جستجوی مقالات مرتبط با کلیدواژه "مدل سازی" در نشریات گروه "عمران"

Most of the noise pollution in big cities is related to traffic, and the construction of highways and traffic flow with high volume and speed creates problems for the nearby residents. Calculating the amount of noise pollution through modeling makes it possible to reduce the effects of noise pollution in the design of highways and surrounding uses. This research, which was conducted on the Hashemi Rafsanjani highway (Misthaq) in Mashhad, by measuring the volume of sound, traffic information, weather information and surrounding uses, using the American federal highway management model (FHWA) with TNM 2.5 software models the emission of noise pollution and compares the obtained results with the measurements made through statistical analysis. The following steps were implemented for this research: 1- collecting information about the volume and speed of traffic, 2- collecting information and characteristics related to the road such as road width, road type, surrounding land use map, green space around the highway, height and density of buildings around the highway, meteorological information such as temperature and humidity, 4- determining sensitive points around the area in terms of noise pollution, such as residential, medical, educational centers, etc., and measuring sound in sensitive points as sound receptors, 5- modeling by TNM 2.5 software, AutoCAD map or GIS layers for the scope of the project should be prepared and converted to DXF format, 6- statistical analysis and comparison of the results obtained through the model and measurements and comparison with the standards, and 7- testing the hypotheses through SPSS statistical software and analyzing the results in the Excel environment. The estimated results of the FHWA model were very close to the observed values (The highest value is 85 db and the lowest value is 55 db), therefore, according to the results of this model, it is reasonably accurate for predicting noise pollution, and the average difference of the Leq values ​​calculated with the measured values ​​is ±3.5 dB. The regression coefficient between the measured values ​​and the values ​​calculated by the model was reported as 0.685. The amount of difference of the predicted values ​​is relatively high only in three stations 1, 7 and 24 and is equal to 14.8, 10.7 and 10.7 dB respectively. In examining the cause of this issue, it can be stated that two stations 1 and 7 are located in a position where, in addition to the sound they receive from the studied highway, they are affected by the traffic of vehicles on other routes near them and receive sound. In the study area, due to the fact that the majority of uses are residential, which is considered as a sensitive area, all measured values ​​in the stations were higher than the standard of the Environmental Protection Organization (55 db). The lowest recorded sound is related to station number 36 with a level of 55.4 dB. This station is located inside the barren lands and is connected to the agricultural lands located between Amirieh and Esmatiye boulevards. The average amount of noise pollution in all stations is 74. The highest sound value is related to station number 24 and is equal to 85.1 dB, which is located at the beginning of Hashemi Street 45 and the dominant use around it is residential. Due to the large number of vehicles, including cars, heavy vehicles, buses, semi-heavy and motorcycles, all areas show high noise pollution that can endanger the health of citizens. The effect of car type was investigated by Pearson's test, and there was the highest correlation between motorcycles and noise pollution, as the number of motorcycles increased, the value of the two noise indices LAeq and LAFmn increased with correlation coefficients of 83% and 84%. In this regard, it is necessary to take necessary measures such as replacing with new electric motorcycles. Allocation of land around highways to sensitive uses, including medical and educational centers, has not been approved, and the effects of noise pollution can be reduced through appropriate planning. There are several solutions to reduce the effects of noise pollution, based on priority, it is possible to correctly locate the uses, consider the distance between highways and sensitive uses, assign this distance to uses such as linear green space, footpaths and bicycles, the creation of barriers that reduce sound waves such as embankment, trees and finally the last priority of using technical equipment such as acoustic wall.

In this study, a model for pricing taxi services is presented with the goal of making the model fair and transparent in a way that reflects the value of the services the taxi provides to the customers while also taking into account various factors that influence the cost of the services. The major pricing strategy in this model bases the taxi fee on the distance covered during the journey. Additionally, the duration of the trip is taken into account because some people may choose a longer journey others may the length of the trip can be longer than normal because of the traffic. The hourly rate of time is taken into account to account for this anomaly. By dividing the hourly rate of travel time by the additional cost, the duration of the journey is determined based on the conditions anticipated by the model. Different pricing strategies are utilized for various hours and designated time periods to control the demand. Price discrimination is the foundation of this tactic. By managing demand, it makes cabs available even during rush hour. In order to accurately and fairly compute the cost based on the real time and distance traveled, the pricing model developed in this research takes into account all the aspects impacting the service for four different modes of operation. Comparing the predicted costs using the research's methodology reveals that practically current fares are unprofitable.

