Daily Archives: November 2, 2026

Authors: Sanjeeva Kumar Vudi, Vidhya K

Abstract: Current high-temperature industrial systems still rely largely on fossil fuels, with hydrogen identified as a key vector for their decarbonization. In this paper, a methodology is developed for the development of an EMS based on hydrogen use in industry, namely in glass and ammonia manufacturing. The EMS will involve the use of renewable electricity, electrolysis for hydrogen generation, its storage, and fuel switching between natural gas and hydrogen in order to minimize the expenses and meet the restrictions related to load of furnaces and emission limits. Model Predictive Control is chosen as the EMS architecture with use of day-ahead forecasts of renewable power generation, electricity price and gas price. The proposed methodology includes the design of the system architecture, mathematical problem statement and constraints. Simulation experiments have shown that introduction of hydrogen improves the economics and increases the share of renewables. Comparison with the systems working only with fossil fuels has confirmed the potential of the proposed approach.

DOI: https://doi.org/10.5281/zenodo.23888249

Published by: vikaspatanker

Authors: Associate Professor Ms. Suja Mary George, Assistant Professor Dr. Babu.P

Abstract: Research on recovery is dominated by samples drawn from elite and collegiate populations, although the majority of individuals who participate in organised sport do so at the community level. This review synthesises published systematic reviews and meta-analyses, chiefly from 2018 to 2026, concerning post-exercise recovery and long-term training adaptation, and evaluates which strategies are appropriate for grassroots athletes. This is a narrative, umbrella-style synthesis: the reported statistics were extracted and plotted, and no raw data were pooled. Cold-water immersion (CWI) reduced soreness (Hedges g = −0.40, 95% CI −0.64 to −0.16) and creatine kinase (g = −0.24, −0.37 to −0.10), yet it did not restore strength. Repeated CWI following resistance training was associated with smaller gains in strength and hypertrophy. Protein supplementation contributed approximately 0.30 kg of fat-free mass and 2.49 kg of one-repetition-maximum strength, with no additional fat-free-mass benefit above a total intake of roughly 1.6 g/kg/day. Training guided by heart-rate variability improved submaximal markers (g = 0.296) but not performance (g = 0.079, not significant). The acute:chronic workload ratio was associated with injury, although its lowest-incidence band (0.8–1.3) carried a 95% interval of 14–94%. Surveys indicated that approximately two thirds of sub-elite athletes slept poorly (65%, PSQI ≥ 5). A five-tier framework is proposed: protect sleep, secure adequate protein, progress load gradually with simple monitoring, use low-cost physical recovery, and ration CWI to tournaments and endurance blocks. Direct trials in grassroots populations remain scarce, and these conclusions are therefore provisional.

DOI: https://doi.org/10.5281/zenodo.23883538

Published by: vikaspatanker

Authors: Patil Saurabh Dnyaneshwar, Shelke Sanskar Ramesh, Sukhadeve Nitesh Suryabhan, Prof. M. S. Nalawade, Dr. V. M. Dhede

Abstract: A sustainable electricity system must supply growing demand with an increasing share of solar, wind and hydro generation whose output cannot be scheduled at will. Balancing such a system depends less on adjusting a few large power plants and more on managing energy intelligently across millions of consumers, storage units and distributed generators. This review focuses on the demand side and the information layer of the smart grid. It examines advanced metering infrastructure, which provides two-way communication between utilities and consumers; demand response and demand-side management, which shift or reduce consumption in response to prices or signals; energy storage and electric vehicles, which absorb surplus renewable energy and release it when needed; and forecasting of load and renewable generation using statistical and machine-learning models. Representative studies on each topic are compared. A layered architecture for an intelligent energy management system is presented in which consumer devices, smart meters, communication networks, an energy management platform and utility services cooperate to minimise cost, losses and emissions while maintaining reliability. Communication requirements, cyber security, privacy and consumer participation are discussed as challenges, and directions such as reinforcement-learning-based demand response and local energy markets are identified.

