Prediction of Cavitation Erosion: An Energy Approach

1998 ◽  
Vol 120 (4) ◽  
pp. 719-727 ◽  
Author(s):  
F. Pereira ◽  
F. Avellan ◽  
Ph. Dupont
Keyword(s):  
Energy Spectrum ◽  
Prediction Model ◽  
Cavitation Erosion ◽  
Threshold Energy ◽  
Leading Edge ◽  
Generation Process ◽  
Efficiency Coefficient ◽  
Volume Data ◽  
Vapor Cavity ◽  
Wide Range

The objective is to define a prediction and transposition model for cavitation erosion. Experiments were conducted to determine the energy spectrum associated with a leading edge cavitation. Two fundamental parameters have been measured on a symmetrical hydrofoil for a wide range of flow conditions: the volume of every transient vapor cavity and its respective rate of production. The generation process of transient vapor cavities is ruled by a Strouhal-like law related to the cavity size. The analysis of the vapor volume data demonstrated that vapor vortices can be assimilated to spherical cavities. Results are valid for both the steady and unsteady cavitation behaviors, this latter being peculiar besides due to the existence of distinct volumes produced at specific shedding rates. The fluid energy spectrum is formulated and related to the flow parameters. Comparison with the material deformation energy spectrum shows a remarkable proportionality relationship defined upon the collapse efficiency coefficient. The erosive power term, formerly suggested as the ground component of the prediction model, is derived taking into account the damaging threshold energy of the material. An erosive efficiency coefficient is introduced on this basis that allows to quantify the erosive potential of a cavitation situation for a given material. A formula for localization of erosion is proposed that completes the prediction model. Finally, a procedure is described for geometrical scale and flow velocity transpositions.

scholarly journals BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2144
Author(s):  
Stefan Reitmann ◽  
Lorenzo Neumann ◽  
Bernhard Jung
Keyword(s):  
Point Clouds ◽  
Training Data ◽  
Sensor Data ◽  
Generation Process ◽  
Data Generation ◽  
Depth Sensor ◽  
Depth Sensing ◽  
Depth Sensors ◽  
3D Point Clouds ◽  
Wide Range

Common Machine-Learning (ML) approaches for scene classification require a large amount of training data. However, for classification of depth sensor data, in contrast to image data, relatively few databases are publicly available and manual generation of semantically labeled 3D point clouds is an even more time-consuming task. To simplify the training data generation process for a wide range of domains, we have developed the BLAINDER add-on package for the open-source 3D modeling software Blender, which enables a largely automated generation of semantically annotated point-cloud data in virtual 3D environments. In this paper, we focus on classical depth-sensing techniques Light Detection and Ranging (LiDAR) and Sound Navigation and Ranging (Sonar). Within the BLAINDER add-on, different depth sensors can be loaded from presets, customized sensors can be implemented and different environmental conditions (e.g., influence of rain, dust) can be simulated. The semantically labeled data can be exported to various 2D and 3D formats and are thus optimized for different ML applications and visualizations. In addition, semantically labeled images can be exported using the rendering functionalities of Blender.

Experimental Studies of Leading Edge Contouring Influence on Secondary Losses in Transonic Turbines

2012 ◽  
Author(s):  
Ranjan Saha ◽  
Jens Fridh ◽  
Torsten Fransson ◽  
Boris I. Mamaev ◽  
Mats Annerfeldt
Keyword(s):  
Gas Turbine ◽  
Guide Vane ◽  
Experimental Studies ◽  
Three Dimensional ◽  
Leading Edge ◽  
Secondary Flows ◽  
Noticeable Effect ◽  
Flow Angle ◽  
Wide Range ◽  
Contour Plots

An experimental study of the hub leading edge contouring using fillets is performed in an annular sector cascade to observe the influence of secondary flows and aerodynamic losses. The investigated vane is a three dimensional gas turbine guide vane (geometrically similar) with a mid-span aspect ratio of 0.46. The measurements are carried out on the leading edge fillet and baseline cases using pneumatic probes. Significant precautions have been taken to increase the accuracy of the measurements. The investigations are performed for a wide range of operating exit Mach numbers from 0.5 to 0.9 at a design inlet flow angle of 90°. Data presented include the loading, fields of total pressures, exit flow angles, radial flow angles, as well as profile and secondary losses. The vane has a small profile loss of approximately 2.5% and secondary loss of about 1.1%. Contour plots of vorticity distributions and velocity vectors indicate there is a small influence of the vortex-structure in endwall regions when the leading edge fillet is used. Compared to the baseline case the loss for the filleted case is lower up to 13% of span and higher from 13% to 20% of the span for a reference condition with Mach no. of 0.9. For the filleted case, there is a small increase of turning up to 15% of the span and then a small decrease up to 35% of the span. Hence, there are no significant influences on the losses and turning for the filleted case. Results lead to the conclusion that one cannot expect a noticeable effect of leading edge contouring on the aerodynamic efficiency for the investigated 1st stage vane of a modern gas turbine.

