Heterogeneously catalyzed biodiesel production from Azadiricha Indica oil: Predictive modelling with uncertainty quantification, experimental optimization and techno-economic analysis.

This study presents predictive modelling with uncertainty analysis, optimization and techno-economic feasibility of Bio-catalyzed Biodiesel Production from Azidirica Indica Oil (BCBPAIO). Central Composite Design (CCD) predictive model and optimum conditions for BCBPAIO were developed in Design Expert software. The model uncertainty analysis was performed using Monte Carlo simulation. The BCBPAIO simulation and economic analysis were conducted in ASPEN Batch Process Developer V10. The correlation coefficient (R2) and adjusted R2 value of the CCD model were 0.9922 and 0.9780 respectively. CCD model certainty gave 73.51% with 100,000 trials; the oil transesterification optimum conditions gave 87.04% conversion with 3.62 wt% of catalysts; and methanol to oil molar ratio of 8:1 at 59 °C for 4 h. The annual production cost, total capital investment, payback time and internal rate of returns are $ 3537105, $ 5243784, 2.67 and 43% respectively. This study shows that the production is profitably feasible.

Black-box modelling, bi-objective optimization and ASPEN batch simulation of phenolic compound extraction from Nauclea latifolia root.

Nauclea latifolia root (NLR) extract is one of phytochemicals used to treat various ailments in most of developing countries. This investigation focuses on modelling, optimization and computer-aided simulation of phenolic solid-liquid extraction from NLR. The extraction experiments were conducted at extraction temperature (ET: 33.79-76.21 °C), process time (PT: 2.79-4.21 h) and solid-liquid ratio (SLC: 0.007929-0.018355 g/ml). Regression models (RM) were developed, using Response Surface Methodology (RSM) in Design Expert software, for predicting and optimizing total phenolic content (TPC) and total flavonoid content (TFC) and also compared with adaptive neuro-fuzzy inference system (ANFIS) modelling in Matlab environment. Aspen Batch Process Developer (ABPD) V10 was used to simulate phenolic extract production and perform material balance of the process. Both Coefficients of determination (R2) of RSM (TFC: 0.9996, TPC: 0.9932) and ANFIS models (TFC: 0.99998, TPC: 0.9982) were compared and predicted satisfactorily. Optimization results show: ET (2.79 h), PT (38.8 °C), SLC (0.0198 g/ml), TFC (25.92 25.92 µg RE/g) and TPC (8.47 mg GAE/g). The phenolic extraction base case simulation results gave batch throughput, annual throughput, number of batches per year 0.0089 g/batch, 0.139 g/year and 1019 batches, respectively. The ABPD predicted TPC and experimental TPC results were compared and gave mean relative deviation error of 3.75%. Thus, ABPD simulation model is reasonably reliable for the scale-up design engineering of the phenolic extract production from NLR.