This work investigates a procedure to design an Industrial Ecosystem for sequestrating CO2 and consuming glycerol in a Chemical Complex with 15 integrated processes. The Complex is responsible for the production of methanol, ethylene oxide, ammonia, urea, dimethyl carbonate, ethylene glycol, glycerol carbonate, β-carotene, 1,2-propanediol and olefins, and is simulated using UNISIM Design (Honeywell). The process environmental impact (EI) is calculated using the Waste Reduction Algorithm, while Profit (P) is estimated using classic cost correlations. MATLAB (The Mathworks Inc) is connected to UNISIM to enable optimization. The objective is granting maximum process sustainability, which involves finding a compromise between high profitability and low environmental impact. Sustainability maximization is therefore understood as a multi-criteria optimization problem, addressed by means of the Pareto optimization methodology for trading off P vs. EI.

The dynamics of flash drums is simulated using a formulation adequate for phase modeling with equations of state (EOS). The energy and mass balances are written as differential equations for the internal energy and the number of moles of each species. The algebraic equations of the model, solved at each time step, are those of a flash with specified internal energy, volume and mole numbers (UVN flash). A new aspect of our dynamic simulations is the use of direct iterations in phase volumes (instead of pressure) for solving the algebraic equations. It was also found that an iterative procedure previously suggested in the literature for UVN flashes becomes unreliable close to phase boundaries and a new alternative is proposed. Another unusual aspect of this work is that the model expressions, including the physical properties and their analytical derivatives, were quickly implemented using computer algebra.

Pyrolysis gasoline - PYGAS - is an intermediate boiling product of naphtha steam cracking with a high octane number and high aromatic/unsaturated contents. Due to stabilization concerns, PYGAS must be hydrotreated in two stages. The first stage uses a mild trickle-bed conversion for removing extremely reactive species (styrene, dienes and olefins) prior to the more severe second stage where sulfured and remaining olefins are hydrogenated in gas phase. This work addresses the reaction network and two-phase kinetic model for the first stage of PYGAS upgrading. Nonlinear estimation was used for model tuning with kinetic data obtained in bench-scale trickle-bed hydrogenation with a commercial Pd/Al2O3 catalyst. On-line sampling experiments were designed to study the influence of variables - temperature and spatial velocity - on the conversion of styrene, dienes and olefins.

A simplified approach is presented to the transient atmospheric dispersion of accidental releases of natural gas, originated by leakages in pressurized ducts on sea level. In this scenario, shut-off valves are used for instantaneous shutdown of tube operation, isolating the harmful inventory, whose transient release is simulated providing estimations of gas instantaneous atmospheric concentration. The analysis further covers the transient behavior inside the ducts through a leakage model and the occurrence of multiple ruptures, synchronized or not, with known spatial distribution. The time-space dispersion model employed accounts for: (i) atmospheric conditions, (ii) wind speed, (iii) transient conditions of gas release into the atmosphere, and (iv) plume rise. The process of continuous release is approximated by a finite sequence of pulses, known as "puffs". Discrete puffs have volume dependent on release intensity, which depends on the actual time instant, as inventory decreases due to emission.

Unsaturated, nitrogenated and sulfured compounds may reach undesirable levels in lubricant base oils, requiring hydrotreatment (HDT) at high temperatures and pressures. HDT processes are well known for their high capital and operational costs due to the use of hydrogen, compressors and multistage heterogeneous reactors. Process costs are thus highly dependent on the applied conditions. An oversized process entails unnecessary costs and capital investment. On the other hand, mild reaction conditions lead to unspecified products. This work analyzes the process using a compositional modeling and a kinetic framework developed previously (Barbosa et al., 2002) for the HDT of lubricant base oils. The industrial reactor is rigorously modeled on an adiabatic and multistage configuration. For the remaining equipment in the flowsheet, we adopt shortcut models for compressors and exchangers. The process is then optimized in terms of its variables subject to product specification constraints.