyvinyl acetate (PVA) over Paraloid B72 (B-72). In addition, the measurement of color alteration values revealed a decrease after using MS compared to the standard sample before applying the polymers, with values of ΔE = 1.48 and 1.82 for B-72 polymer and PVA, respectively.

This research provides nanocontainer solutions for removing aged polymers from the glass surface. This makes the current study a promising step for treating archaeological glass.

Nowadays, thermal comfort plays a prominent role in contemporary construction practices. Appropriate thermal insulation not only offers energy efficiency benefits in buildings but also enhances occupant well-being, comfort, and productivity. Therefore, a comprehensive understanding of the thermal properties of building materials is essential. This research aims to prepare and investigate a lightweight gypsum-based composite incorporating nano montmorillonite with advanced thermal insulation properties, considering both quality and cost-effectiveness while ensuring environmental compatibility.

This study adopts a laboratory experimental approach. A gypsum sample (without additives) and seven samples of gypsum combined with varying percentages of sodium and calcium montmorillonite nanoclays undergo extensive testing and analysis. Subsequently, the properties of these samples are compared.

The results indicate that adding montmorillonite nanoclays to gypsum composites reduces the density of the tested samples and increases their porosity. Moreover, the thermal conductivity coefficient decreases in these samples, significantly improving the thermal insulation properties of the lightweight gypsum plaster. This improvement is more pronounced in samples containing sodium montmorillonite nanoclay compared to calcium-based samples. Additionally, the investigations reveal that compressive strength decreases with the addition of montmorillonite to the samples.

In this research, laboratory experiments were conducted to investigate the physical and mechanical properties of gypsum plaster with varying percentages of sodium and calcium montmorillonite nanoclays. The studied properties include density, porosity, thermal conductivity coefficient, and compressive strength. Additionally, stress-strain diagrams, elastic modulus, and initial and secondary critical stresses were analyzed for each specimen.