• Steel and Composite Structures
• /
• 제26권2호
• /
• pp.241-253
• /
• 2018

Mode II fracture toughness, $K_{IIC}$, of single-ply triaxially woven fabric (TWF) composite due to tow waviness and anisotropy effects were numerically and experimentally studied. The numerical wavy beam network model with anisotropic material description denoted as TWF anisotropic was first validated with experimental Mode II fracture toughness test employing the modified compact tensile shear specimen configuration. 2D planar Kagome and TWF isotropic models were additionally constructed for various relative densities, crack lengths, and cell size parameters for examining effects due to tow waviness and anisotropy. $K_{IIC}$ generally increased with relative density, the inverse of cell size, and crack length. It was found that both the waviness and anisotropy of tow inflict a drop in $K_{IIC}$ of TWF. These effects were more adverse due to the waviness of tow compared to anisotropy.

• Korean Journal of Radiology
• /
• 제21권7호
• /
• pp.869-879
• /
• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.

• 대한지하수환경학회지
• /
• 제4권3호
• /
• pp.111-115
• /
• 1997

파쇄매질에서 불규칙한 양상의 유체유동과 용질이동의 모의를 위하여 연속체 모델을 대체하는 분리단열망 모델의 이용이 확산되고 있다. 분리단열망 모델은 단열내 유량이 단열 간극의 삼승에 비례한다는 삼승법칙과 매질이 이러한 단열의 통계적 조합으로 구성된다는 가정에 바탕을 두고 있다. 본 연구는 단열교차점에서 삼승법칙의 유효성이 유지될 수 있는가를 평가하기 위하여 경계좌표계 변환법을 이용하여 단열간 교차각과 단열에서 유량분포의 관계를 분석하였다. 단열 교차각의 변화에 따른 유선의 분포에 대한 분석을 통하여 단열의 기하학적 형태가 단열의 유량분포에 영향을 미침을 확인하였다. 따라서, 삼승법칙에 대한 엄밀한 수치적 실험적 검증이 필요하다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2016년도 학술발표회
• /
• pp.326-326
• /
• 2016

단층은 지질학적 관점에서 국부적인 지구구조응력(tectonic stress)이 암반 내에 존재하는 어떤 면을 따라 파괴 분기값을 초과하는 경우에 발생하는 매우 큰 공간적 변이에 의한 파괴 면으로 정의된다. 이러한 단층의 수문지질학적 특성은 단층의 공간적인 분포와 간극의 연결성에 따라 변화된다. 단층의 형성이 단층 내의 간극의 생성과 파괴를 이끄는 과정이 포함될 때 단층을 따라 발생되는 변이와 간극의 변화 사이에 복잡한 관계가 존재한다. 본 연구에서는 단층의 기하학적 특성에 따라 변화되는 흐름 변화를 3차원 이산 균열망 모형을 통해 모의 및 분석을 수행하였다. 단층의 기하학적 특성에 대해 3가지 경우를 고려하였다. 첫 번째는 영역 중심에 위치한 폭이 매우 좁고 상대적으로 주위 암반보다 매우 높은 투수성을 가진 단층, 두 번째는 단층 주변에 손상지역(damaged zone)이 존재하는 경우 그리고 세 번째는 relay 구조를 가진 단층이다.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2008년도 추계학술대회논문집
• /
• pp.668-669
• /
• 2008

In this paper, we introduce various coarse-grained elastic network modeling (ENM) techniques as a novel computational method for simulating atomic scale dynamics in macromolecules including DNA, RNA, protein, and polymer. In ENM, a system is modeled as a spring network among representative atoms in which each linear elastic spring is well designed to replace both bonded and nonbonded interactions among atoms in the sense of quantum mechanics. Based on this simplified system, a harmonic Hookean potential is defined and used for not only calculating intrinsic vibration modes of a given system, but also predicting its anharmonic conformational change, both of which are strongly related with its functional features. Various nano and bio applications of ENM such as fracture mechanics of nanocomposite and protein dynamics show that ENM is one of promising tools for simulating atomic scale dynamics in a more effective and efficient way comparing to the traditional molecular dynamics simulation.

