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Jacquard pattern optimizing in weft knitted fabrics via interactive genetic algorithm
Dariush Semnani,Mehdi Hadjianfar,Hamed Aziminia,Mohammad Sheikhzadeh 한국의류학회 2014 Fashion and Textiles Vol.1 No.1
A genetic algorithm is a method to respond to troubles that are indissoluble by common methods and must be utilized to try and fault method. It is difficult to appraise all of responses if there are many answers. Algorithm genetic can contain a large vast of responses and find the best of them by receiving feedbacks from problems. Several designs with different colors can be done in weft knitted Jacquard designing system. However, many patterns might not have enough attractiveness and beauty. The choice of interesting and stylish patterns of the huge set of designs according to customer judgment is difficult. An interactive genetic algorithm that received necessary feedbacks from the user, can be used in design optimization and choosing ideal patterns. In this paper a software has been constructed to optimize jacquard pattern in weft knitted fabrics based on interactive genetic algorithm.
Dariush Semnani,Farshad Hassani,Mehdi Hadjianfar,Pedram Rezazadeh Tehrani 한국의류학회 2016 Fashion and Textiles Vol.3 No.1
The aim of the present research is evaluating the impact resistance of weft knitted fabrics which are knitted in basic patterns from the high tenacity Nylon 66. The woven fabrics have been applied for manufacturing technical and ballistic textiles so far. Although woven fabrics have been demonstrated satisfactory tensile properties, but they have not been resisted against impact, because of their poor strain against tensile forces. This research is important because knitted fabrics are applied in wide range of applications including technical textiles such as, package belts, safety belts, ballistic belts, and can be used to remove ice from airplane wings. Various knitted fabrics with different knitting elements such as knit, tuck and miss loops were produced. Mechanical properties including strength, work of the rupture and impact resistance of knitted samples were tested. The artificial neural network was used to predict mechanical properties of fabrics produced from the knitted structure as fitness function in genetic algorithm. After that, genetic algorithm was applied to find the optimum structure of knitted fabric with maximum impact resistance. The results of the genetic algorithm show that optimum structure of the fabric is cross-miss and rib structure with high stitch density.
Sayed Pedram Rezazadeh Tehrani,Mehdi Hadjianfar,Mehran Afrashi,Dariush Semnani 한국의류학회 2018 Fashion and Textiles Vol.5 No.1
Over the last decades by appearing nanotechnology electrospinning has been reconsidered as a significant method. However, electrospinning production rate is limited by the rate at which the polymer solution or melt is fed to a single jet. Feeding rate can be increased through implementing a wide range of methods such as multiple nozzle electrospinning. In the present work, an innovative “quilled” drum with a peculiar design was rotated in a PAN polymer solution in an electrical field to optimize energy consumption, uniform nanofiber distribution on the collector, and increase production rate. The produced nanofibers were compared with those produced from modified multi-nozzle and single-nozzle electrospinning methods. The mean diameters of nanofibers produced from the quilled drum was 32% greater than that of single-nozzle and 28% less than multi-nozzle electrospinning. The CV% of thickness of the webs were 7.9, 11.2, and 12.5% for the quilled, single nozzle and multi-nozzle methods, respectively which showed the presented method produced more uniform webs. The production rate of this electrospinning was 60 and 17 times more than single and multi-nozzle methods, respectively.