Design Optimization of Ship Hulls via CFD Techniques

2001 ◽  
Vol 45 (02) ◽  
pp. 140-149
Author(s):  
Daniele Peri ◽  
Michele Rossetti ◽  
Emilio F. Campana
Keyword(s):  
Wave Pattern ◽  
Optimization Process ◽  
Objective Functions ◽  
Original Design ◽  
Flow Solver ◽  
Ship Hulls ◽  
Design Variables ◽  
Specific Objective ◽  
Geometrical Constraints ◽  
Computational Fluid Dynamics Cfd

Numerical shape optimization of a tanker ship hull has been carried out with the aid of computational fluid dynamics (CFD) techniques and experimentally verified. The choice of a specific objective function is based on the needs of the user. In the present study, total resistance and wave pattern have been used either separately or linearly combined. In the optimization process, three different algorithms have been tested, coupled together with a CFD flow solver. A perturbation surface has been used to modify the shape of the hull, allowing for a sharp reduction of the number of design variables. Accordingly, with different objective functions and geometrical constraints, several new optimized shapes of the bulb of a tanker ship have been automatically obtained. Among them, two optimized models have been built and tested, in the INSEAN towing tank, against the original design. In both cases the measured data have confirmed the success of the optimization process.

Grid patterns optimization for single-layer latticed domes

2020 ◽  
pp. 136943322095681
Author(s):  
Masaki Teranishi ◽  
Koichiro Ishikawa
Keyword(s):  
Mechanical Properties ◽  
Single Layer ◽  
Objective Functions ◽  
Imperfection Sensitivity ◽  
Grid Pattern ◽  
Geometric Imperfection ◽  
Design Variables ◽  
Geometrical Constraints ◽  
Nodal Coordinates ◽  
Superior Mechanical Properties

In previous studies on optimized single-layer latticed domes, the inner space and external shape of the optimized dome is different from those of the initial dome. This difference may result in loss of structural functionality and aesthetics intended by the designers, making it difficult to separately evaluate the mechanical properties of the grid patterns and shape of the surface. In this study, 64 types of single-layer latticed domes having different geometric properties are optimized to obtain mechanically effective grid patterns. Six types of objective functions are employed. The nodal coordinates of the domes serve as the design variables under geometrical constraints, where the nodes of the domes can be shifted on the surface area. The geometric and mechanical properties of the optimized grid patterns are evaluated quantitatively against the objective functions. Moreover, interactions between the geometric and mechanical properties are investigated. The results show that the optimized grid pattern has superior mechanical properties and geometric imperfection sensitivity. This optimization scheme can be applied for designing mechanically effective grid patterns for single-layer latticed domes.

scholarly journals Optimal design for improving torque performance of permanent magnet motor

2018 ◽  
Vol 7 (2.12) ◽  
pp. 292
Author(s):  
Tae Kyoung Bang ◽  
Kyung Hun Shin ◽  
Jeong In Lee ◽  
Cheol Han ◽  
Sung Kook Cho ◽  
...  
Keyword(s):  
Optimal Design ◽  
Taguchi Method ◽  
Objective Function ◽  
Permanent Magnet ◽  
Optimum Design ◽  
Optimization Process ◽  
Bldc Motor ◽  
Original Design ◽  
Design Point ◽  
Design Variables

Background/Objectives: This paper deals with the optimal design of the BLDC motor considering a rotor structure that is used to electrically drive tools. Generally, electrically driven tools employ the BLDC motor, which should be able to operate in high-speed and high-vibration environments. However, it has the disadvantages of a high torque ripple and significant waveform fluctuation. Therefore, it is necessary to optimize it according to the usage condition.Methods/Statistical analysis: In improving the torque performance, this study performed the optimization process by employing the Taguchi method, which can achieve a robust design based on the design variables. In the optimization process, the objective functions are set using a weighting ratio depending on the importance of the objective function as back EMF, torque performance, and loss. Through the optimization process, the optimal design point that improved the performance of the objective function is derived. The improved design that applied the optimal design point is compared with the original design by using the finite element method (FEM) analysis results.Findings: In this study, the optimum design of the motor according to the design variables and the objective function is derived through the optimum design method using the Taguchi method by adopting the motor for the electrically driven tool as the interior permanent magnet type BLDC motor and the FEM results. Moreover, by comparing the analysis results with the optimized model and the initial model, the optimum design point that satisfies the restriction specification and the rated specification was found.Improvements/Applications: The optimum design point was found by using the Taguchi method and the loss and torque characteristics were improved. 

scholarly journals Assessment of Deterministic Shape Optimizations Within a Stochastic Framework for Supersonic Organic Rankine Cycle Nozzle Cascades

