On a multiscale computational strategy with time and space homogenization for structural mechanics

A new multiscale computational strategy was recently proposed for the analysis of structures described both on a fine space scale and a fine time scale. This strategy, which involves homogenization in space as well as in time, could replace in several domains of application the standard homogenization techniques, which are generally limited to the space domain. It is an iterative strategy which calls for the resolution of problems on both a micro (fine) scale and a macro (homogenized) scale. In this paper, we review the bases of this approach and present improved approximation techniques to solve the micro- and macro-problems.     

Optimum structure with homogeneous optimum cellular material for maximum fundamental frequency

Ultra-light cellular materials exhibit high stiffness/strength to weight ratios and bring opportunity for multifunctional performance. One of their potential applications is to build structure with optimum dynamic performance, which is extremely important for some structural parts in vehicle engineering and attracts a great attention. This paper presents a two-scale optimization method and aims at finding optimal configurations of macro structures and micro-structures of cellular material with maximum structural fundamental frequency. In this method macro and micro densities are introduced as independent design variables for macrostructure and microstructure. Optimizations at two scales are integrated into one system through homogenization theory and base material is distributed between the two scales automatically with optimization model. Microstructure of materials is assumed to be homogeneous at the macro scale to meet today’s manufacture practice and reduce manufacturing cost. Plane structure with homogeneous cellular material and perforated plate are studied. Numerical experiments validate the proposed method and computational model.     

Concurrent topology optimization design of structures and non-uniform parameterized lattice microstructures

This paper presents a novel concurrent topology optimization approach for finding the optimum topologies of macrostructures and their corresponding parameterized lattice microstructures in an integrated manner. Considering the manufacturability of the structure designs and computational efficiency, additional parameters are introduced to define the microstructure unit cell patterns and their non-uniform distribution, which avoids expensive iterative numerical homogenization calculations during topology optimization and results in an easier modelling of structure designs as well. It is worth mentioning that the equivalent properties of material microstructures serve as a link between the macro and the micro scale with the help of homogenization theory and the Porous Anisotropic Material with Penalization (PAMP) model. Besides, sensitivities of global structure compliance with respect to the pseudo-density variables and the microstructure parameter variables are derived, respectively. Moreover, several numerical examples are presented and reasonable solutions have been obtained to demonstrate the efficiency of the proposed method. Finally, mechanical testing is conducted to investigate the better performance of the optimized structure which is fabricated by 3D printing.     

基于多尺度融合的城市交通路网仿真系统研究

目前关于城市交通仿真方面的技术研究较多,但都存在一些问题,如:交通系统大部分在空间尺度上是从微观到宏观的高度综合,在时间尺度上是从秒级到年级高度连续的整合,交通系统的复杂度决定了任何一种单一的尺度都很难对交通现象进行更好的客观仿真。在此基础上,提出了基于多尺度融合的仿真系统,旨在从宏观、中观、微观3个尺度运用相应算法进行融合,并对系统进行设计。最后对基于多尺度融合的城市交通路网优化仿真系统进行实验,通过南京福建路和三牌楼路口信号方案优先的实例对其进行路网仿真实验分析。结果证明,该系统具有实用性和可靠性。     

Micro rotary swaging: process limitations and attempts to their extension

In this paper experimental investigations on micro components that are made by rotary swaging are presented and discussed. At first rotary swaging with its most important process variations is explained basically for the macro scale. Afterwards the fundamental changes of the forming of microcomponents are indicated as well as the smaller machines used henceforth. In this context, the shown process limitations and potential errors are very important. The change in microstructure after rotary swaging is shown in selected geometry and materials. The paper concludes with the planned experimental and analytic investigations as well as the machine design modifications for extension of the process limits of micro rotary swaging.     

