scholarly journals Risk Identification of Heavy Rain-induced Muck soil Landslide

CONVERTER ◽  
2021 ◽  
pp. 32-45
Author(s):  
Shaojie Feng, Hang Hu, Aimin Yao, Shiguo Sun
Keyword(s):  
Evaluation Model ◽  
Slope Angle ◽  
Nonlinear Function ◽  
Heavy Rain ◽  
Data Fitting ◽  
Rapid Identification ◽  
Risk Identification ◽  
Landslide Risk ◽  
Muck Soil ◽  
Logistic Regression Method

Based on Monte Carlo method, this paper calculates landslide probability of muck soil slopes under different rainfall time, rainfall intensity, soil permeability coefficient and slope angle, thus obtaining the probability samples of muck soil landslides. On this basis, logistic regression method of nonlinear classification is used for data fitting and analysis, thus establishing nonlinear function . Function expression is derived by data fitting, and a landslide probability evaluation model is constructed. Based on analysis of engineering examples, the error between this method and the numerical calculation results is within 10%, and the evaluation results are reasonable. It provides theoretical support for rapid identification of muck soil landslide risk under heavy rain conditions.

scholarly journals Erosion Failure of a Soil Slope by Heavy Rain: Laboratory Investigation and Modified GA Model of Soil Slope Failure

2019 ◽  
Vol 16 (6) ◽  
pp. 1075 ◽  
Author(s):  
Xiaofei Jing ◽  
Yulong Chen ◽  
Changshu Pan ◽  
Tianwei Yin ◽  
Wensong Wang ◽  
...  
Keyword(s):  
Laboratory Investigation ◽  
Slope Failure ◽  
Slope Angle ◽  
Heavy Rain ◽  
Annual Rainfall ◽  
Soil Slope ◽  
Saturated Zone ◽  
Wetting Front ◽  
Rainfall Condition ◽  
The Impact

Rainfall has been identified as one of the main causes for slope failures in areas where high annual rainfall is experienced. The slope angle is important for its stability during rainfall. This paper aimed to determine the impact of the angle of soil slope on the migration of wetting front in rainfall. The results proved that under the same rainfall condition, more runoff was generated with the increase of slope angle, which resulted in more serious erosion of the soil and the ascent of wetting front. A modified Green-Ampt (GA) model of wetting front was also proposed considering the seepage in the saturated zone and the slope angle. These findings will provide insights into the rainfall-induced failure of soil slopes in terms of angle.

Design of a low-cost Early Warning System (EWS) in informal settlements in Medellín, Colombia (Project Inform@Risk)

2020 ◽  
Author(s):  
Moritz Gamperl ◽  
John Singer ◽  
Kurosch Thuro
Keyword(s):  
At Risk ◽  
Low Cost ◽  
Slope Angle ◽  
Warning System ◽  
Informal Settlements ◽  
Sensor Nodes ◽  
Landslide Risk ◽  
Area At Risk ◽  
Andean Countries ◽  
The City

<p>Recent developments have led to an increased rural depopulation and migration into cities in Andean countries. This is especially the case in Colombia, where immigration from Venezuela has caused an increase in poverty in cities. In Medellín, the second largest Colombian city, this led to an accelerated growth of informal settlements in the steep slopes in the east and west of the city. Combined with the expected increase of heavy rainfall due to climate change, the landslide risk in this area is expected to increase further over the next decades. The risk is highest in the east of the city, where highly weathered dunites are exposed and the slope angle reaches 20-30° and more. In these regions, rotational slides have repeatedly occurred in the past, as detailed mapping has shown.</p><p>The project Inform@Risk tries to strengthen the resilience of these settlements against rainfall induced landslides, since relocation of the inhabitants at risk currently is not a feasible option. For this, an innovative low-cost EWS is being developed in the Barrio Bello Oriente in the east of the city. Since the exact location of a future landslide is unknown, the EWS requires a network of geosensors throughout the whole area at risk, whereby the network density is controlled by the landslide risk. This flexibility is achieved by combining horizontally installed CSM (Continuous Shear Monitor) cables with open-source wireless LoRa sensor nodes. The sensor nodes are developed on basis of an Arduino system and can be installed on infrastructure as well as in the ground. They all include a tilt sensor and additionally can be equipped with varying geotechnical and hydrogeological sensors, depending on the location and measuring target (e.g. piezometer, extensometer, inclinometer/tiltmeter).</p><p>The data produced by the geosensor network is processed by the Inform@Risk server and made available to the residents and municipal stake holders via an app and homepage. Based on meteorological, hydrological and geotechnical analyses the system can evaluate the current and make predictions of the future hazard situation. If necessary, a warning can be issued via app to the inhabitants.  Ultimately, the system should be replicable in other areas in the Andes and elsewhere in the world.</p><p>This work is funded by the German Ministry of Education and Research (BMBF).</p>

