Numerical 3-D Conjugated Heat Transfer Simulation of a First Inter-Stage Internal Cooled Thermal Barrier Coated Gas Turbine Bucket

As a gas turbine entry temperature (TET) increases, thermal loading on first stage blades increases too and therefore, a variety of cooling techniques and thermal barrier coatings (TBCs) are used to maintain the blade temperature within the acceptable limits. In this work a multi-block three dimensional Navier-Stokes commercial turbomachinery oriented CFD-code has been used to compute steady state conjugated heat transfer (CHT) on the blade suction and pressure coated sides of a rotating first inter-stage (nozzle and bucket) with cooling holes of a 60 MW Gas turbine. A Spallart Allmaras model was used for modeling the turbulence. Convection and radiation were modeled for a super alloy blade with and without TBC. The CFD simulations were configured with a mesh domain of nozzle and bucket inter-stage in order to predict the fluid parameters at inlet and outlet of bucket for validate with turbine inter-stage parameter data test of gas turbine manufacturer. The effects of blade surface temperature changes were simulated with both configurations coated and uncoated blades.

Adaptation Application to Engine Modelling

The optimisation of engine performance by predictive means can help save cost and reduce environmental pollution. This can be achieved by developing a performance model which depicts the operating conditions of a given engine. Such models can also be used for diagnostic and prognostic purposes. Creating such models requires a method that can cope with the lack of component parameters and some important measurement data. This kind of method is said to be adaptive since it predicts unknown component parameters that match available target measurement data. In this paper an industrial aeroderivative gas turbine has been modelled at design and off-design points using an adaptation approach. At design point, a sensitivity analysis has been used to evaluate the relationships between the available target performance parameters and the unknown component parameters. This ensured the proper selection of parameters for the adaptation process which led to a minimisation of the adaptation error and a comprehensive prediction of the unknown component and available target parameters. At off-design point, the adaptation process predicted component map scaling factors necessary to match available off-design point performance data.

Comprehensive Piping Vibration Monitoring Programs

Though piping is one of the largest and most expensive types of components in a plant, piping vibration is seldom monitored in a routine manner. Piping itself rarely fails due to vibration, but the same can not be said for related components such as supports, welds, valves, etc. Typically the only time piping vibration is monitored is if high vibration is perceived by operators or is expected due to plant operational changes such as uprates or major component replacements. The procedure for a comprehensive piping vibration monitoring program is thus not as widely known as that for other components such as rotating machinery. This paper presents the steps involved with monitoring piping vibration, obtaining meaningful data and ways to interpret the data. It could be viewed as a primer to those who have never been involved with vibration testing on piping, or as a guideline and checklist for those who have.

The Effect of Non-Uniform Aerodynamic Loading on the Blade Responses

Turbine blades are always subjected to severe aerodynamic loading. The aerodynamic loading is uniform and Of harmonic nature. The harmonic nature depends on the rotor speed and number of nozzles (vanes counts). This harmonic loading is the main sources responsible for blade excitation. In some circumstances, the aerodynamic loading is not uniform and varies circumferentially. This paper discussed the effect of the non-uniform aerodynamic loading on the blade vibrational responses. The work involved the experimental study of forced response amplitude of model blades due to inlet flow distortion in the presence of airflow. This controlled inlet flow distortion therefore represents a nearly realistic environment involving rotating blades in the presence of airflow. A test rig was fabricated consisting of a rotating bladed disk assembly, an inlet flow section (where flow could be controlled or distorted in an incremental manner), flow conditioning module and an aerodynamic flow generator (air suction module with an intake fan) for investigations under laboratory conditions. Tests were undertaken for a combination of different air-flow velocities and blade rotational speeds. The experimental results showed that when the blades were subjected to unsteady aerodynamic loading, the responses of the blades increased and new frequencies were excited. The magnitude of the responses and the responses that corresponding to these new excited frequencies increased with the increase in the airflow velocity. Moreover, as the flow velocity increased the number of the newly excited frequency increased.

Performance Testing of Coal Fired Power Plants

With the renewed interest in the construction of coal-fired power plants in the United States, there has also been an increased interest in the methodology used to calculate/determine the overall performance of a coal fired power plant. This methodology is detailed in the ASME PTC 46 (1996) Code, which provides an excellent framework for determining the power output and heat rate of coal fired power plants. Unfortunately, the power industry has been slow to adopt this methodology, in part because of the lack of some details in the Code regarding the planning needed to design a performance test program for the determination of coal fired power plant performance. This paper will expand on the ASME PTC 46 (1996) Code by discussing key concepts that need to be addressed when planning an overall plant performance test of a coal fired power plant. The most difficult aspect of calculating coal fired power plant performance is integrating the calculation of boiler performance with the calculation of turbine cycle performance and other balance of plant aspects. If proper planning of the performance test is not performed, the integration of boiler and turbine data will result in a test result that does not accurately reflect the true performance of the overall plant. This planning must start very early in the development of the test program, and be implemented in all stages of the test program design. This paper will address the necessary planning of the test program, including: • Determination of Actual Plant Performance. • Selection of a Test Goal. • Development of the Basic Correction Algorithm. • Designing a Plant Model. • Development of Correction Curves. • Operation of the Power Plant during the Test. All nomenclature in this paper utilizes the ASME PTC 46 definitions for the calculation and correction of plant performance.

