• Title/Summary/Keyword: Parametric algorithm

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Optimal Ball-end and Fillet-end Mills Selection for 3-Axis Finish Machining of Point-based Surface

  • Kayal, Prasenjit
    • International Journal of CAD/CAM
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    • v.7 no.1
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    • pp.51-60
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    • 2007
  • This paper presents an algorithm of optimal cutting tool selection for machining of the point-based surface that is defined by a set of surface points rather than parametric polynomial surface equations. As the ball-end and fillet-end mills are generally used for finish machining in a 3-axis computer numerical control machine, the algorithm is applicable for both cutters. The optimum tool would be as large as possible in terms of the cutter radius and/or corner radius which maximise (s) the material removal rate (i.e., minimise (s) the machining time), while still being able to machine the entire point-based surface without gouging any surface point. The gouging are two types: local and global. In this paper, the distance between the cutter bottom and surface points is used to check the local gouging whereas the shortest distance between the surface points and cutter axis is effectively used to check the global gouging. The selection procedure begins with a cutter from the tool library, which has the largest cutter radius and/or corner radius, and then adequacy of the point-density is checked to limit the accuracy of the cutter selection for the point-based surface within tolerance prior to the gouge checking. When the entire surface is gouge-free with a chosen cutting tool then the tool becomes the optimum cutting tool for a list of cutters available in the tool library. The effectiveness of the algorithm is demonstrated considering two examples.

Parametric identification of the Bouc-Wen model by a modified genetic algorithm: Application to evaluation of metallic dampers

  • Shu, Ganping;Li, Zongjing
    • Earthquakes and Structures
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    • v.13 no.4
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    • pp.397-407
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    • 2017
  • With the growing demand for metallic dampers in engineering practice, it is urgent to establish a reasonable approach to evaluating the mechanical performance of metallic dampers under seismic excitations. This paper introduces an effective method for parameter identification of the modified Bouc-Wen model and its application to evaluating the fatigue performance of metallic dampers (MDs). The modified Bouc-Wen model which eliminates the redundant parameter is used to describe the hysteresis behavior of MDs. Relations between the parameters of the modified Bouc-Wen model and the mechanical performance parameters of MDs are studied first. A modified Genetic Algorithm using real-integer hybrid coding with relative fitness as well as adaptive crossover and mutation rates (called RFAGA) is then proposed to identify the parameters of the modified Bouc-Wen model. A reliable approach to evaluating the fatigue performance of the MDs with respect to the Chinese Code for Seismic Design of Buildings (GB 50011-2010) is finally proposed based on the research results. Experimental data are employed to demonstrate the process and verify the effectiveness of the proposed approach. It is shown that the RFAGA is able to converge quickly in the identification process, and the simulation curves based on the identification results fit well with the experimental hysteresis curves. Furthermore, the proposed approach is shown to be a useful tool for evaluating the fatigue performance of MDs with respect to the Chinese Code for Seismic Design of Buildings (GB 50011-2010).

Process of pulsations of the spherical cavity in a liquid under the influence of ultrasonic vibrations

  • Kuznetsova, Elena L.;Starovoitov, Eduard I.;Vakhneev, Sergey;Kutina, Elena V.
    • Advances in aircraft and spacecraft science
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    • v.9 no.2
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    • pp.95-102
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    • 2022
  • The paper investigates the process of pulsation of a spherical cavity (bubble) in a liquid under the influence of a source of ultrasonic vibrations. The process of pulsation of a cavitation pocket in liquid is investigated. The Kirkwood-Bethe model was used to describe the motion. A numerical solution algorithm based on the Runge-Kutta-Felberg method of 4-5th order with adaptive selection of the integration step has been developed and implemented. It was revealed that if the initial bubble radius exceeds a certain value, then the bubble will perform several pulsations until the moment of collapse. The same applies to the case of exceeding the amplitude of ultrasonic vibrations of a certain value. The proposed algorithm makes it possible to fully describe the process of cavitation pulsations, to carry out comprehensive parametric studies and to evaluate the influence of various process parameters on the intensity of cavitation.

Multi-objective optimization of printed circuit heat exchanger with airfoil fins based on the improved PSO-BP neural network and the NSGA-II algorithm

  • Jiabing Wang;Linlang Zeng;Kun Yang
    • Nuclear Engineering and Technology
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    • v.55 no.6
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    • pp.2125-2138
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    • 2023
  • The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

Rapid construction delivery of COVID-19 special hospital: Case study on Wuhan Huoshenshan hospital

  • Wang, Chen;Yu, Liangcheng;Kassem, Mukhtar A.;Li, Heng;Wang, Ziming
    • Advances in Computational Design
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    • v.7 no.4
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    • pp.345-369
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    • 2022
  • Infectious disease emergency hospitals are usually temporarily built during the pneumonia epidemic with higher requirements regarding diagnosis and treatment efficiency, hygiene and safety, and infection control.This study aims to identify how the Building Information Modeling (BIM) + Industrialized Building System (IBS) approach could rapidly deliver an infectious disease hospital and develop site epidemic spreading algorithms. Coronavirus-19 pneumonia construction site spreading algorithm model mind map and block diagram of the construction site epidemic spreading algorithm model were developed. BIM+IBS approach could maximize the repetition of reinforced components and reduce the number of particular components. Huoshenshan Hospital adopted IBS and BIM in the construction, which reduced the workload of on-site operations and avoided later rectification. BIM+IBS integrated information on building materials, building planning, building participants, and construction machinery, and realized construction visualization control and parametric design. The delivery of Huoshenshan Hospital was during the most critical period of the Coronavirus-19 pneumonia epidemic. The development of a construction site epidemic spreading algorithm provided theoretical and numerical support for prevention. The agent-based analysis on hospital evacuation observed "arched" congestion formed at the evacuation exit, indicating behavioral blindness caused by fear in emergencies.

