Rainfall-Earthquake-Induced Landslide Hazard Prediction by Monte Carlo Simulation: A Case Study of mt. Umyeon in Korea

Vinh Ba-Quang Nguyen,김윤태 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.1

Rainfall and earthquakes are two major triggers for landslides. To assess annual rainfall-earthquake-induced landslide hazards, an ensemble model containing three modules: an uncertainty-analysis module, a simulation module and an output module was proposed. In the uncertainty-analysis module, the input parameters including the topography (slope, curvature), soil depth, rainfall, peak ground acceleration and soil physical properties were considered probabilistic rather than taking specific values. A rainfall-earthquake-induced landslide hazard assessment was carried out in the simulation module, which used two separate methods: a pseudo-static model and a Newmark displacement model based on probabilistic data, which were prepared in the uncertainty-analysis module using the Monte Carlo simulation technique. In the output module, the two landslide hazard evaluations were combined into one map. The combined landslide hazard provides a range of annual probabilities of landslide occurrence corresponding to specific confidence levels. The proposed model can be used for reliable forecasting at specific confidence levels.

A Hybrid Physical and Machine Learning Model for Assessing Landslide Spatial Probability caused by raising of ground water table and Earthquake in Atsuma, Japan - Case Study

Ba-Quang-Vinh Nguyen,송창호,김윤태 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.8

Landslides are catastrophic natural events primed and/or triggered by extreme rainfalls and strong earthquakes. Simultaneous occurrence of rainfall and seismic activity increases the likelihood of landslides. However, the researchers focused on this aspect are not much. In the present research, a hybrid model was developed to predict the landslide occurrences probability in Atsuma, Japan triggered by rainfalls and earthquakes. The proposed model is a combination of a physical and machine learning model for improving the accuracy of the landslide susceptibility mapping. The proposed model consisted of a physical module, a machine learning module and a matrix approach module. The physical module assessed the effects of rainfall and peak ground acceleration (PGA) on landslide occurrence probability based on a pseudo-static model. The machine learning module applied Multilayer Perceptron Neural Networks to assess landslide susceptibility, using 611 landslide events caused by strong earthquakes and extreme typhoons. The landslide susceptibility maps obtained from these two modules were then combined into final susceptibility map through a matrix approach. The final susceptibility map included five susceptible levels: very low, low, moderate, high, and very high. To evaluate the proposed model performance, the resulting models were assessed using the areas under the receiver operating characteristic curves. The areas under the success rate curves from the physical module, machine learning module and matrix-based approach showed 79.2%, 82.7% and 83.9% accuracy, respectively. Furthermore, the predicted rate curves showed that the areas under the curve for physical module, machine learning module and matrix-based approach were 78.4%, 82.3% and 83.4%, respectively. These results suggest that the proposed hybrid model improves the prediction capability compared to physically-based method or machine learning model and can be readily used to assess spatial probability of landslide.

Landslide Susceptibility Assessment Considering Pore Water Pressure Increases due to Rainfall and Earthquake

( Ba-quang-vinh Nguyen ),( Ji-sung Lee ),( Seung-rae Lee ),( Yun-tae Kim ) 대한지질공학회 2019 대한지질공학회 학술발표회논문집 Vol.2019 No.2

Increased pore-water pressure due to rainfall infiltration and earthquakes is a major cause slope instability. The effect of changes in pore-water pressure on slopes due to rainfall has been considered in many studies, while the generation of pore-water pressure due to seismic loading is often disregarded in earthquake-induced landslide susceptibility assessment. Hence, this study propose a model to assess landslide susceptibility that takes into account increased pore-water pressure during both rainfall and earthquakes. The procedure for the proposed method includes two main steps. In step 1, we analyze the change in the groundwater table due to rainfall infiltration and subsurface flow during rainfall. In step 2, the slope safety factor is calculated using an infinite slope model, considering the generation of excess pore-water pressure under cyclic loading during earthquakes. Landslide susceptibility is established based on the slope factor of safety. We validated the proposed model by analyzing rainfall-earthquake-induced landslide events occurring on September 6, 2018 in Atsuma, Japan. According to our results, the area under the receiver operating characteristic curve of the Atsuma landslide data is 82% and the true-positive rate of unstable slope classification is 98.1%. The proposed model was then applied to Mt. Umyeon, Korea, to assess the rainfall-earthquake-induced landslide susceptibility. Our model classifies the likelihood of landslide occurrence according to four susceptibility levels: high, moderate, low and very low. We also compared our results to those of previous models and show that the proposed approach may provide reasonably accurate predictions of landslide susceptibility during rainfall and earthquake.

