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Exploring the Tribo-corrosion Characteristics of Clay- and MgO-Reinforced Composites: A Comparative Study

Journal of The Institution of Engineers (India): Series D 2024年 1-10页

作者： Dwivedi, Shashi Prakash Maurya, Manish Lloyd Institute of Engineering and Technology Uttar Pradesh Greater Noida India Accurate Institute of Management and Technology Uttar Pradesh Greater Noida India

This experimental study explores the tribo-corrosion characteristics of clay- and MgO-reinforced aluminum metal matrix composite. The research focuses on achieving uniform dispersion of reinforcement particles throughout the matrix to enhance mechanical properties. Stir casting technique was used to develop the composite. The addition of 5% MgO and 5% clay to the composite resulted in a significant improvement in tensile strength by approximately 19.82% and hardness by around 20%, attributed to their combined effects in resisting plastic deformation and enhancing resistance to indentation. Thus, clay can be used as secondary reinforcement in developing the composite. The maximum tensile strength and hardness without reinforcing clay and after reinforcing clay was found to be 222.44 MPa, 73 HV and 221.67 MPa, 72 HV. After reinforcing clay, similar types of tensile strength and hardness was achieved. Furthermore, fatigue strength saw a notable enhancement of approximately 23.14% at 1 × 107 cycles. The composite exhibited a low wear rate of 0.0017 mm3/m, indicating favorable resistance to wear for sliding contact applications. Additionally, the corrosion behavior of the composite was examined in the presence of 3.5 wt% NaCl over 120 h, revealing a corrosion rate of 0.587 mm/year, indicative of satisfactory corrosion resistance. These findings contribute valuable insights into the performance and suitability of clay- and MgO-reinforced composites for several engineering applications. © The Institution of Engineers (India) 2024.

关键词： Corrosion rate

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An Experimental Investigation on Mechanical and Tribological Properties of Metal Matrix Composites Fabricated with Waste Aluminum, SAC, and CDPF via Stir Casting

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Journal of The Institution of Engineers (India): Series D 2024年第1期106卷 325-331页

作者： Verma, Shailendra Kumar Dwivedi, Vijay Kumar Dwivedi, Shashi Prakash Department of Mechanical Engineering Institute of Engineering and Technology GLA University Mathura281406 India Department of Mechanical Engineering Noida Institute of Engineering and Technology Greater Noida201306 India Department of Mechanical Engineering Lloyd Institute of Engineering and Technology Greater Noida India

This study focuses on combining spent alumina catalyst (SAC) with carbonized date palm fiber (CDPF) to create a hybrid combination that is integrated into a metal matrix using waste aluminum. The research takes a thorough approach to analyzing the mechanical and tribological characteristics of the produced hybrid composite material. The stir casting process is used to create five samples of scrap aluminum reinforced with SAC (6.25–1.25%) and CDPF (1.25–6.25%). The goal of this strategic volume percentage change is to improve and fine-tune the mechanical and tribological performance of the generated composite materials. By adding 1.25% SAC and 6.25% CDPF to waste aluminum, the mechanical properties have been considerably improved. As a consequence, tensile strength has increased by 21.84%, microhardness has increased by 32.12%, and toughness has increased by 24.54%. Further in the wear investigation, the decrease in coefficient of friction and optimal reduction in rate of wear. In conclusion, these hybrid reinforcements significantly increase both the tribological and mechanical characteristics of metals while having no substantial negative impacts on humans or the ecosystem. © 2024, The Institution of Engineers (India).

关键词： Wear of materials

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EVALUATION OF ALUMINUM OXIDE NANOPARTICLE BLENDED WITH ALCOHOL BASED BIODIESEL AT VARIABLE COMPRESSION RATIOS

EVALUATION OF ALUMINUM OXIDE NANOPARTICLE BLENDED WITH ALCOH...

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作者： Sharma, Payal Chauhan, Nathi Ram Saraswat, Manish IGDTUW India LLOYD Institute of Engineering and Technology India

This paper highlights the use of aluminum oxide nanoparticles as an additive in diesel-butanol blends to show its effect on fuel consumption, emissions and performance. In the present experiment, different concentrations of aluminium oxide nanoadditives (30, 50, and 70 ppm) are used in alcohol-based biodiesel. Butanol has been used in concentrations of 5 and 10 % in diesel and therefore all blends are termed as B5 and B10 in addition to nanoparticle concentration to avoid complexity. These different blends (B5+30, B5+50, B5+70, B10+30, B10+50, B10+70) are tested for various engine loads at a constant speed of 1500 rpm. The experiment was performed on a Variable compression ratio (VCR) engine at varying compression ratios of 16, 17, and 18. Engine characteristics at different compositions of the blend at different compression ratios were provided by the interfaced computer through the software. The enhanced performance effects can be easily seen from the outcomes in the increment in brake thermal efficiency of the blends as compared to neat diesel. Considerable decrement can be observed in carbon monoxide (CO) and unburnt hydrocarbon (HC) values with an increase in compression ratio. Moderate reduction can be observed in NOx at higher loads in contrast to neat diesel. ©2024: The Royal Institution of Naval Architects.

