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1.	Ahlström, Johan, 1990, et al. (författare) Forest residues gasification integrated with electrolysis for production of SNG – modelling and assessment 2018 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 44, s. 109-114 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract This study investigates opportunities for integrating an electrolysis unit with a biomass gasifier for production of synthetic natural gas (SNG). Gasification is a key technology for production of biofuels and chemicals from lignocellulosic biomass, for which an increased demand is expected in the future. H2produced through an electrolyser can be used to increase the output of a gasifier by reaction with CO2to form CH4. Four integrated flowsheet configurations are evaluated with respect to system energy efficiency and process operating revenue. The system energy efficiencies are in the range of 0.55 – 0.8, and the maximum value of operating revenues is 0.245 $/kWhdry biomass. The results show that feeding the Sabatier reactor with the full product gas flow coming from the methanation unit, and separating the unreacted CO2afterwards, is the most attractive configuration with respect to operating revenue.
2.	Andersson, Niklas, et al. (författare) Calibration of a polyethylene plant for grade change optimisations 2011 Ingår i: 21ST European Symposium on Computer Aided Process Engineering. - 1570-7946. - 9780444538956 ; 29, s. 673-677 Konferensbidrag (refereegranskat)abstract A polyethylene plant model coded in Modelica and based on a nonlinear MPC model currently used at Borealis AB is considered for calibration. A case study of model calibration at steady-state for four different operating points are analysed, both when looking at one operating point separately, but also to calibrate several simultaneously. Both model parameters and reactor inputs are calibrated for true plant measurement data. To solve the parameter estimation problem, the JModelica.org platform is used, offering tools to express and solve calibration problems. Calibration was obtained with narrow confidence intervals and shows a potential to improve the model accuracy by changing the parameter values. The results will be used for dynamic optimisations of grade changes.
3.	Badr, Sara, 1985, et al. (författare) Combined basic and fine chemical biorefinery concepts with integration of processes at different technology readiness levels 2018 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 43, s. 1577-1582 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Biorefineries offer promising alternatives to the use of fossil fuels to produce energy and chemicals. This work describes the development of a biorefinery concept to produce adipic acid from Swedish forest residues and lutein from micro-algae. A description is provided for each process line available, its technology readiness level (TRL) and the tools available to model it. Scenarios of the integrated concept are built with associated material flow analysis. Key results of the material inventory of the base case scenario are presented as well as insights into the development of further scenarios. Material flow inventories can then be further used for economic and environmental assessment. Major challenges of integration are discussed in terms of uncertainties and data gaps for processes with low TRL such as scaling up lab experiments, understanding the restrictions of material recycling and its impact on process performance. The feedback given through these scenarios can help guide further experimental efforts.
4.	Caccavo, D., et al. (författare) Modeling the mechanics and the transport phenomena in hydrogels 2018 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 42, s. 357-383 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Hydrogels are polymeric materials widely used in pharmaceutical and biomedical applications. Their uses can be improved by modeling their behavior, in particular the mechanical phenomena and the transport phenomena. The scope of this chapter is to propose a model, simple enough and with a limited number of parameters to be determined, able to capture the full behavior of a swelling hydrogel, with the aim of describing the drug release process as well as—in principle—any other application of hydrogels. The model was derived recalling the basics of the continuum mechanics, the possible approaches to estimate the Helmholtz free energy, and then writing the transport and constitutive equations for a poroelastic material, and for a more realistic poroviscoelastic material (by adding the standard linear solid model as the rheological model). A full extension to multicomponent systems, to describe the drug release phenomenon, is proposed along with a sensitivity analysis (free-swelling simulation by changing the model parameters).
5.	Calvo-Serrano, Raul, et al. (författare) Cradle-to-gate environmental impact prediction from chemical attributes using mixed-integer programming 2017 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 40, s. 1999-2004 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Life Cycle Assessment (LCA) has recently gained widespread acceptance in green chemistry as an effective tool for quantifying the environmental impact of chemicals along their life cycle. Unfortunately, LCA studies require large amounts of data that are hard to gather in practice, a limitation that is particularly critical when assessing the complex processes and value chains present in the chemical industry. With the aim at simplifying these calculations and promoting the wider adoption of environmental principles, in this work we develop an approach that predicts the cradle-to-gate life cycle production impact of organic chemicals from attributes based on their molecular structure and thermodynamic properties. The approach presented relies on a mixed-integer programming (MIP) optimisation framework that streamlines the LCA calculations by systematically constructing multi-linear short-cut predictive models of cradle-to-gate life cycle impact. These models contain key molecular and thermodynamic attributes that are identified using binary variables. On applying our method to an LCA data set containing 83 chemicals, 17 molecular descriptors and 15 thermodynamic properties, we produced estimates for widely used metrics such as cumulative energy demand (CED), global warming potential (GWP) and Eco-indicator 99 (EI99) with relative errors within acceptable ranges considering the nature of any LCA study. Our optimisation-based streamlined LCA framework ultimately leads to simple linear models that are amenable for implementation in computer aided molecular design software, thereby opening new avenues for the inclusion of sustainability principles in the early stages of the development of new chemicals.
