The objective of this study was to develop an optimized and heat integrated methanol production model that could simultaneously satisfy two pressing societal needs (reducing carbon-dioxide emission levels and decreasing the dependency on fossil fuel).

A steady-state methanol synthesis process was modeled in the Aspen Plus simulation environment after extensive research of the conventional methanol manufacturing process, catalytic systems, and kinetic models. Both the dimensional and operational process parameters of the created model were optimized with the help of the model analysis tool of Aspen Plus. Using Aspen Energy Analyzer's heat integration operation and the pinch analysis approach, an integrated energy network was designed.

Further, a comparative analysis of methanol yield from the developed model was performed using three different feedstocks (syn-gas, flue gas, coke oven gas). The result of these analysis showed that the yield from using high purity CO to produce methanol was significantly greater compared to other feedstocks 

Fig 02: Flowsheet of separation section

Fig 03: Schematic of the pilot fermenter

This study focuses on the replacement of conventional fuels with energy carriers of biological origin that have less environmental effects, a necessity in today's technologically advanced world. Bioethanol is a possible alternative to fossil fuel produced by microbial fermentation. Sugarcane molasses and sugarcane industry waste can serve as inexpensive carbon sources for microorganisms producing bioethanol. Improving bioethanol output on an industrial scale is crucial for making the process commercially viable and lucrative. As a tropical nation, the industrial yield of bioethanol in Bangladesh declines with increasing temperature, notably during summer, when utilizing S. cerevisiae.

Our goal was to investigate several process parameters, such as temperature, initial sugar content, and aeration rate, on a pilot size in order to determine the likelihood of boosting ethanol yield on a commercial level. 

The goal of this research is to explore the feasibility and potential benefits of integrating Aspen HYSYS with Python. Aspen HYSYS is an integrated engineering simulation package that is widely used in industry and academia to simulate and predict the behavior of materials and systems under a wide range of conditions. On the other hand, Python is a high-level interpreted language that has powerful libraries and object-oriented programming functionality which make it particularly well-suited to scientific computing as well as engineering applications. Research is underway to identify ways that Aspen HYSYS and Python can be integrated to perform complex simulations more efficiently and accurately, which could reduce the cost and time of designing and manufacturing new products.

Fig 05: A snippet of Python code used for this project.