Grid‐free surface vorticity method applied to flow induced vibration of flexible cylinders

In order to study cross flow induced vibration of heat exchanger tube bundles, a new fluid–structure interaction model based on surface vorticity method is proposed. With this model, the vibration of a flexible cylinder is simulated at Re=2.67 × 10⁴, the computational results of the cylinder response, the fluid force, the vibration frequency, and the vorticity map are presented. The numerical results reproduce the amplitude‐limiting and non‐linear (lock‐in) characteristics of flow‐induced vibration. The maximum vibration amplitude as well as its corresponding lock‐in frequency is in good agreement with experimental results. The amplitude of vibration can be as high as 0.88D for the case investigated. As vibration amplitude increases, the amplitude of the lift force also increases. With enhancement of vibration amplitude, the vortex pattern in the near wake changes significantly. This fluid–structure interaction model is further applied to simulate flow‐induced vibration of two tandem cylinders and two side‐by‐side cylinders at similar Reynolds number. Promising and reasonable results and predictions are obtained. It is hopeful that with this relatively simple and computer time saving method, flow induced vibration of a large number of flexible tube bundles can be successfully simulated. Copyright © 2004 John Wiley & Sons, Ltd.     

Aharonov–Bohm oscillations observed in nanoscale open-dot structures fabricated in an InAs surface inversion layer

We fabricated nanoscale open-dot structures in an InAs surface inversion layer using an atomic-force-microscope oxidation process. Due to its superior nanofabrication capability, small open-dot structures with the feature size ranging between 100 and 300 nm were successfully fabricated. The magnetoresistance signal measured at 4.2 K showed reproducible fluctuations and a periodic oscillation component that varies in both amplitude and periodicity depending on the dot size. We show that the period of the oscillations corresponds to that of the Aharonov–Bohm effect and propose that the possible mechanism for the oscillations is due to the formation of a one-dimensional electron channel enclosing the open-dot structure as a result of the electron transfer from the InAs oxide to InAs.     

Quantum Hall effect in back-gated InAs/GaSb heterostructures under a tilted magnetic field

We investigate the quantum Hall effect (QHE) in the InAs/GaSb hybridized electron–hole system grown on a conductive InAs substrate which act as a back-gate. In these samples, the electron density is constant and the hole density is controlled by the gate-voltage. Under a magnetic field perpendicular to the sample plane, the QHE appears along integer Landau-level (LL) filling factors of the net-carriers, where the net-carrier density is the difference between the electron and hole densities. In addition, longitudinal resistance maxima corresponding to the crossing of the extended states of the original electron and hole LLs make the QHE regions along integer-ν_net discontinuous. Under tilted magnetic fields, these R_xx maxima disappear in the high magnetic field region. The results show that the in-plane magnetic field component enhances the electron–hole hybridization and the formation of minigaps at LL crossings.     

New data on the ternary fission of 252Cf from the Gammasphere facility

Ternary fission of ²⁵²Cf was studied at Gammasphere using eight ΔE×E particle telescopes. Helium, beryllium, boron, and carbon light charged particles (LCPs) emitted with kinetic energy more than 9, 21, 26, and 32 MeV, respectively, were identified. The 3368-keV γ transition from the first 2⁺ excited state in ¹⁰Be was found and the population probability ratio N(2⁺)/N(0⁺) = 0.160 ± 0.025 was estimated. No evidence was found for 3368-keV γ rays emitted from a triple molecular state. For the first time, charge distributions are obtained for ternary fission fragments emitted with helium, beryllium, and carbon LCPs.     

<Emphasis Type="Italic">L</Emphasis><Subscript>1</Subscript> linear interpolator for missing values in time series

We propose a minimum mean absolute error linear interpolator (MMAELI), based on theL ₁ approach. A linear functional of the observed time series due to non-normal innovations is derived. The solution equation for the coefficients of this linear functional is established in terms of the innovation series. It is found that information implied in the innovation series is useful for the interpolation of missing values. The MMAELIs of the AR(1) model with innovations following mixed normal andt distributions are studied in detail. The MMAELI also approximates the minimum mean squared error linear interpolator (MMSELI) well in mean squared error but outperforms the MMSELI in mean absolute error. An application to a real series is presented. Extensions to the general ARMA model and other time series models are discussed. This research was supported by a CityU Research Grant and Natural Science Foundation of China.     

A comparison between optically active CdZnSe/ZnSe and CdZnSe/ZnBeSe self-assembled quantum dots: effect of beryllium

The composition and size of optically active Cd_xZn_1−xSe/ZnSe quantum dots are estimated with a previously developed method. The results are then compared with those obtained for Cd_xZn_1−xSe/Zn_0.97Be_0.03Se QDs. We show that introducing Be into the barrier material enhances both Cd composition and quantum size effect of optically active quantum dots.     

Feed forward neural networks modeling for K–P interactions

Artificial intelligence techniques involving neural networks became vital modeling tools where model dynamics are difficult to track with conventional techniques. The paper make use of the feed forward neural networks (FFNN) to model the charged multiplicity distribution of K–P interactions at high energies. The FFNN was trained using experimental data for the multiplicity distributions at different lab momenta. Results of the FFNN model were compared to that generated using the parton two fireball model and the experimental data. The proposed FFNN model results showed good fitting to the experimental data. The neural network model performance was also tested at non-trained space and was found to be in good agreement with the experimental data.