6.	Chen, Hao, et al. (författare) Dynamic Modelling and Surrogate-based Optimization of Auto-thermal Reforming for Enhanced Hydrogen Production 2024 Ingår i: Computer Aided Chemical Engineering. - : Elsevier B.V.. - 1570-7946. ; 53, s. 1027-1032 Tidskriftsartikel (refereegranskat)abstract Hydrogen energy has been considered as one of the solutions to achieve the net-zero emission scenario by 2050. Steam methane reforming is a widely used industrial process for producing hydrogen from natural gas or methane nowadays. Considering that methane could be utilized as a suitable carrier for hydrogen energy, it is anticipated that steam methane reforming will still play an important role in the future energy sector when it comes to hydrogen production, storage, and transportation. In this work, a one-imensional dynamic model is established to simulate the performance of an auto-thermal reforming reactor, which allows for capturing the localized phenomena inside the reactor over time. A set of input parameters is selected based on the Latin Hypercube Sampling method to generate the training data for the surrogate model development. Singular value decomposition and Gaussian Process regression are then implemented on the training data to construct a surrogate model of the reformer. This surrogate model is subsequently utilized in the optimization process to enhance hydrogen production and lower the maximum catalyst temperature within the reactor. The results show that the surrogate model, developed by using singular value decomposition and Gaussian Process, exhibits a high level of accuracy when compared to the physics-based reformer model. Furthermore, the optimization framework built upon surrogate modelling offers the potential to substantially reduce the computational expenses associated with the optimization process, while preserving the precision of the optimization results. This method could efficiently serve as a tool for parameters optimization of such reactors and could be used to guide the operation of these systems toward improved performance.
7.	Holmqvist, Anders, et al. (författare) A Generic PAT Software Interface for On-Line Monitoring and Control of Chromatographic Separation Systems 2016 Ingår i: 26th European Symposium on Computer Aided Process Engineering. - 1570-7946. - 9780444634283 ; 38, s. 811-816 Konferensbidrag (refereegranskat)abstract This contribution presents a novel process analytical technology (PAT) software interface for online monitoring and control of commercial high-pressure liquid chromatography (HPLC) systems. The developed interface is an add-on to chromatography control software and uses industry-standard bidirectional communication protocols to link sensor technologies with the individual HPLC system components in an overall automation framework that facilitates data acquisition, central operation and control of all instruments. The interface is encoded in the Python™ scripting language and supports versatile data transfer to chromatography control software using either OPC (OLE for process control) or COM (component object model) technologies, which are both based on client/server architectures. By these means, the interface utilizes the flexibility of the high-level programming language for formulating optimal control strategies and enables (semantic) interoperability between the chromatography control software and user defined scripts as well as third-party scientific libraries and numerical packages. The advantages and applicability of the developed interface are highlighted through the implementation of a model-based iterative learning control strategy, in order to assure batch-to-batch repeatability, and open-loop optimal controlled elution trajectories on a commercial HPLC separation system. It is, however, noteworthy that the software interface is completely generic and constitutes a novel framework for implementing any PID control schemes as well as sequential optimal experimental design and model predictive control strategies.
8.	Holmqvist, Anders, et al. (författare) Dynamic Multi-Objective Optimization of Batch Chromatographic Separation Processes 2015 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. - 9780444634290 ; 37, s. 815-820 Konferensbidrag (refereegranskat)abstract This contribution presents a novel offline dynamic multi-objective optimization framework for high-pressure liquid chromatographic (HPLC) processes in batch elution mode. The framework allows for optimization of general elution trajectories parametrized with piecewise constant control signals. It is based on a simultaneous method where both the control and state variables are fully discretized in the temporal domain, using orthogonal collocations on finite elements, and the state variables are discretized in the spatial domain, using a finite volume weighted essentially non-oscillatory (WENO) scheme. The resulting finite dimensional nonlinear program (NLP) is solved using a primal-dual interior point method and automatic differentiation techniques. The advantages of this open-loop optimal control methodology are highlighted through the solution of a challenging ternary complex mixture separation problem for a hydrophobic interaction chromatography (HIC) system. For a bi-objective optimization of the target component productivity and yield, subject to a purity constraint, the set of Pareto solutions generated with general elution trajectories showed considerable improvement in the productivity objective when compared to the Pareto set obtained using conventional linear elution trajectories.
