ABSTRACT: In this paper, artificial neural networks (ANNs) are used in attempt to obtain the strength of polymer-modified concrete (PMC). A database of 36 case records is used to develop and verify the ANN models. Four parameters are considered to have the most significant impact on the magnitude of (PMC) strength and are thus used as the model inputs. These include the Polymer/cement ratio, sand/cement ratio, gravel/cement ratio, and water/ cement ratio. The model output is the strength of (PMC). Multi-layer perceptron trained using the back-propagation algorithm is used. In this work, the feasibility of ANN technique for modeling the concrete strength is investigated. A number of issues in relation to ANN construction such as the effect of ANN geometry and internal parameters on the performance of ANN models are investigated. Design charts for prediction of polymer modified concrete strength are generated based on ANN model. It was found that ANNs have the ability to predict the strength of polymer modified concrete, with a very good degree of accuracy. The ANN models developed to study the impact of the internal network parameters on model performance indicate that ANN performance is reality insensitive to the number of hidden layer nodes, momentum terms or transfer functions. On the other hand, the impact of the learning rate on model predictions is more pronounced.keywords:; Artificial Neural networks; Strength; Polymer Modified Concrete; Modeling.
The current study includes application of QUAL2K model to predict the dissolved oxygen (DO) and Biochemical Oxygen Demand (BOD5) of lower reach of the Diyala River in a stretch of 16.90km using hydraulic and water quality data collected from Ministry of Water Resources for the period (January-April 2014). Google Earth and Arc-GIS technique were used in this study as supported tools to provide some QUAL2K input hydro-geometric data. The model parameters were calibrated for the dry flow period by trial and error until the simulated results agreed well with the observed data. The model performance was measured using different statistical criteria such as mean absolute error (MAE), root mean square error (RMSE) and relative error (RE). The results showed that the simulated values were in good agreement with the observed values. Model output for calibration showed that DO and CBOD concentration were not within the allowable limits for preserving the ecological health of the river with range values (2.51 - 4.80 mg/L) and (18.75 – 25.10 mg/L) respectively. Moreover, QUAL2K was used to simulate different scenarios (pollution loads modification, flow augmentation and local oxygenation) in order to manage the water quality during critical period (low flow), and to preserve the minimum requirement of DO concentration in the river. The scenarios results showed the pollution loads modification and local oxygenation are effective in raising DO levels. While flow augmentation does not give significant results in which the level of DO decrease even with reduction in the BOD5 for point sources. The combination of wastewater modification and local oxygenation (BOD5 of the discharged effluent from point sources should not exceed 15 mg/L and weir construction at critical positions 6.67km from the beginning of the study region with 1m height) is necessary to ensure minimum DO concentrations.
An essential part of managing construction projects is productivity estimation. The accuracy of the construction productivity estimate determines the management quality. This research established a multi-variable linear regression and another mathematical model for the same variables to assess the productivity of building projects using the logistic regression approach. Data from residential, commercial, and educational projects in various regions of Anbar was utilized in the research. Numerous dependent variables were chosen with care. These independent factors, which include age, experience, the quantity of work, level of execution, and security circumstances, may be divided into objective and subjective variables. The person-hour/unit and the cost/unit are two inputs to the system that are used to measure input/output, the parameter known as productivity. The first is used for procedures that need a large amount of labour and is focused only on labour. All impacts are combined in the second cost/unit. The researcher came up with an equation that contains the following factors (Health condition, equipment available, Security, labor, Quality work, morale, the material available, site condition, Experience, Weather, Height, and Age ).
Hydrodynamic modeling of viscous flow in porous media was investigated for fourselected filter media crushed silica, crushed anthracite coal, glass beads and crushed garnet.Typical constants that can be used to estimate head loss for some of the most common designof granular media filters were correlated. The effect of several parameters such as porosity(35%-60%) , temperature(20oC-80oC) and media grain size (0.5-2mm) was studied. Empiricalrelationships were developed using a plot of friction vs. Reynolds number similar to those thathad been successfully used for the flow of fluids in pipes. Analytical models were made todevelop an equation for viscous turbulent flow in porous media from first hydraulic principles.Empirical equation was developed to predict pressure drop in porous media as a function ofbed porosity and evaluated the friction factor as a function to flow type.
