Objectives: To implement Python algorithms to control Aspen HYSYS simulation and generate synthetic data to develop automated data-driven process optimization model.

Methods: A flowsheet of Condensate Fractionation Unit (CFU) was developed and then simulated in Aspen HYSYS. The PyWin32 library, which is a Python algorithm that allows easy access to Window’s Component Object Model (COM), was used to control HYSYS and Microsoft Excel. A Python program was written to create statistical Latin Hypercube Sampling (LHS) method, that generates a near-random sample of parameter values from a multidimensional distribution, giving each simulation case a portion of big LHS sample to execute different cases. After creating a big LHS data sample, HYSYS simulation was run, and the resulting simulation variables of interest were printed to the screen after running all simulation cases, the resultant parameters were stored in an Excel sheet.

Results: A variety of parameters can affect the optimization of CFU unit, like different gas composition (High LPG, Low LPG), condensate API (High API, Low API), condensate to gas ratio from gas platforms (High, Low), oil platforms (High API, Low API), sulfur content (Normal, Max) and variation in inlet temperature (Low, High). A combination of all these factors results in a total of 64 cases of HYSYS simulation that needed to be considered previously. The optimization of CFU unit by HYSYS-Python integration has exhibited promising performance by automating this daunting and time-consuming task. This integration also helped to overcome the major limitations of HYSYS: slowness, large amount of ROM/RAM usage and inability to customize.

Conclusions: Traditionally, theoretical engineering knowledge were used to reduce the number of simulation cases during optimization, still important operating conditions might be overlooked while reducing the number of simulation cases as the composition of condensate could not be easily foreseen. However, one major limitation of this model is that some HYSYS unit operations cannot be navigated using keyboard shortcuts (ex. AdjustOp) and mouse control could lead to automation error.

The substitution of conventional fuels by the energy carriers of biological origin with easing environmental consequences is a requirement of today’s advanced society. Bioethanol is a promising alternative to fossil fuel, derived from renewable biomass through fermentation by microorganisms. Sugarcane molasses, waste from sugar industry can be low-cost C-source for microorganisms to produce bioethanol. It is essential to improve bioethanol yield on an industrial scale to make the process commercially attractive and profitable. Being a tropical country industrially yield of bioethanol in Bangladesh reduces with rising of temperature using Saccharomyces cerevisiae. In this context, this study is aimed at analyzing different process parameters e.g., temperature, initial sugar concentration and aeration rate to enhance industrial scale bioethanol production.

The growth profile of Saccharomyces cerevisiae was monitored in sugar cane molasses in pilot scale (100L) to observe the effects of temperature in ethanol production. At the first step, the raw molasses was collected from molasses storage tank and diluted with water until the concentration of the molasses solution went down from 85 to 19 brix. Meanwhile, yeast was collected from pre-cultured pitching vat about 20L. Then, both seed yeast and diluted molasses were added to the fermentation vat (Pilot Scale). It has a TIC (Temperature Indication Controller) that allows it to carry out the fermentation at a constant temperature. Fermentation was carried out for about 30-36 hours at 25, 30, 35, 38 and 400C maintaining other parameters as similar as industry.

The study found that at 300C most sugars were converted into ethanol with the action of zymase enzyme secreted from Saccharomyces cerevisiae. But at the industrial level, the fermentation temperature went to about 40-450C which severely hinders the microbial activity, since the optimum temperature for Saccharomyces cerevisiae is 25-350C. Moreover, in industries of Bangladesh, there is no heat exchange mechanism is installed to keep the temperature in favor of fermentation process.

It is recommended, if the temperature can be maintained around at 300C by installing heat exchange mechanism, there might be an increment of ethanol production at summer season in Bangladesh.

The ‘scars’ left by wars in the course of time where the chemical weapons(CW) have also been involved has become one of the major concerns of twenty first century. During the last century, several millions died due to the deliberate release of pathogens or toxins and chemical weapons. Sarin gas, Mustard gas, Phosgene gas, Chlorine gas etc. are the deadliest CWs invented till date. Weapons always bring destruction, instead of using these substances as weapons it can be used for various profitable and peaceful purposes. As for example: Mustard gas – from the Great War to frontline chemotherapy (cancer treatment), Nuclear power plant, Chlorine is used as germicide in different water purifier, Phosgene is an important precursor in the manufacture of plastics. Initiative taken by governments and individuals can have a great impact on the safety and security of all people.