9.	Karka, P., et al. (författare) Life Cycle Assessment of Biorefinery Products Based on Different Allocation Approaches 2015 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 37, s. 2573-2578 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Biorefineries constitute representative examples of multifunctional systems which are able to produce, similarly to conventional petroleum refineries, a wide range of chemicals (pharmaceutical constituents, plastics, food additives etc.), energy carriers and power through the optimal use of diverse biomass forms (wheat straw, oils, wood chips, municipal solid waste). For this purpose, biorefineries typically comprise a complicated, integrated network of physical and chemical transformation processes, such as mechanical and physical biomass pretreatment, pyrolysis, gasification, catalytic and enzymatic reactions, and downstream purification processes. For the environmental sustainability assessment of these complicated production systems, Life Cycle Analysis (LCA, ISO-Norm 14040) is considered as a widely acceptable methodology from scientists and engineers including, however, the debated aspect of partitioning the impacts among the co-products' in the biorefinery product portfolio. The aim of this study is to present the influence of the various allocation approaches on the LCA results of biorefinery products. The framework of this analysis systematically incorporates the steps of the LCA methodology as described in the ISO norms and estimates the impacts related with the products of interest, taking into account the contribution of the co- and by-products in the overall production path. For this reason, two wider approaches were adopted, the attributional which describes the impact of the production process itself from a retrospective point of view, and the consequential which focuses on the changes in the level of the output (as well as consumption and disposal) of a product, including market effects from increasing or decreasing demand for the study product, having therefore a more prospective point of view. Several scenarios which describe the possible options for handling those products, were developed and assessed based on different allocation methodologies, namely system expansion (substitution method) and partitioning methods according to the mass, thermal and economic values of the co-products. The estimation of the life cycle impacts of the processes was performed using the Global Warming Potential (GWP), Cumulative Energy Demand (CED) and RECIPE methodologies which provide an assessment of the burdens through the associated LCA indicators. The outcome of this approach provides a range of LCA metrics emphasizing at the variation of the results according to the followed allocation methods and to identify those properties of products (physical, economic, thermal) and system factors (processes to be substituted from the renewable ones, degree of utilization of co- and by-products from the markets etc.) which dominate the LCA results.
10.	Karka, P., et al. (författare) Predictive LCA - a systems approach to integrate LCA decisions ahead of design 2019 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 46, s. 97-102 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Bio-refineries are promising production options of chemicals production, capable to produce a wide range of fuels and chemicals equivalent to the conventional fossil-based products. To establish bio-refineries as mature choices and achieve the commercialization of their technologies, the application of sustainable solutions during the design and development stages are crucial. The innovative character of bio-based production and therefore data availability and access on process modelling details, is a challenging point for decision makers to move towards this direction. Considering the environmental dimension out of the three aspects of sustainability, Life Cycle Assessment (LCA) is a suitable methodology for the evaluation of environmental impacts of bio-based processes because it highlights the stages with the greatest impact along a production chain. LCA studies require large amount of information, usually extracted from detailed flowsheets or from already completed pilot plants, making this procedure, costly, time consuming and not practical to act as a decision- support tool for the development of a bio-refinery. The aim of this study is to develop predictive models for the assessment of LCA metrics and use them to highlight sustainable design options for bio-refineries. Models require the least possible information, which can be obtained from chemistry - level data or early (conceptual) design stages. The modelling techniques used in this study are decision trees and Artificial Neural Networks (ANN), due to their easily interpretable structure and high computational capabilities, respectively. Models are based on the extraction of knowledge from a wide dataset for bio-refineries (it refers to 32 products that is, platform chemicals (e.g., syngas, sugars and lignin) and biofuels (e.g., biodiesel, biogas, and alcohols), starting from diverse biomass sources (e.g., wood chips, wheat straw, vegetable oil)). Input parameters include descriptors of the molecular structure and process related data which describe the production path of a study product. Models are able to predict LCA metrics which cover the most critical aspects of environmental sustainability such as cumulative energy demand (CED) and Climate Change (CC). The average classification errors for decision- tree models range between 17% (± 10%) to 38% (± 11%) whereas for ANN models the average R2cv values (coefficient of determination) range between 0.55 (± 0.42%) to 0.87 (± 0.07%). Demonstration of models is provided using case studies found in literature. Models are used to rank options in various design problems and support decisions on the selection of the most profitable option. Examples of such cases are the selection of the appropriate technology or feedstock to produce a desired product or the preliminary design of a bio-refinery configuration. The proposed approach provides a first generation of models that correlate available and easily accessed information to desirable output process parameters and assessment metrics and can be used as pre-screening tools in the development of innovative processes, ahead of detailed design, thus saving time and money.