ABSTRACT This research models the relationship between traffic characteristics and lane position on a six-lane divided highway. Both macroscopic and microscopic models were developed to analyze speed-density, speed-flow, and flow-density relationships for each lane, using linear and nonlinear approaches. Additionally, microscopic models were created to investigate speed-spacing, speed-headway, and headway-spacing relationships. Data was gathered using video recordings and radar speed guns, and traditional methods were applied to calculate density and spacing distance, which are typically challenging to measure in the field. Microsoft Excel and SPSS ver.26 software were utilized for analysis. The coefficient of determination (R-square) and the chi-square test were employed to assess the goodness of fit for the models. The results indicated no significant differences between the predicted and observed data, demonstrating critical traffic characteristics and providing insights into vehicular and driver behavior. These models can be utilized to identify various parameters of traffic characteristics in future studies on the examined highway.
The frequency of accidents, as well as statistical models of accident frequency, are often used as a foundation for prioritizing improvements to roadway safety by several transportation organizations. However, the use of accident severities in safety programming has frequently been restricted to the locational assessment of accident fatalities, with little or no emphasis being placed on the full severity distribution of accidents (slight damage, serious damage) which is required in order to properly evaluate the advantages of several competing efforts aimed at improving safety. Within the scope of this research, we provide a sufficient modeling technique that may be used to get a better understanding of the accident severity level that occur on highway segments, as well as the influence of traffic characteristics such as annual daily flow, percentage of heavy vehicle and free flow speed. The modeling approach that used in this research (random parameters model) provides the possibility that the estimated values of the model parameters might differ from one road segment to another to account the heterogeneity of the independent variables. The estimated random parameters models are developed using accident severity data and traffic characteristics data that obtained from Fallujha – Al-Qaeam rural multilane road in Al-Anbar province, Iraq. The results of the estimated results suggest annual daily flow, percentage of heavy vehicle and free flow speed all have significant effect on the accident severity level. For the purpose of prioritizing highway safety improvements, a number of government transportation authority’s base their decisions on accident rates and statistical models of accident rates. The random parameters models have been shown to have significant potential for use as a sufficient method in the programming of highway safety.
In this study, eight rectangular reinforced concrete beams strengthened by bottom steel plates firmly interconnected to them by headed-stud shear connectors are manufactured using self compacting concrete and tested up to failure under two point loads to demonstrate the effect of steel-plate thicknesses, lengths, and the shear-connector distributions on the behavior, ductility and strength of this type of beams. A trial mix conforming to the EFNARC Constraints had been successfully carried out to satisfy the three fresh tests of SCC, these tests are flowability, passing ability and segregation resistance. The results show that there is a substantial improvement in the flexural resistance, increasing the flexural stiffness and decreasing the ductility ratio due to thickening steel plate, On contrary, increasing the spacing between shear connectors to 50% had slight effect on the flexural resistance, but subsequent increase of their spacing to 100% had seriously lowered that resistance, The spacing between shear connectors has a primary effect on the average flexural stiffness and ductility ratio. In regard to the steel plate length, its shortening has reduced the flexural resistance significantly, decreased the average flexural stiffness and had increased the ductility ratio. The experimentally determined ultimate flexural strength had been compared with its corresponding one computed by the "Strength Method" using ACI requirements where high agreement gained between them due to the nearly perfect interaction provided by SCC. The eight composite beams had also been analyzed by the non-linear three dimensional Finite Element Analysis employing ANSYS program (release 12.1),where high agreement is achieved compared with experimental results.
The finite element method capable of simulating the behavior of deep foundations subjected to negative skin friction in Basrah soil is investigated. Single piles under drag forces are analyzed using the PLAXIS program with an axisymmetric model. Linear elastic, Soft Soil and Mohr-Coulomb constitutive relations are adopted, where higher order triangular element is chosen for pile and soil clusters. Both pile and soil are modeled using (15)-node triangular elements. Three sites in Basrah province (Umm Qasr Port, Khor Al-Zubair, and Shatt AlArab Hotel) were selected to perform this study. The soil profile and layer characteristics are obtained from the soil investigation reports. Where the negative skin friction is evaluated due to filling loads. It is Conclusion thatSmall relative displacements are necessary to activate the negative skin friction. The elastic shorting for pile effect negative skin friction, due to increase relative displacement. The elastic shorting of the driven pile is more than that of the bored pile due to the less cross-sectional area of the driven pile. The results revealed proportional relation between the developed drag forces and pile section dimensions, interface friction factor, and fill height, with a maximum effect on the section dimension and minimum effect on the interface factor. The locations of neutral points are not sensitive to the above-mentioned factors.
