• Title/Summary/Keyword: Statistical Energy Analysis

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Wave Transmission Analysis of Semi-infinite Mindlin Plates Coupled at an Arbitrary Angle (임의의 각으로 연성된 반무한 Mindlin 판의 파동전달해석)

  • Park, Young-Ho
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.24 no.12
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    • pp.999-1006
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    • 2014
  • Mindlin plate theory includes the shear deformation and rotatory inertia effects which cannot be negligible as exciting frequency increases. The statistical methods such as energy flow analysis(EFA) and statistical energy analysis(SEA) are very useful for estimation of structure-borne sound of various built-up structures. For the reliable vibrational analysis of built-up structures at high frequencies, the energy transfer relationship between out-of-plane waves and in-plane waves exist in Mindlin plates coupled at arbitrary angles must be derived. In this paper, the new wave transmission analysis is successfully performed for various energy analyses of Mindlin plates coupled at arbitrary angles.

Statistical Evaluation of Fracture Characteristics of RPV Steels in the Ductile-Brittle Transition Temperature Region

  • Kang, Sung-Sik;Chi, Se-Hwan;Hong, Jun-Hwa
    • Nuclear Engineering and Technology
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    • v.30 no.4
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    • pp.364-376
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    • 1998
  • The statistical analysis method was applied to the evaluation of fracture toughness in the ductile-brittle transition temperature region. Because cleavage fracture in steel is of a statistical nature, fracture toughness data or values show a similar statistical trend. Using the three-parameter Weibull distribution, a fracture toughness vs. temperature curve (K-curve) was directly generated from a set of fracture toughness data at a selected temperature. Charpy V-notch impact energy was also used to obtain the K-curve by a $K_{IC}$ -CVN (Charpy V-notch energy) correlation. Furthermore, this method was applied to evaluate the neutron irradiation embrittlement of reactor pressure vessel (RPV) steel. Most of the fracture toughness data were within the 95% confidence limits. The prediction of a transition temperature shift by statistical analysis was compared with that from the experimental data.

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Vehicle tire Noise/Vibration Characteristic Analysis using SEA(Statistical Energy Analysis) (SEA를 이용한 승용차 타이어의 소음/진동 특성 해석)

  • 김윤철;채장범;강기석;이상주;이승규
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.11b
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    • pp.719-724
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    • 2001
  • The study on reducing vehicle noise and vibration has gained much attention to ensure the comfortability as well as the safety. These days. in this paper, we applied Statistical Energy Analysis(SEA) to characterize the tire assembly, which is useful analytical tool for mid- and high-frequency range. First, the SEA tire model was developed by dividing the tire and the wheel into several subsystems. The material properties were estimated experimentally. Finally. the SEA model was validated by comparing the estimated and the measured. In addition, we investigated the energy level and the energy transfering paths through the tire assembly in different frequency region.

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Design Sensitivity Studies for Statistical Energy Analysis Modeling of Construction Vehicle Cab (통계적 에너지 해석 모델을 이용한 건설 장비 차실 설계에 관한 연구)

  • 채장범
    • Journal of KSNVE
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    • v.8 no.4
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    • pp.609-615
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    • 1998
  • In recent years there has been an increasing emphasis on shortening design cycles for bringing products to market. This requires the development of computer aided engineering tools which allow analysts to quickly evaluate the effect of design changes on noise, vibration, and harshness. Statistical Energy Analysis (SEA) modeling is a valuable tool for predicting noise and vibration as SEA models are inherently simpler and more robust than deterministic models. SEA modeling can be combined with design sensitivity analysis(DSA) to identify design changes which give the largest performance benefit. This paper describes SEA modeling of an equipment cab. SEA predictions are compared to test data, showing good agreement. The use of design sensitivity analysis in improving cab design is then demonstrated.

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An Application of the Statistical Energy Analysis for Absorbing and Soundproofing Materials of Vehicle (자동차용 흡.차음재의 성능분석을 위한 통계적 에너지 기법의 적용)

  • Lee, Chang-Myung;Lee, Jun;Kim, Dae-Gon
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.13 no.1
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    • pp.33-39
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    • 2003
  • Interior parts of a vehicle are getting important to reduce interior noise. Therefore, prior analysis of cabin noise related with interior parts are necessary at first design stage. Recently, Statistical Energy Analysis(SEA) has been suggested as a possible way for high frequency range noise analysis of interior parts. The validity of noise analysis with SEA to interior parts has been preyed by comparing with experimental result, and the developed method with SEA has been applied in finding optimized interior parts package.

