Bayesian Inference of Experimental Data for Axial Compressor Performance Assessment

2021 ◽  
Author(s):  
Gonçalo G. Cruz ◽  
Cedric Babin ◽  
Xavier Ottavy ◽  
Fabrizio Fontaneto
Keyword(s):  
Bayesian Inference ◽  
Data Assimilation ◽  
Axial Compressor ◽  
Cost Effective ◽  
Radial Pressure ◽  
Good Prediction ◽  
Evaluation Of Performance ◽  
2D Flow ◽  
Assimilation Process ◽  
Compressor Map

Abstract As the next generation of turbomachinery components becomes more sensitive to instrumentation intrusiveness, a reduction of the number of measurement devices required for the evaluation of performance is a possible and cost-effective way to mitigate the arising of non-mastered experimental errors. A first approach to a data assimilation methodology based on Bayesian inference is developed with the aim of reducing the instrumentation effort. A numerical model is employed to provide an initial belief of the flow, that is then updated based on experimental observations, using an ensemble Kalman filter algorithm for inverse problems. Validation of the algorithm is achieved with the usage of experimental measurements not used in the data assimilation process. The methodology is tested for a low aspect ratio axial compressor stage, showing a good prediction of the corrected compressor map, as well as a promising prediction of the inter-row radial pressure distribution and 2D flow field.

Quick Start of an Industrial Gas Turbine Engine Through the Development of “Silent Start” VGV Schedule

2020 ◽  
Author(s):  
Senthil Krishnababu ◽  
Vili Panov ◽  
Simon Jackson ◽  
Andrew Dawson
Keyword(s):  
Guide Vane ◽  
Pressure Ratio ◽  
Axial Compressor ◽  
Rotating Stall ◽  
Rotor Blades ◽  
Start Time ◽  
Turbine Engine ◽  
High Pressure Ratio ◽  
Compressor Map ◽  
Industrial Gas Turbine

Abstract In this paper, research that was carried out to optimise an initial variable guide vane schedule of a high-pressure ratio, multistage axial compressor is reported. The research was carried out on an extensively instrumented scaled compressor rig. The compressor rig tests carried out employing the initial schedule identified regions in the low speed area of the compressor map that developed rotating stall. Rotating stall regions that caused undesirable non-synchronous vibration of rotor blades were identified. The variable guide vane schedule optimisation carried out balancing the aerodynamic, aero-mechanical and blade dynamic characteristics gave the ‘Silent Start’ variable guide vane schedule, that prevented the development of rotating stall in the start regime and removed the non-synchronous vibration. Aerodynamic performance and aero-mechanical characteristics of the compressor when operated with the initial schedule and the optimised ‘Silent Start’ schedule are compared. The compressor with the ‘Silent Start’ variable guide vane schedule when used on a twin shaft engine reduced the start time to minimum load by a factor of four and significantly improved the operability of the engine compared to when the initial schedule was used.

scholarly journals Efficient ensemble data assimilation for coupled models with the Parallel Data Assimilation Framework: Example of AWI-CM

2019 ◽  
Author(s):  
Lars Nerger ◽  
Qi Tang ◽  
Longjiang Mu
Keyword(s):  
Data Assimilation ◽  
Numerical Models ◽  
Computing Time ◽  
Coupled Model ◽  
Ocean Model ◽  
Coupled Models ◽  
Parallel Data ◽  
Efficient Data ◽  
Abstract Data ◽  
Assimilation Process

Abstract. Data assimilation integrates information from observational measurements with numerical models. When used with coupled models of Earth system compartments, e.g. the atmosphere and the ocean, consistent joint states can be estimated. A common approach for data assimilation are ensemble-based methods which use an ensemble of state realizations to estimate the state and its uncertainty. These methods are far more costly to compute than a single coupled model because of the required integration of the ensemble. However, with uncoupled models, the methods also have been shown to exhibit a particularly good scaling behavior. This study discusses an approach to augment a coupled model with data assimilation functionality provided by the Parallel Data Assimilation Framework (PDAF). Using only minimal changes in the codes of the different compartment models, a particularly efficient data assimilation system is generated that utilizes parallelization and in-memory data transfers between the models and the data assimilation functions and hence avoids most of the filter reading and writing and also model restarts during the data assimilation process. The study explains the required modifications of the programs on the example of the coupled atmosphere-sea ice-ocean model AWI-CM. Using the case of the assimilation of oceanic observations shows that the data assimilation leads only small overheads in computing time of about 15 % compared to the model without data assimilation and a very good parallel scalability. The model-agnostic structure of the assimilation software ensures a separation of concerns in that the development of data assimilation methods and be separated from the model application.

scholarly journals Evaluation of in-situ wind speed and wave height measurements against reanalysis data for the Greek Seas