11.	Karka, Paraskevi, 1982, et al. (författare) Production costs of advanced biofuels using a multi-component learning curve model 2021 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 50, s. 1937-1942 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract The production costs of advanced biofuel options are currently higher than those of their fossil fuel equivalents. Capital Expenditures (CAPEX) for the production of liquid biofuels for road, aviation and marine transport sectors have a significant contribution to the overall production cost, together with the feedstock cost. It is, therefore, important to estimate the potential for cost reduction through R&D and experience in assembling a growing number of respective plants (i.e., from first-of-a kind (FOAK) to the Nth plant (NOAK)), which comprise a mix of established and innovative technological components. This could provide valuable information to stakeholders for the expected investment costs to meet European Commission goals in 2050. This study adopts a methodological framework based on the “learning curve theory” to estimate cost reduction as a result from the experience of technology implementation, in terms of numbers or capacity of units implemented. This work applies the learning theory as a multicomponent analysis, which requires a systematic decomposition of the entire production process to identify established and innovative technological components that can be analysed in detail using the corresponding technoeconomic data. The analysis showed that CAPEX reduction in the range of 10-25% could be expected to reach capacities corresponding to NOAK plants in 2050. To reach further CAPEX reduction of 40%, for example, would require higher cumulative annual growth rates to achieve two orders of magnitude increase of cumulative installed capacity. This corresponds to hundreds of GWs or equivalently some hundreds or thousands of large-scale plants to meet the goal of 20-25% transportation fuels consumption to be covered by advanced biofuels in 2050.
12.	Langner, Christian, 1990, et al. (författare) Flexibility analysis of chemical processes considering dependencies between uncertain parameters 2021 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 50, s. 1105-1110 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Chemical processes are usually subject to varying operating conditions. Consequently, the evaluation of the flexibility of a process with respect to variations in inlet conditions is vital to identify bottlenecks in current process flowsheets or new flowsheet design proposals. The flexibility index is a well-established concept to perform flexibility analysis of chemical processes. In this paper, we propose a novel approach to incorporate knowledge regarding dependencies between input parameters when calculating the flexibility index. The aim is to achieve a more accurate indication of a process's flexibility when dependencies between input parameters are present.
13.	Langner, Christian, 1990, et al. (författare) Flexibility analysis of chemical processes considering overlaying uncertainty sources 2022 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 49, s. 769-774 Konferensbidrag (refereegranskat)abstract Chemical processes are often subject to uncertainty. Consequently, the evaluation of the flexibility of a process with respect to variations in inlet conditions is vital to identify bottlenecks in current process flowsheets or new flowsheet design proposals. The flexibility index is a well-established concept to perform flexibility analysis of chemical processes. In this paper, we propose novel reformulations of the flexibility index problem to account for overlaying uncertainty sources which interfere with each other. The aim of the paper is to identify and define overlaying uncertainty sources and to overcome shortcomings of existing approaches when calculating the flexibility index in such situations.
14.	Limleamthong, P., et al. (författare) Screening of Solvents for CO2 Capture considering Sustainability Criteria via Data Envelopment Analysis 2017 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 40, s. 2011-2016 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract The growing trend towards the development of more sustainable chemical products and processes has created a clear need for decision-support tools to evaluate and optimise the sustainability level of a system. In this work, we propose a new methodology to screen and select chemicals according to the extent to which they adhere to sustainability principles that is based on Data Envelopment Analysis (DEA), a technique developed in economics for efficiency assessment. The capabilities of the DEA-based approach in the context of computer aided process engineering are demonstrated through the screening of 125 conventional amine-based solvents for CO 2 capture according to 10 performance indicators, considering technical (economic), environmental and social aspects simultaneously. Our approach eliminates 36% of the solvents (those found inefficient), and establishes in turn quantitative targets and clear guidelines on how to improve them. The DEA models are capable of identifying the practical downsides of amines as main sources of inefficiency, providing clear improvement targets for properties such as vapour pressure, acute toxicity and several life cycle impacts. The final aim of the DEA-based analysis is to facilitate the selection of more sustainable chemicals in the transition towards a more sustainable chemical industry.
