Abstract: The paper presents a thermodynamic cycle analysis
for three turboshaft engines. The first cycle is a Brayton cycle,
describing the evolution of a classical turboshaft, based on the
Klimov TV2 engine. The other four cycles aim at approaching an
Ericsson cycle, by replacing the Brayton cycle adiabatic expansion in
the turbine by quasi-isothermal expansion. The maximum quasi-
Ericsson cycles temperature is set to a lower value than the maximum
Brayton cycle temperature, equal to the Brayton cycle power turbine
inlet temperature, in order to decrease the engine NOx emissions.
Also, the power/expansion ratio distribution over the stages of the gas
generator turbine is maintained the same. In two of the considered
quasi-Ericsson cycles, the efficiencies of the gas generator turbine, as
well as the power/expansion ratio distribution over the stages of the
gas generator turbine are maintained the same as for the reference
case, while for the other two cases, the efficiencies are increased in
order to obtain the same shaft power as in the reference case. For the
two cases respecting the first condition, both the shaft power and the
thermodynamic efficiency of the engine decrease, while for the other
two, the power and efficiency are maintained, as a result of assuming
new, more efficient gas generator turbines.
Abstract: Developments in turbine cooling technology play an important role in increasing the thermal efficiency and the power output of recent gas turbines, in particular the turbojets.
Advanced turbojets operate at high temperatures to improve thermal efficiency and power output. These temperatures are far above the permissible metal temperatures. Therefore, there is a critical need to cool the blades in order to give theirs a maximum life period for safe operation.
The focused objective of this work is to calculate the turbojet performances, as well as the calculation of turbine blades cooling.
The developed application able the calculation of turbojet performances to different altitudes in order to find a point of optimal use making possible to maintain the turbine blades at an acceptable maximum temperature and to limit the local variations in temperatures in order to guarantee their integrity during all the lifespan of the engine.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: In this study, the effects of biogas fuels on the performance of an annular micro gas turbine (MGT) were assessed experimentally and numerically. In the experiments, the proposed MGT system was operated successfully under each test condition; minimum composition to the fuel with the biogas was roughly 50% CH4 with 50% CO2. The power output was around 170W at 85,000 RPM as 90% CH4 with 10% CO2 was used and 70W at 65,000 RPM as 70% CH4 with 30% CO2 was used. When a critical limit of 60% CH4 was reached, the power output was extremely low. Furthermore, the theoretical Brayton cycle efficiency and electric efficiency of the MGT were calculated as 23% and 10%, respectively. Following the experiments, the measured data helped us identify the parameters of dynamic model in numerical simulation. Additionally, a numerical analysis of re-designed combustion chamber showed that the performance of MGT could be improved by raising the temperature at turbine inlet. This study presents a novel distributed power supply system that can utilize renewable biogas. The completed micro biogas power supply system is small, low cost, easy to maintain and suited to household use.