Investigation of Vibration Characteristics using Experimental Statistical Energy Analysis(ESEA) (시험적인 통계적 에너지 기법(ESEA)을 적용한 진동 전달 특성 연구)

  • 이화수;우관제;김종년;이태욱
    • Proceedings of the KSR Conference
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    • 2002.10a
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    • pp.113-118
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    • 2002
  • Vibrational characteristics of coupled beam & plate system are considered on simple system, which consists of plates(2-subsystem) and beams(4-subsystem), using experimental statistical energy analysis(ESEA). First, damping and coupling loss factors of the system are determined by power injection method (PIM). Then, energy distribution of all the subsystem is estimated from the power balance equation. Finally, these quantities are compared with measured energy. The correlation of measured and estimated results for the sample problem is reasonably good.

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Calculation of Coupling Loss Factor for Small reverberation cabin using Statistical Energy Analysis (통계적 에너지 해석법을 이용한 소형 잔향실의 연성손실계수 측정)

  • 김관주;김운경;윤태중;김정태
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.797-801
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    • 2003
  • The Statistical Energy Analysis is based on the power flow and the energy conservation between sub-systems, which enable the prediction of acoustic and structural vibration behavior in mid-high frequency ranges. This paper discusses the identification of SEA coupling loss factor parameters from experimental measurements of small reverberation chamber sound pressure levels and structural accelerations. As structural subsystems, steel plates with and without damping treatment are considered. Calculated CLFs were verified by both transmission loss values for air-borne CLF case and running SEA commercial software As a result, CLFs have shown a good agreement with those computed by software. Acoustical behavior of air-borne noise and structure-borne noise has been examined. which shows reasonable results, too.

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An application of the Statistical Energy Analysis for Absorbing and Soundproofing Materials of Vehicle (자동차용 흡.차음재의 성능분석을 위한 통계적 에너지 기법 적용의 검정)

  • Lee, Chang-Myung;Lee, Jun;Kim, Dae-Gon;Jung, Byoung-In
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.11b
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    • pp.1109-1113
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    • 2001
  • Interior parts of a vehicle are getting important to reduce interior noise of car. Therefore, prior analysis of cabin noise related with interior parts are necessary at first design stage. Recently, Statistical Energy Analysis(SEA) has been suggested as a possible way for meddle of high frequency range analysis with interior parts. This article introduces an example of the application of SEA to predict air born noise of cabin of car.

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Energy Flow Finite Element Analysis(EFFEA) of Coplanar Coupled Mindlin Plates (동일 평면상에서 연성된 Mindlin 판 구조물의 에너지흐름유한요소해석)

  • Park, Young-Ho
    • Journal of the Society of Naval Architects of Korea
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    • v.53 no.4
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    • pp.307-314
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    • 2016
  • Energy flow analysis(EFA) is a representative method that can predict the statistical energetics of structures at high frequencies. Generally, as the frequency increases, the shear distortion and rotatory inertia effects in the out-of-plane motion of beams or plates become important. Therefore, to predict the out-of-plane energetics of coupled structures in the high frequency range, the energy flow analyses of Timoshenko beam and Mindlin plate are required. Unlike the energy flow model of Kirchhoff plate, the energy flow model of Mindlin plate is composed of three kinds of energy governing equations(out-of-plane shear wave, bending dominant flexural wave, and shear dominant flexural wave). This paper performed the energy flow finite element analysis(EFFEA) of coplanar coupled Mindlin plates. For EFFEA of coplanar coupled Mindlin plates, the energy flow finite element formulation of out-of-plane energetics in the Mindlin plate was performed. The general EFFEA program was implemented by MATLAB® language. For the verification of EFFEA of Mindlin plate, the various numerical applications were done successfully.

Application of Piezoelectric Smart Structures for Statistical Energy Analysis (압전 지능 구조물을 이용한 통계적 에너지 해석 기법)

  • 김재환;김정하;김재도
    • Journal of KSNVE
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    • v.11 no.2
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    • pp.257-264
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    • 2001
  • In this research, piezoelectric smart structures are applied for SEA(Statistical Energy Analysis), which is well known approach for high frequency analysis. A new input power measurement based on piezoelectric electrical power measurement is proposed and compared with the conventional method in SEA. As an example, a simple aluminum beam on which piezoelectric actuator is attached is considered. By measuring the electrical impedance and electrical current of the piezoelectric actuator, the electrical power given on the actuator is found and this is In turn converted into the mechanical energy. From the measured value of the stored energy of the beam, the Internal loss factor is calculated and this value shows a good agreement with that given by the conventional method as well as the theoretical value. To compare the coupling loss factor, L-shape beam system which consists of a aluminum beam subsystem and a steel beam subsystem coupled by three pin is taken as second example. The input power and stored energy of each subsystem are found by the proposed approach. The coupling loss factor found by the electrical input power obtained from the piezoelectric actuator exhibits similar trend to the value found by the conventional method as well as the theoretical value. In conclusion, the use of SEA for high frequency application of piezoelectric smart structures is Possible. Especially, the input power that is essential for SEA can be found accurately by measuring the electrical input power of the piezoelectric actuator.

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