Nano-Indentation Measurement of Fracture Toughness of Dental Enamel

Effect of orthodontic bracket bonding-debonding on fracture toughness of human dental enamel was investigated by using nano-indentation test. For this purpose, some ceramic brackets were bonded by a dental adhesive on the buccal surface of sound human teeth enamel. All clinical requirements were considered for bracket bonding and sample preparation. After debonding of the brackets, the teeth were sectioned transverse to their longitudinal axes and from the middle of the bracket region to prepare the samples required for nano-indentation tests. The nanoindentation test was performed on both the enamel under bracket and the intact enamel. The values of fracture toughness of dental enamel in both regions were calculated from the analysis of nano-scale holes observed after the nano-indentation tests. A comparison between the results obtained from the two regions indicated that bracket bonding-debonding significantly decreased the fracture toughness of human dental enamel.     

Optimization of peened-surface laser shock conditions by method of finite element and technique of design of experiments

This paper presents a numerical simulation of the laser shock peening (LSP) process using the finite element method. The majority of controlling parameters of the LSP process have been taken into account. The LSP loading has been characterized by the use of a repetitive time Gaussian increment pressure applied uniformly at a circular impacted zone. The utilized model of the treated material behaviour law is the Johnson-Cook’s visco-elastic-plastic coupled with damage. The proposed model leads to determine the LSP surface modifications: (i) the in-depth residual stresses, (ii) the induced plastic strains and (iii) the superficial damage. These modifications can be significantly induced in few cases, particularly when the operating conditions are not well optimized. An application is carried out on the laser peened titanium aero-engine super alloy Ti-6Al-4V. A satisfactory correlation between the computed and experimental results is observed. Also, it is noted that the computed superficial damage values increase with the growth of the maximal peak pressure of the laser spot, which are physically consistent. Otherwise, in order to optimize the laser peening operating conditions, a design of experiments is established. It allows having surface-response relationships between the operating parameters and the three announced induced effects.     

Novel Framework for Generating Criminals Images Based on Textual Data Using Identity GANs

Text-to-image generation is a vital task in different fields, such as combating crime and terrorism and quickly arresting lawbreakers. For several years, due to a lack of deep learning and machine learning resources, police officials required artists to draw the face of a criminal. Traditional methods of identifying criminals are inefficient and time-consuming. This paper presented a new proposed hybrid model for converting the text into the nearest images, then ranking the produced images according to the available data. The framework contains two main steps: generation of the image using an Identity Generative Adversarial Network (IGAN) and ranking of the images according to the available data using multi-criteria decision-making based on neutrosophic theory. The IGAN has the same architecture as the classical Generative Adversarial Networks (GANs), but with different modifications, such as adding a non-linear identity block, smoothing the standard GAN loss function by using a modified loss function and label smoothing, and using mini-batch training. The model achieves efficient results in Inception Distance (FID) and inception score (IS) when compared with other architectures of GANs for generating images from text. The IGAN achieves 42.16 as FID and 14.96 as IS. When it comes to ranking the generated images using Neutrosophic, the framework also performs well in the case of missing information and missing data.     

Candidate architectures for emerging IoV: a survey and comparative study

Intelligent Transportation System (ITS) is observing significant evolution in terms of technology and investment worldwide. This has given birth to the new concept of Internet of vehicles (IoV) as one of the leading applications of the Internet of Things. IoV aims to offer a better sharing of information and communication between vehicles, enabling higher cooperation for common interests. IoV is increasingly attracting the interest of a significant body of research. The e ort was mostly focused on solving various problems encountered in traditional VANETs, such as lack of coordination between vehicles, insufficient information, scalability, etc. Rapidly, IoV observed, particularly interesting advances taking advantage of exponential growth in communication and data analysis technologies. This includes cloud and/or fog computing, large data analytics, machine learning, and artificial intelligence. In this paper, we make a survey of the existing and recently proposed architecture solutions for IoV systems. Moreover, we define a list of criteria, features, and properties associated to the various architectures in order of making critical and insightful comparisons and assessments. Finally, we outline the key future research perspectives on the topic and define the key technical aspects that will help drive the future of IoV architectures.

     

Assessment of composite beam performance using GWO–ELM metaheuristic algorithm

Composite beams (CBs) include concrete slabs jointed to the steel parts by the shear connectors, which highly popular in modern structures such as high rise buildings and bridges. This study has investigated the structural behavior of simply supported CBs in which a concrete slab is jointed to a steel beam by headed stud shear connector. Determining the behavior of CB through empirical study except its costly process can also lead to inaccurate results. In this case, AI models as metaheuristic algorithms could be effectively used for solving difficult optimization problems, such as Genetic algorithm, Differential evolution, Firefly algorithm, Cuckoo search algorithm, etc. This research has used hybrid Extreme machine learning (ELM)–Grey wolf optimizer (GWO) to determine the general behavior of CB. Two models (ELM and GWO) and a hybrid algorithm (GWO–ELM) were developed and the results were compared through the regression parameters of determination coefficient (R²) and root mean square (RMSE). In testing phase, GWO with the RMSE value of 2.5057 and R² value of 1.2510, ELM with the RMSE value of 4.52 and R² value of 1.927, and GWO–ELM with the RMSE value of 0.9340 and R² value of 0.9504 have demonstrated that the hybrid of GWO–ELM could indicate better performance compared to solo ELM and GWO models. In this case, GWO–ELM could determine the general behavior of CB faster, more accurate and with the least error percentages, so the hybrid of GWO–ELM is more reliable model than ELM and GWO in this study.

