73 research outputs found

    MODELIRANJE NEIZRAVNOM LOGIKOM U PREDVIĐANJU STUPNJA GEOTEHNIČKIH RIZIKA KOD BUŠENJA STIJENA METODOM STROJNOGA BUŠENJA TUNELA

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    This study aims to analyze the level of geotechnical risks and predict the advance rate in rock Tunnel Boring Machine (TBM) tunnelling, using a multi-stage fuzzy logic modelling. Twelve parameters, affecting the geotechnical hazard scenario occurrence, which were clustered into five groups, were used as input parameters and the risk level was used as an output parameter. Also, based on the relation between the risk levels and advance rates, a predictive model for advance rate prediction was proposed. To validate the performance of modelling carried out, data from 58 geological zones in section two of the Zagros tunnel, Iran were used. The obtained results showed that by using the fuzzy logic-based model, in most zones, the risk levels estimated are in good agreement with field observations. Moreover, as expected, the high coefficient of determination (R2) of 0.91 between the risk level estimated and the average advance rate achieved in 58 analyzed zones, confirms the ability of the model proposed to predict the level of geotechnical risks. Furthermore, R2= 0.93, Root Mean Square Error (RMSE) of 0.62 and Variance Accounted For (VAF) of 97.51 between the measured and predicted advance rates show the good performance of the new predictive model developed for the advance rate estimation.U radu je analiziran stupanj geotehničkoga rizika i iznosa napredovanja kod bušenja tunela u stijenama metodom strojnoga bušenja tunela. Pri tomu je uporabljeno višestupanjsko modeliranje neizravnom logikom. Promatrano je 12 varijabli koje utječu na pojavu geotehničkoga rizika. One su svrstane u 5 skupina obilježenih vrijednostima rizika. Predviđen je model napredovanja bušenjem, na temelju rizika i brzine bušenja. Model je provjeren podatcima iz 58 geoloških zona koje su opažene tijekom bušenja sekcije broj 2 u tunelu Zagros (Iran). Rezultati pokazuju kako je primjena neizravne logike u većini zona dovela do procjene rizika koja je u skladu s terenskim opažanjima. Nadalje, velik iznos koeficijenta determinacije (0,91) između procijenjenoga rizika i prosječnoga stupnja napredovanja u 58 zona potvrdio je primjenjivost modela za predviđanje geotehničkoga rizika. Osim toga, vrijednosti R2 = 0,93, srednje kvadratne pogrješke 0,62 i varijance 97,51 između izmjerenoga i predviđenoga iznosa napredovanja pokazale su se vrlo uporabljivim za izradbu novoga modela predviđanja stupnja napredovanja

    Risk Assessment Based on Combined Weighting-Cloud Model of Tunnel Construction

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    In order to reduce the tunnel construction accidents and ensure the safety of personnel, a comprehensive assessment method of tunnel construction risk based on combination weighting and cloud model is constructed according to the characteristics of tunnel construction. The risk assessment index system is established based on researches on engineering geological condition, natural environmental condition, Tunnel engineering design scheme and construction management. On this basis, the tunnel risk is divided into 4 levels and the index risk level standard is proposed. In order to improve the rationality of weighting, a weight calculation method based on AHP, entropy method and Lagrange multiplier method is constructed. Finally, the normal cloud generator is used to form comparison pictures of risk clouds and standard clouds, which demonstrates the risk status of the evaluation indexes at all levels. With reference to Deda Tunnel of Sichuan-Tibet Railway engineering of high integrated risk level, management decision-making is required. The evaluation results are basically consistent with engineering practices, proving that the method has good feasibility and applicability

    Landslides and Cultural Heritage—A Review

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    Cultural heritage sites can be affected by landslides, often causing damage to their integrity, value, and accessibility. Several studies worldwide were focused on the assessment of the potential threats that landslides can pose to the preservation of cultural heritage sites. This article aims to review landslide studies at cultural heritage sites worldwide, analyzing the publications’ temporal distribution, selected methods, geographical and climate contexts, and investigated landslide types. We analyzed a database of 331 publications from 2000 to 2023 in study areas distributed across 47 countries, compiled through systematic queries of theWeb of Science and Scopus catalogs. The results show an increase in the number of publications from 2012 onwards, with most studies performing landslide susceptibility analyses on cultural heritage sites

