Uncertainty Quantification, Rare Events and Mission Optimization: Stochastic Variations of Metal Temperature During a Transient

2014 ◽  
Author(s):  
F. Montomoli ◽  
D. Amirante ◽  
N. Hills ◽  
S. Shahpar ◽  
M. Massini
Keyword(s):  
Standard Deviation ◽  
Gas Turbines ◽  
Rare Events ◽  
Real Life ◽  
Rare Event ◽  
Thermal Response ◽  
Small Variation ◽  
Metal Temperature ◽  
Thermal Gradients ◽  
Maximum Standard Deviation

Gas turbines are designed to follow specific missions and the metal temperature is usually predicted with deterministic methods. However, in real life the mission is subjected to strong variations which can affect the thermal response of the components. This paper presents a stochastic analysis of the metal temperature variations during a gas turbine transient. A Monte Carlo Method (MCM) with Meta Model is used to evaluate the probability distribution of the stator disk temperature. The MCM is applied to a series of CFD simulations of a stator well, whose geometry is modified according to the deformations predicted during the engine cycle by a coupled thermo-mechanical analysis of the metal components. It is shown that even considering a narrow band for the stochastic output, +/− σ, the transient thermal gradients can be up to two orders of magnitude greater than those obtained with a standard deterministic analysis. Moreover, a small variation in the tail of the input probability density function, a rare event, can have serious consequences on the uncertainty level of the temperature. Rare events although inevitable they are not usually considered during the design phase. In this paper it is shown for the first time that is possible to mitigate their effect, minimizing the maximum standard deviation induced by the tail of the input PDF. The mission optimization reduces the maximum standard deviation by 15% and the mean standard deviation of about 12%. The maximum thermal gradients are also reduced by 10%, although this was not the parameter used as the goal in the optimisation study.

Uncertainty Quantification, Rare Events, and Mission Optimization: Stochastic Variations of Metal Temperature During a Transient

2014 ◽  
Vol 137 (4) ◽  
Author(s):  
F. Montomoli ◽  
D. Amirante ◽  
N. Hills ◽  
S. Shahpar ◽  
M. Massini
Keyword(s):  
Standard Deviation ◽  
Gas Turbines ◽  
Rare Events ◽  
Real Life ◽  
Rare Event ◽  
Thermal Response ◽  
Small Variation ◽  
Metal Temperature ◽  
Thermal Gradients ◽  
Maximum Standard Deviation

Gas turbines are designed to follow specific missions and the metal temperature is usually predicted with deterministic methods. However, in the real life, the mission is subjected to strong variations which can affect the thermal response of the components. This paper presents a stochastic analysis of the metal temperature variations during a gas turbine transient. A Monte Carlo method (MCM) with meta-model is used to evaluate the probability distribution of the stator disk temperature. The MCM is applied to a series of computational fluid dynamics (CFD) simulations of a stator well, whose geometry is modified according to the deformations predicted during the engine cycle by a coupled thermomechanical analysis of the metal components. It is shown that even considering a narrow band for the stochastic output, ±σ, the transient thermal gradients can be up to two orders of magnitude greater than those obtained with a standard deterministic analysis. Moreover, a small variation in the tail of the input probability density function (PDF), a rare event, can have serious consequences on the uncertainty level of the temperature. Rare events although inevitable they are not usually considered during the design phase. In this paper, it is shown for the first time that is possible to mitigate their effect, minimizing the maximum standard deviation induced by the tail of the input PDF. The mission optimization reduces the maximum standard deviation by 15% and the mean standard deviation of about 12%. The maximum thermal gradients are also reduced by 10%, although this was not the parameter used as the goal in the optimization study.

Framework for rare event detection using Artificial Neural Network based context free grammar

2020 ◽  
Vol 39 (6) ◽  
pp. 8463-8475
Author(s):  
Palanivel Srinivasan ◽  
Manivannan Doraipandian
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Event Detection ◽  
Performance Metrics ◽  
Rare Events ◽  
Rare Event ◽  
Video Stream ◽  
Context Free Grammar ◽  
Artificial Neural ◽  
Context Free

Rare event detections are performed using spatial domain and frequency domain-based procedures. Omnipresent surveillance camera footages are increasing exponentially due course the time. Monitoring all the events manually is an insignificant and more time-consuming process. Therefore, an automated rare event detection contrivance is required to make this process manageable. In this work, a Context-Free Grammar (CFG) is developed for detecting rare events from a video stream and Artificial Neural Network (ANN) is used to train CFG. A set of dedicated algorithms are used to perform frame split process, edge detection, background subtraction and convert the processed data into CFG. The developed CFG is converted into nodes and edges to form a graph. The graph is given to the input layer of an ANN to classify normal and rare event classes. Graph derived from CFG using input video stream is used to train ANN Further the performance of developed Artificial Neural Network Based Context-Free Grammar – Rare Event Detection (ACFG-RED) is compared with other existing techniques and performance metrics such as accuracy, precision, sensitivity, recall, average processing time and average processing power are used for performance estimation and analyzed. Better performance metrics values have been observed for the ANN-CFG model compared with other techniques. The developed model will provide a better solution in detecting rare events using video streams.