This research concerns, with studying the proposed of a simulation program, which is related with the process of movement and handling of construction materials on site. to reduce the handling wastes cost. This research deals with all factors affecting construction materials movement on site. Through a proposed program, weakness points of the mentioned factors can be specified and treated either with an applied program or Administrative procedures. Detailed literature survey was performed, detailed field investigation, analysis of collected data, and interviews with selected and well qualified and experienced management personal representing a wide variety of construction firms and companies. The results obtained from the mentioned actions confirmed the research hypothesis. A computer program was prepared, to simulate all construction materials movement stages affecting the movement and handling of construction materials. The proposed program, includes and perform several functions such as , simulation of construction materials management activities, evaluation of the existing status, finding out management solutions and training aspects, that helps in training engineers, possessing little experience in managing construction materials on site. To examine the capability extent of applying the proposed program at the site, the program function applied on tow construction projects and to be examined by experts. The examination was illustrated the program efficiency to reduce movement and handling costs of construction materials. The research recommended the applications of the proposed program to get its benefits and to achieve the research objectives. Further and future researches were proposed, such as expert system to evaluate and develop the performance of construction management in the field of on site materials management.
If the employer believes that changing the shape, quality, or quantity of the work or some part of it is appropriate, he has the authority to order the contractor to do so. These instructions would extend the time it takes to accomplish the task and, as a result, the project's completion time. In the majority of situations, the employer and the contractor couldn't agree on how to compute the extra time the contractor was provided as a result of change orders. The aim of this research is to find a mechanism to determine the additional time required to carry out these works, which will vary based on the type of work, the increase in quantity for any work within the contract, etc.. Modify the nature, quality or type of any work, change the levels, lines, position and dimensions of any part of the work, and perform any additional work necessary to finish the works. A field visit and survey will be conducted on the various bridge projects as part of the research to determine the types of change orders and the additional time required for each of them, in addition to the most important reasons for not using the relative change length and how each project differs from the other. Mathematical software can be enhanced to reliably calculate the additional time for each form of change order. Most of the works expected to appear in variation order are steel and concrete works, and asphalt cladding works, with a frequency of each of them (25 percent), followed by excavation works, which have a frequency of (16.66 percent) in bridge projects.
Composite beams, made up of a concrete slab and steel in the IPE steel section, are commonly used in bridges and buildings. Their main function is to enhance structural efficiency by merging the compressive strength of concrete with the tensile resistance of steel, thereby improving overall stiffness, ductility, and load-bearing capacity. This study offers an extensive review of the flexural behavior of steel-concrete composite beams, focusing on the interplay of concrete strength, shear connector types, and interaction levels in determining structural performance. It integrates experimental and numerical research to analyze critical parameters, including load-deflection behavior, shear transfer efficiency, and crack propagation at the steel-concrete interface. The study emphasizes the effect of concrete compressive strength, particularly in ultra-high-performance concrete (UHPC) and lightweight concrete, on stiffness, ductility, and load-bearing capacity while reducing self-weight and enhancing sustainability. The study revealed that fully bonded shear connectors, using CFRP sheets and welded plates, enhance flexural capacity and stiffness. In contrast, partial bonding or pre-debonding reduces performance due to crack propagation. Indented and hot-rolled U-section connectors enhance interaction and minimize slip, while uniform distribution of shear connectors optimizes load capacity and stiffness. Lightweight concrete decreases slab weight without compromising performance, and high-performance materials such as ECC, SFRC, and UHPFRC improve strength and ductility. Numerical modeling, particularly finite element methods, and higher-order beam theories validate experimental results, providing accurate tools for predicting structural behavior under various loading and environmental conditions.
