• The International Journal of Costume Culture
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• v.4 no.3
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• pp.241-248
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• 2001

Re water resistance of shell fabrics intended for we in outdoor apparel was measured using three different standard test methods, ASTM D 751, hydrostatic resistance, procedure A(Mullen test -- with and without a fabric support) and Procedure B (Hydrostatic head test). A database of information on their water resistance performance was created. The data collected with different methods were correlated and the advantages and disadvantages of each method were compared. The Mullen test with a support appears to give higher and more favorable water resistance values on shell fabrics preventing fabric rupture during the test. The hydrostatic head test gave lower hydrostatic pressure values than those measured on the two Mullen tests. The Mullen test is recommended for testing the water resistance of fabrics that high a relatively high water resistance because the Mullen tester applies a wide range of pressure. The hydrostatic head test is recommended for testing the fabrics that have relatively low water resistance. The area of the fabric sample that is in contact with the water is smaller in the Mullen test, so higher pressure levels can be reached and more samples should probably be tested to get a representative value for each fabric types. Furthermore, the hydrostatic head test was deemed more repeatable than the Mullen tests in his study.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.936-943
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• 2002

The Simulated Annealing (SA) algorithm has been successfully applied to various difficult combinatorial optimization problems. Since the performance of a SA algorithm, generally depends on values of the parameters, it is important to select the most appropriate parameter values. In this paper the SA algorithm is optimally designed for performance acceleration, by using the Taguchi method. Several test problems are solved via the SA algorithm optimally designed, and the solutions obtained are compared to solution results McMullen & Frazier(2000). The performance of the SA algorithm is evaluated in terms of solution quality and computation times. Computational results show that the proposed SA algorithm is effective and efficient in finding near-optimal solutions.