scholarly journals Vibroacoustic Optimization Study for the Volute Casing of a Centrifugal Fan

2019 ◽  
Vol 9 (5) ◽  
pp. 859 ◽  
Author(s):  
Jianhua Zhang ◽  
Wuli Chu ◽  
Jinghui Zhang ◽  
Yi Lv
Keyword(s):  
Objective Function ◽  
Control Method ◽  
Weighted Average ◽  
Optimization Method ◽  
Centrifugal Fan ◽  
Noise Optimization ◽  
Design Variables ◽  
Back Panel ◽  
Panel Thickness ◽  
Vibrational Noise

A numerical optimization is presented to reduce the vibrational noise of a centrifugal fan volute. Minimal vibrational radiated sound power was considered as the aim of the optimization. Three separate parts of volute panel thickness (ST: the side panel thickness; BT: the back panel thickness; FT: the front panel thickness) were taken as the design variables. Then, a vibrational noise optimization control method for the volute casing was proposed that considered the influence of vibroacoustic coupling. The optimization method was mainly divided into three main parts. The first was based on the simulation of unsteady flow to the fan to obtain the vibrational noise source. The second used the design of experiments (DoE) method and a weighted-average surrogate model (radial basis function, or RBF) with three design variables related to the geometries of the three-part volute panel thickness, which was used to provide the basic mathematical model for the optimization of the next part. The third part, implementing the low vibrational noise optimization for the fan volute, applied single-objective (taking volute radiated acoustical power as the objective function) and multi-objective (taking the volute radiated acoustical power and volute total mass as the objective function) methods. In addition, the fan aerodynamic performance, volute casing surface fluctuations, and vibration response were validated by experiments, showing good agreement. The optimization results showed that the vibrational noise optimization method proposed in this study can effectively reduce the vibration noise of the fan, obtaining a maximum value of noise reduction of 7.3 dB. The optimization in this study provides an important technical reference for the design of low vibroacoustic volute centrifugal compressors and fans whose fluids should be strictly kept in the system without any leakage.

scholarly journals Vibro-Acoustic Optimization Study for the Volute Casing of a Centrifugal Fan

2018 ◽  
Author(s):  
Jianhua Zhang ◽  
Wuli Chu ◽  
Jinghui Zhang ◽  
Yi Lv
Keyword(s):  
Total Mass ◽  
Control Method ◽  
Target Function ◽  
Optimization Method ◽  
Aerodynamic Noise ◽  
Noise Component ◽  
Acoustic Coupling ◽  
Noise Optimization ◽  
Panel Thickness ◽  
Vibrational Noise

Concerning fan systems with an air pipe connecting air intake and a closed outlet, aerodynamic noise cannot be directly transmitted from the fan inlet and outlet to the outside. At this moment, the volute vibrational radiation noise induced casing surface vibration is the major noise component. The main factors affecting the fan vibrational noise are analyzed through theoretical derivation, then a vibrational noise optimization control method for the volute casing is proposed that considered the influence of vibro-acoustic coupling, taking the panel thickness of the volute (front-panel thickness [FT], side-panel thickness [ST], and back-panel thickness [BT]) as design variables, and the acoustical power of the volute surface and the total mass of the volute as the optimal target function. The optimization method is mainly divided into three main parts: the first was based on the simulation of unsteady flow of the fan to obtain the vibrational noise source; the second, using the design of experimental (DOE) method and the proposed numerical simulation of fluid-structure-acoustic coupling method to obtain the designing space, then the radical-based function (RBF) method is used to construct the approximate surrogate model instead of the simulation model previously mentioned, which was used to provide the basic mathematical model for the optimization of the next part; the third part, implementing the low vibrational noise optimization for the fan volute, applied the single-target (taking volute radiated acoustical power as the target function) and the multi-target (taking the volute radiated acoustical power and volute total mass as the target function) methods. In addition, the fan aerodynamic performance, volute casing surface fluctuations, and vibration response were validated by experiments, showing good agreement. It is of utmost importance that the dynamic pressure measurements and vibrational tests on the volute casing verify the accuracy of the numerical calculation. The optimization results showed that the vibrational noise optimization method proposed in this study can effectively reduce the vibration noise of the fan, obtaining a maximum value of noise reduction of 7.3 dB. The optimization identified in this paper provides a significant reference for the design of a low-vibrational-noise volute.

