Optimasi Multi-Objective Berbasis Keandalan Pada Struktur Tipe Jacket Dengan Mempertimbangkan Reserve Strength Ratio (RSR)

Tito, Brigitta Violyna El (2024) Optimasi Multi-Objective Berbasis Keandalan Pada Struktur Tipe Jacket Dengan Mempertimbangkan Reserve Strength Ratio (RSR). Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Menurut International Energy Agency (IEA) proyeksi permintaan energi global terus meningkat sebesar 45% pada tahun 2030 dengan tingkat pertumbuhan rata-rata sekitar 1,6% per tahun. Bahan bakar fosil seperti minyak dan gas diperkirakan memenuhi sekitar 80% total kebutuhan energi dunia. Salah satu fasilitas yang mendukung dalam operasi eksploitasi minyak dan gas bumi adalah struktur lepas pantai bertipe jacket platform. Tantangan dalam membangun jacket platform adalah biaya dan keandalan struktur. Biaya harus ditekan seminimal mungkin untuk menjaga harga produksi yang stabil. Struktur lepas pantai dirancang untuk menahan beban gelombang ekstrem yang dapat menyebabkan runtuhnya komponen individu atau seluruh struktur. Untuk itu, setiap solusi desain harus dapat mengoptimalkan volume material tanpa mengorbankan integritas strukturnya sehingga lebih efisien. Penelitian ini bertujuan untuk mengembangkan optimasi multi objektif pada desain struktur jacket berbasis keandalan dengan mempertimbangkan kekuatan ultimatnya. Struktur dianalisis secara plastis dengan memprediksi kapasitas ultimatnya berdasarkan parameter Reserve Strength Ratio (RSR). Metode ini dapat menghasilkan desain optimum sekaligus beserta keandalan yang terkait. Sementara metode optimasi deterministik hanya mendapatkan hasil optimum berdasarkan pengurangan materialnya saja tanpa melibatkan keandalan struktur. Fungsi objektif penelitian ini yaitu meminimumkan massa struktur dan sekaligus meningkatkan keandalan struktur. Dengan variabel desain yang dipertimbangkan adalah diameter luar dan ketebalan bracing dan jacket leg. Optimasi multi-objektif biasanya diselesaikan berdasarkan optimalitas pareto., berbeda dengan optimasi objektif tunggal yang diselesaikan dengan satu solusi optimal. Penelitian ini mengintegrasikan finite element analysis (FEA) dan optimasi menggunakan metamodel. Metamodel berbasis neural-network yang digunakan adalah Radial Basis Function (RBF). Metode optimasi yang digunakan yaitu Weighted-Sum Method, metode yang paling sederhana dan banyak digunakan, dengan penyelesaian optimasi nonlinear programming. Hasil penelitian ini menunjukkan desain yang optimal yang meminimalkan massa struktur jacket dan meningkatkan keandalan struktur dalam kondisi beban lingkungan ekstrem memiliki dimensi variabel desain X1, X2, X3, X4 dan X5 masing-masing sebesar 17.1, 1.75, 23.295, 1.65, 1.9. Dan hasil keandalan awal dan keandalan setelah optimasi sebesar masing masing sebesar 3.86 dan 3.213. Dan pada optimasi ini material struktur dapat diturunkan sebesar 10.2% dari berat struktur awal.
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According to the International Energy Agency (IEA), global energy demand is projected to increase by 45% by 2030 with an average growth rate of about 1.6% per year. Fossil fuels such as oil and gas are estimated to fulfill about 80% of the world's total energy needs. One of the facilities that support oil and gas exploitation operations is the jacket platform type offshore structure. The challenge in building a jacket platform is the cost and reliability of the structure. Costs must be minimized to maintain stable production prices. Offshore structures are designed to withstand extreme wave loads that can cause the collapse of individual components or the entire structure. For this reason, any design solution must be able to optimize the volume of material without compromising the integrity of the structure so that it is more efficient. This research aims to develop a multi-objective optimization on reliability-based jacket structure design considering its ultimate strength. The structure is plastically analyzed by predicting its ultimate capacity based on the Reserve Strength Ratio (RSR) parameter. This method can produce the optimum design as well as the associated reliability. Meanwhile, the deterministic optimization method only obtains optimum results based on material reduction without involving structural reliability. The objective function of this research is to minimize the mass of the structure and at the same time increase the reliability of the structure. The design variables considered are the outer diameter and thickness of bracing and jacket leg. Multi-objective optimization is usually solved based on pareto optimality, in contrast to single objective optimization which is solved with one optimal solution. This research integrates finite element analysis (FEA) and optimization using a metamodel. The neural-network-based metamodel used is Radial Basis Function (RBF). The optimization method used is the Weighted-Sum Method, the simplest and most widely used method, with a nonlinear programming optimization solution. The results of this study show that the optimal design that minimizes the mass of the jacket structure and increases the reliability of the structure under extreme environmental load conditions has design variable dimensions X1, X2, X3, X4 and X5 of 17.1, 1.75, 23.295, 1.65, 1.9, respectively. And the results of initial reliability and reliability after optimization amounted to 3.86 and 3.213, respectively. And in this optimization, the structural material can be reduced by 10.2% of the initial structural weight.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Optimasi Multi-Objektif; Keandalan; Analisis Nonlinier; Struktur Jacket; Multi-Objective Optimization; Reliability; Nonlinear Analysis; Jacket Structure
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA169 Reliability (Engineering) T Technology > TC Hydraulic engineering. Ocean engineering > TC1680 Offshore structures
Divisions:	Faculty of Marine Technology (MARTECH) > Ocean Engineering > 38101-(S2) Master Thesis
Depositing User:	Brigitta Violyna El Tito
Date Deposited:	11 Jul 2024 07:12
Last Modified:	11 Jul 2024 07:12
URI:	http://repository.its.ac.id/id/eprint/108248

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