DOI: https://doi.org/10.5281/zenodo.23883414

Published by: vikaspatanker

Authors: Bhalerao Atharv Ashok, Gunjal Ayush Santosh, Gaikwad Darshan Dattatray, Prof. P. S. Dumbre, Prof. M. S. Nalawade5, Dr. V. M. Dhede

Abstract: IoT-based embedded systems integrate sensors, microcontrollers, communication networks and software platforms to connect physical devices with digital applications. They sense the environment, process the readings locally, and transmit useful data to a monitoring platform; depending on the application, the controller can also drive an actuator automatically or act on a remote user command. This paper surveys the literature on such systems under six headings: IoT foundations and reference architectures, low-cost Wi-Fi/Bluetooth microcontrollers such as the ESP32, wireless and messaging protocols, cloud and edge platforms, application domains (smart homes, agriculture, healthcare, industry and environmental monitoring), and security. Twenty-two peer-reviewed works are compared in a summary table. The survey finds that low-cost hardware and lightweight protocols such as MQTT have made monitoring-and-control systems easy to build, but that power consumption, sensor calibration, reliable connectivity and device security remain weak points in most reported prototypes. Based on these gaps, a general ESP32-based monitoring-and-control system is proposed, with local threshold-based automation, MQTT/HTTP data transfer to a cloud dashboard, and design rules for reliability, low power and secure communication.

DOI: https://doi.org/10.5281/zenodo.23883151

Published by: vikaspatanker

Authors: Kale Mayuri Sandip, Mule Mansi Dinesh, Konde Pratiksha Satyawan, Prof. D. S. Bhor, Dr. V. M. Dhede

Abstract: Engineering materials accumulate small cracks during service, and these cracks grow until a component must be repaired or replaced. Self-healing materials are designed to repair such damage on their own, or with only a mild external stimulus, in a way inspired by the healing of wounds in living organisms. This review explains the principles behind self-healing and classifies the approaches into extrinsic systems, in which a healing agent is stored in microcapsules, hollow fibres or vascular channels, and intrinsic systems, in which the material itself contains reversible chemical or physical bonds that re-form after fracture. Representative studies on polymers, composites, cement-based materials, coatings and electronic materials are reviewed and compared. A general functional architecture is presented that describes a self-healing system as a sequence of damage, triggering, transport of healing material, repair reaction and property recovery, and the healing efficiency used to measure performance is defined. Applications in civil engineering, aerospace, automotive, coatings, electronics and biomedical devices are discussed. The review also examines current limitations, such as high cost, a limited number of healing cycles and difficulty in repairing large damage, and outlines directions for future research.

DOI: https://doi.org/10.5281/zenodo.23882829

Published by: vikaspatanker

Authors: Yogesh Machhindra Dhomse, Samarth Shubash Dongre, Dhanraj Shinde, Prof. A. S. Bhor, Prof. M. S. Nalawade, Dr. V. M. Dhede

Abstract: Electric vehicles are replacing internal combustion vehicles in many markets, and power electronics is the technology that makes this transition possible. Every flow of energy in an electric vehicle, from the charging socket to the battery, from the battery to the traction motor, and from the high-voltage pack to the low-voltage accessories, passes through a power electronic converter. This review presents the major power electronic subsystems of a battery electric vehicle: the traction inverter that converts DC to variable-frequency AC, the bidirectional and auxiliary DC–DC converters, the onboard AC–DC charger and the off-board DC fast charger, together with the battery management system that supervises the pack. Motor control by pulse width modulation and field-oriented control is explained. The role of wide-bandgap semiconductors, silicon carbide and gallium nitride, in raising efficiency, switching frequency and power density is discussed and compared with silicon devices. Thermal management, electromagnetic compatibility and functional safety are reviewed as system-level design concerns. A complete power-flow architecture of an electric vehicle is presented, and representative studies are compared. Challenges and future directions, including 800 V architectures, extreme fast charging, integrated chargers and vehicle-to-grid operation, are identified.

DOI: https://doi.org/10.5281/zenodo.23882383

Published by: vikaspatanker

Authors: Patwari Kavyanjali Pramod, Kamble Akanksha Laxman, Sarjine Saniya Janardan, Prof. S. S. Lohote, Prof. M. S. Nalawade, Dr. V. M. Dhede

Abstract: Integrated circuits are now designed, fabricated, tested and packaged by many different organisations spread across the world. This distributed supply chain lowers cost but also creates opportunities for an untrusted party to insert malicious logic, copy intellectual property, overbuild chips, recycle used parts as new, or extract secret keys from a working device. Hardware security in VLSI studies these threats and the design techniques that defend against them. This review classifies the threats by the life-cycle stage at which they arise and by the asset they target, and then surveys the main families of countermeasures: hardware Trojan detection, logic locking and obfuscation, split manufacturing, physical unclonable functions, side-channel and fault-injection resistance, and secure boot built on a hardware root of trust. For each family the operating principle, representative studies and known weaknesses are discussed. A life-cycle security architecture is then presented that maps each protection to the stage of design, fabrication, test and field deployment where it applies. The comparison shows that no single technique secures a chip, and that defence in depth across the life cycle is required. Open problems such as attacks on logic locking, the reliability of PUF responses and the cost of security verification are identified as directions for further work.

