Estimation Of Exergy Research Articles

Biomass chemical exergy estimation using novel intelligent tool: application to biorefinery sustainability

ABSTRACT In response to the growing importance of sustainable energy and environmental considerations in biorefinery technologies, this study introduces a novel hybrid artificial intelligence approach for predicting biomass chemical exergy. The proposed least-squares support vector machine method based on an imperialist competitive algorithm (ICA-LSSVM) combines composition and energy analysis methods to model the chemical energy of biomass accurately. Extensive data were collected to train the model, resulting in a high-precision prediction with a coefficient of determination (R2) of 0.999 and a root mean square error (RMSE) of 30.3. The main point of this study is the development of this accurate model to determine the chemical energy, and also different forms of comparison are used to prove this issue. The sensitivity analysis highlights the direct impact of carbon (C%), hydrogen (H%), and oxygen (O%) percentages on biomass chemical exergy, while nitrogen (N%) and sulfur (S%) exhibit an inverse relationship. The model outperforms existing correlations in the literature, emphasizing its accuracy and practicality for biomass chemical exergy prediction, and contributing to both laboratory and industrial applications. The study emphasizes the model’s real-data reliance and suggests further exploration with an expanded dataset for enhanced industrial applicability.

Specific chemical exergy prediction for biological molecules using hybrid models

In this study, hybrid models for specific chemical exergy prediction were proposed for pure organic compounds. The models were designed from the relation between the compounds standard molar chemical exergy and the reaction Gibbs energy and employing a dataset consisting in 178 pure organic compounds. The model performance was compared to available chemical exergy data from literature. Results indicate that chemical exergy for solid and liquid compounds can be estimated by a unified model with a correlation coefficient and average relative error of 99.41% and 2.30% respectively. Moreover, the model applicability was also evaluated for biological macromolecules chemical exergy estimation, comparing predicted values with those commonly used in biotechnological processes exergetic analysis. The obtained results shows that it is possible the use of a hybrid model to describe pure biomolecules and macromolecules chemical exergy.

Determination of chemical exergy for compounds of biotechnological interest using different estimation methodologies

Different methods of chemical exergy estimation for several organic compounds have been proposed in literature, mainly for those related to the petrochemical and energy industry. However, there is a lack of specific models for the estimation of different biomolecules chemical exergy. The present work aimed to evaluate the performance of two specific chemical exergy estimation methodologies for 42 compounds of biotechnological interest. The methodologies employed were the group contribution method (GC) and semi-empirical correlation. In addition, a methodology for the specific chemical exergy calculation of protein based on empirical information on the amino acid content was proposed. According to the results obtained by the methodologies studied, it was observed that the predicted chemical exergy values of the biomolecules considered were similar to the literature data, presenting an adjustment of R2 > 0.98. The property estimation GC-based method provided better statistical performance, with average absolute error and average relative error of 0.56 MJ kg−1 and 4.21%, respectively.

Comparison of single and double stage regenerative organic rankine cycle for medium grade heat source through energy and exergy estimation

Regenerative organic Rankine cycle (RORC) can be used to improve organic Rankine cycle (ORC) performance. This paper presents a comparison of a single (SSRORC) and double stage regenerative organic Rankine cycle (DSRORC) using a medium grade heat source. Performance for each system is estimated using the law of thermodynamics I and II through energy and exergy balance. Solar thermal is used as the heat source using therminol 55 as a working fluid, and R141b is used as the organic working fluid. The initial data for the analysis are heat source with 200°C of temperature, and 100 L/min of volume flow rate. Analysis begins by calculating energy input to determine organic working fluid mass flow rate, and continued by calculating energy loss, turbine power and pump power consumption to determine net power output and thermal efficiency. Exergy analysis begins by calculating exergy input to determine exergy efficiency. Exergy loss, exergy destruction at the turbine, pump and feed heater is calculated to complete the calculation. Energy estimation result shows that DSRORC determines better net power output and thermal efficiency for 7.9% than SSRORC, as well as exergy estimation, DSRORC determines higher exergy efficiency for 7.69%. ©2019. CBIORE-IJRED. All rights reserved

Cost optimisation of AC-R134a and AC-diethyl ether pair vapour adsorption refrigeration systems

ABSTRACTThe thermoeconomic analysis comprises three major divisions, namely the estimation of exergy of all internal and external streams of VAR system, the estimation of investment and fuel cost and estimation cost rates of streams and the cost of product. The results obtained in the above individual divisions are explained in this paper. Finally, the cost of the product of both working pairs is estimated and compared. The results obtained in each stage of the total research are presented.

Evolving new group contribution-LSSVM model to estimate standard molar chemical exergy of pure organic substances

ABSTRACTChemical exergy values of pure organic compounds are required in order to perform an exergy analysis to achieve the optimum conditions. Development of reliable predictive tools for standard molar chemical exergy estimation, is of great importance. A least squares support vector machine (LSSVM) based group contribution (GC) method is proposed for standard molar chemical exergy prediction of pure organic compounds. The proposed model is trained and evaluated based on a comprehensive data base comprising standard molar chemical exergy for 133 organic compounds. 47 chemical substructures are employed in the process of model development. The proposed model is evaluated using different graphical and statistical error analysis. Determination coefficient (R2) and average absolute relative deviation (AARD%) values of 1.00 and 0.56% indicate the applicability potential and reliability of the predictions from the proposed model.

