Multi-hole Pressure Probes Research Articles

Streamlining multi-hole probe calibration using artificial neural networks

Accurately measuring the three-dimensional flow field characteristics in complex flow fields, particularly in turbomachines, is of utmost importance and is commonly achieved through experimental methods. Multi-hole pressure probes are a proven measuring technique to provide precise readings of flow characteristics in both two-dimensional (2D) and three-dimensional (3D) flow fields. However, manufacturing imperfections have an impact on their measuring accuracy so each probe has a slightly different measuring behavior. In order to take these specific characteristics into account a thorough calibration process prior to utilization has to be applied. This calibration process involves positioning the probe in various flow conditions in a wind tunnel and collecting all relevant data. A model is then established to correlate the measured pressure distribution across the probe holes with known flow conditions. Unfortunately, this calibration process is time-consuming and requires costly equipment.To address these challenges, this study introduces a novel calibration technique that leverages advanced machine learning methods, specifically artificial neural networks (ANNs), to significantly streamline the process. ANNs are renowned for their ability to model diverse systems and adapt and generalize well, making them a promising solution for simplifying the calibration of multi-hole probes. In this research, an ANN calibration model was developed specifically for a 5-hole probe, and its configuration was optimized through an automated hyperparameter optimization process. The performance of the ANN model was then compared to that of a conventional polynomial model. After confirming its accuracy, the ANN model was successfully re-adapted and applied to new probes, requiring minimal calibration data collection. The results highlight the potential of ANNs in probe calibration, as they enable a simplified process that demands fewer calibration data points.

Calibration of Multi Hole Pressure Probes for Three Dimensional Flow Measurements in Subsonic Flow*

The calibration of two multi hole pressure probes with four and five pressure holes are presented at three Mach numbers, viz. M=0.3, 0.4 and 0.5. The calibration was carried out in a subsonic calibration tunnel in yaw angle and pitch angle range of ± 30° at 5° interval. Calibration curves are presented and compared at the three Mach numbers. Calibration data at one Mach number are used as calibration data and calibration data at other Mach numbers are used as measured data to find the flow parameters namely, total pressure and static pressure and flow yaw angle and pitch angle using a lookup table method at these Mach numbers. The interpolation errors are small when the yaw angle and pitch angle range is from -20° to 20° for the four hole probe and from -15° to 15° for the five hole probe. Mach number effects on the flow measurements can be incorporated using the iterative method presented. This method is used to obtain flow parameters in the wake of a steam turbine rotor tip cascade blade. The differences in the obtained values using calibration coefficients at three Mach numbers are found to be negligible.

Evaluations on supervised learning methods in the calibration of seven-hole pressure probes.

Machine learning method has become a popular, convenient and efficient computing tool applied to many industries at present. Multi-hole pressure probe is an important technique widely used in flow vector measurement. It is a new attempt to integrate machine learning method into multi-hole probe measurement. In this work, six typical supervised learning methods in scikit-learn library are selected for parameter adjustment at first. Based on the optimal parameters, a comprehensive evaluation is conducted from four aspects: prediction accuracy, prediction efficiency, feature sensitivity and robustness on the failure of some hole port. As results, random forests and K-nearest neighbors' algorithms have the better comprehensive prediction performance. Compared with the in-house traditional algorithm, the machine learning algorithms have the great advantages in the computational efficiency and the convenience of writing code. Multi-layer perceptron and support vector machines are the most time-consuming algorithms among the six algorithms. The prediction accuracy of all the algorithms is very sensitive to the features. Using the features based on the physical knowledge can obtain a high accuracy predicted results. Finally, KNN algorithm is successfully applied to field measurements on the angle of attack of a wind turbine blades. These findings provided a new reference for the application of machine learning method in multi-hole probe calibration and measurement.

Inversion method for measuring multi-hole probe surface pressure distribution of supersonic compressible atmospheric flow field

The conventional method of measuring a multi-hole probe is based on Bernoulli’s equation and suffers from certain model errors. A computational fluid dynamics-based method was used in this study to reduce the theoretical error and establish a parametric model of the surface pressure of a spherical multi-hole pressure probe for measuring compressible flow fields at supersonic velocities. A flow field inversion method based on the parametric model is proposed herein. Numerical simulations were conducted to validate the proposed method. The experiment results show that in the compressible atmospheric flow field within Mach 1.2–1.7, the measurement errors of the inversion method were 1.3% and 2.35% for velocity and angle, respectively, thus verifying the feasibility of the method. Thus, a new method of measuring multi-hole pressure probe atmospheric flow fields was demonstrated.

