Further investigations and parametric analysis of microstructural alterations under rolling contact fatigue

Bearing elements under rolling contact fatigue (RCF) exhibit microstructural features, known as white etching bands (WEBs) and dark etching regions (DERs). The formation mechanism of these microstructural features has been questionable and therefore warranted this study to gain further understanding. Current research describes mechanistic investigations of standard AISI 52100 bearing steel balls subjected to RCF testing under tempering conditions. Subsurface analyses of RCF-tested samples at tempering conditions have indicated that the microstructural alterations are progressed with subsurface yielding and primarily dominated by thermal tempering. Furthermore, bearing balls are subjected to static load tests in order to evaluate the effect of lattice deformation. It is suggested from the comparative analyses that a complete rolling sequence with non-proportional stress history is essential for the initiation and progression of WEBs, supported by the combination of carbon flux, assisted by dislocation and thermally activated carbon diffusion. These novel findings will lead to developing a contemporary and new-fangled prognostic model applied to microstructural alterations

A multiscale overview of modelling rolling cyclic fatigue in bearing elements

During service, bearing components experience rolling cyclic fatigue (RCF), resulting in subsurface plasticity and decay of the parent microstructure. The accumulation of micro strains spans billions of rolling cycles, resulting in the continuous evolution of the bearing steel microstructure. The bearing steel composition, non-metallic inclusions, continuously evolving residual stresses, and substantial work hardening, followed by subsurface softening, create further complications in modelling bearing steel at different length scales. The current study presents a multiscale overview of modelling RCF in terms of plastic deformation and the corresponding microstructural alterations. This article investigates previous models to predict microstructural alterations and material hardening approaches widely adopted to mimic the cyclic hardening response of the evolved bearing steel microstructure. This review presents state-of-the-art, relevant reviews in terms of this subject and provides a robust academic critique to enhance the understanding of the elastoplastic response of bearing steel under non-proportional loadings, damage evolution, and the formation mechanics of microstructural alterations, leading to the increased fatigue life of bearing components. It is suggested that a multidisciplinary approach at various length scales is required to fully understand the micromechanical and metallurgical response of bearing steels widely used in industry. This review will make significant contributions to novel design methodologies and improved product design specifications to deliver the durability and reliability of bearing elements

Status of the demersal fishery resources of Bangladesh

The present study makes use of the fisheries survey data collected during the period 1984 - 87 by the multi-purpose research vessel RV Anusandhani in the waters of Bangladesh, Bay of Bengal. The data consists of twelve survey cruises directed at the shrimp resources (1985 - 87) and nineteen survey cruises directed at the demersal fish resources (1984 - 86). The biomasses for shrimp and demersal fish during the survey period were estimated, along with a detailed analysis of biomass distribution by depth zone and catch rates for important species of shrimp and demersal fish species. The demersal fish and shrimp biomass during the survey period was estimated as 176 160 t and 857 t, respectively. The levels of biomass when compared with 1973 estimates indicate a tremendous decline, by about 90% for shrimps and 30% for demersal fish. Population parameters for four species of shrimps (for both males and females) as well as for eight demersal fish species were also estimated. The parameter estimates were validated using available growth and mortality parameter values from the literature, and were in turn used to estimate the mean exploitation rate (E) of demersal fish and shrimp species comprising the trawl catch. Mean E values for shrimp species is at 0.61 and 0.57 for demersal fish species, indicating over-exploitation of demersal resources in the Bay of Bengal. Exploratory analysis using surplus production modeling of catch and effort data shows that the maximum sustainable yield (MSY) level for shrimp resources is around 3 500 t, corresponding to a maximum effort level of approximately 6 480 fishing days. Similar analysis for demersal fish catches gave poor correlations between catch rates and fishing effort.Fishery resources, Demersal fisherie, Fishery surveys, Biomass, Population density, Shrimp fisheries, Catch/effort, ISW, Bangladesh,

Shell-and-tube based thermal energy system coupled with flat plate solar collector

