Journal of Graphic Era University

Reliability Analysis of Bucket-Wheel Excavator Parts – Application of Critical Position Selection Algorithm

Dejan Branković, Zdravko Milovanović, Valentina Janièić-Milovanović — Thu, 19 Dec 2024 00:00:00 +0000

Mining machines represent complex technical systems exposed to very difficult and demanding working conditions. The requirement of a high degree of effectiveness of technical systems in surface mines conditions a special organization of maintenance. The maintenance imperative is to ensure high reliability of parts of technical systems. For the maintenance of complex systems, made up of a large number of components, the parts whose failures cause the greatest negative consequences for the complete production system are particularly important. Analysis of the criticality of parts of technical systems directs maintenance activities to the prevention of failure states on key elements and ensuring the highest possible degree of their reliability. The paper presents the methodology of defining the critical position of the technical system Bucket-Wheel Excavator – belt conveyor – dumper on the open pit using the critical position selection algorithm. The basic criterion for choosing a critical position is a comparison of the frequency of failure and the reliability of individual components of technical systems. The results of the analysis confirm the connection of the statistical data analysis of the number of failure states of the working positions of the technical system with empirically determined reliability functions according to the methodology of non-parametric determination of reliability. The presented algorithm represents a methodology for recognizing the critical elements of technical systems whose operation has the greatest impact on the stability of the functioning of the complete technical system. Optimizing critical positions reduces total system downtime, increases productivity and improves overall business results.

Mathematical Modelling: Transforming Concepts Into Reality

Simran Sahlot, Geeta Arora — Wed, 05 Feb 2025 00:00:00 +0000

Mathematical modelling is a powerful tool that bridges the gap between theoretical concepts and real-world phenomena. It involves the development of mathematical equations, algorithms, and computational techniques to describe, analyse, and predict complex systems across various disciplines. Researchers are creating mathematical models based on actual events to meet the demands of this scientific era. The main aim of mathematical modelling is to gain understanding into complex systems, make predictions, and optimize processes. By using mathematical equations, scientists and researchers can simulate and analyse various scenarios, explore the effects of different parameters, and make informed decisions. Mathematical models can provide a better understanding of the given mechanisms governing the system and help uncover relationships and patterns that may not be immediately apparent. Policymakers use mathematical models to inform their choices when deciding on public health interventions like lockdowns, social isolation tactics, and vaccination rollout plans.

Effects of Human Activities from the Indo-Gangetic Plain on the Air Quality in the Foothills of the Himalayas

Nand Kishore, Bipin Singh Koranga, Atul Kumar Srivastava — Wed, 05 Feb 2025 00:00:00 +0000

The relationship between surfaces that measure climatic parameters and the mass concentration of various air pollutants across the Indo-Gangetic Plain (IGP) and Himalayan foothills is investigated using three separate stations. In an industrial area of Delhi, a residential area of Shimla, and a residential area of Hisar, the simultaneous measurement of mass concentrations of air pollutants such as NO2, SO2, RSPM, and SPM, as well as the impact of surface meteorological parameters on their distributions, are investigated for the study period of January 2005 to December 2012. The seasonal variations in air pollutants were also examined. Additionally, a regression analysis between the daily mass concentration of air pollutants and metrological parameters has been carried out. The correlation coefficients between climatic factors and air pollutants were found to be positive with the exception of the correlations between wind direction and SO2 and visibility and NO2. Additionally, the time series of AOD and ASMF, two MODIS-derived daily and monthly mean columnar aerosol parameters, are examined over Delhi, Hisar, and Shimla from 2005 to 2012. The maximum and minimum AOD values for Delhi, Hisar, and Shimla, respectively, are 2.3 and 0.08, 3.5 and 0.09, and 2.6 and 0.06. However, at all three locations, ASMF fluctuated between 0 and 1. The highest values of AOD were observed in the months of June and August, with a pattern of increasing values from January to June and a pattern of decreasing values from August to December. While an increasing pattern was seen during the post-monsoon and winter months, ASMF was found to diminish from February up to April or May. A back-trajectory analysis of the air mass is used to examine the effects of the observed increased air pollution from the IGP over the Himalayan city of Shimla. The trajectories (23%) passing over the IGB in a southeasterly direction were seen to have an impact on Shimla.

Numerical Simulations of Shock-driven Heavy Fluid Layer

Satyvir Singh — Wed, 05 Feb 2025 00:00:00 +0000

The present study presents the numerical simulations for a shocked-heavy fluid layer with a stratified N₂/SF₆/N₂ configuration. Simulations were conducted using a third-order modal discontinuous Galerkin method to solve the compressible two-component Euler equations. The results were validated against experimental data, confirming the accuracy of the computational approach. Dynamics of the heavy fluid layer were found to be strongly influenced by the shock Mach numbers M_s = 1.15, 1.25, 1.5. At a lower Mach number Ms = 1.15, the interface deformations remained smooth and relatively symmetric, with limited vorticity generation and weak perturbations. Baroclinic effects at this stage were minimal, and the instability growth remained linear. As the Mach number increased to M_s = 1.25, the interaction became nonlinear, leading to the formation of small-scaled vortex structures driven by moderate baroclinic effects. Interface mixing intensified as rotational motion increased. At the highest Mach number M_s = 1.5, the interface rapidly evolved into chaotic structures, characterized by significant vorticity amplification, vortex roll-up, and the onset of turbulence. The baroclinic vorticity, resulting from the misalignment of pressure and density gradients, dominated the vorticity production mechanism, particularly at higher Mach numbers. Quantitative analysis demonstrated that average vorticity, baroclinic vorticity, and enstrophy grew rapidly with increasing Mach numbers. Enstrophy, which quantifies turbulence intensity, exhibited pronounced growth at M_s = 1.5, marking the transition to turbulent mixing.

