A Path Toward the Aerodynamic Robust Design of Low Pressure Turbines

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
Francesco Bertini ◽  
Martina Credi ◽  
Michele Marconcini ◽  
Matteo Giovannini
Keyword(s):  
A Priori ◽  
Low Pressure ◽  
Major Effect ◽  
Service Research ◽  
Quality Level ◽  
Operating Cycle ◽  
Manufacturing Defects ◽  
Reported Study ◽  
Configuration Module ◽  
Module Performance

Airline companies are continuously demanding lower-fuel-consuming engines and this leads to investigating innovative configurations and to further improving single module performance. In this framework the low pressure turbine (LPT) is known to be a key component since it has a major effect on specific fuel consumption (SFC). Modern aerodynamic design of LPTs for civil aircraft engines has reached high levels of quality, but new engine data, after first engine tests, often cannot achieve the expected performance. Further work on the modules is usually required, with additional costs and time spent to reach the quality level needed to enter into service. The reported study is aimed at understanding some of the causes for this deficit and how to solve some of the highlighted problems. In a real engine, the LPT module works under conditions which differ from those described in the analyzed numerical model: the definition of the geometry cannot be so accurate, a priori unknown values for boundary conditions data are often assumed, complex physical phenomena are seldom taken into account, and operating cycle may differ from the design intent due to a nonoptimal coupling with other engine components. Moreover, variations are present among different engines of the same family, manufacturing defects increase the uncertainty and, finally, deterioration of the components occurs during service. Research projects and several studies carried out by the authors lead to the conclusion that being able to design a module whose performance is less sensitive to variations (robust LPT) brings advantages not only when the engine performs under strong off-design conditions but also, due to the abovementioned unknowns, near the design point as well. Concept and preliminary design phases are herein considered, highlighting the results arising from sensibility studies and their impact on the final designed robust configuration. Module performance is afterward estimated using a statistical approach.

A Path Towards the Aerodynamic Robust Design of Low Pressure Turbines

2012 ◽  
Author(s):  
Francesco Bertini ◽  
Martina Credi ◽  
Michele Marconcini ◽  
Matteo Giovannini
Keyword(s):  
A Priori ◽  
Low Pressure ◽  
Major Effect ◽  
Quality Level ◽  
Operating Cycle ◽  
Manufacturing Defects ◽  
Reported Study ◽  
Definition Of ◽  
Configuration Module ◽  
Module Performance

Airline companies are continuously demanding lower-fuel-consuming engines and this leads to investigating innovative configurations and to further improving single module performance. In this framework the Low Pressure Turbine (LPT) is known to be a key component since it has a major effect on specific fuel consumption (SFC). Modern aerodynamic design of LPTs for civil aircraft engines has reached high levels of quality, but new engine data, after first engine tests, often cannot achieve the expected performance. Further work on the modules is usually required, with additional costs and time spent to reach the quality level needed to enter in service. The reported study is aimed at understanding some of the causes for this deficit and how to solve some of the highlighted problems. In a real engine, the LPT module works under conditions which differ from those described in the analyzed numerical model: the definition of the geometry cannot be so accurate, a priori unknown values for boundary conditions data are often assumed, complex physical phenomena are seldom taken into account, operating cycle may differ from the design intent due to a non-optimal coupling with other engine components. Moreover, variations are present among different engines of the same family, manufacturing defects increase the uncertainty and, finally, deterioration of the components occurs during service. Research projects and several studies carried out by the authors lead to the conclusion that being able to design a module whose performance is less sensitive to variations (Robust LPT) brings advantages not only when the engine performs under strong off-design conditions but also, due to the abovementioned unknowns, near the design point as well. Concept and Preliminary Design phases are herein considered, highlighting the results arising from sensibility studies and their impact on the final designed robust configuration. Module performance is afterward estimated using a statistical approach.

scholarly journals Development and Use of Machine-Learnt Algebraic Reynolds Stress Models for Enhanced Prediction of Wake Mixing in Low-Pressure Turbines

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
H. D. Akolekar ◽  
J. Weatheritt ◽  
N. Hutchins ◽  
R. D. Sandberg ◽  
G. Laskowski ◽  
...  
Keyword(s):  
Reynolds Stress ◽  
Gene Expression Programming ◽  
A Priori ◽  
Low Pressure ◽  
Navier Stokes ◽  
Flow Features ◽  
Turbulence Closures ◽  
Rans Models ◽  
Development Analysis ◽  
Stress Models

