Experimental validation of a lower-order model for leading-edge noise based on vortex method

2021 ◽  
Author(s):  
Sparsh Sharma ◽  
Thomas F. Geyer ◽  
Ennes Sarradj ◽  
Heiko Schmidt
Keyword(s):  
Lower Order ◽  
Experimental Validation ◽  
Leading Edge ◽  
Vortex Method ◽  
Order Model

scholarly journals Measurement invariance of the distress tolerance scale among university students with and without a history of non-suicidal self-injury

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10915
Author(s):  
Ashley Slabbert ◽  
Penelope Hasking ◽  
Danyelle Greene ◽  
Mark Boyes
Keyword(s):  
University Students ◽  
Measurement Invariance ◽  
Lower Order ◽  
Distress Tolerance ◽  
Factor Model ◽  
Higher Order ◽  
Order Model ◽  
Self Injury ◽  
History Of ◽  
Order Four

Non-suicidal self-injury (NSSI) is the intentional damage to one’s body tissue in the absence of suicidal intent. NSSI primarily serves an emotion regulation function, with individuals engaging in self-injury to escape intense or unwanted emotion. Low distress tolerance has been identified as a mechanism that underlies self-injury, and is commonly assessed using the self-report Distress Tolerance Scale. There are mixed findings regarding the factor structure of the Distress Tolerance Scale, with some researchers utilising a higher-order distress tolerance score (derived from the scores on the four lower-order subscales) and other researchers using the four subscales as unique predictors of psychological outcomes. Neither of these factor structures have been assessed among individuals with a history of self-injury. Of note, an inability to tolerate distress (thought to underlie NSSI) may limit an individual’s capacity to accurately observe and report specific thoughts and emotions experienced in a state of heightened distress, which may impact the validity of scores on the Distress Tolerance Scale. Therefore, measurement invariance should be established before attributing NSSI-related differences on the scale to true differences in distress tolerance. We compared the Distress Tolerance Scale higher-order model with the lower-order four factor model among university students with and without a history of NSSI. Our results indicated that the lower-order four factor model was a significantly better fit to the data than the higher-order model. We then tested the measurement invariance of this lower-order factor model among individuals with and without a history of NSSI, and established configural and full metric invariance, followed by partial scalar and full residual error invariance. These results suggest the four subscales of the Distress Tolerance Scale can be used to confidently discern NSSI-related differences in distress tolerance.

Experimental Validation of Neural-Network-Based Nonlinear Reduced-Order Model for Vertical Sloshing

2022 ◽  
Author(s):  
Marco Pizzoli ◽  
Francesco Saltari ◽  
Giuliano Coppotelli ◽  
Franco Mastroddi
Keyword(s):  
Neural Network ◽  
Experimental Validation ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order

scholarly journals Nonlinear reduced order model of high aspect ratio rectangular wing plate

2018 ◽  
Vol 7 (4.13) ◽  
pp. 195-201
Author(s):  
Thinesh C ◽  
M Y Harmin
Keyword(s):  
Leading Edge ◽  
Reduced Order Model ◽  
Computational Time ◽  
Plate Model ◽  
Order Model ◽  
Reduced Order ◽  
Nonlinear Properties ◽  
First Case ◽  
Trailing Edges ◽  
Nonlinear Deformations

This paper presents a Combined Modal Finite Element (CMFE) approach to develop a Nonlinear Reduced Order Model (NROM) in order to characterize the nonlinear properties of the wing plate model. The wing plate model is subjected to three types of loading cases. The first case considers a uniformly distributed loading on the whole wing plate model for describing the bending deflection; the second case considers a uniformly distributed loading on both leading and trailing edges with one of them of an opposite direction for describing the twisting deflection; the third case considers the loading on the leading edge for describing a combination of bending-twisting deflection. The accuracy of the results is represented in the form of mean error, the standard deviation of the error and the percentage of error. From the findings, the NROMs are able to predict the nonlinear deformations of the wing plate with a minimal computational time and reasonably good accuracy. The results also indicate the importance of the selection modes when conducting the analysis.  

scholarly journals Construction of reduced-order models for fluid flows using deep feedforward neural networks

