Optimization Design of an Axial-Flow Fan Used in Local Ventilation in Mining Industry

2011 ◽  
Author(s):  
Dhaval Desai ◽  
Jiang Zhou
Keyword(s):  
Optimization Design ◽  
Optimization Technique ◽  
Mining Industry ◽  
Axial Flow ◽  
Optimization Method ◽  
Low Noise ◽  
Design Constraint ◽  
Engineering Research ◽  
Blade Element Theory ◽  
Local Ventilation

In a world where the increasing demand on developing energy-efficient systems is probably the most stringent design constraint, the trend in engineering research in recent years has been to optimize the existing technologies rather than to implement new ones. The present work addresses a robust axial-type fan design technique developed using an optimization technique. A fan is indispensable equipment for primary and local ventilation in mining industries. We always pursue the fan with high working efficiency and low noise. In this paper, an optimization method is developed to improve the pneumatic properties of the fan based on the blade element theory. A new type of fan used in local ventilation is designed with the help of computer. It is shown that the new design enhanced the efficient up to 88%. Numerical analysis is also conducted to validate the optimization design results.

Based on ANSYS APDL Language Moving Blade Adjustable Axial Flow Fan Optimization Design

2013 ◽  
Vol 655-657 ◽  
pp. 435-444
Author(s):  
Dong Xia Niu ◽  
Xian Yi Meng ◽  
Ai Hua Zhu
Keyword(s):  
Optimization Design ◽  
Lift Coefficient ◽  
Axial Flow ◽  
Optimization Method ◽  
Structure Parameters ◽  
Continuous Variables ◽  
State Variables ◽  
Axial Flow Fan ◽  
Installation Angle ◽  
Design Variables

In the case of multiple loading conditions, a moving blade adjustable axial flow fan structure parameters are optimized by ANSYS. It is to achieve greater efficiency and less noise for the optimization goal. For different conditions, establish efficiency, noise comprehensive objective function using weighted coefficient method. Select impeller diameter, the wheel hub ratio, leaf number, lift coefficient, speed as design variables, Choose blade installation Angle, the wheel hub place dynamic load coefficient, cascade consistency, allowable safety coefficient as optimization of the state variables. Design variables contain continuous variables and discrete variable. Through the optimization method, we get the optimal structure parameters finally. And at the same time get the corresponding optimal blade installation Angle,under different working conditions.

scholarly journals Fully Parametric Optimization Designs of Wing Components

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zhendong Hu ◽  
Ju Qiu ◽  
Fa Zhang
Keyword(s):  
Optimization Design ◽  
Systematic Approach ◽  
Parametric Optimization ◽  
Structural Strength ◽  
Optimization Technique ◽  
Optimization Method ◽  
Operating Costs ◽  
Traditional Design ◽  
Structure Changes ◽  
Wing Optimization

An optimization technique called shape-linked optimization, which is different from the traditional optimization method, is introduced in this paper. The research introduces an updated wing optimization design in an effort to adapt to continuous structure changes and shapes while optimizing for a lighter weight of the structure. The changing tendencies of the thickness of wing skins and the cross-section areas of the wing beams are fitted to continuous polynomial functions, whose coefficients are designed as variables, which is a different engineering approach from the size variants of the thickness and the area in the traditional optimization. The structural strength, stiffness, and stability are constraints. Firstly, this research unearths the significance of utilizing a modernized optimization process which alters the production of the traditional 12 or over 12 segment wing design and applies new approaches and methods with less variables that contribute to expedited design cycles, decreased engineering and manufacturing expenditures, and a lighter weight aircraft with lower operating costs than the traditional design for the operators. And then, this paper exemplifies and illustrates the validity of the above claims in a detailed and systematic approach by comparing traditional and modernized optimization applications with a two-beam wing. Finally, this paper also proves that the new optimized structure parameters are easier than the size optimization to process and manufacture.