Probabilistic Model-Based Fault Diagnosis of the Rotor System

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.

Resurrecting a Major Coke Calcining Energy Recovery Plant

Refurbishment of the Port Arthur Steam Energy facility began in early 2005 after key commercial agreements were concluded. The plant, which had been idle since October 2000, was originally constructed in 1983 and 1984 to recover energy from three petroleum coke calcining kilns at the Great Lakes Carbon LLC facility. Major repairs were needed because of extensive damage from sulfuric acid corrosion of the HRSG system and deterioration of water treatment facilities. In addition, major improvements were made including an acoustic cleaning system, multiclones for particulate emission reduction, magnesium oxide injection for corrosion control, a complete new control system with all new field instrumentation, stack improvements to increase dispersion, and improvements to the HRSG system and water treatment system to improve reliability and reduce maintenance. Rising energy prices dictated a fast-paced schedule. Following a major reconstruction effort with a peak force of 435 people, the facility was in full operation by August 2005, less than nine months from commencement. The facility is producing approximately 450,000 lb/hr of high pressure steam, the majority of which is sold to the neighboring Valero Port Arthur refinery, and producing 4 to 5 MW of power. By capturing 1800–2000°F heat that would other wise be wasted, the project recovers nearly 5 trillion Bru/year, off setting over 200 tons/yr of NOx and over 280,000 tons/yr of carbon dioxide that would otherwise be emitted by natural gas combustion. The success of the project can be attributed to management of the project which included innovative inspection techniques, development of the scope of work, design of improvements, and extensive construction and repairs.

Experimental Evaluation and Comparison of the Performance and Emissions of a Regenerative Gas Microturbine Using Biodiesel From Various Sources as Fuel

Biodiesel is an alternative fuel that has become more attractive recently because of its environmental benefits and the fact that it is made from renewable resources. As it can be blended in any proportion with mineral Diesel, and there are several reports which presented substantial reductions in emissions of unburned hydrocarbons, carbon monoxide and particulate in IC engines without reducing the output power significantly. The aim of this work was to perform an emissions and performance experimental analysis to evaluate and compare the use of Biodiesel obtained from different sources, Castor, Soy and Palm Oil, on a 30 kW regenerative gas micro turbine engine installed in the laboratories of the Federal University of Itajuba´ – Unifei, Brazil, at different power levels at steady state condition. All the fuels were characterized in terms of its viscosity and heat value, and the thermal performance and the emissions were measured. In all cases, it was performed a comparison between the obtained results with Biodiesel and Diesel. None of the fuels presented any problem related to atomization process in the related tests, and have shown no significant changes in performance of the microturbine reaching levels of around 26% of thermal efficiency. The minimum Heat Rate obtained at full load, was for the Biodiesel from Palm oil case, and the maximum was for Castor oil with a value 8.38% higher than when operated with Diesel. In Addition, when measuring pollutants emissions in the exhaust gases, it was observed a slightly increment in CO and a reduction in NOx concentration.

Numerical Study of Coal Gasification Using Eulerian-Eulerian Multiphase Model

Gasification converts the carbon-containing material into a synthesis gas (syngas) which can be used as a fuel to generate electricity or used as a basic chemical building block for a large number of uses in the petrochemical and refining industries. Based on the mode of conveyance of the fuel and the gasifying medium, gasification can be classified into fixed or moving bed, fluidized bed, and entrained flow reactors. Entrained flow gasifiers normally feature dilute flow with small particle size and can be successfully modeled with the Discrete Phase Method (DPM). For the other types, the Eulerian-Eulerian (E-E) or the so called two-fluid multiphase model is a more appropriate approach. The E-E model treats the solid phase as a distinct interpenetrating granular “fluid” and it is the most general-purposed multi-fluid model. This approach provides transient, three-dimensional, detailed information inside the reactor which would otherwise be unobtainable through experiments due to the large scale, high pressure and/or temperature. In this paper, a transient, three-dimensional model of the Power Systems Development Facility (PSDF) transport gasifier will be presented to illustrate how Computational Fluid Dynamics (CFD) can be used for large-scale complicated geometry with detailed physics and chemistry. In the model, eleven species are included in the gas phase while four pseudo-species are assumed in the solid phase. A total of sixteen reactions, both homogeneous (involving only gas phase species) and heterogeneous (involving species in both gas and solid phases), are used to model the coal gasification chemistry. Computational results have been validated against PSDF experimental data from lignite to bituminous coals under both air and oxygen blown conditions. The PSDF gasifier geometry was meshed with about 70,000, hexahedra-dominated cells. A total of six cases with different coal, feed gas, and/or operation conditions have been performed. The predicted and measured temperature profiles along the gasifier and gas compositions at the outlet agreed fairly well.

Diagnosis of the Operation of Power Plants

A system was developed to diagnose the operation of combined cycle power plants and to determine, when deviations are found, which components are causing the deviations and the impact of each component deviation. The system works by comparing the values of the actual operating variables with some reference values that are calculated by a model that was adjusted to the design heat balances. The model can use the actual values of the environmental parameters as well as the design values, so the effect of environmental changes can be quantified and separated. The determination of the individual equipment impacts is done by adjusting the equipment parameters in order to reproduce the values of the measured variables. The adjustment is done by varying the values of the characteristic parameters of the equipment in order to minimize the sum of the squares of the differences between the values of the measured variables and the calculated values from the model.