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LEAST SQUARES SUPPORT VECTOR MACHINE FOR CONSTITUTIVE MODELING OF CLAY X. Zhou and J. Shen Abstract Constitutive modeling of clay is an important research in geotechnical engineering. It is difficult to use precise mathematical expressions to approximate stress-strain relationship of clay. Artificial neural network (ANN) and support vector machine (SVM) have been successfully used in constitutive modeling of clay. However, generalization ability of ANN has some limitations, and application of SVM in large scale function approximation problems is limited during optimization. In this paper, least squares support vector machine (LSSVM) is proposed to simulate stress-strain relationship of clay. LSSVM is a robust type of SVM, maintains the good features of SVM and also has its own unique advantages. LSSVM offers an effective alternative for mimicking constitutive modeling of clay. The good performance of the LSSVM models is demonstrated by learning and prediction of constitutive relationship of Fujinomori clay under undrained and drained conditions. In the present study, three versions of LSSVM models are built by considering more history points. The results prove that the LSSVM based models are superior to Modified Cam-clay model. Keywords Constitutive modeling, Artificial neural network (ANN), Support vector machine (SVM), Least squares support vector machine (LSSVM), Fujinomori clay چکیده مدل سازی ساختاری خاک رس از جمله تحقیقات مهم در مهندسی ژئوتکنیک است. استفاده از عبارات دقیق ریاضی برای تخمین رابطه تنش-کرنش خاک رس دشوار است. شبکه عصبی مصنوعی (ANN) و ماشین بردار پشتیبان (SVM) با موفقیت در مدل سازی ساختاری خاک رس استفاده شده اند. با این حال، توانایی تعمیم شبکه عصبی با برخی از محدودیتها روبروست و استفاده از SVM در مسائل تقریب تابع در مقیاس بزرگ در طول بهینه سازی محدود است. در این مقاله، حداقل مربعات ماشین بردار پشتیبانی (LSSVM) برای شبیه سازی رابطه تنش-کرنش خاک رس پیشنهاد شده است. LSSVM یک نوع قوی از SVM است که ویژگی های خوب SVM را حفظ کرده و همچنین دارای مزایای منحصر به فرد خود است. LSSVM جایگزین موثری برای تقلید مدل سازی ساختاری خاک رس ارائه می دهد. عملکرد خوب مدل LSSVM با یادگیری و پیش بینی رابطه ساختاری خاک رس Fujinomori تحت شرایط زهکشی نشده و خشک نشان داده می‌شود. در مطالعه حاضر، سه نسخه از مدل LSSVM با در نظر گرفتن نقاط تاریخی بیشتر ساخته شده است. نتایج ثابت می‌کند که مدل های بر اساس LSSVM نسبت به مدل بادامک خاک رس اصلاح شده برتری دارند. منبع دانلود 28-11-4.pdf

The Influence of Biofilm on the Mechanical Behavior of Sand S. W. Perkins,1 P. Gyr,2 and G. James3 REFERENCE: Perkins, S. W., Gyr, P., and James, G., “The Influence of Biofilm on the Mechanical Behavior of Sand,” Geotechnical Testing Journal, GTJODJ, Vol. 23, No. 3, September 2000, pp. 300–312. ABSTRACT: The growth of microbes on the surface of an object results in the formation of a biofilm, which in sand can lead to a reduction of hydraulic conductivity and can be used for groundwater containment and remediation. Sample preparation and testing techniques for triaxial and oedometer experiments were devised for the purpose of examining the influence of biofilm on the stress-straintime properties of Ottawa sand. Results have shown that biofilm has a negligible influence on the strength and stiffness of the sand but increases time-dependent creep deformation. An elasto-viscoplastic constitutive model was calibrated for biofilm and non-biofilm sand and implemented into a finite-element code for the purpose of predicting creep deformation of a slope and a foundation resting on level ground. Numerical simulations showed that additional creep behavior of the biofilm sand had a negligible influence on the behavior of these geotechnical engineering facilities. KEYWORDS: microbial bacteria, biofilm, biobarrier, sand, triaxial testing, oedometer testing, mechanical behavior, creep, constitutive modeling, finite-element modeling GTJ11052J.6514.pdf