Customer Adapted Optimized Maintenance Plan for Gas Turbines

2007 ◽  
Author(s):  
Mathias Wa¨rja ◽  
Pontus Slottner
Keyword(s):  
Gas Turbines ◽  
Creep Damage ◽  
Detailed Knowledge ◽  
Critical Systems ◽  
Fuel Prices ◽  
Initiation And Propagation ◽  
General Material ◽  
Critical Components ◽  
Maintenance Plan ◽  
Selection Of

Maintaining high levels of availability and reliability are essential objectives for many industries, especially those that are subject to high costs due to non-payment as a result of shutdowns of critical systems, e.g. gas turbines. To utilize these systems as effectively as possible, maintenance must be optimized. Though, determining what is optimal is a tough multi-variable task requiring detailed knowledge about components building the system, such as damage mechanisms, TMF/LCF crack initiation and propagation, creep deformation, creep damage, general material deterioration, erosion, oxidation and corrosion. Also, customer specific inputs are essential, e.g. value of the produced entity, fuel prices, unplanned and planned standstill cost. To efficiently funnel this information into a customer adapted, optimized maintenance plan, a probabilistic optimization model is proposed. The model will dynamically calculate the most efficient point in time for a renewal. Further, the model can, as a function of risk willingness, adjust the maintenance plan to any customer’s specific demands. This paper describes (i) the model, (ii) how information is gathered and processed, (iii) how the risk assessment is performed and (iv) how the lifetime prediction is carried out. The optimization itself can be adjusted to aim at: minimizing cost or risk or maximizing availability, performance or reliability. Also, this paper describes how the quantitative selection of critical components included in the optimization is performed.

Customer Adapted Maintenance Plan (CAMP): A Process for Optimization of Gas Turbine Maintenance

2008 ◽  
Author(s):  
Mathias Wa¨rja ◽  
Pontus Slottner ◽  
Markus Bohlin
Keyword(s):  
Gas Turbine ◽  
Preventive Maintenance ◽  
Gas Turbines ◽  
Measurement Techniques ◽  
Test Methods ◽  
Detailed Knowledge ◽  
Critical Systems ◽  
Case Scenario ◽  
Worst Case ◽  
Maintenance Plan

Maintaining high levels of availability and reliability are essential objectives for many industries, especially those that are subject to high costs due to shutdowns of critical systems, e.g. gas turbines. To utilize these systems as effectively as possible, preventive maintenance must be optimized. Determining what is optimal is, however, a multi-variable task requiring detailed knowledge about the components in the system and their different damage mechanisms. These factors have always affected the condition of the gas turbine and maintenance actions, but only recently has it been possible to estimate and measure them correctly for individual components during operation. In the past, it was necessary to construct maintenance intervals from the most critical component (or components), requiring the highest maintenance frequency. An additional worst-case scenario margin was also necessary, taking into account factors such as possible load variation, differences in environment (affecting e.g. power turbine temperatures) and other sources of uncertainty. These uncertainties together have determined traditional maintenance planning, with maintenance packages each containing a set of maintenance activities for a set of components being predetermined and preplanned. With the new CAMP approach, the maintenance strategy is to reach a Retirement For Cause (RFC) strategy, where components are not replaced until a potential failure has been detected. This requires measurement techniques that can monitor how the gas turbine is operated, prognostics capabilities that foresee maintenance needs, and test methods that can determine the state of a component during maintenance events. One important part of CAMP is therefore a prognostic tool which tells us the condition, and therefore the maintenance needs, of individual components within the gas turbine. To handle this information and efficiently make a preventive maintenance plan, software for gas turbine maintenance optimization has been developed. The software can not only calculate the most efficient point in time for a maintenance action, it can also adjust the maintenance plan to any customer’s specific demands. This paper describes the model, gathering and processing of information, risk assessment performance and the result from an optimization which groups maintenance actions as a result of customer prioritized demands. It also describes the software layout and how it is used.

UDIMET 718

Alloy Digest ◽  
1978 ◽  
Vol 27 (11) ◽  
Keyword(s):  
Gas Turbines ◽  
Base Alloy ◽  
Heat Treating ◽  
High Yield ◽  
Nickel Base Alloy ◽  
Aged Condition ◽  
High Yield Strength ◽  
Unusual Combination ◽  
Critical Components ◽  
Nickel Base

Abstract UDIMET 718 is a nickel-base alloy that is precipitation hardenable. It exhibits exceptionally high yield strength up to 1300 F, excellent cryogenic properties down to -423 F and superior weldability even in the fully-aged condition. This unusual combination of characteristics makes it suitable for elevated-temperature applications in gas turbines and in critical components for missiles. This datasheet provides information on composition, physical properties, elasticity, and tensile properties as well as creep. It also includes information on forming, heat treating, machining, joining, and surface treatment. Filing Code: Ni-258. Producer or source: Special Metals Corporation.

