Evaluation of Slug Flow-Induced Flexural Loading in Pipelines Using a Surrogate Model

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Ibrahim A. Sultan ◽  
Ahmed M. Reda ◽  
Gareth L. Forbes
Keyword(s):  
Surrogate Model ◽  
Slug Flow ◽  
Stochastic Perturbation ◽  
Numerical Procedure ◽  
Bending Moment ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Successive Approximations ◽  
Worked Example ◽  
Form Model

Slug flow induces vibration in pipelines, which may, in some cases, result in fatigue failure. This can result from dynamic stresses, induced by the deflection and bending moment in the pipe span, growing to levels above the endurance limits of the pipeline material. As such, it is of paramount importance to understand and quantify the size of the pipeline response to slug flow under given speed and damping conditions. This paper utilizes the results of an optimization procedure to devise a surrogate closed-form model, which can be employed to calculate the maximum values of the pipeline loadings at given values of speed and damping parameters. The surrogate model is intended to replace the computationally costly numerical procedure needed for the analysis. The maximum values of the lateral deflection and bending moment, along with their locations, have been calculated using the optimization method of stochastic perturbation and successive approximations (SPSA). The accuracy of the proposed surrogate model will be validated numerically, and the model will be subsequently used in a numerical example to demonstrate its applicability in industrial situations. An accompanying spreadsheet with this worked example is also given.

scholarly journals Optimization Method for Solving the Reasonable Arch Axis of Long-Span CFST Arch Bridges

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Xuesong Zhang ◽  
Ningyi Liang ◽  
Xiaohong Lu ◽  
Anbang Gu ◽  
Jidong Shan
Keyword(s):  
Yangtze River ◽  
Spline Interpolation ◽  
Bending Moment ◽  
Optimization Procedure ◽  
Element Model ◽  
Optimization Methods ◽  
Optimization Method ◽  
Steel Tube ◽  
Long Span ◽  
Arch Bridges

With the continuous construction of 500 m concrete-filled steel-tube (CFST) arch bridges such as the Bosideng Yangtze River Bridge and the Hejiang Changjiang Highway Bridge, the deviation between the dead pressure line and the arch axis produced by extant arch axis optimization methods increases. Therefore, an arch axis optimization method for long-span CFST arch bridges with a truss section must be designed. Following the optimization of the truss arch axis, this study develops the minimum section eccentricity method that aims to optimize the arch axis of long-span CFST arch bridges. To minimize the main tube eccentricity of the truss arch, the bending moment of the main tubes is reduced by applying the main tube eccentricity method iteratively in a finite element model. Afterward, a smooth and reasonable arch axis is fitted by applying a cubic spline interpolation function in MATLAB. The entire optimization procedure is performed using the Bosideng Yangtze River Bridge as an example. Compared with that of optimal arch axis line types (e.g., parabola and catenary) and other traditional arch axes, the bending moment of main tubes optimized by the proposed method is substantially lower and more uniformly distributed along the arch axis span. The mechanical properties of the finished bridge, including its strength, stiffness, and stability, are all improved, thereby verifying the feasibility of using the proposed method to optimize the arch axis of CFST arch bridges with a truss section.

Dimensioning a recovery boiler furnace using mathematical optimization

TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN
Keyword(s):  
Radial Basis Function Network ◽  
High Capacity ◽  
Mathematical Optimization ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Performance Criteria ◽  
Boiler Furnace ◽  
Starting Point ◽  
Recovery Boiler ◽  
Base Design

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.

scholarly journals Updated Kriging-Assisted Shape Optimization of a Gravity Dam

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 87
Author(s):  
Yongqiang Wang ◽  
Ye Liu ◽  
Xiaoyi Ma
Keyword(s):  
Surrogate Model ◽  
Computational Cost ◽  
Region Of Interest ◽  
Optimization Procedure ◽  
Optimal Shape ◽  
Small Sample ◽  
Gravity Dam ◽  
Kriging Surrogate Model ◽  
Gravity Dams ◽  
Sample Set

The numerical simulation of the optimal design of gravity dams is computationally expensive. Therefore, a new optimization procedure is presented in this study to reduce the computational cost for determining the optimal shape of a gravity dam. Optimization was performed using a combination of the genetic algorithm (GA) and an updated Kriging surrogate model (UKSM). First, a Kriging surrogate model (KSM) was constructed with a small sample set. Second, the minimizing the predictor strategy was used to add samples in the region of interest to update the KSM in each updating cycle until the optimization process converged. Third, an existing gravity dam was used to demonstrate the effectiveness of the GA–UKSM. The solution obtained with the GA–UKSM was compared with that obtained using the GA–KSM. The results revealed that the GA–UKSM required only 7.53% of the total number of numerical simulations required by the GA–KSM to achieve similar optimization results. Thus, the GA–UKSM can significantly improve the computational efficiency. The method adopted in this study can be used as a reference for the optimization of the design of gravity dams.

