Abstract Two-phase flows in feed pipes of thermal separation columns have complex flow patterns and are difficult to predict during sizing and design for geometries with non-straight pipes. Numerical simulation codes have only been validated for very few pipe geometries. This work benchmarks the state-of-the-art Volume-of-Fluid model (VoF) and the Algebraic Interfacial Area Density model (AIAD) for the simulation of two-phase flows with the Eulerian/Eulerian CFD approach for straight pipes and horizontal bends as well as for different pipe diameters and flow rates. Both models are compared and shortcomings of the predicted velocity fields from AIAD in the vicinity of horizontal bends are highlighted. While phase dynamics, e.g., for wavy or disperse flows, are not well reproduced by either model, the phase distribution patterns in straight tubes and bends agree reasonably well with experimental data. Regardless of the geometry, better void fraction prediction is obtained for higher flow velocities and the larger pipe diameter. From the numerical results, recommendations for the selection of feed inlet devices are derived.
{"title":"Comparison of different CFD approaches for the simulation of developing free surface two-phase flow in straight and bent pipes","authors":"A. Döß, T. Höhne, M. Schubert, U. Hampel","doi":"10.1515/cppm-2023-0028","DOIUrl":"https://doi.org/10.1515/cppm-2023-0028","url":null,"abstract":"Abstract Two-phase flows in feed pipes of thermal separation columns have complex flow patterns and are difficult to predict during sizing and design for geometries with non-straight pipes. Numerical simulation codes have only been validated for very few pipe geometries. This work benchmarks the state-of-the-art Volume-of-Fluid model (VoF) and the Algebraic Interfacial Area Density model (AIAD) for the simulation of two-phase flows with the Eulerian/Eulerian CFD approach for straight pipes and horizontal bends as well as for different pipe diameters and flow rates. Both models are compared and shortcomings of the predicted velocity fields from AIAD in the vicinity of horizontal bends are highlighted. While phase dynamics, e.g., for wavy or disperse flows, are not well reproduced by either model, the phase distribution patterns in straight tubes and bends agree reasonably well with experimental data. Regardless of the geometry, better void fraction prediction is obtained for higher flow velocities and the larger pipe diameter. From the numerical results, recommendations for the selection of feed inlet devices are derived.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47198165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Siva, Sampath Kumar Puttapati, Ramya Araga, Shubhanshu Sharma, D. Patle, G. Uday Bhaskar Babu
Abstract Concerning global warming, an energy-efficient power source must produce low or no pollutant emissions and provide an unlimited fuel supply. Proton Exchange Membrane fuel cell (PEMFC) is an electrochemical device that transforms chemical energy into electrical energy. The performance and durability of PEM fuel cells are affected by voltage reversals and fuel starvation. Oxygen Excess Ratio (OER) is a crucial factor in controlling the fuel starvation of the PEMFC system. First, this work identified the PEMFC as an integer order and fractional-order first order plus time delay models using the predictor error method and Grunwald–Letnikov simulation method based on a trust-region-reflect algorithm, respectively. Fractional order models more accurately represented the PEM fuel cell system dynamics. Then, robust fractional filters cascaded with PID controllers based on the Internal Model Control scheme (IMC) are designed for identified integer and fractional order models to regulate the OER by compressor voltage manipulation. The genetic Algorithm (GA) optimization technique is used to find the optimal fractional filter tuning parameters. The proposed controller’s performance regarding Integral Absolute Error (IAE) and Total Variance (TV) is analyzed. Furthermore, the robustness of a perturbed plant and fragility with perturbed controllers are elucidated. The results show that a fractional filter cascaded with fractional order PID controller improves the performance compared to a fractional filter cascaded with integer order PID controllers.