Nonlinear turbulence closures were developed that improve the prediction accuracy of wake mixing in low-pressure turbine (LPT) flows. First, Reynolds-averaged Navier–Stokes (RANS) calculations using five linear turbulence closures were performed for the T106A LPT profile at isentropic exit Reynolds numbers 60,000 and 100,000. None of these RANS models were able to accurately reproduce wake loss profiles, a crucial parameter in LPT design, from direct numerical simulation (DNS) reference data. However, the recently proposed kv2¯ω transition model was found to produce the best agreement with DNS data in terms of blade loading and boundary layer behavior and thus was selected as baseline model for turbulence closure development. Analysis of the DNS data revealed that the linear stress–strain coupling constitutes one of the main model form errors. Hence, a gene-expression programming (GEP) based machine-learning technique was applied to the high-fidelity DNS data to train nonlinear explicit algebraic Reynolds stress models (EARSM), using different training regions. The trained models were first assessed in an a priori sense (without running any RANS calculations) and showed much improved alignment of the trained models in the region of training. Additional RANS calculations were then performed using the trained models. Importantly, to assess their robustness, the trained models were tested both on the cases they were trained for and on testing, i.e., previously not seen, cases with different flow features. The developed models improved prediction of the Reynolds stress, turbulent kinetic energy (TKE) production, wake-loss profiles, and wake maturity, across all cases.

scholarly journals Governança corporativa e sensibilidade investimento-fluxo de caixa no Brasil

2019 ◽  
Vol 17 (2) ◽  
pp. 72
Author(s):  
Breno Augusto de Oliveira Silva ◽  
Daniel Ferreira Caixe ◽  
Elizabeth Krauter
Keyword(s):  
Corporate Governance ◽  
Cash Flow ◽  
A Priori ◽  
Investment Model ◽  
Quality Level ◽  
Financial Constraint ◽  
Publicly Traded Companies ◽  
Flow Sensitivity ◽  
Governance Practices ◽  
Cash Flow Sensitivity

This study aimed to investigate the investment-cash flow sensitivity for Brazilian companies with different degrees of financial constraint according to the quality level of their corporate governance practices. An investment model was estimated through GMM for a panel data of 248 Brazilian publicly traded companies, which were a priori classified in two groups of financial constraint degrees (high and low) according to the Corporate Governance Practices Index (IPGC). The results showed that the quality of corporate governance influences the investment-cash flow sensitivity, and this sensitivity is negative and significant only for firms with poor governance, classified with high financial constraint. Furthermore, it can be concluded that IPGC proved to be an interesting variable for a priori classification of companies and an important determinant of the investment-cash flow sensitivity to identify potentially financially constrained firms.

Investigation of the Accuracy of RANS Models to Predict the Flow Through a Low-Pressure Turbine

2016 ◽  
Vol 138 (12) ◽  
Author(s):  
R. Pichler ◽  
R. D. Sandberg ◽  
V. Michelassi ◽  
R. Bhaskaran
Keyword(s):  
Linear Models ◽  
Turbulence Modeling ◽  
A Priori ◽  
Flow Characteristics ◽  
Turbulence Models ◽  
Low Pressure ◽  
Transport Equations ◽  
Compressible Turbulence ◽  
Low Pressure Turbine ◽  
Rans Models

In the present paper, direct numerical simulation (DNS) data of a low-pressure turbine (LPT) are investigated in light of turbulence modeling. Many compressible turbulence models use Favre-averaged transport equations of the conservative variables and turbulent kinetic energy (TKE) along with other modeling equations. First, a general discussion on the turbulence modeling error propagation prescribed by transport equations is presented, leading to the terms that are considered to be of interest for turbulence model improvement. In order to give turbulence modelers means of validating their models, the terms appearing in the Favre-averaged momentum equations are presented along pitchwise profiles at three axial positions. These three positions have been chosen such that they represent regions with different flow characteristics. General trends indicate that terms related with thermodynamic fluctuations and Favre fluctuations are small and can be neglected for most of the flow field. The largest errors arise close to the trailing edge (TE) region where vortex shedding occurs. Finally, linear models and the scope for their improvement are discussed in terms of a priori testing. Using locally optimized turbulence viscosities, the improvement potential of widely used models is shown. On the other hand, this study also highlights the danger of pure local optimization.

scholarly journals Exercise Intensity May Not Moderate the Acute Effects of Functional Circuit Training on Cognitive Function: A Randomized Crossover Trial

2020 ◽  
Vol 10 (10) ◽  
pp. 738 ◽  
Author(s):  
Jan Wilke ◽  
Caroline Royé
Keyword(s):  
Exercise Intensity ◽  
High Intensity ◽  
Digit Span ◽  
A Priori ◽  
Sample Size Calculation ◽  
Major Effect ◽  
Circuit Training ◽  
Effort Level ◽  
Parametric Data ◽  
Trail Making