scholarly journals Interspecies Chromosome Mapping in Caprimulgiformes, Piciformes, Suliformes, and Trogoniformes (Aves): Cytogenomic Insight into Microchromosome Organization and Karyotype Evolution in Birds

Cells ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 826
Author(s):  
Rafael Kretschmer ◽  
Marcelo Santos de Souza ◽  
Ivanete de Oliveira Furo ◽  
Michael N. Romanov ◽  
Ricardo José Gunski ◽  
...  
Keyword(s):  
Convergent Evolution ◽  
Karyotype Evolution ◽  
Rare Events ◽  
Rare Event ◽  
Chromosome Mapping ◽  
The Other ◽  
Other Hand ◽  
Interchromosomal Rearrangement ◽  
Insight Into ◽  
Phalacrocorax Brasilianus

Interchromosomal rearrangements involving microchromosomes are rare events in birds. To date, they have been found mostly in Psittaciformes, Falconiformes, and Cuculiformes, although only a few orders have been analyzed. Hence, cytogenomic studies focusing on microchromosomes in species belonging to different bird orders are essential to shed more light on the avian chromosome and karyotype evolution. Based on this, we performed a comparative chromosome mapping for chicken microchromosomes 10 to 28 using interspecies BAC-based FISH hybridization in five species, representing four Neoaves orders (Caprimulgiformes, Piciformes, Suliformes, and Trogoniformes). Our results suggest that the ancestral microchromosomal syntenies are conserved in Pteroglossus inscriptus (Piciformes), Ramphastos tucanus tucanus (Piciformes), and Trogon surrucura surrucura (Trogoniformes). On the other hand, chromosome reorganization in Phalacrocorax brasilianus (Suliformes) and Hydropsalis torquata (Caprimulgiformes) included fusions involving both macro- and microchromosomes. Fissions in macrochromosomes were observed in P. brasilianus and H. torquata. Relevant hypothetical Neognathae and Neoaves ancestral karyotypes were reconstructed to trace these rearrangements. We found no interchromosomal rearrangement involving microchromosomes to be shared between avian orders where rearrangements were detected. Our findings suggest that convergent evolution involving microchromosomal change is a rare event in birds and may be appropriate in cytotaxonomic inferences in orders where these rearrangements occurred.

scholarly journals Implementasi Graph Clustering Algorithm Modification Maximum Standard Deviation Reduction (MMSDR) dalam Clustering Provinsi di Indonesia Menurut Indikator Kesejahteraan Rakyat

Faktor Exacta ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 73
Author(s):  
Nurfidah Dwitiyanti ◽  
Septian Wulandari ◽  
Noni Selvia
Keyword(s):  
Economic Growth ◽  
Standard Deviation ◽  
Clustering Algorithm ◽  
Graph Clustering ◽  
Public Welfare ◽  
Poor People ◽  
Equitable Distribution ◽  
Maximum Standard Deviation ◽  
Central Statistics

<p>The population of Indonesia from year to year has increased. The increase in population must also be accompanied by increased economic growth in Indonesia. The increase in economic growth in Indonesia is marked by the reduction in the number of poor people in Indonesia. In addition, the increase in economic growth is reflected in the equitable distribution of public income in the country. Even though there are still many Indonesian people who are not yet prosperous in economic terms. To overcome, it is necessary to have clustering and characteristics of 34 provinces in Indonesia by implementing the Modification Maximum Standard Deviation Reduction (MMSDR) graph clustering algorithm. The data used are indicators of public welfare in 2017 obtained from the Central Statistics Agency. There are 9 indicators of community welfare used in this research. There are four stages in the MMSDR algorithm namely the "MST", "Subdivide", "Biggest Stepping" and "Create Clusters" processes. The results of this study can be seen from the distance between the nodes or between one province and another province produced 22 clusters. From the cluster results obtained using the MMSDR algorithm on welfare data, there are many clusters formed with cluster members formed at most two nodes (province).</p><p> Keywords: MMSDR, Clustering, Welfare of People</p>