2019 ◽  
Vol 141 (7) ◽  
Author(s):  
Alessandro Romei ◽  
Pietro Marco Congedo ◽  
Giacomo Persico
Keyword(s):  
Shape Optimization ◽  
Computational Cost ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Objective Functions ◽  
Flow Solver ◽  
Design Variables ◽  
Stochastic Framework ◽  
Constraint Problem ◽  
The Impact

The design of converging–diverging blades for organic Rankine cycle (ORC) applications widely relies on automated shape-optimization processes. As a result, the optimization produces an adapted-nozzle cascade at the design conditions. However, only few works account for the uncertainties in those conditions and their consequences on cascade performance. The proposed solution, i.e., including uncertainties within the optimization routine, demands an overall huge computational cost to estimate the target output statistic at each iteration of the optimization algorithm. With the aim of understanding if this computational cost is avoidable, we study the impact of uncertainties in the design conditions on the robustness of deterministically optimized profiles. Several optimized blades, obtained with different objective functions, constraints, and design variables, are considered in the present numerical analysis, which features a turbulent compressible flow solver and a state-of-the-art uncertainty-quantification (UQ) method. By including measured field variations in the formulation of the UQ problem, we show that a deterministic shape optimization already improves the robustness of the profile with respect to the baseline configuration. Guidelines about objective functions and blade parametrizations for deterministic optimizations are also provided. Finally, a novel methodology to estimate the mass-flow-rate probability density function (PDF) for choked supersonic turbines is proposed, along with a robust reformulation of the constraint problem without increasing the computational cost.

Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2

2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida
Keyword(s):  
Inverse Problems ◽  
Conceptual Design ◽  
Dimensional Space ◽  
Design Stage ◽  
Objective Functions ◽  
Pareto Solutions ◽  
Design Problems ◽  
Multi Objective ◽  
Design Engineers ◽  
Design Variables

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.

Multi Objective Design Optimization of Two Bar Truss Using NSGA II and TOPSIS

2014 ◽  
Vol 984-985 ◽  
pp. 419-424
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Nsga Ii ◽  
Multi Objective ◽  
Total Displacement ◽  
Design Variables ◽  
Conflicting Objectives

Arriving optimal solutions is one of the important tasks in engineering design. Many real-world design optimization problems involve multiple conflicting objectives. The design variables are of continuous or discrete in nature. In general, for solving Multi Objective Optimization methods weight method is preferred. In this method, all the objective functions are converted into a single objective function by assigning suitable weights to each objective functions. The main drawback lies in the selection of proper weights. Recently, evolutionary algorithms are used to find the nondominated optimal solutions called as Pareto optimal front in a single run. In recent years, Non-dominated Sorting Genetic Algorithm II (NSGA-II) finds increasing applications in solving multi objective problems comprising of conflicting objectives because of low computational requirements, elitism and parameter-less sharing approach. In this work, we propose a methodology which integrates NSGA-II and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving a two bar truss problem. NSGA-II searches for the Pareto set where two bar truss is evaluated in terms of minimizing the weight of the truss and minimizing the total displacement of the joint under the given load. Subsequently, TOPSIS selects the best compromise solution.

Multi-Objective Design Optimization of a Mixed-Flow Pump

2009 ◽  
Author(s):  
Yumiko Takayama ◽  
Hiroyoshi Watanabe
Keyword(s):  
Performance Characteristic ◽  
Performance Characteristics ◽  
Inverse Design ◽  
Surface Model ◽  
Objective Functions ◽  
Mixed Flow ◽  
Multi Objective ◽  
Design Variables ◽  
Flow Head ◽  
Flow Pump

In most cases of high specific speed mixed-flow pump applications, it is necessary to satisfy more than one performance characteristic such as deign point efficiency, shut-off power/head and non-stall characteristic (no positive slope in flow-head curve). However, it is known that these performance characteristics are in relation of trade-offs. As a result, it is difficult to optimize these performance characteristics by conventional way such as trial and error approach by modifying geometrical parameters. This paper presents the results of the multi-objective optimization strategy of mixed-flow pump design by means of three dimensional inverse design approach, Computational Fluid Dynamics (CFD), Design of Experiments (DoE), response surface model (RSM) and Multi Objective Genetic Algorism (MOGA). The parameters to control blade loading distributions and meridional geometries for impeller and diffuser blades in inverse design were chosen as design variables of the optimization process. Pump efficiency, maximum slope in flow-head curve and shut-off power/head were selected as objective functions. Objective functions of pumps, designed by design variables specified in DoE, were evaluated by using CFD. Then, trade-off relations between objective functions were analyzed by using Pareto fronts obtained by MOGA. Some pumps which have specific performance characteristic (non-stall, low shut-off power, high efficiency etc.) designed along the Pareto front were numerically evaluated.

