Composite materials fail under extreme working conditions, particularly at high temperature, due to delamination (separation of fibers from matrix). And therefore it is needed to switch over functionally graded materials (FGMs) which can sustain at high temperature conditions (250–2000°C). There is a need to analyze the fracture and fatigue characteristics of FGM structures and so through this review the emphasis is given on fracture analysis of FGM materials. It has been reported that a combination of extended finite element method and isogeometric analysis methodologies has been used for general mixed-mode crack propagation problems after the introduction of extended isogeometric analysis. Furthermore, recent computational advances have been in the form of multiscale simulations where the part of model is simulated by a finer modeling scale, which can represent details of the material behavior and the interacting effects of material constituents in the finest way. The review is also focused on new advances in analytical and numerical methods for the stress, vibration, and buckling analyses of FGMs. Emphasis has been primarily on to restrict 2D analysis with sorts of compromise in the accuracy of results. First shear deformation theory (FSDT) and third-order shear deformation theory have been extensively used among the various 2D plate theories. FSDT can help us in terms of getting reasonably accurate results with less computational afford. This paper also outlines review on carbon nanotubes (CNT) reinforced FGMs, functionally graded nanocomposites, functionally graded single-walled CNT, FG nanobeam as well as functionally graded piezoelectric materials. Future applications would be based on these smart materials which are supposed to serve us in adverse conditions. Of course, with rise and advent of promising nanotechnology and its potential impact on aerospace industry as well as on other areas, it becomes important to us to compile this review article.

Electrospinning has received wide attention for the preparation of uniform diameter nanofibers (ranging from 5 nm to several hundred nanometers) in films with random as well as aligned fashions of the fibers of various materials for use in biomedical applications. Electrospinning research has provided an in-depth understanding of the preparation of light weight, ultrathin, porous, biofunctional curcumin/gelatin nanofibers having applications in wound dressing, drug release, tissue engineering, etc. In the first half of this article, prior research on electrospun curcumin/gelatin nanofibers is reviewed in depth with nanofibers being desired due to their low diameters since these would have then large surface area to volume ratio and enough film porosity as well as improved mechanical (tensile) strength so that when prepared as mats these nanofibers (having high biocompatibility) could be used for sustained release of curcumin and oxygen to wounds during healing. The synthesis of ultrathin nanofibers (having minimum average diameter) is not a simple task unless numerical investigation is carefully done in the first half of this research article. The authors research described here examined the effects of critical process parameters (in the second half of the paper) such as distance between the spinneret and collector, flow rate, voltage and solution viscosity, on the preparation of uniform and ultrathin nanofibers using scanning electron microscopy (SEM) for characterization of the nanofibers. A 2 ^k factorial design of experiment was found to be a suitable and efficient technique to optimize the critical process parameters used in the preparation of the biofunctional nanofibers with the purpose of having applications in the treatment of problematic wounds such as diabetic chronic ulcers. After parametric investigation, the distance, flow rate and voltage when taken together, were found to have the most significant contributions to the preparation of minimum diameter nanofibers. The primary objective of this research was fulfilled with the development of ultrathin curcumin/gelatin nanofibers having a 181 nm (181 ± 66 nm) average diameter using the optimized setting of a solution having 1.5% gelatin, and 1% curcumin in 10 ml of 98% concentrated formic acid, with the electrospining unit having a voltage of 10 KV, distance from the spinneret to collector drum of 15 cm, flow rate of 0.1 ml h⁻¹, viscosity of 65 cP and drum collector speed of 1000 rpm. However, the lowest average diameter of nanofiber was measured around 147 nm (147 ± 34 nm) which was prepared at a higher voltage, such as 15 KV (at 10 cm distance, 0.15 ml h⁻¹ flow rate and 65 cP viscosity) using the solution. The design of this research paper is based on the view that merely optimization of biofunctional nanofibers may not fully satisfy researchers/engineers unless they are also provided with sufficient information about (a) the entire electrospinning mechanism (numerical investigations of the mechanism) to have better control over preparation of ultrathin nanofibers, and (b) applications of the resulting ultrathin biofunctional nanofibers while fabricating nanofibrous mats (as used now-a-days) for sustained release of curcumin during the critical hours of wound healing and other biomedical applications.

4D printed objects are indexed under additive manufacturing (AM) objects.

Aluminum metal matrix composites are potential materials for aerospace and automobile industrial applications due to their enhanced mechanical and tribological properties. Aluminum reinforced with silicon carbide particles has been developed with enhanced mechanical and tribological behavior, but it lacks wettability between matrix and reinforcement causing weak bonding, which reduces the degree of enhancement. The objectives of this study were to fabricate aluminum-based metal matrix composites with enhanced wettability at varying stirring speeds (350, 450, 550 rpm), stirring time (5, 10, 15 min), weight percentage of SiC (0, 5, 10 wt.%), and weight percentage of MoS₂ (0, 2, 4 wt.%). Nine samples were fabricated using stir casting based on Taguchi L9 orthogonal array. Hardness, tensile strength, and wear rate of the developed composite were investigated and analyzed as a single response characteristic using Taguchi’s signal-to-noise ratio and as a multi-response characteristic using hybrid Taguchi–grey relational analysis (HTGRA). The results revealed that the addition of SiC in the composite produced better hardness, tensile strength, and wear rate. The addition of MoS₂ in the composite showed better hardness and tensile strength only up to 2 wt.% of MoS₂, and in the case of wear rate, the addition of MoS₂ in the composite up to 4% showed better wear resistance. Al–SiC–MoS₂ hybrid composite shows better enhancement in hardness, tensile strength, and wear resistance than the Al–SiC composite.

This paper shows the health monitoring and assessment of a three‐phase induction motor in abnormal conditions using a machine learning algorithm. The convolutional neural network (CNN) and recurrent neural network (RNN) algorithms are the prominent methods used in machine learning algorithms, and the combined method is known as the CRNN method. The abnormal conditions of a three phase‐induction motor are represented by three‐phase faults, line‐to‐ground faults, etc. The pattern of fault current is traced, and key features are extracted by the CRNN algorithm. The performance parameters like THD (%), accuracy, and reliability of abnormal conditions are measured with the CRNN algorithm. The assessment of abnormal conditions is being realized at the terminals of a three‐phase induction motor. A fuzzy logic controller (FLC) is also used to assess such abnormalities. It is observed that performance parameters are found to be better with the CRNN method in comparison to CNN, RNN, ANN, and other methods. Such a realization makes the system more compatible with abnormality recognition.