• International Journal of Automotive Technology
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• 제8권1호
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• pp.75-82
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• 2007

This paper presents practical work on the reduction of gear whine noise. In order to identify the source of the gear whine noise, transfer paths are searched and analyzed by operational deflection shape analysis and experimental modal analysis. It was found that gear whine noise has an air-borne noise path instead of structure-borne noise path. The main sources of air-borne noise were the two global modes caused by the resonance of an axle system. These modes created a vibro-acoustic noise problem. Vibro-acoustic noise can be reduced by controlling the vibration of the noise source. The vibration of noise source is controlled by the modification of structure to avoid the resonance or to reduce the excitation force. In the study, the excitation force of the axle system is attenuated by changing the tooth profile of the hypoid gear. The modification of the tooth profile yields a reduction of transmission error, which is correlated to the gear whine noise. Finally, whine noise is reduced by 10 dBA.

• Structural Engineering and Mechanics
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• 제87권3호
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• pp.221-229
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• 2023

Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.

• 대한기계학회논문집B
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• 제28권5호
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• pp.560-568
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• 2004

We performed the numerical study on the characteristics of the 3-D airflow and dynamic cross contamination in the photolithography process cleanroom. The nonunifurmity, the deflection angle and the global cross contamination were used for analyzing the characteristics and performances of cleanroom. From the numerical results, we knew that the airflow characteristics of the cleanrooms are largely affected by the porosity of panel and the adjustment of dampers and the global cross contamination varies with the location of source and the passage of time through the concentration ratio.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.151-156
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• 2003

We performed the numerical study on the characteristics of the airflow and cross contamination in the photolithography process cleanroom. The nonuniformity, the deflection angle and the global cross contamination were used for analyzing the characteristics and performances of cleanroom. We knew that the airflow characteristics of the cleanrooms are largely affected by the porosity of panel and the adjustment of dampers. And the numerical result showed that the global cross contamination varies with the location of source and the passage of time.

• Steel and Composite Structures
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• 제21권4호
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• pp.805-827
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• 2016

A new type of precast CFST column to RC beam braced frame is proposed in this paper. A series of shake table tests were conducted to excite a one-third scale six-story model for investigating the global seismic performance of this type of structure against earthquake actions. Particular emphasis was given to its dynamic property, global seismic responses and failure path. Correspondingly, a numerical model built on the basis of fiber-beam-element model, multi-layer shell model and element-deactivation method was developed to simulate the seismic performance of the prototype structure. Numerical results were compared with the measured values from shake table tests to verify the validity and reliability of the numerical model. The results demonstrated that the proposed novel precast CFST column to RC beam braced frame performs excellently under strong earthquake excitations; the "strong CFST column-weak RC beam" and "strong connection-weak member" anti-seismic design principles can be easily achieved; the maximum deflections of precast CFSTC-RCB braced frame satisfied the deflection limitations proposed in national code; the numerical model can properly simulate the dynamic property and responses of the precast CFSTC-RCB braced frame that are highly concerned in engineering practice.

• International Journal of Aeronautical and Space Sciences
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• 제17권1호
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• pp.29-36
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• 2016

Tensairity girder is a light weight inflatable fabric structural concept which can be used in road emergency transportation. It uses low pressure air to stabilize compression elements against buckling. With the purpose of obtaining the comprehensive target of minimum deflection and weight under ultimate load, the cross-section and the inner pressure of tensairity girder was optimized in this paper. The Variable Complexity Modeling (VCM) method was used in this paper combining the Kriging approximate method with the Finite Element Analysis (FEA) method, which was implemented by ABAQUS. In the Kriging method, the sample points of the surrogate model were outlined by Design of Experiment (DOE) technique based on Optimal Latin Hypercube. The optimization framework was constructed in iSIGHT with a global optimization method, Multi-Island Genetic Algorithm (MIGA), followed by a local optimization method, Sequential Quadratic Program (SQP). The result of the optimization gives a prominent conceptual design of the tensairity girder, which approves the solution architecture of VCM is feasible and efficient. Furthermore, a useful trend of sensitivity between optimization variables and responses was performed to guide future design. It was proved that the inner pressure is the key parameter to balance the maximum Von Mises stress and deflection on tensairity girder, and the parameters of cross section impact the mass of tensairity girder obviously.

