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Design and Fabrication of Differential Thermal Analyser for Thermal Characterization of Materials
Thermal analysis techniques are widely used in both industrial and scientific domains to understand the changes in structural and chemical composition of materials. The structural and chemical composition of most of the materials undergoes changes when heated. Using various thermal analysis techniques such changes are monitored in various atmospheres of interest. Through these analytical experimental techniques the physical properties of the substance can be studied as a function of temperature. These techniques can be used to characterize, qualitatively and quantitatively a huge range of materials over a substantial temperature range. Results from the thermal analysis instruments can be obtained quickly and henceforth it has wide variety of applications. These thermal methods find widespread use for both quality control and research applications on polymers, pharmaceutical preparations, clay, minerals, metals and alloys. Differential thermal analysis is one of the thermal analysis methods, which records the difference in temperature (??T) between a substance and an inert reference material as a function of furnace temperature or time. Any transformation ?? change in specific heat or an enthalpy of transition ?? can be detected by Differential Thermal Analyser (DTA). The automated DTA is available readily from various manufacturers but it is expensive. Therefore researchers usually prefer to design and build their own instruments as per the individual requirements of experiments under various specialized conditions. Furnace, sample holder, controlled heating source, low noise-high gain amplifier and differential recorder are the main units of a differential thermal analyser. In the present work, we have made an attempt to design and fabricate a low cost differential thermal analyser for the thermal analysis of materials. -
Design and genome engineering of microbial cell factories for efficient conversion of lignocellulose to fuel
The gradually increasing need for fossil fuels demands renewable biofuel substitutes. This has fascinated an increasing investigation to design innovative energy fuels that have comparable Physico-chemical and combustion characteristics with fossil-derived fuels. The efficient microbes for bioenergy synthesis desire the proficiency to consume a large quantity of carbon substrate, transfer various carbohydrates through efficient metabolic pathways, capability to withstand inhibitory components and other degradation compounds, and improve metabolic fluxes to synthesize target compounds. Metabolically engineered microbes could be an efficient methodology for synthesizing biofuel from cellulosic biomass by cautiously manipulating enzymes and metabolic pathways. This review offers a comprehensive perspective on the trends and advances in metabolic and genetic engineering technologies for advanced biofuel synthesis by applying various heterologous hosts. Probable technologies include enzyme engineering, heterologous expression of multiple genes, CRISPR-Cas technologies for genome editing, and cell surface display. 2022 Elsevier Ltd -
Design and Implementation Bidirectional DC-AC Converter for Energy Storage System
This article proposes a bidirectional single-phase dc-ac converter with triple port converter (T-PC) for application of energy storage. This proposed converter provides three ports such as ac port, dc port, and dc bus port to achieve three power interfacing ports. For the direct conversion process, dc port is directly connected to T-PC, and direct power will be exchanged between energy storage device (ESD) and grid when the ESD voltage peak amplitude is lower than the ac voltage. Thus, a dc-dc converter downstream power process gets reduced, and power loss is decreased considerably. Due to multilevel characteristics, switching losses in the T-PC can be reduced. The efficiency of the overall bidirectional dc-ac conversion process can be increased significantly. The circuit model, working principle, and modulation control of T-PC-based bidirectional dc-ac conversion concepts are analyzed. A 1.5-kW test-bench model is developed and its effectiveness is verified to find the merits of suggested conversion. 2021 IEEE. -
Design and implementation of a universal converter for microgrid applications using approximate dynamic programming and artificial neural networks
This paper introduces a novel design for a universal DC-DC and DC-AC converter tailored for DC/AC microgrid applications using Approximate Dynamic Programming and Artificial Neural Networks (ADP-ANN). The proposed converter is engineered to operate efficiently with both low-power battery and single-phase AC supply, utilizing identical side terminals and switches for both chopper and inverter configurations. This innovation reduces component redundancy and enhances operational versatility. The converter's design emphasizes minimal switch usage while ensuring efficient conversion to meet diverse load requirements from battery or AC sources. A conceptual example illustrates the design's principles, and comprehensive analyses compare the converter's performance across various operational modes. A test bench model, rated at 3000W, demonstrates the converter's efficacy in all five operational modes with AC/DC inputs. Experimental results confirm the system's robustness and adaptability, leveraging ADP-ANN for optimal performance. The paper concludes by outlining potential applications, including microgrids, electric vehicles, and renewable energy systems, highlighting the converter's key advantages such as reduced complexity, increased efficiency, and broad applicability. The Author(s) 2024. -