scholarly journals Automatic Design System with Generative Adversarial Network and Convolutional Neural Network for Optimization Design of Interior Permanent Magnet Synchronous Motor

2021 ◽  
Author(s):  
Yuki Shimizu ◽  
Shigeo Morimoto ◽  
Masayuki Sanada ◽  
Yukinori Inoue
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Convolutional Neural Network ◽  
Permanent Magnet ◽  
Optimization Design ◽  
Design System ◽  
Automatic Design ◽  
Wide Range ◽  
Interior Permanent Magnet ◽  
Long Time

The optimal design of interior permanent magnet synchronous motors requires a long time because finite element analysis (FEA) is performed repeatedly. To solve this problem, many researchers have used artificial intelligence to construct a prediction model that can replace FEA. However, because the training data are generated by FEA, it takes a very long time to obtain a sufficient amount of data, making it impossible to train a large-scale prediction model. Here, we propose a method for generating a large amount of data from a small number of FEA results using machine learning. An automatic design system with a deep generative model and a convolutional neural network is then constructed. With its sufficient data, the proposed system can handle three topologies and three motor parameters in a wide range of current vector regions. The proposed system was applied to multi-objective optimization design, with the optimization completed in 13-15 seconds.

scholarly journals Analysis and Prediction of Crash Fatalities in Australia

2019 ◽  
Vol 13 (1) ◽  
pp. 134-140 ◽  
Author(s):  
Fady M.A Hassouna ◽  
Ian Pringle
Keyword(s):  
Prediction Model ◽  
Cause Of Death ◽  
Moving Average ◽  
Economic Losses ◽  
Road Accidents ◽  
Process Data ◽  
Effective Strategies ◽  
Road Users ◽  
Wide Range ◽  
Strategy Design

Introduction: As fatalities, injuries, and economic losses from road accidents are a major concern for governments and their citizens, Australia, like other countries, has designed and implemented a wide range of strategies to reduce the rate of road accidents. Methods: As part of the strategy design process, data on crash deaths were collected and then analyzed to develop more effective strategies. The data of crash deaths in Australia during the years 1965 to 2018 were analyzed based on gender, causes of crash deaths, and type of road users, and then the results were compared with global averages, then a prediction model was developed to forecast the future annual crash fatalities. Results: The results indicate that, based on gender, the rate of male road fatalities in Australia was significantly higher than that of female road fatalities. Whereas based on the cause of death, the first cause of death was over speeding. Based on the type of road users, the drivers and passengers of 4-wheel vehicles had the highest rate of fatalities. Conclusion: The prediction model was developed based on Autoregressive Integrated Moving Average (ARIMA) methodology, and annual road fatalities in Australia for the next five years 2019-2022 have been forecast using this model.

scholarly journals Automatic Design System with Generative Adversarial Network and Convolutional Neural Network for Optimization Design of Interior Permanent Magnet Synchronous Motor

2021 ◽  
Author(s):  
Yuki Shimizu ◽  
Shigeo Morimoto ◽  
Masayuki Sanada ◽  
Yukinori Inoue
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Convolutional Neural Network ◽  
Permanent Magnet ◽  
Optimization Design ◽  
Design System ◽  
Automatic Design ◽  
Wide Range ◽  
Interior Permanent Magnet ◽  
Long Time

The optimal design of interior permanent magnet synchronous motors requires a long time because finite element analysis (FEA) is performed repeatedly. To solve this problem, many researchers have used artificial intelligence to construct a prediction model that can replace FEA. However, because the training data are generated by FEA, it takes a very long time to obtain a sufficient amount of data, making it impossible to train a large-scale prediction model. Here, we propose a method for generating a large amount of data from a small number of FEA results using machine learning. An automatic design system with a deep generative model and a convolutional neural network is then constructed. With its sufficient data, the proposed system can handle three topologies and three motor parameters in a wide range of current vector regions. The proposed system was applied to multi-objective optimization design, with the optimization completed in 13-15 seconds.

