Experimental research was carried out on eight reinforced concrete beams to study the embedded length of the longitudinal reinforcement. Six beams were casted using self compacted concrete, and the two other beams were casted using normal concrete. The test was carried out on beams subjected to two point loads. The strain and the slip of the main reinforcement have been measured by using grooves placed during casting the beams at certain places. The measured strain used to calculate the longitudinal stresses (bond stress) surrounding the bar reinforcement, The study was investigated the using of self compacted concrete SCC on the embedded length of reinforcing bars, and comparing the results with normal concrete. The test results show th

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how

In Incremental sheet metal forming process, one important step is to produce tool path, an
accurate tool path is one of the main challenge of incremental sheet metal forming
process. Various factors should be considered prior to generation of the tool path i.e.
mechanical properties of sheet metal, the holding mechanism, tool speed, feed rate and
tool size. In this work investigation studies have been carried out to find the different tool
path strategies to control the twist effect in the final product manufactured by single point
incremental sheet metal forming (SPIF), an adaptive tool path strategy was proposed and
examined for several Aluminum conical models. The comparison of the proposed tool path with t

The aesthetic expression and its orders are important for steel structures forming. Steel structures are a compilation of structural elements, where its shapes have standard dimensions and pre-fabricated. As the steel construction systems not only aim to achieve the functional requirements for users, but must also have the symbolic aesthetics which provides visually and cognitive expression for viewers. In this sense the research interested in expressional aesthetics in these systems and highlights the importance of attention as structural items. Therefore the visual items which related with steel structures contain some of the most powerful forms of modern architecture, steel structures with a glass cladding, agility an

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp

To achieve sustainability in the field of civil engineering, there has become a great interest in developing reactive powder concrete RPC through the use of environmentally friendly materials to reduce the release of CO₂ gas produced from cement factories as well as contribute to the recycling of industrial wastes that have a great impact on environmental pollution.

In this study, reactive powder concrete was prepared using total binder content of 800 kg/m³, water to binder ratio (0.275), and micro steel fibers  1% by volume of concrete. The experimental program included replacing fly ash with (8, 12, 16) % by cement weight to find the optimal ratio, which achieved the best mechanical proper

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien