Three‐dimensional integration strategies of singular functions introduced by the XFEM in the LEFM

The use of the extended finite element method in the scope of linear elastic fracture mechanics induces the integration of singular functions in terms of the stiffness matrix and in the computation of stress intensity factors using the interaction integral method. An adapted method is proposed in this paper to treat efficiently the three‐dimensional case. The improvement is demonstrated by comparison with standard and other methods found in the literature. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive Compression of Texture Pyramids

High‐quality texture minification techniques, including trilinear and anisotropic filtering, require texture data to be arranged into a collection of pre‐filtered texture maps called mipmaps. In this paper, we present a compression scheme for mipmapped textures which achieves much higher quality than current native schemes by exploiting image coherence across mipmap levels. The basic idea is to use a high‐quality native compressed format for the upper levels of the mipmap pyramid (to retain efficient minification filtering) together with a novel compact representation of the detail provided by the highest‐resolution mipmap. Key elements of our approach include delta‐encoding of the luminance signal, efficient encoding of coherent regions through texel runs following a Hilbert scan, a scheme for run encoding supporting fast random‐access, and a predictive approach for encoding indices of variable‐length blocks. We show that our scheme clearly outperforms native 6:1 compressed texture formats in terms of image quality while still providing real‐time rendering of trilinearly filtered textures.     

Inclusion problem of a two-dimensional finite domain: The shape effect of matrix

With the advance in composite mechanics and micromechanics, there are increasing demands for analytical solutions of inclusion problems in a bounded domain. To echo this need, this study is focused on establishing explicit expressions of elastic fields for a 2D elastic domain containing a circular inclusion at center. Unlike the configuration in the classical Eshelby formulation, the elastic domain in this study is bounded and has shapes other than a circle. To circumvent the mathematical difficulty in solving Green’s function in a finite domain, an approach powered by complex potential method, which has been successfully employed to formulate the elastic fields for inclusion problems where matrix is unbounded or bounded by a circle, is extended to finite domains displaying complicated shapes, particularly, a Pascal’s limaçon and a curved square (an approximation of perfect square) in this study. In order to take advantage of the mathematical simplicity inherent in expressing a circular geometry, conformal mapping is used to transform the complex geometry of the finite domain of interest to a unit circle. The governing complex potentials, which capture the discontinuity on the inclusion–matrix interface due to the uniform eigenstrain within the inclusion, are formulated with the aid of Cauchy integral and then explicitly identified by satisfying the prescribed boundary conditions. In this study, the displacement fields for finite domains bounded by a Pascal’s limaçon and a curved square are obtained based on Dirichlet (displacement) boundary conditions imposed by the far field strain. In addition to asymptotical behaviors, firm agreement is also achieved when the analytical solutions based on complex potentials are compared with the FEM results. Furthermore, inverse of the conformal mapping is discussed here in order to get the explicit expression for elastic fields.     

Progressive filling partitioning and mapping algorithm for Spark based on allocation fitness degree

The job execution mechanism of Spark was analyzed,task efficiency model and Shuffle model were established,then allocation fitness degree (AFD) was defined and the optimization goal was put forward.On the basis of the model definition,the progressive filling partitioning and mapping algorithm (PFPM) was proposed.PFPM established the data distribution scheme adapting Reducers’ computing ability to decrease synchronous latency during Shuffle process and increase cluster the computing efficiency.The experiments demonstrate that PFPM could improve the rationality of workload distribution in Shuffle and optimize the execution efficiency of Spark.     

Back propagation genetic and recurrent neural network applications in modelling and analysis of squeeze casting process

Today, in competitive manufacturing environment reducing casting defects with improved mechanical properties is of industrial relevance. This led the present work to deal with developing the input-output relationship in squeeze casting process utilizing the neural network based forward and reverse mapping. Forward mapping is aimed to predict the casting quality (such as density, hardness and secondary dendrite arm spacing) for the known combination of casting variables (that is, squeeze pressure, pressure duration, die and pouring temperature). Conversely, attempt is also made to determine the appropriate set of casting variables for the required casting quality (that is, reverse mapping). Forward and reverse mapping tasks are carried out utilizing back propagation, recurrent and genetic algorithm tuned neural networks. Parameter study has been conducted to adjust and optimize the neural network parameters utilizing the batch mode of training. Since, batch mode of training requires huge data, the training data is generated artificially using response equations. Furthermore, neural network prediction performances are compared among themselves (reverse mapping) and with those of statistical regression models (forward mapping) with the help of test cases. The results shown all developed neural network models in both forward and reverse mappings are capable of making effective predictions. The results obtained will help the foundry personnel to automate and précised control of squeeze casting process.     

Trained sensory panellists’ response to product alcohol content in the projective mapping task: Observations on alcohol content,product complexity and prior knowledge

Projective mapping has been validated as a practical tool for the rapid sensory profiling of brandy products, although repeatability concerns necessitate repeated measurements in larger sample sets. The reason for poor repeatability could be linked to the complexity of the product type, as well as the physical and possibly psychological factors associated with its high alcohol content. To date no information has been published that tested the effect of these specific factors on panellist performance in projective mapping tasks. This study tested the effect of sample complexity and alcohol content on sensory panel repeatability and accuracy in projective mapping, using six types of commercial alcoholic beverages. In a second objective, the study also tested the effect of prior knowledge of alcohol content of a given product set on panellist performance in projective mapping. The results showed that complexity had the biggest impact on panel performance, while alcohol content had a secondary but decisive influence, largely due to its chemosensory fatiguing nature. Knowledge of the product alcohol content appeared to affect individuals differently, and also had an effect on the terminology used by the panellists to describe the products. The study also introduces the Relative Performance Indicator (RPI) as a new panel performance monitoring tool for projective mapping.     

基于GIS和SLAM的机器人大范围环境自主导航

机器人自主导航技术的基础是其自定位能力,同时同步定位与建图(SLAM)是实现机器人自定位的重要方法。目前由于大规模SLAM技术发展的限制,机器人很难实现在大范围环境下进行建图和导航,并且尚没有结合SLAM和实际地理空间信息指导大范围机器人导航的完整自主导航系统。提出基于GIS和SLAM的机器人大范围环境自主导航方法,利用真实的城市空间路网信息,以地理信息系统(GIS)空间数据库的存储和计算能力为数据支撑,基于提出的大范围导航算法,实现了一套包含空间数据库、SLAM、导航算法的完整系统,具有良好的可复用性和可扩展性,符合实际生活场景,可以指导机器人进行大范围条件下的导航和建图行为。同时通过对机器人激光建图信息的存储,使得再次经过本区域的机器人可以在户外精确定位,实现在室外GPS缺失或误差条件下自身位置的修正。此外地图信息的存储可以实现多机器人对地图信息的复用,为多机器人的规划提供支撑。同时将人类世界的空间信息与机器人建图信息相结合,细化和丰富了原有的空间信息。