Multi-Objective Optimization of Braun-Type Exothermic Reactor for Ammonia Synthesis

The exothermic reactor for ammonia synthesis is a primary device determining the performance of the energy storage system. The Braun-type ammonia synthesis reactor is used as the exothermic reactor to improve the heat release rate. Due to the entirely different usage scenarios and design objectives, its parameters need to be redesigned and optimized. Based on finite-time thermodynamics, a one-dimensional model is established to analyze the effects of inlet gas molar flow rate, hydrogen–nitrogen ratio, reactor length and inlet temperature on the total entropy generation rate and the total exothermic rate of the reactor. It’s found that the total exothermic rate mainly depends on the inlet molar flow rate. Furthermore, considering the minimum total entropy generation rate and maximum total exothermic rate, the NSGA-II algorithm is applied to optimize seven reactor parameters including the inlet molar flow rate, lengths and temperatures of the three reactors. Lastly, the optimized reactor is obtained from the Pareto front using three fuzzy decision methods and deviation index. Compared with the reference reactor, the total exothermic rate of the optimized reactor is improved by 12.6% while the total entropy generation rate is reduced by 3.4%. The results in this paper can provide some guidance for the optimal design and application of exothermic reactors in practical engineering.

Development of the Concept of Entropy: A Simpler Alternative to Carnot Cycle

The relationship between entropy and reversible heat and temperature is developed using a simple cycle, in which an ideal gas is subjected to isothermal expansion and compression and heated and cooled between states. The procedure is easily understood by students if they have knowledge of calculations involving internal energy, reversible work, and heat capacity for an ideal gas. This approach avoids the more time-consuming Carnot cycle. The treatment described here illustrates how the total entropy change resulting from an irreversible process is always positive.

Double-Layer Micro Porous Media Burner from Lean to Rich Fuel Mixture: Analysis of Entropy Generation and Exergy Efficiency

Porous media burner (PMB) is widely used in a variety of practical systems, including heat exchangers, gas propulsion, reactors, and radiant burner combustion. However, thorough evaluations of the performance of the PMB based on the usefulness of entropy generation, thermal and exergy efficiency aspects are still lacking. In this work, the concept of a double-layer micro PMB with a 23 mm cylindrical shape burner was experimentally demonstrated. The PMB was constructed based on the utilization of premixed butane-air combustion which consists of an alumina and porcelain foam. The tests were designed to cover lean to rich combustion with equivalence ratios ranging from ϕ = 0.6 to ϕ = 1.2. It was found that the maximum thermal and exergy efficiency was obtained at ϕ = 1.2 while the lowest thermal and exergy efficiency was found at ϕ = 0.8. Furthermore, the findings also indicated that the total entropy generation, energy loss, and exergy destroyed yield the lowest values at ϕ = 1.0 with 0.0048 W/K, 98.084 W, and 1.456 W, respectively. These values can be stated to be the suitable operating conditions of the PMB. The findings provided useful information on the design and operation in a double-layer PMB.

Effects of non-uniform nanoparticle concentration on entropy generation

The entropy generation analysis of a thermal process is capable of determining the efficiency of that process and is therefore helpful to optimize the thermal system operating under various conditions. There are several ingredients upon which the phenomenon of entropy generation can depend, such as the nature of flow and the fluid, the assumed conditions, and the material properties of the working fluid. However, the dependence of entropy generation phenomenon upon such properties has so far not been fully realized, in view of the existing literature. On the other hand, based upon the existing studies, it has been established that the non-uniform concentration of nanoparticles in the base fluid does cause to enhance the heat transfer rate. Therefore, it is logical to investigate the entropy production under the impact of non-homogenous distribution of nanoparticles. Based upon this fact the aim of current study is to explore a comprehensive detail about the influence of non-homogeneous nanoparticles concentration on entropy production phenomenon by considering a laminar viscous flow past a moving continuous flat plate. Non-uniform concentration is considered in the nanofluid modeling in which the Brownian and thermophoretic diffusions are considered which impart significant effects on velocity and temperature profiles. An exact self-similar solution to this problem is observed to be possible and is reported. The effects of various controlling physical parameters such as Brinkman number, Schmidt number, Prandtl number, diffusion parameter, and concentration parameter on both local as well as total entropy generation number and Bejan number are elaborated by several graphs and Tables. The obtained results reveal a significant impact of all aforementioned parameters on entropy generation characteristics. It is observed that by a 20% increase in nanoparticles concentration the total entropy generation is increased up to 67% for a set of fixed values of remaining parameters.

Multiple-relaxation-time lattice Boltzmann simulation of free convection and irreversibility of nanofluid with variable thermophysical properties

This numerical study demonstrates heat transfer and irreversibility or entropy generation of non-Newtonian power-law Al2O3-H2O (aluminum oxide-water) nanofluids in a square enclosure using multiple-relaxation-time lattice Boltzmann method accelerated by graphics processing unit computing. In this investigation, the effective thermal conductivity and viscosity are variables, and they depend on the fluid temperature and rate of strain, respectively. The enclosure’s left and right walls are uniformly heated with different temperatures, and the upper and lower walls are thermally adiabatic. There is no valid study and results on non-Newtonian fluid using multiple-relaxation-time lattice Boltzmann method for this configuration and hence the novelty of the present results have been ensured. This paper has formulated and appropriately validated the Newtonian and non-Newtonian natural convection problem with the available numerical results. This study includes a set of comprehensive simulations, showing the effects of these fluids’ natural convection by varying three key parameters: the Rayleigh number, the volume fraction of nanoparticles, and the power-law index on the streamlines, isotherms, local and average Nusselt number as well as the local and total entropy generation. The results show that increasing the volume fraction of the nanoparticles from 0% to 2%, the average rate of heat transfer and the total entropy generation increase 6.5% and 7.4%, respectively, while the Rayleigh number, Ra = 105 and the power-law index n = 0.6.

