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The purpose of this study is to perform a numerical analysis of fiber-reinforced polymer (FRP) retrofitting in reinforced concrete (RC) joints at high temperatures and predict models using artificial neural networks (ANN). The aim was to gain insights into their structural behavior across a range of loading conditions from room temperature to 800°C. Additionally, the research assessed the efficiency of carbon fiber-reinforced polymer (CFRP), glass fiber reinforced polymer (GFRP) and aramid fiber reinforced polymer (AFRP) strengthening in enhancing the structural performance of the critical sections.

The linear numerical simulations were conducted to evaluate the performance of RC beam-column joints using finite element modelling (FEM) analysis. The ANN model demonstrated exceptional effectiveness in predicting the stiffness of frames with openings, establishing itself as the premier machine learning algorithm for frame stiffness estimation. In the conventional model, 300°C was proven to be an effective temperature approach. Subsequently, maintaining a constant temperature of 300°C, an in-depth analysis of nearly 30 models of three retrofitting techniques was conducted under thermomechanical loading.

The CFRP retrofits yielded 15% less deflection and 30% more stress than the remaining FRPs, and the ANN models predicted the deflection, main stresses, bending moment and shear force. The ANN model results were compared with those of other frequently used models. The R thresholds (R = 0.954, 0.981, 0.986, 0.968, 0.978 and 0.936) for training, testing and validation indicated that the ANN model achieved data variability. The findings indicate that the ANN model is more accurate because of the strong connection between the numerical model and the prediction.

To identify the pinpoint of critical segments within the rehabilitation section and determine the most effective wrapping method among the three laminates.

The purpose of this study is progressive collapse behavior in buildings. It occurs due to removal/damage of a column by fire, blast or vehicle impact.

The present study investigates the comparative behavior of 3D four-storey moment resisting steel frame using ABAQUS to predict the sensitivity of the structure in progressive collapse because of fire loads. Columns at different levels were given different temperature with reduced material properties and yield strength. Progressive collapse load combination was adopted as per General Service Administration guidelines. Corner, middle, intermediate, multiple corner and multiple intermediate columns were subjected to fire load separately.

The results for displacement, stress, shear force and axial force were captured and discussed.

The study covers linear analysis of steel frame because of different temperature. In linear analysis. columns were subjected to different temperature and their results were studied. Effect of temperature in the structure were captured because of different fire conditions.

The purpose of this study is to investigate the influence of progressive collapse under high temperature for a reinforced concrete (RC) frame. An analytical programme was analysed for a two-bay five-storey RC frame exposed to high temperature at different column locations.

The effects of high temperature protections and locations (i.e. corner, middle and intermediate) on collapse conditions and load distributions were studied for the steady-state linear analysis using finite element software.

The results show that the frame will not collapse suddenly at temperatures up to 400°C. This is attributed to an increase in the deflections of the column, which increases the lateral displacement of adjacent heated columns and governs their buckling. This indicates that the temperature rating in the column against collapse can occur at a range of 500°C-600°C compared to that of individual members. The collapse pattern of RC frames designed as ordinary moment resisting frames, and under ordinary load, combinations is based on GSA guidelines. The results for displacement, stress and axial force were collected and discussed.

The two-bay five-storey frame has been created in finite element software, and linear analysis is used to perform this study with a different temperature.

Progressive collapse because of high temperatures arising from an explosion, vehicle impact or fire is an important issue for structural failure in high-rise buildings.

The present study, using ABAQUS software for the analysis, investigated the progressive collapse of a two-dimensional, three-bay, four-storey steel frame structure from high-temperature stresses.

After structure reaches the temperature results like displacement, stress axial load and shear force are discussed.

Different temperatures were applied to the columns at different heights of a structure framed with various materials. Progressive collapse load combinations were also applied as per general service administration guidelines.

This study covered both steady-state and transient-state conditions of a multistorey-frame building subjected to a rise in temperature in the corner columns and intermediate columns. The columns in the framed structure were subjected to high temperatures at different heights, and the resulting displacements, stresses and axial loads were obtained, analysed and discussed.

Technological innovations in the construction field correspond to a wider revolution in metropolitan life and in structural design. With the demand for advanced concrete technology, the introduction of new reinforced materials in concrete, namely, iron, steel and other reinforcing elements. Reinforcement in concrete is developed in the centuries back and several advancements are being stirred to improvise the properties of the concrete through reinforcements. On the basis of this finding from the earlier research studies, a reinforcement methodology is practiced on the current study to investigate the deflection of the M30 mix concrete frame under thermal load conditions.

For the examination, corner and the middle frame are considered with the reinforcement provided on four zones with 16-mm diameter for compression and 8-mm diameter is used for the stirrup at 150 mm c/c spacing. The load is applied to the column with live and wall load of 3.5 kN/m and 14.7KN/m. The experimentation is carried out by the finite element analysis strategy in ABAQUS simulation software with five test conditions with the bare frame at single, two and three-bay infill. The model of the frame is developed and meshed with the meshing type of C3D8T under 8-node thermally coupled brick mesh type for the mesh size of 25 mm.