scholarly journals Topology Optimization of Hard-Coating Thin Plate for Maximizing Modal Loss Factors

Coatings ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 774
Author(s):  
Haitao Luo ◽  
Rong Chen ◽  
Siwei Guo ◽  
Jia Fu
Keyword(s):  
Topology Optimization ◽  
Objective Function ◽  
Composite Plates ◽  
Optimization Method ◽  
Hard Coating ◽  
Design Variables ◽  
Coating Composite ◽  
Damping Materials ◽  
Topology Optimization Method ◽  
Loss Factors

At present, hard coating structures are widely studied as a new passive damping method. Generally, the hard coating material is completely covered on the surface of the thin-walled structure, but the local coverage cannot only achieve better vibration reduction effect, but also save the material and processing costs. In this paper, a topology optimization method for hard coated composite plates is proposed to maximize the modal loss factors. The finite element dynamic model of hard coating composite plate is established. The topology optimization model is established with the energy ratio of hard coating layer to base layer as the objective function and the amount of damping material as the constraint condition. The sensitivity expression of the objective function to the design variables is derived, and the iteration of the design variables is realized by the Method of Moving Asymptote (MMA). Several numerical examples are provided to demonstrate that this method can obtain the optimal layout of damping materials for hard coating composite plates. The results show that the damping materials are mainly distributed in the area where the stored modal strain energy is large, which is consistent with the traditional design method. Finally, based on the numerical results, the experimental study of local hard coating composites plate is carried out. The results show that the topology optimization method can significantly reduce the frequency response amplitude while reducing the amount of damping materials, which shows the feasibility and effectiveness of the method.

Optimum Design of a Planar Robotic Manipulator

1996 ◽  
Author(s):  
D. F. Berner ◽  
J. A. Snyman
Keyword(s):  
Objective Function Value ◽  
Substantial Reduction ◽  
Weighted Average ◽  
Vertical Motion ◽  
Robotic Manipulators ◽  
Optimization Method ◽  
Constrained Problem ◽  
Design Variables ◽  
Function Formulation ◽  
Optimization Methodology

Abstract A general optimization methodology for the optimal design of robotic manipulators is presented and illustrated by its application to a realistic and practical three link re volute-joint planar manipulator. The end-effector carries out a prescribed vertical motion for which the weighted average torque requirement from electrical driving motors is minimized with respect to positional and dimensional design variables. In addition to simple physical bounds placed on the variables the maximum deliverable torques of the driving motors represent further constraints on the system. The optimization is carried out via a penalty function formulation of the constrained problem to which a proven robust unconstrained optimization method is applied. The problem of degeneracy or lock-up, which may occur for certain choices of design variables, is successfully dealt with by means of a specially proposed procedure in which a high artificial objective function value is computed for such “lock-up trajectories”. Designs are obtained that represent substantial reduction in torque requirement in comparison to that of arbitrarily chosen practical designs.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

Jaya algorithm based optimum design of reinforced concrete retaining walls under dynamic loads

2021 ◽  
Vol 7 (2) ◽  
pp. 64
Author(s):  
Nur Eroğlu ◽  
Sena Aral ◽  
Sinan Melih Nigdeli ◽  
Gebrail Bekdaş
Keyword(s):  
Reinforced Concrete ◽  
Objective Function ◽  
Retaining Wall ◽  
Unit Length ◽  
Optimization Method ◽  
Dynamic Loads ◽  
Jaya Algorithm ◽  
Design Variables ◽  
Projection Length ◽  
Static Conditions

In this study, the optimum dimensioning of a reinforced concrete retaining wall that meets the safety conditions under static and dynamic loads in terms of cost has been performed using Jaya algorithm, which is one of the metaheuristic algorithms. In the optimization process, reinforced concrete design rules and ground stress, sliding and overturn tests have been determined as design constraints for the safe design of the retaining wall. While 5 cross-section dimensions of the retaining wall are defined as the design variable, the objective function is targeted as the total cost per unit length of the retaining wall. In the study, optimum results are also presented by examining the changes of the toe projection length of the retaining wall, which is one of the design variables, narrowing between 0.2-10 m. The design variables minimizing the objective function were found via Jaya algorithm that have single-phase. In addition to achieving optimum dimensioning results in terms of safety and cost with the optimization method used as a result of the reinforced concrete design made by applying the rules of the regulation on buildings to be constructed in earthquake zones, the change in cost in seismic and static conditions was examined.

