scholarly journals Effect of different parameters of heterogeneous dams on safety factor using the neural network. Case study: Marvan dam

2019 ◽  
Vol 32 (02) ◽  
pp. 126-138
Author(s):  
B. Beiranvand ◽  
A. Mohammadzade ◽  
M. Komasi
Keyword(s):  
Neural Network ◽  
Factor Of Safety ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Drainage System ◽  
Friction Angle ◽  
The Body ◽  
The Neural Network ◽  
The Cost

The drainage system is used to guide the flow of water in the earth dams. Construction of drainage in the dam body to collect and direct the drainage formed in the dam body to keep the slope dry and prevent the increase of pore water pressure in the body. One of the main goals of the designers is to find the minimum factor of safety and, consequently, reduce the cost of construction. In this study, the Marvak dam is modeled with the actual characteristics of the materials in the Geostudio software, and with the change in the dimensions of the drain, the material and the slope of the dam body, the minimum Factor of safety of the dam is obtained. In order to predict the minimum Factor of safety, a two-layer neural network has been used. With the training of the neural network based on the data obtained from heterogeneous dams, a minimum Factor of safety has been extracted for optimization of drainage. Finally, it was determined that the internal friction angle of the body material and the slope of the dam have the greatest effect on the dam factor of safety.

Coefficients of active earth pressure with seepage effect

2012 ◽  
Vol 49 (6) ◽  
pp. 651-658 ◽  
Author(s):  
Pérsio L.A. Barros ◽  
Petrucio J. Santos
Keyword(s):  
Pore Water Pressure ◽  
Water Pressure ◽  
Retaining Wall ◽  
Drainage System ◽  
Numerical Procedure ◽  
Ground Surface ◽  
Earth Pressure ◽  
Friction Angle ◽  
Active Earth Pressure ◽  
Plane Failure

A calculation method for the active earth pressure on the possibly inclined face of a retaining wall provided with a drainage system along the soil–structure interface is presented. The soil is cohesionless and fully saturated to the ground surface. This situation may arise during heavy rainstorms. To solve the problem, the water seepage through the soil is first analyzed using a numerical procedure based on the boundary element method. Then, the obtained pore-water pressure is used in a Coulomb-type formulation, which supposes a plane failure surface inside the backfill when the wall movement is enough to put the soil mass in the active state. The formulation provides coefficients of active pressure with seepage effect which can be used to evaluate the active earth thrust on walls of any height. A series of charts with values of the coefficients of active earth pressure with seepage calculated for selected values of the soil internal friction angle, the wall–soil friction angle, and the wall face inclination is presented.

scholarly journals Mechanisms leading to the 2016 giant twin glacier collapses, Aru Range, Tibet

2018 ◽  
Vol 12 (9) ◽  
pp. 2883-2900 ◽  
Author(s):  
Adrien Gilbert ◽  
Silvan Leinss ◽  
Jeffrey Kargel ◽  
Andreas Kääb ◽  
Simon Gascoin ◽  
...  
Keyword(s):  
Pore Water Pressure ◽  
Water Pressure ◽  
Three Dimensional ◽  
Drainage System ◽  
Stress Transfer ◽  
Friction Angle ◽  
Shear Stresses ◽  
Horizontal Distance ◽  
Mountain Glacier ◽  
Caucasus Mountains

Abstract. In north-western Tibet (34.0∘ N, 82.2∘ E) near lake Aru Co, the entire ablation areas of two glaciers (Aru-1 and Aru-2) suddenly collapsed on 17 July and 21 September 2016. The masses transformed into ice avalanches with volumes of 68 and 83×106 m3 and ran out up to 7 km in horizontal distance, killing nine people. The only similar event currently documented is the 130×106 m3 Kolka Glacier rock and ice avalanche of 2002 (Caucasus Mountains). Using climatic reanalysis, remote sensing, and three-dimensional thermo-mechanical modelling, we reconstructed the Aru glaciers' thermal regimes, thicknesses, velocities, basal shear stresses, and ice damage prior to the collapse in detail. Thereby, we highlight the potential of using emergence velocities to constrain basal friction in mountain glacier models. We show that the frictional change leading to the Aru collapses occurred in the temperate areas of the polythermal glaciers and is not related to a rapid thawing of cold-based ice. The two glaciers experienced a similar stress transfer from predominant basal drag towards predominant lateral shearing in the detachment areas and during the 5–6 years before the collapses. A high-friction patch is found under the Aru-2 glacier tongue, but not under the Aru-1 glacier. This difference led to disparate behaviour of both glaciers, making the development of the instability more visible for the Aru-1 glacier through enhanced crevassing and terminus advance over a longer period. In comparison, these signs were observable only over a few days to weeks (crevasses) or were absent (advance) for the Aru-2 glacier. Field investigations reveal that those two glaciers were underlain by soft, highly erodible, and fine-grained sedimentary lithologies. We propose that the specific bedrock lithology played a key role in the two Tibet and the Caucasus Mountains giant glacier collapses documented to date by producing low bed roughness and large amounts of till, rich in clay and silt with a low friction angle. The twin 2016 Aru collapses would thus have been driven by a failing basal substrate linked to increasing pore water pressure in the subglacial drainage system in response to increases in surface melting and rain during the 5–6 years preceding the collapse dates.

