Journal of The Brazilian Society of Mechanical Sciences and Engineering最新文献

Rubber is an engineering polymer of interest in most industrial sectors. In gasketed plate heat exchangers (GPHEs), these elements comprise gaskets that are responsible for sealing the system under high levels of compression, temperature and pressure. Therefore, it is a necessity to understand how operating conditions affect GPHE structural behavior and sealing performance, regarding rubber materials and features. This work aims at determining GPHE integrity and mechanical characteristics with the aid of sealing performance experiments and strain gauge measurements at critical plate locations in a real equipment and in prototypes consisting of GPHE components. Hydrogenated nitrile butadiene rubber (HNBR) and ethylene-propylene-diene rubber (EPDM) gasket materials were evaluated. Based on compression strength experiments, the system stiffness ranged from approximately 0.3 to 7.0 kN/mm regarding the combined effects of the number of plates and the compression level. The combined effects of compressive strength, compression levels and rubber material on sealing performance were obtained with prototypes comprising at least six gaskets, whose conditions presented stable compressive strength behavior. In critical region on the real-scale heat exchanger, the measured von Mises stress level was 316 MPa and 133 MPa using EPDM and HNBR gaskets during tightening, respectively. It is conjectured that higher operation pressure loads can occur with the harder and stiffer material (EPDM), as showed by hydrostatic tests. Empirical correlations were developed in order to relate sealing capacity based on the system geometry, compression level and gasket material.

In the development of blood pumps, clinical and hydraulic performance requirements must be met. Optimization studies addressing biocompatibility and efficiency issues in the design of centrifugal blood pumps are increasing rapidly. This study aims to increase hydraulic efficiency and decrease the hemolysis index which is an indicator of the increase in the amount of free hemoglobin in blood plasma by optimizing the centrifugal blood pump. A centrifugal blood pump, whose dimensions were calculated using classical formulas, was optimized with the genetic algorithm by changing seven dimensions that were likely to have a significant impact on efficiency and hemolysis index. These dimensions are blade inlet angle, blade outlet angle, blade inlet height, blade outlet height, the gap between the blade tip and volute, the gap between disk and volute, and the gap between shroud and volute. By determining the lower and upper limits of these seven dimensions, 183 different pump geometries were generated, and computational fluid dynamics simulations were performed. Using simulation results, two adaptive neuro-fuzzy inference systems for the hemolysis index and hydraulic efficiency were generated. Using these models, optimization was made with the genetic algorithm. The optimum pump found by the genetic algorithm was simulated and compared with the base pump. The results showed that there is generally a direct relationship between hydraulic efficiency and hemolysis index. It was observed that the hemolysis index of the optimum pump decreased from 2.55E−05 of the base pump to 2.45E−05, while the hydraulic efficiency increased from 42.24 to 45.92%.

In this work, the influence of underwater wet welding process parameters on the corrosion resistance of welds produced with oxyrutile electrode was investigated. Although in the standard for underwater wet welds (AWS D3.6 M: 2017), only mechanical strength specifications are required, corrosion is a critical factor since its occurrence is a major cause of mechanical failure in offshore metallic structures. Underwater wet welding experiments were performed in a hyperbaric chamber using a gravity mechanized welding device in direct (DCEN) and reverse (DCEP) welding polarities at currents of 150 A and 180 A and depths of 0.3 and 30 m. Corrosion resistance of the welded zones was evaluated by electrochemical techniques of electrochemical impedance spectroscopy and potentiodynamic polarization in NaCl solution 3.5 wt.%, to reproduce the seawater salinity. The electrochemical results showed different behaviors among the direct and inverse polarities. In DCEN, the corrosion potential values (E_Corr) were close, and the corrosion current densities (i_Corr) varied, while in DCEP, an inverse behavior was observed. Although the lowest corrosion rates were obtained in direct polarity, in both polarities at the lowest welding current the welds showed a higher corrosion resistance.

