Vibroacoustic response of structures and perturbation Reynolds stress near structure-turbulence interface

The interaction between a turbulent flow and certain types of structures which respond to its excitation is investigated. One-dimensional models were used to develop the basic ideas applied to a second model resembling the fuselage construction of an aircraft. In the two-dimensional case a simple membrane, with a small random variation in the membrane tension, was used. A decaying turbulence was constructed by superposing infinitely many components, each of which is convected as a frozen pattern at a different velocity. Structure-turbulence interaction results are presented in terms of the spectral densities of the structural response and the perturbation Reynolds stress in the fluid at the vicinity of the interface

MEMS flow sensors for nano-fluidic applications

This paper presents micromachined thermal sensors for measuring liquid flow rates in the nanoliter-per-minute range. The sensors use a boron-doped polysilicon thinfilm heater that is embedded in the silicon nitride wall of a microchannel. The boron doping is chosen to increase the heater’s temperature coefficient of resistance within tolerable noise limits, and the microchannel is suspended from the substrate to improve thermal isolation. The sensors have demonstrated a flow rate resolution below 10 nL/min, as well as the capability for detecting micro bubbles in the liquid. Heat transfer simulation has also been performed to explain the sensor operation and yielded good agreement with experimental data

Multiband effects on the conductivity for a multiband Hubbard model

The newly discovered iron-based superconductors have attracted lots of interests, and the corresponding theoretical studies suggest that the system should have six bands. In this paper, we study the multiband effects on the conductivity based on the exact solutions of one-dimensional two-band Hubbard model. We find that the orbital degree of freedom might enhance the critical value $U_c$ of on-site interaction of the transition from a metal to an insulator. This observation is helpful to understand why undoped High-$T_c$ superconductors are usually insulators, while recently discovered iron-based superconductors are metal. Our results imply that the orbital degree of freedom in the latter cases might play an essential role.Comment: 4 pages, 5 figure

Arithmetic Properties of Overpartition Pairs

Bringmann and Lovejoy introduced a rank for overpartition pairs and investigated its role in congruence properties of $\bar{pp}(n)$, the number of overpartition pairs of n. In particular, they applied the theory of Klein forms to show that there exist many Ramanujan-type congruences for the number $\bar{pp}(n)$. In this paper, we shall derive two Ramanujan-type identities and some explicit congruences for $\bar{pp}(n)$. Moreover, we find three ranks as combinatorial interpretations of the fact that $\bar{pp}(n)$ is divisible by three for any n. We also construct infinite families of congruences for $\bar{pp}(n)$ modulo 3, 5, and 9.Comment: 19 page

A new look at decomposition of turbulence forcing field and the structural response

Measured cross-spectrum of a turbulence field usually shows some decay in the statistical correlation in addition to convection at a characteristic velocity. It is shown that a decaying turbulence can be decomposed into frozen-pattern components thus permitting a simpler way to calculate the structural response. This procedure also provides a relationship whereby the measured input spectra can be incorporated. The theory is applied to an infinite beam which is backed on one side by a fluid filled cavity and is exposed on the other side by the turbulence excitation. The effect of the free stream velocity is also taken into consideration

Deep Learning Based Vehicle Make-Model Classification

This paper studies the problems of vehicle make & model classification. Some of the main challenges are reaching high classification accuracy and reducing the annotation time of the images. To address these problems, we have created a fine-grained database using online vehicle marketplaces of Turkey. A pipeline is proposed to combine an SSD (Single Shot Multibox Detector) model with a CNN (Convolutional Neural Network) model to train on the database. In the pipeline, we first detect the vehicles by following an algorithm which reduces the time for annotation. Then, we feed them into the CNN model. It is reached approximately 4% better classification accuracy result than using a conventional CNN model. Next, we propose to use the detected vehicles as ground truth bounding box (GTBB) of the images and feed them into an SSD model in another pipeline. At this stage, it is reached reasonable classification accuracy result without using perfectly shaped GTBB. Lastly, an application is implemented in a use case by using our proposed pipelines. It detects the unauthorized vehicles by comparing their license plate numbers and make & models. It is assumed that license plates are readable.Comment: 10 pages, ICANN 2018: Artificial Neural Networks and Machine Learnin