Several different deterministic and probabilistic mathematical approaches have been used to develop modal split models. The data collected by a questionnaire survey approach is frequently associated with subjectivity, imprecision, and ambiguity. additionally, several linguistic terms are used to express some of the transportation planning variables. This can be solved by modeling mode choosing behavior with artificial intelligence techniques such as fuzzy logic. In this research, Ramadi city in Iraq has been selected as a study area. For the purpose of obtaining data, the study area was divided into traffic analysis zones (TAZ). The total number of traffic zones was set as 28 traffic zones, 22 were internal traffic zones and 6 external traffic zones. Field surveys and questionnaires are used to collect data on traffic, land use, and socioeconomic characteristics factors (age, gender, vehicle ownership, family income, trip purpose, trip origin and destination, trip time, waiting duration, duration inside mode, trip origin and destination, trip cost, and type of mode used for transport). The results showed that the modal split models based on the fuzzy inference system can deal with linguistic variables as well as address uncertainty and subjectivity and they gave very good prediction accuracy for future prediction. Fuzzy inference system proved that all factors affected the mode choice with a very strong correlation coefficient (R) equal to 93.1 for general trips but when the results were compared with multiple linear regression model found that the correlation coefficient (R) equal to 28.9 for general trips and the most influential factors on the mode choice are car ownership, age and trip cost. Thus, it can be concluded that fuzzy logic models were more capable of capturing and integrating human knowledge in mode selection behavior. In addition, this study will help decision-makers to plan transportation policies for Ramadi city
Nonlinear numerical analysis of nine reinforced concrete beams with dimensions (150 x 200 x 1200) width, height and length, respectively, was carried out through the finite element theory using the ANSYS software (version 15) to know the effect of different properties of layers in the one beam on the flexural behavior of reinforced concrete beams. The beams are consisting from two layers for the one cross-section. three beams are similar properties layers and the other six are with different properties layers. The beams differ among them depending on the percentage of Polyethylene terephthalate (PET) fibers added, the location of the fibrous concrete layer as well as the thickness of the layer. PET fibers were added in proportions (0%,0.5%, and 1%) from volume of the one layer, with dimension (50 x 4 x 0.3) mm length, width, and thickness respectively. All beams are reinforced with steel reinforcement (6 mm diameter at the top, 10 mm diameter for reinforcement against shear and 12 mm diameter in the tension area). The mechanical properties of each type of mixture have been studied. It was found that the different properties of the layers significantly affected the flexural behavior of reinforced concrete beams. Also the results of the numerical modeling were very close to the laboratory results obtained from the practical study, where the largest difference between the two studies was 8% and 11% for the load and deflection respectively at the ultimate point
This paper presents the numerical study to simulate the flexural behavior of normal strength, high strength and hybrid reinforced concrete beams, under two points load with two different reinforcement ratio. The hybrid beam consists of two layers: the compressive layer is made of high strength concrete, and the tension layer is made of normal strength concrete. The simulation was done with a finite element model using the commercial finite element code, ANSYS (v.9.0). The concrete component material is modeled, the internal steel reinforcement modeled using ''LINK'' elements. The modeled behavior shown a good agreement with the experimental data. The maximum percentage difference in ultimate load-carrying capacity is 8% at the ultimate load level.Analytical study also included the effect of increasing the depth of the normal strength concrete for the hybrid reinforced concrete beam and the effect of increasing the compressive strength for high strength concrete and normal strength concrete respectively on the behavior and the load carrying capacity of the hybrid reinforced concrete beams.
In recent years, a number of researchers have adopted the wet packing (WP) approach to design different types of concrete mixes. Particle grading is a key to the optimization of the wet compactness density; for that reason, all empty spaces that exist in between large-size particles need to be completely filled with particles of smaller size. Previously-conducted studies in this field have been focused on measuring the particle size distribution’s packing density (PD) of the of granular matrices is the purpose of investigating how to increase the PD of cementitious materials. Thus, literature lacks models capable of predicting the optimal PD value. The current study collected and analyzed 216 datasets in order to construct a model for accurate prediction of PD. The main datasets were organized into two categories: modeling datasets and validation datasets. To configure the model in the best way, a hybrid gravitational search algorithm-artificial neural network (GSA-ANN) was also developed in this study. The findings confirmed ANN as an effective alternative for measuring the ultimate PD of cementitious pastes. ANN provided high levels of accuracy, practicality, and effectiveness in the process of predicting the PD value. Based on the final results, the implementation of the hybrid GSA-ANN technique causes a significant decrease in the number of tests conducted on experimental samples, which results in not only saving time and money, but also reducing the CO2 emission volume.