Academic literature on the topic 'Path Ensemble Average'
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Journal articles on the topic "Path Ensemble Average"
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Corrêa, Raul, Marina F. B. Cenni, and Pablo L. Saldanha. "Quantum Interference of Force." Quantum 2 (December 14, 2018): 112. http://dx.doi.org/10.22331/q-2018-12-14-112.
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We show that a quantum particle subjected to a positive force in one path of a Mach-Zehnder interferometer and a null force in the other path may receive a negative average momentum transfer when it leaves the interferometer by a particular exit. In this scenario, an ensemble of particles may receive an average momentum in the opposite direction of the applied force due to quantum interference, a behavior with no classical analogue. We discuss some experimental schemes that could verify the effect with current technology, with electrons or neutrons in Mach-Zehnder interferometers in free space and with atoms from a Bose-Einstein condensate.
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Chen, Yan, Rolf J. Lorentzen, and Erlend H. Vefring. "Optimization of Well Trajectory Under Uncertainty for Proactive Geosteering." SPE Journal 20, no. 02 (August 28, 2014): 368–83. http://dx.doi.org/10.2118/172497-pa.
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Summary Various logging-while-drilling (LWD) and seismic-while-drilling (SWD) tools offer opportunities to obtain geological information near the bottomhole assembly during the drilling process. These real-time in-situ data provide relatively high-resolution information around and possibly ahead of the drilling path compared with the data from a surface seismic survey. The use of these in-situ data offers substantial potential for improved recovery through continuous optimization of the remaining well path while drilling. We show an automated workflow for proactive geosteering through continuous updating of the estimates of the Earth model and robust optimization of the remaining well path under uncertainty. A synthetic example is shown to illustrate the proposed workflow. The estimates of the depths of the reservoir surfaces and the depth of the oil/water contact and their associated uncertainty are obtained through the ensemble Kalman filter by use of directional-resistivity measurements. A robust optimization is used to compute the well position that minimizes the average cost function evaluated on the ensemble of geological models estimated from the ensemble Kalman filter (EnKF). The effect of modeling errors and the effect of joint estimation of the depths of the boundaries and gridblock resistivity are also investigated.
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Pinty, Jean-Pierre, and Christelle Barthe. "Ensemble Simulation of the Lightning Flash Variability in a 3D Cloud Model with Parameterizations of Cloud Electrification and Lightning Flashes." Monthly Weather Review 136, no. 1 (January 1, 2008): 380–87. http://dx.doi.org/10.1175/2007mwr2186.1.
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Abstract A series of ensemble simulations were performed to study the statistics of flash characteristics produced by an electrification and lightning scheme in the cloud-resolving model Méso-NH. Here, the electrical variability of two storms—one supercellular and one multicellular—results from a random triggering location of the flashes and from a branching algorithm that describes the flash path. The study shows that the electrical model is able to generate several estimates of the total flash number for an identical evolution of the dynamics and microphysics of each storm in the 120 ensemble members. The variability of the flash number spans over three standard deviations taken from the ensemble mean. The simulations produce regularly shaped distributions of flash internal parameters (i.e., number of segments and branching levels per flash). The ensemble simulation shows that the model is stable and self-regulatory as suggested by the limited overshoot on the maximum electric field time series. An application to the production of nitrogen oxides indicates that the two storms produce 200 ± 150 mol of NO per flash on average.
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Okuboyejo, Damilola A., and Oludayo O. Olugbara. "Classification of Skin Lesions Using Weighted Majority Voting Ensemble Deep Learning." Algorithms 15, no. 12 (November 24, 2022): 443. http://dx.doi.org/10.3390/a15120443.