Structural Topology Optimization Using Frame Elements Based on the Complementary Strain Energy Concept for Eigen-Frequency Maximization

2005 ◽  
Author(s):  
Akihiro Takezawa ◽  
Shinji Nishiwaki ◽  
Kazuhiro Izui ◽  
Masataka Yoshimura
Keyword(s):  
Topology Optimization ◽  
Cross Sections ◽  
Strain Energy ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Structural Topology ◽  
Energy Concept ◽  
Conceptual Design Phase ◽  
Complementary Strain ◽  
Topology Optimization Method

This paper discuses a new topology optimization method using frame elements for the design of mechanical structures at the conceptual design phase. The optimal configurations are determined by maximizing multiple eigen-frequencies in order to obtain the most stable structures for dynamic problems. The optimization problem is formulated using frame elements having ellipsoidal cross-sections, as the simplest case. Construction of the optimization procedure is based on CONLIN and the complementary strain energy concept. Finally, several examples are presented to confirm that the proposed method is useful for the topology optimization method discussed here.

Structural Optimization of Composite Panel with Lamination Parameters and Equivalent Stiffness Laminate Method

2014 ◽  
Vol 496-500 ◽  
pp. 429-435
Author(s):  
Xiao Ping Zhong ◽  
Peng Jin
Keyword(s):  
Genetic Algorithm ◽  
Structural Optimization ◽  
Composite Structure ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Composite Panel ◽  
Analysis Tool ◽  
Equivalent Stiffness ◽  
Lamination Parameters ◽  
Design Variables

Firstly, a two-level optimization procedure for composite structure is investigated with lamination parameters as design variables and MSC.Nastran as analysis tool. The details using lamination parameters as MSC.Nastran input parameters are presented. Secondly, with a proper equivalent stiffness laminate built to substitute for the lamination parameters, a two-level optimization method based on the equivalent stiffness laminate is proposed. Compared with the lamination parameters-based method, the layer thicknesses of the equivalent stiffness laminate are adopted as continuous design variables at the first level. The corresponding lamination parameters are calculated from the optimal layer thicknesses. At the second level, genetic algorithm (GA) is applied to identify an optimal laminate configuration to target the lamination parameters obtained. The numerical example shows that the proposed method without considering constraints of lamination parameters can obtain better optimal results.

Optimization of Stacking Line and Blade Profile for Design of Axial Flow Fan Blade

2008 ◽  
Author(s):  
Abdus Samad ◽  
Ki-Sang Lee ◽  
Kwang-Yong Kim
Keyword(s):  
Objective Function ◽  
Surrogate Model ◽  
Stokes Equations ◽  
Axial Flow ◽  
Weighted Average ◽  
Optimization Procedure ◽  
Total Efficiency ◽  
Blade Profile ◽  
Axial Flow Fan ◽  
Fan Blade

This work presents a numerical optimization procedure for a low-speed axial flow fan blade with weighted average surrogate model. Reynolds-averaged Navier-Stokes equations with SST turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. The blade profile as well as stacking line is modified to enhance blade total efficiency, i.e., the objective function. Six design variables related to blade lean and blade profile are selected, and a design of experiments technique produces design points where flow analyses are performed to obtain values of the objective function. PBA model is employed as a surrogate model for optimization. A search algorithm is used to find the optimal design in the design space from the constructed surrogate model for the objective function. As a main result, the efficiency is increased effectively by the present optimization procedure.

