Modeling is one way to design and to optimize such process where complexities due to coupling the heat transfer with phase change and the solution of electric field are faced.
The anodic oxidation of OA has clearly shown that the electrode material is an important parameter when optimizing such processes, since the mechanism and the products of several anodic reactions are known to depend on the anode material.
To optimize and control such processes, it is essential to understand the sequence of events that occur in the evolution of the solid phase, rather than simply characterizing the final product recovered at the end of the process.
This makes a process possible where H2 is used for the reduction of CO/CO2; however, optimizing such a process by increasing flow rates or gas pressures might lead to inhibition of H2 consumption.
A great challenge exists in the selection of appropriate membrane materials and the design of proper RED membranes to optimize such an energy-producing process.
This is a bit surprising, considering the large amount of work that has been put into optimizing the design of such processes.
In the first part of the paper, simple models demonstrate that the periodicity of such processes can be optimized in three settings: fixed desorption time, variable desorption time, and variable species concentration in the gas space.
Our approach allows organizations to capture monitoring requirements, optimize such requirements, e.g. choosing the monitoring process with lowest cost or highest availability, and enacting the optimal monitoring process through a service-oriented approach.
Because it uses a population of solutions in the search process and optimizes such that the ranks are minimized, the Pareto optima can provide a measure of uncertainty in prediction.
In order to optimize the processes such as planting, harvesting, handling, threshing, cleaning, sorting, conveying, drying and storing and to reduce the quantitative and qualitative losses of grains and seeds, their physical properties need to be known.