One of the key elements to achieve economic growth and development of the country is financial stability. According to the empirical evidence in recent years and the intertwining of the financial system and the economic development of countries, high economic growth cannot be considered, but it was not successful in the financial markets. Therefore, considering the importance of the combined index of financial and economic stability in the economic growth and development of the country and especially the road transport sector, in this study the role of the combined index of financial and economic stability in the road transport sector of the country during the period of 1370-1401 has been examined. In the first step, the combined index of financial and economic stability was calculated with the help of the cumulative distribution function method, and then to investigate the effects of the combined indicators of financial and economic stability on the road transport sector, the Autoregressive Distributed Lag model was used to achieve the research findings. The results show that both in the short term and in the long term, the combined index of financial and economic stability has a positive effect on the added value of the road transport sector. The short-term and long-term elasticity of added value of the road transport sector is 0.074 and 0.153 respectively, which shows that its long-term elasticity is more than the short-term elasticity. Also, the results of the stability and diagnosis tests show that the coefficients of the variables are stable in the long term..

In this study, the bond strength between rebar and high-performance fiber-reinforced cementitious composites (HPFRCC) containing the combination of three types of steel fibers (1% and 2%), polypropylene and polyvinyl alcohol (0.1, 0.2, 0.3 and 0.4%) has been investigated at the temperature of the laboratory, 400 and 600 °C. For this purpose, at first, 19 specimens were constructed and evaluated for compressive strength testing under the mentioned temperatures, as the silica fume was considered 20% by weight of cement. Among the constructed HPFRCC, four superior mix designs were selected for investigating the bond strength between rebar and HPFRCC using pullout test. The results showed that the bond strength between rebar and HPFRCC samples containing 2% steel fibers with PP fiber in such a way that increasing the temperature up to 400 °C, decreased about 38%. while this reduction rate for the samples containing PVA fibers is about 26%, and this means that PVA fibers have a better performance than PP fibers in term of the bond between concrete and rebar when exposed to high temperatures. By increasing the temperature up to 600°c, the bond strength of rebar and HPFRCC continues to decrease until this drop is about 64% for selected samples containing fibers (2% steel and 3% PP) at the laboratory temperature (i.e., 23°c). The reduction for the HPFRCC sample containing 2% steel and 2% PVA fibers is calculated by 62%. The results of this study and the literatures indicated the effect of different parameters on the bond strength, so for further investigation, the bond strength modelled using artificial intelligence models. The results of rebar bond strength modeling in HPFRCC showed that the performance of the adaptive multivariate regression splines based on error statistical criteria was more accurate than the artificial neural network.

The high statistics of accidents compared to the population and vehicle ownership index in Iran has put reducing the number of accidents more than ever before on the agenda of road engineers. Speed is one of the most effective factors in causing accidents. One of the physical tools for controlling the speed of vehicles is the use of speed bumps and humps in the streets. This study examines the effect of proper implementation of speed humps on reducing the speed of vehicles, as well as reducing the number of accidents. To this end, the speed of vehicles before and after installing 64 speed humps in areas 2 and 10 of Mashhad was recorded through field research. In addition, the physical specifications of speed bumps, such as width, height, distance from intersections, number of lanes on the streets, and distance from warning signs to speed bumps, were measured. Then, using statistical analyses, the effectiveness of each of these parameters in reducing vehicle speed was evaluated. Furthermore, based on the accident statistics of the targeted streets, data before and after installing speed bumps were analyzed using SPSS software and regression analysis. After conducting the initial analysis, it was found that none of the linear regression models were suitable for predicting the accidents. Therefore, the data were analyzed using a nonlinear multiple regression model (R^2=0.87). The results of the analysis showed that the use of speed bumps can have a significant impact on reducing accidents in streets and intersections, provided that proper safety measures are taken into account in their design and installation. In fact, speed bumps can lead to a reduction of approximately 17% in accidents.