To secure optimum utilisation of solar energy sources, a novel shell-and-tube heat exchanger with multi-tube passes and extended surfaces based latent heat storage (LHS) system was designed, developed and commissioned with an integration to flat plate solar collector in Organic Rankine Cycle (ORC). Paraffin, HFE-7000 and water were employed as thermal storage material and heat transfer fluids to sustain simultaneous generation of electricity and heat. It was noticed that the melting/solidification rates and charging/discharging powers were significantly augmented with an increase in Stefan number. However, an increase in Reynolds number had offered a moderate enhancement. The proposed design solution proficiently captured and released 14.35 MJ and 13.63 MJ while charging and discharging at constant inlet temperature for 3 h and 1.5 h, respectively. It was deduced that heat and electricity demands for domestic and industrial applications could be achieved and supplied by regulating inlet operating conditions of LHS system and/or by assembling LHS systems in series or parallel combinations

Effect of Packet Inter-arrival Time on the Energy Consumption of Beacon Enabled MAC Protocol for Body Area Networks

AbstractOne of the major concerns for the development of Wireless Body Area Network (WBAN) is to increase the network lifetime. IEEE 802.15.4 standard for Medium Access Control (MAC) layer can be used for energy efficient and reliable transmission by modifying the different control parameters. Such a modification is very difficult, because an accurate model for the influence of these control parameters of minimum energy and delay is not available. Moreover, there is no mechanism available how to adopt and implement these parameters that can implement on the Body Nodes (BNs). In this paper, we provide the mechanism for emergency data along with normal and periodic data by modifying the superframe structure. Coordinator transmits and extra beacon upon the request of emergency data. A comprehensive analysis of energy consumption of BNs including the affect of packet inter-arrival time is given in this paper. Analysis show that, Contention Access Period (CAP) of superframe is not feasible for emergency data due to its extra delay and energy

A Novel Energy-Efficient Reservation System for Edge Computing in 6G Vehicular Ad Hoc Network

The roadside unit (RSU) is one of the fundamental components in a vehicular ad hoc network (VANET), where a vehicle communicates in infrastructure mode. The RSU has multiple functions, including the sharing of emergency messages and the updating of vehicles about the traffic situation. Deploying and managing a static RSU (sRSU) requires considerable capital and operating expenditures (CAPEX and OPEX), leading to RSUs that are sparsely distributed, continuous handovers amongst RSUs, and, more importantly, frequent RSU interruptions. At present, researchers remain focused on multiple parameters in the sRSU to improve the vehicle-to-infrastructure (V2I) communication; however, in this research, the mobile RSU (mRSU), an emerging concept for sixth-generation (6G) edge computing vehicular ad hoc networks (VANETs), is proposed to improve the connectivity and efficiency of communication among V2I. In addition to this, the mRSU can serve as a computing resource for edge computing applications. This paper proposes a novel energy-efficient reservation technique for edge computing in 6G VANETs that provides an energy-efficient, reservation-based, cost-effective solution by introducing the concept of the mRSU. The simulation outcomes demonstrate that the mRSU exhibits superior performance compared to the sRSU in multiple aspects. The mRSU surpasses the sRSU with a packet delivery ratio improvement of 7.7%, a throughput increase of 5.1%, a reduction in end-to-end delay by 4.4%, and a decrease in hop count by 8.7%. The results are generated across diverse propagation models, employing realistic urban scenarios with varying packet sizes and numbers of vehicles. However, it is important to note that the enhanced performance parameters and improved connectivity with more nodes lead to a significant increase in energy consumption by 2%

A holistic mathematical modelling and simulation for cathodic delamination mechanism – a novel and an efficient approach

This paper addresses a holistic mathematical design using a novel approach for understanding the mechanism of cathodic delamination. The approach employed a set of interdependent parallel processes with each process representing: cation formation, oxygen reduction and cation transport mechanism, respectively. Novel mathematical equations have been developed for each of the processes based on the observations recorded from experimentation. These equations are then solved using efficient time-iterated algorithms. Each process consists of distinct algorithms which communicate with each other using duplex channels carrying signals. Each signal represents a distinct delamination parameter. As a result of interdependency of various processes and their parallel behaviour, it is much easier to analyse the quantitative agreement between various delamination parameters. The developed modelling approach provides an efficient and reliable prediction method for the delamination failure. The results obtained are in good agreement with the previously reported experimental interpretations and numerical results. This model provides a foundation for the future research within the area of coating failure analysis and prediction

