Influence of Filler on the Microstructure,Mechanical Properties and Residual Stresses in TIG Weldments of Dissimilar Titanium Alloys

The influence of titanium alloy (Ti-5Al-2.5Sn) and commercially pure titanium (cpTi) as fillers on dissimilar pulsed tungsten inert gas weldments of Ti-5Al-2.5Sn/cpTi was investigated in terms of microstructure,mechanical/nano-mechanical proper-ties,and residual stresses.A partial martensitic transformation was observed in the weldments for all the welding conditions due to high heat input.The microstructure evolved in the FZ/cpTi interfacial region was observed to be the most sensitive to the proportion of α stabilizer in the filler alloy.Furthermore,the addition of filler alloy improved the tensile properties and nano-mechanical response of the weld joint owing to the increased volume of metal in the weld joint.As compared to the Ti-5Al-2.5Sn wire,the use of cpTi filler wire proved to be better in terms of energy absorbed during tensile and impact tests,tensile strength and ductility of the dissimilar welds.An asymmetrical residual stresses profile was observed close to the weld centerline,with high compressive stresses on the Ti-5Al-2.5Sn side for both the weldments obtained with and without filler wires.This was attributed to mainly the low thermal conductivity of Ti-5Al-2.5Sn.The presence of residual stresses also influenced the nano-hardness profile across the weldments.     

An experimental study of gas void fraction in dilute alcohol solutions in annular gap bubble columns using a four-point conductivity probe

The influence of alcohol concentration on the gas void fraction in open tube and annular gap bubble columns has been investigated using a vertical column with an internal diameter of 0.102 m, containing a range of concentric inner tubes, which formed an annular gap; the inner tubes had diameter ratios from 0.25 to 0.69. Gas (air) superficial velocities in the range 0.014–0.200 m/s were investigated. Tap water and aqueous solutions of ethanol and isopropanol, with concentrations in the range 8–300 ppm by mass, were used as the working liquids. Radial profiles of the local void fraction were obtained using a four-point conductivity probe and were cross-sectionally averaged to give mean values that were within 12% of the volume-averaged gas void fractions obtained from changes in the aerated level. The presence of alcohol inhibited the coalescence between the bubbles and consequently increased the mean gas void fraction at a given gas superficial velocity in both the open tube and the annular gap bubble columns. This effect also extended the range of homogeneous bubbly flow and delayed the transition to heterogeneous flow. Moreover, isopropanol results gave slightly higher mean void fractions compared to those for ethanol at the same mass fraction, due to their increased carbon chain length. It was shown that the void fraction profiles in the annular gap bubble column were far from uniform, leading to lower mean void fractions than were obtained in an open tube for the same gas superficial velocity and liquid composition.     

Optimization and feasibility analysis of a microscale pin-fins heat sink of an ultrahigh concentrating photovoltaic system

Nowadays, the most recent optical configuration based on Cassegrain and Fresnel lens designs of concentrator photovoltaic(CPV) has shown a race to achieve the ultrahigh concentration ratio. Still, none of those has experimentally shown an optical concentration ratio (GC) beyond 2000 suns. This is because their energy concentration ratios are challenged by the excessive temperature raised throughout the optical stages, which diminishes the efficiency of the solar cell. In this context, this research work aims to numerically investigate a microscale pin-fins heat sink configuration to enhance the thermal performance and the cost-competitivity of ultrahigh CPV thermal receiver. The impacts of the solar cell area, cell efficiency, and heat sink's material have been analyzed and discussed. The results showed that a circular pin-fins heat sink could accomplish a drop of 23.28% in the maximum operating cell temperature at 10 000 suns for cell area of 1 × 1 mm² relatively compared to the conventional flat-plate heat sink. Furthermore, for a circular pin-fins heat sink with a cell area of 2 × 2 mm², the cell temperature started exceeding the safe operating range of temperature (80°C) at 8000 suns with an average temperature of 96.1°C and reaching a maximum of 113.91°C at 10 000 suns. A gradient temperature on the planar direction of the aluminum circular pin-fins heat sink was about 1.187°C at 10 000 suns whereas 0.703°C was recorded in the case of a copper circular pin-fins heat sink. The circular pin-fins heat sink showed the highest thermal performance resulting in maintaining the solar cell temperature within its safe operating range even beyond 10 000 suns. From an economic point of view, aluminum circular pin-fins heat sink has been found to be less costly than the copper one. Finally, it was found that at 8000 suns, the flat-plate heat sink cost is more expensive than the traditional pin-fins heat sink by 14.7%, where the flat-plate heat sink becomes the worst economic configuration at 10 000 suns. At that concentration ratio, the cost has increased by 43.38%, 5.75%, and 10.61% compared to the traditional pin-fins heat sink, cylindrical pin-fins heat sink, and circular pin-fins heat sink, respectively.     

