Multiple-Relaxation-Time Lattice Boltzmann Approach to Compressible Flows with Flexible Specific-Heat Ratio and Prandtl Number

A new multiple-relaxation-time lattice Boltzmann scheme for compressible flows with arbitrary specific heat ratio and Prandtl number is presented. In the new scheme, which is based on a two-dimensional 16-discrete-velocity model, the moment space and the corresponding transformation matrix are constructed according to the seven-moment relations associated with the local equilibrium distribution function. In the continuum limit, the model recovers the compressible Navier-Stokes equations with flexible specific-heat ratio and Prandtl number. Numerical experiments show that compressible flows with strong shocks can be simulated by the present model up to Mach numbers $Ma \sim 5$.Comment: Accepted for publication in EP

Research on friction parameter identification under the influence of vibration and collision

Vibration and collision in the process of friction will cause large deviation of identification result with the actual situation. In this paper, friction process with the influence of vibration and collision as well as data collection of this process are implemented; to eliminate influence of vibration and collision in the aspect of the original data, sine filter is introduced into friction model according to the theory of Fourier series; ideas of simulated annealing is introduced into genetic algorithm to form hybrid algorithm, friction parameter can be identified combined with model and test data. The numerical results demonstrate the proposed method has effective identification results for friction process under the influence of the vibration and collision

Research on damping parameter identification of elastomer buffer

The object of this paper is the changing process of damping force as the falling weight impacting the elastomer buffer. The whole mechanical system is built up through practical test and simulation. According to the type of elastomer buffer and the experimental process in shock environment, velocity damping force identification model was established. Wavelet denoising and least square method were used for parameter identification of damping force. Considering the data saturation problem in the traditional least square method, the limited memory least square method was obtained to improve the identification method. The results of parameter identification of damping force based on limited memory method proved that the limited memory method was superior to least square method. The numerical results demonstrate the effectiveness of the identification model

Research on measuring method of large-caliber gun muzzle vibration

In this paper, a measuring system based on binocular vision is developed for the research on large-caliber gun muzzle vibration. The system is consisted of two high-speed cameras and other equipment. The two-step calibration method based on radial constraint is adopted in order to complete the calibration, the inter-frame differential multiplication method is used to detect the centroid of moving target accurately, the improved Kalman filter tracking algorithm is used to obtain the motion trajectory of the muzzle identification point. The system is applied to practice for a type of muzzle vibration measurement and meaningful original data is acquired

Experimental study on a certain elastomer buffer with dynamic identification method

The damping force of elastomer buffer in shock environment is the research object of this paper. The impact experiment and data simulation are used to understand the whole mechanical system. Equation with velocity and damping force is used for modeling according to the specific type of the elastomer buffer. The data of velocity and damping force is obtained by experimental data collection and pretreatment. Genetic algorithm is used to identify parameters according to the time invariant feature of traditional model. Through the results of parameter identification by genetic algorithm it seems that the parameters have the time-varying characteristics. Therefore, time-varying method is used for parameter identification. Limited memory method, which is obtained by the improvement of traditional least square method, is used for time-varying parameter identification. And the fitting accuracy of the identification results is better than that of genetic algorithm. The numerical results prove that the model is effective and parameters are time-varying

Une expérience vécue : l’intersection des langues, du genre et de l'identité dans la traduction

1 online resource (46 pages) : illustrationsIncludes abstract in English and French.Includes bibliographical references (pages 44-46).A saying goes that “to know another language is to possess a second soul.” Passionate about languages, translation and world cultures, the author is always on the way to learn more and decode the meaning of this quote. In this Honors essay, the author is going to explore the topic of gender and resistance in language translation based on her first experience as a translator. Working together with Dr. Bannerjee, Coupeuses d’Azur, an epic French anthology written by Mauritian poet Khal Torabully, is well translated. Based on this particular experience, the author first examines the inherent sexist components in the French language in its rules for grammatical gender, which influences French speakers' way of thinking. Furthermore, the author explores how translation practice, and the role of female translator may help change this current. Secondly, this thesis focuses particularly on the creole language and the musicality of poems in the process of translation from the postcolonial perspective. During the translation process, the author came across many intricacies and nuances, but that’s what made this journey so challenging and rewarding at the same time. To summarize the highlights of this unique learning path, she also depicts her own lived experience in translation

Prandtl number effects in MRT Lattice Boltzmann models for shocked and unshocked compressible fluids

For compressible fluids under shock wave reaction, we have proposed two Multiple-Relaxation-Time (MRT) Lattice Boltzmann (LB) models [F. Chen, et al, EPL \textbf{90} (2010) 54003; Phys. Lett. A \textbf{375} (2011) 2129.]. In this paper, we construct a new MRT Lattice Boltzmann model which is not only for the shocked compressible fluids, but also for the unshocked compressible fluids. To make the model work for unshocked compressible fluids, a key step is to modify the collision operators of energy flux so that the viscous coefficient in momentum equation is consistent with that in energy equation even in the unshocked system. The unnecessity of the modification for systems under strong shock is analyzed. The model is validated by some well-known benchmark tests, including (i) thermal Couette flow, (ii) Riemann problem, (iii) Richtmyer-Meshkov instability. The first system is unshocked and the latter two are shocked. In all the three systems, the Prandtl numbers effects are checked. Satisfying agreements are obtained between new model results and analytical ones or other numerical results.Comment: 17 pages, 8 figure

Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph Generation

This paper investigates the problem of scene graph generation in videos with the aim of capturing semantic relations between subjects and objects in the form of $\langle$subject, predicate, object$\rangle$ triplets. Recognizing the predicate between subject and object pairs is imbalanced and multi-label in nature, ranging from ubiquitous interactions such as spatial relationships (\eg \emph{in front of}) to rare interactions such as \emph{twisting}. In widely-used benchmarks such as Action Genome and VidOR, the imbalance ratio between the most and least frequent predicates reaches 3,218 and 3,408, respectively, surpassing even benchmarks specifically designed for long-tailed recognition. Due to the long-tailed distributions and label co-occurrences, recent state-of-the-art methods predominantly focus on the most frequently occurring predicate classes, ignoring those in the long tail. In this paper, we analyze the limitations of current approaches for scene graph generation in videos and identify a one-to-one correspondence between predicate frequency and recall performance. To make the step towards unbiased scene graph generation in videos, we introduce a multi-label meta-learning framework to deal with the biased predicate distribution. Our meta-learning framework learns a meta-weight network for each training sample over all possible label losses. We evaluate our approach on the Action Genome and VidOR benchmarks by building upon two current state-of-the-art methods for each benchmark. The experiments demonstrate that the multi-label meta-weight network improves the performance for predicates in the long tail without compromising performance for head classes, resulting in better overall performance and favorable generalizability. Code: \url{https://github.com/shanshuo/ML-MWN}.Comment: ICMR 202