{"title":"Oxygen excess ratio control of PEM fuel cell: fractional order modeling and fractional filter IMC-PID control","authors":"M. Siva, Sampath Kumar Puttapati, Ramya Araga, Shubhanshu Sharma, D. Patle, G. Uday Bhaskar Babu","doi":"10.1515/cppm-2022-0050","DOIUrl":"https://doi.org/10.1515/cppm-2022-0050","url":null,"abstract":"Abstract Concerning global warming, an energy-efficient power source must produce low or no pollutant emissions and provide an unlimited fuel supply. Proton Exchange Membrane fuel cell (PEMFC) is an electrochemical device that transforms chemical energy into electrical energy. The performance and durability of PEM fuel cells are affected by voltage reversals and fuel starvation. Oxygen Excess Ratio (OER) is a crucial factor in controlling the fuel starvation of the PEMFC system. First, this work identified the PEMFC as an integer order and fractional-order first order plus time delay models using the predictor error method and Grunwald–Letnikov simulation method based on a trust-region-reflect algorithm, respectively. Fractional order models more accurately represented the PEM fuel cell system dynamics. Then, robust fractional filters cascaded with PID controllers based on the Internal Model Control scheme (IMC) are designed for identified integer and fractional order models to regulate the OER by compressor voltage manipulation. The genetic Algorithm (GA) optimization technique is used to find the optimal fractional filter tuning parameters. The proposed controller’s performance regarding Integral Absolute Error (IAE) and Total Variance (TV) is analyzed. Furthermore, the robustness of a perturbed plant and fragility with perturbed controllers are elucidated. The results show that a fractional filter cascaded with fractional order PID controller improves the performance compared to a fractional filter cascaded with integer order PID controllers.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42654958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In this study, we investigate the thermal stabilities, thermo-kinetic, and thermodynamic behaviours of Corn Cob (CC), Husk (CH), Leaf (CL), and Stalk (CS) during pyrolysis using the Thermogravimetric Analysis (TGA) at a single heating rate of 10 °C/min. Thermo-kinetics and thermodynamic parameters were evaluated for two temperature regions, region I (100–350 °C) and region II (350–500 °C) by employing the Coats–Redfern (CR) integral method to fit the TGA data to sixteen kinetic models. Results showed that diffusion models (D1, D1, D3, and D1) best suited the decomposition of CC, CH, CL, and CS in region I with Ea values of 109.90, 186.01, 129.4, and 78.7 kJ/mol respectively. Similarly, D1, third order model (F3), D3, and nucleation model (P4) with Ea values of 68.50 (CC), 177.10 (CH), 62.10 (CL), and 127.70 (CS) kJ/mol respectively best described residues’ decomposition in region II. Furthermore, kinetic parameters were used to compute the thermodynamic parameters; change in enthalpy (∆H), Gibbs free energy (∆G), and change in entropy (∆S) values for both regions. To study the pyrolytic behaviours of the residues, Artificial Neural Network (ANN) was employed to develop models to predict weight losses in samples by determining the coefficient of determination (R 2) and minimum Mean Square Error (MSE). Results showed ANN as a very important tool for predicting the pyrolytic behaviours of corn residues and other biomass samples.
{"title":"Thermo-kinetics, thermodynamics, and ANN modeling of the pyrolytic behaviours of Corn Cob, Husk, Leaf, and Stalk using thermogravimetric analysis","authors":"Mubarak A. Amoloye, S. Abdulkareem, A. Adeniyi","doi":"10.1515/cppm-2023-0021","DOIUrl":"https://doi.org/10.1515/cppm-2023-0021","url":null,"abstract":"Abstract In this study, we investigate the thermal stabilities, thermo-kinetic, and thermodynamic behaviours of Corn Cob (CC), Husk (CH), Leaf (CL), and Stalk (CS) during pyrolysis using the Thermogravimetric Analysis (TGA) at a single heating rate of 10 °C/min. Thermo-kinetics and thermodynamic parameters were evaluated for two temperature regions, region I (100–350 °C) and region II (350–500 °C) by employing the Coats–Redfern (CR) integral method to fit the TGA data to sixteen kinetic models. Results showed that diffusion models (D1, D1, D3, and D1) best suited the decomposition of CC, CH, CL, and CS in region I with Ea values of 109.90, 186.01, 129.4, and 78.7 kJ/mol respectively. Similarly, D1, third order model (F3), D3, and nucleation model (P4) with Ea values of 68.50 (CC), 177.10 (CH), 62.10 (CL), and 127.70 (CS) kJ/mol respectively best described residues’ decomposition in region II. Furthermore, kinetic parameters were used to compute the thermodynamic parameters; change in enthalpy (∆H), Gibbs free energy (∆G), and change in entropy (∆S) values for both regions. To study the pyrolytic behaviours of the residues, Artificial Neural Network (ANN) was employed to develop models to predict weight losses in samples by determining the coefficient of determination (R 2) and minimum Mean Square Error (MSE). Results showed ANN as a very important tool for predicting the pyrolytic behaviours of corn residues and other biomass samples.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48368484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Hydrogels are possible materials that could be useful in medication delivery systems. Diverse release mechanisms are used when drug molecules embedded in the hydrogel structure need to be released. Both case I and case II of transport refer to the release of the medication during the intermolecular arrangement because of swelling. Numerous mathematical models have been proposed that only include one form of transport; nevertheless, both transport pathways are required for the entire release of a drug from a gel matrix. The case I transport during swelling and the case II transport during the fully swollen condition are both displayed by crosslinked hyaluronic acid hydrogel systems. The methodology put out in this paper enables for the selection of suitable gel compositions while attempting to account for both transit instances. In the Data Envelopment Analysis coupled with principal component analysis approaches are enable the optimization and selection of gel compositions that account for both transport situations.