Influence of Pre-History and Leading Edge Contouring on Aero-Performance of a 3D Nozzle Guide Vane

2013 ◽  
Author(s):  
Ranjan Saha ◽  
Boris I. Mamaev ◽  
Jens Fridh ◽  
Björn Laumert ◽  
Torsten H. Fransson
Keyword(s):  
Guide Vane ◽  
Three Dimensional ◽  
Leading Edge ◽  
Stagnation Line ◽  
Wide Range ◽  
Nozzle Guide Vane ◽  
Turbine Vane ◽  
Loss Coefficients ◽  
Exit Mach Number ◽  
Nozzle Guide

Experiments are conducted to investigate the effect of the pre-history in the aerodynamic performance of a three-dimensional nozzle guide vane with a hub leading edge contouring. The performance is determined with two pneumatic probes (5 hole and 3 hole) concentrating mainly on the endwall. The investigated vane is a geometrically similar gas turbine vane for the first stage with a reference exit Mach number of 0.9. Results are compared for the baseline and filleted cases for a wide range of operating exit Mach numbers from 0.5 to 0.9. The presented data includes loading distributions, loss distributions, fields of exit flow angles, velocity vector and vorticity contour, as well as, mass-averaged loss coefficients. The results show an insignificant influence of the leading edge fillet on the performance of the vane. However, the pre-history (inlet condition) affects significantly in the secondary loss. Additionally, an oil visualization technique yields information about the streamlines on the solid vane surface which allows identifying the locations of secondary flow vortices, stagnation line and saddle point.

Improved compensation for a reduction stepper to meet the challenges for advanced packaging applications

2013 ◽  
Vol 2013 (1) ◽  
pp. 000814-000819 ◽  
Author(s):  
James E Webb ◽  
Steven Gardner ◽  
Elvino DaSilveira
Keyword(s):  
Leading Edge ◽  
Image Features ◽  
Wafer Level ◽  
Projection Lens ◽  
Wafer Level Packaging ◽  
Alignment System ◽  
Wide Range ◽  
Advanced Packaging ◽  
Volume Production ◽  
Mix And Match

Advanced packaging manufacturers require steppers that will provide solutions for the challenges encountered with new advances in wafer-level packaging technologies such as TSV, eWLB, silicon and glass interposers being utilized in leading edge mobile devices. Step and repeat photolithography systems capable of finer imaging with tighter overlay are being introduced to meet the challenging manufacturing requirements associated with the mix and match needed for volume production on larger wafers. A 2X reduction stepper with unique features incorporated that extend the range of compensation is necessary to achieve the tighter specifications needed for many advanced packaging applications printed on 300 to 450mm wafers. A high throughput projection optical system is used to expose circuit patterns from a reticle mask onto a substrate to image features with the optimal fidelity required for advanced packaging technologies. The camera incorporates 350–450nm light from a mercury arc lamp that is transmitted through the mask containing circuit patterns. The imaging field prints a large 52mm × 66mm area in a single exposure. These features enable a system to process wafers in fewer shots which result in higher throughput using lower power. Substrates are positioned with a precise X, Y, Θ stage by locating marks using an off-axis, bright field alignment system with fully trainable mark feature capability. The approach results in precisely placed features within a layer and from layer to layer without directly referencing the reticle. The integrated metrology and precision positioning subsystem technologies are combined with a low distortion projection lens and a wide range of adjustments, allowing the stepper to be integrated into a production line in a mix and match setup with other lithography systems. This equipment can be used to image critical layers on substrates while ensuring grid registration and alignment with other lithography systems that are also printing images in the same process line. Several important global and intra-field image placement relationships for devices requiring multiple layer patterning have been combined in the stepper matching correction software. Further adjustment to the tool can be made to improve overlay when incorporated with fab-wide yield management software for automated, real-time process control. The types of adjustments needed and techniques that can be applied to compensate for image placement errors over large areas are discussed.

scholarly journals Numerical Study of Sediment Erosion Analysis in Francis Turbine

2019 ◽  
Vol 11 (5) ◽  
pp. 1423 ◽  
Author(s):  
Md Rakibuzzaman ◽  
Hyoung-Ho Kim ◽  
Kyungwuk Kim ◽  
Sang-Ho Suh ◽  
Kyung Kim
Keyword(s):  
Erosion Rate ◽  
Cavitation Erosion ◽  
Numerical Study ◽  
Leading Edge ◽  
Suction Side ◽  
Hydraulic Turbine ◽  
Francis Turbine ◽  
Trailing Edge ◽  
Sand Erosion ◽  
Turbine Design

