FLOW CHARACTERISTICS OF WALLFLOW DIESEL PARTICULATE FILTER SYSTEM WITH REVERSE PULSE AIR REGENERATION

To simulate steady airflows inside of wall-flow diesel particulate filters （DPF） with different reverse blowing pipes collocation, a mathematical model of the flow in a DPF is established by an equivalent continuum approach. The experimental results agree well with the theoretical values calculated from the model. Simulation shows that the velocity and the pressure distribution of the filters in the regenerative process are key factors to the filter＇s regeneration. How to decrease the mal-distribution of the flow in the filter and how to achieve the better regenerative performance at the least cost of air consumption in the regenerative process are the ultimate goals of the study. Calculation and experiments show that the goals can be realized through adjusting the angle of two reverse blowing pipes and their relative location suitably.

Effects of dipolar interactions on magnetic properties of Co nanowire arrays

Magnetic properties and magnetization processes of Co nanowire arrays with various packing densities are investigated by means of object-oriented micromagnetic framework（OOMMF） software package with finite difference micromagnetic simulations. The packing density of nanowires is changed with the diameter, number of nanowires and center-to-center spacing between the wires. The magnetization reversal mechanism and squareness of the hysteresis loops of the nanowire arrays are very sensitive to the packing density of nanowires. Clear steps and plateaux on the demagnetization are visible,which turns out that dipolar interactions among the wires have a significant influence on switching field.

Preferred clusters in metallic glasses

In this work, we present a feasible scheme based on framework of the sophisticated Voronoi tessellation method in order to evaluate what clusters should be preferred for building blocks in any given metallic glass, by analysing the fivefold-symmetry axes as well as the degree of structural regularity in various clusters. This scheme is well proved by a group of experiments and calculations, which may have broad implications for exploration of obtaining explicit and proper structural pictures, and understanding the structural origin of the unique properties and glass forming ability in these novel amorphous alloys.

Predicting Total Dwell Time of IPSA Plan Based on Machine Learning and Dose Calculation Models

Objective To establish two models based on machine learning and dose calculation algorithm that can be used for the prediction of the total dwell time and rapid quality control of brachytherapy plans.Methods A total of 1042 cases of treated gynecologic oncology patients were selected,of which 512 were used as training data to establish the model and the rest were used as test data.Each treatment plan optimized by inverse planning simulated annealing with all three catheters of the Fletcher applicator.The source strength Sk,prescription dose D,source dwell time t,and tumor volume V were recorded for each case.RV was defined as Sk·t/D.In accordance with the prescription dosage calculation formula in the planning system and machine learning method,the following equations were established:RV=kV2/3 and RV=a+b · V+c·V2.The R2 correlation coefficient represents the accuracy of the results.Result The dose calculation algorithm-based model is RV=1272×V2/3,R2=0.959,whereas the machine learning-based model is RV=258.8× V-0.359× V2+5110,R2=0.961.The treatment time prediction of the two models,each having 13 and 15 cases,respectively,has an error rate of more than10%,and the dose calculation algorithm-based method is more accurate.Conclusion The treatment time can be quickly predicted according to the planning target volume,and the two prediction models can be used as a way of quality control.

Establishment of a Fast Quality Assurance Method for Three-dimensional Afterloading Treatment Plan

Objective:To study the correlation between tumor size,radiation source intensity,prescription dose,and source dwell time in afterloading treatment plan,and to establish a rapid quality control method for afterloading treatment plan.Methods:A total of 181 patients with gynecological tumor were enrolled in our hospital.A total of 84 patients were installed with three tubes of Fletcher'applicator,58 patients with single uterine tube and 39 patients with vaginal applicator.Each patient was scanned with CT before treatment,and the target area and organs were delineated by doctors.The treatment plan was optimized by IPSA.The planned source intensity,prescription dose,source residence time and tumor volume of each case were recorded and the CI,RV,and k value were calculated,The CI distribution characteristics and the relationship with RV value were analyzed.In addition,46 cases of gynecological tumor patients'afterloading plan used this method for quality control verification.Results:The CI of the three kinds of applicators was normal distribution.The average Ci of Fletcher applicator was 0.720±0.067,k=1394,r=0.894,the average CI of Fletcher applicator was 0.697±0.076,k=1428,r=0.940,the average CI of vaginal applicator was 0.742±0.067,k=1362,r=0.909.Conclusion:Using this method,we could quickly evaluate the target volume,radiation source intensity,prescription dose and treatment time,to determine the cause of deviation according to the feedback results,ensuring that the afterloading treatment plan can be implemented efficiently quickly,and accurately in accordance with the clinical requirements.