Though fossil fueled power plants aren’t as commonly used anymore, coal fired power generation is still a major source of global electricity, making up about 25% of the market in total. Compared to other options in fossil fuel power generation, coal is found to be the most economical choice as well as a reliable option. Making demands that are heavily reliant on other fuels, such as oil-fired for example, slowly levers to coal power generation. The global reserve of coal can be found in abundance when compared to other energy sources (such as oil for example) as there is about 3 times more of it. Also, IGCC comes with an economic benefit as the price of coal has remained relatively constant, which results in a higher degree of confidence when relying on coal as an energy source in the future.
How Does an IGCC Work?
The system uses a high pressure gasifier to turn coal and other carbon based fuels such as high-sulfur coal, heavy petroleum residues and biomass into pressurized clean coal synthesis gas (also known as syngas). The solid coal is gas-fired to produce syngas by gasifying coal in a closed pressurized reactor with a shortage of oxygen to ensure that coal is broken down by the heat and pressure. Before going out of the system, the syngas runs through a pre-combustion separation process to remove impurities, starting with water-gas-shift reaction to increase concentration of hydrogen and efficiency during combustion process, to a physical separation process (through variable methods). After that, a fairly pure syngas is used as a fuel in a combustion turbine that produces electricity. Waste heat contained in a gas turbine’s exhaust is used to produce steam from feed water that further turns a steam turbine to generate additional electricity.
[:en]In the ever-expanding market for waste-heat recovery methods, different approaches have been established in order to combat the latest environmental restrictions while achieving more attractive power plant efficiencies. As gas turbine cycles continue to expand within the energy market, one particular technology has seen a significant upsurge due to a number of its beneficial contributions. Supercritical CO2 (S-CO2) bottoming cycles have allowed low power units to utilize waste heat recovery economically. For many years, the standard for increasing the efficiency level of a GTU (Gas Turbine Unit) was to set up a steam turbine Rankine cycle to recycle the gas turbine exhaust heat. However, the scalability constraints of the steam system restrict its application to only units above 120MW.
[:en]Tip leakage is generated inevitably by the clearance between the rotating blades and the stationary casing of a turbine, and is responsible for both the aerodynamic losses in a turbine stage and the high heat-loads in the tip region . To decrease tip leakage and improve component performance, shroud seal structures have been widely applied to modern turbine components, especially to low pressure turbines, because of their advantage on both aerodynamic and structural features. However, due to the complexity of the shroud geometry, the flow structures and thermodynamic process in shroud can be extremely complicated, that is interactions of vortices, separations, jet flow, etc. Thus, because of the complex geometry of shrouds, as well as strong interactions between the tip leakage and main flow, it is not easy to draw a numerical simulation with satisfactory accuracy and time-costing in shrouded turbines. This begs the question of what should the compromise be between using simplified loss models and full 3D CFD analysis for leakage modelling?
In the main flow path of a turbine the flow will always be dominated by the blades shape, while for leakage cases the flow will be dominated by the motion and evolution of small eddies. Rosic et al.  reviewed the importance of shroud leakage modelling in multistage turbines. The comparison of measurements and 3D calculations shows that the flow in shrouded low aspect ratio turbines is dominated by shroud leakage. This is especially true as regards the loss distribution. The rotor shroud leakage flow greatly increases the secondary flow in the downstream stators and drives low energy fluid towards mid-span. It was pointed out that with very low values of shroud leakage the flow is reasonably well modelled by a simple 1D model of the leakage flow, using sources and sinks on the casing. However, for more representative real clearances, full 3D modelling of the seal and cavity flows is necessary in order to obtain reasonable agreement. Given that developing a simulation method with both high precision and fast solving speed is imperatively demanded for engineers to assess new designs, Zhengping Zou et al.  suggested that one of the potential approaches for solving the problem is a method that couples low dimensional models, 1D and 2D models, of the shroud flow with 3D (three-dimensional) simulations of the main flow passage. Specifically, some boundary source and boundary sink is set on the interface between the shroud and the main flow passage, and the source term and sink term are determined by the shroud leakage model. The schematic of this process is given in Fig. 1. The results of his study  demonstrate that the proposed models and methods will contribute to pursue deeper understanding and better design methods of shrouded axial turbines.
[:en]The term, “mixed flow compressor”, refers to a type of compressor that combines axial and radial flow paths. This phenomenon produces a fluid outflow angle somewhere between 0 and 90 degrees with respect to the inlet path. Referred to as the meridional exit angle, the angled outflow of this mixed flow configuration possesses the advantages of both axial and centrifugal compressors. Axial compressors can produce higher order efficiencies for gas engines, but they have relatively low-pressure ratios unless compounded into several stages. Centrifugal compressors can produce high-pressure ratios in a single stage, but they suffer from a drop in efficiency. The geometrical distinction of mixed flow compressors allows for higher efficiencies while maintaining a limited cross-sectional area. The trade-off for a mixed flow compressor when introduced to aero gas turbines is that there is an associated weight increase due to the longer impellers needed to cover this diagonal surface. However, when related to smaller gas turbines, the weight increase becomes less significant to the overall performance of the engine.
[:en]In recent days, many people find themselves spending time and resources on uncovering the best solution to optimize the power generation cycle. Until recently, 80% of power plants worldwide (whether fossil fuel, nuclear, or clean technology) used steam as its main working fluid and while it is still the most common option, today’s power plants are finding another fluid to use.
Although supercritical CO2 study began in the 1940’s, it was disregarded as an alternative fluid option because it was expensive to explore and steam was still perfectly reliable at the time. Nowadays due to increasing quantity and quality demand in power, researchers are looking into the possibility of replacing steam with supercritical carbon dioxide. The discover of this property, increases the incentive of exploring the technology further. This year, the US Department of Energy is awarding up to $80 million towards projects to build and operate a supercritical CO2 plant.
