Chemical Product and Process Modeling最新文献

{"title":"Taguchi L16 (44) orthogonal array-based study and thermodynamics analysis for electro-Fenton process treatment of textile industrial dye","authors":"Imran Ahmad, D. Basu","doi":"10.1515/cppm-2022-0045","DOIUrl":"https://doi.org/10.1515/cppm-2022-0045","url":null,"abstract":"Abstract Reactive orange 16 (RO16) is the most widely used azo dye in Textile industry. Complex aromatic structures and resistivity to biological decay caused the dye pollutants incompletely treated by the conventional oxidative methods. The current study presents the electro-Fenton-based advanced oxidation treatment of RO16 dye and the process optimization by Taguchi-based design of experiment (DOE). Using a 500 mL volume lab-scale experimental setup, the process was first studied for the principal operational parameters (initial dye concentration (q); [H2O2]/[Fe+2] (R); current density (ρ); and temperature (T)) effect on decolourization (D R ) and COD removal (C R ). Then, by means of the L16 (44) orthogonal array (OA) formation, standard mean and signal-to-noise (S/N) ratio, the process was optimized for the response variables. The result showed the optimized result at q = 100 mg/L, R = 100, ρ = 8 mA/cm2, and T = 32 °C; with D R and C R as 90.023 and 84.344%, respectively. It was found that the current density affects the process most, followed by [H2O2]/[Fe+2] ratio, initial dye concentration, and temperature i.e., ρ > R > q > T. Also, with the analysis of variance (ANOVA), model equations for D R and C R were developed and its accuracy was verified for experimental results. At optimized conditions, the first order removal rate constants (k a ) were found from batch results. Additionally, the thermodynamic constants (ΔH e , ΔS e , and ΔG b ) were also calculated for the nature of heat-energy involved and temperature effect study on dye degradation. The results showed that the process was thermodynamically feasible, endothermic, and non-spontaneous with a lower energy barrier (E A = 46.7 kJ mol−1).","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47373040","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}

{"title":"Multi-objective optimization of a fluid catalytic cracking unit using response surface methodology","authors":"Anish Thomas, M. P. Pavan Kumar","doi":"10.1515/cppm-2022-0018","DOIUrl":"https://doi.org/10.1515/cppm-2022-0018","url":null,"abstract":"Abstract In oil refineries, fluid catalytic cracking (FCC) is a major unit consisting of several process variables and multiple products. Since FCC units are given prime importance as they are contributing a large share in profits, the optimal operation of FCC is always desirable while considering the changing economic scenarios with respect to the products. However, optimization of FCC is quite challenging due to the complex nature of the process. In this work, using Aspen HYSYS V9® catcracker module, process data of FCC was obtained using central composite design (CCD). Second order regression equations for the selected responses were obtained using Analysis of variance (ANOVA) approach. The interaction effects of feed flow, feed temperature, feed pressure, air blower discharge temperature and catalyst circulation rate on responses (yield of products) were presented. Further, the optimization was performed based on a multi-response optimization technique in the Design expert software and the optimal values of the input variables were obtained for the chosen objectives (representing various operation scenarios). The optimal operation scenarios that were obtained for the objectives were validated successfully. This work highlights the use of statistics based soft computing techniques for the optimization of complex chemical engineering operations such as FCC.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"469 - 485"},"PeriodicalIF":0.9,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48479975","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}

{"title":"MSP designing with optimal fractional PI–PD controller for IPTD processes","authors":"S. Sengupta, Somak Karan, C. Dey","doi":"10.1515/cppm-2022-0041","DOIUrl":"https://doi.org/10.1515/cppm-2022-0041","url":null,"abstract":"Abstract An effective tuning methodology of modified Smith predictor (MSP) based fractional controller designing for purely integrating time delayed (IPTD) processes is reported here. IPTD processes with pole at the origin are truly difficult to control; exhibit large oscillations once get disturbed from their steady state. Proposed MSP design consists of fractional PI (proportional-integral) and fractional PD (proportional-derivative) controllers together with P (proportional) controller. Fractional controllers are competent to provide improved closed loop responses due to flexibility of additional tuning parameters. Fractional tuning parameters of PI and PD controllers are derived through optimization algorithms where integral absolute error (IAE) is considered as cost function. Efficacy of the proposed methodology is validated for IPTD processes having wide range of time delay. Stability and robustness issues are explored under process model uncertainties with small gain theorem. Performance of the proposed MSP-FO(PI–PD) controller is validated through simulation study relating five IPTD process models. Overall satisfactory closed loop responses are observed for each case during transient as well as steady state operational phases.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"0 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45250506","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}