15.	Lindholm, Anna, et al. (författare) Hierarchical Production Scheduling - A Case Study at Perstorp 2014 Ingår i: 24th European Symposium on Computer Aided Process Engineering, PTS A and B. - : Elsevier. - 1570-7946. ; 33, s. 511-516, s. 511-516 Konferensbidrag (refereegranskat)abstract Planning and scheduling are functions that have large economic impact in the chemical process industry. For integrated sites with many interconnected production areas, obtaining production schedules that respect all production-related constraints is a complex task. One important issue is the constraints due to disturbances in utilities, such as steam and cooling water. These are often site-wide disturbances that may make it impossible to maintain desired production rates in several production areas at a site. In this study, scheduling at two levels of the functional hierarchy at a site of a world lead chemical industry, Perstorp, is handled. The activities are denoted production scheduling (PS) and detailed production scheduling (DPS). Real data of incoming orders and utility disturbances are used to produce a production schedule and detailed production schedule for one month. The PS and DPS problems are formulated as optimization problems, where production-related constraints such as production rate constraints, inventory limitations, and start-up costs are included. The objective functions of the PS and DPS problems are formulated to reflect the importance of different issues at the site. The procedure aims to show how the hierarchical optimization framework may be used to provide decision support for how to operate the production at a site in order to maximize profit while minimizing the effects of site-wide disturbances.
16.	Morandin, Matteo, 1981, et al. (författare) A cost targeting method for studying investment on heat exchanger network for collection of industrial excess heat 2015 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 37, s. 761-766 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract This paper discusses the design of water based heat collection system for recovery of industrial excess heat. The focus in on the problem of finding the optimal combinations of excess heat sources minimizing heat exchanger network capital costs for different amounts of total recovered heat. A cost targeting approach based on vertical heat transfer between hot process streams and the heat collection medium in Pinch Analysis diagrams is used. The set of process streams where heat shall be recovered is found by solving an optimization problem where heat recovery is maximized while minimizing the capital costs simultaneously. A genetic algorithm based optimization tool is used. The analysis is conducted for three plants belonging to a chemical cluster. The results are compared with results from previous investigations in which the process excess heat sources were chosen based on their incremental heat contribution. The new approach presented in this work allows identifying a much larger set of solutions as well as considerably lower capital costs for similar amount of recovered heat in cases when process streams largely differ in terms of temperature levels and heat transfer properties.
17.	Musulin, Estanislao, et al. (författare) Closing the Information Loop in Recipe-Based Batch Production 2005 Ingår i: European Symposium on Computer-Aided Process Engineering-15 : 38th European Symposium of the Working Party on Computer Aided Process Engineering : ESCAPE-15 (Computer-aided chemical engineering). - 1570-7946. - 0444519874 ; 20, s. 1381-1386 Konferensbidrag (refereegranskat)abstract In addition to the basic regulatory functions, a batch control system must support production planning and scheduling, recipe management, resource allocation, batch report generation, unit supervision and exception handling. A closed-loop framework is presented in this work that integrates decision support tools required at the different levels of a decision-making hierarchical batch control system. Specifically, the proposed framework consists of a reactive batch scheduler (MOPP) and a fault diagnosis system (ExSit-M) developed by the Universitat Politècnica de Catalunya, and a S88-recipe-based coordinator (JGrafchart) developed by the Lund University. These tools need to exchange information to obtain optimal utilization of the production plant. The complete integrated system is built using a general recipe description and other guidelines from ISA S88 standard.
18.	Papadokonstantakis, Stavros, 1974, et al. (författare) Superstructure investigation for P-recovery technologies integration with macroalgae based hydrothermal liquefaction 2018 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 44, s. 1753-1758 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract The aim of this work is to identify profitable and environmentally benign technological paths connecting phosphorus (P) recovery with macroalgae based hydrothermal liquefaction (HTL). For this purpose, a thorough literature review of relevant technologies in different fields of application was carried out. Together with a citation network analysis (CNA) a framework comprising qualitative and quantitative information about process significance, conditions, material and energy flows for a comprehensive list of potentially involved technologies was developed. On the basis of this information framework, processes were combined into a superstructure of options for P-recovery from macroalgae based HTL. Based on criteria such as technology maturity and severity of process conditions, two different but not mutually exclusive approaches for utilizing HTL waste streams were identified: exploiting the carbon and/or the nutrients potential of the streams. The process layout selected consists of hydrothermal liquefaction, catalytic hydrothermal gasification (CHG), incineration of solid residues, acidic leaching of incineration ashes, crystallization and precipitation of P in form of magnesium ammonium phosphate (struvite), methane steam reforming and biocrude upgrading through hydrotreatment. The selected layout's model was based on HTL reaction kinetics (kinetic constants extrapolated from experiment data and verified with laboratory results from HTL of macroalgae Ulva Lactuca collected from several sites of the Swedish coast) and on performances averaging (according to literature sources) for the other subprocesses sections. Net revenues as high as 21 $/tdry macroalgaewere predicted, coming mainly from upgraded oil and a small part from struvite, while including material and energy costs for operating the system. This revenue is highly affected by the cost of the macroalgae feedstock. Finally, environmental aspects and constraints related to the process, were addressed and evaluated with the cumulative energy demand (CED) indicator, which resulted stable around 34 MJeq/kgproducts.