An energy-efficient distributed clustering algorithm for heterogeneous WSNs

Wireless sensor networks (WSNs) were envisaged to become the fabric of our environment and society. However, they are yet unable to surmount many operational challenges such as limited network lifetime, which strangle their widespread deployment. To prolong WSN lifetime, most of the existing clustering schemes are geared towards homogeneous WSN. This paper presents enhanced developed distributed energy-efficient clustering (EDDEEC) scheme for heterogeneous WSN. EDDEEC mainly consists of three constituents i.e., heterogeneous network model, energy consumption model, and clustering-based routing mechanism. Our heterogeneous network model is based on three energy levels of nodes. Unlike most works, our energy consumption model takes into account the impact of radio environment. Finally, the proposed clustering mechanism of EDDEEC changes the cluster head selection probability in an efficient and dynamic manner. Simulation results validate and confirm the performance supremacy of EDDEEC compared to existing schemes in terms of various metrics such as network life.Deanship of Scientific Research at King Saud University Research Group Project No. RG#1435-051.Scopu

Wear Performance Analysis of Ni-Al2O3 Nanocomposite Coatings under Nonconventional Lubrication

This article presents the wear study of Ni-Al2O3 nanocomposite coatings in comparison to uncoated steel contacts under reciprocating motion. A ball-on-flat type contact configuration has been used in this study in which a reciprocating flat steel sample has been used in coated and uncoated state against a stationary steel ball under refrigerant lubrication. The next generation of environmentally friendly refrigerant HFE-7000 has been used as lubricant in this study without the influence of any external lubricant. The thermodynamic applications and performance of HFE-7000 is being studied worldwide as it is replacing the previous generation of refrigerants. No work however has been performed to evaluate the wear performance of HFE-7000 using nanocomposite coatings. The wear scar developed on each of the flat and ball samples was studied under a Scanning Electron Microscope (SEM). The micrographs show that a combination of adhesive and abrasive wear occurs when using uncoated steel samples. Micro-delamination is observed in the case of Ni-Al2O3 nanocomposite coatings accompanied by adhesive and abrasive wear. Wear volume of the wear track was calculated using a White Light Interferometer. Energy-Dispersive X-ray Spectroscopic (EDS) Analysis of the samples reveal fluorine and oxygen on the rubbing parts when tested using coated as well as uncoated samples. The formation of these fluorinated and oxygenated tribo-films help reduce wear and their formation is accelerated by increasing the refrigerant temperature. Ni-Al2O3 nanocomposite coatings show good wear performance at low and high loads in comparison to uncoated contacts. At intermediate loads the coated contacts resulted in increased wear especially at low loads. This increase in wear is associated with the delamination of the coating and the slow formation of protective surface films under these testing conditions

Impact of log parsing on deep learning-based anomaly detection

Software systems log massive amounts of data, recording important runtime information. Such logs are used, for example, for log-based anomaly detection, which aims to automatically detect abnormal behaviors of the system under analysis by processing the information recorded in its logs. Many log-based anomaly detection techniques based on deep learning models include a pre-processing step called log parsing. However, understanding the impact of log parsing on the accuracy of anomaly detection techniques has received surprisingly little attention so far. Investigating what are the key properties log parsing techniques should ideally have to help anomaly detection is therefore warranted. In this paper, we report on a comprehensive empirical study on the impact of log parsing on anomaly detection accuracy, using 13 log parsing techniques, seven anomly detection techniques (five based on deep learning and two based on traditional machine learning) on three publicly available log datasets. Our empirical results show that, despite what is widely assumed, there is no strong correlation between log parsing accuracy and anomaly detection accuracy, regardless of the metric used for measuring log parsing accuracy. Moreover, we experimentally confirm existing theoretical results showing that it is a property that we refer to as distinguishability in log parsing results—as opposed to their accuracy—that plays an essential role in achieving accurate anomaly detection