{"title":"Optimization of hydrogel composition for effective release of drug","authors":"R. Pannala, Ujjwal Juyal, Jagadeeshwar Kodavaty","doi":"10.1515/cppm-2022-0062","DOIUrl":"https://doi.org/10.1515/cppm-2022-0062","url":null,"abstract":"Abstract Hydrogels are possible materials that could be useful in medication delivery systems. Diverse release mechanisms are used when drug molecules embedded in the hydrogel structure need to be released. Both case I and case II of transport refer to the release of the medication during the intermolecular arrangement because of swelling. Numerous mathematical models have been proposed that only include one form of transport; nevertheless, both transport pathways are required for the entire release of a drug from a gel matrix. The case I transport during swelling and the case II transport during the fully swollen condition are both displayed by crosslinked hyaluronic acid hydrogel systems. The methodology put out in this paper enables for the selection of suitable gel compositions while attempting to account for both transit instances. In the Data Envelopment Analysis coupled with principal component analysis approaches are enable the optimization and selection of gel compositions that account for both transport situations.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42697494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The present study performs a three-dimensional CFD analysis to investigate the hydrodynamic and thermal properties of annular finned tubes in a heat exchange system. All computations are performed in the turbulent flow regime (4330 ≤ Re ≤ 8790), and the Transition SST model is applied for turbulence modelling. The impact of Prandtl number (0.7 ≤ Pr ≤ 50) on the various parameters, such as the heat transfer coefficient, heat transfer rate, and pressure drop, are considered. The results indicate that the thermo-hydraulic behaviour is significantly affected by incrementing both Reynolds and Prandtl numbers. The fin’s surface temperature distribution is examined to get a better insight into its thermal performance, and it is observed that the rear portion of the fin contributes the least to heat transfer. Other important parameters like the fin efficiency and Colburn heat transfer factor are found to significantly impact the performance of the heat exchange system for the above range of settings. The velocity contours show the horseshoe vortex formation near the fin-tube junction, and the channelling effect is observed between consecutive tubes. Different fluids are compared based on the j/f factor for enhanced heat transfer at the minimum possible flow resistance.
{"title":"Three-dimensional CFD study on thermo-hydraulic behaviour of finned tubes in a heat exchange system for heat transfer enhancement","authors":"Mohit Raje, A. Dhiman","doi":"10.1515/cppm-2022-0064","DOIUrl":"https://doi.org/10.1515/cppm-2022-0064","url":null,"abstract":"Abstract The present study performs a three-dimensional CFD analysis to investigate the hydrodynamic and thermal properties of annular finned tubes in a heat exchange system. All computations are performed in the turbulent flow regime (4330 ≤ Re ≤ 8790), and the Transition SST model is applied for turbulence modelling. The impact of Prandtl number (0.7 ≤ Pr ≤ 50) on the various parameters, such as the heat transfer coefficient, heat transfer rate, and pressure drop, are considered. The results indicate that the thermo-hydraulic behaviour is significantly affected by incrementing both Reynolds and Prandtl numbers. The fin’s surface temperature distribution is examined to get a better insight into its thermal performance, and it is observed that the rear portion of the fin contributes the least to heat transfer. Other important parameters like the fin efficiency and Colburn heat transfer factor are found to significantly impact the performance of the heat exchange system for the above range of settings. The velocity contours show the horseshoe vortex formation near the fin-tube junction, and the channelling effect is observed between consecutive tubes. Different fluids are compared based on the j/f factor for enhanced heat transfer at the minimum possible flow resistance.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42119471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abdul Raize, P. Kumari, Somasekhara Goud Sontti, A. Atta
Abstract Bubble formation in a square microchannel having a converging shape merging junction has been studied using the Coupled Level-Set and Volume-of-Fluid (CLSVOF) method. The influence of variations in merging junction angles, fluid properties, and operating conditions on the bubble length and pressure drop has been analyzed. The results show a direct relationship between surface tension, gas-liquid flow ratio, and the inverse relation of continuous phase viscosity with the bubble length. Moreover, opposite variations of these parameters are observed for pressure drop. This work reveals a discerning influence of the angle variations of merging junction on the interplay between inertial, viscous, and surface tension forces in the bubble formation mechanism. We envisage that this numerical work will be of significant interest for the process intensification in various industries that deal with gas-liquid microfluidic systems.