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The conventional dermatology practice of performing noninvasive screening tests to detect skin diseases is a source of escapable diagnostic inaccuracies. Literature suggests that automated diagnosis is essential for improving diagnostic accuracies in medical fields such as dermatology, mammography, and colonography. Classification is an essential component of an assisted automation process that is rapidly gaining attention in the discipline of artificial intelligence for successful diagnosis, treatment, and recovery of patients. However, classifying skin lesions into multiple classes is challenging for most machine learning algorithms, especially for extremely imbalanced training datasets. This study proposes a novel ensemble deep learning algorithm based on the residual network with the next dimension and the dual path network with confidence preservation to improve the classification performance of skin lesions. The distributed computing paradigm was applied in the proposed algorithm to speed up the inference process by a factor of 0.25 for a faster classification of skin lesions. The algorithm was experimentally compared with 16 deep learning and 12 ensemble deep learning algorithms to establish its discriminating prowess. The experimental comparison was based on dermoscopic images congregated from the publicly available international skin imaging collaboration databases. We propitiously recorded up to 82.52% average sensitivity, 99.00% average specificity, 98.54% average balanced accuracy, and 92.84% multiclass accuracy without prior segmentation of skin lesions to outstrip numerous state-of-the-art deep learning algorithms investigated.
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Susskind, Leonard. "De Sitter Holography: Fluctuations, Anomalous Symmetry, and Wormholes." Universe 7, no. 12 (November 29, 2021): 464. http://dx.doi.org/10.3390/universe7120464.
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The Goheer–Kleban–Susskind no-go theorem says that the symmetry of de Sitter space is incompatible with finite entropy. The meaning and consequences of the theorem are discussed in light of recent developments in holography and gravitational path integrals. The relation between the GKS theorem, Boltzmann fluctuations, wormholes, and exponentially suppressed non-perturbative phenomena suggests that the classical symmetry between different static patches is broken and that eternal de Sitter space—if it exists at all—is an ensemble average.
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Shi, Min, Dong Dong Yang, Yuan Zhou, Huan Zhao, and Yu Fang. "Analysis of Migraine Induced Monitoring Imaging Data by Multilayer Mixed Cluster Detection." Journal of Medical Imaging and Health Informatics 9, no. 6 (August 1, 2019): 1278–83. http://dx.doi.org/10.1166/jmihi.2019.2729.
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The complex network of resting brain function was constructed by graph theory to study the difference of network topology between migraine patients and normal people. The complex network of brain function of the two groups was constructed respectively, and the average clustering coefficient, characteristic path length, small cosmopolitan, homology, median centrality and other measurement parameters of the two groups of complex networks were calculated and compared. The multi-layer hybrid ensemble clustering detection is introduced for data analysis, and the edge connectivity of consensus is optimized by modular analysis combined with hill climbing algorithm to improve the performance of the multi-layer hybrid ensemble clustering detection process driven by modularity. Conclusion: The abnormal areas of resting brain function network in migraine patients are related to pain management, visual processing and sensory relay, the findings of this study are helpful to better explain the clinical symptoms of migraine.
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Mallick, Swapan. "Impact of Adaptively Thinned GOES-16 Cloud Water Path in an Ensemble Data Assimilation System." Meteorology 1, no. 4 (December 5, 2022): 513–30. http://dx.doi.org/10.3390/meteorology1040032.
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Assimilation of cloud properties in the convective scale ensemble data assimilation system is one of the prime topics of research in recent years. Satellites can retrieve cloud properties that are important sources of information of the cloud and atmospheric state. The Advance Baseline Imager (ABI) aboard the GOES-16 geostationary satellite brings an opportunity for retrieving high spatiotemporal resolution cloud properties, including cloud water path over continental United States. This study investigates the potential impacts of assimilating adaptively thinned GOES-16 cloud water path (CWP) observations that are assimilated by the ensemble-based Warn-on-Forecast System and the impact on subsequent weather forecasts. In this study, for CWP assimilation, multiple algorithms have been developed and tested using the adaptive-based thinning method. Three severe weather events are considered that occurred on 19 July 2019, 7 May and 21 June 2020. The superobbing procedure used for CWP data smoothed from 5 to 15 km or more depending on thinning algorithm. The overall performance of adaptively thinned CWP assimilation in the Warn-on-Forecast system is assessed using an object-based verification method. On average, more than 60% of the data was reduced and therefore not used in the assimilation system. Results suggest that assimilating less than 40% of CWP superobbing data into the Warn-on-Forecast system is of similar forecast quality to those obtained from assimilating all available CWP observations. The results of this study can be used on the benefits of cloud assimilation to improve numerical simulation.
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Yang, Caipei, Yingqi Zhao, Xuan Cai, Wei Wei, Xingxing Feng, and Kaibo Zhou. "Path Planning Algorithm for Unmanned Surface Vessel Based on Multiobjective Reinforcement Learning." Computational Intelligence and Neuroscience 2023 (February 15, 2023): 1–14. http://dx.doi.org/10.1155/2023/2146314.