This study presents triply coupled free vibration analysis of the axially layered Euler–Bernoulli thin-walled beams with unsymmetrical open cross sections in dimensionless and exact manner. Various parameters are normalized with respect to a reference thin-walled beam called as the baseline beam structure. Characteristic equations for determining natural frequencies of the beams are obtained using the transfer matrix method. Different boundary conditions are considered. As a case study, dimensionless solution procedure is applied to the optimization of fundamental natural frequency of cantilevered beam structures. Square of the characteristic equation of the cantilevered beam is taken as an objective function and design variables are chosen as the segment length and volume fraction of the materials. The total mass and total length of the optimized beam are kept equal to those of the reference beam. Axially, two-, three- and five-segmented beam configurations are considered. Optimization routine developed following verification of the coupled free vibration analyses reveals that the final forms of the optimized beam structures can be regarded as tapered beam-like structures and the maximum dimensionless natural frequency without constraint violations is attained for the five-segmented beam and it is 0.51, which represents 22.2142% gain. Also, some conclusions will be drawn.

Graphene-based nanomaterials have recently been used as versatile substances to enhance the overall mechanical properties of polymer composites. The loading of Graphene has significantly enhanced the mechanical strength, which in turn caused challenges with machining and adversely affected the quality and surface characteristics. It is extensively used in the production of high-performance structural components. In this investigation, reduced Graphene Oxide (rGO) have been loaded in Carbon Fiber Reinforced Plastic (CFRP) composites and compared to unreinforced CFRP composites. This reveals, rGO nanofiller positively affected tensile and impact strength. This article investigates the Abrasive water jet machining (AWJM) performances of rGO-modified CFRP composites after the development of composite samples. The influence of AWJM factors and mathematical correlation between AWJM response characteristics like Kerf Taper Angle (KT°), Volume Removal Rate (VRR), Average Roughness (Ra), and Maximum Delamination Length (Max. DLL) was explored. The process variables considered as Stand-off Distance (SOD), Traverse Rate (TR), and Jet Pressure (JP), on CFRP composite with various rGO weight fractions. The Response Surface Methodology (RSM)-based statistical technique was utilized to identify the most crucial and optimal conditions during AWJ machining. ANOVA examines the impact of various inputs on the machining performance. While experimentation, the optimal values for AWJM parameters were determined as SOD = 1.0 mm, TR = 300 mm/min, JP = High (≈ 300 MPa), and the 0.5 wt.% rGO/CFRP was found to have KT° (0.879°), VRR (1393.699 mm³/min), Ra (1.716 µm), and Max. DLL (1.146 mm), which provides an aggregate desirability score of 0.886. The findings revealed that the TR and JP were shown to have a more significant effect on the KT°, VRR, and Ra, while the rGO weight fraction was observed to have a substantial consequence on the Max. DLL. Additionally, the microstructural and topological characterizations of the machined surface revealed that defects could be controlled by incorporating rGO nanofiller into the CFRP. The proposed nanocomposite machining aspects could be endorsed for an efficient manufacturing environment.

This study presents a numerical investigation of bullet impact on sandwich panel structures. This research aims to demonstrate the ideal performance of sandwich panel structures in resisting ballistic loads based on the type of core geometry and materials used. Numerical simulations were conducted using the Johnson–Cook material model and applied in ABAQUS/Explicit software. Parameters such as shot target location and bullet angle of attack were considered in this study to review the structure’s resistance to ballistic loads. The results showed that the sandwich panel structure with decagon core geometry and Armox 500 T material was optimal in resisting the impact of blunt bullets at 500–700 m/s. The contribution of this research is to provide understanding in the field of ballistics by showing the interaction between the sandwich structure and the bullet through the velocity drop that occurs on the bullet and the energy the structure can absorb. Overall, this research provides insight into improving the design and performance of protective structures.

Based on the Abdel-Karim and Ohno model framework, a unified viscoplastic constitutive model (UVCM) is developed in order to simulate the mechanical behavior of austenitic steel under low-cycle fatigue (LCF) loading at room temperature and 600 °C and creep–fatigue (CF) loading at 600 °C, respectively. The effects of viscoplastic static recovery, mean stress evolution and strain range-dependent cyclic softening are incorporated into the UVCM. Moreover, the material parameters are categorized and each type of parameter is subjected to a sensitivity analysis in order to explore its effect on the simulation results. For LCF loading at room temperature and 600 °C, the influence of axial loading, cyclic torsional angle, and loading rate on LCF response are, respectively, studied, and different viscous behavior and cyclic softening characteristics are found. For CF loading at 600 °C, the influence of hold time on CF response is investigated, with shear stress relaxation occurring during the hold time and becoming more pronounced the longer the hold time is. The predicted results are in good agreement with the experimental results, which indicates that the model has good accuracy.

