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The awareness and preservation of the vernacular heritage and traditional construction techniques and materials is crucial as a key element of cultural identity. However, vernacular architecture located in earthquake prone areas can show a particularly poor seismic performance because of inadequate construction practices resulting from economic restraints and lack of resources. The horizontal diaphragms are one of the key aspects influencing the seismic behavior of buildings because of their major role transmitting the seismic actions to the vertical resisting elements of the structure. This paper presents a numerical parametric study adopted to understand the seismic behavior and resisting mechanisms of vernacular buildings according to the type of horizontal diaphragm considered. Detailed finite element modeling and nonlinear static (pushover) analyses were used to perform the thorough parametric study aimed at the evaluation and quantification of the influence of the type of diaphragm in the seismic behavior of vernacular buildings. The reference models used for this study simulate representative rammed earth and stone masonry vernacular buildings commonly found in the South of Portugal. Therefore, this paper also contributes for a better insight of the structural behavior of vernacular earthen and stone masonry typologies under seismic loading.

A brand-new structural type, termed thick wall-thick slab structure, has been developed in recent years based on the reinforced concrete wall structure in Japan. This type of structural system can not only maintain high seismic performance, but also provide large interior space and improve the flexibility of the architectural design that is more favored by architects. In the present study, an equivalent cross-sectional area concept in which a coefficient termed the equivalent cross-sectional area ratio is proposed to estimate the flexural strength of the horizontal member of the interior wall-slab joints, which are critical assemblies in the thick wall-thick slab structures. To capture the stress condition of slab flexural reinforcement for calculating the equivalent cross-sectional area ratio, the method of finite-element analysis was employed in this work. The finite-element modeling was calibrated firstly using two isolated interior wall-slab joints from literature and consequently applied to a parametric numerical study. Finally, results from these finite-element analyses are adopted to propose the equivalent cross-sectional area ratio for modifying the current code formula to predict the flexural strength of interior wall-slab joints in TWTS structures subjected to lateral force.

The aim of this work is to carry out an aerodynamic analysis to assess the power and identify the characteristics of the horizontal axis Magnus type wind turbine with spiral fins. A parametric study is achieved to analyze the effects of the different influence parameters such as the turbine tip speed ratio, the cylinder spinning ratio, the blade aspect ratio and the cylinder hub-tip ratio. The analysis approach adopted in this study is the Blade Element Momentum BEM using the experimental lift coefficient data for the configuration of spinning cylinders with spiral fins. In this analysis, losses are not taken in consideration. Both axial and angular interference coefficients are evaluated for this type of wind turbine. The former is assessed by solving a quadratic equation and the latter is calculated from a classic formulation including the term of spinning. An iterative process is followed to achieve this task. Concerning the obtained results, the aerodynamic characteristics of the Magnus wind turbine, analyzed in this study, provide some elucidation to lead a successful preliminary design of this novel type of machine.

The power conversion efficiency of lead halide perovskite solar cells has been elevated to 25.2%. However, the toxicity of lead and the complex fabrication process of those cells considerably hinder the commercial application of such solar cells. Therefore, lead-free solar cells with comparable power conversion efficiency with a much lower environmental impact have recently attracted enormous attention in both academia and industry. This paper presents a theoretical study to assess the energy conversion capacity of lead-free perovskite solar cells with MASnI3 perovskite as its absorber layer using solar cell capacitance simulator (SCAPS). In particular, the effects of materials of the perovskite solar cells’ electron transport layers (ETLs) and hole transport layers (HTLs) on their energy conversion performance are elaborated. Our results show that Cd0.5Zn0.5S and MASnBr3 are the most suitable materials for ETL and HTL, respectively. It is also found from that the solar cell performance can be further enhanced through optimizing the thickness and defect density of its absorber layer. Moreover, the effects of defect densities in interface layers are investigated. In addition, the effects of ETL and HTL doping densities as well as influences of the back-contact work function and operating temperature of the tin-based perovskite solar cells are discussed. Finally, a glass substrate/FTO/Cd0.5Zn0.5S (ETL)/MASnI3/MASnBr3 (HTL)/back-contact solar cell with a power conversion efficiency of 23.86% is recommended for further optimization.