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It is challenging to perform path planning tasks in complex marine environments as the unmanned surface vessel approaches the goal while avoiding obstacles. However, the conflict between the two subtarget tasks of obstacle avoidance and goal approaching makes the path planning difficult. Thus, a path planning method for unmanned surface vessel based on multiobjective reinforcement learning is proposed under the complex environment with high randomness and multiple dynamic obstacles. Firstly, the path planning scene is set as the main scene, and the two subtarget scenes including obstacle avoidance and goal approaching are divided from it. The action selection strategy in each subtarget scene is trained through the double deep Q-network with prioritized experience replay. A multiobjective reinforcement learning framework based on ensemble learning is further designed for policy integration in the main scene. Finally, by selecting the strategy from subtarget scenes in the designed framework, an optimized action selection strategy is trained and used for the action decision of the agent in the main scene. Compared with traditional value-based reinforcement learning methods, the proposed method achieves a 93% success rate in path planning in simulation scenes. Furthermore, the average length of the paths planned by the proposed method is 3.28% and 1.97% shorter than that of PER-DDQN and dueling DQN, respectively.
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Qazvinian, Vahed, and Dragomir Radev. "Exploiting Phase Transition in Latent Networks for Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (August 4, 2011): 908–13. http://dx.doi.org/10.1609/aaai.v25i1.7972.
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In this paper, we model the pair-wise similarities of a setof documents as a weighted network with a single cutoffparameter. Such a network can be thought of an ensemble of unweighted graphs, each consisting of edges withweights greater than the cutoff value. We look at this network ensemble as a complex system with a temperature parameter, and refer to it as a Latent Network. Ourexperiments on a number of datasets from two different domains show that certain properties of latent networks like clustering coefficient, average shortest path,and connected components exhibit patterns that are significantly divergent from randomized networks. We explain that these patterns reflect the network phase transition as well as the existence of a community structure in document collections. Using numerical analysis,we show that we can use the aforementioned networkproperties to predicts the clustering Normalized MutualInformation (NMI) with high correlation (rho > 0.9). Finally we show that our clustering method significantlyoutperforms other baseline methods (NMI > 0.5)
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Nagao, Hidemi, Yasuteru Shigeta, Hiroyuki Kawabe, Takashi Kawakami, Kiyoshi Nishikawa, and Kizashi Yamaguchi. "Path integral method by means of generalized coherent states and its numerical approach to molecular systems. I. Ensemble average of total energy." Journal of Chemical Physics 107, no. 16 (October 22, 1997): 6283–89. http://dx.doi.org/10.1063/1.474290.
Full textDissertations / Theses on the topic "Path Ensemble Average"
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Giovannelli, Edoardo. "Sampling methods and free energy estimators for computer simulations: development and applications." Doctoral thesis, 2018. http://hdl.handle.net/2158/1124398.
Full textBooks on the topic "Path Ensemble Average"
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Coolen, A. C. C., A. Annibale, and E. S. Roberts. Ensembles with hard constraints. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0005.
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This chapter introduces random graph ensembles involving hard constraints such as setting a fixed total number of links or fixed degree sequence, including properties of the partition function. It continues on from the previous chapter’s investigation of ensembles with soft-constrained numbers of two-stars (two-step paths) and soft-constrained total number of triangles, but now combined with a hard constraint on the total number of links. This illustrates phase transitions in a mixed-constrained ensemble – which in this case is shown to be a condensation transition, where the network becomes clumped. This is investigated in detail using techniques from statistical mechanics and also looking at the averaged eigenvalue spectrum of the ensemble. These phase transition phenomena have important implications for the design of graph generation algorithms. Although hard constraints can (by force) impose required values of observables, difficult-to-reconcile constraints can lead to graphs being generated with unexpected and unphysical overall topologies.
Book chapters on the topic "Path Ensemble Average"
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Johnson, Adriana, Gregory F. Cooper, and Shyam Visweswaran. "A Novel Personalized Random Forest Algorithm for Clinical Outcome Prediction." In MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation. IOS Press, 2022. http://dx.doi.org/10.3233/shti220072.
