Reconstruction by Data Assimilation of the Inner Temperature Field From Outer Measurement in Thick Pipe

2016 ◽  
Author(s):  
Jean-Philippe Argaud ◽  
Bertrand Bouriquet ◽  
Mathieu Courtois ◽  
Jean-Christophe Le Roux
Keyword(s):  
Temperature Field ◽  
Numerical Methods ◽  
Data Assimilation ◽  
Skin Temperature ◽  
Point Of View ◽  
Detailed Knowledge ◽  
Cooling Systems ◽  
Outer Skin ◽  
Thermal Transient ◽  
Thermal Shocks

The detailed knowledge of the inner skin temperature behavior is very important to evaluate and manage the aging of large pipes in cooling systems. We describe here a method to obtain this information as a function of outer skin temperature measurements, in space and time. This goal is achieved by mixing fine simulations and numerical methods such as impulse response and data assimilation. Demonstration is done on loads representing extreme transient stratification or thermal shocks. From a numerical point of view, the results of the reconstruction are outstanding, with a mean accuracy of the order of less than a half percent of the temperature value of the thermal transient.

scholarly journals NUMERICAL MODELING OF GAS TURBINE COOLED BLADES

Aviation ◽  
2005 ◽  
Vol 9 (3) ◽  
pp. 9-18
Author(s):  
Arif Pashayev ◽  
Djakhangir Askerov ◽  
Ramiz Ali Cabar oqlu Sadiqov
Keyword(s):  
Numerical Modeling ◽  
Temperature Field ◽  
Numerical Methods ◽  
Mathematical Models ◽  
Gas Turbine ◽  
Point Of View ◽  
Theoretical Substantiation ◽  
Stationary Temperature Field ◽  
Methods Of Calculation ◽  
Effective Combination

In contrast to methods that do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi‐stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A. Ziqmound continuity modules have been received.

Educational Model for the Kinematic Study of Non-Circular Gears

2013 ◽  
Vol 332 ◽  
pp. 297-304
Author(s):  
Liviu Ciupitu
Keyword(s):  
Numerical Methods ◽  
Industrial Applications ◽  
Point Of View ◽  
Spur Gears ◽  
Test Rig ◽  
Educational Model ◽  
Educational Test ◽  
Kinematic Study ◽  
Variation Curve ◽  
Noncircular Gears

The noncircular gears are used more and more in industrial applications. The paper presents an educational test rig for the kinematic study of non-circular gears. Two gears are studied from kinematic theoretically point of view: a gear with identically oval spur gears and another gear with identically elliptical spur gears, and simulation diagrams are presented. As for the testing rig, a gear with identically oval spur gears has been used. The researchers are able to draw with high precision the variation curve of output angle with respect to input angle. By using numerical methods for integration and differentiation other diagrams could be drawn and a comparation with simulation diagrams could be made.

Real-Time Monitoring of Skin Temperature Field Dynamics During Cryotherapy

Cryobiology ◽  
2021 ◽  
Vol 103 ◽  
pp. 201
Author(s):  
Gennadiy Kovalov ◽  
Galyna Shustakova ◽  
Eduard Gordiyenko ◽  
Yuliya Fomenko ◽  
Mykola Glushchuk
Keyword(s):  
Temperature Field ◽  
Skin Temperature ◽  
Real Time ◽  
Real Time Monitoring

Jointly learning variational data assimilation models and solvers for geophysical dynamics

2021 ◽  
Author(s):  
Ronan Fablet ◽  
Bertrand Chapron ◽  
Lucas Drumetz ◽  
Etienne Memin ◽  
Olivier Pannekoucke ◽  
...  
Keyword(s):  
Neural Networks ◽  
Data Assimilation ◽  
Inverse Problems ◽  
Automatic Differentiation ◽  
Variational Data Assimilation ◽  
Point Of View ◽  
Variational Model ◽  
Short Term ◽  
End To End ◽  
Short Term Forecasting

<p>This paper addresses representation learning for the resolution of inverse problems  with geophysical dynamics. Among others, examples of inverse problems of interest include space-time interpolation, short-term forecasting, conditional simulation w.r.t. available observations, downscaling problems… From a methodological point of view, we rely on a variational data assimilation framework. Data assimilation (DA) aims to reconstruct the time evolution of some state given a series of  observations, possibly noisy and irregularly-sampled. Here, we investigate DA from a machine learning point of view backed by an underlying variational representation.  Using automatic differentiation tools embedded in deep learning frameworks, we introduce end-to-end neural network architectures for variational data assimilation. It comprises two key components: a variational model and a gradient-based solver both implemented as neural networks. A key feature of the proposed end-to-end learning architecture is that we may train the neural networks models using both supervised and unsupervised strategies. We first illustrate applications to the reconstruction of Lorenz-63 and Lorenz-96 systems from partial and noisy observations. Whereas the gain issued from the supervised learning setting emphasizes the relevance of groundtruthed observation dataset for real-world case-studies, these results also suggest new means to design data assimilation models from data. Especially, they suggest that learning task-oriented representations of the underlying dynamics may be beneficial. We further discuss applications to short-term forecasting and sampling design along with preliminary results for the reconstruction of sea surface currents from satellite altimetry data. </p><p>This abstract is supported by a preprint available online: https://arxiv.org/abs/2007.12941</p>