{"title":"Statistical modeling and optimization of the bleachability of regenerated spent bleaching earth using response surface methodology and artificial neural networks with genetic algorithm","authors":"Almoruf O. F. Williams, Oluwaseun D. Akanbi","doi":"10.1515/cppm-2022-0031","DOIUrl":"https://doi.org/10.1515/cppm-2022-0031","url":null,"abstract":"Abstract In this study, the statistical modeling and optimization of the regeneration of spent bleaching earth (SBE) for re-use in the bleaching of crude palm oil (CPO) oil was examined. Having a good model will assist with the successful optimal regeneration of SBE and hence minimize the environmental pollution associated with its current disposal method which is based on dumping as landfills. The SBE samples were de-oiled with the Soxhlet extraction method, using n-hexane for 1 h at 60 °C; treated at temperatures ranging from 300–500 °C; at carbonization time between 30 and 45 min; and with hydrochloric acid concentrations between 1 and 2 M, at a constant stirring time of 30 min, respectively. The operating conditions for the experiment were according to the Central Composite Design (CCD) experimental design using the Design Expert software version 13. The modeling and optimization of the SBE regeneration process was carried out with the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques. Five regression models were developed from the RSM approach and the best one selected based on model selection parameters recommended in the literature. Similarly, ten ANN models with the number of neurons in the hidden layer that varied from 2 to 16 were considered and the best one selected using the mean square error (MSE) and correlation coefficients (R) for the training, validation and testing performances. Results showed that the ANN technique led to a model with a better predictive ability than the RSM one. The optimum experimental bleachability of 71.5% for the regenerated de-oiled SBE was obtained at carbonization temperature of 500 °C, hydrochloric acid concentration of 2M and carbonization time of 45min. Using the Genetic Algorithm (GA), the ANN model resulted in an optimum bleachability of 70.87% with corresponding optimum factors at 468.19 °C, 2 M and 45 min, while the RSM approach gave an optimum bleachability of 73.52% at the corresponding factors of 498.99 °C, 1.57 M and 41.14 min for the carbonization temperature, acid concentration and carbonization time, respectively. The optimum experimental bleachability of the regenerated SBE achieved was 12.5% higher than that of virgin bleaching earth (VBE).","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"505 - 519"},"PeriodicalIF":0.9,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49098126","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}

{"title":"Effect of pipe rotation on heat transfer to laminar non-Newtonian nanofluid flowing through a pipe: a CFD analysis","authors":"Sai Kiran Meesala, Budda Govinda Rao, Datta Bharadwaz Yellapragada","doi":"10.1515/cppm-2022-0021","DOIUrl":"https://doi.org/10.1515/cppm-2022-0021","url":null,"abstract":"Abstract The present numerical study is aimed at investigating the effect of rotation on heat transfer to non-Newtonian nanofluid flowing through a pipe. Non-Newtonian fluid flow under laminar condition with heat transfer finds the applications in various industries like food processing, pharmaceutical and polymer etc. Various proportions (1–3%) of copper nanoparticles are mixed with water to study the heat transfer rates non-Newtonian nanofluid flowing through the rotating pipe. Effect of rotation rate on heat transfer rates are also studied. In this study for 1% nanofluid at a constant rotation rate of 0.8, the Nusselt number is increased by 119.45%. The highest thermal performance factor (TPF) is 1.74, observed at N = 0.8, Pe = 5000, and for 1% volume concentration of non-Newtonian nanofluid.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"487 - 503"},"PeriodicalIF":0.9,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47218109","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}

{"title":"Computational investigation of erosion wear in the eco-friendly disposal of the fly ash through 90° horizontal bend of different radius ratios","authors":"Yatish Kumar Baghel, V. Patel","doi":"10.1515/cppm-2022-0026","DOIUrl":"https://doi.org/10.1515/cppm-2022-0026","url":null,"abstract":"Abstract In the present study, slurry erosion wear was evaluated in 90° horizontal pipe bends of various radius ratios (R/r = 2–10) through a commercial CFD code ANSYS FLUENT. For the suspension of fly ash-water, Euler–Lagrange and two way-coupling methods were employed to predict the slurry erosion wear. The flow through the horizontal bend pipe was simulated using a Standard k–ε turbulence modelling. The computational results were validated with the experimental result of the available literature. Fly ash was taken as the dispersed phase of the solid-liquid combination however water was used as the liquid phase. The fly ash particles size was taken as 150 µm. Various affecting factors, such as velocity (4–10 m/s) and solid concentration (2.5 and 7.5% by volume) of the fly ash, were also studied in this investigation. The erosion rate was maximum in the case of R/r = 4 and minimum for R/r = 10 at all velocities and concentrations. It was also found that the erosion rate increases with the increase in solid concentration and velocity.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"411 - 422"},"PeriodicalIF":0.9,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43206226","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}