A new rearranged abietane diterpene from Clerodendrum inerme with antioxidant and cytotoxic activities

Ba Vinh, Le,Thi Minh Nguyet, Nguyen,Young Yang, Seo,Hoon Kim, Jang,Thi Vien, Le,Thi Thanh Huong, Phan,Van Thanh, Nguyen,Xuan Cuong, Nguyen,Hoai Nam, Nguyen,Van Minh, Chau,Hwang, Inkyu,Ho Kim, Young Taylor & Francis Health Sciences 2018 NATURAL PRODUCT RESEARCH Vol.32 No.17

Rainfall-Earthquake-Induced Landslide Assessment Using a Deep Neural Networks

Ba-Quang-Vinh Nguyen,Yun-Tae Kim 대한토목학회 2020 대한토목학회 학술대회 Vol.2020 No.10

Two new dammarane-type triterpene saponins from Korean red ginseng and their anti-inflammatory effects

Vinh, Le Ba,Lee, Yunjeong,Han, Yoo Kyong,Kang, Jong Seong,Park, Jung Up,Kim, Young Ran,Yang, Seo Young,Kim, Young Ho Elsevier 2017 Bioorganic & medicinal chemistry letters Vol.27 No.23

<P><B>Abstract</B></P> <P> <I>Panax ginseng</I> has been the subject of extensive research on potential medicinal materials. The goal of this study was search the chemical constituents and biological activities of processed <I>Panax ginseng</I>, Korean red ginseng. Our efforts led to the isolation eleven compounds (<B>1</B>–<B>11</B>) including two new compounds <B>1</B> and <B>2</B> from Korean red ginseng using various chromatographic techniques. Chemical structures of isolated compounds were demonstrated by spectroscopic methods (1D-, 2D-NMR, and HR-ESI-MS). The anti-inflammatory effects of the compounds were investigated by inhibiting IL-6 and TNF-α secretion in LPS-activated RAW264.7 cells. Additionally, the effects of the compounds on the expression of COX-2 and iNOS were examined by Western blotting. Compound <B>1</B> significantly reduced the level of proinflammatory cytokines IL-6 and TNF-α secretion in LPS-activated RAW264.7 cells and the expression of COX-2 and iNOS inflammatory enzymes in the cells. These results suggested that compound <B>1</B>, a new ginsenoside might useful in treatment of inflammation.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Bioactive triterpene glycosides from the fruit of <i>Stauntonia hexaphylla</i> and insights into the molecular mechanism of its inflammatory effects

Ba Vinh, Le,Jang, Hyun-Jae,Viet Phong, Nguyen,Dan, Gao,Won Cho, Kyoung,Ho Kim, Young,Young Yang, Seo Pergamon Press 2019 Bioorganic & medicinal chemistry letters Vol.29 No.16

<P><B>Abstract</B></P> <P>Chromatography of the ethanol extract of the medicinal fruit <I>Stauntonia hexaphylla</I> resulted in the purification of 26 compounds (<B>1</B>–<B>26</B>), including two undescribed triterpene saponins <B>1</B> and <B>2</B> (hexaphylosides A and B). Their structures were confirmed by spectroscopic data, including IR, HR QTOF MS, <SUP>1</SUP>H, <SUP>13</SUP>C NMR, COSY, HMQC, HMBC, and TOCSY, and HPLC sugar analysis after acid hydrolysis. The anti-inflammatory effects of the high-purity constituents (<B>1</B>–<B>26</B>) on lipopolysaccharide (LPS)-induced RAW264.7 macrophage cells were investigated by screening nitric oxide production. The NO inhibitory activity of compounds <B>6</B> and <B>10</B> with the IC<SUB>50</SUB> values of 1.33 and 1.10 µM, respectively. The structure-activity relationships (SAR) of the isolated compounds were also analyzed. Furthermore, compounds <B>6</B> and <B>10</B> inhibited the protein expression inducible nitric oxide synthase (iNOS), and cyclooxygenase (COX)-2 via Western blotting analysis. This showed that compounds <B>6</B> and <B>10</B> contributed to the anti-inflammatory effects of <I>S</I>. <I>hexaphylla</I> fruit, which could be developed as a natural nutraceutical and functional food ingredient.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Two new triterpene saponins <B>1</B> and <B>2</B> were established by unambiguously spectroscopic methods and chemical reaction. </LI> <LI> The ethanol extract, fractions, and isolated compounds showed significant NO inhibitory activities. </LI> <LI> Compounds <B>6</B> and <B>10</B> inhibited iNOS and COX-2 expression. </LI> <LI> The <I>S. hexaphylla</I> fruit could be developed as a natural nutraceutical and functional food ingredient. </LI> </UL> </P> <P><B>Graphic abstract</B></P> <P>[DISPLAY OMISSION]</P>