scholarly journals Effects of skin heat conduction on aircraft icing process

2020 ◽  
pp. 095441002097257
Author(s):  
Xiaobin Shen ◽  
Yu Zeng ◽  
Guiping Lin ◽  
Zuodong Mu ◽  
Dongsheng Wen
Keyword(s):  
Heat Conduction ◽  
Temperature Distribution ◽  
Skin Temperature ◽  
Accretion Rate ◽  
Skin Surface ◽  
Ice Thickness ◽  
Ice Accretion ◽  
Aircraft Icing ◽  
Outer Skin ◽  
Lateral Heat

During the aircraft icing process caused by super-cooled droplet impingement, the surface temperature and heat flux distributions of the skin would vary due to the solid substrate heat conduction. An unsteady thermodynamic model of the phase transition was established with a time-implicit solution algorithm, in which the solid heat conduction and the water freezing were analyzed simultaneously. The icing process on a rectangular skin segment was numerically simulated, and the variations of skin temperature distribution, thicknesses of ice layer and water film were obtained. Results show that the presented model could predict the icing process more accurately, and is not sensitive to the selection of time step. The latent heat released by water freezing affects the skin temperature, which in turn changes the icing characteristics. The skin temperature distribution would be affected notably by the boundary condition of the inner skin surface, the lateral heat conduction and thermal property of the skin. It was found that the ice accretion rate of the case that the inner surface boundary is in natural convection at ambient temperature is much smaller than that with constant ambient temperature there; due to the skin lateral heat conduction, the outer skin surface temperature increases first and then decreases with uneven distribution, leading to an unsteady ice accretion rate and uneven ice thickness distribution; a smaller heat conductivity would lead to a more uneven temperature distribution and a lower ice accretion rate in most regions, but the maximum ice thickness could be larger than that of higher heat conductivity skin. Therefore, in order to predict the aircraft icing phenomenon more accurately, it is necessary to consider the solid heat conduction and the boundary conditions of the skin substrate, instead of applying a simple boundary condition of adiabatic or a fixed temperature for the outer skin surface.

scholarly journals Rapid Reconstruction of Simulated and Experimental Temperature Fields Based on Proper Orthogonal Decomposition

2020 ◽  
Vol 10 (11) ◽  
pp. 3729
Author(s):  
Minxin Chen ◽  
Shi Liu ◽  
Shanxun Sun ◽  
Zhaoyu Liu ◽  
Yu Zhao
Keyword(s):  
Temperature Field ◽  
Numerical Methods ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Orthogonal Decomposition ◽  
Reconstruction Method ◽  
Gas Combustion ◽  
Field Reconstruction ◽  
Proper Orthogonal ◽  
Temperature Field Reconstruction

Temperature information has a certain significance in thermal energy systems, especially in gas combustion systems. Generally, measurements and numerical calculations are used to acquire temperature information, but both of these approaches have their limitations. Constrained by cost and conditions, measurement methods are difficult to use to reconstruct the temperature field. Numerical methods are able to estimate the temperature field; however, the calculation process in numerical methods is very complex, so these methods cannot be used in real time. For the purpose of solving these problems, a two-dimensional temperature field reconstruction method based on the proper orthogonal decomposition (POD) algorithm is proposed in this study. In the proposed method, the temperature field reconstruction task is transformed into an optimization problem. Theoretical analysis and simulations show that the proposed method is feasible. Gas combustion experiments were also performed to validate this method. Results indicate that the proposed method can yield a reliable reconstruction solution and can be applied to real-time applications.

scholarly journals Towards understanding neural network signatures of motor skill learning in Parkinson’s disease and healthy aging

2019 ◽  
Vol 92 (1101) ◽  
pp. 20190071 ◽  
Author(s):  
Evelien Nackaerts ◽  
Nicholas D'Cruz ◽  
Bauke W Dijkstra ◽  
Moran Gilat ◽  
Thomas Kramer ◽  
...  
Keyword(s):  
Neural Network ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Learning ◽  
Healthy Aging ◽  
Network Connectivity ◽  
Cognitive Networks ◽  
Skill Learning ◽  
Point Of View ◽  
Detailed Knowledge

