• Title/Summary/Keyword: structural optimal design

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A Study for Application of Active Magnetic Bearing using Quantitative Feedback Theory (Quantitative Feedback Theory를 이용한 능동 자기베어링의 적용 연구)

  • Lee, Gwan-Yeol;Lee, Hyeong-Bok;Kim, Yeong-Bae
    • Journal of the Korean Society for Precision Engineering
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    • v.18 no.11
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    • pp.107-115
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    • 2001
  • Most of rotating machineries supported by contact bearing accompany lowering efficiency, vibration and wear. Moreover, because of vibration, which is occurred in rotating shaft, they have the limits of driving speed and precision. The rotor system has parametric variations or external disturbances such as mass unbalance variations in long operation. Therefore, it is necessary to research about magnetic bearing, which is able to support the shaft without mechanical contact and to control rotor vibration without being affected by external disturbances or parametric changes. Magnetic bearing system in the paper is composed of position sensor, digital controller, actuating amplifier and electromagnet. This paper applied the robust control method using quantitative feedback theory (QFT) to control the magnetic bearing. It also proposed design skill of optimal controller, in case the system has structured uncertainty, unstructured uncertainty and disturbance. Reduction of vibration is verified at critical rotating speed even external disturbance exists. Unbalance response, a serious problem in rotating machinery, is improved by magnetic bearing using QFT algorithm.

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Hydraulic analysis of design alternatives to improve an industrial water distribution system (공업용수 배수관망시스템을 개선하기 위한 설계 대안의 수리해석)

  • Lim, Seong-Rin
    • Journal of Korean Society of Water and Wastewater
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    • v.29 no.1
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    • pp.97-106
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    • 2015
  • A CCTV inspection method has been widely used to assess sewer condition and performance, but Korea lacks a proper decision support system for prioritizing sewer repair and rehabilitation (R&R). The objective of this paper is to introduce the results that we have developed in the Sewer Condition Assessment and Rehabilitation Decision-making (SCARD) Program using MS-EXCEL. The SCARD-Program is based on a standardized defect score for sewer structural and hydraulic assessment. Priorities are ranked based on risk scores, which are calculated by multiplying the sewer severity scores by the environmental impacts. This program is composed of three parts, which are decision-making for sewer condition and performance assessment, decision-making for sewer R&R priority assessment, and decision-making for optimal budget allocation. The SCARD-Program is useful for decision-makers, as it enables them to assess the sewer condition and to prioritize sewer R&R within the limited annual budget. In the future, this program logic will applied to the GIS-based sewer asset management system in local governments.

The study on the safety inspection system model of the tower crane a construction site in Korea (국내 건설현장 타워크레인 안전진단 관리시스템 모델에 관한 연구)

  • Yeon, In-Soo;Seo, Jang-Hoon;Kang, Kyeong-Sik
    • Proceedings of the Safety Management and Science Conference
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    • 2006.11a
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    • pp.499-507
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    • 2006
  • The tower cranes are widely used in very useful construction machine the sites of constructing high-structure and have a structural sensitiveness. Therefore, the accidents have often happened due to the deficiency of laborer's understanding md lack of safety of structure. Till now, as we have research and studied above, we can properly protect accidents by construction equipments particularly crane as well as most disasters which occur frequently in construction site. The goal of this study is the safety inspection model of the tower crane a construction site, which preventible the collapse accident of tower crane which is constructed by using the correcting frame. In order to accomplish the goal of this study, the field survey, the reference investigation and the structure analysis were performed for the collapse accident of tower nine using the correcting data. This study will be proposed a build-up solutions about operating and release of safety constructions and researched about software safety estimation. Also, preventing safety problems of Tower Crane Construction site as applying safety estimation program and laws and regulations. As a result, The real time control of tower crane inspection system is implemented by to illustrate the application of the adopted optimal design model.

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A Study on the Safety Inspection System Model of The Tower Crane a Construction Site in Korea (국내 건설현장 타워크레인 안전진단 관리시스템 모델에 관한 연구)

  • Yoon, In-Soo;Kang, Kyung-Sik
    • Journal of the Korea Safety Management & Science
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    • v.9 no.1
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    • pp.37-49
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    • 2007
  • The tower cranes are widely used in very useful construction machine the sites of constructing high-structure and have a structural sensitiveness. Therefore, the accidents have often happened due to the deficiency of laborer's understanding and lack of safety of structure. Till now, as we have research and studied above, we can properly protect accidents by construction equipments particularly crane as well as most disasters which occur frequently in construction site. The goal of this study is the safety inspection model of the tower crane a construction site, which preventible the collapse accident of tower crane which is constructed by using the correcting frame. In order to accomplish the goal of this study, the field survey, the reference investigation and the structure analysis were performed for the collapse accident of tower crane using the correcting data. This study will be proposed a build-up solutions about operating and release of safety constructions and researched about software safety estimation. Also, preventing safety problems of Tower Crane Construction site as applying safety estimation program and laws and regulations. As a result, The real time control of tower crane inspection system is implemented by to illustrate the application of the adopted optimal design model.

