{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,26]],"date-time":"2023-12-26T10:56:10Z","timestamp":1703588170940},"reference-count":25,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2007,12,12]],"date-time":"2007-12-12T00:00:00Z","timestamp":1197417600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIEDAM"],"published-print":{"date-parts":[[2008,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A fillet curve is provided at the root of the spur gear tooth, as stresses are high in this portion. The fillet curve may be a trochoid or an arc of suitable size as specified by designer. The fillet stress is influenced by the fillet geometry as well as the number of teeth, modules, and the pressure angle of the gear. Because the relationship is nonlinear and complex, an artificial neural network and a backpropagation algorithm are used in the present work to predict the fillet stresses. Training data are obtained from finite element simulations that are greatly reduced using Taguchi's design of experiments. Each simulation takes around 30\u00a0min. The 4-5-1 network and a sigmoid activation function are chosen. TRAINLM function is used for training the network with a learning rate parameter of 0.01 and a momentum constant of 0.8. The neural network is able to predict the fillet stresses in 0.03 s with reasonable accuracy for spur gears having 25\u2013125 teeth, a 1\u20135\u00a0mm module, a 0.05\u20130.45\u00a0mm fillet radius, and a 15\u00b0\u201325\u00b0 pressure angle.<\/jats:p>","DOI":"10.1017\/s0890060408000036","type":"journal-article","created":{"date-parts":[[2007,12,12]],"date-time":"2007-12-12T09:02:03Z","timestamp":1197450123000},"page":"41-51","source":"Crossref","is-referenced-by-count":1,"title":["Prediction of stress in fillet portion of spur gears using artificial neural networks"],"prefix":"10.1017","volume":"22","author":[{"given":"M.S.","family":"Shunmugam","sequence":"first","affiliation":[]},{"given":"N. Siva","family":"Prasad","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2007,12,12]]},"reference":[{"key":"S0890060408000036_ref23","first-page":"1","volume-title":"Artificial Intelligence (AI) Applied to Gear Technology and Industry in General. 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