Design Optimization of Forward-Curved Blades Centrifugal Fan With Response Surface Method

2004 ◽  
Author(s):  
Seoung-Jin Seo ◽  
Kwang-Yong Kim
Keyword(s):  
Response Surface ◽  
Flow Rate ◽  
Stokes Equations ◽  
Computing Time ◽  
Three Dimensional ◽  
Optimization Method ◽  
Design Flow ◽  
Navier Stokes ◽  
Centrifugal Fan ◽  
Design Variables

This paper presents the response surface optimization method using three-dimensional Navier-Stokes analysis to optimize the shape of a forward-curved blades centrifugal fan. For numerical analysis, Reynolds-averaged Navier-Stokes equations with k-ε turbulence model are discretized with finite volume approximations. In order to reduce huge computing time due to a large number of blades in forward-curved blades centrifugal fan, the flow inside of the fan is regarded as steady flow by introducing the impeller force models. Three geometric variables, i.e., location of cut off, radius of cut off, and width of impeller, and one operating variable, i.e., flow rate, were selected as design variables. As a main result of the optimization, the efficiency was successfully improved. And, optimum design flow rate was found by using flow rate as one of design variables. It was found that the optimization process provides reliable design of this kind of fans with reasonable computing time.

Parameter Optimization of a Static Micro-Mixer Using a Sequential Approximate Optimization Method

2006 ◽  
Vol 306-308 ◽  
pp. 471-476
Author(s):  
Seok Yoon Han ◽  
J.S. Maeng ◽  
S.H. Kim ◽  
J.Y. Park
Keyword(s):  
Objective Function ◽  
Cantilever Beam ◽  
Parameter Optimization ◽  
Optimization Method ◽  
Sequential Approximate Optimization ◽  
Mixing Efficiency ◽  
Approximate Optimization ◽  
Design Variables ◽  
Anova Table ◽  
Micro Mixer

Parameter optimization of a static micro-mixer with a cantilever beam was accomplished for maximizing mixing efficiency using a sequential approximate optimization method. The objective function and design variables were chosen as mixing index, and the length and the angle measured from the horizontal of the cantilever beam, respectively. The Optimization problem of the mixer was considered as a series of sub-problems. Approximation to solve the sub-problems was performed by response surface methodology. To verify the reliability and the accuracy of the approximated objective function, ANOVA table and variable selection method were implemented, respectively. It was verified that the sequential approximate optimization method worked very well, and the mixing efficiency was significantly improved compared with the initial design.

An Efficient Bi-Objective Optimization Workflow Using the Distributed Quasi-Newton Method and Its Application to Field Development Optimization

2021 ◽  
Author(s):  
Yixuan Wang ◽  
Faruk Alpak ◽  
Guohua Gao ◽  
Chaohui Chen ◽  
Jeroen Vink ◽  
...  
Keyword(s):  
Objective Function ◽  
Information Sharing ◽  
Optimization Problems ◽  
Weighted Average ◽  
Optimization Method ◽  
Objective Functions ◽  
Weighting Factors ◽  
Derivative Free ◽  
Simulation Results ◽  
Quasi Newton