Support Vibration Diagnostics and Limits in Gas Turbines

2016 ◽  
Author(s):  
Marcin Bielecki ◽  
Salvatore Costagliola ◽  
Piotr Gebalski
Keyword(s):  
Gas Turbine ◽  
Test Data ◽  
Gas Turbines ◽  
Failure Modes ◽  
Real Life ◽  
Reliability Function ◽  
Vibration Diagnostics ◽  
Real Life Data ◽  
Industrial Gas Turbines ◽  
Harmful Effects

The paper deliberates vibration limits for non-rotating parts in application to industrial gas turbines. As a rule such limits follow ISO 10816-4 or API616, although in field operation it is not well known relationship between these limits and failure modes. In many situations, the reliability function is not well-defined, and more comprehensive methods of determining the harmful effects of support vibrations are desirable. In the first part, the undertaken approach and the results are illustrated based on the field and theoretical experience of the authors about the failure modes related to alarm level of vibrations. Here several failure modes and diagnostics observations are illustrated with the examples of real-life data. In the second part, a statistical approach based on correlation of support vs. shaft vibrations (velocity / displacement) is demonstrated in order to assess the risk of the bearing rub. The test data for few gas turbine models produced by General Electric Oil & Gas are statistically evaluated and allow to draw an experimentally based transfer function between vibrations recorded by non-contact and seismic probes. Then the vibration limit with objectives like bearing rub is scrutinized with aid of probabilistic tools. In the third part, the attention is given to a few examples of the support vibrations — among other gas turbine with rotors supported on flexible pedestals and baseplate. Here there is determined a transfer coefficient between baseplate and bearing vibrations for specific foundation configurations. Based on the test data screening as well as analysis and case studies thereof, the conclusions about more specific vibration limits in relation to the failure modes are drawn.

Temperature-Based Optimization of Film Cooling in Gas Turbine Hot Gas Path Components

2013 ◽  
Author(s):  
Felipe A. C. Viana ◽  
Jack Madelone ◽  
Niranjan Pai ◽  
Genghis Khan ◽  
Sanghum Baik
Keyword(s):  
Film Cooling ◽  
Gas Turbines ◽  
Optimization Design ◽  
Goal Attainment ◽  
High Efficiency ◽  
Cooling System ◽  
Computational Cost ◽  
Metal Temperature ◽  
Cooling Flow ◽  
Hot Gas

To achieve high efficiency, modern gas turbines operate at temperatures that exceed melting points of metal alloys used in turbine hot gas path parts. Parts exposed to hot gas are actively cooled with a portion of the compressor discharge air (e.g., through film cooling) to keep the metal temperature at levels needed to meet durability requirements. However, to preserve efficiency, it is important to optimize the cooling system to use the least amount of cooling flow. In this study, film cooling optimization is achieved by varying cooling hole diameters, hole to hole spacing, and film row placements so that the specified targets for maximum metal temperature are met while preserving (or saving) cooling flow. The computational cost of the high-fidelity physics models, the large number of design variables, the large number and nonlinearity of responses impose severe challenges to numerical optimization. Design of experiments and cheap-to-evaluate approximations (radial basis functions) are used to alleviate the computational burden. Then, the goal attainment method is used for optimizing of film cooling configuration. The results for a turbine blade design show significant improvements in temperature distribution while maintaining/reducing the amount of used cooling flow.

Effect of Turbine Blade Tip Cooling Configuration on Tip Leakage Flow and Heat Transfer

2020 ◽  
Vol 142 (2) ◽  
Author(s):  
Sergen Sakaoglu ◽  
Harika S. Kahveci
Keyword(s):  
Heat Transfer ◽  
Turbine Blade ◽  
Gas Turbines ◽  
Thermal Response ◽  
Thermal Conditions ◽  
Tip Clearance ◽  
Leakage Flow ◽  
Tip Leakage Flow ◽  
Tip Leakage ◽  
Blade Tip

Abstract The pressure difference between suction and pressure sides of a turbine blade leads to tip leakage flow, which adversely affects the first-stage high-pressure (HP) turbine blade tip aerodynamics. In modern gas turbines, HP turbine blade tips are exposed to extreme thermal conditions requiring cooling. If the coolant jet directed into the blade tip gap cannot counter the leakage flow, it will simply add up to the pressure losses due to leakage. Therefore, the compromise between the aerodynamic loss and the gain in tip-cooling effectiveness must be optimized. In this paper, the effect of tip-cooling configuration on the turbine blade tip is investigated numerically from both aerodynamics and thermal aspects to determine the optimum configuration. Computations are performed using the tip cross section of GE-E3 HP turbine first-stage blade for squealer and flat tips, where the number, location, and diameter of holes are varied. The study presents a discussion on the overall loss coefficient, total pressure loss across the tip clearance, and variation in heat transfer on the blade tip. Increasing the coolant mass flow rate using more holes or by increasing the hole diameter results in a decrease in the area-averaged Nusselt number on the tip floor. Both aerodynamic and thermal response of squealer tips to the implementation of cooling holes is superior to their flat counterparts. Among the studied configurations, the squealer tip with a larger number of cooling holes located toward the pressure side is highlighted to have the best cooling performance.