Three-Dimensional Finite Element Analysis of Pipe Flange Connections: The Case of Using Compressed Asbestos Sheet Gasket

2002 ◽  
Author(s):  
Tomohiro Takaki ◽  
Toshimichi Fukuoka
Keyword(s):  
Contact Pressure ◽  
Three Dimensional ◽  
Numerical Procedure ◽  
Bending Moment ◽  
Elastic Interaction ◽  
Bearing Surface ◽  
Element Analysis ◽  
Bolt Stress ◽  
Dimensional Finite Element ◽  
Three Dimensional Finite Element

The most important factor for the leakage problem of pipe flange connections is considered to be contact pressure distribution at the gasket bearing surface in service. In this study, the mechanical behaviors of the pipe flange connection are evaluated using FEM as a three-dimensional contact problem, in which a gasket is modeled as a nonlinear one-dimensional gasket element. Here, the contact pressure distributions at the gasket bearing surface and the variations of the bolt stress are estimated under uniform bolt preloads or nonuniform ones due to the elastic interaction during bolting up. The numerical procedure proposed here can successively deal with the processes of bolt-up, applying inner pressure and applying bending moment. The analytical objects are pipe flanges specified in JIS B 2238 with compressed asbestos sheet gaskets being inserted. The validity of the numerical method is ascertained by experiment.

Aeroelastic Optimization of an Industrial Compressor Rotor Blade Geometry

2018 ◽  
Author(s):  
Federico Vanti ◽  
Lorenzo Pinelli ◽  
Andrea Arnone ◽  
Andrea Schneider ◽  
Pio Astrua ◽  
...  
Keyword(s):  
Numerical Procedure ◽  
Optimization Procedure ◽  
Multidisciplinary Optimization ◽  
Optimization Process ◽  
Geometrical Parameters ◽  
Aerodynamic Optimization ◽  
Compressor Rotor ◽  
Wide Range ◽  
Automatic Optimization ◽  
Blade Geometry

This paper describes a multidisciplinary optimization procedure applied to a compressor blade-row. The numerical procedure takes into account both aerodynamic (efficiency) and aeromechanic (flutter-free design) goals nowadays required by turbo-machinery industries and is applied to a low pressure compressor rotor geometry provided by Ansaldo Energia S.p.A.. Some typical geometrical parameters have been selected and modified during the automatic optimization process in order to generate an optimum geometry with an improved efficiency and, at the same time, a safety flutter margin. This new automatic optimization procedure, which now includes a flutter stability assessment, is an extension of an existing aerodynamic optimization process, which randomly perturbs a starting 3D blade geometry inside a constrained range of values, build the fluid mesh and run the CFD steady analysis. The new implementation provides the self-building of the solid mesh, the FEM analysis and finally the unsteady uncoupled aeroelastic analysis to assess the flutter occurrence. After simulating a wide range of geometries, a database with all the constraint parameters and objective functions is obtained and then used to train a neural network algorithm. Once the ANN validation error is converged, an optimization strategy is used to build the Pareto front and to provide a set of optimum geometries redesigning the original compressor rotor. The aim of this paper is to show the opportunity to also take into account the aeroelastic issues in optimization processes.

Topology Optimization of Compliant Mechanisms Using Hybrid Discretization Model

2010 ◽  
Vol 132 (11) ◽  
Author(s):  
Hong Zhou
Keyword(s):  
Topology Optimization ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Diagonal Element ◽  
Initial Guess ◽  
Stress Constraint ◽  
Design Variables ◽  
Hybrid Discretization

The hybrid discretization model for topology optimization of compliant mechanisms is introduced in this paper. The design domain is discretized into quadrilateral design cells. Each design cell is further subdivided into triangular analysis cells. This hybrid discretization model allows any two contiguous design cells to be connected by four triangular analysis cells whether they are in the horizontal, vertical, or diagonal direction. Topological anomalies such as checkerboard patterns, diagonal element chains, and de facto hinges are completely eliminated. In the proposed topology optimization method, design variables are all binary, and every analysis cell is either solid or void to prevent the gray cell problem that is usually caused by intermediate material states. Stress constraint is directly imposed on each analysis cell to make the synthesized compliant mechanism safe. Genetic algorithm is used to search the optimum and to avoid the need to choose the initial guess solution and conduct sensitivity analysis. The obtained topology solutions have no point connection, unsmooth boundary, and zigzag member. No post-processing is needed for topology uncertainty caused by point connection or a gray cell. The introduced hybrid discretization model and the proposed topology optimization procedure are illustrated by two classical synthesis examples of compliant mechanisms.

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