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The term "industrial waste" refers to energy created in industrial operations but not used. Today, the increasing demand and cost of energy, scarcity of energy resources, market competitiveness, and environmental conditions all necessitate the effective utilization of energy. In this context, the heating furnace has been optimized with a new heat exchanger which has a strong corrosion resistance to the corrosive effect of flue gas, and has been designed and developed with high heat transfer capacity. In order to ensure maximum efficiency, the combustion air is got heated with high temperature (850∼1000°C) furnace exhaust gas. Doing so the combustion air can be heated up to a temperature of 390°C. The modified furnace results in energy saving as well as reduces the emissions characteristics of flue gases. This also leads to high-quality and cost-effective production. [ABSTRACT FROM AUTHOR]

The mathematical foundation for this research study is based on classical beam theories. The equivalent Stiffness approach was used to do free vibration analysis on simply supported thin curved beams. A complete parametric investigation of the free vibration response of a hypothetical bimodular compoᵴite material laminated simply supported curved beam was reported. Bimodular composite laminated structures are more complex to analyse than unimodular materials. The motion equations are derived from Hamilton's energy equation and solved using a matrix technique. The fundamental purpose of this investigation will add to a better understanding of free vibration analyᵴis in simply supported bimodular compoᵴite laminated curved beams. [ABSTRACT FROM AUTHOR]

Considering the volume of thermal energy consumed by humans, every breakthrough in thermal energy management strategies can have a significant social impact. Thermal energy storage (TES) serves an important purpose in thermal energy management. Thermal energy storage is critical for balancing energy demand as well as supply, ensuring system stability, along with maximizing the potential of intermittent renewable energy sources. It may not only maximize the use of renewable energy and reduce the price of electricity at nighttime, but also give flexibility as well as auxiliary services for addressing future power supply/demand concerns. There is still a need for a clear and complete source of knowledge to provide related concepts as well as applications even if there are numerous good review materials in the literature covering diverse heat storage systems independently. Different TES types such as sensible, latent as well as sorption have been briefly detailed in this work in order to study their performance. Among these aspects is the design of the components, the material characteristics of the components, the optimization of the components, as well as the integration of the components in different forms from the component level to the system level. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive overview of recent developments in nanofluids, emphasizing their unique thermophysical characteristics and utilization in heat transfer. The discussion covers unification techniques, thermophysical properties, advantages, and disadvantages of nanofluids, focusing on hybrid nanofluids' superior thermal performance in heat exchangers. An experimental study explores the impact of ternary-doped magnetic nanoparticles on nanofluids, revealing enhanced thermal conductivity. The inadequacy of conventional fluids in industrial processes prompts the investigation of trihybrid nanofluids, with an analysis of entropy generation in electromagnetic trihybrid nanofluids. Furthermore, a photovoltaic thermal system's energy and exergy efficiency using different nanofluids are examined, demonstrating temperature reduction, increased electrical power, and improved efficiencies. In the realm of concentrated Solar Power technology, the study explores nanofluids' potential in addressing corrosion challenges in molten salts. Overall, this paper is a valuable reference for engineers and scientists interested in the diverse applications of nanofluids in heat tranᵴfer processes. [ABSTRACT FROM AUTHOR]

The emergence of Industry 4.0 leads to the latest technology, and blockchain is one of them. Blockchain guarantees transparency, decentralization and protection of a transaction. It revolutionizes industries where entrust and security have vital significance. In the blockchain network, data is recorded in the form of blocks. The first block of the blockchain network is acknowledged as Genesis-Block. The rest of the blocks are added to the blockchain in chronological order so that participants entities can keep an eye on digital transactions deprived of the interference of third parties or central authorities. Transactions on the blockchain network require a set of rules and regulations. These rules are known as consensus algorithms. The consensus algorithm is a procedure employed for common agreement, validation, verification, and confirmation of transactions in a blockchain network. Examples of popular consensus algorithms are Proof-of-Work (PoW), Proof-of-Burn (PoB), Proof-of- Stake (BoS), Directed-Acyclic-Graph (DAG), Practical-Byzantine-Fault-Tolerance (PBFT), Proof-of-Elapsed-Time (PoET), etc. Initially, the paper introduces the evolution and categorization of blockchain networks. Subsequently, a brief discussion on available consensus algorithms and the inclusion process of a node in blockchain networks. Furthermore, the paper compares existing blockchain consensus algorithms based on various significant parameters such as scalability, transaction rate, tolerated power, etc. [ABSTRACT FROM AUTHOR]

Tuberculosis is an infectious disease that spreads through the air when someone sneezes or coughs, and it mainly affects the lungs. It is a very common disease, prevailing mainly in undeveloped and developing nations. Inflammation of the lungs Tuberculosis can be diagnosed with the help of radiology by taking a chest X-ray of the patient and a sample of sputum to check whether bacteria (Mycobacterium) exist or not. The techniques of artificial intelligence can help in the diagnosis and fast predictions of tuberculosis. In this research paper, we analysed the dataset of tuberculosis patents by applying the classification models of machine learning. The accuracy of models will be compared by varying the training and testing datasets. The CPU execution time of the classification models is also calculated, to determine which model performs faster. [ABSTRACT FROM AUTHOR]