Design and Implementation of Active Clamp Flyback Converter for High-Power Applications
This paper proposes a solar-powered isolated DCDC converter for high-power applications. The main aim of this paper is to achieve voltage regulation in the output side of the converter and to integrate a lossless active clamp flyback circuit (LACF) to compensate for the high-voltage issues that arise from one-stage DCDC converters. Hardware is developed with a power rating of 2 kW to test the performance of the proposed circuit. The circuit is designed using low-voltage devices and features such as soft switching and regeneration due to the LACF, which enhances efficiency. A novel luminous control algorithm is presented to improve the converter performance. The proposed circuits performance and feasibility are compared with existing converter parameters, such as the number of components in the circuit, voltage rating, and regeneration. 2023 by the authors. -
Design and implementation of Adaptive PI control based dynamic voltage restorer for solar based grid integration
This paper introduces an innovative approach to address voltage fluctuations in solar-based grid integration by implementing an adaptive PI control-based Dynamic Voltage Restorer (DVR). This DVR is engineered to counteract voltage disruptions resulting from grid disturbances and the intermittent nature of solar energy generation. To achieve optimal performance in diverse operating conditions, the adaptive PI controller dynamically adjusts its parameters, adapting to changes in load and solar generation. The system is realized on a digital signal processor (DSP) and evaluated within a laboratory-scale solar-based grid integration setup. The findings reveal that the proposed system effectively mitigates voltage fluctuations, ensuring a stable integration of solar energy into the grid. The adaptive PI control-based DVR outperforms traditional PI control-based DVRs, particularly when dealing with variable solar energy generation. This approach holds significant potential for practical applications in solar-based grid integration systems. 2024 IEEE. -
Design and Implementation of an Optimized Mask RCNN Model for Liver Tumour Prediction and Segmentation
Segmentation of liver tumour is a tedious job due to their large variation in location and closeness to nearby organs. In this research, a novel Mask RCNN prototype is developed which uses ResNet-50 model. The architecture utilizes the masked location of convolution neural network to precisely detect liver tumours by recognizing liver sites to deal with changes in liver and CT snaps with distinct metrics. The preprocessed CT scans are subjected to ResNet-50 model. The data samples used here comprises 130 instances recorded from several clinical sites that are publicly available on the LiTS weblink. The designed model upon deployment generates a promising outcome thereby obtaining a DSC of 0.97%. Thus, we can conclude that the developed model is capable enough to accurately assess liver tumours and thus help patients in early diagnosis. 2023 IEEE. -
Design and implementation of dual-leg generic converter for DC/AC grid integration
A newly designed generic photo-voltaic (PV) DC-DC/DC-AC converter is for direct current (DC) grid or single-phase alternating current (AC) grid integration. Main concept of the proposed converter is universal power conversion, and the same converter is used for DC-DC/DC-AC applications which also aiming for minimum redundancy because the proposed converter can be able to produce DC and AC output from the fixed/variable DC source. The proposed converter is designed with single-stage dual leg topology, with a designed filter, and protection circuits are connected in output/grid side. The proposed circuit is compared with existing topologies, and comparative analyses are made in both chopper (DC-DC) and inverter (DC-AC) modes for universal or generic operation. Real-time implementation of the proposed model is prepared for the power rating of 3.5 KW during inverter mode and 4 KW when same circuit working in chopper mode. Hardware results are obtained from the model from both chopper and inverter modes. Finally, correct applications, advantages, and future work are concluded in the last section. 2023 John Wiley & Sons Ltd. -
Design and Implementation of Low Complexity Multiplier-Less Reconfigurable Band Tuning Filter Structure with Sharp Sub-Bands
Digital flter banks are extensively used for communication purposes for channelization. Reconfgurable non-uniform multi-channels with sharp transition widths are necessary for channelization in digital channelizer and spectrum sensing in wireless communication networks. The aim of this research work is to design reconfgurable flter structures featuring non-uniform and sharp transition newlinewidth channels with reduced number of flter coeffcients. The four different flter structures are proposed in this research for achieving low complexity reconfgurable structure for the design of multiple non-uniform sharp transition width arbitrary bandwidth channels. The foundational newlineelement of this research is centered around the design of a prototype flter. This prototype flter serves as a basis for developing various reconfgurable flter structures. Leveraging the prototype newlineflter s bandwidth characteristics, these structures