scholarly journals Enhanced functional binning for one- and two-point statistics using a posteriori Uncertainty Quantification of LPT data

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Philipp Godbersen ◽  
Andreas Schröder
Keyword(s):  
Uncertainty Quantification ◽  
Measurement Data ◽  
Synthetic Data ◽  
Lagrangian Particle ◽  
Particle Pairs ◽  
Measured Flow ◽  
Error Estimations ◽  
Uncertainty Information ◽  
Subsonic Jet ◽  
Selection Of

In the evaluation of Lagrangian particle tracking (LPT) measurement data the use of spatially binned flow statistics in the form of one, two or multi-point statistics is often an essential step towards better understanding of the measured flow fields. Increasingly there is a focus towards uncertainty quantification of the measurement system however these evaluations are seldom used to directly improve the statistics by directly involving them into the calculation. We present our Functional Binning approach which makes use of such uncertainty information as a core component for the calculation of improved statistics. The improvements towards prior approaches are shown utilizing synthetic data as well as data from a real-world subsonic jet experiment. Beyond the initial formulation for one-point statistics, we show that this approach is readily extended towards two-point statistics and explore more advanced utilizations of uncertainty information for the optimal selection of particle pairs. Furthermore, the benefits of more individualized particle error estimations are investigated and some strategies for archiving such information are investigated.

Real-time Approximation of Photometric Polygonal Lights

2020 ◽  
Vol 3 (1) ◽  
pp. 1-18
Author(s):  
Christian Luksch ◽  
Lukas Prost ◽  
Michael Wimmer
Keyword(s):  
Real Time ◽  
Specular Reflection ◽  
Near Field ◽  
Measurement Data ◽  
Data Sets ◽  
Photometric Measurement ◽  
Integration Technique ◽  
Time Approximation ◽  
Light Emitter ◽  
Selection Of

We present a real-time rendering technique for photometric polygonal lights. Our method uses a numerical integration technique based on a triangulation to calculate noise-free diffuse shading. We include a dynamic point in the triangulation that provides a continuous near-field illumination resembling the shape of the light emitter and its characteristics. We evaluate the accuracy of our approach with a diverse selection of photometric measurement data sets in a comprehensive benchmark framework. Furthermore, we provide an extension for specular reflection on surfaces with arbitrary roughness that facilitates the use of existing real-time shading techniques. Our technique is easy to integrate into real-time rendering systems and extends the range of possible applications with photometric area lights.

scholarly journals 3D Lagrangian particle tracking of a subsonic jet using multi-pulse Shake-The-Box

2021 ◽  
Vol 123 ◽  
pp. 110346
Author(s):  
Peter Manovski ◽  
Matteo Novara ◽  
Nagendra Karthik Depuru Mohan ◽  
Reinhard Geisler ◽  
Daniel Schanz ◽  
...  
Keyword(s):  
Particle Tracking ◽  
Lagrangian Particle Tracking ◽  
Lagrangian Particle ◽  
Subsonic Jet

Adaptation Application to Engine Modelling

2007 ◽  
Author(s):  
Jude Iyinbor
Keyword(s):  
Measurement Data ◽  
Engine Performance ◽  
Performance Model ◽  
Operating Conditions ◽  
Adaptation Process ◽  
Design Point ◽  
Component Map ◽  
Important Measurement ◽  
Unknown Component ◽  
Selection Of

The optimisation of engine performance by predictive means can help save cost and reduce environmental pollution. This can be achieved by developing a performance model which depicts the operating conditions of a given engine. Such models can also be used for diagnostic and prognostic purposes. Creating such models requires a method that can cope with the lack of component parameters and some important measurement data. This kind of method is said to be adaptive since it predicts unknown component parameters that match available target measurement data. In this paper an industrial aeroderivative gas turbine has been modelled at design and off-design points using an adaptation approach. At design point, a sensitivity analysis has been used to evaluate the relationships between the available target performance parameters and the unknown component parameters. This ensured the proper selection of parameters for the adaptation process which led to a minimisation of the adaptation error and a comprehensive prediction of the unknown component and available target parameters. At off-design point, the adaptation process predicted component map scaling factors necessary to match available off-design point performance data.

Calibration and Uncertainty Quantification of Gas Turbine Performance Models

2015 ◽  
Author(s):  
Manuel Arias Chao ◽  
Darrel S. Lilley ◽  
Peter Mathé ◽  
Volker Schloßhauer
Keyword(s):  
Uncertainty Quantification ◽  
Gas Turbine ◽  
Bayesian Approach ◽  
Least Squares Method ◽  
Measurement Data ◽  
Operating Conditions ◽  
Performance Models ◽  
Regression Problem ◽  
Calibration Problem ◽  
Calibration Parameters

