İşleme Burulma Yayının Katılığına Ait Parametrelerin Sayısal ve Deneysel Yöntemlerle Belirlenmesi
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Helical Springs are mechanical parts which are frequently used for designing of machines. Conventionally, they are obtained by turning of wire materials Lately, helical machined springs are improved as an alternative to conventional springs. Helical machined springs have higher efficiency and higher inexorability compared to conventional type springs. In terms of pure moment behaviour, the performance of helical springs are high. They have property of simplifying complicated designs as they are a whole with convenient connecting interface. They are used frequently in critical areas; such as Aviation and Aerospace Industry, Defence Industry and Medical Sector; where specific applications are made. Because machined springs appeared latterly, it is seen that knowledge in the literature is poor. Based on from this point, a study has been conducted to determine moment loads of helical machined springs under angular displacement. In order to determine torsional spring constant of helical machined springs, which are used in specific mechanisms for aviation sector, in a rapid and correct way artificial neural network is improved. This master thesis consists of two main parts namely; experimental and numerical studies. In the experimental studies part; with test setup, torsional moments of machined spring test specimen under angular displacement are determined. In the numerical studies part; finite element methods are generated for the test specimens which are used in experimental studies. Result obtained from analysis model are verified with experimental results. Torsional spring constant value obtained from analysis model is converged to torsional spring constant value obtained from experimental results with average 2.125% error. Later, effect intensities on torsional moment of machined spring dimensions which are determined by dimensional parameters are investigated with correlation technique. At the end of this section, effect intensity on torsional spring constant value of parameters such as radial thickness (𝑡�), axial thickness (𝑏�), helix lenght (𝐿�), mean diameter (𝑑�𝑚�), slot diameter (𝑑�𝑟�), gap (𝑝�); which determine machined spring dimensions; are obtained as 𝑡� >𝑏�>𝐿�> 𝑑�𝑚� > 𝑑�𝑟� >𝑝�. In the next section, for 720 different machined springs parametric analysis studies are performed. With using the results obtained from parametric analysis studies, artificial neural network that estimates torsional spring constant is improved.