• Title/Summary/Keyword: The Propagation Prediction Model

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Prediction and Evaluation of the Road Traffic Noise according to the Conditions of Road-side Building Using RLS-90 and CRTN Model (RLS-90 및 CRTN 모델에 의한 도로 인접건물에서의 도로소음 영향 예측 및 고찰)

  • Lee, Jang-Wook;Kim, Myung-Jun
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.19 no.4
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    • pp.425-432
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    • 2009
  • Recently, reduction of road traffic noise in residential buildings has become one of the most important subjects. To reduce the road traffic noise, noise impact assessment by the road traffic prediction model is required before building construction. For reasonable road traffic noise prediction, it is required to analysis of various factors in road traffic prediction models. This paper was studied the road traffic noise propagation factors such as distance from road to building, receiver height, alignment angle of building and reflection coefficient of the building facade by two calculation models, RLS-90 and CRTN. The result showed that noise reduction was generally higher at bottom stories by ground absorption effect. The reflection coefficient of the building facade was affect of additional sound pressure level by facade reflecting. And alignment angle of building at $90^{\circ}$ was performed effective noise reduction better than $0^{\circ}$.

A study on patterns of propagation for high speed train(KTX) (한국형 고속전철(KTX) 방사패턴에 관한 연구)

  • 구동회;김재철;박태원;문경호
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.05a
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    • pp.836-842
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    • 2001
  • The more sophisticated patterns of propagation model is presented in this paper, which includes three different source characteristics. The spherical, cosine and dipole radiation characteristics compared and sound event level and the maximum sound level are calculated by experiment and calculation. It is shown that patterns of propagation has dipole characteristics for low speed range(below about 150km/h) at electric multiple system. We know that push-pull high speed system(maximum speed: 300km/h) has cosine characteristics of noise propagation. For this purpose, We conduct the experiment of noise and know the empirical formula of noise level and radiation coefficient K. This model of simulation is conducted through point source array model at wheel/rail contact point by using program and experimental formula. We can guess prediction of profile, flat and wear of wheel by above modeling in near field.

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A Study on Radio Wave Propagation Characteristics in A Corridor (복도 내에서의 전파의 전파특성에 관한 연구)

  • Hee-Chang Kang
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.8 no.6
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    • pp.614-619
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    • 1997
  • In this paper, radio-wave propagation characteristics in a rectangular corridor are investigated using a tunnel model of reduced dimensions. Measurements were carried out on vertical polarization characteristics in the frequency range from 2 GHz to 10 GHz. The experimental results for the propagation constant in tunnel model agree satisfactorily with theoretical prediction. It is shown that model method is applicable in determining the propagation characteristics in tunnel.

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Crack propagation in flexural fatigue of concrete using rheological-dynamical theory

  • Pancic, Aleksandar;Milasinovic, Dragan D.;Goles, Danica
    • Computers and Concrete
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    • v.27 no.1
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    • pp.55-62
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    • 2021
  • The concrete fatigue analysis can be performed with the use of fracture mechanics. The fracture mechanics defines the fatigue crack propagation as the relationship of crack growth rate and stress intensity factor. In contrast to metal, the application of fracture mechanics to concrete is more complicated and therefore many authors have introduced empirical expressions using Paris law. The topic of this paper is development of a new prediction of fatigue crack propagation for concrete using rheological-dynamical analogy (RDA) and finite element method (FEM) in the frame of linear elastic fracture mechanics (LEFM). The static and cyclic fatigue three-point bending tests on notched beams are considered. Verification of the proposed approach was performed on the test results taken from the literature. The comparison between the theoretical model and experimental results indicates that the model proposed in this paper is valid to predict the crack propagation in flexural fatigue of concrete.

Examination of Prediction Model for Road Traffic Noise in Apartment (공동주택 도로교통소음 예측방법 고찰)

  • Park, Hyeon-Ku;Song, Guk-Gon;Song, Min-Jeong;Jang, Gil-Soo;Kim, Sun-Woo
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2008.04a
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    • pp.1-4
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    • 2008
  • Prediction models currently being used for road traffic noise in apartment are equation of NIER, HW-NOISE of Korea Expressway Corporation, FHWA of United States, CRTN of United Kingdom, NMPB of France, ASJ RTN-Model 2003 of Japan and ISO 9613-1, 2 as a international standard. ISO 9613 species an engineering method for calculating the attenuation of sound during propagation outdoors in order to predict the levels of environmental noise at a distance from a variety of sources. This study, prior to investigation of every prediction methods listed above, aims to examine the model internationally standardized and to establish a reference for the prediction of road traffic noise in apartment.

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An Analysis on the Propagation Prediction Model of Earth-space Communication Link using Local Data (로컬 데이터를 이용한 지구-우주 통신 링크의 전파 예측 모델 분석)

  • Lee, Hwa-Choon;Kim, Woo-Su;Choi, Tae-Il;Oh, Soon-Soo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.3
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    • pp.483-488
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    • 2019
  • The propagation prediction model of the earth-space communication link used as an international standard was used to calculate and analyze the total losses on the communication path. The standard definition and scope of ITU-R Rec. were analyzed for each parameter(rain, scintillation, atmospheric gas, clouds) used to calculate the total loss. The total losses were calculated using the standard model for each parameter and the statistical data provided by ITU-R, and the results were analyzed using the validation examples data. The rain losses were calculated using long-term local rainfall attenuation statistics data measured in the region, and compared with the calculation results using a rainfall map in the ITU-R Recommendation. The data of Cheollian satellites for the L-Band and Ka-Band were used to calculate the rainfall attenuation. In the range of 0.01% to 0.1%, it was found to have a greater attenuation slope when using local data than attenuation by the model of ITU-R.

