In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

In this work, the free vibration analysis of functionally graded material (FGM) sandwich plates with porosity is conducted using the p-version of the finite element method (FEM), which is based on the first-order shear deformation theory (FSDT). The sandwich plate consists of two face-sheet layers of FGM and a homogeneous core layer. The obtained results are validated using convergence and comparison studies with previously published results. Five porosities distribution models of FGM sandwich plates are assumed and analyzed. The effect of the thickness ratio, boundary conditions, volume fraction exponents, and porosity coefficients of the top and bottom layers of FGM sandwich plates on the natural frequency are addressed.

This paper introduces a system to detect and diagnose anomalies in pumped storage hydropower plants. We collect data from various types of sensors, including those monitoring temperature, vibration, and power. The data are classified according to the operation modes (pump and turbine operation modes) and normalized to remove the influence of the external environment. To detect anomalies and diagnose their types, we adopt a multivariate normal distribution analysis by learning the distribution of the normal data. The feasibility of the proposed system is evaluated using actual monitoring data of a pumped storage hydropower plant. The proposed system can be used to implement condition monitoring systems for other plants through modifications.

Total hip replacement is a crucial intervention for patients with fractured hips who face challenges in natural recovery. The design of durable prostheses requires a comprehensive understanding of the natural processes occurring in bone. This article focuses on static loading analysis, specifically during stumbling activity, aiming to enhance the longevity of prosthetic implants. Three distinct implants, Charnley, Osteal, and Thompson, were selected for a detailed study to determine the most appropriate model. The results revealed critical insights into the distribution of Von Mises stresses on the components of femoral arthroplasty, including the cement, implant, and cortical bone. Furthermore, the examination of shear stress within the cement emerged as a pivotal aspect for all three implants, playing a crucial role in evaluating the performance and durability of hip prostheses. The conclusions drawn from this study strongly suggest that the Thompson model stands out as the most suitable choice for hip joint implants.

This article addresses the quasi-static analysis of time-dependent honeycomb sandwich plates with various geometrical properties based on the bending analysis of elastic honeycomb sandwich plates employing a time function with three unknown coefficients. The novel point of the developed method is that the responses of viscoelastic honeycomb sandwich plates under static transversal loads are clearly formulated in the space and time domains with very low computational costs. The mechanical properties of the sandwich plates are supposed to be elastic for the faces and viscoelastic honeycomb cells for the core. The Boltzmann superposition integral with the constant bulk modulus is used for modeling the viscoelastic material. The shear effect is expressed using the first-order shear deformation theory. The displacement field is predicted by the product of a determinate geometrical function and an indeterminate time function. The simple HP cloud mesh-free method is utilized for discretizing the equations in the space domain. Two coefficients of the time function are extracted by answering the equilibrium equation at two asymptotic times. And the last coefficient is easily determined by solving the first-order linear equation. Numerical results are presented to consider the effects of geometrical properties on the displacement history of viscoelastic honeycomb sandwich plates.

The present study is focused on instigation of the nonlinear mechanical behavior of reinforced concrete beams considering different types of FRP bars through nonlinear finite element simulations. To explore the impact of the FRP reinforcement type and geometry on the nonlinear mechanical behavior of reinforced beam, intensive parametric studies are carried out and discussed. Twenty models were carried out based on the finite element software (ABAQUS). The concrete damage plasticity model was considered. Four types of fiber polymer bars, CFRP, GFRP, AFRP and BFRP as longitudinal reinforcement for concrete beam were used. The validation of numerical results was confirmed by experimental as well as numerical results, then the parametric study was conducted to evaluate the effect of change in different parameters, such as bar diameter size, type of FRP bars and shear span length. All results were analyzed and discussed through, load-deflection diagram. The results showed that the use of FRP bars in rebar concrete beam improves the beam stiffness and enhance the ultimate load capacity. The load capacity enhanced in the range of (20.44-244.47%) when using different types of FRP bars. The load-carrying capacity of beams reinforced with CFRP is the highest one, beams reinforced with AFRP is higher than that reinforced with BFRP but beams reinforced with GFRP recorded the lowest load of capacity compered with other beams reinforced with FRP Bars.

The objective of this study is to investigate the distribution of von Mises stress, peeling stress, and shear stress in the adhesive layer used to bond two composite panels, considering various parameters using a three-dimensional finite element method. The stiffness of the materials and the effect of the stacking order on the amount of load transferred to the adhesive layer were examined to determine which type of laminate generates less stress at the bond line. The study analyzed six different stacking sequences, all with a common first layer in contact with the adhesive and a 0° orientation. Additionally, the impact of using hybrid composites on reducing bond line stress was investigated.