19.	Papadopoulos, A. I., et al. (författare) A Framework for the Integration of Holistic Sustainability Assessment in Computer-Aided Molecular Design 2019 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 46, s. 13-18 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract We propose the integration of a holistic sustainability assessment framework in computer-aided molecular design (CAMD). The framework enables the assessment of life cycle (LCA) and safety, hazard and environmental (SHE) impacts from cradle-to-gate of chemicals designed through CAMD. It enables the calculation of an overall of 14 sustainability-related indices, with some of them aggregating several impact categories. Lack of models and data gaps in property prediction are addressed systematically through a data mining approach which exploits on-line similarity assessment with existing molecules for which data exist or can be predicted. The framework is implemented both simultaneously with CAMD or after CAMD to assess the designed solvents. A case study is presented on the design of phase-change solvents for chemisorption-based post-combustion CO2 capture. Results indicate that the proposed approach enables the identification of verifiably useful phase-change solvents which exhibit favourable performance trade-offs compared to a reference CO2 capture solvent.
20.	Ramin, Pedram, et al. (författare) Fault detection in a benchmark simulation model for wastewater treatment plants 2022 Ingår i: 14th International Symposium on Process Systems Engineering. - 1570-7946. - 9780323851596 ; , s. 1363-1368 Bokkapitel (refereegranskat)abstract The International Water Association (IWA) Benchmark Simulation Models (BSM1 and BSM2) have been successfully used in both industry and academia to test and verify control strategies in wastewater treatment plants (WWTPs). In this study, a new (plant- wide) benchmark simulation model, the BSM2-LT, is developed to evaluate monitoring algorithms. This platform provides opportunities to generate various sensor/actuator and process faults. To make this realistically, different Markov-chain models are used to re- create the alternation of sensor/actuator states based on predefined occurrence probability. The same principle is used to describe the occurrence of toxic/inhibitory compounds. Using this platform, one can test the performance of a monitoring algorithm such as a fault detection method. To demonstrate this in an example, a multivariate method based on adaptive dynamic principal component analysis (dPCA) was used to detect faulty events. The performance of the monitoring algorithm is evaluated with a penalization index, scoring from 0 to 100. While the tested method had a good false alarm score, it resulted in a low false acceptance. While the results could be certainly improved, the main focus of this study is the benchmark simulation model and not presenting a well optimized monitoring algorithm. The software which will be produced and freely distributed in the near future, will allow an objective evaluation of monitoring algorithms for WWTPs for any user.
21.	Sellberg, Anton, et al. (författare) Development and Optimization of a Single Column Analog Model for a Multi-Column Counter-Current Solvent Gradient Purification Process 2017 Ingår i: 27th European Symposium on Computer Aided Process Engineering. - 1570-7946. - 9780444639707 - 0444639705 ; 40, s. 187-192 Bokkapitel (refereegranskat)abstract This contribution presents a modeling and optimization method for multi-column counter-current purification (MCSGP) processes. The model is based on conventional column models and by using the symmetric and cyclic steady state characteristics of the process a single column analog model was developed. The model have been used for dynamic optimization of the MCSGP process. The optimization was based on a simultaneous method where the control and state variables were discretized using a direct and local collocation method on finite elements in the temporal dimension and a finite volume weighted essentially non-oscillatory (WENO) scheme in the spatial dimension. The resulting nonlinear program (NLP) were solved using an interior point method.The case study presented shows that the zero-order hold elution trajectories, developed for single column batch operation, can be extended to semi-continuous multi-column chromatography with product recycling. The optimization results is composed of a set of operating conditions where the product was upgraded to 95% purity with 99% process yield.