Mechanical Properties of Steam Cured High-Strength Steel Fiber-Reinforced Concrete with High-Volume Blast Furnace Slag

  • Yang, Jun-Mo;Yoo, Doo-Yeol;Kim, You-Chan;Yoon, Young-Soo
    • International Journal of Concrete Structures and Materials
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    • v.11 no.2
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    • pp.391-401
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    • 2017
  • In this study, the effects of water-to-binder (W/B) ratio and replacement ratio of blast furnace slag (BFS) on the compressive strength of concrete were first investigated to determine an optimized mixture. Then, using the optimized high-strength concrete (HSC) mixture, hooked steel fibers with various aspect ratios and volume fractions were used as additives and the resulting mechanical properties under compression and flexure were evaluated. Test results indicated that replacement ratios of BFS from 50 to 60% were optimal in maximizing the compressive strength of steam-cured HSCs with various W/B ratios. The use of hooked steel fibers with the aspect ratio of 80 led to better mechanical performance under both compression and flexure than those with the aspect ratio of 65. By increasing the fiber aspect ratio from 65 to 80, the hooked steel fiber volume content could be reduced by 0.25% without any significant deterioration of energy absorption capacity. Lastly, complete material models of steel-fiber-reinforced HSCs were proposed for structural design from Lee's model and the RILEM TC 162-TDF recommendations.

Motion behavior research of liquid micro-particles filtration at various locations in a rotational flow field

  • Yan, Yan;Lin, Yuanzai;Cheng, Jie;Ni, Zhonghua
    • Structural Engineering and Mechanics
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    • v.62 no.2
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    • pp.163-170
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    • 2017
  • This study presents a particle-wall filtration model for predicting the particle motion behavior in a typical rotational flow field-filtration in blower system of cooker hood. Based on computational fluid dynamics model, air flow and particles has been simulated by Lagrangian-particle/ Eulerian-gas approaches and get verified by experiment data from a manufacturer. Airflow volume, particle diameter and local structure, which are related to the particle filtration has been studied. Results indicates that: (1) there exists an optimal airflow volume of $1243m^3/h$ related to the most appropriate filtration rate; (2) Diameter of particle is the significant property related to the filtration rate. Big size particles can represent the filtration performance of blower; (3) More than 86% grease particles are caught by impeller blades firstly, and then splashed onto the corresponding location of worm box internal wall. These results would help to study the micro-particle motion behavior and evaluate the filtration rate and structure design of blower.

Influence of neck width on the performance of ADAS device with diamond-shaped hole plates

  • Wu, Yingxiong;Lu, Jianfeng;Chen, Yun
    • Structural Engineering and Mechanics
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    • v.74 no.1
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    • pp.19-32
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    • 2020
  • Metallic energy-dissipation dampers are widely used in structures. They are comprised of an added damping and stiffness (ADAS) device with many parallel, diamond-shaped hole plates, the neck width of which is an important parameter. However, no studies have analyzed the neck width's influence on the ADAS device's performance. This study aims to better understand that influence by conducting a pseudo-static test on ADAS, with three different neck widths, and performing finite element analysis (FEA) models. Based on the FEA results and mechanical theory, a design neck width range was proposed. The results showed that when the neck width was within the specified range, the diamond-shaped hole plate achieved an ideal yield state with minimal stress concentration, where the ADAS had an optimal energy dissipation performance and the brittle shear fracture on the neck was avoided. The theoretical values of the ADAS yield loads were in good agreement with the test values. While the theoretical value of the elastic stiffness was lower than the test value, the discrepancy could be reduced with the proposed modified coefficient.

A novel reliability analysis method based on Gaussian process classification for structures with discontinuous response

  • Zhang, Yibo;Sun, Zhili;Yan, Yutao;Yu, Zhenliang;Wang, Jian
    • Structural Engineering and Mechanics
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    • v.75 no.6
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    • pp.771-784
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    • 2020
  • Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

Multi response optimization of surface roughness in hard turning with coated carbide tool based on cutting parameters and tool vibration

  • Keblouti, Ouahid;Boulanouar, Lakhdar;Azizi, Mohamed Walid.;Bouziane, Abderrahim
    • Structural Engineering and Mechanics
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    • v.70 no.4
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    • pp.395-405
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    • 2019
  • In the present work, the effects of cutting parameters on surface roughness parameters (Ra), tool wear parameters (VBmax), tool vibration (Vy) and material removal rate (MRR) during hard turning of AISI 4140 steel using coated carbide tool have been evaluated. The relationships between machining parameters and output variables were modeled using response surface methodology (RSM). Analysis of variance (ANOVA) was performed to quantify the effect of cutting parameters on the studied machining parameters and to check the adequacy of the mathematical model. Additionally, Multi-objective optimization based desirability function was performed to find optimal cutting parameters to minimize surface roughness, and maximize productivity. The experiments were planned as Box Behnken Design (BBD). The results show that feed rate influenced the surface roughness; the cutting speed influenced the tool wear; the feed rate influenced the tool vibration predominantly. According to the microscopic imagery, it was observed that adhesion and abrasion as the major wear mechanism.

Development of Prediction Model of Chloride Diffusion Coefficient using Machine Learning (기계학습을 이용한 염화물 확산계수 예측모델 개발)

  • Kim, Hyun-Su
    • Journal of Korean Association for Spatial Structures
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    • v.23 no.3
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    • pp.87-94
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    • 2023
  • Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.