Entropy-based Optimization for Heat Transfer Enhancement in Tubes with Helical Fins

In this work, a tube with internal helical fins is analyzed and optimized from an entropy generation point of view. Helical fins, in addition to providing heat transfer enhancements, have the potential to level the temperature of the tube under non-uniform circumferential heating. The geometric parameters of helical fins are optimized under two different entropy-based formulations. Specifically, this work focuses on comparing the optimal design solution obtained through the minimization of total entropy and through the multiobjective optimization of the thermal and viscous entropy contributions when considered as two separate objectives. The latter quantities being associated with heat transfer and pressure drops, it is shown that, from a design optimization point of view, it is important to separate both entropies which are conflicting objectives.

Entropy generation and heat transport of Cu–water nanoliquid in porous lid-driven cavity through magnetic field

Purpose The purpose of this paper is to investigate the effects of Ha and the Nanoparticles (NP) volume fraction over the irreversibility and heat transport in Darcy–Forchheimer nanofluid saturated lid-driven porous medium. Design/methodology/approach The present paper highlights entropy generation because of mixed convection for a lid-driven porous enclosure filled through a nanoliquid and submitted to a uniform magnetic field. The analysis is achieved using Darcy–Brinkman–Forchheimer technique. The set of partial differential equations governing the considered system was numerically solved using the finite element method. Findings The main observations are as follows. The results indicate that the movement of horizontal wall is an important factor for the entropy generation inside the porous cavity filled through Cu–water nanoliquid. The variation of the thermal entropy generation is linear through NPs volume fraction. The total entropy generation reduces when the Darcy, Hartmann and the nanoparticle volume fraction increase. The porous media and magnetic field effects reduce the total entropy generation. Practical implications Interest in studying thermal interactions by convective flow within a saturating porous medium has many fundamental considerations and has received extensive consideration in the literature because of its usefulness in a large variety of engineering applications, such as the energy storage and solar collectors, crystal growth, food processing, nuclear reactors and cooling of electronic devices, etc. Originality/value By examining the literature, the authors found that little attention has been paid to entropy generation encountered during convection of nanofluids. Hence, this work aims to numerically study entropy generation and heat transport in a lid-driven porous enclosure filled with a nanoliquid.

Electric Vehicles That Extract Heat from the Air Without Charging: Entropy Law Does Not Prohibit This

Electromobiles protect the biosphere in places of human residence. Globally, they destroy it, as the electrical energy they consumed is extracted using "dirty" energy carriers. This article suggests learning the electromobiles to generate electrical energy in eco-friendly way, extracting heat from the air. Specifically, we suggest to equip the electromobiles with the Or lov and etc. installation, which schematically is a converging tube where the air flow is by itself accelerated and, according to the Bernoulli equation, is cooled; and its narrow end contains the electrical energy generating turbine. The problem is that the Orlovand etc. installation is prohibited by the entropy increase law due to the flow entropy decrease during its operation. However, it is important that actually in this case the Clausius entropy, i.e. thermal entropy, decreases. The thermal and total entropy increase laws are different laws that separately require verification. Planck, Fermi et al. indicatedthe cases of total conversion of heat into other forms of energy accompanied by thermal en- tropy decrease. These cases, proving invalidity of the thermal entropy increase law, admit transition to electromobiles with air heat trac- tion. As well as transition of water transport to ship's electric engines with water heat traction.

Quantifying Causal Contributions in Earth Systems by Normalized Information Flow

To understand the plethora of important processes that are characterized by their complexity, from global pandemics to global climate change, it may be critical to quantify causal contributions between time series variables. Here, we examine an empirical linear relationship between the rate of changing causes and effects with various multipliers. Sign corrected normalized information flow (nIFc) tends to provide the best estimates of causal contributions, often in situations where such causality is poorly reflected by regressions. These include: i) causal contributions with alternating feedback (correlation) sign, ii) significant causal time-lags, iii) significant noise contributions, and iv) comparison among many causes to an overall mean effect, especially with teleconnection. Estimates of methane-climate feedbacks with both observational and Earth system model CESM2 data are given as examples of nonlinear process quantification and model assessment. The relative causal contribution is hypothesized to be proportional to |nIF|, i.e. the ratio between entropy (degree of uncertainty) received from the cause-variable (i.e. information flow, |IF|) and the total entropy change of the effect-variable. Large entropy, associated with noise, deteriorates the estimates of total entropy change, and hence nIF, while the proportional relationship between the relative causal contribution and IF improves.

Optimizing Walktrap’s Community Detection in Networks Using the Total Entropy Fit Index

*Exploratory graph analysis* (EGA) is used to estimate the structural organization of variables, uncovering latent dimensions as clusters of nodes. EGA first estimates a weighted network then uses the Walktrap algorithm to detect clusters of nodes. The Walktrap algorithm uses random walks to estimate the topography of a graph. The number of random walks taken (*t*) is typically set statically. However, the impact of *t* and the properties determining its optimization have yet to be fully researched. The present study proposes and tests a new approach optimizing *t* by iteratively varying *t* and employ *total entropy fit index* as a fit index to identify the number of steps that best fit the data using a Monte-Carlo simulation varying data structure characteristics. Results indicate that the proposed method is most effective for a higher number of variables per factor and when variables are polytomous. Varying *t* is important as spurious connections are introduced between communities. An empirical example using the Developmental Coordination Disorder Questionnaire is shown demonstrating improved measure interpretation by optimizing the Walktrap algorithm. The paper finishes with a discussion about the relevance of the findings and future directions for research.