Showing papers by "Mohsen Hajihassani published in 2020"

On the metaheuristic models for the prediction of cement-metakaolin mortars compressive strength

Abstract: In recent years, metakaolin, as a highly reactive pozzolan, has been in the center of research concerning mortar-based materials. Metakaolin is used as an addition in cement-mortars, substituting the cement fraction to a certain extent, in order to enhance sustainability of cement mortars, both in terms of environmental impact of raw materials production, as well as in terms of improving cement-based mortars durability under environmental actions. However, as metakaolin affects the mechanical performance of cement-based mortars, it is important to know the compressive strength that these blended mortars achieve at 28-days, in terms of structural design. Toward this direction, metaheuristic models such as ANN and Genetic Programming (GP) models have been developed and trained through the use of a database, compiled by available, in the literature, experimental works related to cement and blended cement-metakaolin mortars. In the model development phase, the most important parameters affecting the strength of concrete-based mortars, were investigated and selected. In addition, the effect of the selected transfer functions, as well as the initial values of weights and biases on the performance of ANN models, were also investigated. Based on this analysis, it was shown that ANNs with selected transfer functions (such as the RadialBasis transfer function, the Soft-Max transfer function, and the Normalized Radial Basis transfer function) were, able to reliably simulate the 28-days compressive strength of the cement-based mortars. In addition, it was shown that parameters such as the cement grade and the maximum diameter of aggregates, are very important in determining compressive strength of the cement-based mortars; this is an important finding, because these parameters are usually not taken into account in the research studies concerned in the prediction of compressive strength through computational models.

3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods

Abstract: Tunnel construction in urban areas causes ground displacement which may distort and damage overlying buildings and municipal utilities. It is therefore extremely important to predict tunneling-induced ground movements in tunneling projects. To predict the tunneling-induced ground movements, artificial neural networks (ANNs) have been used as flexible non-linear approximation functions. These methods, however, have significant limitations that decrease their accuracy and applicability. To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. In this paper, a hybrid particle swarm optimization (PSO) algorithm-based ANN is developed to predict the maximum surface settlement and inflection points in transverse and longitudinal directions. Subsequently, the transverse and longitudinal troughs were obtained by means of empirical equations and 3D surface settlement troughs were ploted. For this purpose, extensive data consisting of measured settlements from 123 settlement markers, geotechnical properties and tunneling parameters were collected from the Karaj Urban Railway Project in Iran. The optimum values of PSO parameters were determined with the help of sensitivity analysis. On the other hand, to find the optimal architecture of the network, trial-and-error method was used. The final hybrid model including eight inputs, a hidden layer and three outputs was used to predict transverse and longitudinal tunneling-induced ground movements. The results demonstrated that the proposed model can very accurately predict three-dimensional ground movements induced by tunneling.

Ground Movements Prediction in Shield-Driven Tunnels using Gene Expression Programming

Abstract: The increase in population and traffic in metropolitan areas has led to the development of underground transportation spaces. Therefore, the estimation of the surface settlement caused by the construction of underground structures should be accurately considered. Several methods have been developed to predict tunneling-induced surface settlement. Among these methods, artificial intelligence-based methods have received much attention in recent years. This paper is aimed to develop a model based on Gene Expression Programming (GEP) algorithm to predict surface settlement induced by mechanized tunneling. For this purpose, Tehran Metro Line 6 was simulated numerically to investigate the effects of different parameters on the surface settlement, and 85 datasets were prepared from numerical simulations. Subsequently, several GEP models were implemented using the obtained datasets from numerical simulations and finally, a model with 30 chromosomes and 3 genes was selected as the optimum model. A comparison was made between obtained maximum surface settlements by the proposed GEP model and numerical simulation. The results demonstrated that the proposed model could predict surface settlement induced by mechanized tunneling with a high degree of accuracy. Finally, a mathematical equation was derived from the proposed GEP model, which can be easily used for surface settlement prediction.

An Overview of the Reliability Analysis Methods of Tunneling Equipment

Abstract: The absolute prevention of damage occurrence is not possible, thus reducing the probability of failure in a system and its impact is very important regarding the operation of a whole system. A failure in a system or in its subsystems makes negative results such as the stop in the production process, rising labor costs, and increasing the cost of maintenance. Reliability, in recent years, is mentioned as one of the most significant aspects of the quality of goods and services. In the past, reliability concerned sensitive and complex industries such as military, nuclear, and aerospace where the lack of their reliability could cause irreparable damage to the entire system. However, today it has become a universal concern. Tunneling equipment has grown in size and complexity and therefore, lack of reliability may cause massive costs to this equipment. Therefore, reliability determination in order to identify the components and subsystems with low reliability is essential. The aim of this study is to review the methods of tunneling equipment reliability analysis including statistical analysis, failure mode and effects analysis, Markov and fault tree methods. In addition, previous available research on the reliability analysis of tunneling equipment is presented.

A Review on Tunnel–Pile Interaction Applied by Physical Modeling

Abstract: Tunneling close beneath piles is becoming increasingly common in densely populated areas. It has therefore become important to understand more about the mechanism of the soil movements and interaction between the tunnel and piles. Physical modeling, which can replicate the actual tunnel construction and related process, is most widely used to investigate the mechanism of pile–tunnel interaction and validate the predicted results by other solutions. This paper presents a review of studies on that matter followed by a quantitative comparison of the pile movements and loads due to tunneling. In this regard, all previous studies of physical modeling of the prototype including single and multiple gravity tests have been reviewed. In addition, modeling of pile–tunnel interaction has been categorized into two groups of tunneling with the existence of single pile and group of piles. Finally, the results and findings of the most recent studies in the field of tunnel–pile interaction have been discussed. Collecting and analyzing of these data provide a better understanding of the interaction as well as indicating where further research is needed.

Clogging Potential of Earth-Pressure Balance Shield Driven Tunnels

Abstract: Nowadays, the construction of urban tunnels for rapid transportation in metropolises is necessary. Since these tunnels are excavated at low depths, they are often associated with different problems and hazards. Some of them can reduce the efficiency of the tunnel boring machines and sometimes will stop the project. Among these problems the clogging can cause problems at the cutter head, in the chamber, and in other sections where the material transference occurs.

Numerical Investigation of Innovative Support Frame of Openings in the Segmental Tunnel Lining

Abstract: To supply safety in the tunnels, it is necessary to construct escape routes and emergency exits that are performed by locating cross passages. These passages connect two tunnels transversely and apply escape routes. Using temporary steel structures to supply the ring stability in practice and reinforced concrete frame to stabilize the ring permanently can be appropriate to form a solid frame that transfers the opened ring's load to the opening surroundings. In this paper, a 3D finite element simulation was performed to analyze the influence of opening construction in the segmental concrete lining and a temporary support system. Using the simulation, stress and deformation distribution of the steel frame, bolts, and segmental lining were obtained. The results show that by increasing the number of bolts from 18 to 30, the induced stress in the steel frame and bolts decreased to 76 and 59 percent, respectively. In addition, the maximum displacement in the segmental lining and the maximum opening value of the joints decline to 62.7 and 75 percent, respectively. Finally, it can be concluded that the steel frame can be used as a temporary support system.