This study aimed to investigate the relationships between driver locus of control and risky behaviors, as well as traffic violations and accidents. Participants in this study were 289 male and 116 female drivers who completed a form including the newly developed Iranian Driver Traffic locus of Control Questionnaire (TLOC-IR), Driver Behaviour Questionnaire (DBQ), and items related to drivers’ driving records and demographics. The results of structural equation modeling (SEM) showed that most components of the locus of control, except for the sub-section of religious factors and other drivers, have a significant relationship with driving behavior. According to the results of this study, the internal locus of control has a negative relationship with various types of violations and driving errors, and on the other hand, the components of the external locus of control, including luck and destiny, have a positive relationship with more risky driving behavior and accidents. These findings indicate that locus of control is an effective variable in predicting the behavior of Iranian drivers and can be used to determine effective strategies to reduce high-risk driving. According to the results of this study, drivers with internal locus of control show safer behaviors than drivers with external locus of control; Therefore, strengthening the internal locus of control in drivers can lead to safer driving behaviors.

Landslides are a common natural hazard around the world, but the accuracy of the maps produced can be impacted by various adverse effects and uncertainties. Researchers have continuously sought to improve the accuracy of landslide susceptibility maps. This study aims to create a landslide susceptibility map for Austria using t-test and random forest models. Nine criteria for landslide occurrence, including elevation, slope, aspect, distance to drainages, distance to faults, distance to roads, land cover, lithology, and precipitation, were used. In the t-test model, the weight of each criterion was calculated using the t-statistical test and then combined with each other using the Simple Additive Weighting technique to draw the final landslide susceptibility map. The random forest model was trained using multiple decision trees and based on the landslide occurrence points and criterion layers, the relative weight of each layer was calculated, resulting in the final landslide susceptibility map. The receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) were used to compare the two models, with the results showing that the random forest model performed better with an AUC of 0.893, compared to the t-test model with an AUC of 0.852. The importance of different criteria was assessed, and it was found that slope and precipitation were the most important factors in the occurrence of landslides in both models. The results showed that both models have unique advantages in landslide susceptibility mapping. Accordingly, the higher accuracy of the random forest model, and the possibility of weighting the criteria and sub-criteria in the t-test model, make both models practical in this field.

The Ghotor doublet earthquake happened on 23 Feb 2020 near Khoy and Salmas cities in west Azerbaijan province of Iran near Iran-Turkey border .The first large event with a magnitude of 5.8 Mww (USGS) happened at 5:52 UTC (9:23 AM local time) and followed by a second large event of magnitude 6.0 Mw (USGS) at 16:00 UTC. The second event inflicted most of the building damages. No surface rupture has been reported for the events. We estimated the areal extent of the surface displacement related to the 2020 Ghotor doublet earthquakes using three sets of C-band imagery from the European Space Agency Sentinel 1A and 1B satellites. Due to small ground displacement, we could not model the fault geometry of the first mainshock. The ascending and descending displacement maps of the second main shock are used to jointly invert the causative fault plane parameters. To obtain the source parameters, we first down-sampled the unwrapped LOS surface displacements by a quadtree algorithm and then inverted the unwrapped interferograms to infer the geometry of a single rectangular plane with uniform slip in a uniform elastic half-space. The fault geometry parameters are location (X, Y, and Depth), size (length and width), orientation (strike, dip, and rake), and uniform slip of the rupture plane. We assume the X, Y, and depth to correspond to the center of the top edge of the rupture plane. We used a nonlinear inversion method as implemented in the open-source software called Geodetic Bayesian Inversion Software (GBIS) released by Centre for Observation and Modeling of Earthquakes, Volcanoes, and Tectonics (COMET). We used Okada‘s (1985) displacement green functions to model the displacement field. The calculated optimal model illustrates a northeast-striking (N24°) left-lateral rupture plane dipping ~86° towards the west. Once the geometry of the fault plane with uniform slip was estimated, we expanded the rupture plane 20 km along-strike and 12 km along down-dip directions and divided it into 1291 individual patches to obtain the distributed slip on the rupture plane. Each patch has a fixed geometry according to optimal source parameters obtained from the nonlinear modeling, and the slip was allowed to vary freely on the fault plane. We used a modified version of the open-source software called FaultResampler 1.4 to apply the linear inversion for calculating slip distribution on the rupture plane. The coseismic rupture concentrates around a center depth of 3 km with a maximum slip of 97±8  cm. Assuming a rigidity modulus of 30 GPa, the geodetic moment is estimated to be 1.517E+18 Nm, equivalent to a moment magnitude of 6.05 Mw.