• 한국생산제조학회지
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• 제21권6호
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• pp.954-960
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• 2012

Nowadays, rapidly changing and unstable global economic environments request a lot of roles to engineers. In this situation, product should be designed to make more profit by cost down and to satisfy distinguished performance comparing to other competitive ones. In this research, the optimization design of the industrial robot casting will be done. The weight and deflection have to be reduced as objective functions and stress has to be constrained under some constant value. To reduce time cost, CCD (Central Composite Design) will be used to make experimental design. And RSM (Response Surface Methodology) will be taken to make regression model for objective functions and constraint function. Finally, optimization will be done with Genetic Algorithm. In this problem, the objective functions are multiple, so NSGA-II which is brilliant and efficient for such a problem will be used. For the solution quality check, the diversity between Pareto solutions will be also checked.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.651-656
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• 2007

Changes in measured structural responses induced by a damage could be significantly smaller than those by environmental effects such as temperature and temperature gradients. It is highly desirable to develop a methodology to distinguish the changes due to the structural damage from those by the environmental variations. In this study, a novel method to extract the damage-induced deflection under temperature variations is presented using the outlier analysis on the deflections obtained using the modal flexibility matrices. The main idea is that temperature change in a bridge would produce global increase or decrease in deflections over the whole bridge while structural damages may cause local variations in deflections near the damage locations. Hence, the correlation between the deflection measurements may show high abnormality near the damage locations. A series of laboratory tests were carried out on a bridge model with a steel box-girder for 14 days. It has been found that the damage existence assessment and localization can carried out for a case with relatively small damage under the temperature variations

• Structural Engineering and Mechanics
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• 제66권3호
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• pp.399-409
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• 2018

This paper demonstrates the potential application of machine learning algorithms for approximate prediction of the load and deflection capacities of the novel type of Laced Steel Concrete-Composite (LSCC) beams proposed by Anandavalli et al. (Engineering Structures 2012). Initially, global and local responses measured on LSCC beam specimen in an experiment are used to validate nonlinear FE model of the LSCC beams. The data for the machine learning algorithms is then generated using validated FE model for a range of values of the identified sensitive parameters. The performance of four well-known machine learning algorithms, viz., Support Vector Regression (SVR), Minimax Probability Machine Regression (MPMR), Relevance Vector Machine (RVM) and Multigene Genetic Programing (MGGP) for the approximate estimation of the load and deflection capacities are compared in terms of well-defined error indices. Through relative comparison of the estimated values, it is demonstrated that the algorithms explored in the present study provide a good alternative to expensive experimental testing and sophisticated numerical simulation of the response of LSCC beams. The load carrying and displacement capacity of the LSCC was predicted well by MGGP and MPMR, respectively.

• Steel and Composite Structures
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• 제42권2호
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• pp.209-219
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• 2022

Offshore platforms in seismically active areas must be designed to survive in the face of intense earthquakes without a global structural collapse. This paper scrutinizes the seismic performance of a newly designed and established jacket type offshore platform situated in the entrance of the Gulf of Suez region based on the API-RP2A normalized response spectra during seismic events. A nonlinear finite element model of a typical jacket type offshore platform is constructed taking into consideration the effect of structure-soil-interaction. Soil properties at the site were manipulated to generate the pile lateral soil properties in the form of load deflection curves, based on API-RP2A recommendations. Dynamic characteristics of the offshore platform, the response function, output power spectral density and transfer functions for different elements of the platform are discussed. The joints deflection and acceleration responses demands are presented. It is generally concluded that consideration of the interaction between structure, piles and soil leads to higher deflections and less stresses in platform elements due to soil elasticity, nonlinearity, and damping and leads to a more realistic platform design. The earthquake-based analysis for offshore platform structure is essential for the safe design and operation of offshore platforms.