This work gives a detailed description of the models, methods, and equipment used in a bachelor’s degree lab course. The connections between simulation results and real-world data are highlighted and tools for making the models useful for process design tasks are portrayed. The models cover the production chain for fuel-grade bioethanol, starting from the fermentation of sugar with yeast. In only one semester (14 weeks with 180 minutes per week) the students achieve to produce high-purity ethanol. Some exemplary results of the process designs and their comparison to the realized intermediate and final products are given together with production cost data.

Middle vessel batch distillation (MVBD) is an alternative configuration of the conventional batch distillation with improved sustainability index. This article presents a comparison of model-based control approaches for MVBD column. Specifically, two control approaches - sequential (open-loop optimization followed by closed-loop control) and simultaneous (closed-loop optimization and control) are pursued. These two approaches are compared in terms of their effectiveness, overall performance, and robustness to plant-model mismatch. The effectiveness of these control strategies is illustrated using a simulation case study of a ternary mixture separation consisting of benzene, toluene and o-xylene.

A generally applicable framework for the evaluation of the sustainability of distillation processes is proposed by aligning indicators directly to selected sustainable development goals (SDGs) created by the United Nations. The indicators are related to the goals good health and well-being (SDG 3), clear water and sanitation (SDG 6), affordable and clean energy (SDG 7), decent work and economic growth (SDG 8), industry, innovation and infrastructure (SDG 9), responsible consumption and production (SDG 12), climate action (SDG 13) and life below water (SDG 14). A total of 12 sustainability indicators, including human toxicity potential, wastewater generation, water consumption, renewable energy share, energy demand, material footprint, profit, waste generation, recycling ratio of waste, greenhouse gas emission, eutrophication potential and acidification potential are assigned to selected SDGs. The application of the indicators is illustrated by two case studies: a batch (BD) and a conti... [more]

Multi-component batch distillation, wherein multi-component mixtures are separated using a single column, is a crucial separation technique in the chemical industry. Traditionally, the components are separated in the descending order of volatility (direct sequence). Similar to continuous distillation, a specific separation sequence can optimize batch distillation. This work aims to generate such optimal sequence for a batch distillation in a computationally efficient manner. Specifically, the proposed approach extends the marginal vapor rate method, which is used for sequencing continuous distillation to multi-cut batch separation. The approach addresses challenges arising due to dynamic nature of batch distillation. The proposed methodology is validated using simulation case studies.

This model uses the CHEMCAD unit operation Batch Column together with tools for data reconciliation and optimization. Some experimental data is included.
It is used as a template in the course Green Processes at Berlin University of Applied Science (BHT), where students use it to regress measured data from lab experiments and to design an optimal process.

Wine batch distillation in a copper pot still heated directly by combustion is unusual. It is a niche sector. Few studies are available on the subject and even fewer have studied it from a thermal point of view. In a context of ecology awareness and regularly increasing gas taxes, finding less energy consuming and more performing solutions has become necessary. Two methods already exist to recover energy for such pot stills, however improvements could be made. The present study focuses on the heating zone of an experimental pot still. First, a thermal diagnosis based on a nodal model is conducted in transient regime. The major sites of energy expenditure and waste are thus identified and quantified. Results highlight significant losses both in combustion smoke and by conduction to the environment resulting from a limited thermal performance of the system. Proposals are then made to enhance it. For instance, the preheating could be optimized and more thermal waste could be recovered.

In this work, an algorithm was developed to determine different possibilities of distillation cuts to support productivity and improve the final quality of cachaça, a Brazilian spirit beverage. The distillation process was simulated using the Aspen Plus® software, considering a wide range of fermented musts compositions available in the literature obtained by fermentation with different yeast strains. Twenty-four simulations were carried out considering eight compounds as follows: water and ethanol (major compounds); acetic acid, acetaldehyde, ethyl acetate, 1-propanol, isobutanol, and isoamyl alcohol (minor compounds). The calculations considered a long-time process, i.e., until almost all the ethanol in the fermented must was distilled. The algorithm enabled the identification of countless distilling cuts, resulting in products with different alcoholic grades and process yields. One fermented must became viable to produce cachaça after the suggested non-traditional method of cuts pro... [more]