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Machine learning algorithms that derive predictive models are useful in predicting patient outcomes under uncertainty. These are often “population” algorithms which optimize a static model to predict well on average for individuals in the population; however, population models may predict poorly for individuals that differ from the average. Personalized machine learning algorithms seek to optimize predictive performance for every patient by tailoring a patient-specific model to each individual. Ensembles of decision trees often outperform single decision tree models, but ensembles of personalized models like decision paths have received little investigation. We present a novel personalized ensemble, called Lazy Random Forest (LazyRF), which consists of bagged randomized decision paths optimized for the individual for whom a prediction will be made. LazyRF outperformed single and bagged decision paths and demonstrated comparable predictive performance to a population random forest method in terms of discrimination on clinical and genomic data while also producing simpler models than the population random forest.
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Gams, Matjaz, and Matej Ozek. "Use of Data Mining Techniques for Process Analysis on Small Databases." In Dynamic and Advanced Data Mining for Progressing Technological Development, 422–36. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-908-3.ch017.
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The pharmaceutical industry was for a long time founded on rigid rules. With the new PAT initiative, control is becoming significantly more flexible. The Food and Drug Administration is even encouraging the industry to use methods like machine learning. The authors designed a new data mining method based on inducing ensemble decision trees from which rules are generated. The first improvement is specialization for process analysis with only a few examples and many attributes. The second innovation is a graphical module interface enabling process operators to test the influence of parameters on the process itself. The first task is creating accurate knowledge on small datasets. The authors start by building many decision trees on the dataset. Next, they subtract only the best subparts of the constructed trees and create rules from those parts. A best tree subpart is in general a tree branch that covers most examples, is as short as possible and has no misclassified examples. Further on, the rules are weighed, regarding the number of examples and parameters included. The class value of the new case is calculated as a weighted average of all relevant rule predictions. With this procedure the authors retain clarity of the model and the ability to efficiently explain the classification result. In this way, overfitting of decision trees and overpruning of the basic rule learners are diminished to a great extent. From the rules, an expert system is designed that helps process operators. Regarding the second task of graphical interface, the authors modified the Orange explanation module so that an operator at each step takes a look at several space planes, defined by two chosen attributes (Demšar et al., 2004). The displayed attributes are the ones that appeared in the classification rules triggered by the new case. The operator can interactively change the current set of process parameters in order to check the improvement of the class value. The task of seeing the influence of combining all the attributes leading to a high quality end product (called design space) is now becoming human comprehensible, it does not demand a highdimensional space vision any more. The method was successfully implemented on data provided by a pharmaceutical company. High classification accuracy was achieved in a readable form thus introducing new comprehensions.
Conference papers on the topic "Path Ensemble Average"
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Nickol, Jeremy, Matthew Tomko, Randall Mathison, Jong S. Liu, Mark Morris, and Malak F. Malak. "Heat Transfer and Pressure Measurements for the Forward Purge Cavity, Inner Endwall, and Rotor Platform of a Cooled Transonic Turbine Stage." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-76978.
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An experiment is performed using a cooled transonic high-pressure turbine stage operating at design-corrected conditions. Pressure measurements are taken at several locations within the forward purge cavity between the high-pressure stator and rotor, as well as on the blade platforms and vane inner endwalls. Double-sided Kapton heat-flux gauges are installed on the upper surface of the rotor blade platform (open to the hot gas path flow) and underneath the platform (exposed to coolant and leakage flow). The blade airfoil and purge flow cooling are supplied by the same flow circuit and must be varied together, but the influence of the airfoil cooling has previously been shown to be negligible in the platform region flow of interest to this study. A separate cooling circuit supplies the aft purge flow between the rotor and downstream components. The vane cooling holes have been blocked off for this experiment to simplify analysis. In order to determine the effect of the purge flow on the blade aerodynamics and heat transfer, the forward and aft cooling flow rates are varied independently. Both time-averaged and time-accurate results are presented for the pressure and heat-flux data to illustrate the complex interactions between the purge cavity flow structures and the external flow. Time-accurate data are presented using both Fast-Fourier Transforms (FFTs) to identify driving frequencies and ensemble average plots to highlight the impact of different wake shapes.
