Robust decisions in power system investments
The Turkish electrical system has been studied, particularly for the near term investment programme. The objective of the study was to determine the most likely investment alternatives for the next ten-year period, from a cost effectiveness point of view. A dynamic linear programming model was used in representing the national energy system, with special emphasis on the electricity sector. Hydro, coal, nuclear and oil-fired power plants as well as their interconnection investments were modelled. A 27-year planning horizon was defined. The scenario approach was utilized in establishing the effects of different factors, such as foreign currency requirements of projects, nuclear plant costs and nuclear fuel costs, demand growth rates for electricity as well as other fuels, availability of foreign currency and skilled manpower, and the development rates of coal mines, coal power plants and nuclear power plants. After analyzing the results of 24 different scenarios, robust plans for developing the power system are suggested. Other investments that are subject to the realization of certain conditions are also indicated.
Robust contingency plans for transportation investment planning
A multistage decision process for transportation investment planning is described. Most transportation investment problems inherently involve multiple criteria and uncertainty. To deal with the variations arising from changes in external environments, robust contingency plans should be integrated in the planning process-not after plans are developed-to account for uncertainty. With the proposed decision process, a multiple criteria decision-making (MCDM) method is first used to select a set of good potential designs (or potential solutions). Corresponding optimal contingency plans for each design under uncertainty are then prepared. Robustness considerations are used in making the final selection among contingency plans. To demonstrate the proposed decision-making process, a scenario approach is applied to develop a multistage decision-making process for transportation investment planning problems. Finally, an example of regional transportation investment is presented to illustrate the method. >
Selective and sensitive TNT sensors using biomimetic polydiacetylene-coated CNT-FETs.
Miniaturized smart sensors that can perform sensitive and selective real-time monitoring of target analytes are tremendously valuable for various sensing applications. We developed selective nanocoatings by combining trinitrotoluene (TNT) receptors bound to conjugated polydiacetylene (PDA) polymers with single-walled carbon nanotube field-effect transistors (SWNT-FET). Selective binding events between the TNT molecules and phage display derived TNT receptors were effectively transduced to sensitive SWNT-FET conductance sensors through the PDA coating layers. The resulting sensors exhibited an unprecedented 1 fM sensitivity toward TNT in real time, with excellent selectivity over various similar aromatic compounds. Our biomimetic receptor coating approach may be useful for the development of sensitive and selective micro- and nanoelectronic sensor devices for various other target analytes.