The effect of pore-water pressure on NATM tunnel linings in decomposed granite soil

2005 ◽  
Vol 42 (6) ◽  
pp. 1585-1599 ◽  
Author(s):  
J H Shin ◽  
D M Potts ◽  
L Zdravkovic
Keyword(s):  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Drainage System ◽  
Tunnel Lining ◽  
Natm Tunnel ◽  
Decomposed Granite ◽  
Secondary Lining ◽  
Granite Soil ◽  
Functional Components

Tunnelling in a water bearing soil often produces a long-term interaction between the tunnel lining and the surrounding soil. With respect to lining design, infiltration and external pore-water pressures are often one of the most important factors to be considered. Development of pore-water pressure may accelerate leakage and cause deterioration of the lining. This can be particularly troublesome to structural and functional components of the tunnel and can often lead to structural failure. However, as a result of the complicated hydraulic boundary conditions and the long times often required for pore pressure equilibration, research on this subject is scarce. Consequently, most design approaches deal with the effects of pore-water pressure on the tunnel lining in a qualitative manner. In this paper, the development of pore-water pressure and its potential effects on the tunnel lining are investigated using the finite element method. In particular, the deterioration of a drainage system caused by clogging is considered. It is shown that the development of pore-water pressure on the lining is dependent on the lining permeability and the deterioration of the drainage system, particularly for a tunnel with both a primary and a secondary lining. The magnitude of pore-water pressure on a new Austrian tunnelling method (NATM) tunnel constructed in decomposed granite soil and the effect of tunnel shape are investigated. Design curves for estimating pore-water pressure loads on a secondary lining are proposed.Key words: numerical analysis, tunnel lining, decomposed granite.

scholarly journals Optimization of machining parameters during Drilling by Taguchi based Design of Experiments and Validation by Neural Network

2018 ◽  
Vol 15 (2) ◽  
pp. 294-301
Author(s):  
Reddy Sreenivasulu ◽  
Chalamalasetti SrinivasaRao
Keyword(s):  
Neural Network ◽  
Design Of Experiments ◽  
Computational Cost ◽  
Machining Parameters ◽  
Burr Size ◽  
Taguchi Design Of Experiments ◽  
The Neural Network ◽  
Input Parameters ◽  
Hole Making ◽  
The Cost

Drilling is a hole making process on machine components at the time of assembly work, which are identify everywhere. In precise applications, quality and accuracy play a wide role. Nowadays’ industries suffer due to the cost incurred during deburring, especially in precise assemblies such as aerospace/aircraft body structures, marine works and automobile industries. Burrs produced during drilling causes dimensional errors, jamming of parts and misalignment. Therefore, deburring operation after drilling is often required. Now, reducing burr size is a serious topic. In this study experiments are conducted by choosing various input parameters selected from previous researchers. The effect of alteration of drill geometry on thrust force and burr size of drilled hole was investigated by the Taguchi design of experiments and found an optimum combination of the most significant input parameters from ANOVA to get optimum reduction in terms of burr size by design expert software. Drill thrust influences more on burr size. The clearance angle of the drill bit causes variation in thrust. The burr height is observed in this study.  These output results are compared with the neural network software @easy NN plus. Finally, it is concluded that by increasing the number of nodes the computational cost increases and the error in nueral network decreases. Good agreement was shown between the predictive model results and the experimental responses.  

scholarly journals Integrated Simulation Modeling Approach for Investigating Pore Water Pressure Induced Landslides

2022 ◽  
Author(s):  
Sahila Beegum ◽  
P J Jainet ◽  
Dawn Emil ◽  
K P Sudheer ◽  
Saurav Das
Keyword(s):  
Pore Water ◽  
Factor Of Safety ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Simulation Models ◽  
Integrated Simulation ◽  
Hill Slope ◽  
Slope Factor ◽  
The Stability ◽  
The Hill

Abstract Soil pore water pressure analysis is crucial for understanding landslide initiation and prediction. However, field-scale transient pore water pressure measurements are complex. This study investigates the integrated application of simulation models (HYDRUS-2D/3D and GeoStudio–Slope/W) to analyze pore water pressure-induced landslides. The proposed methodology is illustrated and validated using a case study (landslide in India, 2018). Model simulated pore water pressure was correlated with the stability of hillslope, and simulation results were found to be co-aligned with the actual landslide that occurred in 2018. Simulations were carried out for natural and modified hill slope geometry in the study area. The volume of water in the hill slope, temporal and spatial evolution of pore water pressure, and factor of safety were analysed. Results indicated higher stability in natural hillslope (factor of safety of 1.243) compared to modified hill slope (factor of safety of 0.946) despite a higher pore water pressure in the natural hillslope. The study demonstrates the integrated applicability of the physics-based models in analyzing the stability of hill slopes under varying pore water pressure and hill slope geometry and its accuracy in predicting future landslides.