Design Optimization of Axial-Flow Pump Blades Based on iSIGHT

2015 ◽  
Author(s):  
Lijian Shi ◽  
Fangping Tang ◽  
Rongsheng Xie ◽  
Lilong Qi ◽  
Zhengdong Yang
Keyword(s):  
Numerical Simulation ◽  
Numerical Optimization ◽  
Optimization Design ◽  
Axial Flow ◽  
Optimization Method ◽  
Simulation Software ◽  
Multidisciplinary Optimization ◽  
Design Parameters ◽  
Axial Flow Pump ◽  
Flow Pump

This paper research the influence of cascade dense degree and airfoil placed angle on hydralic performance of axial flow pump blades. Which combines the numerical optimization technology with the advanced CFD simulation technique, replaces designers’ experience by mathematical models for controlling of the blade design direction. Finally, a platform for of the optimization design of axial-flow pump blades is built in this paper. The platform which based on the multidisciplinary optimization software iSIGHT is to design and optimize the axial flow blades. The automatic optimization design platform for axial-flow blade was established, in which the parameterization modeling, mesh, flow computation and numerical optimization are combined together. The use of the numerical simulation software CFD for disciplinary analysis improved the reliability and accuracy of the results of the prediction model. Found the approximate geometric design parameters of the design conditions based on numerical simulation, and the technology of numerical optimization was used for constrained optimized analysis based on these parameters. Optimized impeller efficiency improved about 0.7% while satisfying the constraint condition, shows that the optimization method for axial flow blade base on iSIGHT platform is effective and feasible. Meanwhile, the optimization method can greatly shorten the design cycle, reduce design cost optimization.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

Parameter study and optimization design of a hat oblique tunnel portal

2021 ◽  
pp. 095440972110140
Author(s):  
Zijian Guo ◽  
Tanghong Liu ◽  
Wenhui Li ◽  
Yutao Xia
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Pareto Front ◽  
Optimization Problem ◽  
Optimization Method ◽  
Design Parameters ◽  
Parameter Study ◽  
Buffer Structure ◽  
Tunnel Entrance ◽  
The Ideal

The present work focuses on the aerodynamic problems resulting from a high-speed train (HST) passing through a tunnel. Numerical simulations were employed to obtain the numerical results, and they were verified by a moving-model test. Two responses, [Formula: see text] (coefficient of the peak-to-peak pressure of a single fluctuation) and[Formula: see text] (pressure value of micro-pressure wave), were studied with regard to the three building parameters of the portal-hat buffer structure of the tunnel entrance and exit. The MOPSO (multi-objective particle swarm optimization) method was employed to solve the optimization problem in order to find the minimum [Formula: see text] and[Formula: see text]. Results showed that the effects of the three design parameters on [Formula: see text] were not monotonous, and the influences of[Formula: see text] (the oblique angle of the portal) and [Formula: see text] (the height of the hat structure) were more significant than that of[Formula: see text] (the angle between the vertical line of the portal and the hat). Monotonically decreasing responses were found in [Formula: see text] for [Formula: see text] and[Formula: see text]. The Pareto front of [Formula: see text] and[Formula: see text]was obtained. The ideal single-objective optimums for each response located at the ends of the Pareto front had values of 1.0560 for [Formula: see text] and 101.8 Pa for[Formula: see text].

Well Placement Technique and Production Optimization for Mature Field - A Case Study of L-X Field

2020 ◽  
Vol 46 ◽  
pp. 168-179
Author(s):  
Patrick Nwafor ◽  
Kelani Bello
Keyword(s):  
Oil And Gas ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Oil And Gas Industry ◽  
Optimization Method ◽  
Simulation Software ◽  
Production Optimization ◽  
Direct Optimization ◽  
Well Placement ◽  
Local Optimal Solution

A Well placement is a well-known technique in the oil and gas industry for production optimization and are generally classified into local and global methods. The use of simulation software often deployed under the direct optimization technique called global method. The production optimization of L-X field which is at primary recovery stage having five producing wells was the focus of this work. The attempt was to optimize L-X field using a well placement technique.The local methods are generally very efficient and require only a few forward simulations but can get stuck in a local optimal solution. The global methods avoid this problem but require many forward simulations. With the availability of simulator software, such problem can be reduced thus using the direct optimization method. After optimization an increase in recovery factor of over 20% was achieved. The results provided an improvement when compared with other existing methods from the literatures.

