Multi-Objective Design Optimization of Drilling Riser Operability Envelope for Ultra-Deep Water

2018 ◽  
Author(s):  
Hezhen Yang ◽  
Chan Ghee Koh ◽  
Ying Min Low ◽  
Peter Francis Bernad Adaikalaraj
Keyword(s):  
Design Optimization ◽  
Deep Water ◽  
Optimization Design ◽  
Oil And Gas ◽  
Minimum Weight ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Deep Waters ◽  
Riser Design

This paper presents an efficient methodology for multi-objective design optimization of drilling riser in ultra-deep water considering maximum operability window and minimum weight of drilling riser system. As exploration activity moves to ultra-deep waters, the associated drilling cost increases, putting pressure on the operators to expand the drilling operability and reduce costs. Drilling systems are an integral part of oil and gas exploration particularly in deep waters. The drilling riser design requires a time-consuming design loops and scenarios analyzed with different FEM models, such as connected mode, drift-off, hang-off, recoil analysis, emergency disconnection, etc. The main purposes of this work is to improve the safety and cost-effective for drilling riser design by employing multi-objective optimization based on metamodel. The Radial Basis Function (RBF) metamodel is constructed by the design of experiment sampling and is utilized to solve the problem of time-consuming analyses. In the optimization module, multi-objective optimization by a non-dominated sorting genetic algorithm II is performed. Thereby, RBF optimum solutions forming a Pareto set are obtained and compared with accuracy analysis to determine their validity. The optimization results indicate that the proposed optimization strategy is valid and provide an efficient optimization design method for drilling riser in ultra-deep water.

Multi-Objective Optimization Based on TTR Interference Analysis

2013 ◽  
Vol 753-755 ◽  
pp. 1217-1220
Author(s):  
Da Wei Ji ◽  
Yi Huang ◽  
Qi Zhang
Keyword(s):  
Deep Water ◽  
Present Method ◽  
Critical Issue ◽  
Multi Objective Optimization ◽  
Interference Analysis ◽  
Multi Objective ◽  
Riser Design ◽  
Offshore Industry

Riser interference has become a critical issue in riser design with the progression of offshore industry into deep water. It indicates that the potential for interference between Top Tension Risers (TTR) depends not only on the Top Tension Factor (TTF), but also on the riser spacing size. For riser system, each impassive factor of interference could make a different effect (cost and safety), which is often incompatible. A Multi-Objective Optimization (MOO) method is proposed to harmonize the two incompatible objectives: cost and safety. Therefore, it greatly facilitates to adapt the present method to riser interference optimization. Example is given to demonstrate the effectiveness and robustness of the proposed method.

The Application of an Immune Clonal Selection Algorithm Based on the Information Entropy in Truss Structure Multi-Objective Optimization

2012 ◽  
Vol 249-250 ◽  
pp. 1119-1125
Author(s):  
Chang Yuan Hu ◽  
He Sheng Tang ◽  
Li Xin Deng ◽  
Song Tao Xue
Keyword(s):  
Information Entropy ◽  
Optimization Design ◽  
Clonal Selection ◽  
Minimum Weight ◽  
Truss Structures ◽  
Penalty Function Method ◽  
Clonal Selection Algorithm ◽  
Multi Objective Optimization ◽  
Selection Algorithm ◽  
Multi Objective

In order to solve the conflict multi-objective optimization of truss structures between the structure minimum weight and safety redundancy, the immune clonal selection algorithm based on information entropy was adopted in this paper. Based on the immunology theory, the non-dominated neighbor-based selection, proportional cloning and elitism strategy were introduced in the multi-objective immune clonal selection algorithm (MOICSA) to enhance the diversity, the uniformity and the convergence of the obtained solution. Mathematical models for truss multi-objective optimization design are constructed, in which the information entropy value of bar stress is taken as one of objective functions, and penalty function method was used to deal with violated constraints. Several classical problems are solved using the MOICSA algorithm, and the results compared with other optimization methods. The simulation results show that the method can achieve the effect of multiple-objective optimization successfully.

Multi-Objective Optimization Design of Steel Frames Based on Multiple Attribute Decision-Making Method

2013 ◽  
Vol 368-370 ◽  
pp. 830-837
Author(s):  
Mao Qiao Cui ◽  
Hai Yan Huang ◽  
Fu Lai Wang ◽  
Yong Qiu
Keyword(s):  
Decision Making ◽  
Optimization Design ◽  
Intuitionistic Fuzzy Set ◽  
Optimal Solution ◽  
Multiple Attribute Decision Making ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multiple Attribute ◽  
High Level

This paper describes in detail a multi-objective optimization strategy and decision-making method in the process of steel frame optimization design. A step-by-step analysis process integrating optimization algorithm and model analysis is proposed to solve the present problem. A multi-objective algorithm method using fast Non-dominated Sorting Genetic Algorithm is employed to obtain the Pareto-optimal solution set through an evolutionary optimization process. A high-level multiple attribute decision-making method based on intuitionistic fuzzy set theory is adopted to rank these solutions from the best to worst, and to determine the best solution. An example is used to demonstrate the proposed optimization model and decision-making method.