Fused deposition modelling (FDM) is a widely used additive layer manufacturing process that deposits thermoplastic material layer-by-layer to produce complex geometries within a short time. Increasingly, fibres are being used to reinforce thermoplastic filaments to improve mechanical performance. This paper reviews the available literature on fibre reinforced FDM to investigate how the mechanical, physical, and thermal properties of 3D-printed fibre reinforced thermoplastic composite materials are affected by printing parameters (e.g., printing speed, temperature, building principle, etc.) and constitutive materials properties, i.e., polymeric matrices, reinforcements, and additional materials. In particular, the reinforcement fibres are categorized in this review considering the different available types (e.g., carbon, glass, aramid, and natural), and obtainable architectures divided accordingly to the fibre length (nano, short, and continuous). The review attempts to distil the optimum processing parameters that could be deduced from across different studies by presenting graphically the relationship between process parameters and properties. This publication benefits the material developer who is investigating the process parameters to optimize the printing parameters of novel materials or looking for a good constituent combination to produce composite FDM filaments, thus helping to reduce material wastage and experimental time.

The structural performance of parallel flange I-section steel beams is significantly influenced by localized web buckling, particularly under compressive and shear forces. Geometric imperfections, including initial out-of-plane web deformation, flange waviness, web thickness variation, residual stresses and welding distortions, can exacerbate web buckling, leading to premature failure. This study investigates the localized web buckling strength of a parallel flange I-section steel beam with widths ranging from 210 mm to 350 mm and depths ranging from 600 mm to 1750 mm by incorporating these geometric imperfections into numerical models using IDEA StatiCa and Abaqus. A nonlinear finite element analysis (FEA) approach is adopted, where IDEA StatiCa is utilized for structural stability assessment and section capacity verification, while Abaqus is employed to conduct detailed nonlinear buckling simulations. The study examines the influence of imperfection magnitudes, varying web slenderness ratios and different loading conditions. The primary objective is to establish a correlation between imperfection effects and web buckling resistance, providing insights into critical buckling loads and post-buckling behavior. The study is conducted in accordance with the provisions of the Indian Standard IS 800:2007 - General Construction in Steel. The provisions related to web slenderness, buckling coefficients and effective width calculations are incorporated into the analysis to validate the numerical results against theoretical predictions.

In this work, the performance of anion exchange membrane (AEM) electrolysis is evaluated. A parametric study is conducted, focusing on the effects of various operating parameters on the AEM efficiency. The following parameters—potassium hydroxide (KOH electrolyte concentration (0.5–2.0 M), electrolyte flow rate (1–9 mL/min), and operating temperature (30–60 °C)—were varied to understand their relationship to AEM performance. The performance of the electrolysis unit is measured by its hydrogen production and energy efficiency using the AEM electrolysis unit. Based on the findings, the operating parameters greatly influence the performance of AEM electrolysis. The highest hydrogen production was achieved with the operational parameters of 2.0 M electrolyte concentration, 60 °C operating temperature, and 9 mL/min electrolyte flow at 2.38 V applied voltage. Hydrogen production of 61.13 mL/min was achieved with an energy consumption of 48.25 kW·h/kg and an energy efficiency of 69.64%.