{"title":"Insights into the bubble formation dynamics in converging shape microchannels using CLSVOF method","authors":"Abdul Raize, P. Kumari, Somasekhara Goud Sontti, A. Atta","doi":"10.1515/cppm-2023-0030","DOIUrl":"https://doi.org/10.1515/cppm-2023-0030","url":null,"abstract":"Abstract Bubble formation in a square microchannel having a converging shape merging junction has been studied using the Coupled Level-Set and Volume-of-Fluid (CLSVOF) method. The influence of variations in merging junction angles, fluid properties, and operating conditions on the bubble length and pressure drop has been analyzed. The results show a direct relationship between surface tension, gas-liquid flow ratio, and the inverse relation of continuous phase viscosity with the bubble length. Moreover, opposite variations of these parameters are observed for pressure drop. This work reveals a discerning influence of the angle variations of merging junction on the interplay between inertial, viscous, and surface tension forces in the bubble formation mechanism. We envisage that this numerical work will be of significant interest for the process intensification in various industries that deal with gas-liquid microfluidic systems.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45420194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In this paper, proportional-integral-derivative (PID) controllers are tuned for unstable first-order plus dead time (UFOPDT) systems. Genetic algorithm (GA) is used to find the parameters of the PID controller for UFOPDT systems under the constraint of robustness measure. By curve fitting, the controller parameters are expressed as the functions of the UFOPDT model parameters. Two tuning formulas which consider robustness and the tradeoff between disturbance rejection and robustness of the closed-loop system are proposed. The proposed tuning formulas extend the application range of the existing methods and simulation results show that the tuned PID controllers can achieve good performance for UFOPDT systems.
{"title":"Tuning of PID controllers for unstable first-order plus dead time systems","authors":"Jianyu Bi, W. Tan, Mei Yu","doi":"10.1515/cppm-2023-0027","DOIUrl":"https://doi.org/10.1515/cppm-2023-0027","url":null,"abstract":"Abstract In this paper, proportional-integral-derivative (PID) controllers are tuned for unstable first-order plus dead time (UFOPDT) systems. Genetic algorithm (GA) is used to find the parameters of the PID controller for UFOPDT systems under the constraint of robustness measure. By curve fitting, the controller parameters are expressed as the functions of the UFOPDT model parameters. Two tuning formulas which consider robustness and the tradeoff between disturbance rejection and robustness of the closed-loop system are proposed. The proposed tuning formulas extend the application range of the existing methods and simulation results show that the tuned PID controllers can achieve good performance for UFOPDT systems.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49304497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06eCollection Date: 2024-04-01DOI: 10.1515/cppm-2023-0026
Hossein Hassanzadeh, Saptarshi Joshi, Seyed Mohammad Taghavi
We study positively buoyant miscible jets through high-speed imaging and planar laser-induced fluorescence methods, and we rely on supervised machine learning techniques to predict jet characteristics. These include, in particular, predictions to the laminar length and spread angle, over a wide range of Reynolds and Archimedes numbers. To make these predictions, we use linear regression, support vector regression, random forests, K-nearest neighbour, and artificial neural network algorithms. We evaluate the performance of the aforementioned models using various standard metrics, finding that the random forest algorithm is the best for predicting our jet characteristics. We also discover that this algorithm outperforms a recent empirical correlation, resulting in a significant increase in accuracy, especially for predicting the laminar length.