{"title":"Removal of glycerol from biodiesel using multi-stage microfiltration membrane system: industrial scale process simulation","authors":"S. Kusumocahyo, R. C. Redulla, K. Fulbert, A. A. Iskandar","doi":"10.1515/cppm-2022-0024","DOIUrl":"https://doi.org/10.1515/cppm-2022-0024","url":null,"abstract":"Abstract Biodiesel purification is one of the most important downstream processes in biodiesel industries. The removal of glycerol from crude biodiesel is commonly conducted by an extraction method using water, however this method results in a vast amount of wastewater and needs a lot of energy. In this study, microfiltration membrane was used to remove glycerol from biodiesel, and a process simulation was carried out for an industrial scale biodiesel purification plant using a microfiltration membrane system. The microfiltration experiment using a simulated feed solution of biodiesel containing glycerol and water showed that the membrane process produced purified biodiesel that met the international standards. The result of the process simulation of a multi-stage membrane system showed that the membrane area could be minimized by optimizing the concentration factor of every stage with the aid of a computer program that was written in Phyton programming language with Visual Studio Code. The overall productivity of a single stage membrane system was the same with that of the multi-stage system, however the single stage system required a larger membrane area. To produce 750 m3 day−1 of purified biodiesel, a multi-stage membrane system consisting of 10 membrane modules required a total membrane area of 1515 m2 that was 57% smaller compared to the single stage system consisting of one membrane module. This membrane area reduction was equivalent to a reduction of the total capital cost of 30%. Based on the analysis of the total capital cost, it was found that the optimum number of stages was 4 since it showed a minimum value of the total capital cost with a membrane area of 1620 m2 that was equivalent to the reduction of the total capital cost of 34%. The result of this simulation showed that the multi-stage microfiltration membrane has great potential to replace the conventional method in biodiesel industries.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"451 - 467"},"PeriodicalIF":0.9,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42048705","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}

{"title":"Enhanced design of PID controller and noise filter for second order stable and unstable processes with time delay","authors":"Banda Sai Rahul, M. Ajmeri","doi":"10.1515/cppm-2022-0028","DOIUrl":"https://doi.org/10.1515/cppm-2022-0028","url":null,"abstract":"Abstract In this work, a PID controller along with a noise filter is designed using direct synthesis method for second order stable and unstable processes with time delay. Proposed method involves a single design parameter λ whose value need to be adjusted such that a desired balance between performance and robustness of the system is achieved. Guidelines to select suitable values of λ based on the maximum sensitivity values are provided. Various computer simulations are performed in presence of measurement noise on stable, unstable, integrating and double integrating dynamic systems to illustrate the advantages of suggested control method over some contemporary techniques. Performance measures (integral absolute error and integral squared error) and robustness measures such as maximum sensitivity (M s), complimentary sensitivity (M t) are calculated for the quantitative performance evaluation of the proposed tuning strategy. The suggested tuning algorithm is simple and it yields improved closed loop response compared to some reported methods, satisfactory robustness and smooth control action in presence of noise.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"435 - 449"},"PeriodicalIF":0.9,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48919139","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}

{"title":"Optimal sequencing of conventional distillation column train for multicomponent separation system by evolutionary algorithm","authors":"P. Giri, Y. Mahajan","doi":"10.1515/cppm-2022-0027","DOIUrl":"https://doi.org/10.1515/cppm-2022-0027","url":null,"abstract":"Abstract The best structure of multicomponent separation techniques can be obtained using optimal distillation sequencing. Because distillation sequences contribute significantly to the fixed and operational cost of the entire chemical process, developing a systematic approach for choosing the most appropriate and economic distillation sequences becomes an important field of study. Due to its high dimensional space and combinatorial nature, synthesis of the optimal conventional distillation column sequence is a tough problem in the field of process plant development and optimization. A novel method for the synthesis of an optimal conventional distillation column sequence is suggested in this study. Genetic algorithm, an evolutionary algorithm is at the heart of the proposed method. The Total Annual Cost (TAC) is the main basis used to evaluate alternative configurations. To estimate the total cost of each sequence, rigorous methods are used to design all columns in the sequence. The proposed method’s performance and that of the conventional quantitative approach are compared using the results of a five component benchmark test problem used by researchers in this field. According to the comparison results, the suggested algorithm outclasses the other methods and is more adaptable than other existing approaches.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"423 - 434"},"PeriodicalIF":0.9,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44184078","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}

{"title":"A comparative study: conventional and modified serpentine micromixers","authors":"Ranjitsinha R. Gidde, S. Wangikar, P. Pawar, B. Ronge","doi":"10.1515/cppm-2022-0022","DOIUrl":"https://doi.org/10.1515/cppm-2022-0022","url":null,"abstract":"Abstract The study of flow and mixing dynamics for conventional micromixers as well as micromixers with split and recombine (SAR) units has been carried out using laminar and transport diluted physics modules. Initially, a pilot numerical analysis was done for the basic Y-shaped curved, rectangular and triangular serpentine micromixers. Later, SAR units have been added to these basic designs and the effect of SAR units on the performance characteristics viz., mixing index, pressure drop, performance index and pumping power has been studied. In-depth qualitative analysis was also carried out to visualize the flow and mixing dynamics for the Reynolds number in the range from 0.1–50. The study results revealed that the square shaped chambers and circular obstacle based rectangular serpentine micromixer (SCCO-RSM) demonstrated better performance as compared to the other designs. The proposed micromixer is the better candidate for microfluidics applications such as Lab-On-a-Chip (LOC), Micro-Total-Analysis-Systems (µTAS) and Point of Care Testing (POCT), etc.","PeriodicalId":9935,"journal":{"name":"Chemical Product and Process Modeling","volume":"18 1","pages":"521 - 539"},"PeriodicalIF":0.9,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41650679","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}