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Bianchini, Alessandro, Davide Biliotti, Giovanni Ferrara, Lorenzo Ferrari, Elisabetta Belardini, Marco Giachi, Libero Tapinassi, and Giuseppe Vannini. "A Systematic Approach to Estimate the Impact of the Aerodynamic Force Induced by Rotating Stall in a Vaneless Diffuser on the Rotordynamic Behavior of Centrifugal Compressors." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-95754.
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One of the main challenges of the present industrial research on centrifugal compressors is the need of extending the left margin of the operating range of the machines. As a result, interest is being paid in accurately evaluating the amplitude of the pressure fluctuations caused by rotating stall, which usually occurs prior to surge. The related aerodynamic force acting on the rotor can produce subsynchronous vibrations, which can prevent the machine to further operate, in case their amplitude is too high. These vibrations are often contained thanks to the stiffness of the oil journals. Centrifugal compressors design is, however, going towards alternative journal solutions having lower stiffness levels (e.g. Active Magnetic Bearings or Squeeze Film Dampers), which hence will be more sensitive to this kind of excitation: consequently, a more accurate estimation of the expected forces in presence of dynamic external forces like those connected to an aerodynamically unstable condition is needed to predict the vibration level and the compressor operability in similar conditions. Within this scenario, experimental tests were carried out on an industrial impeller operating at high peripheral Mach number. The dedicated test rig was equipped with several dynamic pressure probes that were inserted in the gas flow path; moreover, the rotor vibrations were constantly monitored with typical vibration probes located near the journal bearings. The pressure field induced by the rotating stall in the vaneless diffuser was reconstructed by means of an ensemble average approach, defining the amplitude and frequency of the external force acting on the impeller. The calculated force value was then included in the rotordynamic model of the test rig: the predicted vibrations on the bearings were compared with the measurements, showing satisfactory agreement. Finally, the prospects of the proposed approach are discussed by investigating the response of a real machine in high-pressure functioning when different choices of journal bearings are made.
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Schobeiri, M. T., and R. E. Radke. "Effects of Periodic Unsteady Wake Flow and Pressure Gradient on Boundary Layer Transition Along the Concave Surface of a Curved Plate." In ASME 1994 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/94-gt-327.
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Boundary layer transition and development on a turbomachinery blade is subjected to highly periodic unsteady turbulent flow, pressure gradient in longitudinal as well as lateral direction, and surface curvature. To study the effects of periodic unsteady wakes on the concave surface of a turbine blade, a curved plate was utilized. On the concave surface of this plate, detailed experimental investigations were carried out under zero and negative pressure gradient. The measurements were performed on an unsteady flow research facility using a rotating cascade of rods positioned upstream of the curved plate. Boundary layer measurements using a hot-wire probe were analyzed by the ensemble-averaging technique. The results presented in the temporal-spatial domain display the transition and further development of the boundary layer, specifically the ensemble-averaged velocity and turbulence intensity. As the results show, the turbulent patches generated by the wakes have different leading and trailing edge velocities and merge with the boundary layer resulting in a strong deformation and generation of a high turbulence intensity core. After the turbulent patch has totally penetrated into the boundary layer, pronounced becalmed regions were formed behind the turbulent patch and were extended far beyond the point they would occur in the corresponding undisturbed steady boundary layer.
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Funazaki, K., and Y. Aoyama. "Studies on Turbulence Structure of Boundary Layers Disturbed by Moving Wakes." In ASME Turbo Expo 2000: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/2000-gt-0272.
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An attempt is made to measure wake-affected boundary layers on a flat plate by means of a split-film probe. Although a number of studies have been made to reveal the transitional behavior of boundary layers subjected to periodic wake passing, much is still unknown on the turbulence structure of those boundary layers. It is because most of the studies measured the boundary layers by single hot-wire probe. This measurement therefore aims at the determination of the turbulent structure of the incoming wakes as well as the disturbed boundary layers mainly in terms of ensemble-averaged Reynolds shear stress and turbulence intensity. Unsteady velocity vectors associated with the wakes and wake-induced turbulence patch (a number of turbulent spots) are also determined in detail. In comparison to a conventional how-wire probe, the probe used in this study is less sensitive to fluctuations of high frequency and less accurate in the near-wall measurement due to its relatively large diameter of its sensor. However, new and important information is obtained on the structure of wake-induced turbulence patch, which provides more insight into the wake-induced boundary layer transition than before. In addition, the measured velocity field following the turbulent patch indicates a clear image of calmed region.
