Machine Performance Check束流均匀性改变对Portal Dosimetry计划剂量验证的影响

目的:探究Machine Performance Check(MPC)系统束流均匀性变化对Portal Dosimetry(PD)计划验证的影响,为临床MPC均匀性的阈值设定和电子影像系统(EPID)的校准频率提供参考。方法:选取本中心EDGE加速器上首次治疗患者26例和10 cm×10 cm方野1例,制定治疗计划和验证计划。在MPC束流均匀性偏差增大的情况下,分别在EPID校准前和校准后执行验证计划,并在计划系统PD模块中分析,统计对比图像剂量和γ通过率。本研究还列出EDGE加速器一年间MPC束流均匀性的结果。结果:MPC 1年的统计结果显示束流均匀性偏差的升高趋势明显并且速度加快,表明EPID存在设备老化现象。EPID校准前后验证计划的图像剂量和γ通过率的对比结果表明不同能量方野计划在影像板中心附近的剂量差异为1%~2%,临床射野计划由于复杂性提高,剂量差异最大可以达到10%。EPID校准后的γ通过率高于校准前。结论:EPID探测器的一致性改变对PD计划剂量验证有一定影响,提示临床MPC均匀性阈值为2%时能够对PD计划剂量验证起到预警作用,EPID应在MPC重新采集基线之前校准,以保证验证计划的质量,保证患者放疗的安全性。

Implementation of Pre-Heating System in Stenters for Improving Machine Performance and Increasing Efficiency

In textile finishing, stenters always draw considerable attention to newer inventions to boost up production via maximum utilization of energy. Prior to main drying or heat-setting chambers, intermediate heating of cylindrical system especially by steam has a direct blessing to moisture evaporation, processing speed, fabric quality and so on. Based on actual operational data, this study reveals the outcomes of a pre-heating module installed within a stenter. After employing the pre-heating system to knit fabrics of different structures and compositions, 23% - 61% moisture reduction was found and the speed of processing fabrics was increased simultaneously by 17% - 30% without any compromise on fabric quality. Moreover, no less than 8.21% savings in annual electricity consumption were observed.

Energy-Performance Tradeoffs in laaS Cloud with Virtual Machine Scheduling

In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce energy consumption by optimizing the utilization of physical servers or network elements.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,this paper proposes a two-stage VM scheduling scheme:(1) We propose a static VM placement scheme to minimize the number of activating PMs and network elements to reduce the energy consumption;(2) In the premise of minimizing the migration costs,we propose a dynamic VM migration scheme to minimize the maximum link utilization to improve the network performance.This scheme makes a tradeoff between energy efficiency and network performance.We design a new twostage heuristic algorithm for a solution,and the simulations show that our solution achieves good results.

Assessment of Lubrication Property and Machining Performance of Nanofluid Composite Electrostatic Spraying(NCES)Using Different Types of Vegetable Oils as Base Fluids of External Fluid

The current study of minimum quantity lubrication(MQL)concentrates on its performance improvement.By contrast with nanofluid MQL and electrostatic atomization(EA),the proposed nanofluid composite electrostatic spraying(NCES)can enhance the performance of MQL more comprehensively.However,it is largely influenced by the base fluid of external fluid.In this paper,the lubrication property and machining performance of NCES with different types of vegetable oils(castor,palm,soybean,rapeseed,and LB2000 oil)as the base fluids of external fluid were compared and evaluated by friction and milling tests under different flow ratios of external and internal fluids.The spraying current and electrowetting angle were tested to analyze the influence of vegetable oil type as the base fluid of external fluid on NCES performances.The friction test results show that relative to NCES with other vegetable oils as the base fluids of external fluid,NCES with LB2000 as the base fluid of external fluid reduced the friction coefficient and wear loss by 9.4%-27.7%and 7.6%-26.5%,respectively.The milling test results display that the milling force and milling temperature for NCES with LB2000 as the base fluid of external fluid were 1.4%-13.2%and 3.6%-11.2%lower than those for NCES with other vegetable oils as the base fluids of external fluid,respectively.When LB2000/multi-walled carbon nanotube(MWCNT)water-based nanofluid was used as the external/internal fluid and the flow ratio of external and internal fluids was 2:1,NCES showed the best milling performance.This study provides theoretical and technical support for the selection of the base fluid of NCES external fluid.