scholarly journals Influencing Factors and Evaluation Model of Quality Risks in Intelligent Manufacturing Mobile Supply Chain

2020 ◽  
Vol 53 (6) ◽  
pp. 953-961
Author(s):  
Yujie He
Keyword(s):  
Supply Chain ◽  
Influencing Factors ◽  
Time Management ◽  
Evaluation Model ◽  
Intelligent Manufacturing ◽  
Risk Identification ◽  
Evaluation Index System ◽  
Factors Affecting ◽  
Four Dimensions ◽  
Quality Risk

The intelligent manufacturing (IM) supply chain (SC) involves multiple distributed agents. The mobile supply chain (MSC) technology supports the real-time management of key information resources in the supply chain of IM products. This paper explores the influencing factors and evaluation model of quality risks in IM MSC, trying to make realistic evaluation of the actual quality risks of the enterprise. Firstly, the authors constructed a quality risk identification framework for IM MSC, and a hierarchical evaluation index system (EIS) based on the factors affecting quality risks. Besides, the features and attributes of four dimensions of quality risks were specified, and the corresponding intuitive triangular fuzzy numbers were given. Next, an evaluation model was established for the quality risks of IM MSC based on backpropagation neural network (BPNN). After the evaluation of quality risks, a contract model was designed for the quality risk control in IM MSC. The proposed EIS and models were proved effective through experiments.

scholarly journals Bus passenger flow congestion risk evaluation model based on the Pressure-State-Response framework: A case study in Beijing

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041988356 ◽  
Author(s):  
Siyong Ma ◽  
Jiancheng Weng ◽  
Chang Wang ◽  
Dimitrios Alivanistos ◽  
Pengfei Lin
Keyword(s):  
Network Flow ◽  
Risk Evaluation ◽  
Travel Demand ◽  
Evaluation Model ◽  
Risk Identification ◽  
Risk Level ◽  
Transit System ◽  
State Response ◽  
Passenger Flow ◽  
Pressure State

Urban public transport is a very essential mode for urban residents’ commute travel; however, the unbalanced spatial and temporal distribution of travel demand usually leads to passenger flow congestion risk at certain section and time. Meanwhile, the risk is short of quantified description. Based on the Pressure-State-Response framework, the study puts forward three bus passenger flow congestion risk evaluation indexes including the alternative pressure, the congestion intensity, and the transport efficiency. Then, the evaluation model is proposed based on the entropy method, and the risk is divided into four levels by K-means clustering. The article considers the 3rd Ring Road corridor in Beijing as a case to identify the risk level. The results show that the risk in the peak hours of weekdays is generally about 1.5 times higher than the risk in the weekends. The congestion risk is stable in level 3 during the majority time of morning peak hours. The duration intensity of level 4 risk is less than 0.1 during weekdays, indicating that the highest flow congestion can be quickly evacuated in a short time. The integrated passenger risk identification and evaluation model was proposed to identify the passenger flow risk level and induce the network flow distribution more reasonable. The study also provides technical support for ensuring the public transit system safety.