DOI: https://doi.org/10.5281/zenodo.23857172

Published by: vikaspatanker

Authors: Bhor Aniket Madhav, Boddawar Kunal Chandrakant, Walke Yashraj Dinkar, Prof. S. L. Rahane, Prof. M. S. Nalawade, Dr. V. M. Dhede

Abstract: Cloud platforms deliver compute, storage and software as on-demand services, yet the data centres behind them draw large and continuous amounts of electricity for servers, network fabrics and cooling plants. Green cloud computing is the body of techniques that lowers this energy and carbon footprint without breaking the service-level commitments made to users. This survey organises the field into four layers of intervention: efficient hardware and facility design, virtualization with dynamic consolidation of virtual machines, energy- and carbon-aware scheduling of workloads, and integration of renewable supply. For each layer the paper explains the underlying principle, reviews representative studies, and compares their objectives, metrics and limitations. Building on this review, a layered conceptual framework is described in which a monitoring module gathers utilization, power and grid-carbon signals, a prediction module estimates near-term demand, and a decision engine places and migrates workloads on the most suitable servers while idle hosts are switched to low-power states. Evaluation through simulation toolkits or a small private-cloud test bed is discussed together with metrics such as power usage effectiveness, energy per request and SLA violation rate. Open issues, including the energy cost of migration, accurate carbon accounting and the trade-off between consolidation and performance, are identified as directions for further study.

DOI: https://doi.org/10.5281/zenodo.23857172

Published by: vikaspatanker

Authors: Randive Abhijeet Santosh, Sadaphal Harshal Ravindra, Shinde Prashant Shantaram, Prof. S. E. Shinde, Prof. M. S. Nalawade, Dr. V. M. Dhede

Abstract: Artificial intelligence workloads are dominated by multiply-and-accumulate operations on very large weight matrices. In conventional processors these weights must be moved repeatedly between memory and the arithmetic units, and this data movement, rather than the arithmetic itself, consumes most of the energy and time. Memristor-based in-memory computing (IMC) addresses this limitation by performing computation inside the memory array. A memristor is a two-terminal resistive switching device whose conductance can be programmed and retained, so it can store a weight. When memristors are arranged in a crossbar, Ohm's law and Kirchhoff's current law cause the column currents to equal the product of an input voltage vector and the conductance matrix, so a complete vector–matrix multiplication is obtained in a single analog step. This review explains the memristor concept and its physical realisations, the working principle of crossbar arrays, and the peripheral circuits and system architecture needed to build an accelerator. Representative device-level and system-level studies are compared. The benefits for AI inference and training are assessed against non-idealities such as device variability, limited precision, conductance drift, wire resistance and the cost of analog-to-digital conversion. Applications and research directions are identified.

DOI: https://doi.org/10.5281/zenodo.23881928

Published by: vikaspatanker

Authors: Chavan Prathmesh Sambhaji, Dhakne Vaibhav Balasaheb, Giram Devandra Rajandra, Prof. S. D. Chougule, Prof. M. S. Nalawade, Dr. V. M. Dhede

Abstract: Electric fans are used for personal comfort and for cooling equipment such as power supplies, boilers, incubators and ovens. A fan that always runs at full speed wastes energy and produces unnecessary noise, while manual speed selection depends on the user noticing a change in temperature. Automatic fan speed control solves this by measuring temperature and adjusting fan speed continuously. This paper reviews the design of such controllers built around low-cost microcontrollers of the AVR family, such as the ATmega8, ATmega168 and ATmega328 used on Arduino boards. The review covers temperature sensing with the LM35 and alternative sensors, analog-to-digital conversion, pulse width modulation (PWM) drive through a transistor stage, display of set and measured values on a 16×2 LCD, and the power supply. Control strategies ranging from on–off and stepped control to proportional, PID and fuzzy logic control are explained and compared. A reference architecture and control flow are presented for a stand-alone controller using a 12 V, 2 A supply, together with design calculations. Applications in air-conditioning, water heaters, incubators and industrial process equipment, as well as limitations and possible improvements such as wireless monitoring, are discussed.

DOI: https://doi.org/10.5281/zenodo.23881620

Published by: vikaspatanker