2017 ◽  
pp. 486 ◽  
Author(s):  
DAFNI SIFNIOTI ◽  
TAKVOR SOUKISSIAN ◽  
SERAFEIM POULOS ◽  
PANAGIOTIS NASTOS ◽  
MARIA HATZAKI
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Reanalysis Data ◽  
Error Statistics ◽  
Evaluation Of Performance ◽  
Assimilation Process ◽  
Temporal And Spatial ◽  
Wave Hindcasting ◽  
Buoy Data

ERA-Interim, ECMWF’s reanalysis product, includes wave and atmospheric characteristics, with high temporal and spatial scale, providing more information on the marine state. Even though their assimilation process has been validated and verified in numerous studies, their performance in more local scales is still under examination. This research focuses on the evaluation of performance of ERA-Interim reanalysis datasets in the Greek Seas for wind and wave characteristics in comparison to POSEIDON buoy data. The results prove fair to good correlation for wave height (r = 0.67-0.94) and wind speed (r= 0.71-0.83) and different error statistics per sub-region. The upper 10% analysis shows an underestimate of 10-15% for wind speed and wave height from ERA-Interim in relation to the buoy measurements. The ERA-Interim and the buoy monthly means and standard deviations are also presented and discussed according to seasonal patterns. The results of the study are compared to other researches of wave hindcasting and wind reanalysis data for the Greek Seas and globally. It is shown that ERA-Interim products could be regarded as representative for the Greek Seas, although their application should be made with caution regarding the assessment of extreme conditions (i.e. given in analyses of upper percentiles) and especially at nearshore locations due to complex coastline configuration enhanced by the great number of islands.

scholarly journals Inter-Stage Dynamic Performance of an Axial Compressor of a Twin-Shaft Industrial Gas Turbine

Machines ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 83
Author(s):  
Samuel Cruz-Manzo ◽  
Senthil Krishnababu ◽  
Vili Panov ◽  
Chris Bingham
Keyword(s):  
Gas Turbine ◽  
Dynamic Performance ◽  
Axial Compressor ◽  
Modeling Framework ◽  
Axial Compressors ◽  
Stage Performance ◽  
Compressor Map ◽  
Stage Characteristic ◽  
Industrial Gas Turbine ◽  
Semi Empirical

In this study, the inter-stage dynamic performance of a multistage axial compressor is simulated through a semi-empirical model constructed in the Matlab Simulink environment. A semi-empirical 1-D compressor model developed in a previous study has been integrated with a 0-D twin-shaft gas turbine model developed in the Simulink environment. Inter-stage performance data generated through a high-fidelity design tool and based on throughflow analysis are considered for the development of the inter-stage modeling framework. Inter-stage performance data comprise pressure ratio at various speeds with nominal variable stator guide vane (VGV) positions and with hypothetical offsets to them with respect to the gas generator speed (GGS). Compressor discharge pressure, fuel flow demand, GGS and power turbine speed measured during the operation of a twin-shaft industrial gas turbine are considered for the dynamic model validation. The dynamic performance of the axial-compressor, simulated by the developed modeling framework, is represented on the overall compressor map and individual stage characteristic maps. The effect of extracting air through the bleed port in the engine center-casing on transient performance represented on overall compressor map and stage performance maps is also presented. In addition, the dynamic performance of the axial-compressor with an offset in VGV position is represented on the overall compressor map and individual stage characteristic maps. The study couples the fundamental principles of axial compressors and a semi-empirical modeling architecture in a complementary manner. The developed modeling framework can provide a deeper understanding of the factors that affect the dynamic performance of axial compressors.

scholarly journals Best Paper Selection

2019 ◽  
Vol 28 (01) ◽  
pp. 055-055
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Bayesian Inference ◽  
Data Assimilation ◽  
Image Enhancement ◽  
Privacy Preserving ◽  
Similarity Learning ◽  
Cardiac Image ◽  
The Future

Albers DJ, Levine ME, Stuart A, Mamykina L, Gluckman B, Hripcsak G. Mechanistic machine learning: how data assimilation leverages physiological knowledge using bayesian inference to forecast the future, infer the present, and phenotype. J Am Med Inform Assoc 2018;25(10):1392-401 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6188514/ Oktay O, Ferrante E, Kamnitsas K, Heinrich M, Bai W, Caballero J, Cook SA, de Marvao A, Dawes T, O'Regan DP, Kainz B, Glocker B, Rueckert D. Anatomically Constrained Neural Networks (ACNNs): application to cardiac image enhancement and segmentation. IEEE Trans Med Imaging 2018;37(2):384-95 https://spiral.imperial.ac.uk:8443/handle/10044/1/50440 Lee J, Sun J, Wang F, Wang S, Jun CH, Jiang X. Privacy-preserving patient similarity learning in a federated environment: development and analysis. JMIR Med Inform 2018;6(2):e20 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5924379/