Functional circuit training (FCT) has been demonstrated to acutely enhance cognitive performance (CP). However, the moderators of this observation are unknown. This study aimed to elucidate the role of exercise intensity. According to an a priori sample size calculation, n = 24 healthy participants (26 ± 3 years, 13 females), in randomized order, performed a single 15-min bout of FCT with low (20–39% of the heart rate reserve/HRR), moderate (40–59% HRR) or high intensity (maximal effort). Immediately pre- and post-workout, CP was measured by use of the Digit Span test, Stroop test and Trail Making test. Non-parametric data analyses did not reveal significant differences between conditions (p > 0.05) although parameter-free 95% confidence intervals showed pre-post improvements in some outcomes at moderate and high intensity only. The effort level does not seem to be a major effect modifier regarding short-term increases in CP following HCT in young active adults.

Self-consistency between input and output data for models describing elastic properties of fractured media: does conventional models satisfy this criterion?

2020 ◽  
Author(s):  
Andrey V. Radostin ◽  
Vladimir Yu. Zaitsev
Keyword(s):  
Elastic Properties ◽  
Elastic Moduli ◽  
A Priori ◽  
Applied Pressure ◽  
Measurement Data ◽  
Structural Features ◽  
Crack Model ◽  
Reported Study ◽  
Conventional Models ◽  
Self Consistency

<p>Models that adequately describe the effect of crack-like defects on the elastic moduli of solids are one of the key "ingredients" needed to obtain diagnostic conclusions about the structural features of the material. The change in the velocities of longitudinal and shear elastic waves depending on the pressure is one of the most popular methods of measuring the connection of these moduli with the cracks present in the material. For commonly considered models with an isotropic crack orientation (which makes the medium on average isotropic), the measurement of these two velocities is sufficient to determine two independent moduli (for example, the shear and bulk moduli) through which other characteristics of interest can be expressed. In this case, the applied pressure, gradually closing the cracks, is a control parameter that regulates the concentration of cracks.</p><p>It is quite natural when constructing models to obtain expressions relating the elastic moduli with the crack concentration (the latter cannot be to directly monitored when the applied pressure is varied). In this regard, some additional considerations are used about the relationship of crack concentration to pressure, which allows one to relate the model expressions with the moduli measured during the pressure variation. Assuming some approximations relating the pressure and concentration with free fitting parameters in the model, it is possible to achieve the best agreement of model with the experimental dependences on pressure. This approach looks natural and is conventionally used, resulting in apparently satisfactory agreement between the model predictions and the measurement data.</p><p>Here we show that this apparent agreement is often achieved at the expense of strong violation of self-consistency between the input data fed into the model and the output of the model. This violation is far from obvious in conventional approaches based on the use of an auxiliary (and not directly measurable) relationship between concentration and pressure. To find out the fact of either violation or fulfillment of the condition of self-consistency, here we describe such a form of the model, in which its input parameters can be expressed in terms of experimentally measured values (in contrast to the crack concentration that cannot be monitored as a function of pressure). In the proposed description of the fractured material, the cracks are characterized by the shear- and normal compliances, the ratio of which is not a priori fixed and can be extracted from the experimental data.The proposed procedure of interpretation of experimental pressure dependences allows one to explicitly verify the model self-consistency and assess the elastic properties of real cracks that is many cases appear to be strongly different from the properties intrinsic to the standard penny-shape-crack model.</p><p>The reported study was supported by RFBR, project number 19-05-00536.</p>

On Deposition and Build-Up Detachment in Compressor Fouling

2018 ◽  
Author(s):  
Nicola Casari ◽  
Michele Pinelli ◽  
Alessio Suman
Keyword(s):  
Gas Turbines ◽  
Particle Deposition ◽  
A Priori ◽  
A Priori Estimate ◽  
Major Effect ◽  
Surface Shape ◽  
Adhesion Forces ◽  
Severe Problem ◽  
Two Bodies ◽  
Uncontrolled Variation

