Abstract
The water jetting system for a jack-up spudcan requires the suitable design considering the platform/spudcan particulars, environments, and soil conditions, either the surficial clay or surficial sand. The usage of water jetting depends critically on soil conditions. The water jetting is usually used for the smooth and fast extraction of the spudcan in the surficial clay condition. It is also required for inserting spudcan up to the required depth in the surficial sand condition, which is investigated in this paper. Especially, it should be very careful to use the water jetting during an installation of spudcan in the surficial sand condition, because there is a risk of overturning accident related to the punch-through. Therefore, in this study, the effect of water jetting flow rate and time on the change of soil properties and penetration resistance is analyzed to better understand their interactions and correlations when inserting the spudcan with water jetting in surficial sand condition. For the investigation, a wind turbine installation jack-up rig (WTIJ) is selected as the target platform and the multi layered soil (surficial sand overlaying clays) is considered as the soil condition. The environmental loading and soil-structure interaction (SSI) analysis are performed by using CHARM3D and ANSYS. This kind of investigation and simulation is needed to decide the proper water jetting flow rate and time of spudcan for the given design condition.
Key Words
jack-up platform; spudcan; water jetting; flow rate; duration; soil-structure interaction;
surficial sand; soil resistance; punch-through
Address
Dong-Seop Han: Research Institute of Green Energy Equipment, Dong-A University, Busan, South Korea
Seung-Jun Kim and Moo-Hyun Kim: Coastal and Ocean Eng. Division, Zachry Dept. of Civil Eng., Texas A&M University, College Station, Texas, USA
Abstract
This study is devoted to the optimal design of compressed bars under axial tensile or compressive forces and exposed to a corrosive environment. Dolinskii\' s linear stress corrosion model is adopted for analysis. Analytical and numerical results are derived for optimal variation of the cross-sectional area of the bar along its axis.
Key Words
corrosive; environment; design; bars; tension; compression
Address
Mark M. Fridman: Kryvyi Rih National University, 7/29 Yuzhniy Avenue, UA-50026, Kryvyi Rih, Ukraine
Isaac Elishakoff: Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL33431-0991, USA
Abstract
Three dimensional (3D) non-linear finite element analysis of offshore pipeline is investigated in this work with the help of general purpose software Abaqus. The general algorithm for the finite element approach is introduced. The 3D seabed mesh, limited to a corridor along the pipeline, is extracted from survey data via Fledermous software. Moreover soil bearing capacity and coefficient of frictions, obtained from the field survey report, and are introduced into the finite element model through the interaction module. For a case of study, a 32inch pipeline with API 5L X65 material grade subjected to high pressure and high temperature loading is investigated in more details.
Key Words
offshore pipeline; Abaqus; stress and strain analysis; three dimensional
Address
Ali Shaghaghi Moghaddam: Young Researchers and Elite Club, Takestan Branch, Islamic Azad University, Takestan, Iran;
Pipeline Engineer, Iranian offshore and construction company (IOEC), Vila street, Tehran, Iran
Saeid Mohammadnia and Mohammad Sagharichiha: Pipeline Engineer, Iranian offshore and construction company (IOEC), Vila street, Tehran, Iran
Abstract
This study presents the development of predictive models for uplift capacity of suction caisson in clay using an artificial intelligence technique, extreme learning machine (ELM). Other artificial intelligence models like artificial neural network (ANN), support vector machine (SVM), relevance vector machine (RVM) models are also developed to compare the ELM model with above models and available numerical model in terms of different statistical criteria. A ranking system is presented to evaluate present models in identifying the \'best\' model. Sensitivity analyses are made to identify important inputs contributing to the developed models.
Key Words
suction caisson; uplift capacity; extreme learning machine; support vector machine; artificial neural network; statistical performance criteria
Address
Pradyut Kumar Muduli, Sarat Kumar Dasand Rupashree Sahoo: Department of Civil Engineering, National Institute of Technology, Rourkela, Odisha, India
Pijush Samui: Centre for Disaster Mitigation and Management, VIT University, Vellore-632014, India