Considering its key effect on the welfare and health of society, water plays a crucial role in the growth of communities and is one of the most important natural resources. In recent years, the problem of scarcity of water resources has been exacerbated by the growing population worldwide and increased competition for access to water resources, which leads to increased costs of water use. Therefore, the use of this vital resource requires proper management. The present study was entitled Predicting and Modeling the Urban Water Consumption Pattern in Tabriz to Investigate and Analyze the Urban Water Consumption Pattern Using Geographic Information System (GIS).

 One of the main public needs of people in all societies is public health. Identifying pathogenic agents and how they are transmitted and distributed in the environment is one of the management methods in providing the health needs of communities [1]. Studying the distribution of diseases is important for two reasons. First, these studies can be a way to find the causes of diseases, and second, the geographical distribution of diseases can be an indicator of how people and human groups interact with the environment [6]. Therefore, it is necessary to design a system for data management in order to control and care for infectious diseases. The spatial information system with the possibility of using satellite information is a new and cost-effective method in line with this need, which in the long run will compensate the initial investment by reducing the costs of data collection and disease control, and in addition, the way to use these facilities in information management systems. and provides care for other diseases. Because health and illness always have a spatial dimension [8]. Identifying and displaying spatial patterns plays an important role in establishing health policies. For many, spatial data analysis is the same as map production. The use of disease distribution maps for epidemiological purposes has a long history. The first step in the design of spatial information systems in Hamadan city is to examine the human location and the potential and actual information sources of the infectious disease care system. The main purpose of using the spatial information system is to strengthen and support the care and management system of infectious diseases and create the ability to analyze the spatial information and then make timely decisions [9].

 The studied area:

This research was implemented in Hamadan city. Demographic information was prepared from the demographic information related to the census of 2015 in Hamedan city, and to obtain information on infectious diseases, it was extracted from the classified information set of patients in Bo Ali Sina University of Medical Sciences, Hamedan city. Specific results of this research are presented in several sections.

 The information needed in this research is collected by using library studies, checking similar domestic and foreign research records, collecting descriptive information by questioning and studying the documents available in libraries, as well as field research. In this research, in order to develop the methodology and processes for investigating the distribution of diseases, as well as the effect of interactive GIS systems on the control and management of diseases, two series of analysis and evaluation are carried out. descriptive test and inferential test; Therefore, in order to implement the stage of identifying the distribution of diseases during a 5-year period in Hamedan city, first all the necessary data of the health centers and Boali University of Medical Sciences of Hamedan are prepared and collected, after verifying the information based on statistical methods and performing the Smirnov test. Kolmogorov, data distribution is examined. After that, the distribution of the obtained data is checked with the T-statistics test. Finally, after performing the descriptive test, this information is categorized and then analyzed based on the characteristics of the diseases and their time period, the results of these analyzes are shown in the form of tables and evaluation charts. In the spatial statistics test, in order to evaluate spatial systems on the control and management of diseases in a 5-year period, first, spatial information based on the location of the residence of each case, longitude and latitude related to the residence of each patient for the spatial analysis of the disease was obtained and in a database stored and then classified based on the main diseases. In this regard, after checking the accuracy of the entered data, secondary analysis is defined based on the main charts and tables. By examining the location of sick people in the geographic information system (GIS) and entering the information and characteristics of patients in this system, important information such as the distribution of the disease, examination of the produced clusters, geographical effects on the disease, the speed of spread and transmission of the disease can be obtained. For spatial analysis, Moran's spatial autocorrelation method and Pearson's statistical test are used to estimate the correlation of diseases with spatial characteristics in the GIS environment. It is also possible to implement a suitable system process framework in order to model the distribution of different diseases outside of the current research based on the mechanism of the spatial information system and satellite images in the control and management of diseases in any region. This framework includes types of diseases and time-spatial distribution patterns that cause and effect relationships between entities will be presented in the form of a block diagram.