A novel application of a Fresnel lens for a solar stove and solar heating

This paper presents a novel design and the prototyped solar cooking stove which uses a large Fresnel lens for the concentration of sunlight. The technology demonstrates high safety and efficiency of solar cooking and heating using Fresnel lenses which are low cost and available from off-the-shelf. The stove has a fixed heat-receiving area located at the focal point of the lens. The sunlight tracking system rotates the Fresnel lens about its focal point in both zenith and azimuth angles. The tracking is accomplished through a revolving motion of two rotation arms that hold the lens and a horizontal rotation of a platform that the lens system stands on. The rotation of the arms tracks the sunlight in zenith plane, while the rotation of the platform tracks in the azimuth plane. Since the solar tracking allows the Fresnel lens to concentrate sunlight to a fixed small heat-receiving area, relatively low heat loss and high energy efficiency is made possible. The heat is used to maintain a stovetop surface at temperatures around as high as 300 °C, which is practical for cooking applications in a very safe, user-friendly, and convenient manner. The system also demonstrates the possibility of transferring heat using a working fluid for indoor heating and cooking. Wider applications using the system for solar thermal collection and utilization are also undergoing development.     

Frequent Failures of Motor Shaft in Seawater Desalination Plant: Some Case Studies

The failure of a shaft from a motor in a pump or a compressor has been a phenomenon of common occurrence in seawater desalination plants. The origin of the problem in majority of cases is either the inability of the material to withstand the level of dynamic stresses to which shaft is subjected during operation and/or inadequacy of the design. The shortcoming in the design may be responsible for initiating localized corrosion which ultimately leads to failure of the component. The mode of failure of the shaft could be stress-related failure such as stress corrosion cracking, mechanical fatigue or corrosion fatigue, and/or localized corrosion such as crevice corrosion. This paper describes some recent case studies related to shaft failures in seawater desalination plants. The case studies include shearing of a shaft in brine recycle pump in which a combination of environment, design, and stresses played important role in failure. In another case, ingress of chloride inside the key slot was the main cause of the problem. The failure in a high pressure seawater pump in a SWRO plant occurred due to cracking in the middle of the shaft.     

A Joint Algorithm for Resource Allocation in D2D 5G Wireless Networks

With the rapid development of Internet technology, users have an increasing demand for data. The continuous popularization of traffic-intensive applications such as high-definition video, 3D visualization, and cloud computing has promoted the rapid evolution of the communications industry. In order to cope with the huge traffic demand of today’s users, 5G networks must be fast, flexible, reliable and sustainable. Based on these research backgrounds, the academic community has proposed D2D communication. The main feature of D2D communication is that it enables direct communication between devices, thereby effectively improve resource utilization and reduce the dependence on base stations, so it can effectively improve the throughput of multimedia data. One of the most considerable factor which affects the performance of D2D communication is the co-channel interference which results due to the multiplexing of multiple D2D user using the same channel resource of the cellular user. To solve this problem, this paper proposes a joint algorithm time scheduling and power control. The main idea is to effectively maximize the number of allocated resources in each scheduling period with satisfied quality of service requirements. The constraint problem is decomposed into time scheduling and power control subproblems. The power control subproblem has the characteristics of mixed-integer linear programming of NP-hard. Therefore, we proposed a gradual power control method. The time scheduling subproblem belongs to the NP-hard problem having convex-cordinality, therefore, we proposed a heuristic scheme to optimize resource allocation. Simulation results show that the proposed algorithm effectively improved the resource allocation and overcome the co-channel interference as compared with existing algorithms.     