An investigation was conducted to determine the effects of operating parameters for various electrode types on hydrogen gas production through electrolysis, as well as to evaluate the efficiency of the polymer electrolyte membrane (PEM) electrolyzer. Deionized (DI) water was fed to a single-cell PEM electrolyzer with an active area of 36 cm2. Parameters such as power supply (50–500 mA/cm2), feed water flow rate (0.5–5 mL/min), water temperature (25−80 °C), and type of anode electrocatalyst (0.5 mg/cm2 PtC [60%], 1.5 mg/cm2 IrRuOx with 1.5 mg/cm2 PtB, 3.0 mg/cm2 IrRuOx, and 3.0 mg/cm2 PtB) were varied. The effects of these parameter changes were then analyzed in terms of the polarization curve, hydrogen flowrate, power consumption, voltaic efficiency, and energy efficiency. The best electrolysis performance was observed at a DI water feed flowrate of 2 mL/min and a cell temperature of 70 °C, using a membrane electrode assembly that has a 3.0 mg/cm2 IrRuOx catalyst at the anode side. This improved performance of the PEM electrolyzer is due to the reduction in activation as well as ohmic losses. Furthermore, the energy consumption was optimal when the current density was about 200 mA/cm2, with voltaic and energy efficiencies of 85% and 67.5%, respectively. This result indicates low electrical energy consumption, which can lower the operating cost and increase the performance of PEM electrolyzers. Therefore, the optimal operating parameters are crucial to ensure the ideal performance and durability of the PEM electrolyzer as well as lower its operating costs.

The impact of process conditions on the synthesis of NiMoO4 nanostructures using a solution combustion synthesis (SCS) method, in which agar powder and Ni(NO3)2 were utilized as fuel and as the oxidant, respectively, was thoroughly studied. The results show that the calcination temperature had a significant implication on the specific surface area, phase composition, particle size, band gap, and crystallite size. The influence of calcination time on the resulting physicochemical/structural/morphological properties of NiMoO4 nanostructures was found to be a major effect during the first 20 min, beyond which these properties varied to a lesser extent. The increase in the Ni/Mo atomic ratio in the oxide impacted the combustion dynamics of the system, which led to the formation of higher surface area materials, with the prevalence of the β-phase in Ni-rich samples. Likewise, the change in the pH of the precursor solution showed that the combustion reaction is more intense in the high-pH region, entailing major implications on the physicochemical properties and phase composition of the samples. The change in the fuel content showed that the presence of agar is important, as it endows the sample with a fluffy, porous texture and is also vital for the preponderance of the β-phase.

Water pollution is an increasing global issue that societies are facing and is threating human health, ecosystem functions and agriculture production. The distinguished features of artificial intelligence (AI) based modeling can deliver a deep insight pertaining to rising water quality concerns. The current study investigates the predictive performance of gene expression programming (GEP), artificial neural network (ANN) and linear regression model (LRM) for modeling monthly total dissolved solids (TDS) and specific conductivity (EC) in the upper Indus River at two outlet stations. In total, 30 years of historical water quality data, comprising 360 TDS and EC monthly records, were used for models training and testing. Based on a significant correlation, the TDS and EC modeling were correlated with seven input parameters. Results were evaluated using various performance measure indicators, error assessment and external criteria. The simulated outcome of the models indicated a strong association with actual data where the correlation coefficient above 0.9 was observed for both TDS and EC. Both the GEP and ANN models remained the reliable techniques in predicting TDS and EC. The formulated GEP mathematical equations depict its novelty as compared to ANN and LRM. The results of sensitivity analysis indicated the increasing trend of input variables affecting TDS as HCO3− (22.33%) > Cl− (21.66%) > Mg2+ (16.98%) > Na+ (14.55%) > Ca2+ (12.92%) > SO42− (11.55%) > pH (0%), while, in the case of EC, it followed the trend as HCO3− (42.36%) > SO42−(25.63%) > Ca2+ (13.59%) > Cl− (12.8%) > Na+ (5.01%) > pH (0.61%) > Mg2+ (0%). The parametric analysis revealed that models have incorporated the effect of all the input parameters in the modeling process. The external assessment criteria confirmed the generalized outcome and robustness of the proposed approaches. Conclusively, the outcomes of this study demonstrated that the formulation of AI based models are cost effective and helpful for river water quality assessment, management and policy making.