Pub Date : 2024-03-15DOI: 10.1016/j.compchemeng.2024.108664
Thomas Puleston , Andreu Cecilia , Ramon Costa-Castelló , Maria Serra
This paper presents a nonlinear observer to estimate the active species concentrations in vanadium flow batteries. To conduct the estimation, the observer relies only on current, flow rate and two half-cell voltage measurements. In contrast to previous works in the field, the proposed observer is capable to deal simultaneously with two significant and challenging conditions: (1) a not necessarily high flow rate, which results in different concentrations for tanks and cells, and (2) presence of crossover and oxidation side reactions, that result in imbalance between the electrolytes on the positive and negative sides of the system. The stability and convergence of the observer are formally demonstrated using a Lyapunov analysis and subsequently validated through comprehensive computer simulations. Finally, utilising the information provided by the observer, a strategy to independently regulate the flow rate of each electrolyte based on their individual state of charge is developed.
{"title":"Nonlinear observer for online concentration estimation in vanadium flow batteries based on half-cell voltage measurements","authors":"Thomas Puleston , Andreu Cecilia , Ramon Costa-Castelló , Maria Serra","doi":"10.1016/j.compchemeng.2024.108664","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108664","url":null,"abstract":"<div><p>This paper presents a nonlinear observer to estimate the active species concentrations in vanadium flow batteries. To conduct the estimation, the observer relies only on current, flow rate and two half-cell voltage measurements. In contrast to previous works in the field, the proposed observer is capable to deal simultaneously with two significant and challenging conditions: (1) a not necessarily high flow rate, which results in different concentrations for tanks and cells, and (2) presence of crossover and oxidation side reactions, that result in imbalance between the electrolytes on the positive and negative sides of the system. The stability and convergence of the observer are formally demonstrated using a Lyapunov analysis and subsequently validated through comprehensive computer simulations. Finally, utilising the information provided by the observer, a strategy to independently regulate the flow rate of each electrolyte based on their individual state of charge is developed.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424000826/pdfft?md5=dfb7a8f9d0acd37b75e2aea37d95b948&pid=1-s2.0-S0098135424000826-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140160700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-15DOI: 10.1016/j.compchemeng.2024.108657
Lorenz T. Biegler
With growing needs to develop and improve climate-friendly processes, optimization strategies are essential at all levels of decision-making in chemical and energy processes, including process development, process synthesis and design, as well as process operations, control, scheduling, and planning. Challenges include the formulation of well-posed and well-conditioned process models, and development and application of efficient, reliable optimization algorithms. Here we describe a synthesis of optimization concepts and algorithms that enable large-scale nonlinear programming, nonintrusive decomposition strategies and the inclusion of a wide class of surrogate models. All of these are crucial to address challenging nonconvex, multi-scale problems in Computer Aided Process Engineering (CAPE). These elements are demonstrated through dynamic optimization strategies for novel energy generation, demand-based optimization for specialty chemicals, and optimization with integrated heterogeneous models for carbon capture processes.
{"title":"Multi-level optimization strategies for large-scale nonlinear process systems","authors":"Lorenz T. Biegler","doi":"10.1016/j.compchemeng.2024.108657","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108657","url":null,"abstract":"<div><p>With growing needs to develop and improve climate-friendly processes, optimization strategies are essential at all levels of decision-making in chemical and energy processes, including process development, process synthesis and design, as well as process operations, control, scheduling, and planning. Challenges include the formulation of well-posed and well-conditioned process models, and development and application of efficient, reliable optimization algorithms. Here we describe a synthesis of optimization concepts and algorithms that enable large-scale nonlinear programming, nonintrusive decomposition strategies and the inclusion of a wide class of surrogate models. All of these are crucial to address challenging nonconvex, multi-scale problems in Computer Aided Process Engineering (CAPE). These elements are demonstrated through dynamic optimization strategies for novel energy generation, demand-based optimization for specialty chemicals, and optimization with integrated heterogeneous models for carbon capture processes.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424000759/pdfft?md5=6fff59ef9213873abf6b2a8a786ef8a3&pid=1-s2.0-S0098135424000759-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140160701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-12DOI: 10.1016/j.compchemeng.2024.108658
Kyoungmin Lee, Jong Min Lee
We propose computational fluid dynamics (CFD)-enveloped Bayesian optimization (EBO), a novel optimizer that integrates EBO with CFD to reduce the required CFD simulations by utilizing previous optimization data. The proposed optimizer was applied to determine the optimal catalyst packing ratio of the Fischer–Tropsch microchannel reactor that minimizes the maximum temperature and maximizes the productivity of long-chain hydrocarbons by utilizing the CFD model. The obtained results indicate that the number of iterations required to reach the optimal points is lower than that of BO, and the optimal result exhibits a 5% improvement from the initial condition. The optimizer was evaluated across various catalyst packing cases to assess its robustness. Nevertheless, the proposed optimizer was consistently able to reach optimal points that BO could not achieve. We anticipate that this optimizer can be widely applied to optimize the operating condition of a chemical reactor in the presence of previous optimization data.
