Preparation and property of seal coating for gas turbine compressor

Double-layer structure of seal coating which consisted of a Ni5Al bond coating and a Ni25 graphite top coating were prepared on steel substrate of gas turbine compressor cylinder block.Bond coating was prepared by atmospheric plasma spraying and top coating was prepared by flame spraying.The microstructure,mechanical properties and abradability of the coating were characterized by scanning elec-tron microscope(SEM),hardness tester,universal testing machine,thermal shock testing machine and abradability testing machine.The res-ults show that the overall spraying structure of the seal coating is uniform,the nickel metal phase is the skeleton supporting the entire coat-ing,and the coating is well bonded without separation.The seal coating has a bonding strength of not less than 7.7 MPa,excellent thermal stability,and thermal shock resistance cycle numbers at 500℃more than 50;the scratch length,deepest invasion depth and wear amount of the coating increase with rise of test temperature,with almost no coating adhesion,indicating that the seal coating has excellent abradability.

Development of High Efficiency Swing Compressor for R32 Refrigerant

In the age of global warming, energy saving features and overall reduction of environmental impact are critical components that must be addressed when developing new HVAC （heating ventilation and air conditioning） units. We chose R32 refrigerant, with its lower LCCP （life cycle climate performance） as a more sustainable choice than R410A. However, R32 has its drawbacks. Due to its smaller molecular weight, internal leakage loss is higher for R32. Moreover, high discharge gas temperature decreases the reliability of the compressor, and makes a large overheating loss increase. In this study, we will describe the technologies （reducing the piston pressurizing force, heat-insulating structure, optimizing the port diameter） that were developed to overcome these drawbacks. We will also oresent the performance and reliability of the newly develoned high efficiency swing, comnressor series for R32 refrigerant.

Simulation of natural gas transmission pipeline network system performance

Simulation has proven to be an effective tool for analyzing pipeline network systems （PNS） in order to determine the design and operational variables which are essential for evaluating the performance of the system. This paper discusses the use of simulation for performance analysis of transmission PNS. A simulation model was developed for determining flow and pressure variables for different configuration of PNS. The mathematical formulation for the simulation model was derived based on the principles of energy conservation, mass balance, and compressor characteristics. For the determination of the pressure and flow variables, solution procedure was developed based on iterative Newton Raphson scheme and implemented using visual C＋＋6. Evaluations of the simulation model with the existing pipeline network system showed that the model enabled to determine the operational variables with less than ten iterations. The performances of the compressor working in the pipeline network system xvhich includes energy consumption, compression ratio and discharge pressure were evaluated to meet pressure requirements ranging from 4000-5000 kPa at various speed. Results of the analyses from the simulation indicated that the model could be used for performance analysis to assist decisions regarding the design and optimal operations of transmission PNS.

A Self-Learning Diagnosis Algorithm Based on Data Clustering

The article describes an approach to building a self-learning diagnostic algorithm. The self-learning algorithm creates models of the object under consideration. The models are formed periodically through a certain time period. The model includes a set of functions that can describe whole object, or a part of the object, or a specified functionality of the object. Thus, information about fault location can be obtained. During operation of the object the algorithm collects data received from sensors. Then the algorithm creates samples related to steady state operation. Clustering of those samples is used for the functions definition. Values of the functions in the centers of clusters are stored in the computer’s memory. To illustrate the considered approach, its application to the diagnosis of turbomachines is described.

Cascading Failure Propagation Simulation in Integrated Electricity and Natural Gas Systems

The sharp increase in the total installed capacity of natural gas generators has intensified the dynamic interaction between the electricity and natural gas systems,which could induce cascading failure propagation across the two systems that deserves intensive research.Considering the distinct time response behaviors of the two systems,this paper discusses an integrated simulation approach to simulate the cascading failure propagation process of integrated electricity and natural gas systems(IEGSs).On one hand,considering instantaneous re-distribution of power flows after the occurrence of disturbance or failure,the steady-state AC power flow model is employed.On the other hand,gas transmission dynamics are represented by dynamic model to capture the details of its transition process.The interactions between the two systems,intensified by energy coupling components(such as gas-fired generator and electricity-driven gas compressor)as well as the switching among the operation modes of compressors during the cascading failure propagation process,are studied.An IEGS composed of the IEEE 30-bus electricity system and a 14-node 15-pipeline gas system is established to illustrate the effectiveness of the proposed simulation approach,in which two energy sub-systems are coupled by compressor and gas-fired generator.Numerical results clearly demonstrate that heterogeneous interactions between electricity and gas systems would trigger the cascading failure propagation between the two coupling systems.

Efficiency Analysis of an Arrayed Liquid Piston Isothermal Air Compression System for Compressed Air Energy Storage

Compressed air energy storage(CAES)is an important technology in the development of renewable energy.The main advantages of CAES are its high energy capacity and environmental friendliness.One of the main challenges is its low energy density,meaning a natural cavern is required for air storage.High-pressure air compression can effectively solve the problem.A liquid piston gas compressor facilitates high-pressure compression,and efficient convective heat transfer can significantly reduce the compression energy consumption during air compression.In this paper,a near isothermal compression method is proposed to increase the surface area and heat exchange by using multiple tube bundles in parallel in the compression chamber in order to obtain high-pressure air using liquid-driven compression.Air compression with a compression ratio of 6.25:1 is achieved by reducing the tube diameter and increasing the parallel tube number while keeping the compression chamber cross-sectional area constant in order to obtain a high-pressure air of 5 MPa.The performances of this system are analyzed when different numbers of tubes are applied.A system compression efficiency of 93.0%and an expansion efficiency of 92.9%can be achieved when 1000 tubes are applied at a 1 minute period.A new approach is provided in this study to achieve high efficiency and high pressure compressed air energy storage.