scholarly journals Optimization Design of a Riser-Drill String Coupling System Based on CAE Techniques

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Shiyao Qin ◽  
Ruiming Wang ◽  
Deyi Fu ◽  
Gaowei Wang
Keyword(s):  
Optimization Design ◽  
Optimal Solution ◽  
Drill String ◽  
Dynamic Responses ◽  
Optimization Strategy ◽  
Effect Analysis ◽  
Coupling System ◽  
The Monte Carlo Method ◽  
Optimization Parameters ◽  
The Stability

In a riser-drill string coupling system, the drill string extends from platform to downhole, and its exterior tube is divided by mud line into two parts: riser for upside and borehole for downside. Due to such a pipe-in-pipe structure, an improved dynamic model is proposed to take the multipoint interactions between the inner and outer pipes into consideration. The dynamic responses of this system are analyzed by Computer Aided Engineering (CAE) techniques; specifically, it is numerically simulated in Abaqus; then, both the parametric sensitivity analysis and the main effect analysis are carried out in Isight to determine the optimization parameters and the optimization strategy. Moreover, six-sigma algorithm in Isight is applied to simultaneously drive the neighborhood cultivation genetic algorithm (NCGA) to conduct multiobjective optimization and drive the Monte Carlo method to analyze the stability of the obtained optimal solution. Based on the above investigations, a software package is developed via the secondary developments of both Abaqus and Isight. By this way, the optimization design of the riser-drill string coupling system based on dynamic analysis can be conducted effectively and efficiently.

CFD Based Multi-Disciplinary Optimization Design of High-Performance Deep Sea Seismic Vessel

2017 ◽  
Author(s):  
Mao Xiaofei ◽  
Zhang Wenxu ◽  
Qian Jiankui ◽  
Wu Minghao
Keyword(s):  
High Performance ◽  
Optimization Design ◽  
Optimal Solution ◽  
Solution Set ◽  
Short Term ◽  
Hull Form ◽  
Optimal Solution Set ◽  
Computational Fluid Dynamics Cfd ◽  
The Stability

This paper focuses on the application of a ship hull form multi-disciplinary optimization (MDO) system based on the computational fluid dynamics (CFD). Using the iSIGHT software, the MDO system integrates an automatic geometry transformation program and high-fidelity CFD solvers for different sub-disciplines. Hydrodynamics analysis subsystem includes resistance, seakeeping and stability modules. The resistance and seakeeping is analyzed by commercial potential-flow CFD codes, the stability is assessed by in-house code. The geometry variation output can be automatically used by the numerical solvers. By means of the design of experiment (DOE) technique, a neural network metamodel is trained to predict short term motion response of the derived ships efficiently. The system has been used in a seismic vessel’s hull form optimization to minimize the resistance and maximize the long term seakeeping operability index. Meanwhile, the stability in waves is concerned as a constraint. The hybrid MIGA-NLPQL optimization algorithm is applied for a global-to-local search in resistance optimization. For the synthesis optimization, a Pareto optimal solution set has been obtained and the final solution is achieved by trade-off analysis of the solution set. The entire automatic optimization process can be used for the preliminary design of new high performance vessels.

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 Hybrid optimization design approach of asymmetric base-isolation coupling system for twin buildings

2021 ◽  
pp. 146134842199296
Author(s):  
Wonsuk Park ◽  
Seung-Yong Ok
Keyword(s):  
Vibration Control ◽  
Optimization Design ◽  
Base Isolation ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Efficient Design ◽  
Coupling System ◽  
Twin Buildings

This study proposes a new configuration of asymmetric base-isolation coupling system for the vibration control of twin buildings, and also presents an efficient design method of using a hybrid optimization technique integrated with preference-based dimensionality reduction technique. The purpose of the proposed optimization approach is to guarantee the compromise optimal solution of well-balancing the mutually conflicting design objectives. In order to demonstrate the proposed approach, the adjacent 20-story twin buildings subjected to earthquake excitations were adopted as target buildings and it was verified through numerical examples that the proposed optimization technique can successfully find the optimal solution to achieve various design objectives in a balanced manner. The seismic performance was also compared with the existing different-story connection system with uniform distribution of dampers. The comparative results of the seismic performances between two systems clearly demonstrate that the proposed system can achieve great performance improvement over the existing system while maintaining balanced design preferences. Thus, it can be concluded that the proposed system can be a very effective system for the vibration control problem of the twin buildings.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

Separating the Contributions in Localization Methods: A Technique to Enhance Identification of Damping Related Parameters

1999 ◽  
Author(s):  
Hervé Algrain ◽  
Calogero Conti ◽  
Pierre Dehombreux
Keyword(s):  
Finite Element ◽  
Model Updating ◽  
Element Model ◽  
Dynamic Responses ◽  
Finite Element Model Updating ◽  
Global Localization ◽  
Localization Method ◽  
The Family ◽  
Family Based ◽  
The Stability

Abstract Finite Element Model Updating has for objective to increase the correlation between the experimental dynamic responses of a structure and the predictions from a model. Among different initial choices, these procedures need to establish a set of representative parameters to be updated in which some are in real error and some are not. It is therefore important to select the correct properties that have to be updated to ensure that no marginal corrections are introduced. In this paper the standard localization criteria are presented and a technique to separate the global localization criteria in family-based criteria for damped structures is introduced. The methods are analyzed and applied to both numerical and experimental examples; a clear enhancement of the results is noticed using the family-based criteria. A simple way to qualify the stability of a localization method to noise is presented.

