A New Method for Measuring Water Vapour Transfers Through Fabrics

Marolleau, A; Salaün, Fabien; Dupont, Daniel; Gidik, Hayriye; Ducept, S

doi:10.1007/s12221-020-8996-7

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…In addition, combined with related research, 41–44,48,50 parameters after dimension reduction mainly include motion state indexes (standing, squatting down, jogging, resting), thermal and moisture indexes (fabric structure, gram weight, horizontal density, maximum wetting radius, evaporation rate, moisture resistance, thermal resistance, liquid water diffusion rate, moisture regain), pressure indexes (static drape coefficient, shear stiffness (horizontal), longitudinal stress, tensile elasticity (longitudinal), bending stiffness (longitudinal)), and tactile indexes (average friction coefficient, contact cold and warm feeling, surface roughness).…”

Section: Methodsmentioning

confidence: 93%

“…Through a summary of some relevant literature, 41–52 the main factors affecting wearing comfort are the fabric composition, fabric structure, average friction coefficient, surface roughness/μm, bending stiffness (horizontal)/gf · cm 2 · cm −1 , bending stiffness (longitudinal)/gf · cm 2 · cm −1 , tensile elasticity (horizontal)/%, tensile elasticity (longitudinal)/%, gram weight/g · m −2 , longitudinal density/number of coils · 5 cm −2 , horizontal density/count · 5 cm −2 , thickness/mm, contact cold and warm feeling/w · cm −2 , air permeability/l · m −2 · s −1 , moisture regain/%, moisture permeability/g/(m 2 · h), moisture resistance/Pa · m 2 · W −1 , thermal resistance/°C · m 2 · W −1 , heat preservation rate/%, heat transfer coefficient/W · m −2 · K −1 , longitudinal stress/cN · cm −1 , transverse stress/cN · cm −1 , static drape coefficient/%, compression recovery rate/%, wicking height/cm/30 min, shear stiffness (transverse)/gf/cm · degree, shear stiffness (longitudinal)/gf/cm · degree, evaporation rate/g · h −1 , liquid water diffusion rate/mm · s −1 , and maximum wetting radius/mm, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Motion comfort analysis of tight-fitting sportswear from multi-dimensions using intelligence systems

Cheng

Wang

Zeng

et al. 2022

Textile Research Journal

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Focusing on the “human–sport-clothing” system, this paper analyzed the influence of combinations of different tights and sport states on human body parts and overall body comfort from multiple dimensions. However, the motion state and some fabric parameters are non-numerical parameters, which could not be used for model analysis directly. In addition, there are too many numerical fabric parameters whose relationships are complicated, and it is difficult for general models to deal with these relationships, resulting in low accuracy of the comfort prediction model. Moreover, when using the artificial neural network to study comfort, it has some difficulties in expressing comfort and low prediction accuracy. To solve these problems, One-Hot was used to encode non-numerical parameters, and then intelligent algorithms were adopted to deal with these complex fabric parameters. Finally, a comfort prediction model was established in combination with an adaptive fuzzy reasoning system. The results showed that different fabric combinations and motion states had significant effects on local comfort (comfort of specific human body parts) and global comfort (whole body comfort). Moreover, the prediction model with non-numerical parameters has higher accuracy than the model without non-numerical parameters, which indicated that the prediction accuracy of the model had been improved after the introduction of One-Hot coding, so the non-numerical parameters cannot be ignored. The particle swarm optimization algorithm-cuckoo search algorithm-adaptive network-based fuzzy inference system hybrid model was superior to the particle swarm optimization algorithm-adaptive network-based fuzzy inference system and cuckoo search algorithm-adaptive network-based fuzzy inference system model in predicting local comfort and global comfort.

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Section: Methodsmentioning

confidence: 93%

Section: Methodsmentioning

confidence: 99%

Motion comfort analysis of tight-fitting sportswear from multi-dimensions using intelligence systems

Cheng

Wang

Zeng

et al. 2022

Textile Research Journal

View full text Add to dashboard Cite

show abstract

“…Moisture regain indicates moisture containment in the form of water vapor, which can be affected by the chemical composition of fibers. 28 Specimens composed of cellulose fibers, such as cotton and rayon, had high moisture regain due to the hydrophilic functional groups in their chemical structure. In contrast, synthetic fibers, including polyester, nylon, and acryl, had low moisture regain since they lack hydrophilic functional groups, attracting less moisture.…”

Section: Evaluation Of Fabric Propertiesmentioning

confidence: 99%

Effect of fabric properties on the laundry movement, mechanical action, and motor current of front-loading washers

Song,

Kim,

Chang

et al. 2023

Textile Research Journal

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Laundering is essential for maintaining personal hygiene but can lead to fabric damage, such as color fading and fiber loss, caused by frequent and excessive mechanical action. Front-loading washers utilize mechanical force such as falling, rotating, and sliding to remove soil from textiles, where fabric properties influence these movements, resulting in varied mechanical actions depending on fabric type. Herein, the relationship between fabric properties and movement pertaining to mechanical action was analyzed, focusing on correlated fabric movements and motor torque current parameters. The results demonstrate that fabric properties, such as wet friction, moisture regain, thickness, and stiffness, significantly influence fabric movement in laundering. Moisture regain was associated with fabric movement, causing hydrophilic fabrics to undergo concentrated and repeated movements, resulting in higher rates of thread removal. In addition, heavier, thicker, and stiffer fabrics displayed dynamic changes in fabric shape, contributing to increased Poka-Dot removal. The motor current data required for rotating the drum was analyzed in association with the fabric properties. Using the current parameters as internal nodes of a decision tree model, fabric types were successfully classified. The results imply that the real-time current data and laundry movement information can be utilized for optimizing washing technologies for different fabric types, ultimately maximizing washing efficiency and minimizing fabric damage.

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Combination of a simplified one-dimensional human thermoregulatory model with the water circulation temperature control and RO membrane sweating systems in the thermal manikin

Nie

Tian²,

Xue³

et al. 2023

International Journal of Thermal Sciences

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A New Method for Measuring Water Vapour Transfers Through Fabrics

Cited by 4 publications

References 22 publications

Motion comfort analysis of tight-fitting sportswear from multi-dimensions using intelligence systems

Motion comfort analysis of tight-fitting sportswear from multi-dimensions using intelligence systems

Effect of fabric properties on the laundry movement, mechanical action, and motor current of front-loading washers

Combination of a simplified one-dimensional human thermoregulatory model with the water circulation temperature control and RO membrane sweating systems in the thermal manikin

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