From the simulation outcome, the effect of thermal gradient on the reinforced concrete is analyzed and its structural properties are plotted as performance graphs in the result section.

Under the thermal load condition, the model is simulated for 180 min for five different cases and analyzed the deflection parameters such as deformation, stress and failure rate.

This paper aims to provide a detailed study on the influence of slip flow and thermal jump over mixed convection flow along an exponentially stretching surface. Also, impacts of suction/blowing, volumetric heat source/sink and velocity ratio parameter will be studied in this analysis.

The modeled governing equations for the assumed problem are dimensional nonlinear partial differential equations in nature. To reduce these equations, non-similar transformations are used to get the dimensionless nonlinear partial differential equations. Then, quasi-linearization technique is used to linearize these non-dimensional nonlinear partial differential equations. Finally, an implicit finite difference scheme is used to discretize the resulting equations.

The physical explanations are provided for the variations of various non-dimensional governing parameters over the velocity and temperature profiles. Also, the effects of these dimensionless parameters on skin friction coefficient and heat transfer rate are scrutinized in a manner which highlights their physical interpretation. The detailed discussion exhibits the fact that the streamwise co-ordinate velocity ratio parameter, partial slip parameter and the thermal jump parameter have significant influence over the flow and thermal fields.

This work has not been reported in the literature to the authors’ best of knowledge.

The purpose of this paper is to consider the influence of slip flow and thermal jump and to investigate its effects on unsteady mixed convection along an exponentially stretching surface. It is also intended to explore the influence of suction/injection and volumetric heat source/sink on the fluid flow.

The assumed problem is modelled into governing equations which are dimensional non-linear partial differential equations in nature. To obtain solutions, initially the governing equations were made non-dimensional by the suitable non-similar transformations. Then, the dimensionless non-linear partial differential equations are linearized with the aid of Quasilinearization technique. The so obtained equations are discretized by the implicit finite difference method.

The detailed analysis of the considered problem displays that the non-similarity variable reduces the velocity and temperature profiles. For higher values of mixed convection parameter, the magnitude of velocity profile as well as the Nusselt number increase. The unsteady variable diminishes the fluid flow. The higher values of velocity ratio parameter reduce the skin-friction coefficient. Further, the magnitude of skin-friction coefficient and heat transfer rate are to minimize for increasing values of partial slip and thermal jump parameters, respectively. Volumetric heat source and injection parameters are to rise the flow behavior within the momentum and thermal boundary layers significantly.

To the best of authors’ knowledge, no such investigation has been found in the literature.

The purpose of this study aims to obtain excellent products, consistent investigation and manufacturing process control which are the preconditions that organizations have to consider. Nowadays, manufacturing industry apprise process capability index (C_pi) to evaluate the nature of their things with an expect to enhance quality and also to improve the productivity by cutting down the operating cost. In this paper, process capability analysis was applied during wire electrical discharge machining (WEDM) of titanium grade 6, to study the process performance within specific limits.

Four machine input parameters, namely, pulse ON time, pulse OFF time, wire feed and wire tension, were chosen for process capability study. Experiments were carried out according to Taguchi’s L27 orthogonal array. The value of C_pi was evaluated for two machining attributes, namely, average surface roughness and material removal rate (MRR). For these two machining qualities, single response optimization was executed to explore the input settings, which could optimize WEDM process ability.

Optimum parameter settings for average surface roughness and MRR were found to be TON: 115 µs, TOFF: 55 µs, WF: 4 m/min and WT: 6 kg⁻F and TON: 105 µs, TOFF: 60 µs, WF: 4 m/min and WT: 5 kg⁻F.

Process capability analysis constantly checks the process quality through the capability index keep in mind the end goal to guarantee that the items made are complying with the particulars, providing data for product plan and process quality enhancement for designer and engineers, giving the support to decrease the cost of item failures.

Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

The purpose of this study is to examine the postprocessed wire tool surface using scanning electron microscopy and find out the streamlined conditions of input process variables using multi-objective optimization techniques to get minimum wire wear values.

A federated mode of response surface methodology (RSM) and artificial neural network (ANN) is used to optimize the process variables during the machining of a nickel-based superalloy.

The study explores that with the rise in spark-off time and spark gap voltage, the rate of wire tool consumption also escalates.

Most of the researchers used the RSM technique for the optimization of process variables. The RSM generates a second-order regression model during the modeling and optimization of a manufacturing process whose major limitation is to fit the collected data to a second-order polynomial. The leading edge of ANN on the RSM is that it has comprehensive approximation capability, i.e. it can approximate virtually all types of nonlinear functions, including quadratic functions also.