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... 

With frequent heatwaves and drought-downpour cycles, climate change gives rise to severe desiccation cracks. In this research, a probabilistic machine learning (ML) framework is developed to improve the deterministic models. Therefore, a complete set of data-driven soil and environment parameters, including initial water content (IWC), crack water content (CWC), final water content (FWC), soil layer thickness (SLT), temperature (Temp), and relative humidity (RH), is utilized as inputs to predict the crack surface ratio (CSR). Also, a comprehensive set of MLs, including an ensemble of regression trees (i.e., random forests [RF] and regression trees [RT]), gradient-boosted trees (viz. GBT and... 

Parametric three-dimensional (3D) finite element analyses (FEAs) were performed for eccentrically loaded reinforced concrete (R/C) short columns, strengthened with textile-reinforced mortar (TRM), under cyclic loading. Damage states of R/C columns were determined before and after strengthening to evaluate TRM efficiency for each state: steel reinforcement yielding, concrete crack on tensile face, and concrete crushing on compressive face. Each column, corresponding to different damage states, was strengthened with TRM, assuming various schemes along with an assorted number of layers. Employing a rigorous 3D-FE model, a comprehensive parametric study was conducted to assess the effects of... 

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... 

Prediction of thermal crack propagation in desiccated soils is imperfect due to the obscure field measurements, modeling approximations, and the underlying soil uncertainties. To address these issues, a probabilistic framework is developed to quantify the uncertainties and enhance the crack estimation reliability. Hence, the uncertainties associated with the soil properties, including the tensile strength, matric suction, Poisson's ratio, elastic modulus and suction ratio are associated in a probabilistic model. Then, the probabilistic model is utilized with the improved Monte Carlo simulation to calculate the failure probability due to the exceedance of the crack propagation. Furthermore,... 

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... 

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... 

A probabilistic method is proposed in this study to predict the spreading profile of the coronavirus disease 2019 (COVID-19) in the United State (US) via time-variant reliability analysis. To this end, an extended susceptible-exposed-infected-vaccinated-recovered (SEIVR) epidemic model is first established deterministically, considering the quarantine and vaccination effects, and then applied to the available COVID-19 data from US. Afterwards, the prediction results are described as a time-series of the number of people infected, recovered, and dead. Upon introducing the extended SEIVR model into a limit-state function and defining the model parameters including transmission, recovery, and... 

Rockfall is a significant hazard to sites that are located at the foot of rock slopes. In such sites, there is a notable need to evaluate the potential for rockfall, estimate the extent of areas at risk, and design retaining structures to reduce the risk of rockfall-induced. This paper presents a probabilistic framework for predicting the formation and progression of rockfalls and for evaluating the performance of retaining walls under rockfalls. To this end, first a probabilistic model for the rock projectile motion on a slope is presented. The model accounts for prevailing uncertainties, i.e., the trigger points, rock shape, projectile path, and slope material properties, which include... 

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... 

This paper presents a review of the existing models for the estimation of explosion-induced crushed and cracked zones. The control of these zones is of utmost importance in the rock explosion design, since it aims at optimizing the fragmentation and, as a result, minimizing the fine grain production and recovery cycle. Moreover, this optimization can reduce the damage beyond the set border and align the excavation plan with the geometric design. The models are categorized into three groups based on the approach, i.e., analytical, numerical, and experimental approaches, and for each group, the relevant studies are classified and presented in a comprehensive manner. More specifically, in the... 

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... 

This paper is to investigate the extent and speed of the spread of the coronavirus disease 2019 (COVID-19) pandemic in the United States (US). For this purpose, the fractional form of the susceptible-exposed-infected-recovered-vaccinated-quarantined-hospitalized-social distancing (SEIR-VQHP) model is initially developed, considering the effects of social distancing, quarantine, hospitalization, and vaccination. Then, a Monte Carlo-based back analysis method is proposed by defining the model parameters, viz. the effects of social distancing rate (α), infection rate (β), vaccination rate (ρ), average latency period (γ), infection-to-quarantine rate (E), time-dependent recovery rate (λ),... 

Using multiple antennas at the transmit and receive sides of a passive radar brings both the benefits of MIMO radar and passive radar. However one of the obstacles arisen in such configuration is the receive antennas placement in proper positions so that the radar performance is improved. Here we just consider the case of positioning one receiver among multiple illuminators of opportunity. Indeed it is a start for the solution of optimizing the geometry of the multiple receivers in a passive radar  

SbCl3 supported on montmorillonite K-10 is an efficient catalyst for the ring opening of epoxides with aromatic amines under solvent-free conditions and microwave irradiation to give the corresponding b-amino alcohols in high yields with high regioselectivity  

In this paper, we consider an integrated sensing and communication (ISAC) system with wireless power transfer (WPT) where an unmanned aerial vehicle (UAV)-based radar serves a group of energy-limited communication users in addition to its sensing functionality. In this architecture, the radar senses the environment in phase 1 (namely sensing phase) and mean-while, the communications users (nodes) harvest and store the energy from the radar transmit signal. The stored energy is then used for information transmission from the nodes to UAV in phase 2, i.e., uplink phase. Performance of the radar system depends on the transmit signal as well as the receive filter; the energy of the transmit... 

One of the important obstacles in MIMO (Multiple Input Multiple Output) radars is the issue of designing proper transmit signals. Indeed, the capability of signal design is a significant advantage in MIMO radars, through which, the system can achieve much better performance. Many different aspects of this performance improvement have been considered yet, and the transmit signals have been designed to attain such goal, e.g., getting higher SNR or better detector's performance at the receiver. However, an important tool for evaluating the radar's performance is its ambiguity function. In this paper, we consider the problem of transmit signal design, in order to optimize the ambiguity function... 

Two gains play key roles in recently developed MIMO wireless communication systems: "spatial diversity" gain and "spatial multiplexing" gain. The diversity gain refers to the capability to decrease the error rate of the MIMO channel, while the multiplexing gain implicitly refers to the amount of increase in the capacity of the MIMO channel. It has been shown that there is a fundamental tradeoff between these two types of gains, meaning interplay between increasing reliability (via an increase in the diversity gain) and increasing data rate (via an increase in the multiplexing gain). On the other hand, recently, MIMO radars have attracted much attention for their superior ability to enhance... 

It is a well known fact that using multiple antennas at transmit and receive sides improves the detection performance. However, in such multiple-input multiple-output (MIMO) configuration, proper positioning of transmitters and receivers is a big challenge that can have significant influence on the performance of the overall system. In addition, determining the power of each transmitter under a total power constraint is a problem that should be solved in order to enhance the performance and coverage of such a system. In this paper, we design the Neyman-Pearson detector under the Rayleigh scatter model and use it to introduce a criterion for the antenna placement at both transmit and receive... 

There has been much interest, recently, towards exploiting the Multiple-Input Multiple-Output (MIMO) technique in radar. It is shown that using multiple antennas at transmit and receive sides can improve the performance of the system. However, in order to analyze the system's performance, its ambiguity function, i.e. the ambiguity function of a MIMO radar, is needed to be defined. In this paper, beginning from the information theoretic definitions, we derive such function, specifically for a MIMO radar with widely separated antennas