Cross Validation of Multistage Compressor Map Generation by Means of Computational Fluid Dynamics and Stage-Stacking Techniques

2014 ◽  
Author(s):  
Nicola Aldi ◽  
Mirko Morini ◽  
Michele Pinelli ◽  
Pier Ruggero Spina ◽  
Alessio Suman
Keyword(s):  
Experimental Data ◽  
Fluid Dynamic ◽  
Three Dimensional ◽  
Axial Compressor ◽  
Map Generation ◽  
Multistage Compressor ◽  
Compressor Map ◽  
Set Up ◽  
Main Effects

Gas turbine operating state determination consists of the assessment of the modification, due to deterioration and fault, of performance and geometric data characterizing machine components. One of the main effects of deterioration and fault is the modification of compressor and turbine performance maps. In this paper, three-dimensional numerical simulations of a multistage axial compressor are carried out. As a case study, the axial sections (i.e. the first six stages) of the Allison 250-C18 axial-centrifugal compressor are considered for the numerical investigation. Simulations are performed by means of a commercial computational fluid dynamic code. A multistage numerical model is set up and validated against the experimental data, gathered from an in-house test rig. Computed performance maps and main flow field features show fairly good agreement with the experimental data. The model is then used to cross-validate the results of zero-dimensional stage-stacking procedures and the stage maps obtained by means of a multistage CFD calculation (i.e. to evaluate the mutual consistency of the two methods for the generation of multistage compressor maps). The stage-stacking procedure results adequately fit the behavior of the multistage compressor.

scholarly journals Treatment of Observation Error due to Unresolved Scales in Atmospheric Data Assimilation

2006 ◽  
Vol 134 (10) ◽  
pp. 2900-2915 ◽  
Author(s):  
Tijana Janjić ◽  
Stephen E. Cohn
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Covariance Matrix ◽  
Covariance Function ◽  
Model Problem ◽  
Numerical Models ◽  
Observation Error ◽  
State Dependent ◽  
Full State ◽  
Assimilation Process

Abstract Observations of the atmospheric state include scales of motion that are not resolved by numerical models into which the observed data are assimilated. The resulting observation error due to unresolved scales, part of the “representativeness error,” is state dependent and correlated in time. A mathematical formalism and algorithmic approach has been developed for treating this error in the data assimilation process, under an assumption that there is no model error. The approach is based on approximating the continuum Kalman filter in such a way as to maintain terms that account for the observation error due to unresolved scales. The two resulting approximate filters resemble the Schmidt–Kalman filter and the traditional discrete Kalman filter. The approach is tested for the model problem of a passive tracer undergoing advection in a shear flow on the sphere. The state contains infinitely many spherical harmonics, with a nonstationary spectrum, and the problem is to estimate the projection of this state onto a finite spherical harmonic expansion, using observations of the full state. Numerical experiments demonstrate that approximate filters work well for the model problem provided that the exact covariance function of the unresolved scales is known. The traditional filter is more convenient in practice since it requires only the covariance matrix obtained by evaluating this covariance function at the observation points. A method for modeling this covariance matrix in the traditional filter is successful for the model problem.

Residence Time Distribution and Disinfection of Secondary Effluents by Infiltration Percolation

1999 ◽  
Vol 40 (4-5) ◽  
pp. 215-222 ◽  
Author(s):  
F. Brissaud ◽  
M. Salgot ◽  
A. Bancolé ◽  
C. Campos ◽  
M. Folch
Keyword(s):  
Pilot Plant ◽  
Time Distribution ◽  
Wastewater Reuse ◽  
Cost Effective ◽  
Maximum Load ◽  
Faecal Coliform ◽  
Good Prediction ◽  
Agricultural Wastewater ◽  
Secondary Effluents ◽  
The Relationship

Infiltration percolation is used as a tertiary treatment in order to meet the WHO's microbiological standards applying to unrestricted agricultural wastewater reuse. Faecal coliform removal, Δfc, was investigated in laboratory columns and on a 565 m2 pilot plant. Δfc observed in laboratory columns was shown to be closely related to water detention time distribution, DTD. The relationship between Δfc and DTD, which has been determined from column tests, allowed a good prediction of the disinfection performances of the pilot plant for hydraulic loads of 0.54 and 0.66 m/d. For 0.82 m/d, the maximum load that could be tested on the plant, the mean faecal coliform removal was more than 1 log. unit higher than predicted. These unexpected good performances, though calling for more comprehensive explanation, speak for the widespreading of a reliable and cost-effective extensive technique.

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