A Systematic Optimization Design Method for Thermal Management of Passenger Vehicles

2021 ◽  
pp. 1-27
Author(s):  
Jie Zhang ◽  
Qidong Wang ◽  
Han Zhang ◽  
Min Zhang ◽  
Jianwei Lin
Keyword(s):  
Prediction Model ◽  
Surface Temperature ◽  
Thermal Management ◽  
Optimization Design ◽  
Cfd Simulation ◽  
Optimal Solution ◽  
Optimization Method ◽  
Drive Shaft ◽  
Management Problem ◽  
Systematic Optimization

Abstract In this study, a systematic optimization method for the thermal management problem of passenger vehicle was proposed. This article addressed the problem of the drive shaft sheath surface temperature exceeded allowable value. Initially, the causes and initial measures of the thermal problem were studied through computational fluid dynamics (CFD) simulation. Furthermore, the key measures and the relevant parameters were determined through Taguchi method and significance analysis. A prediction model between the parameters and optimization objective was built by radial basis function neural network (RBFNN). Finally, the prediction model and particle swarm optimization (PSO) algorithm were combined to calculate the optimal solution, and the optimal solution was selected for simulation and experiment verification. Experiment results indicated that this method reduced the drive shaft sheath surface temperature promptly, the decreasing amplitude was 22%, which was met the experimental requirements.

scholarly journals Managing cost uncertainties in transportation and assignment problems

1998 ◽  
Vol 2 (1) ◽  
pp. 65-104 ◽  
Author(s):  
V. Adlakha ◽  
H. Arsham
Keyword(s):  
Time Lag ◽  
Real Life ◽  
Optimal Solution ◽  
Global Market ◽  
Solution Algorithm ◽  
Assignment Problems ◽  
The Stability ◽  
Order Assignment ◽  
Cost Parameters ◽  
The Cost

In a fast changing global market, a manager is concerned with cost uncertainties of the cost matrix in transportation problems (TP) and assignment problems (AP).A time lag between the development and application of the model could cause cost parameters to assume different values when an optimal assignment is implemented. The manager might wish to determine the responsiveness of the current optimal solution to such uncertainties. A desirable tool is to construct a perturbation set (PS) of cost coeffcients which ensures the stability of an optimal solution under such uncertainties.The widely-used methods of solving the TP and AP are the stepping-stone (SS) method and the Hungarian method, respectively. Both methods fail to provide direct information to construct the needed PS. An added difficulty is that these problems might be highly pivotal degenerate. Therefore, the sensitivity results obtained via the available linear programming (LP) software might be misleading.We propose a unified pivotal solution algorithm for both TP and AP. The algorithm is free of pivotal degeneracy, which may cause cycling, and does not require any extra variables such as slack, surplus, or artificial variables used in dual and primal simplex. The algorithm permits higher-order assignment problems and side-constraints. Computational results comparing the proposed algorithm to the closely-related pivotal solution algorithm, the simplex, via the widely-used pack-age Lindo, are provided. The proposed algorithm has the advantage of being computationally practical, being easy to understand, and providing useful information for managers. The results empower the manager to assess and monitor various types of cost uncertainties encountered in real-life situations. Some illustrative numerical examples are also presented.

Multidisciplinary Optimization Design for Section Layout of Complex Umbilical Cables Based on Intelligent Algorithm

2015 ◽  
Author(s):  
Zhixun Yang ◽  
Jun Yan ◽  
Guojun Ma ◽  
Qingzhen Lu ◽  
Minggang Tang ◽  
...  
Keyword(s):  
Optimization Design ◽  
Oil And Gas ◽  
Power Transmission ◽  
Optimal Solution ◽  
Point Of View ◽  
Multidisciplinary Optimization ◽  
Intelligent Algorithm ◽  
Control Functions ◽  
Offshore Oil And Gas ◽  
Ocean Environment

Umbilical which links the top floater and the subsea devices provides control functions through electrical cables and hydraulic remote transmission. They are treated as the “lifeline” of the subsea production system for offshore oil and gas exploitation. During operation, umbilical needs to undertake self-weight and periodical load due to the ocean environment. Meanwhile, the heat during power transmission in electric cable is released to the umbilical body, which influences the mechanical properties and optical transmission in the cable. However, there are a number of components and many kinds of sectional arrangement for the umbilical. So the sectional design with multiple components needs to be solved as a multidisciplinary optimization problem. From the mechanical point of view, the umbilical structure should be designed with more compacted and symmetric layout to obtain even probability of resistance to loads and reduce structural stress to improve its fatigue performance. Concerning thermal effect, these units should be arranged to dissipate the heat easily to avoid the influence on the functional and structural components. In this paper, compactedness, symmetry and temperature distribution are quantified through introducing corresponding indices. Then multidisciplinary optimization framework is established. Particle Swarm Optimization (PSO) intelligent algorithm is adopted to carry out the optimization to obtain the optimal solution, which is far superior to the initial design. The optimization design strategy is proved to be effective and efficient by some numerical examples, which provides reference for design of umbilical cables.

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