Dynamic Pressure Sensors Research Articles

Influence of tip air injection on the unsteady blade force under circumferential pressure distortion

In order to further understand the impact of tip air injection on compressor stability under circumferential pressure distortion, a series of experimental studies on tip air injection under uniform and circumferential distortion were conducted on a low-speed single rotor axial flow compressor. The unsteady measurements were carried out by use of microsensors and strain gauges bonded on the rotor blade surfaces, and a collection of dynamic pressure sensors installed on the casing wall. Results indicate that with the increase in the injected momentum ratio, the load at the leading edge near the rotor blade tip obviously decreases, thereby delaying the stall. By comparing the pressure distribution on the rotor blade surface under different injected momentum ratios, tip air injection can effectively suppress flow separation at the blade tip to enhance flow capability. In addition, it can also weaken the fluctuation of tip leakage flow and reduce the dynamic stress similar to natural vibration near the blade root both in stationary and rotating coordinate systems. Under the condition of inlet circumferential distortion, tip air injection can significantly reduce the load at the distorted region and suppress the low-frequency disturbances measured on the rotor blade surface caused by inlet distortion. In addition, the dynamic stress near the blade root can also be effectively reduced by tip air injection. It implies that tip air injection can both extend the stall margin and reduce blade vibration when suffering from circumferential distortion; thus, the compressor can safely operate.

Understanding Unsteady Vortex Structure and Shedding Frequency of Cylindrical Hole Film Cooling: Insights From Experimental and Numerical Approaches

Abstract To enhance film cooling effectiveness and reduce mixing loss, it is imperative to understand the dynamics of the unsteady vortex system and its interaction with the mainstream flow. In this study, a comprehensive experimental investigation was conducted to assess the film cooling effectiveness of a flat-plate cylindrical hole, along with the structure of the vortex system and the frequency of vortex shedding. This was achieved using a variety of techniques including pressure-sensitive paint (PSP), particle image velocimetry (PIV), hot-wire anemometry, and dynamic pressure sensors. To complement the experimental findings, a detailed analysis of the evolution mechanisms of unsteady coherent vortices was performed using the detached eddy simulation (DES) numerical method. The findings of the study revealed that the Kelvin–Helmholtz (K–H) shear vortex patterns on the windward side undergo a transition from clockwise to counterclockwise rotation with increasing blowing ratios. Large-scale vortex sheds from the K–H shear vortices, ultimately evolving into the hairpin vortex in the downstream region. Additionally, the study proposed two evolution models for the vortex systems in the film cooling flow field at different blowing ratios and elucidated the evolution mechanisms of counter-rotating vortex pair (CRVP). The results of the spectral analysis revealed a notable discrepancy in the slopes of the eigenfrequencies, which could be attributed to variations in the evolution patterns of the vortex systems.

Combining Machine Learning, Embedded Sensor Networks and Additive Burner Design for Combustor Structural Health Monitoring

Abstract The crystAIr project is about sensitising burners for flame monitoring based on a discrete number of dynamic pressure sensors and a machine learning approach. The context is the development of better aircraft engines and the prospect of technical solutions for hydrogen-fuelled gas turbines. The combination of sensors and appropriate signal processing is designed to mimic a ‘feel’ for the state of the flame. The idea is to monitor the gas turbine's correct operation in real-time and anticipate impending problems such as flame blowout, combustion instability or flashback. Compared to conventional flame monitoring based on signal sampling, thresholding, band-pass analysis and time-lag measurement, this method should be less computationally intensive, more sensitive and more robust to artefacts. Not only should it be more responsive, but it should also anticipate problems based on a lessons-learned approach and outperform the conventional precursors. An unassisted machine learning method is used to achieve this. A custom-built AM burner designed for this experiment provides multiple instrumentation options. A powerful data acquisition system is set up to collect data on multiple channels, over a long time duration and at high speed to collect the learning signal chunks. The focus is on the detection of flames and, more specifically, the moment of their ignition and extinction, the operating conditions that are prone to flashback and the stability of the combustion. Additional measurement techniques are used to refine the learning method. The paper covers all these points and presents the first results.