are categorized into two main groups: narrow band prototype flters and wide band prototype flters. The narrow band prototype flter category comprises structures capable of designing a single fnite impulse response flter with a narrow passband characterized by sharp transition widths. In contrast, the wide band prototype flter category includes structures capable of designing a single FIR flter with a wide passband also characterized by sharp transition widths. A novel flter structures are designed with the help of interpolated newlinefnite impulse response, cosine modulation technique, complex exponential modulation technique and frequency response masking techniques. The proposed method is evaluated using MATLAB R2019b, where the linear phase FIR flter coeffcients are computed based on the Parks-McClellan algorithm. The examples are employed to illustrate the effcient operation of the proposed designs. The results point to the fact that the proposed designs have less multiplier complexity than existing cuttingedge techniques. -
Design and Implementation of Machine Learning-Based Hybrid Model for Face Recognition System
Face recognition technologies must be able to recognize users faces in a chaotic environment. Facial detection is a different issue from facial recognition in that it requires reporting the position and size of every face in an image, whereas facial recognition does not allow for this. Due to their general similarity in look, the photographs of the same face have several alterations, which makes it a challenging challenge to solve. Face recognition is an extremely challenging process to do in an uncontrolled environment because the lighting, perspective, and quality of the image to be identified all have a significant impact on the process's output. The paper proposed a hybrid model for the face recognition using machine learning. Their performance is calculated on the basis of value derived for the FAR, FRR, TSR, ERR. At the same time their performance is compared with some existing machine learning model. It was found that the proposed hybrid model achieved the accuracy of almost 98%. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Design and Implementation of Smart Manufacturing Systems Through AR for Data-Driven Digital Twin System
Modification of size, residual stress, and surface roughness have an enormous impact on a complex mechanical products final machining quality. Machine quality can be ensured using Digital Twin (DT) technology by checking the real-time machining process. The virtualreal separation display method is the most modern DT System (DTS). It results in the ineffective transmission of the necessary restricting the use of the DTS by processing data on-site technicians to support field processing. Augmented Reality (AR) monitoring the manufacturing process approach to solve this problem is proposed based on the DT. First, the dynamic multi-view for AR is built using data from multiple sources. Second, real-time monitoring of complex products intermediate processes incorporates AR to encourage communication between the users of the DT machining system. The outcome of the system can prevent errors that cannot be fixed. An application case for observing will be used to confirm the viability and the efficacy of the proposed method. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Design and Optimization of Friction Stir Welding of Al-Cu BUTT Joint Configuration using Taguchi Method
Friction stir welding (FSW) is a solid-state welding technique in which the joint quality was predominantly subjected to heat formation throughout the metal welding process. The weld joint produced from FSW was better than the other fusion welding process. In this research, the base plates AA6101 and C11000 of 5 mm thickness were joined using the hardened oil-hardened non-shrinkable steel(OHNS) tool by the FSW method. The design of experiment (DOE) was used to optimize the input parameters such as tool rotational speed (rpm), feed rate (mm/min), and tool pin offset (mm) on output parameter ultimate tensile strength (UTS). The design of experiment (DOE) was carried out by employing a Taguchi L9 orthogonal array, three factors, and three levels for obtaining a quality joint with good strength. The results of nine trial runs from the Taguchi experimental approach were formulated and analyzed using the statistical tool analysis of variance (ANOVA) using MINITAB 19 software. ANOVA analysis was employed to find the contribution of the input parameters toward the output. The optimized input process parameters will help to create effective weld joints. This study revealed that tool pin offset towards softer metal at medium tool rotational speed would create joints with the highest UTS. Scanning Electron Microscope (SEM) was applied to investigate the structural changes in the FSW of Al-Cu joints. 2022, Books and Journals Private Ltd.. All rights reserved. -
Design and optimization of the process parameters for friction stir welding of dissimilar aluminium alloys
