• Title/Summary/Keyword: Artificial ground

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Design response spectra-compliant real and synthetic GMS for seismic analysis of seismically isolated nuclear reactor containment building

  • Ali, Ahmer;Abu-Hayah, Nadin;Kim, Dookie;Cho, Sung Gook
    • Nuclear Engineering and Technology
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    • v.49 no.4
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    • pp.825-837
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    • 2017
  • Due to the severe impacts of recent earthquakes, the use of seismic isolation is paramount for the safety of nuclear structures. The diversity observed in seismic events demands ongoing research to analyze the devastating attributes involved, and hence to enhance the sustainability of base-isolated nuclear power plants. This study reports the seismic performance of a seismically-isolated nuclear reactor containment building (NRCB) under strong short-period ground motions (SPGMs) and long-period ground motions (LPGMs). The United States Nuclear Regulatory Commission-based design response spectrum for the seismic design of nuclear power plants is stipulated as the reference spectrum for ground motion selection. Within the period range(s) of interest, the spectral matching of selected records with the target spectrum is ensured using the spectral-compatibility approach. NRC-compliant SPGMs and LPGMs from the mega-thrust Tohoku earthquake are used to obtain the structural response of the base-isolated NRCB. To account for the lack of earthquakes in low-to-moderate seismicity zones and the gap in the artificial synthesis of long-period records, wavelet-decomposition based autoregressive moving average modeling for artificial generation of real ground motions is performed. Based on analysis results from real and simulated SPGMs versus LPGMs, the performance of NRCBs is discussed with suggestions for future research and seismic provisions.

A Study on the Hardening Characteristics of Ground Injection Grout under Various Curing Conditions (다양한 양생조건에서 지반주입 그라우트의 경화특성에 대한 연구)

  • Heo, Hyungseok;Park, Innjoon
    • Journal of the Korean GEO-environmental Society
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    • v.21 no.11
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    • pp.11-20
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    • 2020
  • For water barrier and reinforcing grout in soft ground, the verification of durability was conducted over the initial and long-term ages under various curing conditions. The grout was made of water glass system, fast-hardening mineral (FHM) system, and acrylic polymer system. There were three types of curing conditions that were tab water curing, artificial seawater curing, and atmospheric curing. And the various tests were performed for each sample by age, uniaxial compressive strength, length change, and weight change. As artificial seawater, MgCl2 and MgSO4 aqueous solutions were prepared and used, respectively. As the test results, the fast-hardening mineral system and acrylic polymer system were cured stably without significant change in durability in tap water and artificial sea water, whereas water glass system showed a very rapid drop in durability under artificial sea water conditions compared to tap water. In atmospheric curing conditions, durability is lowered compared to water curing in all cases, and in particular, the weight loss in the FHM system and water glass system is about 62% and 60%, respectively, resulting in a significant decrease in durability.

New method for generation of artificial ground motion by a nonstationary Kanai-Tajimi model and wavelet transform

  • Amiri, G. Ghodrati;Bagheri, A.;Fadavi, M.
    • Structural Engineering and Mechanics
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    • v.26 no.6
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    • pp.709-723
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    • 2007
  • Considering the vast usage of time-history dynamic analyses to calculate structural responses and lack of sufficient and suitable earthquake records, generation of artificial accelerograms is very necessary. The main target of this paper is to present a novel method based on nonstationary Kanai-Tajimi model and wavelet transform to generate more artificial earthquake records, which are compatible with target spectrum. In this regard, the generalized nonstationary Kanai-Tajimi model to include the nonstationary evaluation of amplitude and dominant frequency of ground motion and properties of wavelet transform is used to generate ground acceleration time history. Application of the method for El Centro 1940 earthquake and two Iranian earthquakes (Tabas 1978 and Manjil 1990) is presented. It is shown that the model and identification algorithms are able to accurately capture the nonstationary features of these earthquake accelerograms. The statistical characteristics of the spectral response of the generated accelerograms are compared with those for the actual records to demonstrate the effectiveness of the method. Also, for comparison of the presented method with other methods, the response spectra of the synthetic accelerograms compared with the models of Fan and Ahmadi (1990) and Rofooei et al. (2001) and it is shown that the response spectra of the synthetic accelerograms with the method of this paper are close to those of actual earthquakes.