关键词： Biodiesel

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Challenges and issues in facial emotion recognition techniques

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International Journal of Business Intelligence and Data Mining 2024年第2期24卷 160-182页

作者： Khan, Nizamuddin Singh, Ajay Vikram Agrawal, Rajeev Amity Institute of Information Technology Amity University Uttar Pradesh Noida201303 India Lloyd Institute of Engineering and Technology Uttar Pradesh Greater Noida201306 India

We analyse the most obvious distributed writing in facial emotion recognition conveyed throughout the last decade in this paper. This paper assesses the analysis of the work done as such far and tries to assess each based on a set of composite parameters. Also, under the equivalent, we look for future work based on new specialisation regions and identify research gaps. There is a project underway to determine the optimum procedure that could be employed to meet all of the established constraints. Furthermore, a heading is expected for work ahead on new stronghold locations below the same. The magnitude of such labour cannot be undervalued, especially for the injured and the more prepared, where outer appearance may continue to play an important role in conveying thoughts in a robotic manner. Furthermore, there are numerous other beneficial applications that cover a wide variety of our daily lives. © 2024 Inderscience Enterprises Ltd.. All rights reserved.

关键词： Emotion Recognition

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Enhancing Feature Extraction Technique Through Spatial Deep Learning Model for Facial Emotion Detection

Annals of Emerging Technologies in Computing

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Annals of Emerging Technologies in Computing 2023年第2期7卷 9-22页

作者： Khan, Nizamuddin Singh, Ajay Vikram Agrawal, Rajeev Amity Institute of Information Technology Amity University UP Noida India Lloyd Institute of Engineering and Technology UP G. Noida India

Automatic facial expression analysis is a fascinating and difficult subject that has implications in a wide range of fields, including human–computer interaction and data-driven approaches. Based on face traits, a variety of techniques are employed to identify emotions. This article examines various recent explorations into automatic data-driven approaches and handcrafted approaches for recognising face emotions. These approaches offer computationally complex solutions that provide good accuracy when training and testing are conducted on the same datasets, but they perform less well on the most difficult realistic dataset, FER-2013. The article's goal is to present a robust model with lower computational complexity that can predict emotion classes more accurately than current methods and aid society in finding a realistic, all-encompassing solution for the facial expression system. A crucial step in good facial expression identification is extracting appropriate features from the face images. In this paper, we examine how well-known deep learning techniques perform when it comes to facial expression recognition and propose a convolutional neural network-based enhanced version of a spatial deep learning model for the most relevant feature extraction with less computational complexity. That gives a significant improvement on the most challenging dataset, FER-2013, which has the problems of occlusions, scale, and illumination variations, resulting in the best feature extraction and classification and maximizing the accuracy, i.e., 74.92%. It also maximizes the correct prediction of emotions at 99.47%, and 98.5% for a large number of samples on the CK+ and FERG datasets, respectively. It is capable of focusing on the major features of the face and achieving greater accuracy over previous fashions. © 2023 by the author(s). Published by Annals of Emerging Technologies in Computing (AETiC),.

关键词： Feature extraction

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Sawdust-Reinforced Glass Fiber Epoxy-Based Composite: Fabrication and Analysis of Mechanical Properties

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Journal of The Institution of Engineers (India): Series D 2024年 1-12页

作者： Chauhan, Shailendra Singh Maurya, Manish Dwivedi, Shashi Prakash Babu Banarsi Das Institute of Technology and Management Uttar Pradesh Lucknow India Accurate Institute of Management and Technology Uttar Pradesh Greater Noida India Lloyd Institute of Engineering and Technology Uttar Pradesh Greater Noida India

The aim of this research is to develop a glass fiber epoxy/sawdust composite using leftover sawdust from the industry as reinforcement. Teak, sal, and rubber wood powders were used as reinforcing materials, while epoxy resin (LY556) was utilized as a matrix material for composite synthesis. The mechanical property, i.e., hardness, was used as a response variable. Response surface approach was used to design the trials. In order to plan experiments and analysis of data, a software design expert 11 was used. A quadratic regression model was developed for the forecasting of the outcome of process constraints on the hardness of the composite material. Confirmation experiments revealed that the built model performs effectively in the test environment. Flexible intensity, impact intensity, density, and compressive strength are among the mechanical and physical properties that are evaluated. The mechanical parameters of the composite at the optimal level of process parameter were found to have hardness (21.45 BHN), tensile strength (65.6 MPa), impact energy (5.1 kJ/m2), compressive strength (38 MPa), and density (618 kg/m3). © The Institution of Engineers (India) 2024.