{"title":"Optimization of Fischer–Tropsch microchannel reactor using computational fluid dynamics and enveloped Bayesian optimization","authors":"Kyoungmin Lee, Jong Min Lee","doi":"10.1016/j.compchemeng.2024.108658","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108658","url":null,"abstract":"<div><p>We propose computational fluid dynamics (CFD)-enveloped Bayesian optimization (EBO), a novel optimizer that integrates EBO with CFD to reduce the required CFD simulations by utilizing previous optimization data. The proposed optimizer was applied to determine the optimal catalyst packing ratio of the Fischer–Tropsch microchannel reactor that minimizes the maximum temperature and maximizes the productivity of long-chain hydrocarbons by utilizing the CFD model. The obtained results indicate that the number of iterations required to reach the optimal points is lower than that of BO, and the optimal result exhibits a 5% improvement from the initial condition. The optimizer was evaluated across various catalyst packing cases to assess its robustness. Nevertheless, the proposed optimizer was consistently able to reach optimal points that BO could not achieve. We anticipate that this optimizer can be widely applied to optimize the operating condition of a chemical reactor in the presence of previous optimization data.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140138048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-12DOI: 10.1016/j.compchemeng.2024.108661
William L. Luyben
The need for refrigeration cooling at two different sub-ambient temperature levels is an important problem in some processes. A modern grocery store is an extremely important global example in which there is a need for a moderate temperature heat sink (5 °C) to keep food cool but also a need for a significantly colder heat sink (− 20 °C) for frozen food products. If the two temperatures are not too different, a single refrigerant can be used. The compression refrigeration configuration then consists of two compressors operating in parallel, a single condenser, a single refrigerant liquid surge drum and multiple evaporators. Liquid refrigerant at high pressure is split into a large number of parallel streams to feed individual evaporators in the cooling and freezing compartments. This paper studies how this multi-variable interacting dynamic system can be modeled and controlled using simple conventional controllers.
{"title":"Dynamic simulation and control of dual-evaporator compression refrigeration systems","authors":"William L. Luyben","doi":"10.1016/j.compchemeng.2024.108661","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108661","url":null,"abstract":"<div><p>The need for refrigeration cooling at two different sub-ambient temperature levels is an important problem in some processes. A modern grocery store is an extremely important global example in which there is a need for a moderate temperature heat sink (5 °C) to keep food cool but also a need for a significantly colder heat sink (− 20 °C) for frozen food products. If the two temperatures are not too different, a single refrigerant can be used. The compression refrigeration configuration then consists of two compressors operating in parallel, a single condenser, a single refrigerant liquid surge drum and multiple evaporators. Liquid refrigerant at high pressure is split into a large number of parallel streams to feed individual evaporators in the cooling and freezing compartments. This paper studies how this multi-variable interacting dynamic system can be modeled and controlled using simple conventional controllers.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140138047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Efficient control loop performance is pivotal in process industries to ensure optimal production, maintain product quality, and adhere to regulatory standards. Poorly tuned controllers can disrupt these objectives, necessitating accurate detection methods. This paper introduces a novel approach for detecting poor controller tuning through advanced techniques: the Gramian Angular Field (GAF) and Stack Auto-Encoder (SAE). Unlike manual methods, this automated system promptly identifies poorly tuned controllers, offering real-time monitoring and timely alerts to operators. The proposed methodology is substantiated through two case studies: the ISDB dataset and the pulp and paper dataset. The outcomes illustrate that the proposed approach correctly determines the appropriate outcome for the majority of the analyzed control loops across diverse industries.