Derailment and wheel wear in railways are of major concern which involve complex operating and conflicting dynamics parameters. Metro trains undergoes through sharp turns, steep gradients, frequent high acceleration and decelerations, and overloading during peak hours which heighten the multivariate ate aspect of the problems. In this work, an attempt has been made to investigate the derailment coefficient and wheel wear of all the eight wheels of a BEML (Bharat Earth Movers Limited) metro coach under different operating scenarios. Various running conditions are generated through response surface methodology (RSM) approach by varying vehicle speed, axle load and friction at the rail-wheel contact. For this, a multibody vehicle dynamics model replicating BEML metro coach is built in commercial software Simpack. The developed multibody dynamics model is validated from the field trials conducted in Kolkata, India, by matching vehicle motion and ride comfort indices along the track. Validated multibody dynamics model is then used for simulating different running scenarios according to the central composite design (CCD) scheme. Data generated from the multibody dynamics model under different operating scenarios are taken as inputs and outputs target data for a deep neural network (DNN) model. Results of the RSM approach indicate that lower friction at the rail-wheel contact is desirable for lower wear indices and smaller derailment coefficients. Operating speed, in the speed range considered, has little influence on wear index and derailment coefficient. Results of the developed DNN model demonstrate that the mean absolute percentage error (MAPE) value is lower than 4% for all the eight wheels in both training and test.

The development of deep learning has led to great success in the bearing fault diagnosis. However, the issue of limited fault samples impedes the extensive application of most fault diagnosis approaches based on deep learning. To address this challenge, a new few-shot fault diagnosis method based on mutual centralized learning (MCL) and simple and parameter-free attention (SimAM) is put forward in this paper. First, MCL is adopted to diagnose the bearing fault with small samples, which employs a bidirectional approach rather than the traditional unidirectional method to better learn mutual affiliations between the fault features, having better few-shot classification ability. Furthermore, a new feature extractor module is constructed through the SimAM to improve the feature extraction capability of the MCL model by providing better feature maps for classification. The effectiveness of the proposed method is tested on CWRU bearing dataset and our own bearing dataset. The experimental results show that the proposed MCL-SimAM model can effectively recognize the bearing fault with few samples. Additionally, the comparison experiments demonstrate that the proposed model is superior to the comparable models [relation network (RN), prototypical network (PN), and matching network (MN), deep subspace networks (DSN), and ridge regression differentiable discriminator (R2D2)], which has a better recognition accuracy in few-shot scenarios.

The investigation of various instabilities in the fluid flow between two rotating cylinders, known as Taylor–Couette instability, has significant implications for the design of industrial equipment. One effective method of controlling flow instabilities is by introducing axial flow to Taylor–Couette flow. In this study, the impact of adding axial flow to Taylor–Couette at different radii ratios was numerically analyzed using the direct protocol approach. This involved creating Taylor vortex flow first, followed by introducing axial flow to eliminate the vortices and stabilize the flow. The research was conducted on seven radius ratios, ranging from 0.77 to 0.95. The shape of the vortices, as well as their formation and disappearance, were examined using vorticity contours and velocity levels. The axial Reynolds number of the flow stabilizer was calculated using velocity profiles and skin friction coefficient evolution on the inner cylinder for each case. The results indicate that decreasing the ratio of the inner and outer cylinder radii resulted in a significant reduction of the Axial Re-laminarization Reynolds Number (ARRN) of the flow. The skin friction coefficient value reaches its minimum value, and when the axial Reynolds number reaches ARRN, it remains constant along the length of the inner cylinder. Finally, a mathematical equation was formulated to forecast changes in the axial re-laminarized Reynolds number in relation to the radius ratio of the two cylinders.