Life Prediction of Power Turbine Components for High Exhaust Back Pressure Applications: Part I — Disks

2015 ◽  
Author(s):  
Dipankar Dua ◽  
Brahmaji Vasantharao
Keyword(s):  
Steady State ◽  
Secondary Flow ◽  
Gas Turbines ◽  
Life Prediction ◽  
Creep Damage ◽  
Back Pressure ◽  
System Level ◽  
Cyclic Life ◽  
Power Turbine ◽  
The Impact

Industrial and aeroderivative gas turbines when used in CHP and CCPP applications typically experience an increased exhaust back pressure due to pressure losses from the downstream balance-of-plant systems. This increased back pressure on the power turbine results not only in decreased thermodynamic performance but also changes power turbine secondary flow characteristics thus impacting lives of rotating and stationary components of the power turbine. This Paper discusses the Impact to Fatigue and Creep life of free power turbine disks subjected to high back pressure applications using Siemens Energy approach. Steady State and Transient stress fields have been calculated using finite element method. New Lifing Correlation [1] Criteria has been used to estimate Predicted Safe Cyclic Life (PSCL) of the disks. Walker Strain Initiation model [1] is utilized to predict cycles to crack initiation and a fracture mechanics based approach is used to estimate propagation life. Hyperbolic Tangent Model [2] has been used to estimate creep damage of the disks. Steady state and transient temperature fields in the disks are highly dependent on the secondary air flows and cavity dynamics thus directly impacting the Predicted Safe Cyclic Life and Overall Creep Damage. A System-level power turbine secondary flow analyses was carried out with and without high back pressure. In addition, numerical simulations were performed to understand the cavity flow dynamics. These results have been used to perform a sensitivity study on disk temperature distribution and understand the impact of various back pressure levels on turbine disk lives. The Steady Sate and Transient Thermal predictions were validated using full-scale engine test and have been found to correlate well with the test results. The Life Prediction Study shows that the impact on PSCL and Overall Creep damage for high back pressure applications meets the product design standards.

Superalloy Cooling System for the Composite Rim of an Inside-Out Ceramic Turbine

2017 ◽  
Author(s):  
N. Courtois ◽  
F. Ebacher ◽  
P. K. Dubois ◽  
N. Kochrad ◽  
C. Landry ◽  
...  
Keyword(s):  
Gas Turbines ◽  
Cooling System ◽  
High Strength ◽  
Carbon Composite ◽  
Flow Rate Ratio ◽  
Small Scale ◽  
Inlet Temperature ◽  
Operating Temperatures ◽  
Critical Components ◽  
Inside Out

The use of ceramics in gas turbines potentially allows for very high cycle efficiency and power density, by increasing operating temperatures. This is especially relevant for sub-megawatt gas turbines, where the integration of complex blade cooling greatly affects machine capital cost. However, ceramics are brittle and prone to fragile, catastrophic failure, making their current use limited to static and low-stress parts. Using the inside-out ceramic turbine (ICT) configuration solves this issue by converting the centrifugal blade loading to compressive stress, by using an external high-strength carbon-polymer composite rim. This paper presents a superalloy cooling system designed to protect the composite rim and allow it to withstand operating temperatures up to 1600 K. The cooling system was designed using one-dimensional (1D) models, developed to predict flow conditions as well as the temperatures of its critical components. These models were subsequently supported with computational fluid dynamics and used to conduct a power scalability study on a single stage ICT. Results suggest that the ICT configuration should achieve a turbine inlet temperature (TIT) of 1600 K with a composite rim cooling-to-main mass flow rate ratio under 5.2% for power levels above 350 kW. A proof of concept was performed by experimental validation of a small-scale 15 kW prototype, using a commercially available bismaleimide-carbon (BMI-carbon) composite rim and Inconel® 718 nickel-based alloy. The combination of numerical and experimental results show that the ICT can operate at a TIT of 1100 K without damage to the composite rim.

scholarly journals Vulnerability analysis and method of selection of communication protocols for information transfer in Internet of Things systems

