• Title/Summary/Keyword: numerical test

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Deep-Learning Seismic Inversion using Laplace-domain wavefields (라플라스 영역 파동장을 이용한 딥러닝 탄성파 역산)

  • Jun Hyeon Jo;Wansoo Ha
    • Geophysics and Geophysical Exploration
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    • v.26 no.2
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    • pp.84-93
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    • 2023
  • The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.

Design and Analysis of a Mooring System for an Offshore Platform in the Concept Design Phase (해양플랜트 개념설계 단계에서의 계류계 초기 설계 및 해석)

  • Sungjun Jung;Byeongwon Park;Jaehwan Jung;Seunghoon Oh;Jongchun Park
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.2
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    • pp.248-253
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    • 2023
  • Most offshore platforms utilize chain mooring systems for position keeping. However, information regarding related design modification processes is scarce in literature. This study focuses on the floating liquefied natural gas (LNG) bunkering terminal (FLBT) as the target of shore platform and analyzes the corresponding initial mooring design and model tests via numerical simulations. Subsequently, based on the modified design conditions, a new mooring system design is proposed. Adjusting the main direction of the mooring line bundle according to the dominant environmental direction is found to significantly reduce the mooring design load. Even turret-moored offshore platforms are exposed to beam sea conditions, leading to high mooring tension due to motions in beam sea conditions. Collinear environmental conditions cannot be considered as design conditions. Mooring design loads occur under complex conditions of wind, waves, and currents in different environmental directions. Therefore, it is essential appropriately assign the roll damping coefficients during mooring analysis because the roll has a significant effect on mooring tension.

Seismic performance assessment of single pipe piles using three-dimensional finite element modeling considering different parameters

  • Duaa Al-Jeznawi;Jitendra Khatti;Musab Aied Qissab Al-Janabi;Kamaldeep Singh Grover;Ismacahyadi Bagus Mohamed Jais;Bushra S Albusoda;Norazlan Khalid
    • Earthquakes and Structures
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    • v.24 no.6
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    • pp.455-475
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    • 2023
  • The present study investigates the non-linear soil-pile interaction using three-dimensional (3D) non-linear finite element models. The numerical models were validated by using the results of extensive pile load and shaking table tests. The pile performance in liquefiable and non-liquefiable soil has been studied by analyzing the liquefaction ratio, pile lateral displacement (LD), pile bending moment (BM), and frictional resistance (FR) results. The pile models have been developed for the different ground conditions. The study reveals that the results obtained during the pile load test and shaking cycles have good agreement with the predicted pile and soil response. The soil density, peak ground acceleration (PGA), slenderness ratio (L/D), and soil condition (i.e., dry and saturated) are considered during modeling. Four ground motions are used for the non-linear time history analyses. Consequently, design charts are proposed depended on the analysis results to be used for design practice. Eleven models have been used to validate the capability of these charts to capture the soil-pile response under different seismic intensities. The results of the present study demonstrate that L/D ratio slightly affects the lateral displacement when compared with other parameters. Also, it has been observed that the increasing in PGA and decreasing L/D decreases the excess pore water pressure ratio; i.e., increasing PGA from 0.1 g to 0.82 g of loose sand model, decrease the liquefaction ratio by about 50%, and increasing L/D from 15 to 75 of the similar models (under Kobe earthquake), increase this ratio by about 30%. This study reveals that the lateral displacement increases nonlinearly under both dry and saturated conditions as the PGA increases. Similarly, it is observed that the BM increases under both dry and saturated states as the L/D ratio increases. Regarding the acceleration histories, the pile BM was reduced by reducing the acceleration intensity. Hence, the pile BM decreased to about 31% when the applied ground motion switched from Kobe (PGA=0.82 g) to Ali Algharbi (PGA=0.10 g). This study reveals that the soil conditions affect the relationship pattern between the FR and the PGA. Also, this research could be helpful in understanding the threat of earthquakes in different ground characteristics.

Prediction of the Static Deflection Profiles on Suspension Bridge by Using FBG Strain Sensors (FBG 변형률센서를 이용한 현수교의 정적 처짐형상 추정)

  • Cho, Nam-So;Kim, Nam-Sik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5A
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    • pp.699-707
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    • 2008
  • For most structural evaluation of bridge integrity, it is very important to measure the geometric profile, which is a major factor representing the global behavior of civil structures, especially bridges. In the past, because of the lack of appropriate methods to measure the deflection profile of bridges on site, the measurement of deflection has been restricted to just a few discrete points along the bridge, and the measuring points have been limited to the locations installed with displacement transducers. Thus, some methods for predicting the static deflection by using fiber optic strain sensors has been applied to simply supported bridges. In this study, a method of estimating the static deflection profile by using strains measured from suspension bridges was proposed. Based on the classical deflection theory of suspension bridges, an equation of deflection profile was derived and applied to obtain the actual deflection profile on Namhae suspension bridge. Field load tests were carried out to measure strains from FBG strain sensors attached inside the stiffening girder of the bridge. The predicted deflection profiles were compared with both precise surveying data and numerical analysis results. Thus, it is found that the equation of predicting the deflection profiles proposed in this study could be applicable to suspension bridges and the FBG strain sensors could be reliable on acquiring the strain data from bridges on site.