In the past decade, neurorehabilitation has been shown to be an effective therapeutic supplement for patients with Parkinson’s disease (PD). However, patients still experience severe problems with the consolidation of learned motor skills. Knowledge on the neural correlates underlying this process is thus essential to optimize rehabilitation for PD. This review investigates the existing studies on neural network connectivity changes in relation to motor learning in healthy aging and PD and critically evaluates the imaging methods used from a methodological point of view. The results indicate that despite neurodegeneration there is still potential to modify connectivity within and between motor and cognitive networks in response to motor training, although these alterations largely bypass the most affected regions in PD. However, so far training-related changes are inferred and possible relationships are not substantiated by brain–behavior correlations. Furthermore, the studies included suffer from many methodological drawbacks. This review also highlights the potential for using neural network measures as predictors for the response to rehabilitation, mainly based on work in young healthy adults. We speculate that future approaches, including graph theory and multimodal neuroimaging, may be more sensitive than brain activation patterns and model-based connectivity maps to capture the effects of motor learning. Overall, this review suggests that methodological developments in neuroimaging will eventually provide more detailed knowledge on how neural networks are modified by training, thereby paving the way for optimized neurorehabilitation for patients.

Hemihypoglossal-Facial Nerve Transfer: Technical Description and Key Points: 2-Dimensional Operative Video

2020 ◽  
Vol 20 (1) ◽  
pp. E53-E54
Author(s):  
Guido Caffaratti ◽  
Sebastián Juan María Giovannini ◽  
Daniel Orfila ◽  
Mariano Socolovsky
Keyword(s):  
Facial Nerve ◽  
Facial Palsy ◽  
High Speed ◽  
Hypoglossal Nerve ◽  
Nerve Transfer ◽  
Point Of View ◽  
Detailed Knowledge ◽  
Key Points ◽  
Psychological Point ◽  
Cervical Segment

ABSTRACT Irreversible facial palsy, generally post-traumatic or postsurgical, can have devastating consequences for the patient from a functional, aesthetic, and psychological point of view. Among all of the reconstructive techniques, the hemihypoglossal-facial nerve transfer, which avoids the complete section of the hypoglossal nerve, is preferred by senior authors because of its excellent results and very low morbidity.1-5 This technique can be carried out in any neurosurgical center because it requires only basic instruments of microsurgery and a high-speed drill. However, detailed knowledge of the anatomy of the facial nerve in both its intrapetrosal and extracranial segments and of the hypoglossal nerve in its cervical segment is essential.1,6,7 Thus, previous practice in a cadaveric laboratory is recommended. The purpose of this video is to describe the technical nuances and key points of hemihypoglossal-facial nerve transfer. It was made using the surgical videos of 5 patients with a complete and irreversible facial paralysis who were operated using this technique in our institution between May and September 2019, all of whom consented to the procedure and to use for scientific purposes. The footages were edited, making a film in which the surgical technique is described in a stepwise fashion, emphasizing its most important features. To conclude, we would like to emphasize that the timing of surgery is of utmost importance and that this technique is both effective and reliable. Figures in the video at 00:54 and 01:35 are reprinted by permission from CCC: Springer Nature, Acta Neurochirurgica, Treatment of complete facial palsy in adults: comparative study between direct hemihypoglossal-facial neurorrhaphy, hemihipoglossal-facial neurorrhaphy with grafts, and massater to facial nerve transfer. Socolovsky M, Martins RS, di Masi G, Bonilla G, Siqueira M, vol 158, 945-957, copyright 2016.

scholarly journals Ensemble Kalman Filtering with a Divided State-Space Strategy for Coupled Data Assimilation Problems*

2014 ◽  
Vol 142 (12) ◽  
pp. 4542-4558 ◽  
Author(s):  
Xiaodong Luo ◽  
Ibrahim Hoteit
Keyword(s):  
Data Assimilation ◽  
State Space ◽  
Point Of View ◽  
Coupled Systems ◽  
Current Status ◽  
Estimation Strategy ◽  
Coupled Subsystems ◽  
Coupled Data Assimilation ◽  
Augmented State ◽  
Lorenz 96

Abstract This study considers the data assimilation problem in coupled systems, which consists of two components (subsystems) interacting with each other through certain coupling terms. A straightforward way to tackle the assimilation problem in such systems is to concatenate the states of the subsystems into one augmented state vector, so that a standard ensemble Kalman filter (EnKF) can be directly applied. This work presents a divided state-space estimation strategy, in which data assimilation is carried out with respect to each individual subsystem, involving quantities from the subsystem itself and correlated quantities from other coupled subsystems. On top of the divided state-space estimation strategy, the authors also consider the possibility of running the subsystems separately. Combining these two ideas, a few variants of the EnKF are derived. The introduction of these variants is mainly inspired by the current status and challenges in coupled data assimilation problems and thus might be of interest from a practical point of view. Numerical experiments with a multiscale Lorenz 96 model are conducted to evaluate the performance of these variants against that of the conventional EnKF. In addition, specific for coupled data assimilation problems, two prototypes of extensions of the presented methods are also developed in order to achieve a trade-off between efficiency and accuracy.

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