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Energy Efficiency and Conservation Technologies
Published in Swapan Kumar Dutta, Jitendra Saxena, Binoy Krishna Choudhury, Energy Efficiency and Conservation in Metal Industries, 2023
Jitendra Saxena, Binoy Krishna Choudhury
Second Law of Thermodynamics: It is impossible for a heat engine to produce a network in a complete cycle if it exchanges heat only with bodies at a single fixed temperature (Kelvin-Planck statement). Also, it is impossible to construct a device which, operating in a cycle, will produce no effect other than the transfer of heat from a cooler to a hotter body (Clausius statement). Second Law thus limits the efficiency of conversion of heat energy into mechanical work, and also gives rise to the concept of entropy. Entropy is a measure of dis-orderliness. It increases with irreversibility. Two main causes of irreversibility in industrial systems, such as that of metal industries, are heat transfer through finite temperature difference and friction. Therefore, no practical system can be reversible, nor attain the theoretical limit of thermodynamic efficiency of reversible processes. Entropy may be considered as the amount of unavailable energy within a given system.
An Overview of System of Systems and Associated Emergent Behavior
Published in Larry B. Rainey, O. Thomas Holland, Emergent Behavior in System of Systems Engineering, 2022
Entropy (the Second Law of Thermodynamics) is typically considered a measure of heat but is rather more specifically a measure of disorder in a system and observes that closed systems progress to disorder over time. Fundamentally, entropy S is defined in terms of temperature T and heat Q by: ΔS=ΔQT
Energy Today
Published in Anco S. Blazev, Global Energy Market Trends, 2021
Any form of energy may be transformed into another form. For example, all types of potential energy could be converted into kinetic energy when the objects are given freedom to move to different position (as for example, when an object falls off a support). When energy is in a form other than thermal energy, it may be transformed with good or even perfect efficiency, to any other type of energy, including electricity or production of new particles of matter. With thermal energy, however, there are often limits to the efficiency of the conversion to other forms of energy, as described by the second law of thermodynamics.
Entropy-based artificial dissipation as a corrective mechanism for numerical stability in convective heat transfer
Published in Numerical Heat Transfer, Part B: Fundamentals, 2023
Peter U. Ogban, Greg F. Naterer
The design of thermofluid systems is governed by conservation laws of fluid motion and energy. The First Law of Thermodynamics characterizes the quantity of energy in a system, while the Second Law of Thermodynamics measures the quality of energy or its potential to do useful work. The Second Law provides a special insight into energy use and its optimization. This study focuses on a novel application of the Second Law for the prediction of thermal and viscous irreversibilities locally. It uses this prediction as a numerical error indicator and corrective mechanism. Entropy production computation can serve as a diagnostic tool for tracking energy losses (irreversibilities) in thermofluid systems. Designers of energy systems may use entropy-based loss tracking as a tool to identify irreversibilities in a system.
Entropy generation and mixed convection of CuO–water near an oblique stagnation point: modified Chebyshev wavelets approach
Published in Waves in Random and Complex Media, 2022
Tabinda Sajjad, Rizwan Ul Haq, Muhammad Usman
The second law of thermodynamics asserts that the state of entropy of the entire universe, as an isolated system, will always increase over time. ‘The process of heat transfer occurs in a specific direction from hotter region to colder region.’ Bejan and Kestin [36] were the first who discuss about entropy generation in fluids. Entropy is responsible for the loss of useful energy during the heat transfer process. It is important in application of any engineering model. Minimization of entropy can produce more economic models [37]. The production of system may increase by diminishing factors responsible for entropy generation [38]. Approximate entropy (ApEn) of blood pressure gives more clear results about higher and low risks of hypertensive crises [39]. Entropy analysis is used in facial electromyogram. It uses entropy change to discuss the tension and stress in human facial nerves. Entropy change could be considered as the composite measure in change in physiological behavior toward a stimulus or stressor [40]. Entropy of system increases when heat supply increases, e.g. entropy increases when solid is converted to liquid.
Intelligent computing through neural networks for entropy generation in MHD third-grade nanofluid under chemical reaction and viscous dissipation
Published in Waves in Random and Complex Media, 2022
Muhammad Asif Zahoor Raja, Rafia Tabassum, Essam Roshdy El-Zahar, Muhammad Shoaib, M. Ijaz Khan, M. Y. Malik, Sami Ullah Khan, Sumaira Qayyum
Entropy is a measurable physical attribute mostly linked with a condition or disorder, unpredictability, or uncertainty. It has many applications in biological systems, economics, sociology, meteorology, climate change, cosmology, and information systems, including telecommunications data transmission. Entropy has the effect of making specific processes irreversible. The second law of thermodynamics holds that the entropy of an isolated system left to spontaneous development cannot decrease with time because it always reaches a state of thermodynamic equilibrium, where the entropy is greatest. Using entropy optimisation, Alsaedi et al. [21] investigated the MHD TGNF flow by considering binary chemical reaction and activation energy past a stretching sheet. Hayat et al. [22] exemplified heat transmission in a mixed convective stream of carbon nanotubes with entropy generation subjected to a curved stretching surface. Under the influence of magnetic and electric fields, Khan et al. [23] explored EG in electro-magneto dynamical mixed convection flow. Nayak et al. [24] used EG to explore an MHD Hamilton’s Crosser flow by considering the Darcy-Forchheimer. The Jeffrey nanofluid stream under the effects of entropy generation was studied by Le et al. [25]. Using the Buongiorno model, Adnan et al. [26] evaluated the EG in a convective stream of hybrid nanofluid fluid using magnetic force impact. The EG was presented by Adnan et al. [27] in a nanofluid flow passing through convergent and divergent channels.