Exergy analysis of intercooled reheat combined cycle with ammonia water mixture based bottoming cycle

The present paper deals with exergy analysis of a combined cycle with ammonia water mixture as the working fluid in the bottoming cycle. The effect of varying ammonia mass fraction on the thermodynamic performance of various elements of the considered combined cycle configuration is studied. The analysis reveals that as the ammonia mass fraction increases, the availability increases in low pressure gas turbine of the topping cycle, reheater, heat recovery vapor generator (HRVG), low pressure turbine, and decreases in economizer, refrigerant heat exchanger and absorber. Results obtained are useful as the exergy estimation indicates that amongst all thermodynamic elements in the considered combined cycle, the maximum availability is destroyed in HRVG followed by low pressure gas turbine which is good input for designers to improve HRVG.

Exergy analysis of the process of regeneration of spent sulphuric acid by WSA technology

A process of production of sulphuric acid by the WSA technology was examined using design data from the Haldor TOPSOE Co., published in the literature. The survey of the literature showed that an exergy estimation of the process of sulphuric acid regeneration by the WSA technology has not been made so far. The aim of the present study is to estimate the exergy efficiency of the process of sulphuric acid production by the WSA technology and compare it to the existing ones. The exergy losses were determined and analysed, as well as the overall exergy efficiency of the process. The total exergy losses were high -3387.36 MJ/t. The external losses were 25.75%, internal ones а -74.25%. The exergy efficiency was found to be 52.4%. The exergy analysis made is of practical importance and can be used by the sulphuric acid producers when choosing an efficient technology for the installation.

Energy and exergy estimation for a combined cycle of solid CO2 production and NH3-H2O single effect absorption chiller

In order to reduce the compression power, to use an integrated thermal-driven cycle, and to mitigate the CO2 content in the air, a new combined cycle of absorption chiller and vaporcompression refrigeration cycle to produce carbon dioxide dry ice was devised and analyzed. In this study, the energy and the exergy analyses of the combined cycle were presented. The combined cycle simulation was carried out by using EES (Engineering Equation Solver) program. The CO2 condensation pressure and the generator temperature were considered as key parameters. Results show that the total compression and pumping power using the present combined cycle can be reduced remarkably, amounting to 44.4 %, in comparison with that in the conventional ammonia cooling system. Most of the irreversibility occur in the absorption system and the irreversibility of the absorber has the largest portion. The temperature reduction of the solution or increase in the cooling water temperature can improve the irreversibility of the absorber. However, the latter decreases the irreversibility more than the former.

Estimating Petroleum Exergy Production and Consumption Using a Simulated Annealing Approach

This study deals with the development of the petroleum exergy production and consumption relations in order to better analyze exergy values and predict the future projections using the simulated annealing (SA) approach, which is a powerful technique used to solve many optimization problems. The exergy estimation is performed based on the indicators of gross domestic product (GDP) and the percentage of vehicle ownership figures in Turkey, which is given as an illustrative example. The so-called SA exergy production and consumption (SAPEX) model is developed, while the exergy values obtained using the SAPEX model are also compared with those using the genetic algorithm (GA) approach. It is determined that the SAPEX model developed predicts the exergy values better than the GA model. It may be concluded that the models proposed here can be used as an alternative solution and estimation technique to available estimation techniques in predicting the future energy and exergy utilization values of countries. This study is also expected to give a new direction to engineers, scientists, and policy makers in implementing energy planning studies and in dictating the energy strategies as a potential tool.

Estimating Energy and Exergy Production and Consumption Values Using Three Different Genetic Algorithm Approaches. Part 1: Model Development

The present study, consisting of two parts, proposes new models for estimating energy and exergy production and consumption values using the genetic algorithm approach. Part 1 of this study deals with the model development, while the application and testing with various scenarios will be treated in Part 2. In this regard, the genetic algorithm energy (GAEN) and genetic algorithm exergy (GAEX) estimating models have been proposed. During the energy and exergy estimation, independent variables are the GDP, population, and the ratio of export to import. The three forms of the GAEN and GAEX are developed, of which one is linear, second is exponential and the third is a mix of the exponential and linear form of the equations. Among them, the best fit models in terms of average relative errors and for the testing period are selected for future estimation and proposed both for GAEN and GAEX. It may be concluded that the models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques.

Three different genetic algorithm approaches to the estimation of residential exergy input/output values

This study develops residential exergy input/output estimation equations in order to better analyze exergy values and predict the future projections using genetic algorithm (GA) notion. GA EXnergy Input/Output Estimation Model (GAEXIEM/GAEXOEM) is used to estimate the future residential exergy input/output values based on the indicators of gross domestic product, population, import, export, house production, cement production and basic house appliances consumption. The model is applied to Turkey's residential sector, of which exergy input and output values were 861.06 and 77.32 PJ in 2002, respectively. The three different estimation models are proposed in quadratic forms. Developed models are validated with actual data, while future estimation of exergy values is projected for the years between 2003 and 2023. It may be concluded that all the models developed seem to be capable of predicting the residential–commercial exergy input/output values of Turkey as well as countries. This study is also expected to give a new direction to engineers, scientists, and policy makers in implementing energy planning studies and in dictating the energy strategies as a potential tool.

Ecosystem maturity — towards quantification

An attempt is made to rank 41 steady-state models of aquatic ecosystems on the basis of their maturity. Maturity is quantified using several of Odum's attributes of ecosystem maturity. It is shown that it is possible to make such a ranking, and that the ranking seems to confirm our intuitive perception of ecosystem maturity. The ranking is compared to rankings based on various ecosystem goal functions. The maturity ranking shows a strong negative correlation with relative ascendency, and thus a strong positive correlation with system overhead, a possible measure of ecosystem stability. The analyses suggest that another goal function, exergy, as calculated here is mainly a function of system biomass, and that it might be appropriate to reconsider the computational aspect of exergy estimation. Most importantly the analyses point to the feasibility of using comparisons of ecosystem models as a tool for enhancing our understanding of ecosystem characteristics, notably sustainability.