Experimental investigation of geometry effects and performance of five-hole probe in measuring jets in crossflow

Vortical and shear flows are common in turbomachinery. Multi-hole pressure probes are used in turbomachinery flows in order to provide robust and accurate measurements of both pressure and velocity components. In this study, two different miniature five-hole probes are designed and fabricated, both with a cobra shape. The probe tip was 1.45 mm and it was maintained in that size for the length of the cobra shape formation, providing very close proximity to the solid boundaries and reduced flow blockage. The difference among the probes corresponded to the head geometry, as the one probe was formed with a pyramid tip shape, while the other was maintained with a flat shape. The calibration process was carried out in an open-circuit suction wind tunnel for the range of ±32⁰ in yaw and pitch direction. The results showed that the pyramid probe exhibits a high flow angle spatial sensitivity and a reliable measurement range of ±28⁰ in yaw and pitch direction. The flat probe provided unexpected well angle sensitivity and reliable measurements data despite the fact that it is of a very simple form. The pyramid probe showed superior performance. In particular, the pyramid probe offers 12.5% wider operating range. In order to prove the effectiveness of the pyramid probe, measurements were obtained in a jet in cross flow. In order to evaluate the performance of the probe, further, a surface fit model was employed to produce ideal calibration coefficients. These were used to redefine the magnitude of the velocities in the measured flow domain. The accuracy in measurements was assessed, comparing the velocities produced by the two variants of pressure coefficients. The results indicate that the pyramid probe operates reliably in a very large range of constantly changing velocity vector, which occurs in jet in cross flow.

Five hole probe errors caused by fluctuating incidence

Steady multi-hole pressure probes are used extensively in turbomachinery research. While various sources of error are known, this paper demonstrates that fluctuations in probe incidence can be particularly damaging for accuracy. A simple, quasi-steady model of five-hole-probe response explains why angle fluctuations can cause large errors in the indicated total and static pressure. The model explains why measurements in a shedding wake over-estimated loss by 40%. Simulated traverses behind rotors show similar behavior: fluctuating incidence causes efficiency to be under-estimated by over 1% in some cases. The model can correct five-hole-probe errors using an estimate of unsteady flow angles. This approach reduces errors by an order of magnitude and can be used to post-correct existing test data.

Effect of an Axially Tilted Variable Stator Vane Platform on Penny Cavity and Main Flow

Abstract This paper presents the impact of an axially tilted variable stator vane (VSV) platform on penny cavity flow and passage flow, with the aid of both optical and pneumatic measurements in an annular cascade wind tunnel as well as steady computational fluid dynamics (CFD) analyses. Variable stator vanes in axial compressors require a clearance from the endwalls. This means that penny cavities around the vane platform are inevitable. Production and assembly deviations can result in a vane platform which is tilted about the circumferential axis. Penny cavity and main flow in geometries with and without platform tilting were compared in an annular cascade wind tunnel. Detailed particle image velocimetry (PIV) measurements were conducted inside the penny cavity and in the vane passage. Steady pressure and velocity data was obtained by two-dimensional multi-hole pressure probe traverses in the inflow and the outflow. Furthermore, pneumatic measurements were carried out using pressure taps inside the penny cavity. Additionally, oil flow visualization was conducted on the airfoil, hub, and penny cavity surfaces. Steady CFD simulations have been benchmarked against experimental data. The results show that tilting the vane platform reduces the penny cavity leakage mass flow. By decreasing penny cavity leakage, platform tilting also affects the passage flow where it leads to a reduced turbulence level and total pressure loss in the leakage flow region. In summary, the paper demonstrates the influence of penny platform tilting on cavity flow and passage flow and provides new insights into the mechanisms of penny cavity-associated losses.

High-temperature Calibration Facility for Calibrating Multihole Pressure Probes

High-temperature Calibration Facility for Calibrating Multihole Pressure Probes

Neural-Network-Based Sensor Data Fusion for Multi-Hole Fluid Velocity Probes

For measuring three components of velocity in unknown flow fields, multi-hole pressure probes possess a significant advantage. Unlike methods such as hot-wire anemometry, laser-Doppler velocimetry and particle-image velocimetry, multi-hole pressure probes can provide not only the three components of local velocity, but also static and stagnation pressures. However, multi-hole probes do require exhaustive calibration. The traditional technique for calibrating these probes is based on either look-up tables or polynomial curve fitting, but with the low cost and easy availability of powerful computing resources, neural networks are increasingly being used. Here, we explore the possibility to further reduce measurement uncertainty by implementing neural-network-based methods that have not been previously used for probe calibration, including supervised and unsupervised learning neural networks, regression models and elastic-map methods. We demonstrate that calibrating probes in this way can reduce the uncertainty in flow angularity by as much as 50% compared to conventional techniques.

