Characterization of an Automated Spinning‐Band Column as a Module for Laboratory Distillation

Bittorf, Lukas; Böttger, Nils; Neumann, Daniel; Winter, Alina; Kockmann, Norbert

doi:10.1002/ceat.202000602

Cited by 5 publications

(13 citation statements)

References 36 publications

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“…The HETP value for ambient pressure depending on band speed, gas factor, and liquid loading was already investigated in a previous publication . Here we look closer in the following results at the dependency of the separation efficiency on the column pressure.…”

Section: Resultsmentioning

confidence: 51%

“…The general structure and operation is explained for the spinning band column before going into details of the features. Further details of the spinning band and behavior regarding flooding and mass transport are published in ref . The presented findings of design changes will be compared to the previous results.…”

Section: Column and Spinning Band Designmentioning

confidence: 82%

“…In the following, the HETP value of the two band designs is further investigated in the range of possible band speeds, where no flooding occurs. As described in the earlier publication, HETP values for the standard 30° band design vary between 5 and 10 cm depending on band speed and F-factors. In Figure , HETP values are compared for both designs.…”

Section: Resultsmentioning

confidence: 99%

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Spinning Band Distillation Column–Rotating Element Design and Vacuum Operation

Bittorf

Pathak

Kockmann

2021

Ind. Eng. Chem. Res.

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To lower the barriers to entry into modular production, applicable, flexible modules that can be integrated into modular plants are needed already in the laboratory environment for reaction and separation processes. Such a module with the continuous operated spinning band column for distillation is presented here. Modifications from the classical batch spinning band column extending the operating window and making the column more flexible are described. Particularly the variation of the slope of the spinning band as well as a flexible feeding system are investigated, where the height of the feeding position can be adjusted within the column. Furthermore, a vacuum unit is added to the column allowing for the separation of temperature-sensitive materials. The column achieves HETP values between 4 cm for vacuum operation and very low throughput of 3 g min–1 and 8 cm for ambient pressure and moderate throughputs of up to 8 g min–1. The operation range is limited by flooding effects to the gas factor range of 0.9 to 2.3 Pa0.5 and a liquid load between 3 and 10 m3 m–2 h–1. By changing the slope of the spinning band, it is possible to operate the column with higher separation performance but lower throughputs or, in contrary, with lower separation performance but higher throughputs. By adapting the feeding height, the separation can be moved either to the heavy or to the light key component. In combination with a modular automation and sensor system, the spinning band column represents a versatile and robust distillation tool.

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Section: Resultsmentioning

confidence: 51%

Section: Column and Spinning Band Designmentioning

confidence: 82%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Spinning Band Distillation Column–Rotating Element Design and Vacuum Operation

Bittorf

Pathak

Kockmann

2021

Ind. Eng. Chem. Res.

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“…At a certain point, depending on band speed, liquid loads, and vapor velocity, the liquid is accumulating, which results in flooding. For detailed information about the spinning band column and its behavior see 39, 40, 63, 64 Flooding can be seen visually but also detected by very steep rise of the pressure drop, which is measured via a pressure difference transmitter between bottom and head of the distillation column.…”

Section: Methodsmentioning

confidence: 99%

“…Multivariate time series data can be tricky to deal with as the temporal structure should be preserved in some way during the training process. One way to make supervised learning methods applicable to time series data is the sliding window method 40, which transforms data in such a way that past and “future” measurements are preserved for each data point. For this use case, the future pressure drop (Δ p t +1 , Δ p t +2 , …) will be predicted based on the past data of pressure drop and other significant parameters X i (…, Δ p t – 1 , X 1, t – 1 , … , Δ p t , X 1 ,t , …).…”

Section: Flooding Detection In the Distillation Column By ML Toolsmentioning

confidence: 99%

Flooding Prevention in Distillation and Extraction Columns with Aid of Machine Learning Approaches

Oeing

Neuendorf

Bittorf

et al. 2021

Chemie Ingenieur Technik

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Flooding of separation columns is a severe limitation in the operation of distillation and liquid‐liquid extraction columns. To observe operation conditions, machine learning algorithms are implemented to recognize the flooding behavior of separation columns on laboratory scale. Besides this, the investigated columns already provided the modular automation interface Module Type Package (MTP), which is used for data access of necessary sensor data. Hence, artificial intelligence (AI) tools with deep learning offer high potential for the process industry and allow to capture operating states that are otherwise difficult to detect or model. However, the advanced methods are only hesitantly applied in practice due to complex combination of operational sensing, data analysis, and active control of the equipment. This article provides an overview on how AI‐based algorithms can be implemented in existing laboratory plants. Process sensor data as well as image data are used to model the flooding behavior of distillation and extraction columns for stable and robust operational conditions.

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Design of Module Type Package Services for Modular Downstream Units and Process Analytic Technology

et al. 2023

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Modularization of process plants with its standardization activities is one of the current responses to react to dynamic markets, shorter product life cycles, and uncertain supply chains. Standardized solutions for intelligent process equipment assemblies with own automation promise high potential for chemical and pharmaceutical industries. Despite the standardized description of the module type package (MTP) and the corresponding service concept, the implementation of the service logic is left to the manufacturer, which often leads to finding various granular services for different process functions or assemblies. In this contribution, different service design approaches for a generic ‘separate’ service are investigated on the example of a solvent extraction and a distillation column. Additionally, a Raman spectroscope device for process analysis is implemented via MTP with an ‘analyze’ service. Pros and cons of the different service design approaches are discussed in the context of a fast and flexible process development in the laboratory.

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Characterization of an Automated Spinning‐Band Column as a Module for Laboratory Distillation

Cited by 5 publications

References 36 publications

Spinning Band Distillation Column–Rotating Element Design and Vacuum Operation

Spinning Band Distillation Column–Rotating Element Design and Vacuum Operation

Flooding Prevention in Distillation and Extraction Columns with Aid of Machine Learning Approaches

Design of Module Type Package Services for Modular Downstream Units and Process Analytic Technology

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