{"title":"Predicting buoyant jet characteristics: a machine learning approach.","authors":"Hossein Hassanzadeh, Saptarshi Joshi, Seyed Mohammad Taghavi","doi":"10.1515/cppm-2023-0026","DOIUrl":"10.1515/cppm-2023-0026","url":null,"abstract":"<p><p>We study positively buoyant miscible jets through high-speed imaging and planar laser-induced fluorescence methods, and we rely on supervised machine learning techniques to predict jet characteristics. These include, in particular, predictions to the laminar length and spread angle, over a wide range of Reynolds and Archimedes numbers. To make these predictions, we use linear regression, support vector regression, random forests, K-nearest neighbour, and artificial neural network algorithms. We evaluate the performance of the aforementioned models using various standard metrics, finding that the random forest algorithm is the best for predicting our jet characteristics. We also discover that this algorithm outperforms a recent empirical correlation, resulting in a significant increase in accuracy, especially for predicting the laminar length.</p>","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11098531/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48780321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1515/cppm-2023-frontmatter3
{"title":"Frontmatter","authors":"","doi":"10.1515/cppm-2023-frontmatter3","DOIUrl":"https://doi.org/10.1515/cppm-2023-frontmatter3","url":null,"abstract":"","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136108101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jordan O’Callaghan, John Fitzpatrick, Fergal Lalor, E. Byrne
Abstract Despite steam sterilisation in autoclaves being a common industrial method of sterilisation, very little research has been conducted into quantifying the resources these processes demand and their associated environmental impacts. This paper aims to investigate industrial steam sterilisation in autoclaves with particular application to the biopharmaceutical industry. A mathematical model of a steam autoclave was developed to examine relationships between load size, load material properties and autoclave capacity with energy consumption, environmental impact and cost of sterilisation. The two main energy requirements are thermal energy to produce the clean steam for sterilising, and electrical energy for the vacuum pump. The study showed that thermal energy is dominant, particularly as load increases. The percentage of the maximum load at which the autoclave is operated has a major impact on the specific energy requirement or the energy required to sterilise per unit mass of load. For a given autoclave, the energy requirement increases with increased load but the specific energy requirement decreases. This in turn impacts on the emissions and the energy cost. It is thus shown that it is much more energy efficient to operate at higher loads, making the autoclave much more energy and cost effective, and with less environmental impact. There is potential for applying the analysis presented in this work for conducting optimisation studies for determining the sizes of autoclaves that could minimise the energy requirement, environmental impact and economic cost (3E) of investments for specified load versus time profiles.
{"title":"Investigating the energy, environmental, and economic challenges and opportunities associated with steam sterilisation autoclaves","authors":"Jordan O’Callaghan, John Fitzpatrick, Fergal Lalor, E. Byrne","doi":"10.1515/cppm-2022-0053","DOIUrl":"https://doi.org/10.1515/cppm-2022-0053","url":null,"abstract":"Abstract Despite steam sterilisation in autoclaves being a common industrial method of sterilisation, very little research has been conducted into quantifying the resources these processes demand and their associated environmental impacts. This paper aims to investigate industrial steam sterilisation in autoclaves with particular application to the biopharmaceutical industry. A mathematical model of a steam autoclave was developed to examine relationships between load size, load material properties and autoclave capacity with energy consumption, environmental impact and cost of sterilisation. The two main energy requirements are thermal energy to produce the clean steam for sterilising, and electrical energy for the vacuum pump. The study showed that thermal energy is dominant, particularly as load increases. The percentage of the maximum load at which the autoclave is operated has a major impact on the specific energy requirement or the energy required to sterilise per unit mass of load. For a given autoclave, the energy requirement increases with increased load but the specific energy requirement decreases. This in turn impacts on the emissions and the energy cost. It is thus shown that it is much more energy efficient to operate at higher loads, making the autoclave much more energy and cost effective, and with less environmental impact. There is potential for applying the analysis presented in this work for conducting optimisation studies for determining the sizes of autoclaves that could minimise the energy requirement, environmental impact and economic cost (3E) of investments for specified load versus time profiles.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49615097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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