Implementation:

 The purpose of this study is to prepare a map of the spatial and temporal clusters of infectious diseases, to investigate the factors affecting the disease and their impact, and finally to find a method to model the prevalence of the disease, this model can help disease management and control programs. All information and documents related to the causes of the disease were extracted by study and evaluation. In this regard, it is necessary to perform processing related to the model on descriptive items with the same spatial unit; Therefore, the required spatial unit was considered for all factors. In order to model the diseases using the moving average model, first the zoning map of Hamedan city was prepared using the number of infected patients in each region. Then, using the moving average model and using the Raster Calculator computing space in ArcGIS software, the final disease distribution model was produced.

Today, ground transportation systems are facing a major challenge which has come to be known as traffic congestion. Since traffic and congestion are complex and dynamic phenomena, it is difficult and sometimes impossible to apply conventional mathematical models on them. Thus agent-based technologies with high compatibility with the afore-mentioned characteristics can be used to model the phenomenon of congestion and detect effective congestion mitigation/aggravation parameters. Considering the role of bus rapid transit in the transportation of passengers, mitigation of congestion and reduction of passenger waiting time and travel time are among the objectives of the present study. Therefore, agent-based simulation of the movement of bus rapid transit (BRT) fleets is used to achieve the afore-mentioned goal. In the present study, NetLogo is used to code the model and run the simulation. Three different scenarios were taken into account in this study. Change of effective factors in each of the three scenarios led to significant improvements in the BRT performance analysis results. Finally, after general analysis and comparison of different scenarios, results and suggestions were presented to improve the performance of BRT fleets. In the attempt to achieve the goals (i.e. reduction of passenger waiting time at stations and reduction of travel time), the bridge scenario was found to be more suitable and effective than the smart light and status quo scenarios.

In this research, a truss model is introduced to simulate the in-plane behavior of masonry walls in different failure modes. In the proposed model, the structural members are divided into smaller two-dimensional panels and then a truss system is used to model each panel. How to determine the geometry, dimensions and behavioral model of these truss elements are introduced according to the behavioral mechanism and failure modes of the masonry wall. The dimensions of the truss members are determined in such a way that the stiffness of the truss model is the same as the stiffness of the initial panel, under different loads. In this regard, the computational method introduced by Aghababaei is used. The elasto-plastic-fracture model developed at the University of Tokyo is used for compressive behavior of elements. Barimani et al. evaluated and verified the accuracy of this model. Also for tensile and post cracking behavior of masonry, the tension softening model of Maekawa et al. is used. In order to apply the effects of cracking on the compressive behavior of the diagonal elements, a softening model dependent on the crack width is introduced. The idea used is generally based on the smeared crack approach. In this model, after identifying the pair of each diagonal element and as soon as a crack occurs in one diagonal element, the behavior of the other diagonal element is modified by multiplying the force values ​​in a proposed function. Then, the results of the analysis are evaluated based on ASCE41 code in different failure modes. Also, for verification, two I-shaped masonry walls, three masonry walls with rectangular cross-section and an arched walls are numerically analyzed using the proposed model and the results of numerical and experimental tests are compared. The results show that the proposed model, while simple, has a good ability to estimate the nonlinear behavior of masonry wall.

