Computer Aided Chemical Engineering

Journal: Computer Aided Chemical Engineering

Publisher

Elsevier

ISSN

1570-7946

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Publications 1 - 10 of 106

Uncovering the True Cost of Ionic Liquids using Monetization
Baaqel, Husain; Tulus Merlich, Victor; Chachuat, Benoît; et al. (2020)
Computer Aided Chemical Engineering ~ Proceedings of the 30th European Symposium on Computer Aided Process Engineering (ESCAPE30)
Due to their attractive properties, ionic liquids have found their way into many applications where they show high potential to replace existing chemicals. However, rising concerns over their ecological impacts, e.g., toxicity and biodegradability, and high cost have limited their use. Techno-economic and life cycle assessment studies were carried out to compare ionic liquids with existing solvents, yet the outcome of these analyses is often hard to interpret, as multiple metrics need to be considered simultaneously between which trade-offs exist. Here, for the first time the concept of monetization is coupled with process simulation and life cycle assessment to estimate the true cost of four lignocellulosic biomass pretreament solvents: triethylammonium hydrogen sulfate [TEA][HSO4], 1-methylimidazolium hydrogen sulfate [HMIM][HSO4], acetone from fossil sources and glycerol from renewable sources. The results show that monetized cost can be higher than or as high as the production cost. The real cost of production accounting for externalities can be more than 100% of direct costs estimated using conventional economic assessment methods. Our results show that [TEA][HSO4] has the lowest cost, while glycerol has the highest cost. We expect this to be a starting point for future studies targeting the design of more sustainable ionic liquids. © 2020 Elsevier B.V.
Decarbonisation of the Industrial Sector by means of Fuel Switching, Electrification and CCS
Luh, Sandro; Budinis, Sara; Schmidt, Thomas; et al. (2018)
Computer Aided Chemical Engineering ~ 28th European Symposium on Computer Aided Process Engineering
The industrial sector will have to undergo major changes in order to reduce its emissions with the goal of climate change mitigation. In this context, the iron and steel subsector accounts for the highest CO2 emissions share. This work uses a simulation model of the global energy system and quantifies the impacts of different measures for CO2 reduction (such as fuel switching, electrification and Carbon Capture and Storage - CCS) on investment and operation decisions. The reported scenarios consider the implementation of a CO2 price as a policy instrument to decarbonise the industrial sector. The selected case study covers steel production in the USA up to the year 2050. The results show that single measures such as fuel switching, electrification and CCS adoption alone have a limited impact on the decarbonisation of the iron and steel sector and should be rather implemented all together in an integrated approach towards climate change mitigation.
Assessing the Environmental Potential of Hydrogen from Waste Polyethylene
Salah, Cecilia; Cobo Gutiérrez, Selene; Guillén Gosálbez, Gonzalo (2022)
Computer Aided Chemical Engineering ~ 14th International Symposium on Process Systems Engineering
In 2019, nearly 370 million tonnes of waste plastic were generated, an amount that has been steadily increasing over the years. Here we assess hydrogen production from waste polyethylene in the context of a circular economy of plastics. Based on the gasification of polyethylene waste (wPG), we performed a Life Cycle Assessment (LCA) study following the ReCiPe method. Our results show that the wPG process coupled with carbon capture and storage (CCS) performs very well environmentally relative to other H2 production routes, outperforming steam methane reforming (SMR) with and without CCS and biomass gasification (BG) in the three endpoint impact categories.
Data-based tiered approach for improving pharmaceutical batch production processes
Eberle, Lukas G.; Sugiyama, Hirokazu; Papadokonstantakis, Stavros; et al. (2014)
Computer Aided Chemical Engineering ~ 24th European Symposium on Computer Aided Process Engineering
