The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world.

A correlation based on pressuremeter, SPT and CPT tests for characterizing of coastal alluvium: A study for phase 14 South Pars, Iran.

Pressuremeter Test (PMT), Cone Penetration Test (CPT), and Standard Penetration Test (SPT) are the key in-situ experiments to directly estimate the in-situ modulus of deformation and strength parameters of soils, which are highly used in coastal alluvium. In addition, CPT and SPT are unique tests for estimating engineering properties that are ideal for onshore regions. These tests are adaptable for coastal alluvium with different saturation levels, which facilitates the determination of the field deformation modulus.

A Deep Learning Method for the Prediction of the Index Mechanical Properties and Strength Parameters of Marlstone.

The index mechanical properties, strength, and stiffness parameters of rock materials (i.e., uniaxial compressive strength, c, ϕ, E, and G) are critical factors in the proper geotechnical design of rock structures.

A novel empirical classification method for weak rock slope stability analysis.

This study presents a novel empirical classification system for stability analysis of rock slopes in weak rock based on their geotechnical and geological properties. For this purpose, consideration is given to the marly rock slopes, which include three main groups of weak rock (lime marlstone, marlstone, and marly limestone). The 40 different slopes located in the South Pars special zone (Assalouyeh), southwest of Iran, are targeted in classification.

A Q-based empirical method to stability assessment of mountain rock slopes in multiple faults zone: A case for North of Tabriz.

The present article provides an empirical relationship for rock slope stability assessment based on Q classification. The relationship is used as a correction procedure for classic Q for mountain regions with multiple fractures related to several faults. The relationship is derived from 25 distinct jointed slopes near the North Tabriz Fault (NTF).

Deep learning-based landslide susceptibility mapping.

Landslides are considered as one of the most devastating natural hazards in Iran, causing extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas can be used to plan for and mitigate the consequences of catastrophic landsliding events. Here, we developed a deep convolutional neural network (CNN-DNN) for mapping landslide susceptibility, and evaluated it on the Isfahan province, Iran, which has not previously been assessed on such a scale.

An empirical classification method for South Pars marls by Schmidt hammer rebound index.

The presented article provides an experimental classification for South Pars marls (SPM), southwest of Iran, using the Schmidt hammer rebound index, marl geological classes, and SPM geo-engineering characteristics. In this regard, 45 samples of marls (rock) are selected on the studied site and tested by geotechnical in-situ and laboratory tests such as Schmidt hammer, uniaxial compressive strength (UCS), laboratory direct-shear (LDS) to estimate the geo-engineering characteristics of SPM. These specimens are categorised by Pettijohn's marl classification in 3 main groups (concluded argillaceous lime, calcareous marl, and marlstone) and established the geologic class and geo-engineering properties as well as Schmidt hammer rebound index.

An empirical method for slope mass rating-Q correlation for Isfahan province, Iran.

The presented article provides an empirical method on rock slope classification, slope mass rating (SMR), Q, stability condition, failure type and stabilisation procedures for 35 road/railway discontinuous rock slopes after field surveys in Isfahan Province of Iran. Also, it presents the empirical correlation for SMR and Q classification system that prepares a link between the stability status (safety factor, reliability condition) and stabilisations (failure mechanism, support system) which performed on natural/trench slopes cases related sedimentary rocks cuts in the studied region. As results, the SMR-Q equation for Isfahan Province obtained as SMR = 11.

Discontinuous rock slope stability analysis under blocky structural sliding by fuzzy key-block analysis method.

This study presents a fuzzy logical decision-making algorithm based on block theory to effectively determine discontinuous rock slope reliability under various wedge and planar slip scenarios. The algorithm was developed to provide rapid response operations without the need for extensive quantitative stability evaluations based on the rock slope sustainability ratio. The fuzzy key-block analysis method utilises a weighted rational decision (multi-criteria decision-making) function to prepare the 'degree of reliability (degree of stability-instability contingency)' for slopes as implemented through the Mathematica software package.