Currently tons of dye produced per year, about the one sixth tons are converted into wastewater in various industries such as textiles and dyeing, which are among the toxic, carcinogenic and mutagenic wastes due to the presence of aromatic rings in their structure. This issue has attracted a lot of attention to the purification of such compounds. Ozone is one of the strong oxidizers which produces non-toxic compounds due to its decomposition. Ozone can convert many organic materials into simpler compounds through both direct and indirect oxidation mechanisms, including degradation of wastewater that contains double bonds components such as aromatic compounds and dyes. The purpose of this study was to investigate modeling, optimization and the interactions between parameters affecting the ozonation process in removal of Acid Orange 7 in order to achieve the highest removal efficiency for the highest possible initial dye concentration under the lowest ozone injection rate, no change in initial wastewater pH and the shortest reaction time by the use of response surface method. The RSM was performed using 4 parameters pH, initial dye concentration, ozone injection rate and time with 5 levels which ends up in 30 experimental tests. The results showed that correlation coefficients and adjusted correlation coefficients were 96.85 and 94.92, respectively, and p-value for model (less than 0.0001) and lack of fit (0.0507) were obtained as significant and non-significant, respectively. These results indicate the consistency and high reliability of the modeling results. Normal error, error independence and variance stability control were also checked which showed that the closeness between the actual and predicted values and the uniform distribution of the results obtained on the normal line indicates the uniform distribution of the error. The results and predictions of the software, the random distribution and distribution of the results indicate the suitability of the assumption considered by the software regarding the stability of the variance. Based on variance stability control, the effect of the experiments on the responses provided by the software. If one of the experiments is outside the range, this experiment will have a negative impact on the overall results of the software. In the case of experiments performed, this control was also well performed. Based on model equation the most important parameters are the injection rate of ozone (Q(O3)), pH, reaction time (T) and initial dye concentration [Dye], respectively, in which all parameters except the initial dye concentration have a positive effect on dye removal efficiency. After the related tests the optimum condition were the initial dye concentration of 480 mg/L, pH of 7.7, ozonation rate of 0.6 L/min and ozonation duration of 60 min which resulted in 90% dye removal efficiency. It was also found that the most effective factors were injectable ozone rate, time, pH, and dye concentration, respectively. The results showed that determining the appropriate domains can be of great importance in achieving the desired results from the response surface method. Also, the ozonation process is able to purify the dye from high initial concentrations to high removal efficiency, indicating the high strength of this applied process in the decomposition of complex organic compounds. Ozonation kinetic rate is based on pseudo first order which was increased from 0.3 to 0.6 by enhancing injected ozone rate from 0.2 to 0.6 L/min respectively and further increase of ozone injection rate didn’t had any effect on its kinetic rate.

The Management and Planning Organization is responsible for classifying of contractors and uses criteria to assess the ability and competence of contractors. One of the factors evaluating the productivity of a project is time and the impact of the contractor's performance on this index is undeniable. In this study, a model for ranking contractors with the approach of reduction in delays in construction projects is presented. In this model, in addition to the criteria of the Regulations for Competence of Contractors of the Plan and Budget Organization, according to extensive research in previous studies and the opinion of relevant experts, using the FMEA method, four other criteria are identified as effective criteria for delay and severity to select a contractor. Eight criteria were modeled through genetic algorithm method so that the existing documents of contracting companies in the Isfahan Municipality Deputy for Urban Development were collected and considered as model input data. After analyzing them with the model and comparing the qualification score with the existing score The Company, the final model was extracted.Finally, by calculating the qualification score and ranking in the proposed model, the relocation of a number of companies and the decline from the previous position was seen due to unauthorized delays, so that sometimes it even led to a change in the company's rating. Comparing the qualification score of the two models, a change in slope from 1.3% to 8.9% was also seen, which indicated the effect of the proposed criteria on the qualification score.

One of the most significant concerns of recent years among scientists has been related to waste management actions and policies. Unfortunately, landfills are filled with various debris and demolition from old building including waste concrete, glass, brick, ceramic, and plastic. Waste concrete seems to occupy a large volume of these landfills; thus, they are potentially among the most appropriate choices for recycling process. However, different papers have focused on the impact of recycled concrete aggregates in concrete and in recent years, no specific model has been recommended to predict the behavior of parent concrete in recycled concrete. In this study, a central composite design along with response surface methodology was employed to prepare experimental designs and model the properties of concrete made of recycled aggregates. Effective factors included compressive strength of parent concrete, substitution rate of parent concrete, and value of cement, while the compressive strength, tensile strength, and water absorption of recycled concrete were introduced as goal responses. Based on the statistical analysis, all recommended models were adequate with acceptable coefficient of determination ( ). Response surface and perturbation plots revealed that compressive strength, tensile strength, and water absorption of recycled concretes depended heavily on the compressive strength of parent concrete. Moreover, in order to generate concretes with higher compressive strength than the compressive strength of parent concrete, the value of compressive strength for parent concrete should be above MPa. However, for low-strength parent concretes, substitution rate should be limited in order to reduce undesirable performance. As the compressive strength of recycled concrete aggregates increased from to MPa, the compressive strength of recycled concrete was enhanced by over percent. In this substitution, water absorption reduced over percent. Additionally, when the compressive strength of recycled aggregates was fixed at MPa, by changing substitution rate from % to %, the compressive strength of recycled concrete increased from to MPa. The tensile strength of recycled concrete also was enhanced from to MPa.