{"title":"Detection of poor controller tuning with Gramian Angular Field (GAF) and StackAutoencoder (SAE)","authors":"Amirreza Memarian, Seshu Kumar Damarla, Alireza Memarian, Biao Huang","doi":"10.1016/j.compchemeng.2024.108652","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108652","url":null,"abstract":"<div><p>Efficient control loop performance is pivotal in process industries to ensure optimal production, maintain product quality, and adhere to regulatory standards. Poorly tuned controllers can disrupt these objectives, necessitating accurate detection methods. This paper introduces a novel approach for detecting poor controller tuning through advanced techniques: the Gramian Angular Field (GAF) and Stack Auto-Encoder (SAE). Unlike manual methods, this automated system promptly identifies poorly tuned controllers, offering real-time monitoring and timely alerts to operators. The proposed methodology is substantiated through two case studies: the ISDB dataset and the pulp and paper dataset. The outcomes illustrate that the proposed approach correctly determines the appropriate outcome for the majority of the analyzed control loops across diverse industries.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140138049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-12DOI: 10.1016/j.compchemeng.2024.108653
Kwanghyun Cho , Ketong Shao , Ali Mesbah
Bayesian optimization (BO) has emerged as a useful paradigm for automatic calibration (aka auto-tuning) of advanced optimization- and learning-based controllers whose closed-loop performance depends on the choice of several tuning parameters in highly nonlinear and nonconvex ways. However, BO approaches to controller auto-tuning commonly rely on the assumption that system dynamics remain constant, which does not hold for systems with time-varying dynamics, for example, due to gradual aging or persistent environmental drifts. This challenge can be further compounded when gradual and persistent system drifts occur over a series of process runs. Existing time-varying BO (TVBO) approaches with spatio-temporal kernels fall short of effectively handling an integer run index, which is imperative for capturing run-to-run changes in the system behavior. To this end, this paper presents a run-indexed TVBO (RI-TVBO) approach that can systematically account for run-to-run process drifts as the system is queried over sequential process runs. The proposed approach relies on adapting the non-stationary Wiener process kernel to accommodate an integer run index, instead of time. This is done via positional encoding that incorporates the integer run index and, thus, enables describing run-to-run variations in system dynamics. The positional embedding vector associated with each run index is then mapped onto a scalar value to leverage the relationships between different process runs within the probabilistic surrogate model of the objective function in RI-TVBO. The performance of RI-TVBO is evaluated for auto-tuning of an offset-free model predictive controller for a low-temperature plasma-assisted process for thin film deposition. Simulation results demonstrate the superior performance of RI-TVBO over standard BO and TVBO under different scenarios of run-to-run process drifts encountered in plasma-assisted deposition processes in semiconductor manufacturing.
{"title":"Run-indexed time-varying Bayesian optimization with positional encoding for auto-tuning of controllers: Application to a plasma-assisted deposition process with run-to-run drifts","authors":"Kwanghyun Cho , Ketong Shao , Ali Mesbah","doi":"10.1016/j.compchemeng.2024.108653","DOIUrl":"10.1016/j.compchemeng.2024.108653","url":null,"abstract":"<div><p>Bayesian optimization (BO) has emerged as a useful paradigm for automatic calibration (aka auto-tuning) of advanced optimization- and learning-based controllers whose closed-loop performance depends on the choice of several tuning parameters in highly nonlinear and nonconvex ways. However, BO approaches to controller auto-tuning commonly rely on the assumption that system dynamics remain constant, which does not hold for systems with time-varying dynamics, for example, due to gradual aging or persistent environmental drifts. This challenge can be further compounded when gradual and persistent system drifts occur over a series of process runs. Existing time-varying BO (TVBO) approaches with spatio-temporal kernels fall short of effectively handling an integer run index, which is imperative for capturing run-to-run changes in the system behavior. To this end, this paper presents a run-indexed TVBO (RI-TVBO) approach that can systematically account for run-to-run process drifts as the system is queried over sequential process runs. The proposed approach relies on adapting the non-stationary Wiener process kernel to accommodate an integer run index, instead of time. This is done via positional encoding that incorporates the integer run index and, thus, enables describing run-to-run variations in system dynamics. The positional embedding vector associated with each run index is then mapped onto a scalar value to leverage the relationships between different process runs within the probabilistic surrogate model of the objective function in RI-TVBO. The performance of RI-TVBO is evaluated for auto-tuning of an offset-free model predictive controller for a low-temperature plasma-assisted process for thin film deposition. Simulation results demonstrate the superior performance of RI-TVBO over standard BO and TVBO under different scenarios of run-to-run process drifts encountered in plasma-assisted deposition processes in semiconductor manufacturing.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140281729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-11DOI: 10.1016/j.compchemeng.2024.108655
Peter Jul-Rasmussen , Arijit Chakraborty , Venkat Venkatasubramanian , Xiaodong Liang , Jakob Kjøbsted Huusom
With increased accessibility of process data from the production lines in chemical and biochemical production plants, the use of data-based modeling methods is gaining interest. In this work, three different data-based modeling approaches are applied for modeling aeration in a pilot scale bubble column. In all three modeling approaches the same serial hybrid-model structure is used, combining a species conservation balance based on first-principles with different data-based models for the overall volumetric mass transfer coefficient (). Simple empirical correlations with parameters fit to process data provide transparent models but lack the accuracy of Artificial Neural Networks (ANNs). ANNs provide models with high accuracy within the operation regimes used for training, however, the models are prone to overfitting, and their black-box nature results in models that are difficult to interpret. As an alternative, a symbolic regression-inspired technique is used for discovering symbolic equations, resulting in interpretable models with accuracy that is comparable to that of the ANN.