Risk Evaluation Model of Wind Energy Investment Projects Using Modified Fuzzy Group Decision-making and Monte Carlo Simulation

2020 ◽  
pp. 097674792096322
Author(s):  
Abdolmajid Erfani ◽  
Mehdi Tavakolan
Keyword(s):  
Wind Energy ◽  
Cost Estimation ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Risk Identification ◽  
Energy Investment ◽  
Investment Projects ◽  
Proposed Model ◽  
Energy Projects ◽  
Fuzzy Group Decision Making

The recent increasing trend of investments in wind energy projects to support sustainable development requires an appropriate risk evaluation model to ensure the success of these projects. Early studies focus on opinion and discussion from subject matter experts. However, the expertise level in the subject is varied, and evaluation without considering expert competency can cause biased results. On the other hand, most of the project cost estimation models do not consider uncertainty in all cash flow parameters. In response, this article proposes a model that evaluates risks in wind energy investment projects by considering the knowledge and background of experts. Then, an integrated model of risk evaluation and cost estimation is developed. The model consists of three main stages: risk identification based on a systematic literature review (SLR); risk analysis phase 1 based on a modified fuzzy group decision-making; and risk analysis phase 2 based on a Monte Carlo simulation method. The main advantages of the proposed model are: (a) providing a comprehensive risk identification in wind energy investment projects; (b) using a modified fuzzy model to improve the risk assessment process by considering the expert competency in wind energy projects; and (c) establishing an integrated model to evaluate the cash flow of the investment. A wind farm in the Middle East is selected as the case study to examine the usability and practicality of the proposed model. The results show that the most important risks are ‘change in regulation and policy’, ‘dependency on the international market for importing raw materials’ and ‘market competitiveness’. On the other hand, the financial assessment under uncertainty shows that the profitability of the investment can be varied, and it emphasises the importance of an appropriate risk management process to guarantee the success of the investment.

Study on Naval Vessel Repair Risk Evaluation Model Based on Fuzzy Cognitive Map

2013 ◽  
Vol 668 ◽  
pp. 480-484 ◽  
Author(s):  
Yao Lu ◽  
Li Fang ◽  
Gong Jun
Keyword(s):  
Risk Evaluation ◽  
Evaluation Model ◽  
Risk Identification ◽  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Naval Vessel ◽  
Model Based ◽  
Safety Accident ◽  
Ship Repair ◽  
Risk Evaluation Model

Based on the problems of improper and erroneous repair easily happening during naval vessel repair, a ship repair risk evaluation model was put forth on the basis of risk identification, and then solved and simulated to effectively control the risks of naval vessel repair, reduce the errors of repair, and prevent safety accident.

scholarly journals Rill morphological change characteristics and influencing factors on different soil types in the Loess Plateau, China

2021 ◽  
Author(s):  
zimiao he ◽  
xinxiao yu ◽  
Qiang Cai ◽  
Jijun He ◽  
shilong hao ◽  
...  
Keyword(s):  
Loess Plateau ◽  
Rainfall Intensity ◽  
Sandy Loam ◽  
Slope Angle ◽  
Heavy Rain ◽  
Structure Stability ◽  
Rill Erosion ◽  
Shape Parameters ◽  
The Loess Plateau ◽  
Positive Effect

Soil properties play an important role in rill development and erosion. In this investigation, rill morphology developmental processes under sandy loam (SL), light loam (LL), medium loam (ML) and heavy loam (HL) soils on the Loess Plateau, China, were compared using laboratory experiments. Experimental analysis included two rainfall intensities (90 and 120 mm/h) and four slope treatments (0°, 15°, 20° and 25%). Results indicate that HL is the most prone to rill development, and SL, LL and ML are prone to rill development under heavy rain, with SL rill erosion being the most sensitive to heavy rain. The development of rills in SL are mainly characterized by an increase in rill width and merging nodes; rills in HL were mainly characterized by an increase in rill length, merging nodes and rill number. LL and ML rill development indices were between SL and HL. Differences in runoff collection caused by rill morphology differences further promoted differences in soil erosion. Rainfall intensity has a positive effect on rill shape parameters of all soils; slope has a positive and negative double effect on SL, LL and ML rill shape parameters, and only a positive effect on HL rill shape parameters. The sensitivity of rill parameters to rainfall intensity and slope angle depends on soil infiltration performance, surface soil stability and soil structure stability. Based on soil characteristic factors and rill morphological parameters, an empirical model of slope erosion in the loess region was established.

