Model-Based Simulation Approach for Pre-Front End Engineering Design Studies for Subsea Field Architecture Development

2021 ◽  
pp. 1-21
Author(s):  
Hamdi Mnasri ◽  
Matthew A. Franchek ◽  
Taoufik Wassar ◽  
Yingjie Tang ◽  
Amine Meziou

Summary Presented is a model-based methodology identifying subsea field architectures that satisfy prespecified multiphysics constraints. The proposed methodology prioritizes the identified subsea system using a multiobjective optimization approach considering two objective functions, which are minimizing pressure drop reflecting the maximization of production flow rates and minimizing capital expenditures. The architecture solutions produce manifolds positioning and optimal pipeline routing/sizing. A convex combination approach creates the multiobjective optimization criterion enabling weighting among constraints such as hydraulic, topological, structural, and flow assurance, as well as technical issues and financial limitations. The optimization problem is computationally solved using a hybrid method with a global multistart algorithm that combines a scatter search process with a gradient-based local nonlinear problem solver. A case study is provided to test the proposed methodology including the effect of varying the weights among the constraints. This deep-dive analysis demonstrates the potential offered by the proposed methodology, illustrated by the ability to perform several investigations such as wells-grouping analysis and insulation effect on the overall optimization procedure, as well as to provide a tracking tool for flow-assurance factors, namely erosion and corrosion rates along the subsea layout. Hence, we present a demonstration of the capabilities of the proposed model-based subsea field layout optimization procedure.

Author(s):  
Ashraf O. Nassef

Auxetic structures are ones, which exhibit an in-plane negative Poisson ratio behavior. Such structures can be obtained by specially designed honeycombs or by specially designed composites. The design of such honeycombs and composites has been tackled using a combination of optimization and finite elements analysis. Since, there is a tradeoff between the Poisson ratio of such structures and their elastic modulus, it might not be possible to attain a desired value for both properties simultaneously. The presented work approaches the problem using evolutionary multiobjective optimization to produce several designs rather than one. The algorithm provides the designs that lie on the tradeoff frontier between both properties.


1994 ◽  
Vol 31 (02) ◽  
pp. 149-160
Author(s):  
Donald C. Wyatt ◽  
Peter A. Chang

A numerically optimized bow design is developed to reduce the total resistance of a 23 000 ton ammunition ship (AE 36) at a speed of 22 knots. An optimization approach using slender-ship theory for the prediction of wave resistance is developed and applied. The new optimization procedure is an improvement over previous optimization methodologies in that it allows the use of nonlinear constraints which assure that the final design remains within practical limits from construction and operational perspectives. Analytic predictions indicate that the AE 36 optimized with this procedure will achieve a 40% reduction in wave resistance and a 33% reduction in total resistance at 22 knots relative to a Kracht elliptical bulb bow design. The optimization success is assessed by the analysis of 25th scale model resistance data collected at the David Taylor Research Center deepwater towing basin. The experimental data indicate that the optimized hull form yields a 51% reduction in wave resistance and a 12% reduction in total resistance for the vessel at 22 knots relative to the Kracht bulb bow design. Similarly encouraging results are also observed when comparisons are made with data collected on two other conventionally designed AE 36 designs.


2008 ◽  
Vol 26 (16) ◽  
pp. 2969-2976 ◽  
Author(s):  
Ademar Muraro ◽  
Angelo Passaro ◽  
Nancy Mieko Abe ◽  
Airam Jonatas Preto ◽  
Stephan Stephany

Author(s):  
Yaojun Lu ◽  
Chun Liang ◽  
Juan J. Manzano-Ruiz ◽  
Kalyana Janardhanan ◽  
Yeong-Yan Perng

This paper presents a multiphysics approach for characterizing flow-induced vibrations (FIVs) in a subsea jumper subject to internal production flow, downstream slug, and ocean current. In the present study, the physical properties of production fluids and associated slugging behavior were characterized by pvtsim and olga programs under real subsea condition. Outcomes of the flow assurance studies were then taken as inputs of a full-scale two-way fluid–structure interaction (FSI) analysis to quantify the vibration response. To prevent onset of resonant risk, a detailed modal analysis has also be carried out to determine the modal shapes and natural frequencies. Such a multiphysics approach actually integrated the best practices currently available in flow assurance (olga and pvtsim), computational fluid dynamics (CFD), finite element analysis (FEA), and modal analysis, and hence provided a comprehensive solution to the FSI involved in a subsea jumper. The corresponding results indicate that both the internal production flow, downstream slugs, and the ocean current would induce vibration response in the subsea jumper. Compared to the vortex-induced vibration (VIV) due to the ocean current and the FIV due to the internal production flow, pressure fluctuation due to the downstream slug plays a dominant role in generating excessive vibration response and potential fatigue failure in the subsea jumper. Although the present study was mainly focused on the subsea jumper, the same approach can be applied to other subsea components, like subsea flowline, subsea riser, and other subsea production equipment.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yindong Shen ◽  
Wenliang Xie ◽  
Jingpeng Li

The timetabling problem (TTP) and vehicle scheduling problem (VSP) are two indispensable problems in public transit planning process. They used to be solved in sequence; hence, optimality of resulting solutions is compromised. To get better results, some integrated approaches emerge to solve the TTP and VSP as an integrated problem. In the existing integrated approaches, the passenger comfort on bus and the uncertainty in the real world are rarely considered. To provide better service for passengers and enhance the robustness of the schedule to be compiled, we study the integrated optimization of TTP and VSP with uncertainty. In this paper, a novel multiobjective optimization approach with the objectives of minimizing the passenger travel cost, the vehicle scheduling cost, and the incompatible trip-link cost is proposed. Meanwhile, a multiobjective hybrid algorithm, which is a combination of the self-adjust genetic algorithm (SGA), large neighborhood search (LNS) algorithm, and Pareto separation operator (PSO), is applied to solve the integrated optimization problem. The experimental results show that the approach outperforms existing approaches in terms of service level and robustness.


2006 ◽  
Vol 129 (2) ◽  
pp. 144-153 ◽  
Author(s):  
Andrzej W. Ordys ◽  
Masayoshi Tomizuka ◽  
Michael J. Grimble

The paper discusses state-space generalized predictive control and the preview control algorithms. The optimization procedure used in the derivation of predictive control algorithms is considered. The performance index associated with the generalized predictive controller (GPC) is examined and compared with the linear quadratic (LQ) optimal control formulation used in preview control. A new performance index and consequently a new algorithm is proposed dynamic performance predictive controller (DPPC) that combines the features of both GPC and preview controller. This algorithm minimizes the performance index through a dynamic optimization. A simple example illustrates the features of the three algorithms and prompts a discussion on what is actually minimized in predictive control. The DPPC algorithm, derived in this paper, provides for a minimum of the predictive performance index. The differences and similarities between the preview control and the predictive control have been discussed and optimization approach of predictive control has been explained.


2017 ◽  
Vol 58 ◽  
pp. 732-741 ◽  
Author(s):  
Yu-Jun Zheng ◽  
Yue Wang ◽  
Hai-Feng Ling ◽  
Yu Xue ◽  
Sheng-Yong Chen

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