Effective hydraulic turbine design prevents sediment and cavitation erosion from impacting the performance and reliability of the machine. Using computational fluid dynamics (CFD) techniques, this study investigated the performance characteristics of sediment and cavitation erosion on a hydraulic Francis turbine by ANSYS-CFX software. For the erosion rate calculation, the particle trajectory Tabakoff–Grant erosion model was used. To predict the cavitation characteristics, the study’s source term for interphase mass transfer was the Rayleigh–Plesset cavitation model. The experimental data acquired by this study were used to validate the existing evaluations of the Francis turbine. Hydraulic results revealed that the maximum difference was only 0.958% compared with the CFD data, and 0.547% compared with the experiment (Korea Institute of Machinery and Materials (KIMM)). The turbine blade region was affected by the erosion rate at the trailing edge because of their high velocity. Furthermore, in the cavitation–erosion simulation, it was observed that abrasion propagation began from the pressure side of the leading edge and continued along to the trailing edge of the runner. Additionally, as sediment flow rates grew within the area of the attached cavitation, they increased from the trailing edge at the suction side, and efficiency was reduced. Cavitation–sand erosion results then revealed a higher erosion rate than of those of the sand erosion condition.

Recent progress in flapping wings for micro aerial vehicle applications

2020 ◽  
pp. 095440622091742
Author(s):  
Naeem Haider ◽  
Aamer Shahzad ◽  
Muhammad Nafees Mumtaz Qadri ◽  
Syed Irtiza Ali Shah
Keyword(s):  
Leading Edge ◽  
Flapping Wing ◽  
Flapping Wings ◽  
Structural Flexibility ◽  
Micro Aerial Vehicles ◽  
Flexible Wings ◽  
Performance Variables ◽  
Aerial Vehicles ◽  
Wide Range ◽  
Wing Geometry

Micro aerial vehicles using flapping wings are under investigation, as an alternative to fixed-wing and rotary-wing micro aerial vehicles. Such flapping-wing vehicles promise key potential advantages of high thrust, agility, and maneuverability, and have a wide range of applications. These applications include both military and commercial domains such as communication relay, search and rescue, visual reconnaissance, and field search. With the advancement in the computational sciences, developments in flapping-wing micro aerial vehicles have progressed exponentially. Such developments require a careful aerodynamic and aeroelastic design of the flapping wing. Therefore, aerodynamic tools are required to study such designs and configurations. In this paper, the role of several parameters is investigated, including the types of flapping wings, the effect of the kinematics and wing geometry (shape, configuration, and structural flexibility) on performance variables such as lift, drag, thrust, and efficiency in various modes of flight. Kinematic variables have a significant effect on the performance of the flapping wing. For instance, a high flap amplitude and pitch rotation, which supports the generation of the strong leading-edge vortex, generates higher thrust. Likewise, wing shape, configuration, and structural flexibility are shown to have a large impact on the performance of the flapping wing. The wing with optimum flexibility maximizes thrust where highly flexible wings lead to performance degradation due to change in the effective angle of attack. This study shows that the development of the flexible flapping wing with performance capabilities similar to those of natural fliers has not yet been achieved. Finally, opportunities for additional research in this field are recommended.

scholarly journals A Statistical Vertically Mixed Runoff Model for Regions Featured by Complex Runoff Generation Process

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2324
Author(s):  
Peng Lin ◽  
Pengfei Shi ◽  
Tao Yang ◽  
Chong-Yu Xu ◽  
Zhenya Li ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Mixed Model ◽  
Soil Surface ◽  
Extreme Rainfall ◽  
Distributed Model ◽  
Generation Process ◽  
Efficiency Coefficient ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Runoff Model

Hydrological models for regions characterized by complex runoff generation process been suffer from a great weakness. A delicate hydrological balance triggered by prolonged wet or dry underlying condition and variable extreme rainfall makes the rainfall-runoff process difficult to simulate with traditional models. To this end, this study develops a novel vertically mixed model for complex runoff estimation that considers both the runoff generation in excess of infiltration at soil surface and that on excess of storage capacity at subsurface. Different from traditional models, the model is first coupled through a statistical approach proposed in this study, which considers the spatial heterogeneity of water transport and runoff generation. The model has the advantage of distributed model to describe spatial heterogeneity and the merits of lumped conceptual model to conveniently and accurately forecast flood. The model is tested through comparison with other four models in three catchments in China. The Nash–Sutcliffe efficiency coefficient and the ratio of qualified results increase obviously. Results show that the model performs well in simulating various floods, providing a beneficial means to simulate floods in regions with complex runoff generation process.

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