22.	Sellberg, Anton, et al. (författare) Multi-flowrate Optimization of the Loading Phase of a Preparative Chromatographic Separation 2018 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. - 9780444642356 ; 43, s. 1619-1624 Bokkapitel (refereegranskat)abstract This contribution consists of a multi-flow rate optimization method to maximize the key performance indicators, yield, degree of resin utilization and productivity for a chromatographic loading step. The protein adsorption to the resin is modeled using a mechanistic column model with a steric mass action adsorption isotherm. The model was used to optimize the flow rate trajectories and the loading duration by using a simultaneous method where the controls and state variables were discretized using a direct and local collocation method on finite elements in the temporal dimension and a finite volume weighted essentially non-oscillatory scheme in the spatial dimension. The discretized nonlinear program was solved using an interior point method. The two and three dimensional pareto fronts for the multi-objective optimization are presented and the multi-flow rate strategy showed considerable improvement in all objectives at different points on the pareto front.
23.	Shavalieva, Gulnara, 1987, et al. (författare) Knowledge mining from scientific literature for acute aquatic toxicity: classification for hybrid predictive modelling 2022 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 51, s. 1465-1470 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract This work proposes a systematic method consisting of state-of-the-art text processing approaches and human-machine interaction for the extraction of useful sentences and data in tabular, graphical, and numerical form, containing information particularly relevant for hybrid modelling. It is applied to the domain of acute aquatic toxicity of chemicals, which is particularly relevant for the safety, health, and environmental hazard assessment of chemicals. Nearly 400 papers from 2000-2021 were identified and processed with the proposed method. The results indicate that the vast amount of knowledge can be efficiently processed in orders of magnitude faster than conventional methods without loss of detail and interpretation depth. The information is in a form that can be useful in hybrid modelling with respect to model and predictor selection, prioritization, and constraints, addressing data gaps, and validating and interpreting model performance.
24.	Shavalieva, Gulnara, 1987, et al. (författare) Prediction of Sustainability Related Properties: Data Science Methods with Incorporated Prior Knowledge 2020 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 48, s. 1897-1902 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Many of the registered chemicals, newly synthesized or long existing, lack information on their hazard for the environment and human health. To perform the holistic safety assessment of chemicals, data on molecular properties, mostly obtained by test on living organisms, are collected. However, extensive experimentation is neither economically feasible nor ethical, and thus development of accurate prediction models is required. The recent advances in the area are associated with data science methods; however, there are certain limitations of these models with respect to their transparency, interpretability or even availability of well distributed training data to ensure robust generalization. Hybrid models combining machine learning with prior knowledge of the research field can potentially provide the solution to these limitations. The current study presents the first step of creating hybrid models, namely extraction of knowledge that can be utilized to create prior knowledge for future incorporation into hybrid models.
25.	Shavalieva, Gulnara, 1987, et al. (författare) Sustainability assessment using local lazy learning: The case of post-combustion CO2 capture solvents 2018 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 44, s. 823-828 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract The consideration of sustainability is very important for the assessment of life cycle, environmental, health and safety properties of chemicals used in various applications. The screening of wide ranges of molecular structures, prior to the identification of the optimum and most sustainable options, requires the use of efficient and inclusive predictive models. Group contribution (GC) models are popular for the evaluation of numerous molecular options, but they support the calculation of few properties related to sustainability, while their predictive capabilities are often limited by significant data gaps. To address such challenges, we propose the use of a local learning approach as a means of evaluating sustainability properties for a wide range of molecular structures. Supplementing GC methods with data mining ones, such as local lazy learning approaches and exploiting molecular similarities has a potential to improve the predictive capacity of sustainability indices and offers an alternative when GC methods or empirical models are not available for life cycle assessment (LCA) and environmental, health and safety (EHS) hazard assessment indicators. The proposed approach is applied to predict a set of properties (bioaccumulation, persistence and acute aquatic toxicity) of 101 commercial solvents for post-combustion CO2capture.
26.	Svensson, Elin, 1980 (författare) Optimal Multi-Period Investment Analysis for Flexible Pulp Mill Utility Systems 2015 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. ; 37, s. 1853-1858 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract The techno-economic potential for new technologies in pulp mills is conventionally studied assuming annual averages, based on the assumption that the pulp mill is continuously operated at a constant production rate close to its design capacity. Recent work has shown, however, that a technology, such as lignin extraction, which can improve the operating flexibility of the pulp mill utility system, has a value associated with its flexibility that is not captured in such average-value models. These previous results indicated a risk of significant errors if heat load variations were not properly modelled. This paper presents a multi-period optimization model for the planning of design and operating decisions connected to pulp mill utility systems, which in this work has been extended with back-pressure and condensing turbine models. The model optimizes technology selection, equipment capacities and operating loads under the influence of demand variations, considering part-load efficiencies and operating load limits. Application of the model to an illustrative example showed that lignin extraction can compete with electricity production already at a lignin price of 22 €/MWh in the presence of variations due to poor off-design performance for the turbines. This demonstrates the usefulness of the proposed modelling approach.
