A multi-moment finite volume formulation for shallow water equations on unstructured mesh

A novel and accurate finite volume method has been presented to solve the shallow water equations on unstructured grid in plane geometry. In addition to the volume integrated average (VIA moment) for each mesh cell, the point values (PV moment) defined on cell boundary are also treated as the model variables. The volume integrated average is updated via a finite volume formulation, and thus is numerically conserved, while the point value is computed by a point-wise Riemann solver. The cell-wise local interpolation reconstruction is built based on both the VIA and the PV moments, which results in a scheme of almost third order accuracy. Efforts have also been made to formulate the source term of the bottom topography in a way to balance the numerical flux function to satisfy the so-called C-property. The proposed numerical model is validated by numerical tests in comparison with other methods reported in the literature. (C) 2010 Elsevier Inc. All rights reserved.

Optimization of evanescent wave imaging for the visualization of protein adsorption layers

We have optimized the settings of evanescent wave imaging for the visualization of a protein adsorption layer. The enhancement of the evanescent wave at the interface brought by the incident angle, the polarized state of light beam as well as a gold layer is considered. In order to improve the image contrast of a protein monolayer in experiments, we have optimized three factors-the incident angle, the polarization of light beam, and the thickness of an introduced thin gold layer with a theoretical simulation.

Optimization of magnetic field for CR dipole magnet

High homogeneity of the CR (collector ring) dipole magnet for FAIR (Facility for Antiproton and Ion Research) project at GSI is essential. The two optimized and analysis methods are introduced in detail. In order to obtain an ideal integral magnetic field distribution, the complicated end chamfer has been designed. By chamfering the removable pole, the distribution tolerance of high magnetic field is optimized to +/- 2 x 10(-4). The method of adding a mirror plane is suitable for the high magnetic field and it doesn't fit the low one. The OPERA is used to optimize the dipole magnetic field.

Rotating wheel filter design and optimization for a uniform depth dose distribution in heavy ion therapy

Treatment planning of heavy-ion radiotherapy involves predictive calculation of not only the physical dose but also the biological dose in a patient body. The goal in designing beam-modulating devices for heavy ion therapy is to achieve uniform biological effects across the spread-out Bragg peak (SOBP). To achieve this, a mathematical model of Bragg peak movement is presented. The parameters of this model have been resolved with Monte Carlo method. And a rotating wheel filter is designed basing on the velocity of the Bragg peak movement.

Optimization design of magnetic field on cold yoke superconducting solenoid

The optimized design of magnetic field for a cold yoke superconducting solenoid is introduced in this paper. Using some kinds of optimization designs and OPERA, we optimize the main solenoid, cold yoke and compensated winding. Through this design, the requests of the superconducting solenoid are realized.

Simulation of micromegas detector by garfield program

In this paper, a batch file which describes the detailed structure and the corresponding physical process of Micro-Mesh Gaseous Structure (Micromegas) detector, the macro commands and the control structures based on the Garfield program has been developed. And using the Garfield program controlled by this batch file, the detector's gain and spatial resolution have been investigated under different conditions. These results obtained by the simulation program not only exhibit the influences of the mesh and drift voltage, the mixture gas proportion, the distance between the mesh cathode and the printed circuit board readout anode, and the Lines Per Inch of the mesh cathode on the gain and spatial resolution of the detector, but also are very important to optimize the design, shorten the experimental period, and save cost during the detector development. Additionally, they also indicate that the Garfield program is a powerful tool for the Micromegas detector design and optimization.

Optimization of the HIRFL-CSR cluster target

A new gas delivery system is designed and installed for HIRFL-CSR cluster target. The original blocked nozzle is replaced by a new one with the throat diameter of 0.12mm. New test of hydrogen and argon gases are performed. The stable jets can be obtained for these two operation gases. The attenuation of the jet caused by the collision with residual gas is studied. The maximum achievable H-2 target density is 1.75x10(13) atoms/cm(3) with a target thickness of 6.3x10(12) atoms/cm(2) for HIRFL-CSR cluster target. The running stability of the cluster source is tested both for hydrogen and argon. The operation parameters for obtaining hydrogen jet are optimized. The results of long time running for H-2 and Ar cluster jets look promising. The jet intensity has no essential change during the test for H-2 and Ar.