2021 ◽  
pp. 133-149
Author(s):  
Maryna Kolisnyk
Keyword(s):  
Internet Of Things ◽  
Initial Data ◽  
Information Transfer ◽  
System Analysis ◽  
Communication Protocols ◽  
Critical Systems ◽  
Smart Objects ◽  
Corporate System ◽  
The Given ◽  
Selection Of

The subject of study in the paper is the analysis of technologies, architectures, vulnerabilities and cyberattacks, communication patterns of smart objects, messaging models, and Internet of Things (IoT) / Web of Things (WoT) protocols for solving applied problems of critical and non-critical systems. The goal is to develop a method for selecting messaging models and application-level protocols in non-critical and critical multi-level IoT/WoT systems, provided that the type of access to intelligent objects is initially determined by the initial data, as well as analysis of vulnerabilities and attacks using these protocols. Objectives: to formalize the procedure for choosing communication protocols for IoT/WoT systems; analyze possible vulnerabilities of communication protocols; develop a method for selecting communication protocols for given initial data, depending on the selected type of communication template for smart objects; check practically the proposed method. The methods of research are methods of system analysis. The following results were obtained. The analysis of the features of communication protocols is conducted by comparing the main interrelated characteristics of IoT/WoT, the results of which are presented in the form of a table. A method has been developed for selecting communication protocols, depending on the selected type of communication template. The analysis of possible vulnerabilities of communication protocols and possible attacks using these protocols is conducted. The author has tested the method using the example of a corporate system (Smart House) based on the WoT concept. Findings. The scientific novelty of the results obtained is as follows: the analysis conducted in the paper shows that currently there is no unified approach to the choice of a messaging model and application-level protocols for building IoT/WoT, depending on the selected type of communication template for smart objects. The method for selecting communication protocols for the given conditions (for each IoT system its interaction pattern will correspond, depending on which components interact with each other), improved by the authors of the paper, makes it possible to simplify the task of using separate protocols for given IoT systems, considering vulnerabilities of protocols.

scholarly journals Effects of Turbine Design on Particulate Erosion of Turbine Airfoils

1991 ◽  
Author(s):  
J. H. Wagner ◽  
B. V. Johnson ◽  
D. W. Geiling
Keyword(s):  
Gas Turbines ◽  
Combustion Process ◽  
Particle Diameter ◽  
Surface Erosion ◽  
Erosion Rates ◽  
Trajectory Calculations ◽  
Design Characteristics ◽  
Turbine Airfoils ◽  
Turbine Design ◽  
Selection Of

An analytic study was conducted to determine the effects of turbine design, airfoil shape and material on particulate erosion of turbine airfoils in coal-fueled, direct-fired gas turbines used for electric power generation. First-stage, mean-line airfoil sections were designed for 80 MW output turbines with 3 and 4 stages. Two-dimensional particle trajectory calculations and erosion rate analyses were performed for a range of particle diameters and densities and for ductile and ceramic airfoil materials. Results indicate that the surface erosion rates can vary by a factor of 5 and that erosion on rotating blades is not well correlated with particle diameter. The results quantify the cause/effect turbine design relationships expected and assist in the selection of turbine design characteristics for use downstream of a coal-fueled combustion process.

scholarly journals Modelling of Metallic Particle Binders for Increased Part Density in Binder Jet Printed Components

2019 ◽  
Author(s):  
Joseph Roberts ◽  
Peter Green ◽  
Kate Black ◽  
Christopher Sutcliffe
Keyword(s):  
Particle Size ◽  
Critical Radius ◽  
Detailed Knowledge ◽  
Particle Sizes ◽  
Powder Bed ◽  
Beneficial Effects ◽  
Drop Tests ◽  
Maximum Particle ◽  
Packing Efficiency ◽  
Selection Of

Binder jet printed components typically have low overall density in the green state and high shrinkage and deformation after heat treatment. It has previously been demonstrated that, by including nanoparticles of the same material in the binder, these properties can be improved as the nanoparticles can fill the interstices and pore throats between the bed particles. The beneficial effects from using these additive binder particles can be improved by maximising the binder particle size, enabling the space within the powder bed to be filled with a higher packing efficiency. The selection of maximum particle size for a binder requires detailed knowledge of the pores and pore throats between the powder bed particles. In this paper, a raindrop model is developed to determine the critical radius at which binder particles can pass between pores and penetrate the bed. The model is validated against helium pycnometry measurements and binder particle drop tests. It is found that the critical radius can be predicted, with acceptable accuracy, using a linear function of the mean and standard deviation of the particle radii. Percolation theory concepts have been employed in order to generalise the results for powder beds that have different mean particle sizes and size distributions. The results of this work can be employed to inform the selection of particle sizes required for binder formulations, to optimise density and reduce shrinkage in printed binder jet components.

