Sharif Digital Repository

The reinforcement of concrete columns with fabric reinforced cementitious matrix (FRCM) is one of the most challenging issues in the construction of concrete structures, as there is still an absence of a promising model to assess their performance. This is because the behavior of such elements is complex and accompanied by a high margin of uncertainty. To address this issue, this study compiles a large dataset of the performance of FRCM-reinforced concrete columns under monotonic load. The obtained dataset is then used to train an artificial neural network (ANN) as a promising method for predicting the compressive strength of concrete columns with acceptable accuracy. Afterward, using a... 

In this paper, an advanced integrated pixel-level method based on the deep convolutional neural network (DCNN) approach named DeepLabv3+ is proposed for weak interlayers detection and quantification. Furthermore, a database containing 32,040 images of limestone, dolomite, loess clay, and red clay is established to verify this method. The proposed model is then trained, validated, and tested via feeding multiple weak interlayers. Moreover, robustness and adaptability of the proposed model are evaluated, and the weak interlayers are extracted. Compared with the fully convolutional network (FCN)-based method and traditional image techniques, the proposed model provides higher accuracy in terms... 

Predicting the way diseases spread in different societies has been thus far documented as one of the most important tools for control strategies and policy-making during a pandemic. This study is to propose a network autoregressive (NAR) model to forecast the number of total currently infected cases with coronavirus disease 2019 (COVID-19) in Iran until the end of December 2021 in view of the disease interactions within the neighboring countries in the region. For this purpose, the COVID-19 data were initially collected for seven regional nations, including Iran, Turkey, Iraq, Azerbaijan, Armenia, Afghanistan, and Pakistan. Thenceforth, a network was established over these countries, and the... 

This paper develops a trend line-based algorithm for signal decomposition in which the adjusted Savitzky–Golay filter is utilized to initiate the decomposition process. In this line, the proposed algorithm determines some special trend lines, mainly composed of the natural frequency of a bridge. An easy-to-implement algorithm is then provided to formulate this process and to decompose the given signal into its components in a systematic way. Additionally, a residual signal is generated by the proposed algorithm to store the detected noise and to reconstruct the original signal. To verify the proposed algorithm in the field of bridge health monitoring, a set of numerical and experimental... 

This study introduces a simple and efficient method to determine the peak floor acceleration (PFA) at different performance levels for three types of plane reinforced concrete (RC) structures: moment-resisting frames (MRFs), infilled–moment-resisting frames (I-MRFs), and wall-frame dual systems (WFDSs). By associating the structural maximum PFA response with the deformation response, the acceleration-sensitive nonstructural components, and the building contents, can be designed to adhere to the performance-based seismic design of the supporting structure. Thus, the proposed method can accompany displacement-based seismic design methods to design acceleration-sensitive nonstructural elements... 

Natural gas hydrate, a crystalline solid existing under high-pressure and low-temperature conditions, has been regarded as a potential alternative energy resource. It is globally widespread and occurs mainly inside the pores of deepwater sediments and sediments under permafrost area. Hydrate production via well depressurization is deemed well-suited to existing technology, in which the pore pressure is lowered, the natural gas hydrate is dissociated into water and gas, and the water and gas are produced from well. This method triggers multiphysics processes such as fluid flow, heat transfer, energy adsorption, chemical reaction and sediment deformation, all of which are dependent on the... 

Due to the interference problems of complex on-site installations attached to shield tunnel lining surface, deep learning models, developed for leakage datasets of shield tunnels, are not prepared to meet engineering requirements. Therefore, it is of utmost importance to optimize the original model based on the characteristics of leakage datasets. For this purpose, the present study adopted Mask R-CNN as the baseline and improved its performance from two aspects, including the properties of shield tunnel leakage datasets and detection errors of the original model in the testing set. With reference to the properties of leakage datasets, the model compression technique was implemented to... 

Much research has been conducted and published on the examination of the behavior of reinforced steel and concrete structures with a FRP system. Nevertheless, the performance of FRP differs from that of FRCM, particularly at high temperature and ultimate strength. The present study provides a review of previous research on structural elements (viz. beams, columns, arches, slabs, and walls) retrofitted with FRCM systems, taking account of various parameters, such as layers, composite types, configurations, and anchors for controlling or delaying failure modes (FMs). Additionally, this paper discussed the details of different FMs observed during experimental tests, such as crushed concrete or...