On the Hydraulic Characteristics of Efficient Long Wave Energy Absorber-Eco-breaker 2 (장파 제어체 Eco-breaker 2의 수리특성)

  • Cho, Yong Jun;Kim, Ho Min
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5B
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    • pp.547-558
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    • 2008
  • With the advent of super cargo ship due to the explosive increase in the amount of cargo shipped via seas, some mega ports are under construction in South Korea, to accommodate the super cargo ship, and some of them already enter their final phase. To sustain the harbor tranquility, mega ports usually comprise huge vertical type breakwaters which are intrinsically vulnerable to the attack of long waves. In this rationale, we present the chamber type breakwater with a circular curtain wall - Eco-breaker 2, to alleviate the reflection of long waves and numerically investigate the hydraulic characteristics of Eco-breaker 2. As a wave driver, we use the Navier-Stokes eq., the most robust wave driver, using SPH (Smoothed Particle Hydrodynamics) and LES (Large Eddy Simulation). For the verification of numerical results, we also carried out hydraulic model test. It is shown that Eco-breaker 2 can effectively alleviate the reflection of long waves with its inherited large organized eddies encompassing the water chamber and some region off the curtain wall of varying size. It is also shown that the scope and strength of large organized eddies strongly depends on the incident wave period, and the reflection coefficient can be lowered to 0.18 by tuning the size of water chamber such that resident time at the chamber is just short of the half period of incident waves. Based on these results, we present the specification of Eco-breaker 2 to boost its use on the development of water environment friendly harbor worldwide.

Development of Steel Composite Cable Stayed Bridge Weigh-in-Motion System using Artificial Neural Network (인공신경망을 이용한 강합성 사장교 차량하중분석시스템 개발)

  • Park, Min-Seok;Jo, Byung-Wan;Lee, Jungwhee;Kim, Sungkon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6A
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    • pp.799-808
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    • 2008
  • The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.

Seismic analysis of tunnel considering the strain-dependent shear modulus and damping ratio of a Jointed rock mass (절리암반의 변형률 의존적 전단탄성계수 및 감쇠비 특성을 고려한 터널의 내진 해석)

  • Song, Ki-Il;Jung, Sung-Hoon;Cho, Gye-Chun;Lee, Jeong-Hark
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.12 no.4
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    • pp.295-306
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    • 2010
  • Contrary to an intact rock, the jointed rock mass shows strain-dependent deformation characteristics (elastic modulus and damping ratio). The maximum elastic modulus of a rock mass can be obtained from an elastic wave-based exploration in a small strain level and applied to seismic analyses. However, the assessment and application of the non-linear characteristics of rock masses in a small to medium strain level ($10^{-4}{\sim}0.5%$) have not been carried out yet. A non-linear dynamic analysis module is newly developed for FLAC3D to simulate strain-dependent shear modulus degradation and damping ratio amplification characteristics. The developed module is verified by analyzing the change of the Ricker wave propagation. Strain-dependent non-linear characteristics are obtained from disks of cored samples using a rock mass dynamic testing apparatus which can evaluate wave propagation characteristics in a jointed rock column. Using the experimental results and the developed non-linear dynamic module, seismic analyses are performed for the intersection of a shaft and an inclined tunnel. The numerical results show that vertical and horizontal displacements of non-linear analyses are larger than those of linear analyses. Also, non-linear analyses induce bigger bending compressive stresses acting on the lining. The bending compressive stress concentrates at the intersection part. The fundamental understanding of a strain-dependent jointed rock mass behavior is achieved in this study and the analytical procedure suggested can be effectively applied to field designs and analyses.

Geotechnical Hybrid Simulation System for the Quantitative Prediction of the Residual Deformation in the Liquefiable Sand During and After Earthquake Motion (액상화 가능 지반의 진동 도중 및 후의 잔류 변형에 대한 정량적 예측을 위한 하이브리드 시뮬레이션 시스템)

  • Kwon, Young Cheul
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1C
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    • pp.43-52
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    • 2006
  • Despite several constitutive models have been proposed and applied, it is still difficult to choose a suitable model and to estimate adequate analysis parameters. Furthermore, a cyclic shear behavior under the volume change caused by the seepage is more complex. None of the constitutive model is available at present in the expression of the cyclic behavior of soil under an additional volume change condition by seepage. Therefore, a new geotechnical hybrid simulation system which can control the pore water immigration was developed. The system enables a quantitative evaluation of the residual deformation such as lateral spreading and settlement caused by the liquefaction. The seismic responses in a one-dimensional slightly inclined multilayered soil system are taken into consideration, and the soils are governed by both equation of motion and the continuity equation. Furthermore, the estimation and the selection of the soil parameter for the representation of the strong nonlinearity of the material are not required, because soil behaviors under the earthquake motions are directly introduced instead of a numerical soil constitutive model. This paper presents the concept and specifications of the system. By applying the system to an example problem, the permeability effect on the seismic response during cyclic shear is studied. The importance of the volume change characteristics of sandy soil during and after cyclic shear is shown in conclusion.

Optimal Sensor Placement for Improved Prediction Accuracy of Structural Responses in Model Test of Multi-Linked Floating Offshore Systems Using Genetic Algorithms (다중연결 해양부유체의 모형시험 구조응답 예측정확도 향상을 위한 유전알고리즘을 이용한 센서배치 최적화)

  • Kichan Sim;Kangsu Lee
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.3
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    • pp.163-171
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    • 2024
  • Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

Analysis of Infrared Characteristics According to Common Depth Using RP Images Converted into Numerical Data (수치 데이터로 변환된 RP 이미지를 활용하여 공동 깊이에 따른 적외선 특성 분석)

  • Jang, Byeong-Su;Kim, YoungSeok;Kim, Sewon;Choi, Hyun-Jun;Yoon, Hyung-Koo
    • Journal of the Korean Geotechnical Society
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    • v.40 no.3
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    • pp.77-84
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    • 2024
  • Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.