• 한국지반환경공학회 논문집
• /
• 제25권5호
• /
• pp.15-19
• /
• 2024

본 연구는 대심도 조건에서 고효율 그라우팅 기술 개발을 목표로 하여, 다양한 주입 재료의 적용 가능성을 실험적으로 검증하였다. 1종 보통 포틀랜드 시멘트(OPC)와 마이크로 시멘트(MC)의 입자 크기 분석 및 주입 모형 실험을 통해 각 재료의 주입성능을 평가했다. 국내 대심도 기준, 즉 지하 40미터 이하 조건에서 Barton's Cubic Network 이론을 활용하여 암반 절리 간격을 산정했으며, 선정된 조건에서 입자 크기의 통과 가능성을 분석한 결과, MC는 암반 절리 간격을 통과한 반면, OPC는 간극을 통과하지 못하였다. 실험 장치 및 면적 계산 프로그램을 활용한 주입 모형 실험 결과에 따르면, OPC는 입자 크기가 크기 때문에 주입에 실패한 반면, MC는 고점도 조건에서도 주입이 가능한 것으로 나타났다. 이러한 연구 결과를 바탕으로, 주입 재료에 따른 대심도 조건에서 그라우트 재료의 적용 가능성을 정량적 및 가시적으로 도출하였으며, 고점도 MC 재료는 대심도 암반 절리면 차수 보강에 효과적일 것으로 예상된다.

• 한국지하수토양환경학회:학술대회논문집
• /
• 한국지하수토양환경학회 2002년도 추계학술발표회
• /
• pp.32-35
• /
• 2002

In order to characterize the migration of DNAPL in rock fractures, the dynamic macromodified invasion percolation (DMMIP) model, that is able to reflect the viscous force of groundwater in a fracture network, is suggested. DMMIP simulations are verified against the laboratory expenments, which shows a good qualitative and quantitative agreement.

• Water Engineering Research
• /
• 제2권2호
• /
• pp.123-138
• /
• 2001

An injection experiment was carried ut to investigate the pressure domain within which hydromechanical coupling influences considerably the hydrologic behavior of a granite rock mass. The resulting database is used for testing a numerical model dedicated to the analysis of such hydromechanical interactions. These measurements were performed in an open hole section, isolated from shallower zones by a packer set at a depth of 275 m and extending down to 840 m. They consisted in a series of flow meter injection tests, at increasing injection rates. Field results showed that conductive fractures from a dynamic and interdependent network, that individual fracture zones could not be adequately modeled as independent systems, that new fluid intakes zones appeared when pore pressure exceeded the minimum principal stress magnitude in that well, and that pore pressures much larger than this minimum stress could be further supported by the circulated fractures. These characteristics give rise to the question of the influence of the morphology of the natural fracture network in a rock mass under anisotropic stress conditions on the effects of hydromechanical couplings.

• Journal of Mechanical Science and Technology
• /
• 제19권7호
• /
• pp.1393-1404
• /
• 2005

Fatigue crack growth and life have been estimated based on established empirical equations. In this paper, an alternative method using artificial neural network (ANN) -based model developed to predict fatigue damages simultaneously. To learn and generalize the ANN, fatigue crack growth rate and life data were built up using in-plane bending fatigue test results. Single fracture mechanical parameter or nondestructive parameter can't predict fatigue damage accurately but multiple fracture mechanical parameters or nondestructive parameters can. Existing fatigue damage modeling used this merit but limited real-time damage monitoring. Therefore, this study shows fatigue damage model using backpropagation neural networks on the basis of X -ray half breadth ratio B / $B_o$, fractal dimension $D_f$ and fracture mechanical parameters can estimate fatigue crack growth rate da/ dN and cycle ratio N / $N_f$ at the same time within engineering limit error ($5\%$).

• International Journal of Naval Architecture and Ocean Engineering
• /
• 제12권1호
• /
• pp.354-366
• /
• 2020

This work mainly focuses on determination of the fully plastic J-integral solutions for welded center cracked plates subjected to remote tension loading. Detailed three-dimensional elasticeplastic Finite Element Analyses (FEA) were implemented to compute the fully plastic J-integral along the crack front for a wide range of crack geometries, material properties and weld strength mismatch ratios for 900 cases. According to the database generated from FEA, Back-propagation Neural Network (BPNN) model was proposed to predict the values and distributions of fully plastic J-integral along crack front based on the variables used in FEA. The determination coefficient R2 is greater than 0.99, indicating the robustness and goodness of fit of the developed BPNN model. The network model can accurately and efficiently predict the elastic-plastic J-integral for weld centerline crack, which can be used to perform fracture analyses and safety assessment for welded center cracked plates with varying strength mismatch conditions under uniaxial loading.