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Dell’Era, Giulia, Mehmet Mersinligil, and Jean-François Brouckaert. "Assessment of Unsteady Pressure Measurement Uncertainty: Part 1 — Single Sensor Probe." In ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/gt2015-42608.
Full textAbstract:
With the advancements in miniaturization and temperature capabilities of piezo-resistive pressure sensors, pneumatic probes — which are the long established standard for flow-path pressure measurements in gas turbine environments — are being replaced with unsteady pressure probes. Any measured quantity is by definition inherently different from the ‘true’ value, requiring the estimation of the associated errors for determining the validity of the results and establishing respective confidence intervals. In the context of pressure measurements, the calibration uncertainty values, which differ from measurement uncertainties, are typically provided. Even then, the lack of a standard methodology is evident as uncertainties are often reported without appropriate confidence intervals. Moreover, no time-resolved measurement uncertainty analysis has come to the attention of the authors. The objective of this paper is to present a standard method for the estimation of the uncertainties related to measurements performed using single sensor unsteady pressure probes, with the help of measurements obtained in a one and a half stage low pressure high speed axial compressor test rig as an example. The methodology presented is also valid for similar applications involving the use of steady or unsteady sensors and instruments. The static calibration uncertainty, steady measurement uncertainties and unsteady measurement uncertainties based on phase-locked and ensemble averages are presented in this contribution. Depending on the number of points used for the averaging, different values for uncertainty have been observed, underlining the importance of having greater number of samples. For unsteady flows, higher uncertainties have been observed at regions of higher unsteadiness such as tip leakage vortices, hub corner vortices and blade wakes. Unfortunately, the state of the art in single-sensor miniature unsteady pressure probes is comparable to multi-hole pneumatic probes in size, preventing the use of multi-hole unsteady probes in turbomachinery environments. However, the angular calibration properties of a single sensor probe obtained via an aerodynamic calibration may further be exploited as if a three-hole directional probe is employed, yielding corrected total pressure, unsteady yaw angle, static pressure and Mach number distributions based on the phase-locked averages with the expense of losing the time-correlation between the virtual ports. The aerodynamic calibration and derivation process are presented together with the assessment of the uncertainties associated to these derived quantities by the authors in [1]. In the virtual three-hole mode, similar to that of a single-sensor probe, higher uncertainty values are observed at regions of higher unsteadiness.
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Schobeiri, M. T., and B. O¨ztu¨rk. "Experimental Study of the Effect of Periodic Unsteady Wake Flow on Boundary Layer Development, Separation, and Re-Attachment Along the Surface of a Low Pressure Turbine Blade." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53929.
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The paper experimentally studies the effects of periodic unsteady wake flow on boundary layer development, separation and re-attachment along the suction surface of a low pressure turbine blade. The experimental investigations were performed on a large scale, subsonic unsteady turbine cascade research facility at Turbomachinery Performance and Flow Research Laboratory (TPFL), Texas A&M University. The experiments were carried out at a Reynolds number of 110,000 (based on suction surface length and exit velocity) with a free-stream turbulence intensity of 1.9%. One steady and two different unsteady inlet flow conditions with the corresponding passing frequencies, wake velocities, and turbulence intensities were investigated. The reduced frequencies cover the entire operating range of LP turbines. In addition to the unsteady boundary layer measurements, blade surface measurements were performed at the same Reynolds number. The surface pressure measurements were also carried out at one steady and two periodic unsteady inlet flow conditions. The results presented in ensemble-averaged, and the contour plot forms help to understand the physics of the separation phenomenon under periodic unsteady wake flow. It was found that the suction surface displayed a strong separation bubble for these three different reduced frequencies. For each condition, the locations and the heights defining the separation bubble were determined by carefully analyzing and examining the pressure and the mean velocity profile data. The location of boundary layer separation was independent of the reduced frequency level. However, the extent of the separation was strongly dependent on the reduced frequency level. Once the unsteady wake started to penetrate into the separation bubble, the turbulent spot produced in the wake paths caused a reduction of the separation bubble height.