A novel approach based on artificial neural network for calibration of multi-hole pressure probes

Imperfections in the manufacturing process of flow measuring probes affect their measuring behavior. Nevertheless, in order to provide the highest possible accuracy, each individual multi-hole pressure probe has to be calibrated before using them in turbomachinery. This paper presents a novel method based on artificial neural networks (ANN) to predict the flow parameters of multi-hole pressure probes. A two-stage ANN approach using multilayer perceptron (MLP) is proposed in this study. The two-stage prediction approach involves two MLP networks, which represent the calibration data and the prediction error. For a given set of inputs, outputs from both networks are combined to estimate the measured value. The calibration data of a 5-hole probe at RWTH Aachen was used to develop and validate the proposed ANN models and two-stage prediction approach. The results showed that the ANN can predict the flow parameters with high accuracy. Using the two-stage approach, the prediction accuracy was further improved compared to polynomial functions, i.e. a commonly used method in probe calibration. Furthermore, the proposed approach offers high interpolation capabilities while preventing overfitting (i.e. failure to fit new data). Unlike polynomials, it is shown that the ANN based method can provide accurate predictions at intermediate points without large oscillations.

Development of unsteady multi-hole pressure probes based on fiber-optic pressure sensors

For measurements of unsteady flow phenomena with multi-hole pressure probes, pressure transducers are integrated in the probe near the probe tip. The application of additive manufacturing enables a wide variation in probe geometries for complex use cases. The spatial characteristics of the unsteady probe are determined by the steady state calibration in a known free-jet wind tunnel. Furthermore, the acoustic/pneumatic line-cavity system, that emerges inside the channels of the probe, is investigated in detail in the temporal calibration. In order to realize multi-hole probes with higher temporal resolution, which can be operated in harsh environments, a fiber-optic pressure sensor is developed. The measurement principle of the fiber-optic sensor is based on the Fabry-Pérot interferometer effect. The sensor is operated differentially with a pressure capillary by either pressurizing the sensor or using the surrounding static pressure as the reference pressure. Besides calibration of the sensor, comparisons with a state-of-the-art piezo-resistive pressure transducer have been performed. The focus of this work is on the reproducibility of both frequency response and amplitude.

A robust calibration method for seven-hole pressure probes

Multi-hole pressure probe remains an incomparably efficient method of flow measurement due to its simplicity and convenience. An appropriate calibration method is necessary to establish the relations between flow parameters and pressure data. In this paper, a robust calibration method for seven-hole pressure probes is presented, which can also be applied when a hole port is malfunctioning. First, a seven-hole probe was designed and manufactured by 3D printing techniques, and calibration measurements were conducted with a two-degree of freedom calibration apparatus in wind tunnel. Second, theoretical expressions for static pressure coefficients of seven-hole probes were deduced, which guides the establishment of new pressure normalization method in the absence of static and total pressure. Thereafter, a calibration algorithm using the new pressure normalization method was proposed. Finally, effects of sample selection criteria, sample size, and atmospheric static pressure offset on the calibration accuracy of the new algorithm were evaluated. And the case that one port is invalid was studied. Based on the findings obtained from this study, the feasibility and robustness of the new calibration method were validated, and the method can also be easily applied to other multi-hole (including but not limited to seven-hole) pressure probes.

Multirotor UAV-Based Platform for the Measurement of Atmospheric Turbulence: Validation and Signature Detection of Tip Vortices of Wind Turbine Blades

AbstractThe present study describes the development of a technique for the measurement of atmospheric turbulence and temperature at a point in space based on the integration of a fast-response multihole pressure probe and a thermocouple with an inertial measurement unit on a multirotor UAV-based platform. This allows for an accurate measurement of time series of the three components of the velocity vector and temperature at any point in space in which the UAV can fly within the limitations of its autonomy. The presented technique relies on an accurate correction of the three-component velocity vector measured by the pressure probe on the frame of reference of the UAV—noninertial—with the information provided by the inertial measurement unit. The study includes a validation of the technique against sonic anemometry and the measurement of the signature of tip vortices shed by the blades of a full-scale wind turbine as an example of its potential.

