Temperature Field
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2021 ◽  
Vol 169 ◽  
pp. 108416
Michał Malendowski ◽  
Wojciech Szymkuć ◽  
Piotr Turkowski ◽  
Adam Glema ◽  
Wojciech Węgrzyński

2021 ◽  
Vol 4 (1) ◽  
Pei-Chao Cao ◽  
Ying Li ◽  
Yu-Gui Peng ◽  
Minghong Qi ◽  
Wen-Xi Huang ◽  

AbstractNon-Hermitian wave system has attracted intense attentions in the past decade since it reveals interesting physics and generates various counterintuitive effects. However, in the diffusive system that is inherently non-Hermitian with natural dissipation, the robust control of heat flow is hitherto still a challenge. Here we introduce the skin effect into diffusive systems. Different from the skin effect in wave systems, where asymmetric couplings were enabled by dynamic modulations or judicious gain/loss engineering, asymmetric couplings of the temperature fields in diffusive systems can be realized by directly contacted metamaterial channels. Topological heat funneling is further presented, where the temperature field automatically concentrates towards a designated position and shows a strong immunity against the defects. Our work indicates that the diffusive system can provide a distinctive platform for exploring non-Hermitian physics as well as thermal topology.

Berend Denkena ◽  
Carsten Schmidt ◽  
Marc Timmermann ◽  
Andreas Friedel

AbstractThis paper presents a novel method for a precise localization of the automated-fiber-placement head, without the need for a data access to the machine control. It is based on a sub-pixel accurate optical-flow-algorithm which determines information about the heads movement by means of the material flow in sequences of IR images. Using local curvatures in the temperature field of the IR images, feature matrices are created which can locally be compared to the features of successive images. Thus, the translation between images become visible. This enables the possibility to perform an accurate ($$16.8\,\upmu{\mathrm{m}}$$ 16.8 μ m ) and self-sufficient process monitoring that additionally is capable of capturing the motion and position information of the AFP system and can be linked to existing algorithms for defect detection and classification.

Shaolin Chen ◽  
Hong Zhang ◽  
Liaoping Hu ◽  
Guangqing He ◽  
Fen Lei ◽  

The fatigue life of turbine housing is an important index to measure the reliability of a radial turbocharger. The increase in turbine inlet temperatures in the last few years has resulted in a decrease in the fatigue life of turbine housing. A simulation method and experimental verification are required to predict the life of a turbine housing in the early design and development process precisely. The temperature field distribution of the turbine housing is calculated using the steady-state bidirectional coupled conjugate heat transfer method. Next, the temperature field results are considered as the boundary for calculating the turbine housing temperature and thermomechanical strain, and then, the thermomechanical strain of the turbine housing is determined. Infrared and digital image correlations are used to measure the turbine housing surface temperature and total thermomechanical strain. Compared to the numerical solution, the maximum temperature RMS (Root Mean Square) error of the monitoring point in the monitoring area is only 3.5%; the maximum strain RMS error reached 11%. Experimental results of temperature field test and strain measurement test show that the testing temperature and total strain results are approximately equal to the solution of the numerical simulation. Based on the comparison between the numerical calculation and experimental results, the numerical simulation and test results were found to be in good agreement. The experimental and simulation results of this method can be used as the temperature and strain (stress) boundaries for subsequent thermomechanical fatigue (TMF) simulation analysis of the turbine housing.

2021 ◽  
Vol 11 (20) ◽  
pp. 9435
Ning Wang ◽  
Jiajia Chen ◽  
Huifang Wang ◽  
Shiyou Yang

In simulations of three-dimensional transient physics filled through a numerical approach, the order of the equation set of high-fidelity models is extremely high. To eliminate the large dimension of equations, a model order reduction (MOR) technique is introduced. In the existing MOR methods, the block Arnoldi algorithm-based MOR method is numerically stable, achieving a passively reduced order model. Nevertheless, this method performs poorly when it is applied to very wide-frequency transients. To eliminate this deficiency, multipoint MOR methods are emerging. However, it is hard to directly apply an existing multipoint MOR method to a 3-D transient field equation set. The implementation issues in a reduction process (such as the selection of expansion points, the number of moments matched at a point and the error bound) have not been explored in detail. In this respect, an adaptive multipoint model reduction model based on the Arnoldi algorithm is proposed to obtain the reduced-order models of a 3-D temperature field. The originality of this study is the proposal of a novel adaptive algorithm for selecting expansion points, matching moments automatically, using a posterior-error estimator based on temperature response coupled with a network topological method (NTM). The computational efficiency and accuracy of the proposed method are evaluated by the numerical results from solving the temperature field of a prototype insulated-gate bipolar transistor (IGBT).

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