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Copyright of Journal of Textiles & Engineers / Tekstil ve Mühendis is the property of Union of Chambers of Turkish Engineers & Architects, Chamber of Textile Engineers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, an energy-management strategy based on fuel economy is presented to achieve a further range increase for range-extended light commercial vehicles. Estimation of the energy-management strategy was carried out using a neural-network-based surrogate model for an range-extended vehicle. Surrogate-based optimization plays an important role in optimization problems, which are based on complex structures with uncertainties in data sets due to various conditions. Neural networks have advantages in creating surrogate-based models in cases of complex problems with uncertainties in data sets to evaluate the process and estimate the outputs. This study discusses additional power-unit applications and vehicle integration for a light commercial electric vehicle. It provides preliminary design work and techniques for identifying NVH problems in particular. SIMULINK and neural-network-based surrogate models are established, and the changeable parameters of the vehicle, such as mass, battery/fuel-tank capacity, internal combustion engine power and electric motor power units are simulated in different dynamic and static conditions to determine an energy-management strategy for a range-extended vehicle based on fuel economy under various conditions. It was seen that APU parameters and an energy-management strategy significantly affected the fuel consumption of REX. A neural-network-based surrogate-model approach gave high-precision results in predicting the operating strategy according to different loading conditions to reduce fuel consumption. In some cases, it can be required to determine the fuel consumption results in various conditions with the variables, which may be out-of-boundary conditions. It was seen that the proposed neural-network-model also offers higher prediction ability in cases of unexpected results in data sets of various conditions compared to regression analysis. The results show that estimation and optimization of energy management using a neural-network-based surrogate model can be achieved by adapting the operating strategy according to different loading conditions to reduce fuel consumption. This study presents an approach for future new vehicle projects by transforming a prototype light commercial electric vehicle to REX. The proposed approach was developed to design the most efficient range-extended vehicle by changing all variables without costly computations and time-consuming analysis. It is possible to generate variable data sets and to have reference knowledge for future vehicle projects. [ABSTRACT FROM AUTHOR]

Recycling of materials such as textiles, plastics, glasses, papers and metals instead of storing, burying or burning results a reduction in raw material demands of industry. This means also that a reduction in amount of money, time and energy spent on to obtain raw materials. From this point of view, the main purpose of this study was determined as the production of textile surfaces with high waste fiber content by recycling textile fiber wastes in sizes that cannot be used in the textile manufacturing industry again. In this sense, various composite plates that can be used for sound and heat insulation on the exterior and interior surfaces of the buildings were produced by using unconventional methods from the waste fibers varying in lenghts of 1-25 mm. The effect of changed parameters such as density, fiber type, waste fiber ratio and aluminum foil layer addition were investigated. As a result of the tests, it was observed that the thermal conductivity coefficient values of the all produced composite panels varied between 0.033-0.038 W/mK, and the sound transmission loss values between 24.2-32.6 dB. [ABSTRACT FROM AUTHOR]

In this study, subjective evaluation of towel samples with distinctive fiber contents was investigated. The subjective evaluation questionnaire was performed both by experts with professional experience in the towel sector and by non-experts in this sector. The evaluation was conducted by 30 experts (18 males and 12 females) and 30 non-experts (17 males and 13 females). The experts and non-experts were asked this question: "Could you state parameters that define towel quality with the exception of color and pattern?". Each expert and non-expert had to mention at least 3 parameters. During the evaluation phase, they could visually experienced the color of all towel samples and the information were given about the features like fiber content, yarn count, grammage etc. By touching all samples, towel quality perceptions of the parameters specified for each sample were evaluated subjectively by experts' and non-experts' viewpoint. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Textiles & Engineers / Tekstil ve Mühendis is the property of Union of Chambers of Turkish Engineers & Architects, Chamber of Textile Engineers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Textile & Apparel / Tekstil ve Konfeksiyon is the property of Tekstil ve Konfeksiyon and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Textile & Apparel / Tekstil ve Konfeksiyon is the property of Tekstil ve Konfeksiyon and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Textile & Apparel / Tekstil ve Konfeksiyon is the property of Tekstil ve Konfeksiyon and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Textile & Apparel / Tekstil ve Konfeksiyon is the property of Tekstil ve Konfeksiyon and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)