Friction Stir Welding (FSW) is one of the unique solid state welding technique that is fast gaining importance because of its ability to produce strong joints. The friction stir welding technique is effectively used in this research to join 5 mm thick dissimilar aluminium alloys of AA 7075-O and AA 5052-O grade. The effect of tool pin profile and tool rotational speed on the mechanical properties like micro-hardness and tensile strength are studied by the optimized Design of Experiments (DOE). The experiments are designed based on L16 orthogonal array considering TAGUCHI techniques for four design parameters and four parametric levels. The outcomes of experimental techniques are tabulated and TAGUCHI analysis, Analysis of Variance (ANOVA) are carried out in Minitab software. From the experimental results and statistical techniques, the methodology is validated and the outcomes of the experiments are found to be in close agreement with the statistical results with the error less than 5% of the mean difference value. The optimized process parameters for better micro hardness are as follows: tool rotational speed of 1200 rpm, feed of 120 mm/min, tool offset of 1 mm, and cylindrical tapered pin tool profile; while the optimized design of process parameters for better tensile strength are as follows: tool rotational speed of 1400 rpm, feed of 120 mm/min, tool offset of 1 mm and cylindrical tapered pin profile. The design and optimization of the process parameters for friction stir welding of dissimilar aluminium alloys is necessary for high strength weld joints. 2021, Paulus Editora. All rights reserved. -
Design and optimization of the process parameters for fusion deposition modelling by experimental and finite element approach
Fused Deposition Modelling (FDM) is a rapidly evolving technology since the last couple of years. This method is also used for rapid prototyping, which uses layer on top of layer deposition of the material using hot extruders to build a given 3D model. 3D printing technology basically a tool-less process designed specifically to avoid assembly requirements with intricate geometry and complex features created at no extra cost and at the same time it is an energy-efficient technology that can provide environmental efficiencies in terms of both the manufacturing process and material utilization. This research primarily focuses on analyzing the critical process parameters and its influence on the properties of the components made out of FDM process. The FDM specimens are fabricated by using four factors (parameters) at three levels, and the factors are layer thickness, travel speed of the extruder, infill ratio, and infill density. The experiments are designed based on Taguchi L-9 orthogonal array. Total three responses are considered and they are tensile strength compressive strength and flexural strength. Taguchi analysis has done to optimize the factors and its levels. Finite element analysis has also done and compared with the experimental results. 2022 Author(s). -
Design and optimization of three class object detection modalities for manufacturing steel surface fault diagnosis and dimensionality classification
The main objective of this research is to create and improve three different object identification techniques for identifying surface flaws and categorising dimensions in steel that has been fabricated. RetinaNet, YOLOv3, and Faster R-CNN are the selected modalities in the experiment. The main goal is to evaluate these modalities' ability to detect and classify defects on steel surfaces in terms of accuracy, precision, recall, and F1 score. This assessment makes use of a varied collection of steel surface photos that show different kinds and sizes of faults. Training, validation, and testing sets make up the dataset's partitioning. The training set is used to train and optimise the three modalities, while the testing and validation sets are used to evaluate their performance. According to the study's findings, all three methods provide excellent of 0.92. RetinaNet comes in second with an F1 score of 0.89, followed by YOLOv3 with an F1 score of 0.87, while the Faster R-CNN modality obtains the greatest overall performance with an F1 score. The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024. -
Design and performance analysis of braking system in an electric vehicle using adaptive neural networks
Research article emphasizes on the impact of braking concepts considering regenerative braking system and energy consumption aspects in electric vehicles through a new perspective. The electric vehicle system is modeled and simulated using the MATLAB/Simulink software. A dataset is developed using the virtual simulation environment created by co-simulation using the MATLAB/Simulink and the IPG Carmaker software. This dataset is also used in a neural network model based on adaptive neuro fuzzy logic and the system performance is analyzed. Parameters considered for training the neural network are the brake pedal displacement, braking change rate and the need for brake application. The highlight of this study is the focus on a front wheel driven electric vehicle, which uses a standard drive cycle input to validate the model. The significant parameters evaluated in this study include the braking effects, kinetic energy, regenerative braking torque, battery state of the charge and the motor torque. The torque generation and its intended braking force requirements based on the acceleration, deceleration and braking conditions are the notable observations. The regenerative capability of this proposed system design is also illustrated along with the surface plots based on the training dataset. Investigation and analysis reveal that, the battery state of charge could be revived throughout the drive with a steady and stable increase. Transitions of motor torques between tractive and regenerative phases are also illustrated and explained for clarity and brevity. 2023 Elsevier Ltd -
Design and performance analysis of eight channel demultiplexer using 2D photonic crystal with trapezium cavity
