This work presents an innovative approach to enhancing the performance of concrete with reclaimed asphalt pavement (RAP) aggregates using titanium dioxide (TiO2) nanoparticles. Traditional limestone coarse aggregates were partially replaced with 30% and 50% RAP aggregates; a subset of mixtures containing RAP aggregates was treated with TiO2 nanoparticles. The rheological, mechanical, and long-term properties of concrete, along with changes in its chemical composition following the addition of RAP and TiO2, were evaluated. Results revealed that using 30% and 50% RAP in concrete mixtures reduced their compressive strength by 18% and 27%, respectively. However, using TiO2 in those mixtures enhanced their compressive strength by 8.7% an

Perceived Trust of Stakeholders: Predicting the Use of COBIT 2019 to Reduce Information Asymmetry

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

Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

Carbon Fiber-Reinforced Polymer (CFRP) bars have several advantages over traditional steel reinforcement, including low density, erosion resistance, and higher tensile strength. The ACI 440.11-22 code permits CFRP as reinforcement; however, there are limited experimental studies on its application in Reinforced Concrete (RC) columns under combined loads. This study utilized theoretical analysis and Finite Element Analysis (FEA) to investigate 25 square slender concrete columns (kL/r = 17) affected by concentric and eccentric loads, examining variables, like CFRP bar contribution, eccentricity-to-depth ratio, and reinforcement arrangement. The results demonstrated CFRP's effectiveness in these columns, with failure modes varying from

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

In the present work, the focusing was on the study of the x-ray diffraction, dielectric constant, loses dielectric coefficient, tangent angle, alter- natively conductivity and morphology of PET/BaTio3. The PET/BaTio3 composite was prepared for polyethylene terephthalate PET polymer composite containing 0, 10, 20, 30, 40, 50, and 60 wt. % from Barium titanate BaTi03 powder. The composite of two materials leads to form mixing solution and hot-pressing method. The effect of BaTio3 on the structure and dielectric properties with morphology was studied on PET matrix polymer using XRD, LCR meter and SEM.