Optimal Calibration of Directional Velocity Probes

The calibration of directional velocity probes can require significant facility time and resources, especially if carried out in situ. The techniques of the design of experiments are therefore applied in order to formally optimize the selection of calibration points. A model is proposed for a generalized directional velocity probe, and this model is used to generate an approximate, polynomial response surface model that is shown to agree well with measurements from both multisensor hot-wire probes and multihole pressure probes, in a variety of geometries. The process of D optimality is then applied based on this response surface model, and a typical probe is calibrated accordingly. The probe is then used to scan the wake of a vortex generator in order to test the efficacy of the reduced calibrations. D-optimal calibration points are shown to offer a significant improvement in data fidelity over conventional rectangular grids, and minimal additional uncertainty is incurred after a 25-fold reduction in the number of calibration points.

Measuring wind with Small Unmanned Aircraft Systems

Small Unmanned Aircraft Systems (SUAS) are an emerging technology that is suitable for multitude of applications requiring small sensor payloads including airborne wind measurement. This work discusses the considerations and limitations of different SUAS configurations, in particular Multi-rotor UAS (MUAS), and their capabilities when operating within the Atmospheric Boundary Layer (ABL). Several methods for measuring fluctuating flows from SUAS are discussed, and preliminary results from a quadrotor-mounted Multi-Hole Pressure Probe (MHPP) “flying anemometer” platform are presented. Flights at a range of altitudes demonstrated that in-situ measurements of both mean wind velocity and turbulence intensity from hovering airborne platform are feasible. This indicates that MUAS can be used as flexible wind sensing platforms with good high spatial resolution. Suggestions for how future SUAS technological and operation developments may further improve wind engineering applications are also discussed.

Full-scale flow measurement on a tall building with a continuous-wave Doppler Lidar anemometer

While building aerodynamics have been widely studied, most investigations have been conducted in wind tunnels or through computational simulation. Full-scale experiments are least common, as they are usually costly, require significant time and effort and are subject to uncontrolled meteorological conditions. This research examines the feasibility of using a continuous-wave Doppler Lidar, as opposed to traditional experimental instrumentation for flow measurements around full-scale buildings. The normalised mean velocities and the turbulence intensities measured around a full-size, nominally cuboid building in suburban terrain were compared to results from Cobra multi-hole pressure probes mounted on the full-size building and from a 1/100-scale wind-tunnel test. The normalised mean velocities measured in the tests were within 2% of each other; however, the turbulence intensities obtained from the wind-tunnel experiments were 2–6% higher than the nominal value of 14% measured in the full-scale testing. These effects appeared mainly due to the relatively low sampling frequency of the Lidar, combined with the spatial averaging over a relatively large area. It was concluded that Lidar instrumentation shows promise for characterising the flowfield around full-scale buildings, if the scanning cone angle can be reduced and the sampling rate increased.

A new technique for investigating the induced and profile drag coefficients of a smooth wing and a tubercled wing

The induced and profile drag coefficients of a wing are typically determined through a complex experimental technique, such as wake surveying. Such a technique requires measurement of all three orthogonal components of the downstream velocity to find the components of drag, which results in the necessary usage of a sophisticated and costly measurement device, such as multi-hole pressure probe. However, in this paper data is presented which demonstrate that the relative changes in the induced and profile drag coefficients can largely be determined through the sole measurement of the downstream, streamwise velocity. To demonstrate this, the induced and profile drags of two NACA 0021 wings, one with a smooth leading edge and the other wing a tubercled leading edge for comparison, are determined through the measurement of the three orthogonal velocities. The downstream, streamwise velocity distribution of each wing is then constructed and relationships can be determined. The wings were surveyed at 3°, 9°, and 12°. It has been found that the relative magnitude of the profile drag coefficient can be found for all considered angles of attack, while the relative magnitude of the induced drag coefficient can be found at 9° and 12°. These findings produce an innovative, simpler, and more cost effective experimental technique in determining the components of drag of a wing, and reduces the burdensome requirement of a sophisticated measurement device for such an experiment. Further investigation is required to determine the induced drag at 3°.