Spatial Analysis of the Landslide Characteristics Caused by Heavy Rainfall in the Northern Kyushu District in July, 2017 Using Topography, Geology, and Rainfall Levels

2018 ◽  
Vol 13 (5) ◽  
pp. 832-845 ◽  
Author(s):  
Toru Danjo ◽  
◽  
Tomohiro Ishizawa ◽  
Takashi Kimura
Keyword(s):  
Heavy Rainfall ◽  
Metamorphic Rock ◽  
Slope Failure ◽  
Slope Angle ◽  
Heavy Rain ◽  
River Basins ◽  
Trigger Factors ◽  
Rainfall Analysis ◽  
Sediment Disaster ◽  
Kyushu District

The heavy rain in Northern Kyushu District on July 5, 2017 caused a sediment disaster, resulting in the loss of many lives and damage to buildings. In this study, the primary causes (topography and geology) and trigger factors (rainfall) for the sediment disaster were spatially analyzed to examine factors contributing to slope failure. As a result, it was found that the number of slope failures was highest in metamorphic rock areas and the occurrence density of the landslides was highest in plutonic rock areas. In addition, the slope angle of the slope-failure source point was sizable in volcanic rock areas and many landslides occurred in the valley-formed areas. A rainfall analysis showed that the Akatani, Shirakitani, Sozu, Kita, Naragaya, Myoken, Katsura river basins and Ono, Ohi, Sata, Inaibaru river basins are different rainfall distributions, which significantly affected the slope-failure occurrence density.

scholarly journals Effects of Soil Compaction in the Fight against Unpaved Roads Degradation Due to Erosion Caused by Heavy Rain: Proposition of a Specific CBR Evaluation Model

Engineering ◽  
2021 ◽  
Vol 13 (03) ◽  
pp. 95-104
Author(s):  
Timothée Thierry Odi Enyegue ◽  
Eric Flavien Mbiakouo-Djomo ◽  
Hugues Tsanga ◽  
Fabien Kenmogne ◽  
Blaise Ngwem Bayiha ◽  
...  
Keyword(s):  
Soil Compaction ◽  
Evaluation Model ◽  
Heavy Rain ◽  
Unpaved Roads

scholarly journals Impact of geomorphometric parameters on landslide occurrence and distribution in Yamuna River Basin, North-Western Himalaya, India

2021 ◽  
Author(s):  
Ravi Shankar ◽  
Gyan Prakash Satyam ◽  
Prakash Kumar Singh ◽  
Ranjeet Kumar Paswan
Keyword(s):  
Drainage Basin ◽  
Landscape Evolution ◽  
Climatic Factors ◽  
Slope Angle ◽  
Western Himalaya ◽  
Drainage Density ◽  
Landslide Risk ◽  
Yamuna River ◽  
Landslide Occurrence ◽  
The Impact

Abstract Landscape evolution is a dynamic process controlled by several geomorphic parameters along with geology, tectonics and climatic condition of the area. The Himalayan mountain belt is highly geodynamic with immature topography which offer one of the best places to study the impact of geomorphotectonic characteristics on the occurrence and distribution of landslides along with tectonically modified geomorphic features. The morphotectonic study of the drainage basin is extensively utilized to analyze the landscape evolution in the study area along with impact of neotectonic activity in landscape evolution. The study shows that the Yamuna River, originating from the mighty Himalayas, flows downslope by adjusting its course due to ongoing tectonic activities, underlying structures, and climatic factors. Active tectonics play important role in modifying the landscape and impacting the occurrence and distribution of landslides. The characteristics of rainfall induced landslides have been studied in relation to morphotectonic parameters. The analysis shows that the probability density of landslides was highest in the range of 25o-30o and that landslide size increased up to 20o-25o slope angle, decreasing on further increase in slope angle. The study also shows that slope angle merely controls number of landslides rather than size of the landslides. Landslides were mostly restricted to South facing slopes. About 91% of the landslide occur in the drainage density range of 1.2 to 2.1 km/km2 while landslides show very low occurrence in either lower (< 1.2) or higher (> 2.1) drainage density. The present analysis can be very helpful in landslide risk reduction and landslide hazard zonation and probably to plan critical locations for installation of early warning signals.

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