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.

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.

Capillary zone electrophoresis investigation of the interaction between heparin and granulocyte-colony stimulating factor

The interaction between standard heparin, low-molecular-weight heparin (LMWH), and granulocyte-colony stimulating factor (G-CSF) was studied by capillary zone electrophoresis. Both qualitative and quantitative characterizations of the heparin-protein binding were determined. The binding constants of the two different groups of heparins with G-CSF, calculated from the Scatchard plot by regression, were 4.805 x 10(5) m(-1) and 4.579 x 10(5) m(-1), respectively. The two binding constants measured are of the same order of magnitude at 10(5) m(-1), indicating that LMWH contains most of the functional groups bound to G-CSF by standard heparin.

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.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. 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 both basic and acidic samples.

Multivariate optimization in micellar electrokinetic capillary chromatography

The optimization of the organic modifier concentration in micellar electrokinetic capillary chromatography (MECC) has been achieved by a uniform design and iterative optimization method, which has been developed for the optimization of composition of the mobile phase in high performance liquid chromatography. According to the proposed method, the uniform design technique has been applied to design the starting experiments, which can reduce the number of experiments compared with traditional simultaneous methods, such as the orthano design. The hierarchical chromatographic response function has been modified to evaluate the separation quality of a chromatogram in MECC. An iterative procedure has been adopted to search the optimal concentration of organic modifiers for improving the accuracy of retention predicted and the quality of the chromatogram. Validity of the optimization method has been proved by the separation of 31 aromatic compounds in MECC. (C) 2000 John Wiley & Sons, Inc.

solving global unconstrained optimization problems by symmetry-breaking

IEEE Computer Society; International Association for; Computer and Information Science, ACIS