随着化工和生化生产厂生产线工艺数据的可获取性不断提高,基于数据的建模方法的使用越来越受到关注。在这项工作中,我们采用了三种不同的基于数据的建模方法,对中试规模气泡塔中的曝气进行建模。这三种建模方法都采用了相同的串行混合模型结构,将基于第一原理的物种守恒平衡与不同的基于数据的总体积传质系数(KLa)模型相结合。与工艺数据参数拟合的简单经验相关性提供了透明的模型,但缺乏人工神经网络(ANN)的准确性。人工神经网络可在用于训练的运行条件下提供高精确度的模型,但模型容易过度拟合,其黑箱性质导致模型难以解释。作为一种替代方法,我们采用了一种受符号回归启发的技术来发现符号方程,从而得到可解释的模型,其准确性可与 ANN 相媲美。
{"title":"Hybrid AI modeling techniques for pilot scale bubble column aeration: A comparative study","authors":"Peter Jul-Rasmussen , Arijit Chakraborty , Venkat Venkatasubramanian , Xiaodong Liang , Jakob Kjøbsted Huusom","doi":"10.1016/j.compchemeng.2024.108655","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108655","url":null,"abstract":"<div><p>With increased accessibility of process data from the production lines in chemical and biochemical production plants, the use of data-based modeling methods is gaining interest. In this work, three different data-based modeling approaches are applied for modeling aeration in a pilot scale bubble column. In all three modeling approaches the same serial hybrid-model structure is used, combining a species conservation balance based on first-principles with different data-based models for the overall volumetric mass transfer coefficient (<span><math><mrow><msub><mrow><mi>K</mi></mrow><mrow><mi>L</mi></mrow></msub><mi>a</mi></mrow></math></span>). Simple empirical correlations with parameters fit to process data provide transparent models but lack the accuracy of Artificial Neural Networks (ANNs). ANNs provide models with high accuracy within the operation regimes used for training, however, the models are prone to overfitting, and their black-box nature results in models that are difficult to interpret. As an alternative, a symbolic regression-inspired technique is used for discovering symbolic equations, resulting in interpretable models with accuracy that is comparable to that of the ANN.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424000735/pdfft?md5=3477d1f0e4cfdb2734621b49ea7ff3f6&pid=1-s2.0-S0098135424000735-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140138050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-11DOI: 10.1016/j.compchemeng.2024.108647
I. Jul-Jørgensen , P. Facco , K.V. Gernaey , M. Barolo , C.A. Hundahl
This study investigates the use of Raman spectroscopy fused with other types of data (e.g., pH, temperature and turbidity) for multivariate statistical process control of two pharmaceutical case studies: one simulated industrial-scale fed-batch process for the production of penicillin and one real lab-scale crystallization process. The monitoring schemes are built on local principal component analysis models and hyper-parameters are tuned with regards to highest accuracy in fault detection. Accuracies above 90% are obtained for all types of data and level of DF. Furthermore, for the first case study the model built solely on spectra achieves higher fault detection rates, when only considering faults that also result in off-specification quality. This is supported by the fact that the fault is not necessarily detected when it occurs, but rather when it starts to affect quality variables as measured by the spectra.