Sequential Sampling Based Reliability Analysis for High Dimensional Rare Events With Confidence Intervals

2020 ◽  
Author(s):  
Yanwen Xu ◽  
Pingfeng Wang
Keyword(s):  
Confidence Interval ◽  
Confidence Intervals ◽  
Computational Efficiency ◽  
Rare Events ◽  
Computational Cost ◽  
Rare Event ◽  
Probability Analysis ◽  
High Dimensional ◽  
Dimensional System ◽  
Study Results

Abstract Analysis of rare failure events accurately is often challenging with an affordable computational cost in many engineering applications, and this is especially true for problems with high dimensional system inputs. The extremely low probabilities of occurrences for those rare events often lead to large probability estimation errors and low computational efficiency. Thus, it is vital to develop advanced probability analysis methods that are capable of providing robust estimations of rare event probabilities with narrow confidence bounds. Generally, confidence intervals of an estimator can be established based on the central limit theorem, but one of the critical obstacles is the low computational efficiency, since the widely used Monte Carlo method often requires a large number of simulation samples to derive a reasonably narrow confidence interval. This paper develops a new probability analysis approach that can be used to derive the estimates of rare event probabilities efficiently with narrow estimation bounds simultaneously for high dimensional problems. The asymptotic behaviors of the developed estimator has also been proved theoretically without imposing strong assumptions. Further, an asymptotic confidence interval is established for the developed estimator. The presented study offers important insights into the robust estimations of the probability of occurrences for rare events. The accuracy and computational efficiency of the developed technique is assessed with numerical and engineering case studies. Case study results have demonstrated that narrow bounds can be built efficiently using the developed approach, and the true values have always been located within the estimation bounds, indicating that good estimation accuracy along with a significantly improved efficiency.

Graph Theoretic Analysis of Advance Combined Cycle Power Plants Alternatives With Latest Gas Turbines

2013 ◽  
Author(s):  
Nikhil Dev ◽  
Gopal Krishan Goyal ◽  
Rajesh Attri ◽  
Naresh Kumar
Keyword(s):  
Power Plant ◽  
Gas Turbines ◽  
Heat Recovery ◽  
Power Plants ◽  
Real Life ◽  
Combined Cycle ◽  
Turbine Engines ◽  
Steam Generation ◽  
Graph Theoretic ◽  
Early Decision

In the present work, graph theory and matrix method is used to analyze some of the heat recovery possibilities with the newly available gas turbine engines. The schemes range from dual pressure heat recovery steam generation systems, to triple pressure systems with reheat in supercritical steam conditions. From the developed methodology, result comes out in the form of a number called as index. A real life operating Combined Cycle Power Plant (CCPP) is a very large and complex system. Efficiency of its components and sub-systems are closely intertwined and insuperable without taking the effect of others. For the development of methodology, CCPP is divided into six sub-systems in such a way that no sub-system is independent. Digraph for the interdependencies of sub-system is organized and converted into matrix form for easy computer processing. The results obtained with present methodology are in line with the results available in literature. The methodology is developed with a view that power plant managers can take early decision for selection, improvements and comparison, amongst the various options available, without having in-depth knowledge of thermodynamics analysis.

scholarly journals Redesign of the MS6001 First Stage Bucket for Improved Cooling and Extended Life

1997 ◽  
Author(s):  
Jerry K. Jaqueway ◽  
Robert J. Pistor
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Service Life ◽  
Metal Temperature ◽  
Thermal Gradients ◽  
Element Analysis ◽  
Cooling Performance ◽  
Bulk Metal ◽  
Cooling Design ◽  
Unit Performance

The objective of this paper is to critically review the cooling design for the MS6001 first stage buckets and examine alternate designs for improved cooling. Several basic designs were considered to improve cooling performance, extend service life, and improve the reliability of the first stage bucket. Of the designs being considered and compared with existing and past designs, two options containing 13 and 13M (modified) cooling holes were investigated. The target for the design which was met by the 13M design, was to reduce bucket bulk metal temperature by an average of 13.9°C (25°F), while maintaining current unit performance and bucket integrity. Finite element analysis was performed to evaluate the aerofoil thermal gradients and the results demonstrate that a cooler core and an overall reduction in bulk metal temperature was obtained with the modified designs. In addition to the design analysis, bucket alloys were reviewed and IN-738 was chosen for its reliability and predictable performance.

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