Identification of Acoustic Sources on Antares Launch Pad Using Microphone Phased Array

A microphone phased array (MPA) was mounted in the vicinity of pad 0A of Mid-Atlantic Regional Spaceport located on NASA’s Wallops Flight Facility to identify the evolution of acoustic sources from hold-down to an elevation of ∼200 ft during the launch of an Antares rocket (Northrop Grumman [NG]-19). The MPA was equipped with 70 piezo-resistive dynamic pressure sensors, a visible-band and an infrared-band camera, and a two-axis accelerometer. The noise map demonstrated an effective use of the water injection system to attenuate noise from plume impingement on the pad. They also pointed out the outlet of the exhaust duct, through which the steam and plume mixture ejected out, to be the primary noise source during a significant interval of time. A comparison with prior such measurements during the maiden launch of the Antares vehicle in 2013 showed significant attenuation of noise sources during the NG-19 launch. A strong source caused by the impingement of plume on the pad surface during the 2013 launch was found to be attenuated in 2023. The results showed the utility of an MPA in quantifying the impact of changes made to a launch pad.

Leak detection and localization in water distribution systems using advanced feature analysis and an Artificial Neural Network

This study capitalizes on a dataset, originally including 280 sensory measurements from a laboratory-scale water distribution system, to advance the concept of leakage diagnosis and localization. The water distribution test rig are formulated in two configurations, namely looped and branched layouts. The paper processed time-domain data from accelerometers and dynamic pressure sensors into advanced statistical features of: Autocorrelation Coefficient (Au-C), and Signal Energy (Sig-E), to detect and localize the water leakage. By the Employment of these two features, the research developed an expert system of an Artificial Neural Network (ANN) model designed with optimal parameters, neurons, and hidden layers to classify the presence and pinpoint the location of leaks within the water test rig. The effectiveness of the current approach is quantitatively evaluated using F1-scores and accuracy metrics. A robust capability for both detecting and localizing leaks under varying conditions was established with a highest accuracy and F1-score of 86.5 % and 86.2 %, respectively. The findings underscore the potential of integrating advanced features with Artificial Intelligence (AI) in enhancing the reliability and dependability of water management expert systems. This approach contributes to the broader application of AI in managing water resources and infrastructure resilience with its support to improve leakage whereabouts.

High sensitivity distributed dynamic pressure sensor based on dual-linear frequency modulated optical frequency domain reflectometry.

In this Letter, we propose and experimentally demonstrate a highly sensitive distributed dynamic pressure sensor based on a dual-linear frequency modulated optical frequency domain reflectometry (OFDR) and a coating thickness-enhanced single-mode fiber (SMF). A dual-sideband linear frequency modulation (LFM) signal is used to interrogate the sensing fiber, which allows us to obtain a dual-sideband Rayleigh backscattering signal. Due to the opposite slopes of the two LFM sidebands, the Rayleigh backscattering spectra of the two sidebands drift in opposite directions when the fiber is disturbed. By subtracting the frequency shifts of the two spectra, we can double the system's sensitivity. We further enhance the sensitivity by using an SMF with a coating thickness of 200 μm. This results in a pressure sensitivity of 3979 MHz/MPa, a measurement accuracy of 0.76 kPa, and a spatial resolution of 35 cm over a 500 m optical fiber. Our system successfully detected a dynamic pressure change at a sampling rate of 1.25 kHz, demonstrating the sensor's excellent dynamic measuring capabilities.

Corner Separation Control Using Sweeping Jet Actuator in a Compressor Cascade

Abstract In the pursuit of advancing active flow control (AFC) technology, a more promising nonsteady actuator known as sweeping jet actuator (SJA) has been equipped on the endwall to manage the corner separation in a compressor cascade, while the steady jet actuators with holes were used for comparison. Experimental investigations have been conducted in a low-speed wind tunnel with an inflow Mach number of 0.23. Five-hole probe measurements and the oil flow visualizations were carried out to demonstrate the performance and physics of steady and unsteady blowing on controlling the corner separation. The transient data at the measurement plane were also obtained using the dynamic pressure sensors to get insight into the unsteady characteristics. Variation of jet momentum of both actuators and the excitation frequency of the SJA allows determination of favorable control parameters. Using the SJA with only 0.13% of the cascade mass flow, the total pressure loss which takes the additional energy input into account is reduced by 14.2%, while the steady jet achieves a reduction of 8.4%. The results highlight the superior characteristics of the SJA in controlling the corner separation.