scholarly journals UTILIZING SITE CHARACTERISTICS IN NEURAL NETWORK MODELLING OF PERCENTAGE COST-TIME OVERRUN OF BUILDING PROJECTS

2017 ◽  
Vol 8 (1) ◽  
pp. 1-15
Author(s):  
A. O. Ujene ◽  
A. A. Umoh
Keyword(s):  
Neural Network ◽  
Cost Overrun ◽  
Construction Costs ◽  
Network Modelling ◽  
Building Projects ◽  
The Neural Network ◽  
Site Characteristics ◽  
Neural Network Prediction ◽  
The Cost ◽  
Prediction Approach

This study evaluated the site characteristics influencing the time and cost delivery of building projects, determined the range of percentage cost and time overrun and developed a neural network model for predicting the percentage cost and time overrun using the site characteristics of building projects. The study evaluated twelve site characteristics and two performance indicators obtained from records of construction costs, contract documents, and valuation reports of 126 purposively sampled building projects spread across several cities in Nigeria. Analyses were with descriptive and artificial neural network. It was concluded that with fairly favourable site characteristics, cost overrun range reached 77.95% with a mean variation of 44.36%, while time overrun range reached 51.23% with a mean variation of 26.77%. It was found that the accuracy performance levels of 91.93% and 91.43% for the cost and time overrun predictions respectively were very high for the optimum models. Building projects have eight significant site characteristics which can be used to reliably predict the percentage overrun, among which the ground water level, level of available infrastructure and labour proximity around the site are the most important predictors of cost and time overrun. The study recommended that project owners, consultants, contractors and other stakeholders should always use the eight identified site characteristics in predicting percentage cost and time overrun, with more priority on the first three characteristics. The study also recommended the neural network prediction approach due to its prediction accuracy.

scholarly journals KOMPARASI ALGORITMA NEURAL NETWORK DAN NAÏVE BAYES UNTUK MEMPREDIKSI PENYAKIT JANTUNG

2019 ◽  
Vol 15 (2) ◽  
pp. 189-194 ◽  
Author(s):  
Hendri Mahmud Nawawi ◽  
Jajang Jaya Purnama ◽  
Agung Baitul Hikmah
Keyword(s):  
Neural Network ◽  
Heart Disease ◽  
Naive Bayes ◽  
Healthy Lifestyle ◽  
Naïve Bayes ◽  
The Body ◽  
Early Age ◽  
Regular Exercise ◽  
The Neural Network ◽  
Bayes Algorithm

Heart disease is one of the types of deadly diseases whose treatment must be dealt with as soon as possible because it can occur suddenly to the sufferer.  Factors of heart disease that are recognized based on the condition of the body of a sufferer need to be known from an early age so that the risk of possible instant attacks can be minimized or can be overcome in various ways such as a healthy lifestyle and regular exercise that can regulate heart health in the body.  By looking at the condition of a person's body based on sex, blood pressure, age, whether or not a smoker and some indicators that become a person's characteristics of heart disease are described in a study using the Neural Network and Naïve Bayes algorithm with the aim of comparing the level of accuracy to attributes influential to predict heart disease, so the results of this study can be used as a reference to predict whether a person has heart disease or not.

scholarly journals Field Test Research on Red Clay Slope under Atmospheric Action

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kaisheng Chen
Keyword(s):  
Internal Friction ◽  
Water Content ◽  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Friction Angle ◽  
Internal Friction Angle ◽  
Red Clay ◽  
Failure Characteristics ◽  
Clay Slopes

By embedding water content sensors and pore water pressure sensors inside the red clay slope on-site in Guiyang, Guizhou, shear tests were performed on soil samples at different depths of the slope under different weather. The changes of water content, pore water pressure, and shear strength index of the slope inside the slope under the influence of the atmosphere were tracked and tested, and the failure characteristics and evolution of the red clay slope were analyzed. It is believed that the depth of influence of the atmosphere on red clay slopes is about 0.7 m, rainfall is the most direct climatic factor leading to the instability of red clay slopes, and the evaporation effect is an important prerequisite for the catastrophe of red clay slopes. The cohesion and internal friction angle of the slope soil have a good binary quadratic function relationship with the water content and density. The water content and density can be used to calculate the cohesion and internal friction angle. Failure characteristics of red clay slopes: the overall instability failure is less, mainly surface failure represented by gullies and weathering and spalling, and then gradually evolved into shallow instability failure represented by collapse and slump. The damage evolution law is as follows: splash corrosion and surface corrosion stage⟶ fracture development stage⟶ gully formation stage⟶ gully development through stage⟶ local collapse stage⟶ slope foot collapse stage.

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