2019 ◽  
Vol 872 ◽  
pp. 963-994 ◽  
Author(s):  
Hugo F. S. Lui ◽  
William R. Wolf
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Fluid Flows ◽  
Leading Edge ◽  
Feedforward Neural Networks ◽  
Orthogonal Decomposition ◽  
Reduced Order Models ◽  
Order Model ◽  
Sparse Regression ◽  
Reduced Order ◽  
Proper Orthogonal

We present a numerical methodology for construction of reduced-order models (ROMs) of fluid flows through the combination of flow modal decomposition and regression analysis. Spectral proper orthogonal decomposition is applied to reduce the dimensionality of the model and, at the same time, filter the proper orthogonal decomposition temporal modes. The regression step is performed by a deep feedforward neural network (DNN), and the current framework is implemented in a context similar to the sparse identification of nonlinear dynamics algorithm. A discussion on the optimization of the DNN hyperparameters is provided for obtaining the best ROMs and an assessment of these models is presented for a canonical nonlinear oscillator and the compressible flow past a cylinder. Then the method is tested on the reconstruction of a turbulent flow computed by a large eddy simulation of a plunging airfoil under dynamic stall. The reduced-order model is able to capture the dynamics of the leading edge stall vortex and the subsequent trailing edge vortex. For the cases analysed, the numerical framework allows the prediction of the flow field beyond the training window using larger time increments than those employed by the full-order model. We also demonstrate the robustness of the current ROMs constructed via DNNs through a comparison with sparse regression. The DNN approach is able to learn transient features of the flow and presents more accurate and stable long-term predictions compared to sparse regression.

J0501-2-3 Experimental Validation of CFD Analyses of Showerhead Cooling on a Blade Leading Edge Model

2009 ◽  
Vol 2009.7 (0) ◽  
pp. 15-16
Author(s):  
Toshihiko TAKAHASHI ◽  
Ken-ichi FUNAZAKI ◽  
Bin Salleh Hamidon ◽  
Eiji SAKAI ◽  
Kazunori WATANABE
Keyword(s):  
Experimental Validation ◽  
Leading Edge ◽  
Cfd Analyses ◽  
Blade Leading Edge

Scaling of detonation velocity in cylinder and slab geometries for ideal, insensitive and non-ideal explosives

2015 ◽  
Vol 773 ◽  
pp. 224-266 ◽  
Author(s):  
Scott I. Jackson ◽  
Mark Short
Keyword(s):  
Phase Velocity ◽  
Detonation Velocity ◽  
Lower Order ◽  
Higher Order ◽  
Slab Thickness ◽  
Two Dimensional ◽  
Order Model ◽  
Scaling Behaviour ◽  
Geometric Scaling ◽  
Shock Curvature

Experiments were conducted to characterize the detonation phase-velocity dependence on charge thickness for two-dimensional detonation in condensed-phase explosive slabs of PBX 9501, PBX 9502 and ANFO. In combination with previous diameter-effect measurements from a cylindrical rate-stick geometry, these data permit examination of the relative scaling of detonation phase velocity between axisymmetric and two-dimensional detonation. We find that the ratio of cylinder radius ($R$) to slab thickness ($T$) at each detonation phase velocity ($D_{0}$) is such that $R(D_{0})/T(D_{0})<1$. The variation in the $R(D_{0})/T(D_{0})$ scaling is investigated with two detonation shock dynamics (DSD) models: a lower-order model relates the normal detonation velocity to local shock curvature, while a higher-order model includes the effect of front acceleration and transverse flow. The experimentally observed $R(D_{0})/T(D_{0})$ (${<}1$) scaling behaviour for PBX 9501 and PBX 9502 is captured by the lower-order DSD theory, revealing that the variation in the scale factor is due to a difference in the slab and axisymmetric components of the curvature along the shock in the cylindrical geometry. The higher-order DSD theory is required to capture the observed $R(D_{0})/T(D_{0})$ (${<}1$) scaling behaviour for ANFO. An asymptotic analysis of the lower-order DSD formulation describes the geometric scaling of the detonation phase velocity between the cylinder and slab geometries as the detonation phase velocity approaches the Chapman–Jouguet value.

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