Utilizing partial least square and support vector machine for TBM penetration rate prediction in hard rock conditions

Rate of penetration(ROP) of a tunnel boring machine(TBM) in a rock environment is generally a key parameter for the successful accomplishment of a tunneling project. The objectives of this work are to compare the accuracy of prediction models employing partial least squares(PLS) regression and support vector machine(SVM) regression technique for modeling the penetration rate of TBM. To develop the proposed models, the database that is composed of intact rock properties including uniaxial compressive strength(UCS), Brazilian tensile strength(BTS), and peak slope index(PSI), and also rock mass properties including distance between planes of weakness(DPW) and the alpha angle(α) are input as dependent variables and the measured ROP is chosen as an independent variable. Two hundred sets of data are collected from Queens Water Tunnel and Karaj-Tehran water transfer tunnel TBM project. The accuracy of the prediction models is measured by the coefficient of determination(R2) and root mean squares error(RMSE) between predicted and observed yield employing 10-fold cross-validation schemes. The R2 and RMSE of prediction are 0.8183 and 0.1807 for SVMR method, and 0.9999 and 0.0011 for PLS method, respectively. Comparison between the values of statistical parameters reveals the superiority of the PLSR model over SVMR one.

Dynamic Modeling of the Feed Drive System of a CNC Metal Cutting Machine

Studying the vibrational behavior of feed drive systems is important for enhancing the structural performance of computer numerical control(CNC)machines.The preload on the screw and nut position have a great influence on the vibration characteristics of the feed drive as two very important operational conditions.Rotational acceleration of the screw also affects the performance of the CNC feed drive when machining small parts.This paper investigates the influence of preload and nut position on the vibration characteristics of the feed drive system of a CNC metal cutting machine in order to be able to eliminate an observed resonance occurred at high rotational speeds of the screw,corresponding to high feed rates.Additionally,rational structural parameters of the feed drive system are selected in order to increase the rotational acceleration for improving the performance of the CNC machine.Experiments and analyses showed that by selecting specific parameters of feed drive system and simultaneously applying a certain value of preload,a 97%increase in rotational acceleration and 30%time reduction considering the vibration resistance at high rotational speeds can be achieved.

Experimental study of MWEDM technology

This work deals with an experimental investigation of the machining characteristics of Micro Wire Electrical Discharge Machining (MWEDM). The MWEDM process consists of only one cutting operation varying with machining conditions. Experimental results show that the peak current and pulse duration have an obvious influence on surface roughness and machining time, and they also have an optimum value for the highest cutting speed. The servo reference voltage influences the surface roughness and machining time as well. In particular, the surface characteristics of work-pieces and a micro wire electrode were analyzed in detail too. Utilizing a micro wire electrode with diameter 30μm, MWEDM can machine a micro slot 38μm wide, which proves that the discharge gap can be controlled not more than 4μm. It can also machine micro gears respectively with a module 40μm, thickness 1mm, and a module 100μm, thickness 3.5mm. All kinds of micro shaped holes and complex micro parts can be easily machined as well.

Error Prediction in Industrial Robot Machining: Optimization Based on Stiffness and Accuracy Limit

Among the advantages of using industrial robots for machining applications instead of machine tools are flexibility, cost effectiveness, and versatility. Due to the kinematics of the articulated robot, the system behaviour is quite different compared with machine tools. Two major questions arise in implementing robots in machining tasks: one is the robot’s stiffness, and the second is the achievable machined part accuracy, which varies mainly due to the huge variety of robot models. This paper proposes error prediction model in the application of industrial robot for machining tasks, based on stiffness and accuracy limits. The research work includes experimental and theoretical parts. Advanced machining and inspection tools were applied, as well as a theoretical model of the robot structure and stiffness based on the form-shaping function approach. The robot machining performances, from the workpiece accuracy point of view were predicted.