Bio-glycerol was synthesized from Cameroon palm kernel oil (PKO) through the transesterification procedure. Palm kernel oil extracted from palm kernel seeds using mechanical expression and solvent extraction was purif...Bio-glycerol was synthesized from Cameroon palm kernel oil (PKO) through the transesterification procedure. Palm kernel oil extracted from palm kernel seeds using mechanical expression and solvent extraction was purified and characterized by physico-chemical methods and used in the transesterification process to give biodiesel and bio-glycerol. The biodiesel was purified and characterized as reported in previous articles. Our focus in this article is on glycerol, an important by-product of the transesterification process which has potential pharmaceutical, cosmetic and engineering applications. The bio-glycerol was purified by acidification and the purified glycerol was subjected to physical and chemical characterization. The specific gravity of glycerol was obtained as 1.2 kg/L, viscosity at 40°C gave 1500 cSt and 500 cSt at 100°C;pH was 7.4;the flash point was 160°C, and the ASTM color was 2.0 before purification and zero after purification. The sulfur content was 0.016%w/v. This sulfur content is low thus posing no environment threat. The chemical composition of the synthesized bio-glycerol determined using IR spectroscopy and gas chromatography-mass spectrometry (GC-MS) confirmed the known chemical structure of glycerol. The purification and analysis of bio-glycerol is important as it can find applications in the pharmaceutical, cosmetic and food industries inter alia.展开更多
This paper proposes a hill-climbing particle swarm optim ization algorithm with variable width neighborhood (vwnHCPSO).The new method ass umes that some stochastic particles are produced in an initial neighborhood of ...This paper proposes a hill-climbing particle swarm optim ization algorithm with variable width neighborhood (vwnHCPSO).The new method ass umes that some stochastic particles are produced in an initial neighborhood of t he best particle P_g at the first iteration of PSO.Then the best individual P_gn of the stochastic particles is found. If P_gn is better than P_g,P_g is replaced with P_gn and the next iteration of PSO goes on. If P_gn is not better than P_g,the neighborhood wid th of the best particle P_g is broadened, the stochastic particles producti on is renewed and the best individual P_gn of stochastic particles is f ound again. If P_gn can be better than P_g now, P_g is repla ced with P_gn and the next iteration of PSO can go on. Otherwise, the neighborhood width of the best particle P_g is broadened again and the next iteration of PSO does not go on until the best individual P_gn of stoc hastic particles is found or the neighborhood width exceeds the scheduled width . Then, vwnHCPSO, hill-climbing particle swarm optimization algorithm with inv ariable width neighborhood (HCPSO) and PSO are used to resolve several well-kno wn and widely used test functions’ optimization problems. Results show t hat vwnHCPSO has greater efficiency, better performance and more advantages in m any aspects than HCPSO and PSO. Next, vwnHCPSO is used to train artificial neur al network (NN) to construct a practical soft-sensor of light diesel oil flash point of the main fractionator of fluid catalytic cracking unit (FCCU).The obtai ned results and comparison with actual industrial data indicate that the new met hod proposed in this paper is feasible and effective in soft-sensor of light di esel oil flash point.展开更多
文摘Bio-glycerol was synthesized from Cameroon palm kernel oil (PKO) through the transesterification procedure. Palm kernel oil extracted from palm kernel seeds using mechanical expression and solvent extraction was purified and characterized by physico-chemical methods and used in the transesterification process to give biodiesel and bio-glycerol. The biodiesel was purified and characterized as reported in previous articles. Our focus in this article is on glycerol, an important by-product of the transesterification process which has potential pharmaceutical, cosmetic and engineering applications. The bio-glycerol was purified by acidification and the purified glycerol was subjected to physical and chemical characterization. The specific gravity of glycerol was obtained as 1.2 kg/L, viscosity at 40°C gave 1500 cSt and 500 cSt at 100°C;pH was 7.4;the flash point was 160°C, and the ASTM color was 2.0 before purification and zero after purification. The sulfur content was 0.016%w/v. This sulfur content is low thus posing no environment threat. The chemical composition of the synthesized bio-glycerol determined using IR spectroscopy and gas chromatography-mass spectrometry (GC-MS) confirmed the known chemical structure of glycerol. The purification and analysis of bio-glycerol is important as it can find applications in the pharmaceutical, cosmetic and food industries inter alia.
文摘This paper proposes a hill-climbing particle swarm optim ization algorithm with variable width neighborhood (vwnHCPSO).The new method ass umes that some stochastic particles are produced in an initial neighborhood of t he best particle P_g at the first iteration of PSO.Then the best individual P_gn of the stochastic particles is found. If P_gn is better than P_g,P_g is replaced with P_gn and the next iteration of PSO goes on. If P_gn is not better than P_g,the neighborhood wid th of the best particle P_g is broadened, the stochastic particles producti on is renewed and the best individual P_gn of stochastic particles is f ound again. If P_gn can be better than P_g now, P_g is repla ced with P_gn and the next iteration of PSO can go on. Otherwise, the neighborhood width of the best particle P_g is broadened again and the next iteration of PSO does not go on until the best individual P_gn of stoc hastic particles is found or the neighborhood width exceeds the scheduled width . Then, vwnHCPSO, hill-climbing particle swarm optimization algorithm with inv ariable width neighborhood (HCPSO) and PSO are used to resolve several well-kno wn and widely used test functions’ optimization problems. Results show t hat vwnHCPSO has greater efficiency, better performance and more advantages in m any aspects than HCPSO and PSO. Next, vwnHCPSO is used to train artificial neur al network (NN) to construct a practical soft-sensor of light diesel oil flash point of the main fractionator of fluid catalytic cracking unit (FCCU).The obtai ned results and comparison with actual industrial data indicate that the new met hod proposed in this paper is feasible and effective in soft-sensor of light di esel oil flash point.