Time-Series Estimation based AI Algorithm for Energy Management in a Virtual Power Plant System

  • Yeonwoo LEE
    • Korean Journal of Artificial Intelligence
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    • v.12 no.1
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    • pp.17-24
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    • 2024
  • This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

Identification of Fuzzy Inference Systems Using a Multi-objective Space Search Algorithm and Information Granulation

  • Huang, Wei;Oh, Sung-Kwun;Ding, Lixin;Kim, Hyun-Ki;Joo, Su-Chong
    • Journal of Electrical Engineering and Technology
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    • v.6 no.6
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    • pp.853-866
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    • 2011
  • We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.

Efficient Point-to-Multipoint ABR Flow Control Algorithm based on Congestion Depth (폭주 정도의 측정을 통한 효율적인 점대 다중점 ABR 흐름 제어)

  • Chung, Hye-Ryoun;Chung, Tai-Myoung
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.9
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    • pp.3002-3010
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    • 2000
  • ATM forum defined several ATM oriented services such as ABR, VBR, CBR, UBR, and others. Among them, ABR service is considered as one of the most appropriate ones in the LAN environment. ABR controls network traffic by using RM cells according to ATM forum standard. In particular, the point-to-multipoint ABR service in general uses consolidation algorithms to solve feedback implosion at the branch point. Consolidation algorithms alleviate propagation delay and network congestion problem: thus, the efficiency of consolidation algorithm is closely related to the network performance. In this paper, we describe the limitation of existing consolidation algorithms based on thorough analysis, and then propose an algorithm that performs better than the existing algorithms. We show that the proposed algorithm improves network performance through a parametric simulation, In our simulation the performance measure is the cell rate which is controlled by exploiting the congestion depth. We also found that the proposed algorithm not only improves efficiency of network, but also eliminates the consolidation noise.

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Flood Frequency Analysis using SIR Algorithm (SIR 알고리즘을 이용한 홍수량 빈도해석에 관한 연구)

  • Moon, Kiho;Kyoung, Minsoo;Kim, Duckgil;Kawk, Jaewon;Kim, Hungsoo
    • Journal of Wetlands Research
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    • v.10 no.3
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    • pp.125-132
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    • 2008
  • Generally, stationary is considered as a basic assumption in frequency analysis. However, rainfall and flood discharge are changing due to the climate change and climate variability. Therefore, there is a new opinion that changing pattern of rainfall and flood discharge must be considered in frequency analysis. This study suggests the flood frequency analysis methodology using SIR algorithm which was developed from bootstrap could be used for considering climate change. Than is, SIR algorithm is selected for resampling method considering changing pattern of flood discharge and it has been used for resampling method with likelihood function. Resampled flood discharge data considering the increase of flood discharge pattern are used for parametric flood frequency analysis and this results are compared with frequency analysis results by Bootstrap and original observations. As the results, SIR algorithm shows the greatest flood discharge than other methods in all frequencies and this may reflect the increasing pattern of flood discharge due to the climate change and climate variability.

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Performance Evaluation of JADE-MUSIC Estimation for Indoor Environment

  • Satayarak, Peangduen;Rawiwan, Panarat;Chamchoy, Monchai;Supanakoon, Pichaya;Tangtisanon, Prakit
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1654-1659
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    • 2003
  • In this paper, the performance evaluation of the JADE-MUSIC estimation based on the indoor channel is presented. By means of the JADE-MUSIC algorithm, DOA and time delay can be obtained simultaneously. In the JADE-MUSIC method, the channel impulse response is first estimated from the received samples and then this impulse response is employed to estimate DOAs and time delays of multipath waves. Moreover, according to the JADE-MUSIC characteristics, it can work in cases when the number of impinging waves is more than the number of antenna elements, unlike the traditional parametric subspace-based method, such a case is not true. Therefore, we employ the JADE-MUSIC algorithm applying for the real indoor environment where is rich of the multipath propagation waves and can imply that the number of waves is very possibly higher than that of the array element. The experiment is carried out in our laboratory considered to be the real indoor environment. The performance of the JADE-MUSIC algorithm is evaluated in terms of the comparison between the simulation and experiment results by using the simulated channel model and the real indoor channel model, respectively. It is clear that the joint angle and delay estimation using the simulated channel model are in good agreement with the estimation using the real indoor channel model. Therefore, we can say that the JADE-MUSIC algorithm accomplishes the high performance to jointly estimate the angle and delay of the arriving signal for the indoor environment.

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