Optimal design of a parallel robotic gripper using enhanced multi-objective ant lion optimizer with a sensitivity analysis approach

2020 ◽  
Vol 40 (5) ◽  
pp. 703-721
Author(s):  
Golak Bihari Mahanta ◽  
Deepak BBVL ◽  
Bibhuti B. Biswal ◽  
Amruta Rout
Keyword(s):  
Sensitivity Analysis ◽  
Distribution Function ◽  
Design Parameters ◽  
Objective Functions ◽  
Content Type ◽  
Multi Objective ◽  
The Past ◽  
Design Variables ◽  
Pick And Place ◽  
Ant Lion

Purpose From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems. Design/methodology/approach In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer. Findings This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis. Practical implications The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries. Originality/value In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

scholarly journals Pipeline Compressor Redesign With the Consideration of Both Noise and Performance

2000 ◽  
Author(s):  
Yuri I. Biba ◽  
Zheji Liu ◽  
D. Lee Hill
Keyword(s):  
High Efficiency ◽  
Aerodynamic Characteristics ◽  
The Body ◽  
Design Parameters ◽  
Original Design ◽  
Tonal Noise ◽  
Experimental Performance ◽  
Expected Performance ◽  
Computational Fluid Dynamics Cfd ◽  
And Performance

A complete effort to redesign the aerodynamic characteristics of a single-stage pipeline compressor is presented. The components addressed are the impeller, diffuser region, and the volute. The innovation of this effort stems from the simultaneous inclusion of both the noise and aerodynamic performance as primary design parameters. The final detailed flange-to-flange analysis of the new components clearly shows that the operating range is extended and the tonal noise driven by the impeller is reduced. This is accomplished without sacrificing the existing high efficiency of the baseline machine. The body of the design effort uses both Computational Fluid Dynamics (CFD) and vibro-acoustics technology. The predictions are anchored by using the flange-to-flange analysis of the original design and its experimental performance data. By calculating delta corrections and assuming that these deltas are approximately the same for the new design, the expected performance is extrapolated.

scholarly journals Balancing and Simulation of a Double Crank-Rocker Engine Model for Optimum Reduction of Shaking Forces and Shaking Moments

2021 ◽  
Vol 8 (2) ◽  
pp. 237-245
Author(s):  
Anwr M. Albaghdadi ◽  
Masri B. Baharom ◽  
Shaharin A. Sualiman
Keyword(s):  
Dynamic Analysis ◽  
Objective Function ◽  
Conventional Method ◽  
Optimization Process ◽  
New Model ◽  
Engine Model ◽  
Design Variables ◽  
Driving Torque ◽  
Related Design ◽  
Shaking Moment

In this paper, a new configuration of Crank-Rocker (CR) model has been proposed by duplicating its mechanism. The method has been implemented to overcome vibration problem on a single-piston Crank-Rocker engine caused by system unbalance. The new method suggests combining conventional method of adding counterweights to reduce shaking forces and eliminating the inertial moments on system by implementing the new layout. A dynamic study of the new model is presented, then the objective function is derived and implemented to perform the optimization process. Related design variables and system constraints are introduced to determine attached counterweights optimized characteristics. For results validation, the simulation, dynamic analysis, and optimization process were conducted using ADAMS VIEW® software. The output results were presented and discussed to verify the validity of the suggested method. It was noticed that the method was very effective and has managed to reduce the total shaking forces by about 91%, shaking moment by about 66%; and the driving torque by 27%.

Structure Characteristic Analysis and Optimization Design for Microsatellite

2010 ◽  
Vol 431-432 ◽  
pp. 425-428
Author(s):  
Kan Zheng ◽  
Wen He Liao ◽  
Xiang Zhang
Keyword(s):  
Optimization Design ◽  
Plate Thickness ◽  
Fem Analysis ◽  
Optimization Process ◽  
Structure Characteristic ◽  
Characteristic Analysis ◽  
Design Variables ◽  
Mechanics Characteristic ◽  
Quadratic Programming Method ◽  
Panel Thickness

According to the structural layout and mechanics characteristic of microsatellite, the FEM was established reasonably. Base on the FEM analysis and its characteristics, the structure of microsatellite was optimization designed. In the optimization process, the optimization model was established with the design variables of aluminum panel thickness, core plate thickness and skeleton thickness, and subjected to stiffness, strength, displacement and size constraints. Then, used the sequential quadratic programming method for optimization analysis. The results of the optimization demonstrates that the weight of structure loss significantly, and the whole structure weight of the microsatellite loss 11%.Meanwhile, the iterative times of the optimization process is few, so it is very Meaningful and useful for actual project application.

Sign in / Sign up

Export Citation Format

Share Document