Trustworthy AI in Biometrics: A Comprehensive Review of Trends and Challenges

Shefali Arora, Kanu Goel, Shikha Gupta, Ruchi Mittal, Avinash Kumar Shrivastava — Tue, 18 Feb 2025 00:00:00 +0000

Deep Learning (ML) and Artificial Intelligence (AI) are rapidly spreading over many application domains. However, the creation of intelligent systems is constrained by inherent flaws in the learning algorithms that are employed. One major barrier to the application of these techniques is the unpredictable nature of model performance. The reliability of a model is determined by its capacity to remove biases, elucidate findings, and adapt to changes in input data. The idea of trustworthy AI uses a variety of machine learning techniques to explain a model’s decision-making process, hence boosting user confidence in the model’s output. The significance of reliable AI in the context of biometrics is the main topic of this study. Our survey identifies the several types of reliable AI that can be used to increase the dependability of the choices made.

Assessment of Alternative Controller Tuning Techniques for Systems without Ultimate Parameters

Ishita Uniyal, Padmanabh Thakur, Parvesh Saini — Tue, 18 Feb 2025 00:00:00 +0000

This work presented in this article aims at designing and analysingalternate methods for tuning of the Proportional – Integral – Derivative (PID) controller for the plants that do not possess the ultimate parameters (ultimate gain and ultimate period). The motivation lies in the fact that the conventional methods such as the Ziegler-Nichols (Z-N) approach require the ultimate parameters for designing the PID controllers. However, because there exist some plants which do not have these parameters, and hence it is difficult to design controllers for such plants using conventional approaches directly. So, there is a need of using some alternative ways to design controllers for such plants. So, in the presented work, Particle Swarm Optimization (PSO), Extended Forced Oscillations (EFO), and Internal Model Control (IMC) methods have been applied for designing PID controllers suitable for such a plant. All the techniques were tested for their capability in optimizing control performance on rise time, settling time, overshoot, and error indices like Integral of Absolute Error (IAE), Integral of Squared Error (ISE), Integral of Time-Weighted Absolute Error (ITAE), and Integral of Time Squared Error (ITSE). Special attention was given to the objective function of ITAE minimization for the PSO-based PID controller. The results show that out of various approaches, the PSO-based PID controller provides the fastest response with minimum overshoot and low values of errors compared to EFO-based and IMC-based PID controllers. The EFO-based PID controller gave a mediocre performance while the IMC-based PID turned out to be the worst, giving a response that was the slowest with maximum errors. This work is carried out for a comprehensive comparison of various alternative tuning approaches, and it presents PSO-based PID as the most robust and reliable solution for plants with no ultimate parameters hence proposes it as an efficient alternative to conventional PID tuning strategies.

Suitability of Recycled Aggregates for Application in Structural Concrete: Experimental Study

Tado Gyadi, Sudip Basack — Tue, 18 Feb 2025 00:00:00 +0000

Demolition wastes have been increasing day by day as the age-old concrete structures are to be replaced for a new one. In order to reduce the impact of this demolished concrete in nature, recycling it as coarse aggregates appearsto be a highly sustainable option. Recycled aggregates comprise crushed, graded inorganic particles processed from the materials that have been used in the construction and demolition debris. The aim of this project is to determine the suitability of recycled aggregates for application in structural concrete in terms of strength and serviceability criteria. The initial questions concerning the strength of aggregate and workability enhancement aredue to the associated mortar content. Few tests were conducted on the properties of the new aggregate, such as specific gravity, water absorption, and aggregate crushing value. Properties of concrete such as compression strength, splitting tensile strength, flexural strength, and modulus of elasticity were found out. Finally, the application of recycled coarse aggregates in pavement construction was studied. A brief comparison of the cost efficiency was also evaluated.

Battery and Ultra-Capacitor Based Hybrid Energy Storage System Utilizing a Multi-Input DC-DC Buck-Boost Converter

Tue, 18 Feb 2025 00:00:00 +0000

Hybrid power systems have evolved into a vital component of contemporary power networks, finding application in various domains ranging from automotive to small-scale off-grid setups. Their purpose is to optimize the utilization of diverse energy sources. This study delves into the efficacy of integrating ultra-capacitors and batteries synergistically. Employing a multi-input converter to drive a variable DC load, the aim is to minimize losses and expenses. In the proposed configuration, a single inductor is utilized, facilitating the integration of a variable array of distributed energy sources. Notably, this converter expedites ultra-capacitor (UC) charging by offering a low inductance pathway, distinguishing it from conventional multi-input DC-DC converters. This proposed topology is bidirectional and adaptable to accommodate varying numbers of energy sources. The obtained numerical results reveal the converter’s effectiveness in stabilizing output voltage and current, making it suitable for multiple applications like electric vehicles, fuel cell systems, and renewable energy integration. Additionally, in the proposed topology, the results showed that it could charge a 2000F UC from a 300V source from 40% to 100% in just 400s and from a 150V battery from 20% to over 90% in just 200s due to the single inductor present in the charging path. Moreover, the load voltages are below 2% in all operational modes when either one or two sources are driving the load. Future research may focus on refining control algorithms to further enhance system efficiency and expand its applicability across different sectors.