关键词： Hardness

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Agro-industrial waste management employing benefits of artificial intelligence

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Environmental Science and Pollution Research 2024年第22期31卷 33148-33154页

作者： Rai, Amrita Kundu, Krishanu Department of Electronics and Communications Lloyd Institute of Engineering and Technology UP Greater Noida201306 India ECE Department GL Bajaj Institute of Technology and Management UP Greater Noida201306 India

By 2050, the world’s population is predicted to reach over 9 billion, which requires 70% increased production in agriculture and food industries to meet demand. This presents a significant challenge for the agri-food sector in all aspects. Agro-industrial wastes are rich in bioactive substances and other medicinal properties. They can be used as a different source for manufacturing products like biogas, biofuels, mushrooms, and tempeh, the primary ingredients in various studies and businesses. Increased importance is placed on resource recovery, recycling, and reusing (RRR) any waste using advanced technology like IoT and artificial intelligence. AI algorithms offer alternate, creative methods for managing agro-industrial waste management (AIWM). There are contradictions and a need to understand how AI technologies work regarding their application to AIWM. This research studies the application of AI-based technology for the various areas of AIWM. The current work aims to discover AI-based models for forecasting the generation and recycling of AIWM waste. Research shows that agro-industrial waste generation has increased worldwide. Infrastructure needs to be upgraded and improved by adapting AI technology to maintain a balance between socioeconomic structures. The study focused on AI’s social and economic impacts and the benefits, challenges, and future work in AIWM. The present research will increase recycling and reproduction with a balance of cost, efficiency, and human resources consumption in agro-industrial waste management. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Farms

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Maximum power tracking from solar PV system by using fuzzy-logic and incremental conductance techniques

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Materials Today: Proceedings 2023年 79卷 267-277页

作者： Kumar, Pramod Shrivastava, Ashish Lloyd Institute of Engineering and Technology UP Greater Noida 201306 India ShriVishwakarma Skill University Haryana Gurugram 122003 India

This paper includes 60KW solar PV design and graphically present the output by using input parameters i.e. insolation and temperature. To extract and maximize the output power of solar PV and buck-boost converter, the two techniques are used i.e. fuzzy-logic and incremental conductance. In this paper, these two techniques designed and simulated in MATLAB tool boxes and tracking solar PV through a buck-boost converter to produce desired and stable output in terms of voltage, current and *** paper also provides a MATLAB simulation design and performance for PV modeling and buck-boost converter. By studying different outputs of different techniques from simulation results, the best technique and result will be considered. © 2022

关键词： Buck-Boost converter

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COMPARATIVE STUDY OF SEISMIC ANALYSIS OF RCC BUILDING USING IS CODE 1893:2016 (PART-1) AND NEPAL BUILDING CODE 105:2020

COMPARATIVE STUDY OF SEISMIC ANALYSIS OF RCC BUILDING USING ...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Timilsena, Homraj Singh, Ashuvendra Kumar, Mukesh Goyal, Samaksh Department of Civil Engineering Dev Bhoomi Institute of Technology Dehradun India Lloyd Institute of Engineering & Technology Greater Noida India Department of Law Quantum University India

ISBN: (纸本)9798350355338

Nepal lies in Indian SubContinent. Before Nepal Building code has been drafted use of Indian code were common. After recent amendment in NBC 105:1994, NBC 105:2020 is released. This paper presents the analysis of 3 storey with staircase cover, 5 storey with stair cover, 7 storey with stair cover and 10 storey with staircase cover. For all these cases study has been done in Hard soil, Medium Soil and Soft Soil using IS and NBC code. The response of building has been studied by using response spectrum method. For 3 and 5 storey building three models has been studied, model 1 uses time period having no effect of infill wall and model 2 uses time period based on based dimension using IS code, Model 3 uses time period mentioned in NBC code. For 7 and 10 storey building shear wall has been assigned, hence model 2 uses time period based on based dimension using IS code, Model 3 uses time period mentioned in NBC code. Base shear, Storey drift are compared for all three models in different soil types. © 2024 IEEE.

关键词： Stairs

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Noise Removal of EMG Signal for Healthy Person Using Wavelet Decomposition Method with Three Different Wavelet Families to Identify the Best Wavelet for Noise Removal

Noise Removal of EMG Signal for Healthy Person Using Wavelet...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Dubey, Alok Singh, Rupali Rai, Amrita Department of Electronics and Communication Engineering SRM Institute of Science and Technology Delhi NCR Campus Ghaziabad India ECE Department Lloyd Institute of Engineering and Technology Greater Noida India

ISBN: (纸本)9798350355338

Electromyography (EMG) is a study of muscle function and finds application in biomedicine and clinical settings. During myoelectrical simulation, EMG signal records useful muscle responses and noise. Noise is originated normally from technical and biological sources which interferes with muscle activity analysis and thus, requires careful study. Removal of this noise from the EMG signal is crucial which can be carried out using different techniques. This paper explores the wavelet decomposition technique for the removal of noise from EMG signal with different types of mother wavelets. Further, the analysis is performed to identify the best mother wavelet to produce processed biomedical signal. Moreover, the Signal-to-Noise Ratio (SNR) for the noise free EMG signal has been estimated to determine the best wavelet for removing the noise from the biomedical signal. © 2024 IEEE.

关键词： Wavelet decomposition

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