一种应用于欠采样图像的自适应稀疏重建方法

针对图像稀疏重建中因使用固定参数的全变分(TV)正则项所带来的图像细节缺失和阶梯效应问题,提出了一种自适应二阶广义全变分(TGV)约束的图像稀疏重建算法.该算法采用二阶广义全变分模型权衡图像的一阶导数和二阶导数,且能够根据每次迭代得到的重构解及对应张量函数自适应地修正权重系数,实现图像的稀疏重建.与全变分正则模型和固定参数广义全变分正则模型相比,该算法能更好地保持图像轮廓和细节信息,提高重建图像的峰值信噪比(PSNR)和结构相似度(SSIM).     

储层物性时变对油藏水驱开发的影响

针对水驱油藏储层物性时变影响油田开发效果和剩余油分布的问题,分析了采用过水倍数表征物性时变规律会造成计算结果不稳定的原因,提出基于面通量的物性时变表征方法,并通过矿场资料分析、黑油模型改进、软件编制,建立了相应的数值模拟技术。利用该技术研究物性时变对油藏开发的影响,结果表明:考虑渗透率和相渗曲线综合时变后,剩余油主要富集在靠近生产井的主流线两侧,油藏采出程度比不考虑物性时变提高8.3百分点;渗透率和相渗曲线时变的影响存在一定差异,渗透率时变会使开发效果稍微变差,相渗曲线时变会使开发效果明显提高。该技术解决了基于过水倍数的物性时变数值模拟方法计算结果受网格尺寸影响的问题,对准确预测油藏开发指标和剩余油分布具有重要的应用价值。     

两种反演方法在NP-4号构造区的联合应用

NP-4号构造区主要发育扇三角洲沉积体系,储层物性较好,但储层横向变化快、厚度薄,单一的反演方法无法同时满足储层预测的精度要求。在做好测井曲线标准化等准备工作的基础上,先利用确定性反演确定储层的大致展布范围和横向变程,再利用地质统计学反演中的随机反演和序贯高斯配置协模拟得到纵向分辨率更高的波阻抗体和伽马体。此方法可以逐步提高反演的精度,在实际应用中取得了较好的效果。     

环境温度波动对磨床立柱几何精度的影响

针对环境温度波动的变化造成机床热误差从而影响其加工精度的问题,以实验室某磨床立柱为研究对象,采用有限元分析法对不同环境温度波动下的磨床立柱的温度场和热变形情况进行了仿真分析,进而得到了环境温度波动幅值和频率对其几何精度的影响规律。研究结果表明,当环境温度波动幅值为2 、波动周期为2/3 h时,立柱导轨的垂直度热误差＜1 μm,直线度热误差＜0.5 μm。在保证磨床加工精度的同时,可大幅减小车间温度控制的难度,节约能源。     

全浮动芯棒连轧管机孔型对钢种适应性的模拟研究

应用MSC.SuperForm有限元仿真软件,基于现场生产工艺,模拟了Φ140 mm全浮动芯棒连轧管机Φ195 mm孔型的钢管连轧过程,研究了连轧过程中C22和超级13Cr两种钢的金属流动、轧制力等规律性.结果表明：与C22相比较,超级13Cr更易产生宽展,金属横向流动倾向性更大,所以在高合金管轧制用孔型设计时,需特别注意金属过充倾向;超级13Cr的轧制力较C22增大60％以上,机架、轧辊的弹性变形量更大,在轧辊辊缝预调时,应加大超级13Cr的预压靠量,在孔型设计时,也需考虑其弹性变形量,以补偿高合金钢轧制时大轧制力引起的机架、轧辊的弹性变形量的影响.     

氢内燃机循环变动特性

为探索氢内燃机的循环变动特性,基于一台2.0,L 进气道喷射式氢内燃机,开展了氢内燃机循环变动特性及影响因素的试验研究．试验结果表明：平均指示压力的循环变动系数是评价氢内燃机循环变动特性的理想特征参数;怠速转速越高,氢内燃机的循环变动越小;随混合气浓度提高,氢内燃机循环变动显著减小,点火提前角对循环变动的影响变弱,同时循环变动系数最小时对应的点火提前角逐渐趋近压缩上止点;节气门开度在0～20%范围时,随节气门开度增大循环变动显著减小;在怠速工况下,进气过程中喷氢会导致氢内燃机循环变动增加．     

Inventory-shortage driven optimisation for product configuration variation

Inventory control is a critical problem in manufacturing systems. Inventory shortage significantly affects system productivity, while excessive stocks increase the operation cost. It is difficult to avoid fully inventory shortage under mass customisation manufacturing based on product configuration. In this paper, we propose a new approach for inventory-shortage driven optimisation of dynamic product configuration variation to meet the requirements of product configuration change and find suitable combination of parts by considering cost, lead-time and inventory variation. The multi-objective optimisation model uses a multi-objective genetic algorithm and adds impact cost, lead-time and inventory factors to the normal configuration optimisation model. An industrial case study demonstrates the practicality and effectiveness of the proposed approach. By means of this research, valid solutions for configuration variation are available to the decision makers.     

Improvement of AS/RS performance using design and application of common zone

Minimization of overall queue length in AS/RS is studied in this research. In general, class-based storage policy is recommended for overall AS/RS operation, but it has a rack shortage problem under demand variation. To resolve this problem, an area along the board of two classes in AS/RS racks is allocated and is named the common zone. This zone is designed to handle the rack shortage problem associated with the items in a particular class under class-based storage policy. Thirty percent common zone size is determined as the most favorable allocation among various sizes through simulation experiments. This particular size common zone policy is compared with other well-known policies such as class-based, relocation, and random storage policy. These four operation policies under three different levels of workloads with demand variations are simulated. Crane moving time, rack shortages, delay times as well as throughputs are checked for the policy evaluation.     

A Robustness Approach to Reliability

Reliability of products is here regarded with respect to failure avoidance rather than probability of failure. To avoid failures, we emphasize variation and suggest some powerful tools for handling failures due to variation. Thus, instead of technical calculation of probabilities from data that usually are too weak for correct results, we emphasize the statistical thinking that puts the designers focus on the critical product functions. Making the design insensitive to unavoidable variation is called robust design and is handled by (i) identification and classification of variation, (ii) design of experiments to find robust solutions, and (iii) statistically based estimations of proper safety margins. Extensions of the classical failure mode and effect analysis (FMEA) are presented. The first extension consists of identifying failure modes caused by variation in the traditional bottom–up FMEA analysis. The second variation mode and effect analysis (VMEA) is a top–down analysis, taking the product characteristics as a starting point and analyzing how sensitive these characteristics are to variation. In cases when there is sufficient detailed information of potential failure causes, the VMEA can be applied in its most advanced mode, the probabilistic VMEA. Variation is then measured as statistical standard deviations, and sensitivities are measured as partial derivatives. This method gives the opportunity to dimension tolerances and safety margins to avoid failures caused by both unavoidable variation and lack of knowledge regarding failure processes. Copyright © 2012 John Wiley & Sons, Ltd.     

Few‐view image reconstruction combining total variation and a high‐order norm

This work presents a novel computed tomography reconstruction method for few‐view problem based on a compound method. To overcome the disadvantages of total variation (TV) minimization method, we use a high‐order norm coupled within TV and the numerical scheme for our method is given. We use the root mean square error as a referee. The numerical experiments demonstrate that our method achieves better performance than existing reconstruction methods, including filtered back projection, expectation maximization, and TV with projection on convex sets. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 249–255, 2013