FAIR项目Super-FRS超导二极磁铁端部优化；End Optimization of Dipole Magnet of Super-FRS for FAIR

介绍了Super-FRS超导二极磁铁的磁场优化和端部削斜方案,采用OPERA软件对活极头进行削斜计算,得出合理的活极头尺寸,使各场下的积分均匀度在要求范围内达到了±2×10-4。最后将计算的积分场均匀度与磁场测量的结果进行比较,结果吻合得较好,验证了这种端部活极头优化计算方法的正确性。

Design optimization of the APF DTL in the SSC-linac

A linear accelerator as a new injector for the SSC (Separated Sector Cyclotron) of the HIRFL (Heavy ton Research Facility Lanzhou) is being designed. The DTL (Drift-Tube-Linac) has been designed to accelerate U-238(34+) from 0.140 MeV/u to 0.97 MeV/u. To the first accelerating tank which accelerates U-238(34+) to 0.54 MeV/u, the approach of Alternating-Phase-Focusing (APF) is applied. The phase array is obtained by coupling optimization software Dakota and beam optics code LINREV. With the hybrid of Multi-objective Genetic Algorithm (MOGA) and a pattern search method, an optimum array of asynchronous phases is determined. The final growth, both transversely and longitudinally, can meet the design requirements. In this paper, the deign optimization of the APF DTL is presented.

The Application of Toolkit of Optimization in Designs of Accelerator Magnets

The traditional design of accelerator magnet usually involves many time consuming iterations of the manual analysis process. A software platform to do these iterations automatically is proposed in this paper. In this platform, we use DAKOTA (a open source software developed by Sandia National Laboratories) as the optimizing routine, which provides a variety of optimization methods and algorithms, and OPERA (software from Vector Fields) is selected as the electromagnetic simulating routine. In this paper, two examples of designs of accelerator magnets are used to illustrate how an optimization algorithm is chosen and the platform works.

Application of uniform design and genetic algorithm in optimization of reversed-phase chromatographic separation

An optimization method based on uniform design in conjunction with genetic algorithm is described. According to the proposed method, the uniform design technique was applied to the design of starting experiments, which can reduce the number of experiments compared with traditional simultaneous methods, such as simplex. And genetic algorithm was used in optimization procedure, which can improve the rapidity of optimal procedure. The hierarchical chromatographic response function was modified to evaluate the separation equality of a chromatogram. An iterative procedure was adopted to search for the optimal condition to improve the accuracy of predicted retention and the quality of the chromatogram. The optimization procedure was tested in optimization of the chromatographic separation of 11 alkaloids in reversed-phase ion pair chromatography and satisfactory optimal result was obtained. (C) 2003 Elsevier B.V. All rights reserved.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Modeling and optimization for separation of ionic solutes in pressurized flow capillary electrochromatography

By manipulation of applied pressure or voltage, pressurized flow capillary electrochromatography (P-CEC) permits unique control of selectivity for ionic solutes. A simple mathematical model has been developed to describe the quantitative relationship between the electrochromatographic retention factor (k(*)) of charged solutes and the applied voltage and pressure. The validity of the model was verified experimentally with hydrophilic interaction mode CEC (HI-CEC). On the basis of the model developed, it was found that the value of k(*) could be predicted accurately using only a limited number of data points from the initial experiments at different voltages or pressures. Correlation between the experimentally measured and calculated k(*) was excellent, with a correlation coefficient greater than 0.999. Optimization for the separation of peptides by P-CEC was also performed successfully on the basis of the proposed model.