    Integration of natural and technological risks in Lombardy, Italy

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    Abstract. Multi-risk assessment is becoming a valuable tool for land planning, emergency management and the deployment of mitigation strategies. Multi-risk maps combine all available information about hazard, vulnerability, and exposed values related to different dangerous phenomena, and provide a quantitative support to complex decision making. We analyse and integrate through an indicator-based approach nine major threats affecting the Lombardy Region (Northern Italy, 25 000 km2), namely landslide, avalanche, flood, wildfire, seismic, meteorological, industrial (technological) risks; road accidents, and work injuries. For each threat, we develop a set of indicators that express the physical risk and the coping capacity or system resilience. By combining these indicators through different weighting strategies (i.e. budgetary allocation, and fuzzy logic), we calculate a total risk for each threat. Then, we integrate these risks by applying AHP (Analytic Hierarchy Process) weighting, and we derive a set of multi-risk maps. Eventually, we identify the dominant risks for each zone, and a number of risk hot-spot areas. The proposed approach can be applied with different degree of detail depending on the quality of the available data. This allows the application of the method even in case of non homogeneous data, which is often the case for regional scale analyses. Moreover, it allows the integration of different risk types or metrics. Relative risk scores are provided from this methodology, not directly accounting for the temporal occurrence probability of the phenomena

    Analytical Hierarchical Modeling Of Glacial Lake Outburst Flood Potential In The Khumbu Region, Nepal

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    The Himalayas have seen increasingly devastating glacial lake outburst floods (GLOF), particularly in recent years. These floods are becoming more significant and common as the climate continues to rapidly warm in the region, making accurate and frequent accounting of GLOF hazards a top priority. This study presents a methodology for efficiently modeling GLOF hazards using predominately free, global satellite remote sensing data in conjunction with an analytical hierarchical model (AHP) to inventory GLOF hazards in the Khumbu Region. Findings indicate rapidly retreating and thinning glaciers with a 34% increase in lake area, including a 303% increase in supraglacial water area. Using Imja Tsho to evaluate the sensitivity of the model, 25 potentially hazardous lakes are delineated, with four classified as very high risk and four classified as an extreme risk. Imja Tsho and Lumding Tsho rank as the highest-risk glacial lakes, with Lumding Tsho increasing its growth rate 77% percent in 2013-2019 versus 1962-2007. Unlike Imja Tsho, no mitigation work is in place to reduce the risk posed by Lumding Tsho, and few in situ studies have been conducted. Based on these findings, it is critical to form a mitigation plan to lower the risk associated with Lumding Tsho and assess the potential impact of an outburst event. Projected warming of the region and associated increase in GLOF hazard shows the continued study of GLOF hazards and mitigation is crucial to protecting vulnerable communities

    Decision aid system founded on nonlinear valuation, dispersion-based weighting and correlative aggregation for wire rope selection in slope stability cable nets

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    This paper presents a decision aid system to address hierarchically structured decision-making problems based on the determination of the satisfaction provided by a group of alternatives in relation to multiple conflicting subcriteria grouped into criteria. The system combines the action of three new methods related to the following concepts: nonlinear valuation, dispersion-based weighting and correlative aggregation. The first includes five value functions that allow the conversion of the ratings of the alternatives regarding the subcriteria into the satisfaction they produce in a versatile and simple manner through the Beta Cumulative Distribution Function. The use of measures of dispersion to weight the subcriteria by giving more importance to those factors that can make a difference due to their heterogeneity is revised to validate it when the values are not normally distributed. Dependencies between subcriteria are taken into account through the determination of their correlation coefficients, whose incorporation adjusts the results provided by the system to favour those alternatives having a balanced behaviour with respect to conflicting aspects. The overall satisfaction provided by each alternative is determined using a prioritisation operator to avoid compensation between criteria when aggregating the subcriteria. The system was tested through a novel field of application such as the selection of wire rope to form slope stability cable nets.The authors wish to express their gratitude to the IP department of INCHALAM S.A., whose collaboration and support made this paper possible

    Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

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    Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control. Iran is one of the most seismically active countries in the world. The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria. An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes. Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria. The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes. The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1. The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95%. A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map. The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure. The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

    Investigation of rockfall and slope instability with advanced geotechnical methods and ASTER images

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    The objective of this thesis was to identify the mechanisms associated with the recurrence of rock-slope instability along the R518 and R523 roads in Limpopo. Advanced geotechnical methods and ASTER imagery were used for the purpose while a predictive rockfall hazard rating matrix chart and rock slope stability charts for unsaturated sensitive clay soil and rock slopes were to be developed. The influence of extreme rainfall on the slope stability of the sensitive clay soil was also evaluated. To achieve the above, field observations, geological mapping, kinematic analysis, and limit equilibrium were performed. The latter involved toppling, transitional and rotational analyses. Numerical simulation was finally resorted to. The following software packages were employed: SWEDGE, SLIDE, RocData, RocFall, DIPS, RocPlane, and Phase 2. The simulation outputs were analyzed in conjunction with ASTER images. The advanced remote sensing data paved the way for landslide susceptibility analysis. From all the above, rockfall hazard prediction charts and slope stability prediction charts were developed. Several factors were also shown by numerical simulation to influence slope instability in the area of study, i.e. sites along the R518 and R523 roads in the Thulamela Municipality. The most important factors are extreme rainfall, steep slopes, geological features and water streams in the region, and improper road construction. Owing to the complexity of the failure mechanisms in the study area, it was concluded that both slope stability prediction charts and rock hazard matrix charts are very useful. They indeed enable one to characterize slope instability in sensitive clay soils as well as rockfall hazards in the study area. It is however recommended that future work is undertaken to explore the use of sophisticated and scientific methods. This is instrumental in the development of predictive tools for rock deformation and displacement in landslide events.Electrical and Mining EngineeringD. Phil. (Mining Engineering

    Assessment of earthquake-triggered landslides in Central Nepal

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    Landslides are recurrent in Nepal due to active tectonics, high precipitation, complex topography, geology, and land use practices. Reliable landslide susceptibility maps are crucial for effective disaster management. Ongoing research has improved landslide mapping approaches, while further efforts are needed to assess inventories and enhance susceptibility mapping methods. This thesis aims to evaluate the landslides caused by the Gorkha earthquake in 2015 and develop reliable landslide susceptibility maps using statistical and geospatial techniques. There are four main objectives: (i) proposing clustering-based sampling strategies to increase the efficiency of landslide susceptibility maps over random selection methods, (ii) identifying and delineating effective landslide mapping units, (iii) proposing an innovative framework for comparing inventories and their corresponding susceptibility maps, and (iv) implementing a methodology for landslide-specific susceptibility mapping. Firstly, a comprehensive Gorkha earthquake-induced landslide inventory was initially compiled, and six unsupervised clustering algorithms were employed to generate six distinct training datasets. An additional training dataset was also prepared using a randomised approach. Among the tested algorithms, the Expectation Maximization using the Gaussian Mixture Model (EM/GMM) demonstrated the highest accuracy, confirming the importance of prioritising clustering patterns for training landslide inventory datasets. Secondly, slope units were introduced as an effective mapping unit for assessing landslides, delineating 112,674 slope unit polygons over an approximately 43,000 km2 area in Central Nepal. This is the first instance of generating such comprehensive mapping and making it publicly accessible. Thirdly, a comparison of five post-Gorkha earthquake inventories and susceptibility was conducted, revealing similarities in causative factors and map performance but variations in spatial patterns. Lastly, a rockfall inventory along two significant highways was developed as a landslide-classified inventory, and the rockfall susceptibility was evaluated. A segment-wise map with a 1 to 5 scale indicating low to high susceptibility was published for public use. This thesis proposes new approaches to landslide inventory sampling and earthquake-triggered landslide assessment. It provides publicly accessible databases for Central Nepal's slope unit map and rockfall susceptibility along the major highways. These findings can benefit researchers, planners, and policymakers to enhance risk management practices by advancing landslide assessment, particularly for earthquake-induced landslides in Central Nepal
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