{"title":"Data fusion of Raman spectra in MSPC for fault detection and diagnosis in pharmaceutical manufacturing","authors":"I. Jul-Jørgensen , P. Facco , K.V. Gernaey , M. Barolo , C.A. Hundahl","doi":"10.1016/j.compchemeng.2024.108647","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108647","url":null,"abstract":"<div><p>This study investigates the use of Raman spectroscopy fused with other types of data (e.g., pH, temperature and turbidity) for multivariate statistical process control of two pharmaceutical case studies: one simulated industrial-scale fed-batch process for the production of penicillin and one real lab-scale crystallization process. The monitoring schemes are built on local principal component analysis models and hyper-parameters are tuned with regards to highest accuracy in fault detection. Accuracies above 90% are obtained for all types of data and level of DF. Furthermore, for the first case study the model built solely on spectra achieves higher fault detection rates, when only considering faults that also result in off-specification quality. This is supported by the fact that the fault is not necessarily detected when it occurs, but rather when it starts to affect quality variables as measured by the spectra.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140112643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The application of ultrasound is recently gaining significant interest in crystallization because of its significant impact on nucleation and growth rates, particle breakage, crystal habit, polymorphism, and crystal size distribution. Pyrazinamide, an essential drug for the treatment of mycobacterium tuberculosis, has four different polymorphic forms. The metastable -polymorph exhibit plate-type habit which is desirable for downstream operations compared to commercially available needle-type -polymorph. This contribution presents a detail experimental and computational study on the effect of ultrasound and its amplitude on nucleation, growth, and breakage of crystals for unseeded batch cooling sonocrystallization of -polymorph of pyrazinamide from its 1,4-dioxane solution. A series of sonocrystallization experiments are conducted with different cooling rates and ultrasonic amplitudes and a bivariate population balance model involving crystal nucleation, growth, and breakage is developed and fully validated. The model simulations give important insights on time evolution of mean crystal size and aspect ratio of plate-type crystals.
{"title":"Multivariate population balance modeling and simulation of ultrasound-assisted crystallization of a plate-type pharmaceutical: Nucleation, growth, and breakage","authors":"Abhishek Maharana , Ashok Das , Jitendra Kumar , Debasis Sarkar","doi":"10.1016/j.compchemeng.2024.108651","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108651","url":null,"abstract":"<div><p>The application of ultrasound is recently gaining significant interest in crystallization because of its significant impact on nucleation and growth rates, particle breakage, crystal habit, polymorphism, and crystal size distribution. Pyrazinamide, an essential drug for the treatment of <em>mycobacterium tuberculosis</em>, has four different polymorphic forms. The metastable <span><math><mi>δ</mi></math></span>-polymorph exhibit plate-type habit which is desirable for downstream operations compared to commercially available needle-type <span><math><mi>α</mi></math></span>-polymorph. This contribution presents a detail experimental and computational study on the effect of ultrasound and its amplitude on nucleation, growth, and breakage of crystals for unseeded batch cooling sonocrystallization of <span><math><mi>δ</mi></math></span>-polymorph of pyrazinamide from its 1,4-dioxane solution. A series of sonocrystallization experiments are conducted with different cooling rates and ultrasonic amplitudes and a bivariate population balance model involving crystal nucleation, growth, and breakage is developed and fully validated. The model simulations give important insights on time evolution of mean crystal size and aspect ratio of plate-type crystals.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140122717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-11DOI: 10.1016/j.compchemeng.2024.108656
Sonja H.M. Germscheid , Benedikt Nilges , Niklas von der Assen , Alexander Mitsos , Manuel Dahmen
This work studies synergies arising from combining industrial demand response and local renewable electricity supply. To this end, we optimize the design of a local electricity generation and storage system with an integrated demand response scheduling of a continuous power-intensive production process in a multi-stage problem. We optimize both total annualized cost and global warming impact and consider local photovoltaic and wind electricity generation, an electric battery, and electricity trading on day-ahead and intraday market. We find that installing a battery can reduce emissions and enable large trading volumes on the electricity markets, but significantly increases cost. Economically and ecologically-optimal operation of the process and battery are driven primarily by the electricity price and grid emission factor, respectively, rather than locally generated electricity. A parameter study reveals that cost savings from the local system and flexibilizing the process behave almost additively.
{"title":"Optimal design of a local renewable electricity supply system for power-intensive production processes with demand response","authors":"Sonja H.M. Germscheid , Benedikt Nilges , Niklas von der Assen , Alexander Mitsos , Manuel Dahmen","doi":"10.1016/j.compchemeng.2024.108656","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2024.108656","url":null,"abstract":"<div><p>This work studies synergies arising from combining industrial demand response and local renewable electricity supply. To this end, we optimize the design of a local electricity generation and storage system with an integrated demand response scheduling of a continuous power-intensive production process in a multi-stage problem. We optimize both total annualized cost and global warming impact and consider local photovoltaic and wind electricity generation, an electric battery, and electricity trading on day-ahead and intraday market. We find that installing a battery can reduce emissions and enable large trading volumes on the electricity markets, but significantly increases cost. Economically and ecologically-optimal operation of the process and battery are driven primarily by the electricity price and grid emission factor, respectively, rather than locally generated electricity. A parameter study reveals that cost savings from the local system and flexibilizing the process behave almost additively.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424000747/pdfft?md5=62a6dbce8d5025b761d07555d04e3b4c&pid=1-s2.0-S0098135424000747-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140339121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}