Design and Optimization of Piezoelectric Pressure Sensor with AlN as piezo electric material for High-Temperature Application using COMSOL 5.3

Dynamic pressure sensors in contrast to static pressure sensors measure pressure changes in liquids or gases generated due to a blast, a propulsion or an explosion, where the temperature is normally high which is above 700°C[1]. Piezoelectric pressure sensors with their inherent advantage of direct transduction capability are drawing attention for high-temperature applications. Lead Zirconate Titanate (PZT) and Zinc Oxide (ZnO) are popular ferroelectric materials for Piezoelectric sensor applications. Aluminum Nitride (AlN) is a suitable candidate for high-temperature applications with its high melting point of 2673 K, the piezoelectric property remaining stable even up to 1423K, the energy band gap of 6.2eV, piezoelectric coefficient d33 of 7pC/N and pressure handling capacity up to 10 MPa. In this study, COMSOL Multiphysics 5.3 was used to analyse the pressure sensing capability of AlN film by optimizing the crystal orientation and the dimension of AlN in addition to studying suitability of using at high temperature. Also a comparison is done on the high temperature performance of pressure sensor using Silicon and Silicon Carbide as diaphragm.

A study on dynamic pressure sensor based on Pitot tube structure.

To meet the demand for the accurate measurements of the dynamic pressure of a shock wave, a composite dynamic pressure sensor design method is proposed based on the formation mechanism, propagation characteristics, special testing environment of the dynamic pressure, and Pitot tube structure. The dynamic pressure of the shock wave is evaluated by the total pressure and static pressure units installed in the composite sensor. FLUENT simulation software was used to analyze the aerodynamic characteristics of the dynamic pressure sensor, and parameters such as the structural size and inlet position of the sensor were determined. In response to the special experimental environment of the shock wave, the requirements for the dynamic pressure measurements under damage conditions were analyzed, and a dynamic pressure testing system was established. Dynamic pressure tests with four 2,4,6-trinitrotoluene [C7H5(NO2)3] equivalents of 1, 2, 15, and 20kg were carried out. The experimental results show that the proposed sensor design method can accurately and effectively measure the dynamic pressure signal, and the dynamic pressure gain multiple decreases with an increase in the proportional distance. This provides an effective testing method for evaluating the dynamic pressure damage effect of ammunition systems.

A New Model of Air-Oxygen Blender for Mechanical Ventilators Using Dynamic Pressure Sensors.

Respiratory diseases are among the leading causes of death globally, with the COVID-19 pandemic serving as a prominent example. Issues such as infections affect a large population and, depending on the mode of transmission, can rapidly spread worldwide, impacting thousands of individuals. These diseases manifest in mild and severe forms, with severely affected patients requiring ventilatory support. The air-oxygen blender is a critical component of mechanical ventilators, responsible for mixing air and oxygen in precise proportions to ensure a constant supply. The most commonly used version of this equipment is the analog model, which faces several challenges. These include a lack of precision in adjustments and the inspiratory fraction of oxygen, as well as gas wastage from cylinders as pressure decreases. The research proposes a blender model utilizing only dynamic pressure sensors to calculate oxygen saturation, based on Bernoulli's equation. The model underwent validation through simulation, revealing a linear relationship between pressures and oxygen saturation up to a mixture outlet pressure of 500 cmH2O. Beyond this value, the relationship begins to exhibit non-linearities. However, these non-linearities can be mitigated through a calibration algorithm that adjusts the mathematical model. This research represents a relevant advancement in the field, addressing the scarcity of work focused on this essential equipment crucial for saving lives.

PDMS diaphragm based miniature fiber-optic Fabry-Perot dynamic pressure sensor for turbomachinery application.

Small-sized, highly sensitive dynamic pressure sensors are crucial in the field of turbomachinery application. In this paper, a fiber-tip structure dynamic pressure sensor utilizing a small piece of glass tube as the air cavity and PDMS material as the diaphragm was fabricated. It has the advantage of being small in size with the diameter of 125µm while having high sensitivity of 26.26pm/kPa. The fabrication process was described in detail, which is simple and cost-effective. The sensor characteristics were studied theoretically and experimentally. Quasi-square pressure signal of different frequencies generated by the siren disk were measured by the sensor and compared with that obtained from the commercial piezoresistive pressure sensor to verify the accuracy of the proposed sensor. The R2 of the four pairs of pressure waveforms were 0.94, 0.81, 0.93, and 0.96, respectively. Stability testing of the sensor was also performed, showing that the sensor can work reliably under dynamic pressure environment.

Underwater Biomimetic Lateral Line Sensor Based on Triboelectric Nanogenerator for Dynamic Pressure Monitoring and Trajectory Perception.