Development and Flight Testing of a Turbulence Mitigation System for Micro Air Vehicles

There are significant challenges associated with the flight control of fixed-wing micro air vehicles MAVs operating in complex environments. The scale of MAVs makes them particularly sensitive to atmospheric disturbances thus limiting their ability to sustain controlled flight. Bio-inspired, phase-advanced sensors have been identified as promising sensory solutions for complementing current inertial-only attitude sensors. This paper describes the development and flight testing of a bio-inspired, phase-advanced sensor and associated control system that mitigates the impact of turbulence on MAVs. Multihole pressure probes, inspired by the sensory function of bird feathers, are used to measure the flow pitch angle and velocity magnitude ahead of the MAV's wing. The sensors provide information on the disturbing phenomena before it causes an inertial response in the aircraft. The sensor output is input to a simple feed-forward control architecture, which enables the MAV to generate a mitigating response to the turbulence. The results from wind-tunnel and outdoor testing in high levels of turbulence are presented. The disturbance rejection performance of the phase-advanced sensory system is compared against that of a conventional inertial-based control system. The developed sensory system shows significant improvement in terms of disturbance rejection performance compared to that of standard inertial-only control system. It is concluded that a phase-advanced sensory systems can complement conventional inertial-based sensors to improve the attitude-tracking performance of MAVs.

Fabrication and calibration of a sub-miniature 5-hole probe with embedded pressure sensors for use in extremely confined and complex flow areas in turbomachinery research facilities

Multi-hole pressure probes are often employed in experimental facilities to measure the three dimensional flow field due to their ability to simultaneously provide the distributions of the static and total pressures as well as the three components of the velocity vectors. In cases where these probes are employed in turbomachinery research facilities it is essential for them to be accurate, respond to local parameter disturbances quickly and exhibit a high flow angle spatial sensitivity. Thus, the physical dimensions of the probe must be as small as possible. In addition the small size of the probe reduces the flow blockage and the corresponding local disturbances of the flow, especially when it approaches the solid boundaries of the blade channels. The present study refers to the fabrication and calibration of a sub-miniature in dimensions 5-hole probe, for use in complex internal flow areas arising in turbomachinery research. In order to reduce the need for a longer sampling time as the size of the probe gets smaller, the length of the stem that transfers the pressure from the tip of the probe to the sensor has to be minimized. This effect was compensated by embedding the pressure sensors right at the end of the probe׳s stem. This minimizes the air volume and thus the oscillations inside the flexible connecting tubes that usually connect each port of the probe to its corresponding pressure sensor. The fabrication methodology of the probe and data acquisition system is extensively described, as well as the non-nulling method employed for the calibration. Furthermore, application of the probe on a reference configuration geometry often used in turbomachinery research is illustrated in order to validate the effectiveness and novel characteristics of the probe. The result is a construction and calibration technique that allows the relevant laboratories to build on their own such instruments that may cost several thousand dollars (or euros) when bought from the open market.

Methodology for the Design of an Aerodynamic Package for a Formula SAE Vehicle

Recent changes to the rules regarding aerodynamics within Formula SAE, combined with faster circuits at the European FSAE events, have made the implementation of aerodynamic devices, to add down-force, a more relevant topic. As with any race series it is essential that a detailed analysis is completed to establish the costs and benefits of including an aerodynamic package on the vehicle. The aim of the work reported here was to create a methodology that would fully evaluate all aspects of the package and conclude with an estimate of the likely gain in points at a typical FSAE event. The paper limits the analysis to a front and rear wing combination, but the approach taken can be applied to more complex aerodynamic packages. An initial wind tunnel investigation of the potential flow interactions between the driver's helmet and rear wing using a multi-hole pressure probe is reported and the data used in a two-dimensional CFD calculation to provide an accurate prediction of the likely down-force from the wing package. The chosen configurations are tested in a comprehensive wind tunnel program and a map of potential setups generated. The potential aerodynamic configurations are assessed in both quasi-static and dynamic handling analysis to demonstrate the effects of aerodynamic lift, lift distribution, aerodynamic drag, and the effect of additional weight, weight distribution and height of the center of gravity. The paper includes a description of the wind tunnel model and scaling considerations and a description of the handling model and the lap simulation methods. The results shows that a simple front and rear wing combination, providing relative low down-force (1000N at 110kph on a vehicle of 280kg, including driver), gives an improvement in performance equating to a gain of approximately 40 points during the event. The largest improvements are seen during the autocross and endurance events. This gain is considered sufficient to justify the inclusion of the package on the vehicle. Copyright © 2014 SAE International.