scholarly journals Machine Learning in Gas Turbines

2018 ◽  
Vol 140 (09) ◽  
pp. S54-S55 ◽  
Author(s):  
V. Michelassi ◽  
C. Allegorico ◽  
S. Cioncolini ◽  
A. Graziano ◽  
L. Tognarelli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Applications Of Machine Learning ◽  
Selection Of

This paper describes a selection of Baker Hughes, a GE company (BHGE) activities to support Gas Turbine (GT) design and operation from simple to more elaborate applications of Machine Learning (ML).

Enhanced Early Warning Diagnostic Rules for Gas Turbines Leveraging on Bayesian Networks

2020 ◽  
Author(s):  
Ernesto Escobedo ◽  
Liliana Arguello ◽  
Marzia Sepe ◽  
Ilaria Parrella ◽  
Stefano Cioncolini ◽  
...  
Keyword(s):  
Gas Turbines ◽  
Probabilistic Approach ◽  
Training Dataset ◽  
Auxiliary Equipment ◽  
Data Set ◽  
Deep Dive ◽  
Industrial Systems ◽  
Business Application ◽  
Model Training ◽  
Selection Of

Abstract The monitoring and diagnostics of Industrial systems is increasing in complexity with larger volume of data collected and with many methods and analytics able to correlate data and events. The setup and training of these methods and analytics are one of the impacting factors in the selection of the most appropriate solution to provide an efficient and effective service, that requires the selection of the most suitable data set for training of models with consequent need of time and knowledge. The study and the related experiences proposed in this paper describe a methodology for tracking features, detecting outliers and derive, in a probabilistic way, diagnostic thresholds to be applied by means of hierarchical models that simplify or remove the selection of the proper training dataset by a subject matter expert at any deployment. This method applies to Industrial systems employing a large number of similar machines connected to a remote data center, with the purpose to alert one or more operators when a feature exceeds the healthy distribution. Some relevant use cases are presented for an aeroderivative gas turbine covering also its auxiliary equipment, with deep dive on the hydraulic starting system. The results, in terms of early anomaly detection and reduced model training effort, are compared with traditional monitoring approaches like fixed threshold. Moreover, this study explains the advantages of this probabilistic approach in a business application like the fleet monitoring and diagnostic advanced services.

Diversity and Multi-Version Systems

2014 ◽  
pp. 178-232
Author(s):  
Alexander Siora ◽  
Vladimir Sklyar ◽  
Vyacheslav Kharchenko ◽  
Eugene Brezhnev
Keyword(s):  
Printed Circuit Boards ◽  
Linguistic Diversity ◽  
Cost Effective ◽  
Ordinal Scale ◽  
Critical Systems ◽  
Safety Critical ◽  
Common Cause Failures ◽  
Safety Critical Systems ◽  
Diversity Strategy ◽  
Selection Of

To protect safety-critical systems from common-cause failures that can lead to potentially dangerous outcomes, special methods are applied, including multi-version technologies operating at different levels of diversity. A model representing different diversity types during the development of safety-critical systems is suggested. The model addresses diversity types that are the most expedient in providing required safety. The diversity of complex electronic components (FPGA, etc.), printed circuit boards, manufacturers, specification languages, design, and program languages, etc. are considered. The challenges addressed are related to factors of scale and dependencies among diversity types, since not all combinations of used diversity are feasible. Taking these dependencies into consideration, the model simplifies the choice of diversity options. This chapter presents a cost effective approach to selection of the most diverse NPP Reactor Trip System (RTS) under uncertainty. The selection of a pair of primary and secondary RTS is named a diversity strategy. All possible strategies are evaluated on an ordinal scale with linguistic values provided by experts. These values express the expert’s degree of confidence that evaluated variants of secondary RTS are different from primary. All diversity strategies are evaluated on a set of linguistic diversity criteria, which are included into a corresponding diversity attribute. The generic fuzzy diversity score is an aggregation of the linguistic values provided by the experts to obtain a collective assessment of the secondary RTS’s similarity (difference) with a primary one. This rational diversity strategy is found during the exploitation stage, taking into consideration the fuzzy diversity score and cost.

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