Spatial probability assessment of landslide considering increases in pore-water pressure during rainfall and earthquakes: Case studies at Atsuma and Mt. Umyeon

Nguyen, Ba-Quang-Vinh,Lee, Seung-Rae,Kim, Yun-Tae Catena Verlag 2020 Catena Vol.187 No.-

<P><B>Abstract</B></P> <P>Increased pore-water pressure due to rainfall infiltration and cyclic loading is a major cause of slope instability. Many studies have been carried out to assess rainfall-induced landslide spatial probability based on physical models, combining hydrological models to analyze changes in pore-water pressure on slopes due to rainfall. However, the generation of pore-water pressure due to seismic loading is often disregarded during assessments of earthquake-induced landslide susceptibility. Hence, in this paper, we propose a model to assess landslide spatial probability that takes into account increased pore-water pressure during both rainfall and earthquakes. The procedure for the proposed method includes two main steps. In step 1, we analyze the change in the groundwater table due to rainfall infiltration and subsurface flow during rainfall. In step 2, the slope safety factor is calculated using an infinite slope model, considering the generation of excess pore-water pressure under cyclic loading during earthquakes. Landslide spatial probability is established based on the slope factor of safety. We validated the proposed model by analyzing rainfall-earthquake-induced landslide events occurring on September 6, 2018 in Atsuma town, Japan. According to our results, the area under the receiver operating characteristic curve of the Atsuma landslide data is 82.4% and the true-positive rate of unstable slope classification is 98.1%. The proposed model was then applied to Mt. Umyeon, Korea, to assess the spatial probability of rainfall-earthquake-induced landslide. Our model classifies the likelihood of landslide occurrence according to four susceptibility levels: high, moderate, low and very low. We also compared our results to those of previous models and show that the proposed approach may provide reasonably accurate predictions of landslide spatial probability during rainfall and earthquake events.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Considering the change in pore-water pressure due to rainfall and earthquake. </LI> <LI> Good performance with real landslide events in Atsuma. </LI> <LI> Cumulative rainfall strongly affect the area of susceptibility class. </LI> <LI> Peak ground acceleration strongly affect the area of susceptibility class. </LI> <LI> Excess pore-water pressure is the main reason for slope instability. </LI> </UL> </P>

Effect of clay fraction and water content on rheological properties of sand-clay mixtures

Nguyen, Vinh Ba Quang,Kang, Hyo-Sub,Kim, Yun-Tae Springer-Verlag 2018 Environmental Earth Sciences Vol.77 No.16

A LQR Neural Network Control Approach for Fast Stabilizing Rotary Inverted Pendulums

Huynh Vinh Nghi,Dinh Phuoc Nhien,Dang Xuan Ba 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.23 No.1

Rotary inverted pendulum (RIP) is a well-known system that is commonly employed as an ideal benchmarking model for verifying linear and nonlinear control algorithms thanks to unique unstable and highly nonlinear natures. In this paper, an intelligent control method is developed for stabilizing such the RIP system in upright posture. The controller is structured from a linear quadratic regulator (LQR) and an online radial basis function (RBF) Neural-Network compensator. The LQR term plays a crucial role in yielding the nominal control signal based on a linearized model. Meanwhile, the neural control term is adopted to suppress the systematic deviation and external disturbances as the system is far from the equilibrium state. A damping segment-wise adaptation rule is proposed to activate the network operation. Stability of the closed-loop system is then proven by Lyapunov analyses. Effectiveness and feasibility of the advanced controller are confirmed throughout comparative simulation and real-time experiments.