Calibration and uncertainty quantification for gas turbine (GT) performance models is a key activity for GT manufacturers. The adjustment between the numerical model and measured GT data is obtained with a calibration technique. Since both, the calibration parameters and the measurement data are uncertain the calibration process is intrinsically stochastic. Traditional approaches for calibration of a numerical GT model are deterministic. Therefore, quantification of the remaining uncertainty of the calibrated GT model is not clearly derived. However, there is the business need to provide the probability of the GT performance predictions at tested or untested conditions. Furthermore, a GT performance prediction might be required for a new GT model when no test data for this model are available yet. In this case, quantification of the uncertainty of the baseline GT, upon which the new development is based on, and propagation of the design uncertainty for the new GT is required for risk assessment and decision making reasons. By using as a benchmark a GT model, the calibration problem is discussed and several possible model calibration methodologies are presented. Uncertainty quantification based on both a conventional least squares method and a Bayesian approach will be presented and discussed. For the general nonlinear model a fully Bayesian approach is conducted, and the posterior of the calibration problem is computed based on a Markov Chain Monte Carlo simulation using a Metropolis-Hastings sampling scheme. When considering the calibration parameters dependent on operating conditions, a novel formulation of the GT calibration problem is presented in terms of a Gaussian process regression problem.

scholarly journals A multi-site cutting device implements efficiently the divide-and-conquer strategy in tumor sampling

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1587 ◽  
Author(s):  
Jose I. Lopez ◽  
Jesus M. Cortes
Keyword(s):  
Synthetic Data ◽  
Daily Practice ◽  
Divide And Conquer ◽  
Intratumor Heterogeneity ◽  
Pathology Laboratory ◽  
Simple Method ◽  
French Fry ◽  
Histological Processing ◽  
Tumor Sampling ◽  
Selection Of

We recently showed that in order to detect intra-tumor heterogeneity a Divide-and-Conquer (DAC) strategy of tumor sampling outperforms current routine protocols. This paper is a continuation of this work, but here we focus on DAC implementation in the Pathology Laboratory. In particular, we describe a new simple method that makes use of a cutting grid device and is applied to clear cell renal cell carcinomas for DAC implementation. This method assures a thorough sampling of large surgical specimens, facilitates the demonstration of intratumor heterogeneity, and saves time to pathologists in the daily practice. The method involves the following steps: 1. Thin slicing of the tumor (by hand or machine), 2. Application of a cutting grid to the slices (e.g., a French fry cutter), resulting in multiple tissue cubes with fixed position within the slice, 3. Selection of tissue cubes for analysis, and finally, 4. Inclusion of selected cubes into a cassette for histological processing (with about eight tissue fragments within each cassette). Thus, using our approach in a 10 cm in-diameter-tumor we generate 80 tumor tissue fragments placed in 10 cassettes and, notably, in a tenth of time. Eighty samples obtained across all the regions of the tumor will assure a much higher performance in detecting intratumor heterogeneity, as proved recently with synthetic data.

Uncertainty Quantification of Channelized Reservoir Using Ensemble Smoother with Selective Measurement Data

2014 ◽  
Vol 32 (5) ◽  
pp. 805-816 ◽  
Author(s):  
Kyungbook Lee ◽  
SeungPil Jung ◽  
Hyundon Shin ◽  
Jonggeun Choe
Keyword(s):  
Uncertainty Quantification ◽  
Measurement Data ◽  
Ensemble Smoother

Tuning Criterion of Variable Piezoelectric Circuitry for Frequency-Shift-Based Damage Identification Enhancement

Aerospace ◽  
2006 ◽  
Author(s):  
L. J. Jiang ◽  
J. Tang ◽  
K. W. Wang
Keyword(s):  
Frequency Shift ◽  
Piezoelectric Transducer ◽  
Structural Damage ◽  
Damage Identification ◽  
Measurement Data ◽  
Frequency Measurement ◽  
Damage Effect ◽  
Plate Structures ◽  
Curve Veering ◽  
Selection Of

A new concept of using piezoelectric transducer circuitry with tunable inductance to enhance the performance of frequency-shift-based damage identification method has been recently proposed. While previous work has shown that the frequency-shift information used for damage identification can be significantly enriched by tuning the inductance in the piezoelectric circuitry, a fundamental issue of this approach, namely, how to tune the inductance to best enhance the damage identification performance, has not been addressed. Therefore, this research aims at advancing the state-of-the-art of such a technology by proposing guidelines to form favorable inductance tuning such that the enriched frequency measurement data can effectively capture the damage effect. Our analysis shows that when the inductance is tuned to accomplish eigenvalue curve veering, the change of system eigenvalues induced by structural damage will vary significantly with respect to the change of inductance. Under such curve veering, one may obtain a series of frequency-shift data with different sensitivity relations to the damage, and thus the damage characteristics can be captured more effectively and completely. When multiple tunable piezoelectric transducer circuitries are integrated with the mechanical structure, multiple eigenvalue curve veering can be simultaneously accomplished between desired pairs of system eigenvalues. An optimization scheme aiming at achieving desired set of eigenvalue curve veering is formulated to find the critical inductance values that can be used to form the favorable inductance tuning for multiple piezoelectric circuitries. In the numerical analyses of damage identification, an iterative second-order perturbation-based algorithm is used to identify damages in beam and plate structures. Numerical results show that the performance of damage identification is significantly affected by the selection of inductance tuning, and only when the favorable inductance tuning is used, the locations and severities of structural damages can be accurately identified.

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