Enhancing yield in production is paramount for success in the increasingly competitive pharmaceutical industry, especially for manufacturers of costly biopharmaceutical products. Effort and complexity of implementing enhancements are forcing decision makers to first identify and quantify potentials and opportunities and then trigger process reviews efficiently. Data for supporting such quantifications have been traditionally recorded in the industry; the trend towards better accessibility of production data now facilitates consulting them and the need for developing appropriate tools gets evident. We present a four-level approach to convert production data into serviceable information, supporting the prioritization of processes and assisting real-life changes based on information from analysing production conditions. The approach was applied at a drug product manufacturing plant on a sample of 43 batches; main loss causes were identified and quantified. The three dominant loss sources account for nearly two-third of losses and are largely batch-size independent.
Shape Constrained Splines with Discontinuities for Anomaly Detection in a Batch Process
Villez, Kris; Habermacher, Jonathan (2015)
Computer Aided Chemical Engineering
Mixed-Integer Dynamic Scheduling Optimization for Demand Side Management
Baader, Florian J.; Mork, Maximilian; Xhonneux, André; et al. (2020)
Computer Aided Chemical Engineering ~ 30th European Symposium on Computer Aided Process Engineering
With fluctuating electricity prices, demand side management (DSM) promises to reduce energy costs. DSM of processes and energy supply systems requires scheduling optimization to consider transient behavior and binary on/off-decisions resulting in challenging mixed-integer dynamic programs. In this work, we present an efficient scheduling optimization approach that captures scheduling-relevant dynamics in a linear scale-bridging model and relies on collocation for time discretization. The resulting mixed-integer linear program (MILP) can be solved with state-of-the-art solvers. We apply the approach to a case study on building DSM. A detailed simulation model represents an office building, which allows load shifting through dynamic concrete core activation and is heated by a heat pump with minimum part-load. The DSM scheduling optimization approach reduces energy cost significantly compared to a rule-based scheduler without DSM if electricity price volatility is high. At the same time, the optimization is sufficiently fast to perform online scheduling.
Efficient Waste Management based on Scheduling Optimization of Waste Treatment Plants
Capón-García, Elisabet; Papadokonstantakis, Stavros; Hungerbühler, Konrad (2013)
Computer Aided Chemical Engineering ~ 23rd European Symposium on Computer Aided Process Engineering
Identification of multicomponent mass transfer by means of an incremental approach
Bardow, André; Marquardt, Wolfgang (2003)
Computer Aided Chemical Engineering ~ European Symposium on Computer Aided Process Engineering-13
In this work, an incremental approach to model identification is introduced. The new method follows the steps of model development in the identification procedure. This reduces uncertainty in the estimation problems. Furthermore, it allows the efficient exploitation of model structure and thereby reduces the computational expense substantially. The proposed method is applied to examples from binary and ternary diffusive mass transfer and its performance is compared to current approaches.
Flexibility-expansion planning for enhanced balancing-power market participation of decentralized energy systems
Nolzen, Niklas; Leenders, Ludger; Bardow, André (2021)
Computer Aided Chemical Engineering ~ 31st European Symposium on Computer Aided Process Engineering
The rising share of renewable energy sources in power supply and the shut-down of conventional power plants lead to a need for new providers of balancing power. Balancing-power could be newly provided by the flexibilization of decentralized energy systems. In this contribution, we propose flexibility-expansion planning for decentralized energy systems to account for investments in additional units for flexibilization. Flexibility-expansion planning leads to a stochastic optimization model for optimal investment decisions towards increased operational flexibility. The stochastic optimization model consists of a design optimization and a two-stage stochastic program. In a case study, the method is applied to a decentralized energy system participating in the German tertiary balancing-power market. Savings of up to 5.9 % can be achieved with additional investments in heat storage. Thus, flexibility-expansion planning allows operators of decentralized energy systems to optimally invest in flexible technologies for improved balancing-power market participation.
Efficiency Analysis of Utilities Use in the Batch Chemical Industry
Rerat, Claude; Straehl, Patrick; Papadokonstantakis, Stavros; et al. (2010)
Computer Aided Chemical Engineering ~ 20th European Symposium on Computer Aided Process Engineering

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