Diagnosing type and amount of deficits in beams and structure is highly important in terms of performance and impact. Despite of paramount studies on CFRP application, its usage as Strips can be mentioned as one of the most important ways. Using Half Scale in building structure and lab beams would provide more adducible results. Considering type of breakdown and its progress, the growth cracks on the surface of beams is different. In all constructions, the manner of implementation and the quality of materials are two important principles in terms of performance and efficiency of the structure. In present study, type breakdown in the beam of reinforce concrete is addressed in a nondestructive manner. In this technique, by using finite element method in identifying beam breakdown without creating an unstable condition, one can achieve a nondestructive situation in experiments which is significantly cost – effective. Hence, 16 250mm × 250mm × 2100mm concrete beams were built and divided into two groups with and without FRP composite. Each group has a control beam and remained samples have breakdown in concrete and rebar. Prepared beams were put in a 4 – point experiment and, upon gathering and analyzing relevant data, beams prototyping was begun. By using finite element method, all beams were prototyped in lab. The findings from prototyping and lab analyses are compared in the format of load – location change graph. One can consider the results of prototyping as a proper approximation of lab samples.

International Roughness Index is one of the most important indices to assess the pavement quality, and it is generally employed in pavement maintenance planning. In this study, by virtue of differential evolutionary programming and Long Term Pavement Performance data, two prediction models are introduced to predict pavement deterioration function and treatments’ improvement. For pavement deterioration modeling, climate condition, traffic, and pavement structural features are taken into account. Besides, the most-applicable pavement treatments utilized in Iran are considered in this investigation. 520 and 336 data are applied to model pavement deterioration and treatments’ improvement. The predicted models have a very high accuracy and can be used in various fields. The pavement deterioration model and treatments’ improvement model reach the coefficient determination of 99% and 97% for both training and testing data, which indicates the high-level accuracy of the introduced models. The treatments’ improvement model provides the mean squared error of 0.2 approximately.

The reason for drilling optimization is high drilling costs and low drilling speed of wells. The ultimate goal of the optimization process is to reduce the disturbing parameters in the drilling operation to the minimum possible and also to change the hydraulic and mechanical parameters to achieve the optimalrate of penetration. In practice, drilling processes are often performed experimentally, which is not immune to error and has led to unwanted losses. In the first part of this study, the improved Bourgoyne Young model is implemented on data related to 10 wells from Ramin oil field using genetic algorithm method. The reason for choosing this model is that it has more influential factors than other models. The required data can also be found in the daily reports. After implementing the information of the studied wells on the model, we saw a high agreement between the actual and predicted data. This means that this model is a good option for modeling drilling operations in Ramin field. In the second part, using the constructed model, genetic algorithm and hydraulic optimization equations, we present a drilling optimization model and optimize the data of a sample well. The results of this optimization and its comparison with the actual well data show that the rate of penetration has improved by an average of 100%  and also the hole cleaning is in good condition. This significantly reduces drilling time and the high cost of renting onshore and offshore rigs.

Scour in vicinity of hydraulic structures is considered as one of the most important parameters to design the structures. In this study, scour pattern at downstream of submerged weirs was predicted using the novel method “Extreme Learning Machine”. In current study, in order to survey the accuracy of the numerical model, the Monte Carlo Simulations(MCs) was employed. In addition, the k-fold cross validation was utilized so as to validate the results of numerical models. Then, regarding with input parameters, five ELM models were developed. Firstly, the number of optimized hidden neurons for soft computing model was calculated. Next, the best activation function for numerical model was chosen. Analysis of activation function showed that the sigmoid activation function predicted the scour around submerged weirs with more accuracy. Additionally, results of sensitivity analysis proved that the superior model estimated the scour in terms of U0/Uc, z/ht,d50/ht. This model simulated the scour around submerged weirs with reasonable accuracy, for instance, determination coefficient and scatter index were computed 0.880 and 0.127, respectively. Moreover, the velocity parameter U0/Uc was identified as the most effective input variable. Finally, a matrix was provided to estimate the scour depth for engineers without previous knowledge of Extreme Learning Machine.