     

Analysis of corrosion protection behavior of Al2O3-TiO2 oxide ceramic coating on carbon steel pipes for petroleum industry

Corrosion is the deterioration of materials by chemical interaction with their environment. In the oil and gas industry, corrosion of the pipelines and other equipment is one of the leading causes of failure and the corrosion-related costs are very high. Hence, corrosion protection is an essential requirement. In this study, the objective is to analysis of the corrosion protection behavior of spray Alumina-Titania (Al₂O₃-TiO₂) oxide ceramic coating on carbon steel pipes C45 using two different thermal spray coatings processes. These two different thermal spraying coating, High velocity oxy-fuel (HVOF) and plasma thermal spraying techniques can be used instead of extensive treatment by expensive chemical formation of coatings on pipelines and equipment to improve or restore a component's surface properties or dimensions and to protect them from corrosion. Molten or semi-molten ceramic composite powders are sprayed on the surface in order to produce a dense coating layer. FESEM of coated samples showed that a high temperature of plasma coating method end in melting the ceramic powders and creation of completely melted regions on the coated samples’ surface compared to HVOF coating techniques. Corrosion testing of coated samples in seawater (3.5% NaCl) was conducted within 30 days. Electrochemical impedance spectroscopy (EIS) as well as potentiodynamic polarization outcomes represented that the corrosion resistivity of plasma coating technique for this type of ceramic composite is better than HVOF coating technique. However, both types of coating techniques are protecting the substrate against seawater.     

Adjustment of Aging Temperature for Reaching Superelasticity in Highly Ni-Rich Ti-51.5Ni NiTi Shape Memory Alloy

In this research, the effects of aging temperature on the phase transformation, mechanical properties, and superelasticity of Ti–51.5 at.% Ni alloy were investigated. For this purpose, samples were solution annealed and then aged at different temperatures ranging from 300 to 700°C. The results showed that the change of aging temperature has a great influence on the behavior of the alloy. Aging at 300 and 400°C led to the occurrence of the austenite to R phase (A ? R) transformation. By aging at these temperatures, the ultimate tensile strength and elongation did not change significantly compared to the solution annealed sample. Aging at 500 and 600°C led to the appearance of B19′ phase during cooling cycle of differential scanning calorimetry tests. Samples aged at 500 and 600°C showed the best mechanical properties, in comparison with the other aging temperatures. Maximum tensile strength of 1250 MPa and the elongation of 25% were obtained by aging at 500 and 600°C, respectively. Solution-annealed sample showed no superelastic property. Complete superelasticity was observed by aging at 400 and 500°C. The sample aged at 700°C showed the transformation behavior and mechanical properties similar to the solution annealed sample.     

Synthesis of mesoporous ZSM-5 from rice husk ash with ultrasound assisted alkali-treatment method used in catalytic cracking of light naphtha

A series of mesoporous ZSM-5 zeolite was synthesized with ultrasonic assisted alkali-treatment technique and their catalytic activity was investigated in catalytic cracking of light naphtha. ZSM-5 zeolite was synthesized from rice husk ash without using any organic template. Effect of alkali-treatment conditions on physicochemical properties of synthesized zeolite was investigated with XRD, FESEM, TEM, N2 adsorption-desorption isotherm, NH3-TPD and TGA technique. It was found that ultrasound energy facilitates the creation of hierarchical structure of ZSM-5 during alkali-treatment. According to XRD analysis, zeolite structure was preserved after 20 min ultrasonic assisted alkaline treatment. However, prolonged dessilication time led to the destruction of MFI zeolite structure. The synthesized ZSM-5 represented highly ordered hexagonal-shape morphology. With increasing alkali-treatment time, the plough land roughness appeared on the surface of zeolite. Comparison of the textural properties samples revealed that the mesopore surface area of alkali-treated samples increased considerably with the increase of ultrasonic assisted alkali-treatment time. Results from catalytic activity tests showed that ultrasound energy has great influence on the activity of ZSM-5. The sample had the highest activity after alkali-treated for 20 min in presence of ultrasound energy which was due to their appropriate hierarchical structure.     

Investigation of the Effect of Tungsten Substitution on Microstructure and Abrasive Wear Performance of In Situ VC-Reinforced High-Manganese Austenitic Steel Matrix Composite

Particulate VC-reinforced high-manganese austenitic steel matrix composites with different vanadium and tungsten contents were synthesized by conventional alloying and casting route. Microstructural characterizations showed that the composites processed by in situ precipitation of the reinforcements were composed of V₈C₇ particulates distributed in an austenitic matrix. It was observed that addition of tungsten to austenite increases work-hardening rate of subsurface layer during pin-on disk wear test. The maximum abrasive wear resistance was achieved at tungsten content equal to 2 wt pct. However, excessive addition of tungsten promoted the formation of W₃C phase and reduced the abrasive wear resistance because of decrease in distribution homogeneity and volume fraction of the reinforcing VC particles.     

Maximum forces sustained during various methods of exiting commercial tractors, trailers and trucks

Many commercial vehicles have steps and grab-rails to assist the driver in safely entering/exiting the vehicle. However, many drivers do not use these aids. The purpose of this study was to compare impact forces experienced during various exit methods from commercial equipment. The study investigated impact forces of ten male subjects while exiting two tractors, a step-van, a box-trailer, and a cube-van. The results showed that exiting from cab-level or trailer-level resulted in impact forces as high as 12 times the subject's body weight; whereas, fully utilizing the steps and grab-rails resulted in impact forces less than two times body weight. An approach that emphasizes optimal design of entry/exit aids coupled with driver training and education is expected to minimize exit-related injuries.