Developing desirable sensors is crucial for underwater perceptions and operations. The perceiving organs of marine creatures have greatly evolved to react accurately and promptly underwater. Inspired by the fish lateral line, this study proposes a triboelectric dynamic pressure sensor for underwater perception. The biomimetic lateral line sensor (BLLS) has high sensitivity to the disturbance amplitude/frequency, good adaptability to underwater environments and (relative) low cost. The sensors are deployed at the bottom of the test basin to perceive various moving objects, such as a robotic fish, robotic seal, etc. By analyzing the electrical signal of the sensor, the motion parameters of the objects passed over can be obtained. By monitoring signal variations across multiple sensors, the ability to sense different disturbance movement trajectories, including linear and angular trajectories, is achievable. The study will prove significant in forming an unconventional underwater perceiving method, which can back-up the sonic/optical sensors when are impaired in complex underwater environments.

Experimental methodology for the characterization of a hydrogen-fuelled Pressure Gain Combustor

Gas turbines have been a key technology in many industrial sectors for over 50 years and they will continue to play a crucial role in the energetic scenario. Nevertheless, these systems are approaching their efficiency limits and performance improvements are becoming increasingly difficult to achieve. In this context, Pressure Gain Combustion (PGC) has emerged as a promising technology: replacing the isobaric combustion with a quasi-isochoric process creates a rise in total pressure across the combustion chamber, enhancing their potential performances. However, it is a complex process influenced by combustion chemistry, heat transfer, and fluid dynamics, and its unsteadiness increases the complexity of measurement campaigns. Thus, several challenges still need to be addressed for its development.This paper shows the experimental methodology followed to characterize an innovative deflagrative-based PGC fuelled with 100% hydrogen. Dynamic pressure sensors were installed inside, upstream, and downstream of the combustion chamber and acquired at a high frequency (1 MHz) to describe in detail the process.Downstream the combustor, an orifice simulated the pressure drop across the turbine. Different fuel pressure has been tested, varying the operating parameters and the position of the pressure sensors inside the chamber. For each configuration, a detailed analysis of the mean pressure trends and cycle-to-cycle variation was carried out and will help optimize the system in the following tasks of the project. The experimental methodology described can be used to better investigate the physics of Pressure Gain Combustors and allow complete exploitation of their potentiality in terms of work extracted, resource consumption, and pollutant emission.

Flame dynamics and combustion instability induced by flow-flame interactions in a centrally-staged combustor

This study mainly investigates the flame and flow characteristics under combustion instability in a centrally-staged swirl spray combustor, using 5 kHz CH* chemiluminescence (CL) and 15 Hz particle image velocimetry (PIV). The inlet air total temperature and total pressure are up to 600 K and 1 MPa, respectively. A dynamic pressure sensor with an acquisition frequency of 20 kHz is located downstream of the combustor casing. The pressure signal shows large-amplitude limit cycle oscillations when the fuel split ratio of the pilot stage decrease. The phase-averaged CH* CL images indicate that the periodic ignition/extinction of the main stage flame triggers combustion instability. A proper orthogonal decomposition (POD) analysis based on the reacting flow field further explains this phenomenon. The first two POD modes containing three coherent vortex pairs are associated with the extinction and ignition of the main stage flame, respectively. The vortex pairs located at the central shear layer (CSL) generated by Kelvin-Helmholtz (K-H) instability affect the primary recirculation zone (PRZ). The change in the size of the PRZ influences the main stage flame dynamics. In a cycle of oscillation, ignition happens when the size of PRZ increases and the coupling between the main and pilot stages enhances. Extinction takes place when the opposite happens. The flow-flame interaction mechanism demonstrated in this study provides strong experimental support for understanding combustion instability in aero-engine combustors.

Acoustic sources identified using a microphone phased array during a rocket engine test

A new phased array of microphones, suitable for the harsh environment of a rocket launch, was built and tested during a static firing of an RS-25 engine. It uses 70 piezo-resistive, dynamic pressure sensors, optimally distributed on a 10.5-ft diameter open frame dome structure and has a 200-ft long cable bundle to carry the signals to a weather-protected cabinet containing the data systems. The test stand was imaged using an infra-red camera and a visible wavelength camera, and the beamformed noise maps were superimposed on the photographs. The first-time data from a full-scale engine test stand showed that the plume deflector at the bottom of the engine was the primary noise source. The openings of the test stand around the nozzle exit were also found to be noise sources particularly at higher frequencies. The final goal is to utilize the array during NASA’s Artemis-II launch at Kennedy Space Center.

