Glass fiber–reinforced polymer (GFRP) reinforcement provides an effective alternative to conventional steel in concrete structures due to its corrosion resistance. Nevertheless, the lower elastic modulus of GFRP necessitates careful consideration of serviceability behavior in GFRP-reinforced concrete members. This study presents a numerical sectional analysis model for predicting the flexural response and ultimate capacity of hybrid reinforced concrete beams incorporating embedded GFRP profiles in combination with either mild steel or GFRP reinforcement bars under monotonic static loading. The proposed model employs realistic nonlinear stress–strain relationships for concrete and steel, together with secant moduli of elasticity

Background: Type 2 diabetes mellitusand chronic periodontitis hold a close relationship that has been the focus of many researches. Currently there is an appreciation to the role of adipose tissue-derived substances "the adipokines" in immune-inflammatory responses; also, there is an interest in using the simple non-invasive saliva in diagnosing and linking oral and general health problems. The current study aims to determine the periodontal health status in the chronic periodontitis patients with and without poorly or well controlled type 2 diabetes mellitus, measure the salivary levels of two adipokines "leptin and resistin", pH and flow rate and then correlate between these clinical periodontal, biochemical and physical parameters in eac

Background This study establishes a mathematically consistent and computational framework for the simultaneous identification of two time-dependent coefficients in a one-dimensional second-order parabolic partial differential equation. The considered problem is governed by nonlocal initial, boundary, and integral overdetermination conditions. Methods The direct problem is solved using the Crank-Nicolson finite difference method (FDM), which ensures unconditional stability and second-order accuracy in both spatial and temporal discretizations. The corresponding inverse problem is reformulated as a nonlinear regularized least-squares optimization problem and efficiently solved used the MATLAB subroutine

The utilization of recycled brick tile powder as a replacement for conventional filler in the asphalt concrete mix has been studied in this research. This research evaluates the effectiveness of recycled brick tile powder and determines its optimum replacement level. Using recycled brick tile powder is significant from an environmental standpoint as it is a waste product from construction activities. Sixteen asphalt concrete samples were produced, and eight were soaked for a day. Samples contained 5% Bitumen, 2% to 5% brick tile powder, and conventional stone dust filler. The properties of samples were evaluated using the Marshall test. It was observed that the resistance to stiffness and deformation of asphalt concrete

In Australia, most of the existing buildings were designed before the release of the Australian standard for earthquake actions in 2007. Therefore, many existing buildings in Australia lack adequate seismic design, and their seismic performance must be assessed. The recent earthquake that struck Mansfield, Victoria near Melbourne elevated the need to produce fragility curves for existing reinforced concrete (RC) buildings in Australia. Fragility curves are frequently utilized to assess buildings’ seismic performance and it is defined as the demand probability surpassing capacity at a given intensity level. Numerous factors can influence the results of the fragility assessment of RC buildings. Among the most important factors that can affe

GFRP was employed in constructions as an alternative to steel, which has many advantages like lightweight, large tensile strength and resist corrosion. Existing researches are insufficient in studying the influence of hybrid reinforced concrete composite columns encased by GFRP I-section (RCCCEG) and I-section steel (RCCCES). In this study twenty one (RC) specimens of a cross-section of 130 mm × 160 mm, with different length (long 1600 mm and short 750 mm) were encased by using I-section (steel and GFRP) and tested under various loading (concentric, eccentric and flexural loads). The test was focused on the influence of many parameters; load-carrying capacity, mode of failure, deformation and drawing an interaction diagram (N-

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.