Groundwater Level Prediction Using ANFIS Algorithm (ANFIS 알고리즘을 이용한 지하수수위 예측)

  • Bak, Gwi-Man;Bae, Young-Chul
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.6
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    • pp.1235-1240
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    • 2019
  • It is well known that the ground water level changes rapidly before and after the earthquake, and the variation of ground water level prediction is used to predict the earthquake. In this paper, we predict the ground water level in Miryang City using ANFIS algorithm for earthquake prediction. For this purpose, this paper used precipitation and temperature acquired from National Weather Service and data of underground water level from Rural Groundwater Observation Network of Korea Rural Community Corporation which is installed in Miryang city, Gyeongsangnam-do. We measure the prediction accuracy using RMSE and MAPE calculation methods. As a result of the prediction, the periodic pattern was predicted by natural factors, but the change value of ground water level was changed by other variables such as artificial factors that was not detected. To solve this problem, it is necessary to digitize the ground water level by numerically quantifying artificial variables, and to measure the precipitation and pressure according to the exact location of the observation ball measuring the ground water level.

A Study on the Visual Evaluation for the Combination of 'Clothing and ground' (의복, 배경의 조합에 따른 시각적 이미지 연구(제1보))

  • 주소현;이경희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.23 no.1
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    • pp.78-89
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    • 1999
  • Clothes enhance visual images through the interaction between space and background of the wearer. The influence of background is important as that of the clothes when the observer understands the images. We look at fashion pictures used as important as that various backgrounds are presented depending on the image of the clothes. The clothing the model wears in the pictures takes on shape and space which supports the clothes. The background interact to from the whole image. The background has an important influence on the delivery of image for the clothes. However when the clothes are presented in the background there are some cases that all or parts of clothes can be shown. We must consider the composition ratio of the clothes and background which influences the whole image of the clothing. These interactions and influences on the whole image in regards to clothing background and the ratio will be the focus of this study. clothing was Modern Mannish Casual, Feminine, Ground was decided artificial setting 1 natural setting 1, indoor setting 1, artificial setting 2, natural setting 2, indoor setting 2, Percentage of Clothing was 80% , 140%, 200%,. Thus visual stimulus were 72 pictures that were combined Clothing Ground and Percentage of Clothing, the main survey of questionary consisted of their evaluation of the Picture image combined Clothing and Ground by 30 semantic differential bi-polar scales and the subjects were 50 students majoring in clothing and textile. The data analyzed by factor analysis MCA, MDS, The major finding were as follows : 1) As a result of factor analysis, 5 factors -Attractiveness Hardness and softness Cuteness Attention Cool and Warm factor were found out as constructing factors the Picture image combined Clothing and Ground 2) According to multidimensional positioning map were presented in a stimulus position the perceptive image differed in degree of similarity as a ground construction of stimulus in spite of same clothing image. It will aid in choosing the most beneficial background for any clothing brand. It will enhance the picture images to their full potential in any advertising medium.

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Experimental study on the applicability of liquid air as the refrigerant in artificial ground freezing for subsea tunnels (해저터널을 위한 동결공법 냉매로서의 액화공기 적용성에 대한 실험적 연구)

  • Son, Young-Jin;Choi, Hyeungchul;Moon, Hung-Man;Choi, Hangseok;Ko, Tae Young
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.18 no.2
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    • pp.175-181
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    • 2016
  • In this paper, the liquid air was selected as the refrigerant in artificial ground freezing to be used for rapid ground freezing and to reduce the risk of suffocation and the applicability of liquid air was verified. In order to evaluate the stability of the liquid air, the oxygen concentration of mixtures with liquid nitrogen and liquid oxygen was experimentally examined to meet the oxygen concentration criteria in the Occupational Safety and Health Act. In addition, the effects of the mixture ratio of liquid nitrogen and liquid oxygen, pressure and flow rate change in the storage vessel on the oxygen concentration in the liquid air were investigated. As a result, the ratio of liquid nitrogen and liquid oxygen 8: 2 was shown to meet the oxygen concentration standards. Pressure and flow rate change in the storage vessel did not have significant effects on the oxygen concentration in the liquid air.

A case study on a tunnel back analysis to minimize the uncertainty of ground properties based on artificial neural network (인공신경망 기법에 근거한 지반물성치의 불확실성을 최소화하기 위한 터널 역해석 사례연구)

  • You, Kwang-Ho;Song, Won-Young
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.14 no.1
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    • pp.37-53
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    • 2012
  • There is considerable uncertainty in ground properties used in tunnel designs. In this study, a back analysis was performed to find optimal ground properties based on the artificial neural network facility of MATLAB program of using tunnel monitoring data. Total 81 data were constructed by changing elastic modulus and coefficient of lateral pressure which have great influence on tunnel convergence. A sensitivity analysis was conducted to establish an optimal training model by varying the number of hidden layers, the number of nodes, learning rate, and momentum. Meanwhile, the optimal training model was selected by comparing MSE (Mean Squared Error) and coefficient of determination ($R^2$) and was used to find the correct elastic moduli of layers and the coefficient of lateral pressure. In future, it is expected that the suggested method of this study can be applied to determine the optimum tunnel support pattern under given ground conditions.

Prediction of Ultimate Bearing Capacity of Soft Soils Reinforced by Gravel Compaction Pile Using Multiple Regression Analysis and Artificial Neural Network (다중회귀분석 및 인공신경망을 이용한 자갈다짐말뚝 개량지반의 극한 지지력 예측)

  • Bong, Tae-Ho;Kim, Byoung-Il
    • Journal of the Korean Geotechnical Society
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    • v.33 no.6
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    • pp.27-36
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    • 2017
  • Gravel compaction pile method has been widely used to improve the soft ground on the land or sea as one of the soft ground improvement technique. The ultimate bearing capacity of the ground reinforced by gravel compaction piles is affected by the soil strength, the replacement ratio of pile, construction conditions, and so on, and various prediction equations have been proposed to predict this. However, the prediction of the ultimate bearing capacity using the existing models has a very large error and variation, and it is not suitable for practical design. In this study, multiple regression analysis was performed using field loading test results to predict the ultimate bearing capacity of ground reinforced by gravel compaction pile, and the most efficient input variables are selected through evaluation of error by leave one out cross validation, and a multiple regression equation for the prediction of ultimate bearing capacity was proposed. In addition, the prediction error was evaluated by applying artificial neural network using the selected input variables, and the results were compared with those of the existing model.

A Study on Development of Artificial Neural Network (ANN) for Deep Excavation Design (깊은굴착 설계를 위한 인공신경망 개발에 관한 연구)

  • Yoo, Chungsik;Yang, Jaewon;Abbas, Qaisar;Aizaz, Haider Syed
    • Journal of the Korean Geosynthetics Society
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    • v.17 no.4
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    • pp.199-212
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    • 2018
  • This research concerns the prediction method for ground movement and wall member force due to determination structural stability check and failure check during deep excavation construction. First, research related with excavation influence parameters is conducted. Then, numerical analysis for various excavation conditions were conducted using Finite Element Method and Beam-column elasto-plasticity method. Excavation analysis database was then constructed. Using this database, development of ANN (artificial neural network) was performed for each ground movements and using structural member forces. By comparing the numerical analysis results with ANN's prediction, it is validated that development of ANN can be used efficient for prediction of ground movement and structural member forces in deep excavation site.