Earthquake Demand Energy Attenuation Model for Liquefaction Potential Assessment

Baziar, Mohammad Hassan; Rostami, Hamid

doi:10.1193/030816eqs037m

Cited by 15 publications

(4 citation statements)

References 35 publications

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“…They collected a data bank and proposed an equation to simply estimate the values of soil capacity strain energy. Regarding the demand energy, Baziar and Rostami (2017) used the seismological parameters of an earthquake to develop a method that can successfully predict earthquake demand strain energy at any site. One of the main advantages of the energy approach is that it considers the effect of the entire shear stress and shear strain time histories simultaneously and is independent of the loading and stress path amplitudes.…”

Section: Energy Approachmentioning

confidence: 99%

Mitigation of liquefaction triggering due to bio-gas-induced desaturation using element tests and the strain energy approach

Baziar

Amirabadi

2021

Earthquake Spectra

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Currently, conventional remediation of liquefaction triggering may have many environmental effects, and this important issue has led researchers to look for more sustainable methods. In this research, one of the new bio-improvement methods (biogas) has been used to generate gas bubbles within a soil, susceptible to liquefaction. Using this method, two bio materials create ammonium ions and carbonate, in which ammonium ion is converted into nitrate due to the presence of bacteria in water, and they are eventually converted to nitrogen gas in an anaerobic condition. The nitrogen bubbles created in water reduce the soil’s degree of saturation, which in effect increases the soil’s resistance to liquefaction occurrence. In this study, two sources of urease enzyme were used to reduce the soil degree of saturation. The effects of various parameters, including the optimum concentration of each substance for optimum time to generate gas bubbles, as well as the effect of the oxygen amount in water were investigated using monotonic triaxial tests. The results illustrated that the addition of the mentioned two substances to the oxab (water with 60 ppm oxygen) or tap water decreased the pore water pressure due to desaturation. Finally, the energy approach was used to test the substance containing the amount of oxab with the highest decrease in pore water generation, here called “optimum selection,” in the cyclic triaxial device, and the results were analyzed to evaluate liquefaction occurrence. The outcome of these results revealed that compared with the strain energy of the non-treated sample, the treated sample had a much higher strain energy; in other words, the treated sample needed a larger amount of loading to trigger liquefaction.

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Section: Energy Approachmentioning

confidence: 99%

Mitigation of liquefaction triggering due to bio-gas-induced desaturation using element tests and the strain energy approach

Baziar

Amirabadi

2021

Earthquake Spectra

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“…where ρ is the mass density of sand and assumed 2000 kg/m 3 , h is the depth of liquefaction zone, and a max is the peak acceleration. The technique has been proved effective [9,11,30]. In Figure 14, reconstructed shear stress-strain loops were shown for calculation of W liq and recalculated parameters σ' m0 and k p were also provided.…”

Section: Energy-based Analysis and Database Buildingmentioning

confidence: 99%

Evaluation of Liquefaction Potential in Saturated Sand under Different Drainage Boundary Conditions—An Energy Approach

Yao

Wang

Liu

et al. 2019

JMSE

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Drainage conditions are supposed to have significant influence on sand liquefaction behavior. An infiltration device was utilized in cyclic triaxial tests to reproduce different drainage conditions by altering dry density of the within silt. Permeability coefficient ratio (kp) was utilized for quantifying the drainage boundary effect. Cyclic triaxial tests were conducted on saturated Fujian standard sand samples. Test results were used to evaluate the liquefaction potential by using the energy approach. It can be concluded that, if kp increases slightly bigger than zero, excess pore water pressure (EPWP) will respond more fiercely, and the dissipated energy that triggers sand liquefaction will be less. By considering kp, an energy-based database was built by taking kp into consideration and different neural network (NN) models were constructed to predict liquefaction potential by energy approaches accurately under different drainage boundary conditions. It was suggested that the neuro-fuzzy (NF)-based NN model has more satisfactory performance.

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“…Nowadays most engineering complex problems are jointed with advances mathematical-based theories (Ebrahimi, Moradi, et al 2016;Ebrahimi, Taleshi, et al 2016;Baziar and Rostami 2017;Gao, Guirao, et al 2018;Gao, Wang, et al 2018;Hamid et al 2018;Fan et al 2019;Gao et al 2019;Liu et al 2019;Qiao, Huang, et al 2019;Qiao, Tian, et al 2019;Zhang et al 2019;Yang 2019a, 2019b;Chen et al 2020;Jinlong et al 2020;Liu, Zhang, Chen, et al 2020;Pourya et al 2020;Zhou, Moayedi, Bahiraei, et al 2020;Zhou, Moayedi, Foong 2020). Advances in technologies of remote sensing data acquisition, along with the increasing use of machine learning algorithms to analyze large sets of biological, biophysical, spectral has contributed to accurate mapping and differentiation of world's landscape (Pettorelli et al 2014;Murray et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of tree-base data mining algorithms in land used/land cover mapping in a semi-arid environment through Landsat 8 OLI image; Shiraz, Iran

Moayedi

Jamali

Gibril

et al. 2020

Geomatics, Natural Hazards and Risk

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Land Use Land Cover (LULC) mapping has been used in different environmental applications including disaster management, risk analysis, heat island mapping, and the effects of urbanization on environmental changes such as floods and droughts in the recent decade. The earth's natural surface coverage including urban infrastructure, surface vegetation, bare soil can be identified with LULC maps. Besides, LULC is one of the most important tasks in natural hazards, planning activities, resource management, and global monitoring studies. The present study aimed to improve the level of land used and land cover change mapping in a semi-arid environment using Landsat 8 Operational Land Imager (OLI) image. In this research, several tree-based algorithms for LULC mapping are used and compared. These algorithms are used in a combination model implementation of WEKA 3.8 and R programming language to provide a method of a fit-for-purpose algorithms for LULC mapping. It is found that Reduced Error Pruning Tree (REP Tree) is the best approach according to the training and test datasets which are four classes including the build-up, soil, roads, and vegetation region pixels in a semi-arid environment. For the training dataset, the best values of Overall Accuracy (OA), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) is determined, 99.7313, 0.002 and 0.0354 as well as for the test dataset are 99.7313, 0.002 and 0.0354, respectively. Finally, trained models of the implemented data mining algorithms are used for the classification of a different dataset without using any training data where the Logical Analysis of Data Tree (LAD Tree) algorithm shows the best performance in terms of OA, MAE, and RMSE with values of 99.2815, 0.0057, and 0.0557 respectively.

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Earthquake Demand Energy Attenuation Model for Liquefaction Potential Assessment

Cited by 15 publications

References 35 publications

Mitigation of liquefaction triggering due to bio-gas-induced desaturation using element tests and the strain energy approach

Mitigation of liquefaction triggering due to bio-gas-induced desaturation using element tests and the strain energy approach

Evaluation of Liquefaction Potential in Saturated Sand under Different Drainage Boundary Conditions—An Energy Approach

Evaluation of tree-base data mining algorithms in land used/land cover mapping in a semi-arid environment through Landsat 8 OLI image; Shiraz, Iran

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