scholarly journals Mechanical properties optimization of the steering column based on multi-objective optimization design

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668294 ◽  
Author(s):  
Si Chen ◽  
Zhaohui Wang ◽  
Mi Lv
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Optimization Design ◽  
Strain Difference ◽  
Optimization Method ◽  
Equivalent Strain ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Multi Objective ◽  
Initial Results

The mechanical properties of the steering column have a significant influence on the comfort and stability of a vehicle. In order for the mechanical properties to be improved, the rotary swaging process of the steering column is studied in this article. The process parameters, including axial feed rate, hammerhead speed, and hammerhead radial reduction, are systematically analyzed and optimized based on a multi-objective optimization design. The response surface methodology and the genetic algorithm are employed for optimal process parameters to be obtained. The maximum damage value, the maximum forming load, and the equivalent strain difference obtained with the optimal process parameters are, respectively, decreased by 30.09%, 7.44%, and 57.29% compared to the initial results. The comparative results present that the quality of the steering column is improved. The torque experiments and fatigue experiments are conducted with the optimal steering column. The maximum torque is measured to be 260 NM, and the service life is measured to be 2 weeks (40 NM, 2500 times), which are, respectively, increased by 8.3% and 8.69% compared to the initial results. The above results display that the mechanical properties of the steering column are optimized to verify the feasibility of the multi-objective optimization method.

scholarly journals Low Power Digital Multimedia Telecommunication Designs

VLSI Design ◽  
2001 ◽  
Vol 12 (3) ◽  
pp. 301-315 ◽  
Author(s):  
Koon-Shik Cho ◽  
Jun-Dong Cho
Keyword(s):  
Motion Estimation ◽  
Low Power ◽  
Communication Systems ◽  
Matched Filter ◽  
Optimization Technique ◽  
Low Power Design ◽  
Multimedia Systems ◽  
Wireless Multimedia ◽  
Design Constraint ◽  
Power Capability

The increasing prominence of wireless multimedia systems and the need to limit power capability in very-high density VLSI chips have led to rapid and innovative developments in low-power design. Power reduction has emerged as a significant design constraint in VLSI design. The need for wireless multimedia systems leads to much higher power consumption than traditional portable applications. This paper presents possible optimization technique to reduce the energy consumption for wireless multimedia communication systems. Four topics are presented in the wireless communication systems subsection which deal with architectures such as PN acquisition, parallel correlator, matched filter and channel coding. Two topics include the IDCT and motion estimation in multimedia application.These topics consider algorithms and architectures for low power design such as using hybrid architecture in PN acquisition, analyzing the algorithm and optimizing the sample storage in parallel correlator, using complex matched filter that analog operational circuits controlled by digital signals, adopting bit serial arithmetic for the ACS operation in viterbi decoder, using CRC to adaptively terminate the SOVA iteration in turbo decoder, using codesign in RS codec, disabling the processing elements as soon as the distortion values become great than the minimum distortion value in motion estimation, and exploiting the relative occurrence of zero-valued DCT coefficient in IDCT.

Probabilistic Optimal Design Using Successive Surrogate Probability Density Functions

1990 ◽  
Author(s):  
R. J. Eggert ◽  
R. W. Mayne
Keyword(s):  
Probability Density ◽  
Optimization Method ◽  
Probability Density Functions ◽  
Density Functions ◽  
Matching Method ◽  
Design Constraint ◽  
New Approach ◽  
Function Formulation ◽  
The Moment ◽  
Theoretical Considerations

Abstract Probabilistic optimization using the moment matching method and the simulation optimization method are discussed and compared to conventional deterministic optimization. A new approach based on successively approximating probability density functions, using recursive quadratic programming for the optimization process, is described. This approach incorporates the speed and robustness of analytical probability density functions and improves accuracy by considering simulation results. Theoretical considerations and an example problem illustrate the features of the approach. The paper closes with a discussion of an objective function formulation which includes the expected cost of design constraint failure.

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