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Stadtmüller, Peter, Leonhard Fottner, and Andreas Fiala. "Experimental and Numerical Investigation of Wake-Induced Transition on a Highly Loaded LP Turbine at Low Reynolds Numbers." In ASME Turbo Expo 2000: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/2000-gt-0269.
Full textAbstract:
Experimental and numerical results of LP turbine cascade tests performed to investigate wake interaction effects on boundary layer transition are presented. The data obtained at different inlet flow angles, turbulence levels and Mach numbers are compared and discussed with special focus on low Reynolds number conditions. For the boundary layer, calculated propagation velocities of disturbances are introduced to explain the transition process on the suction side of the blade over time. Using a moving bar wake generator and surface-mounted hot films as well as surface pressure tappings, the effects of periodic wake passing were studied in the High-Speed Cascade Wind Tunnel on the aft-loaded LPT profile T106. Blade pitch was increased as compared with design point conditions to achieve a higher blade loading. As a result, a large separation bubble formed on the suction side of the surface and allowed unsteady boundary layer development to be studied in great detail. Starting at a characteristic Reynolds number, massive separation occurred on the suction side under steady state conditions, i.e. the boundary layer was unable to reach the back pressure at the trailing edge. By using the wake generator, it was possible to reduce this separation and thus decrease profile pressure losses by 50%. The primary objective of the study was to provide unsteady ensemble-averaged hot film data together with information on the wake induced path, sufficient for the validation of numerical simulations. Such a simulation of the experiment was conducted using the Unsteady Boundary Layer Interaction Method, which takes into account the influence of boundary layer displacement on the velocity distribution and the time-dependent turbulence level in the outflow. The computations provide a good description of the wall shear stress in the transitional region and are in good agreement with the experimental data. By plotting propagation directions of boundary layer disturbances in space-time diagrams, it is shown that one characteristic direction is deviated around the so-called becalmed region and the temporarily separated region into the wake-induced transitional region.
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Dell’Era, Giulia, Mehmet Mersinligil, and Jean-François Brouckaert. "Assessment of Unsteady Pressure Measurement Uncertainty: Part 2 — Virtual Three Hole Probe." In ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/gt2015-42615.
Full textAbstract:
With the advancements in miniaturization and temperature capabilities of piezo-resistive pressure sensors, pneumatic probes — which are the long established standard for flow-path pressure measurements in gas turbine environments — are being replaced with unsteady pressure probes. On the other hand, any measured quantity is by definition inherently different from the ‘true’ value, requiring the estimation of the associated errors for determining the validity of the results and establishing respective confidence intervals. In the context of pressure measurements, the calibration uncertainty values, which differ from measurement uncertainties, are typically provided. Even then, the lack of a standard methodology is evident as uncertainties are often reported without appropriate confidence intervals. Moreover, no time-resolved measurement uncertainty analysis has come to the attention of the authors. The objective of this paper is to present a standard method for the estimation of the uncertainties related to measurements performed using single sensor unsteady pressure probes, with the help of measurements obtained in a one and a half stage low pressure high speed axial compressor test rig as an example. The methodology presented is also valid for similar applications involving the use of steady or unsteady sensors and instruments. The static calibration uncertainty, steady measurement uncertainties and unsteady measurement uncertainties based on phase-locked and ensemble averages are presented by the authors in [1]. Depending on the number of points used for the averaging, different values for uncertainty have been observed, underlining the importance of having greater number of samples. For unsteady flows, higher uncertainties have been observed at regions of higher unsteadiness such as tip leakage vortices, hub corner vortices and blade wakes. Unfortunately, the state of the art in single-sensor miniature unsteady pressure probes is comparable to multi-hole pneumatic probes in size, preventing the use of multi-hole unsteady probes in turbomachinery environments. However, the angular calibration properties of a single sensor probe obtained via an aerodynamic calibration may further be exploited as if a three-hole directional probe is employed, yielding corrected total pressure, unsteady yaw angle, static pressure and Mach number distributions based on the phase-locked averages with the expense of losing the time-correlation between the virtual ports. The aerodynamic calibration and derivation process are presented together with the assessment of the uncertainties associated to these derived quantities in this contribution. In the virtual three-hole mode, similar to that of a single-sensor probe, higher uncertainty values are observed at regions of higher unsteadiness.