27.	Tallvod, Simon, et al. (författare) A novel process design for automated quality analysis in an integrated biopharmaceutical platform 2022 Ingår i: 32nd European Symposium on Computer Aided Process Engineering. - 1570-7946. - 9780323958790 ; 51, s. 619-624 Bokkapitel (refereegranskat)abstract This contribution describes a novel process design consisting of the implementation of a high performance liquid chromatography (HPLC) system into an existing integrated biopharmaceutical purification platform in order to extend the possibilities of analysis. This setup is controlled by a custom-made set of software tools, namely the combination of Orbit along with a C# based program called Satellite, which is used to link the HPLC system to Orbit. By using this process design, automated analysis of the continuous process flow is made possible, generating full wavelength spectra, and automated pool quality analysis. These spectra contain at least an order of magnitude more data compared to a standard chromatogram, which can be utilized for further analysis, while the pool quality analyses can be used for making decisions regarding how to proceed with a particular pool. The results of the study show the successful implementation of automated analytic tools to the purification process, which also indicates that the process carries promise as a generalizable platform for Orbit-controlled designs for different analysis purposes.
28.	Tan, S. T., et al. (författare) SMART : An Integrated Planning and Decision Support Tool for Solid Waste Management 2014 Ingår i: Computer Aided Chemical Engineering. - : ELSEVIER SCIENCE BV. - 1570-7946. ; 33, s. 271-276, s. 271-276 Tidskriftsartikel (refereegranskat)abstract Solid waste management (SWM) system combined waste streams, waste collection, treatment and disposal methods are critically important to a regional, to achieve environmental economic and societal benefits. Decision-makers often have to rely on optimization models to examine a cost effective, environmentally sound waste management alternative. This paper presents a new systematic framework for long term effective planning and scheduling of SWM. This framework has been converted into software called Solid Waste Management Resource Recovery Tool (SMART). SMART is a first-of-a-kind SWM tool to facilitate the tradeoffs analysis between technical, economical, and environmental at national, regional, state, province, or community level. This simple tool is useful for decision makers for the selection of MSW technology including incineration, landfill, composting and recycling are while minimising the costs and meet CO2 reductions target. The developed tool was applied in Iskandar Malaysia as a case study.
29.	Yamanee-Nolin, Mikael, et al. (författare) Single-shooting optimization of an industrial process through co-simulation of a modularized Aspen Plus Dynamics model 2019 Ingår i: Computer Aided Chemical Engineering. - 1570-7946. - 9780128186343 ; 2019 Tidskriftsartikel (refereegranskat)abstract The Python Module Coupler (PyMoC) is a tool for co-simulation of Aspen Plus Dynamics modules that together make up an overall process flowsheet. The tool requires only user input in the form of file paths to Aspen Plus Dynamics modules, and it is able to automatically make the required connections there between, and keep track of the simulation whilst updating the streams regularly. This contribution briefly discusses the implementation and mechanisms of PyMoC, and then applies it to a multi-module, single-shooting constrained optimization problem, where an industrial set-up consisting of an evaporator system coupled to a distillation column is studied. This serves as a showcase of PyMoC's functionality and usability, as well as its potential in serving as a helpful tool for practitioners of model-based studies who could benefit from modularizing their models. Utilizing PyMoC for this purpose, the optimization results indicate that the operating costs induced from the steam consumption can be reduced by 54% compared to a nominal operating case, but a holistic, full-process study is necessary to understand the full set of possibilities, causes, and effects.
30.	Yamanee-Nolin, Mikael, et al. (författare) Unbiased Selection of Decision Variables for Optimization 2017 Ingår i: 27 European Symposium on Computer Aided Process Engineering. - 1570-7946. - 9780444639653 ; 40, s. 253-258 Konferensbidrag (refereegranskat)abstract Complex chemical processes require complex simulation models. Selecting decision variables for optimization is increasingly difficult. This paper presents a study of a Subset Selection Algorithm (SSA) applied to the selection of decision variables to facili-tate a reduction of the decision variable combination sets to consider for a process designer, aimed towards improving said selection, optimization, and thereby resource efficiency. The results help conclude that SSA is able to reduce the consideration set of decision variable combinations for the process designer, and selects combination sets that are more effective in terms of minimizing the objective.

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