Compressor fouling is a severe problem for both heavy-duty and aero-propulsion gas turbines. Particles can impinge on the blade and annulus surfaces, sticking there. The consequences of particle deposition are the increase of the roughness and an uncontrolled variation in the surface shape. These problems have a major effect on the performance of the compressor over time. Variations in the flow field can make the flow quantities close to the deposit to change, and it may happen that the conditions for the sticking do not hold any longer. If this is the case, the build-up detachment may happen. This occurrence can mitigate the fouling effects and may be exploited for keeping the performance of the compressor as high as possible over the operating period. In this work, an innovative model is proposed in order to evaluate the adhesion forces and the possible detachment. Particularly, the same forces that keep a gecko stuck to a surface are considered: the van der Waals forces (due to the proximity of the two bodies) and the Laplace force (due to the curvature of the liquid film related to the humidity). The so formulated model, named gecko-like for such a reason, is used for the numerical analyses of a deposition problem. Both the sticking and possible build-up detachment are considered. The outcome of this work can be regarded as an a-priori estimate of the forces to be kept into account when dealing with compressor fouling problems.

scholarly journals Potential causal factors of CFS/ME: a concise and systematic scoping review of factors researched

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Ashley Elizabeth Muller ◽  
Kari Tveito ◽  
Inger Johanne Bakken ◽  
Signe A. Flottorp ◽  
Siri Mjaaland ◽  
...  
Keyword(s):  
Scoping Review ◽  
A Priori ◽  
Chronic Fatigue ◽  
Case Control Studies ◽  
Causal Factors ◽  
Fatigue Syndrome ◽  
Comparison Groups ◽  
Reported Study ◽  
Patient Advocacy Group ◽  
Study Designs

Abstract Background Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) is understood as a complex condition, likely triggered and sustained by an interplay of biological, psychological, and social factors. Little oversight exists of the field of causal research. This systematic scoping review explores potential causal factors of CFS/ME as researched by primary studies. Methods We searched eight databases for primary studies that examined potential causal factors of CFS/ME. Based on title/abstract review, two researchers independently sorted each study’s factors into nine main categories and 71 subordinate categories, using a system developed with input given during a 2018 ME conference, specialists and representatives from a ME patient advocacy group, and using BMJ Best Practice’s description of CFS/ME etiology. We also extracted data related to study design, size, diagnostic criteria and comparison groups. Results We included 1161 primary studies published between January 1979 and June 2019. Based on title/abstract analysis, no single causal factor dominated in these studies, and studies reported a mean of 2.73 factors. The four most common factors were: immunological (297 studies), psychological (243), infections (198), and neuroendocrinal (198). The most frequent study designs were case–control studies (894 studies) comparing CFS/ME patients with healthy participants. More than half of the studies (that reported study size in the title/abstract) included 100 or fewer participants. Conclusion The field of causal hypotheses of CFS/ME is diverse, and we found that the studies examined all the main categories of possible factors that we had defined a priori. Most studies were not designed to adequately explore causality, rather to establish hypotheses. We need larger studies with stronger study designs to gain better knowledge of causal factors of CFS/ME.

scholarly journals Improvement in the Quantification of Foreign Object Defects in Carbon Fiber Laminates Using Immersion Pulse-Echo Ultrasound

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2919
Author(s):  
Nathaniel J. Blackman ◽  
David A. Jack ◽  
Benjamin M. Blandford
Keyword(s):  
High Resolution ◽  
Carbon Fiber ◽  
A Priori ◽  
Detection Methods ◽  
Absolute Difference ◽  
Average Error ◽  
Foreign Object ◽  
Manufacturing Defects ◽  
Foreign Objects ◽  
Pulse Echo

This research presents a new technique using pulse echo ultrasound for sizing foreign objects within carbon fiber laminates. Carbon fiber laminates are becoming increasingly popular in a wide variety of industries for their desirable properties. It is not uncommon for manufacturing defects to occur within a carbon fiber laminates, causing waste, either in the discarding of failed parts or the overdesign of the initial part to account for these anticipated and undetected errors. One such manufacturing defect is the occurrence of a foreign object within the laminate. This defect will lead to a localized weakness within the laminate including, but not limited to, stress risers, delamination, and catastrophic failure. This paper presents a method to analyze high-resolution c-scan full waveform captured data to automatically capture the geometry of the foreign object with minimal user inputs without a-priori knowledge of the shape of the defect. This paper analyzes twelve samples, each a twelve-lamina carbon fiber laminate. Foreign objects are made from polytetrafluoroethylene (PTFE) measuring 0.05 mm (0.002 in.) thick and ranging in diameter from 12.7 mm (0.5 in) to 1.588 mm (0.0625 in), are placed within the laminates during fabrication at varying depths. The samples are analyzed with a custom high-resolution c-scan system and smoothing, and edge detection methods are applied to the collected c-scan data. Results are presented on the sizing of the foreign objects with an average error of 6% of the true area, and an average absolute difference in the estimation of the diameter of 0.1 mm (0.004 in), an improvement over recently presented ultrasonic methods by a factor of three.

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