Abstract Although it is possible to apply traditional optimization algorithms to determine the Pareto front of a multi-objective optimization problem, the computational cost is extremely high, when the objective function evaluation requires solving a complex reservoir simulation problem and optimization cannot benefit from adjoint-based gradients. This paper proposes a novel workflow to solve bi-objective optimization problems using the distributed quasi-Newton (DQN) method, which is a well-parallelized and derivative-free optimization (DFO) method. Numerical tests confirm that the DQN method performs efficiently and robustly. The efficiency of the DQN optimizer stems from a distributed computing mechanism which effectively shares the available information discovered in prior iterations. Rather than performing multiple quasi-Newton optimization tasks in isolation, simulation results are shared among distinct DQN optimization tasks or threads. In this paper, the DQN method is applied to the optimization of a weighted average of two objectives, using different weighting factors for different optimization threads. In each iteration, the DQN optimizer generates an ensemble of search points (or simulation cases) in parallel and a set of non-dominated points is updated accordingly. Different DQN optimization threads, which use the same set of simulation results but different weighting factors in their objective functions, converge to different optima of the weighted average objective function. The non-dominated points found in the last iteration form a set of Pareto optimal solutions. Robustness as well as efficiency of the DQN optimizer originates from reliance on a large, shared set of intermediate search points. On the one hand, this set of searching points is (much) smaller than the combined sets needed if all optimizations with different weighting factors would be executed separately; on the other hand, the size of this set produces a high fault tolerance. Even if some simulations fail at a given iteration, DQN’s distributed-parallel information-sharing protocol is designed and implemented such that the optimization process can still proceed to the next iteration. The proposed DQN optimization method is first validated on synthetic examples with analytical objective functions. Then, it is tested on well location optimization problems, by maximizing the oil production and minimizing the water production. Furthermore, the proposed method is benchmarked against a bi-objective implementation of the MADS (Mesh Adaptive Direct Search) method, and the numerical results reinforce the auspicious computational attributes of DQN observed for the test problems. To the best of our knowledge, this is the first time that a well-parallelized and derivative-free DQN optimization method has been developed and tested on bi-objective optimization problems. The methodology proposed can help improve efficiency and robustness in solving complicated bi-objective optimization problems by taking advantage of model-based search optimization algorithms with an effective information-sharing mechanism.

Optimization of Support Locations of Beam and Plate Structures Under Self-Weight by Using a Sprung Structure Model

2009 ◽  
Vol 131 (2) ◽  
Author(s):  
Gang-Won Jang ◽  
Ho Seong Shim ◽  
Yoon Young Kim
Keyword(s):  
Objective Function ◽  
Optimization Method ◽  
Extensive Study ◽  
Plate Structures ◽  
Design Variables ◽  
Gradient Based ◽  
Elastically Supported ◽  
Structural Behaviors ◽  
Important Design

To find support locations minimizing uneven deformation is an important design issue in a large plate under self-weight. During the imprinting process of LCD panels, for instance, a large variation in the deflection of an LCD panel due to its self-weight deteriorates the quality of nanoscale imprinted lines. Motivated by this need, this research aims to develop an efficient gradient-based optimization method of finding optimal support locations of beam or plate structures under self-weight. To use a gradient-based algorithm, the support locating problem is formulated with continuous design variables. In this work, a beam or plate structure is assumed to be supported by a set of distributed springs, which are attached to all nodes of the discretized model of a given structure. The spring stiffness is made to vary continuously as a function of the design variable in which unsupported and supported states of a structure are represented with springs having limit stiffness values. Because elastically supported structures exhibit considerably different structural behaviors from structures without elastic supports, it is difficult to select an objective function fulfilling the design goal and ensuring convergence to distinct supported-unsupported states without ambiguous intermediate states. To address this issue, an extensive study is conducted and an appropriate objective function is then suggested. An optimization formulation using the objective function is presented and several numerical problems are considered to check the validity and usefulness of the developed formulation.

Pretension Optimization Method for Complex Cablenet System

2014 ◽  
Vol 574 ◽  
pp. 143-146
Author(s):  
Guo Qiang You ◽  
Ying Bai Xie
Keyword(s):  
Objective Function ◽  
Axial Symmetry ◽  
Mathematic Model ◽  
Optimization Method ◽  
Gradient Algorithm ◽  
Matrix Analysis ◽  
Analysis Method ◽  
Design Variables ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient

Based on balance matrix analysis method and considered the evenness of pretension distribution as objective function, a pretension optimization method is proposed for complex cablenet system of large span structure. In this method, the whole cablenet system is firstly divided into several groups according to its axial symmetry to simplify its balance matrix, and then balance matrix analysis method is used to analyze balance matrix of grouped cablenet system. Next, the corresponding optimum mathematic model for grouped cablenet system can be established with pretension solutions coefficients as design variables and evenness of pretension distribution as objective function. Finally, generalized reduced gradient algorithm is used to solve the optimum mathematic model of an example, and the result is satisfactory.

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