In this work, an eight-channel dense wavelength division multiplexing demultiplexer is designed with a 2D photonic crystal triangular lattice. The proposed demultiplexer consists of a centre bus waveguide, an isosceles trapezium resonant cavity, and an eight-circular ring cavity (CR1, CR2, CR3, CR4, CR5, CR6, CR7, and CR8). The point defect resonant cavity consists of seven rods to drop different wavelengths from eight cavities, each of eight drop waveguides. The design is very simple to realise. The finite difference time domain and plane wave expansion method methods were used to analyse the proposed designs band structure and transmission spectrum. The resonant wavelengths are 1.5441 ?m, 1.5443 ?m, 1.544 49 ?m, 1.5447 ?m, 1.5449 ?m, 1.5451 ?m, 1.5453 ?m, and 1.5455 ?m respectively. The proposed device provides a high-quality factor, transmission efficiency, and low crosstalk. The devices footprint is 490.0 ?m2, which can be easily incorporated into photonic integrated circuits. 2023 IOP Publishing Ltd. -
Design and performance evaluation of a multi-load and multi-source DC-DC converter for efficient electric vehicle power systems
This paper introduces the design and comprehensive performance evaluation of a novel Multi-Load and Multi-Source DC-DC converter tailored for electric vehicle (EV) power systems. The proposed converter integrates a primary battery power source with a secondary renewable energy sourcespecifically, solar energyto enhance overall energy efficiency and reliability in EV applications. Unlike conventional multi-port converters that often suffer from cross-regulation issues and limited scalability, this converter ensures stable power distribution to various EV subsystems, including the motor, air conditioning unit, audio systems, and lighting. A key feature of the design is its ability to independently manage multiple power loads while maintaining isolated outputs, thus eliminating the inductor current imbalance that is common in traditional systems. Experimental validation using a 100W prototype demonstrated the converters ability to deliver stable 24V and 48V outputs from a 12V input, with output voltage deviations kept within 1%, significantly improving upon the 5% deviations typically seen in existing converters. Furthermore, the system achieved an impressive 93% efficiency under variable load conditions. The modular nature of the converter makes it not only suitable for EV applications but also for a broader range of industries, including renewable energy systems and industrial power supplies. This paper concludes by discussing optimization strategies for future improvements and potential scaling of the technology for commercial use in sustainable energy applications. The Author(s) 2024. -
Design and Simulation of 6.2m Wide-Field Telescope for Spectroscopic Survey
The upcoming large astronomical telescopes are trending towards the Segmented Primary Mirror due to technological advancements & manufacturing feasibility. We have designed a wide-field optical IR spectroscopic survey telescope that can deliver spectra of several millions of astronomical sources. The baseline design of this telescope is a 6.2 m segmented primary mirror with hexagonal mirror segments of 1.44m size, intersegment Edge sensors, and soft positioning actuators. The telescope is designed to provide a 2.5deg FOV achieved through a system of wide field corrector lenses with a design residual ~0.2". Also, it delivers an f/3.61 beam suitable for directly feeding optical fibres. A mechanical concept of the telescope is designed with a truss-based mirror cell to support the segmented primary mirror and keep the deformation to a minimum. As the primary mirror is segmented, the deformation due to different disturbances like wind, vibration and thermal effects must be corrected to a nanometer accuracy to make it act like a monolithic primary mirror. This is achieved through an active control system using three actuators and six inter-segment edge sensors. A simulation tool, codeSMT, is built based on the state-space model of a soft actuator with Multiple-Input Multiple-Output (MIMO) capability to incorporate dynamic wind disturbance from the IAO Hanle site and vibration effects. A detailed error multiplier analysis is performed numerically using this tool and is in good agreement with analytical calculations. A parameter sensitivity analysis is performed to fine-tune the primary mirror control system variables. This paper presents the Optical, Mechanical and Active Control system design approach of a 6.2m wide-field telescope currently under conceptual design. 2024 SPIE. -
Design and Simulation of a Multi-purpose Adjustable Modular Robot for Precision Agriculture
Global population growth, climate change, and labor shortages all represent substantial obstacles to meeting global food needs, and agricultural robots provide a possible solution. This work uses a survey to evaluate user behavior toward using agricultural wheel robots on small farms. The survey was conducted in various parts of India (Coimbatore, Bhubaneswar, and Silchar), where 250 large and medium commercial farmers participated. After the survey, a new robotic system architecture is a multi-purpose, adjustable, modular, and affordable robotic platform designed for precision agriculture. A unique feature is added to the design, which helps the robot to adjust by itself based on the row distances and crop heights. The software was designed using the Fusion 360, and simulation is carried out in GAZEBO and Robot Operating System (ROS). 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.