A major concern for pump system engineers over the last fifty years has been caviation. Cavitation is defined as the formation of vapor bubbles in low pressure regions within a flow. Generally, this phenomenon occurs when the pressure value within the flow-path of the pump becomes lower than the vapor pressure; which is defined as the pressure exerted by a vapor in thermodynamic equilibrium conditions with its liquid at a specified temperature. Normally, this happens when the pressure at the suction of the pump is insufficient, in formulas NPSHa ≤ NPSHr, where the net positive suction head is the difference between the fluid pressure and the vapor pressure at the pump suction and the “a” and “r” stand respectively for the values available in the system and required by the system to avoid cavitation in the pump.The manifestation of cavitation causes the generation of gas bubbles in zones where the pressure gets below the vapor pressure corresponding to that fluid temperature. When the liquid moves towards the outlet of the pump, the pressure rises and the bubbles implode creating major shock waves and causing vibration and mechanical damage by eroding the metal surfaces. This also causes performance degradation, noise and vibration, which can lead to complete failure. Often a first sign of a problem is vibration, which also has an impact on pump components such as the shaft, bearings and seals.
Implementation feasibility of power plant design relies heavily on the economic benefits. More often than not, newer technology cannot be implemented due to high cost of electric generation which would not be acceptable in the market since energy is a price sensitive commodity. Sometimes while deciding on a design to choose, we are given a choice between a high initial equipment cost and efficiency versus a lower capital cost with lower efficiency. The designer must be able to choose which design would fit best with their needs and goals.
While running a power generation plant, there are three types of cost that need to be taken into consideration: capital cost, operational cost and financing cost. With point one and two to being of higher priority.
[:en]This post will examine the meshing requirements for an accurate analysis of flow characteristics in terms of turbomachinery applications, based on Marco Stelldinger et al study . Computational Fluid Dynamics (CFD) are widely used for the analysis and the design of turbomachinery blade rows. A well-established method is the application of semi-unstructured meshes, which uses a combination of structured meshes in the radial direction and unstructured meshes in the axial as well as the tangential direction. Stelldinger’s paper presents a library for turbomachinery meshing, which enables the generation of semi-unstructured meshes for turbomachinery blade passages, including cavities, fillets and varying clearance sizes. The focus lies on the generation of a mesh that represents the real geometry as accurately as possible, while the mesh quality is preserved.
The above was achieved by using two different approaches. The first approach divides the blade passage into four parts. Inside of these parts, a structured grid is generated by solving a system of elliptic partial differential equations. The second approach is based on the domain being split into fourteen blocks. It has benefits concerning computational time towards the first one, because of a faster generation procedure as well as a faster performance of the inverse mapping.
[:en] Combined Cycle Power Plants are among the most common type of power generation cycle. Demand of CCP application has risen across board due to the rising energy demand (and consumption) as well as growing environmental awareness. Combined cycle is a matured energy that has been proven to generate much lower CO2 (and other environmental footprints) compared to a traditional fossil fuel steam or gas turbine power generation cycle Consequently, this application is often looked as a “better” substitute compared to other a fossil fuel technologies. That being said, CCP is still a temporary alternative to substitute SPP since although CCP generally is more environmentally friendly, CCP process still requires the combustion of fossil fuel (though at a significantly lower degree compared to SPP) for initial heat/energy source.
The application takes two kinds of thermodynamic cycle in assembly to work together from the same heat source. Fluid Air and fuel enters a gas turbine cycle (Joule or Brayton) to generate electricity, waste heat/energy from working fluid will then be extracted then go through a Heat Recovery Steam Generator and towards steam turbine cycle (Rankine) to generate extra electricity. The main advantage of this cycle combination is the improvement of overall net efficiency (around 50-60% higher compared to each cycle alone), thus, lower fuel expenses. With that being said, net efficiency of a CCP is often inflated especially on systems which use a low-temperature waste heat.
[:en]With the advent of emerging technologies in the space of human-computer interaction (HCI), a prevalent challenge has been finding methods that can accurately represent these motions in real time. Applications using RGB-D cameras to track movements for consumer-based systems has already been employed by Microsoft in the space of tracking silhouette movements in video games as well as app navigation in the Microsoft Kinect system. However, tracking methods must evolve in order to successfully represent the complexity of human hand motion. The two main categories of 3D hand articulation tracking methods consist of appearance-based and model-based tracking. Appearance-based tracking methods are efficient in the limited space of comparing the present model to a number of already defined hand configurations. Model-based tracking methods allow the computational configuration to explore a continuous space in which the hand motions are optimized at a high dimensional space in near real time.
If the computer tracks the human wrist with six degrees of freedom and the other joints accordingly, the ensuing dimensional analysis occurs at a high dimensional space. A saddle joint (2 DOF) at the base of the each finger plus the additional hinge joints (1 DOF each) at the middle of the finger describes each finger with four degrees of freedom. In turn, the problem of tracking the articulation of a single hand is performed in a dimensional space of 27. This highly dimensional problem formulation requires an optimization technique specific to the problem that can provide a uniform coverage of the sampled space. Quasi-random sequences are known to exhibit a more uniform coverage of a high dimensional compared to random samples taken from a uniform distribution. The Sobol sequence, developed by Russian mathematician Ilya Sobol, describes a quasi-random low-discrepancy sequence that more evenly distributes a number of points in a higher dimensional space. Figure 1 represents the distribution discrepancy between a pseudorandom number generation and a quasi-random low-discrepancy Sobol sequence generation.