Artificial Intelligence Based Sentiment Analysis for Health Crisis Management in Smart Cities

Smart city promotes the unification of conventional urban infrastructure and information technology (IT) to improve the quality of living and sustainable urban services in the city. To accomplish this, smart cities necessitate collaboration among the public as well as private sectors to install IT platforms to collect and examine massive quantities of data. At the same time, it is essential to design effective artificial intelligence (AI) based tools to handle healthcare crisis situations in smart cities. To offer proficient services to people during healthcare crisis time, the authorities need to look closer towards them. Sentiment analysis (SA) in social networking can provide valuable information regarding public opinion towards government actions. With this motivation, this paper presents a new AI based SA tool for healthcare crisis management (AISA-HCM) in smart cities. The AISA-HCM technique aims to determine the emotions of the people during the healthcare crisis time, such as COVID-19. The proposed AISA-HCM technique involves distinct operations such as pre-processing, feature extraction, and classification. Besides, brain storm optimization (BSO) with deep belief network (DBN), called BSO-DBN model is employed for feature extraction. Moreover, beetle antenna search with extreme learning machine (BAS-ELM) method was utilized for classifying the sentiments as to various classes. The use of BSO and BAS algorithms helps to effectively modify the parameters involved in the DBN and ELM models respectively. The performance validation of the AISA-HCM technique takes place using Twitter data and the outcomes are examined with respect to various measures. The experimental outcomes highlighted the enhanced performance of the AISA-HCM technique over the recent state of art SA approaches with the maximum precision of 0.89, recall of 0.88, F-measure of 0.89, and accuracy of 0.94.     

Metaheuristic Resource Allocation Strategy for Cluster Based 6G Industrial Applications

The emergence of Beyond 5G (B5G) and 6G networks translated personal and industrial operations highly effective, reliable, and gainful by speeding up the growth of next generation Internet of Things (IoT). Industrial equipment in 6G encompasses a huge number of wireless sensors, responsible for collecting massive quantities of data. At the same time, 6G network can take real-world intelligent decisions and implement automated equipment operations. But the inclusion of different technologies into the system increased its energy consumption for which appropriate measures need to be taken. This has become mandatory for optimal resource allocation in 6G-enabled industrial applications. In this scenario, the current research paper introduces a new metaheuristic resource allocation strategy for cluster-based 6G industrial applications, named MRAS-CBIA technique. MRAS-CBIA technique aims at accomplishing energy efficiency and optimal resource allocation in 6G-enabled industrial applications. The proposed MRAS-CBIR technique involves three major processes. Firstly, Weighted Clustering Technique (WCT) is employed to elect the optimal Cluster Heads (CHs) or coordinating agents with the help of three parameters namely, residual energy, distance, and node degree. Secondly, Decision Tree-based Location Prediction (DTLP) mechanism is applied to determine the exact location of Management Agent (MA). Finally, Fuzzy C-means with Tunicate Swarm Algorithm (FCM-TSA) is used for optimal resource allocation in 6G industrial applications. The performance of the proposed MRAS-CBIA technique was validated and the results were examined under different dimensions. The resultant experimental values highlighted the superior performance of MRAS-CBIR technique over existing state-of-the-art methods.     

Deep recurrent neural networks with word embeddings for Urdu named entity recognition

Named entity recognition (NER) continues to be an important task in natural language processing because it is featured as a subtask and/or subproblem in information extraction and machine translation. In Urdu language processing, it is a very difficult task. This paper proposes various deep recurrent neural network (DRNN) learning models with word embedding. Experimental results demonstrate that they improve upon current state‐of‐the‐art NER approaches for Urdu. The DRRN models evaluated include forward and bidirectional extensions of the long short‐term memory and back propagation through time approaches. The proposed models consider both language‐dependent features, such as part‐of‐speech tags, and language‐independent features, such as the “context windows” of words. The effectiveness of the DRNN models with word embedding for NER in Urdu is demonstrated using three datasets. The results reveal that the proposed approach significantly outperforms previous conditional random field and artificial neural network approaches. The best f‐measure values achieved on the three benchmark datasets using the proposed deep learning approaches are 81.1%, 79.94%, and 63.21%, respectively.     

Temperature and Humidity Controlled Test Bench for Temperature Sensor Characterization

A temperature and humidity-controlled test bench for a wirelessly-powered ultra-low-power temperature sensor IC is presented. It consists of a closed metallic structure of 0.02 m³, forming a faraday-cage around the design under test (DUT), thermally insulated using Polyethylene foam, to provide electromagnetic interference (EMI) clean and thermally stable test environment with an operating temperature range of -10 °C to 100 °C. The temperature control with a settling accuracy of?±?0.6 °C is achieved with air-cooled 100 W Peltier modules, having fast dynamics to reach 95% of the required temperature within 15 min. The humidity is controlled by air circulation through a desiccant pocket, managed at around 15% to avoid water droplets during defrosting. A controllable vacuum of?~?1.3 kPa is achieved through a vacuum pump when?<?15% of de-humification is needed. The system operates at a lower power consumption of 30 W during the temperature retention phase, with acoustic noise of 58 dB-SPL achieved.