scholarly journals Multi-Objective Optimization Design of a Novel Integral Squeeze Film Bearing Damper

Machines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 206
Author(s):  
Yipeng Zhang ◽  
Lidong He ◽  
Jianjiang Yang ◽  
Gang Zhu ◽  
Xingyun Jia ◽  
...  
Keyword(s):  
Optimization Design ◽  
Structural Parameters ◽  
Rotor System ◽  
Squeeze Film ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Practical Applications ◽  
Multi Objective ◽  
Transmitted Force

In order to better control the vibration of the rotor system so as to improve the stability and safety of the rotor, a novel vibration control solution is needed. In this paper, the multi-objective optimization problem is used for designing a novel integral squeeze film bearing damper (ISFBD). The method attempts to reduce the stiffness and stress convergence of ISFBD, which can greatly decrease the transmitted force of the rotor system and better use the damping effect to dissipate the vibration energy. The finite element model of ISFBD is established to analyze the stiffness and stress, and the correctness of the calculation is verified by setting up a stiffness test platform. The sensitivity of different structural parameters of stiffness and stress is analyzed by ANOVA. Meanwhile, the non-dominated sorting genetic algorithm (NSGA-II) and grey correlation analysis (GRA) algorithms are coupled for multi-objective optimization of stiffness and stress. The results indicate that optimized ISFBD can distribute 26.6% of the rotor system’s energy and reduce 59.3% of the transmitted force at the bearing location. It is also proved that the optimization strategy is effective, which can provide a useful method for ISFBD design in practical applications.

Multi-Objective Optimization Design for Cutting Head of Roadheader

2010 ◽  
Vol 450 ◽  
pp. 75-78 ◽  
Author(s):  
Xin Zhang ◽  
Xiao Zhe Liu ◽  
Jian Wu Zhang ◽  
Qing Liang Zeng
Keyword(s):  
Energy Consumption ◽  
Optimization Design ◽  
Specific Energy Consumption ◽  
Mean Value ◽  
Energy Utilization ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cutting Head ◽  
Quadratic Programming Method

Aiming at load fluctuations and energy consumption of cutting head, a novel optimization strategy is presented in this paper, which is making every pick loaded uniformly and keeping number of picks in cutting section constant at every moment. It also considers the coal compression-tension effect and the action of pick tilt angle to pick force. The mathematical model of multi-objective optimization design for pick arrangement parameters and motion parameters of cutting head is established firstly, and then the sequential quadratic programming method (SQP) is chosen to compile the program of optimization design. The optimization example shows that in the premise of outline dimensions of cutting head unchanged, the load torque fluctuation decreases for 92%, which reduces the torsional vibration of transmission system of roadheader effectively. The swing force fluctuation also decreases for 83%, which enhances the stability of swing feed. Although the mean value of cutting head’ load decreases a little, all the load peaks decline after optimization, which avoid the single pick overload. And, the specific energy consumption decreases for 21%, which improves the energy utilization of roadheader.

Integrated Design and Multi-Objective Optimization of a Single Stage Heat-Pump Turbocompressor

2013 ◽  
Author(s):  
J. Schiffmann
Keyword(s):  
Design Optimization ◽  
High Efficiency ◽  
Integrated Design ◽  
Heat Pumps ◽  
Small Scale ◽  
Multi Objective Optimization ◽  
Design Constraints ◽  
Multi Objective ◽  
Wide Range ◽  
Standard Design

Small scale turbomachines in domestic heat pumps reach high efficiency and provide oil-free solutions which improve heat-exchanger performance and offer major advantages in the design of advanced thermodynamic cycles. An appropriate turbocompressor for domestic air based heat pumps requires the ability to operate on a wide range of inlet pressure, pressure ratios and mass flows, confronting the designer with the necessity to compromise between range and efficiency. Further the design of small-scale direct driven turbomachines is a complex and interdisciplinary task. Textbook design procedures propose to split such systems into subcomponents and to design and optimize each element individually. This common procedure, however, tends to neglect the interactions between the different components leading to suboptimal solutions. The authors propose an approach based on the integrated philosophy for designing and optimizing gas bearing supported, direct driven turbocompressors for applications with challenging requirements with regards to operation range and efficiency. Using previously validated reduced order models for the different components an integrated model of the compressor is implemented and the optimum system found via multi-objective optimization. It is shown that compared to standard design procedure the integrated approach yields an increase of the seasonal compressor efficiency of more than 12 points. Further a design optimization based sensitivity analysis allows to investigate the influence of design constraints determined prior to optimization such as impeller surface roughness, rotor material and impeller force. A relaxation of these constrains yields additional room for improvement. Reduced impeller force improves efficiency due to a smaller thrust bearing mainly, whereas a lighter rotor material improves rotordynamic performance. A hydraulically smoother impeller surface improves the overall efficiency considerably by reducing aerodynamic losses. A combination of the relaxation of the 3 design constraints yields an additional improvement of 6 points compared to the original optimization process. The integrated design and optimization procedure implemented in the case of a complex design problem thus clearly shows its advantages compared to traditional design methods by allowing a truly exhaustive search for optimum solutions throughout the complete design space. It can be used for both design optimization and for design analysis.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

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