Flowsheet simulations of chemical processes on an industrial scale require the solution of large systems of nonlinear equations,so that solvability becomes a practical issue.Additional constraints from technical,econo...Flowsheet simulations of chemical processes on an industrial scale require the solution of large systems of nonlinear equations,so that solvability becomes a practical issue.Additional constraints from technical,economic,environmental,and safety considerations may further limit the feasible solution space beyond the convergence requirement.A priori,the design variable domains for which a simulation converges and fulfills the imposed constraints are usually unknown and it can become very time-consuming to distinguish feasible from infeasible design variable choices by simply running the simulation for each choice.To support the exploration of the design variable space for such scenarios,an adaptive sampling technique based on machine learning models has recently been proposed.However,that approach only considers the exploration of the convergent domain and ignores additional constraints.In this paper,we present an improvement which particularly takes the fulfillment of constraints into account.We successfully apply the proposed algorithm to a toy example in up to 20 dimensions and to an industrially relevant flowsheet simulation.展开更多
Modern production processes in chemical, pharmaceutical and biological industries are characterized by complex process structures, which consist of different apparatuses and process steps. Modeling the entire process ...Modern production processes in chemical, pharmaceutical and biological industries are characterized by complex process structures, which consist of different apparatuses and process steps. Modeling the entire process requires simulating all units altogether, while taking into account interconnections between them, Nevertheless, in the area of solids processing, there is nowadays an unfilled gap from the side of computer support of process modeling in allowing effective optimization and prediction of the behavior of the whole plant, This paper presents a tool for flowsheet simulation which allows the simulation of the stationary behavior of complex processes dealing with solids and its extension towards dynamic modeling, Also, a new simulation concept is proposed on the basis of the multiscale approach. On the macroscale, fiowsheet simulation is performed with the help of the SolidSim system. Parameters for the macromodels in Solid-Sim are predicted by microscale simulation. The models for the two scales are then coupled by inter-scale communication laws. Application of the proposed modeling concept is shown by an example of fluidized bed granulation.展开更多
基金This work was developed within the Fraunhofer Cluster of Excellence“Cognitive Internet Technologies”.
文摘Flowsheet simulations of chemical processes on an industrial scale require the solution of large systems of nonlinear equations,so that solvability becomes a practical issue.Additional constraints from technical,economic,environmental,and safety considerations may further limit the feasible solution space beyond the convergence requirement.A priori,the design variable domains for which a simulation converges and fulfills the imposed constraints are usually unknown and it can become very time-consuming to distinguish feasible from infeasible design variable choices by simply running the simulation for each choice.To support the exploration of the design variable space for such scenarios,an adaptive sampling technique based on machine learning models has recently been proposed.However,that approach only considers the exploration of the convergent domain and ignores additional constraints.In this paper,we present an improvement which particularly takes the fulfillment of constraints into account.We successfully apply the proposed algorithm to a toy example in up to 20 dimensions and to an industrially relevant flowsheet simulation.
文摘Modern production processes in chemical, pharmaceutical and biological industries are characterized by complex process structures, which consist of different apparatuses and process steps. Modeling the entire process requires simulating all units altogether, while taking into account interconnections between them, Nevertheless, in the area of solids processing, there is nowadays an unfilled gap from the side of computer support of process modeling in allowing effective optimization and prediction of the behavior of the whole plant, This paper presents a tool for flowsheet simulation which allows the simulation of the stationary behavior of complex processes dealing with solids and its extension towards dynamic modeling, Also, a new simulation concept is proposed on the basis of the multiscale approach. On the macroscale, fiowsheet simulation is performed with the help of the SolidSim system. Parameters for the macromodels in Solid-Sim are predicted by microscale simulation. The models for the two scales are then coupled by inter-scale communication laws. Application of the proposed modeling concept is shown by an example of fluidized bed granulation.
