Titlebook: Materials Design and Applications II; Lucas F. M. da Silva Book 2019 Springer Nature Switzerland AG 2019 MDA 2018 Porto.Shape Memory Compo

NO610

书目名称Materials Design and Applications II影响因子(影响力)




书目名称Materials Design and Applications II影响因子(影响力)学科排名




书目名称Materials Design and Applications II网络公开度




书目名称Materials Design and Applications II网络公开度学科排名




书目名称Materials Design and Applications II被引频次




书目名称Materials Design and Applications II被引频次学科排名




书目名称Materials Design and Applications II年度引用




书目名称Materials Design and Applications II年度引用学科排名




书目名称Materials Design and Applications II读者反馈




书目名称Materials Design and Applications II读者反馈学科排名

Jogging

NIP

entreat

BARB

好色

Comparison of Artificial Neural Network and Adaptive Neuro Fuzzy Inference Systems for Predicting thaximum and minimum principal stresses through which fatigue limit of punch is estimated. The factors affecting the life of punch are examined and a mathematical model is established using artificial neural network (ANN) and adaptive neuro fuzzy inference systems (ANFIS). The developed model is utili

态度暖昧

Comparison Between Hot Rolled and PM/HIP Processed Duplex Stainless Steel UNS S31803tting corrosion resistance and toughness. The steel with basic composition 21.0–23.0%Cr, 4.5–6.5%Ni, 2.5–3.5%Mo, 0.08–0.20%N was developed in the 1980s and became the most popular DSS used in the oil and gas industry. The mechanical properties and corrosion resistance are optimized with a microstruc

Root494

Venules

冥界三河

Inverse Methodology for Estimating the Heat Transfer Coefficient in a Duplex Stainless Steel Castingesses in the end cast components. In this work, a numerical model was developed to simulate the cooling of a duplex stainless steel casting on a furan-bonded sand mold. The heat transfer coefficient (HTC) as a function of temperature was determined by an inverse method. A good agreement between expe