Machine learning in concrete's strength prediction

  • Al-Gburi, Saddam N.A.;Akpinar, Pinar;Helwan, Abdulkader
    • Computers and Concrete
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    • v.29 no.6
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    • pp.433-444
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    • 2022
  • Concrete's compressive strength is widely studied in order to understand many qualities and the grade of the concrete mixture. Conventional civil engineering tests involve time and resources consuming laboratory operations which results in the deterioration of concrete samples. Proposing efficient non-destructive models for the prediction of concrete compressive strength will certainly yield advancements in concrete studies. In this study, the efficiency of using radial basis function neural network (RBFNN) which is not common in this field, is studied for the concrete compressive strength prediction. Complementary studies with back propagation neural network (BPNN), which is commonly used in this field, have also been carried out in order to verify the efficiency of RBFNN for compressive strength prediction. A total of 13 input parameters, including novel ones such as cement's and fly ash's compositional information, have been employed in the prediction models with RBFNN and BPNN since all these parameters are known to influence concrete strength. Three different train: test ratios were tested with both models, while different hidden neurons, epochs, and spread values were introduced to determine the optimum parameters for yielding the best prediction results. Prediction results obtained by RBFNN are observed to yield satisfactory high correlation coefficients and satisfactory low mean square error values when compared to the results in the previous studies, indicating the efficiency of the proposed model.

Analysis of Input Factors of DNN Forecasting Model Using Layer-wise Relevance Propagation of Neural Network (신경망의 계층 연관성 전파를 이용한 DNN 예보모델의 입력인자 분석)

  • Yu, SukHyun
    • Journal of Korea Multimedia Society
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    • v.24 no.8
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    • pp.1122-1137
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    • 2021
  • PM2.5 concentration in Seoul could be predicted by deep neural network model. In this paper, the contribution of input factors to the model's prediction results is analyzed using the LRP(Layer-wise Relevance Propagation) technique. LRP analysis is performed by dividing the input data by time and PM concentration, respectively. As a result of the analysis by time, the contribution of the measurement factors is high in the forecast for the day, and those of the forecast factors are high in the forecast for the tomorrow and the day after tomorrow. In the case of the PM concentration analysis, the contribution of the weather factors is high in the low-concentration pattern, and that of the air quality factors is high in the high-concentration pattern. In addition, the date and the temperature factors contribute significantly regardless of time and concentration.

Vertical Z-vibration prediction model of ground building induced by subway operation

  • Zhou, Binghua;Xue, Yiguo;Zhang, Jun;Zhang, Dunfu;Huang, Jian;Qiu, Daohong;Yang, Lin;Zhang, Kai;Cui, Jiuhua
    • Geomechanics and Engineering
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    • v.30 no.3
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    • pp.273-280
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    • 2022
  • A certain amount of random vibration excitation to subway track is caused by subway operation. This excitation is transmitted through track foundation, tunnel, soil medium, and ground building to the ground and ground structure, causing vibration. The vibration affects ground building. In this study, the results of ANSYS numerical simulation was used to establish back-propagation (BP) neural network model. Moreover, a back-propagation neural network model consisting of five input neurons, one hidden layer, 11 hidden-layer neurons, and three output neurons was used to analyze and calculate the vertical Z-vibration level of New Capital's ground buildings of Qingdao Metro phase I Project (Line M3). The Z-vibration level under different working conditions was calculated from monolithic roadbed, steel-spring floating slab roadbed, and rubber-pad floating slab roadbed under the working condition of center point of 0-100 m. The steel-spring floating slab roadbed was used in the New Capital area to monitor the subway operation vibration in this area. Comparing the monitoring and prediction results, it was found that the prediction results have a good linear relationship with lower error. The research results have good reference and guiding significance for predicting vibration caused by subway operation.

Fatigue Growth Life Prediction for Collinear Multiple Surface Cracks (동일평면상에 존재하는 복수표면균열의 피로성장수명예측)

  • Lee, J.H.;Choy, Y.S.;Kim, Y.J.
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.7 s.94
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    • pp.1668-1677
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    • 1993
  • The objective of this paper is to develop a computational model for predicting the fatigue propagation of collinear multiple surface cracks under constant amplitude and variable amplitude loadings. After examining fatigue crack growth behavior for CT specimens and single surface crack specimens, empirical equations of(11) and(12) are proposed for the prediction of fatigue life in a multiple surface crack geometry. The accuracy of the proposed model is verified using a life prediction computer program. Several case studies were performed to check the accuracy of the proposed model and to verify the usefulness of the developed program. Good agreement is observed between the numerical results based on the proposed model and the published experimental data.