Random Forest Model of Flow Pattern Identification in Scavenge Pipe Based on EEMD and Hilbert Transform

Complex oil and gas two-phase flow exists within an aero-engines bearing cavity scavenge pipe, prone to lubricated self-ignition and coking. Lubricant system designers must be able to accurately identify and understand the flow state of the scavenge pipe. The prediction accuracy of previous models is insufficient to meet the more demanding needs. This paper establishes a visualized flow pattern identification test system for the scavenge pipe, with a test temperature of up to 370 k, using a high-speed camera to photograph four flow patterns, decomposing the pressure signals obtained from high-frequency dynamic pressure sensors using the ensemble empirical mode decomposition (EEMD) method, and then performing Hilbert transform, using the Hilbert spectrum to quantify the changes of amplitude and frequency with time, and establishing the energy and flow pattern correspondence analysis. Then the energy percentage of IMFs is used as the input of feature values, and the random forest algorithm machine learning is used for predictive classification. The experimental results show that the flow pattern recognition rate established in this paper can reach 98%, which can identify the two-phase flow pattern in the scavenge pipe more objectively and accurately.

Chameleon-inspired flexible photonic crystal lens-shaped dynamic pressure sensor based on structural color shift

Chameleon-inspired flexible photonic crystal lens-shaped dynamic pressure sensor based on structural color shift

Dynamic Calibration Method of Blast Pressure Pencil Probes Based on Adjustable Shock Tube

Dynamic calibration is one of the important ways to obtain the dynamic performance parameters of pressure sensors, and shock tube calibration is a common method for dynamic calibration of pressure sensors. To study the dynamic calibration method of the shock tube of the blast pressure pencil probes, such as free-field pressure sensors and dynamic pressure sensors, a convenient and adjustable PVC-U (unplasticized polyvinyl chloride) shock tube is developed. Taking the dynamic pressure sensor as the research object, the feasibility of dynamic calibration of shock tube based on CFD (Computational Fluid Dynamics) techniques is discussed. Finally, the dynamic calibration experiment based on shock tube is carried out, and the time-domain and frequency-domain signals are analyzed. The results are in good agreement with the theoretical analysis. The results show that the shock tube can effectively excite the natural frequency of the dynamic pressure sensor, and the developed shock tube can indeed achieve the dynamic calibration and dynamic experiments of pencil probes.

МОДАЛЬНЫЙ АНАЛИЗ ОПТОВОЛОКОННОГО РЕЗОНАНСНОГО ПЬЕЗОЭЛЕКТРОЛЮМИНЕСЦЕНТНОГО ДАТЧИКА ДАВЛЕНИЯ

An electro-mechanical mathematical model of the functioning of an optical fiber resonance piezoelectroluminescent (RPEL) sensor with an external nonlinear elastic buffer layer has been developed. The sensor is designed to measure the distribution spectrum along the length of the dynamic and/or static pressure sensor using a resonant diagnostic method based on the results of measuring the amplitude spectrum of the intensity of the resulting light flux at the output from the fiber of the sensor. The numerical values of the frequency characteristics (- these are the proportionality coefficients for the informative relationship "pressure/resonance frequency") of the optical fiber RPEL sensor, which are used in the algorithm for finding the pressure spectrum, for different (first six) modes of vibration, are determined.

Experimental Investigations of Centrifugal Compressor Surge Noise

Abstract Surge is a crucial problem for achieving a good working range of centrifugal compressor and power cycle safety. Effective and early detection of the surge is essential to avoid its onset. In this paper, experiments measuring the pressure and acoustic signals have been conducted to investigate the surge. The compressor prototype used in this study consists of an impeller wheel with backward blades, a vaneless diffuser, and a downstream discharge volute. The compressor prototype was instrumented with steady pressure and temperature sensors to characterize the performance map, a fast dynamic pressure sensor to measure the surge-induced pressure fluctuation, and 13 microphones to record the acoustic pressure on the inlet duct wall and in the far field. The transient experimental data were analyzed in time and frequency domains. The noise related to surge is identified as a chord sound from multiple sources that radiate acoustic impulse synchronously at the compression system surge frequency (below 10 Hz in the current experiment). A previously rarely discussed surge inception is identified from the acoustic spectrogram within the frequency range of 30–85 Hz, but not reflected by the pressure signal, in which an increase of the sound pressure level (SPL) is detected before the mass flow rate achieves the surge point. The mechanism is that the pressure fluctuation corresponding to the inception is too weak, within the detecting range of microphones that measures acoustic signals, and lower than the bottom limit of the commonly used dynamic pressure sensors. It suggests that acoustic measurement may have advantages in surge inception detection and prediction.