Computational Fluid Dynamics (CFD) tools are used to investigate fluid flow and scalar mixing in micromixers where low molecular diffusivities yield advection dominant transport. In these applications, achieving a numerical solution is challenging. Numerical procedures used to overcome these difficulties may cause misevaluation of the mixing process. Evaluation of the mixing performance of these devices without appropriate analysis of the contribution of numerical diffusion yields over estimation of mixing performance. In this study, two- and four-inlet swirl-generating micromixers are examined for different mesh density, flow and molecular diffusivity scenarios. It is shown that mesh densities need to be high enough to reveal numerical diffusion errors in scalar transport simulations. Two-inlet micromixer design was found to produce higher numerical diffusion. In both micromixer configurations, when cell Peclet numbers were around 50 and 100 for Reynolds numbers 240 and 120, the numer... [more]

The integration of scheduling and process planning can eliminate resource conflicts and hence improve the performance of a manufacturing system. However, the focus of most existing works is mainly on the optimization techniques to improve the makespan criterion instead of more efficient uses of energy. In fact, with a deteriorating global climate caused by massive coal-fired power consumption, carbon emission reduction in the manufacturing sector is becoming increasingly imperative. To ease the environmental burden caused by energy consumption, e.g., coal-fired power consumption in use of machine tools, this research considers both makespan as well as environmental performance criteria, e.g., total power consumption, in integrated process planning and scheduling using a novel multi-objective memetic algorithm to facilitate a potential amount of energy savings; this can be realized through a better use of resources with more efficient scheduling schemes. A mixed-integer linear programmi... [more]

Accurate predictive mathematical models are urgently needed in synthetic biology to support the bottom-up design of complex biological systems, minimizing trial-and-error approaches. The majority of models used so far adopt empirical Hill functions to describe activation and repression in exogenously-controlled inducible promoter systems. However, such equations may be poorly predictive in practical situations that are typical in bottom-up design, including changes in promoter copy number, regulatory protein level, and cell load. In this work, we derived novel mechanistic steady-state models of the lux inducible system, used as case study, relying on different assumptions on regulatory protein (LuxR) and cognate promoter (Plux) concentrations, inducer-protein complex formation, and resource usage limitation. We demonstrated that a change in the considered model assumptions can significantly affect circuit output, and preliminary experimental data are in accordance with the simulated ac... [more]