Pressure-sensitive molecular film for investigation of micro gas flows

For the development of micro- and nano-technology, it has been strongly desired to understand thermo-fluid phenomena inside or around micro- and nano-devices. An optical measurement technique based on the absorption and the emission of photons by molecules is useful for experimental analyses of thermo-fluid phenomena of micro and nanoflows. The pressure-sensitive paint (PSP) technique is a potential diagnostic tool for pressure measurements of micro/nano gas flows because it works as a so-called “molecular sensor”. However, the micro-scale measurement of PSP has been limited by the aggregation of the luminescent molecules and their thick film due to the use of a polymer binder. In our previous work, we adopted the Langmuir–Blodgett (LB) technique to fabricate pressure-sensitive molecular film (PSMF) with ordered molecular assemblies, and investigated properties of PSMF. In this study, a novel approach to enhance the luminescent intensity of PSMF is proposed, and the pressure distribution in a micro-nozzle is successfully measured by using PSMF. Moreover, we compared the pressure distribution measured by PSMF with that numerically analyzed by the direct simulation monte carlo (DSMC) method, showing good agreement with each other.     

Design and manufacturing of micro milling tools

The actual geometrical design of micro milling tools has been adopted from macro tools, assuming that the effects during the milling process are analogical. Experience has also proved that micro tools respond to influences in a very different way than macro tools do. So it is very important to achieve a comprehensive understanding of the entire process by taking a structural, mechanical and cutting technological approach to micro milling tools in order to be able to optimize them. Oftentimes, structural details such as the rake angle and the twist angle impede further miniaturization and are impossible to achieve with conventional manufacturing techniques. This paper deals with an alternative method to manufacture structural optimized milling tools, namely Electro Discharge Machining (EDM). The present state of research already puts the deficits of the currently available tools on display. Manufacturing tolerances of ±10 μm on a micro tool are insufficient to ensure constant cutting conditions for the commonly used lateral infeed or feed per tooth of a few micrometers. Sometimes, only one cutting edge is engaged, which results in increased wear, increased cutting forces, minor surface quality and a higher risk of milling cutter breakage. That is why a single-edged micro milling tool has been developed. It guarantees clear adjustment of the process parameters, feed per edge and lateral infeed. For that purpose, stability analyses of simple stylus geometries have been conducted by means of FEM simulations. Corresponding to the results of the simulation the geometry of this tool was optimized in several steps. The resulting tool with a diameter down to 30 μm was machined on the EDM-machine (Sarix SX 100) at the wbk—Institute of Production Science. Initial tests have been carried out and showed the ability of these tools to optimize cutting process.     

Country crime analysis using the self-organizing map,with special regard to demographic factors

Modern research on criminal phenomena has been revolving not only around preventing existing offenses, but also around analyzing the criminal phenomena as a whole so as to overcome potential happenings of similar incidents. Criminologists and international law enforcement have been attracted to the cause of examining demographic context on which a crime is likely to arise. Traditionally, little has been explored in using demographic variables as determinants of the aggregate level of crime in the crime literature. Rapid development and ubiquitous application of information technology enables academic field to perform crime analysis using visualization techniques. Automation and networking make it available to access massive amounts of crime data, typically in the form of crime statistics. In numerous fields, studies and research have shown that visualization techniques are valuable; in crime research, nevertheless, there is a general lack of its application. In order to efficiently and effectively process crime data, criminologists and law enforcement are in demand of a more powerful tool. The self-organizing map (SOM), one of the widely used neural network algorithms, may be an appropriate technique for this application. The purpose of this study is to apply the SOM to mapping countries with different situations of crime. A total of 56 countries and 28 variables are included in the study. We found that some roughly definite patterns of crime situation can be identified in traditionally homogeneous countries. In different countries, positive correlation on crime in some countries may have negative correlation in other countries. Overall, correlation of some factors on crime can still be concluded in most groups. Results of the study prove that the SOM can be a new tool for mapping criminal phenomena through processing of large amounts of crime data.     

海量层次信息的Focus+Context交互式可视化技术

综述了海量层次信息可视化与Focus Context技术的相关工作,针对海量层次信息可视化的交互问题,在嵌套圆可视化技术的基础上提出了基于上下文感知的Focus Context交互式可视化技术.首先,基于外切圆排列方法提出对圆心进行三角网格剖分的方法,为变形计算建立上下文;然后,针对变形计算前后上下文一致性问题,在三角网格邻居跟踪方法的基础上,提出了用于同层兄弟节点上下文感知的外切圆变形排列方法,以及用于父子节点上下文感知的嵌套圆迭代排列方法.实验结果表明。上述方法在实现焦点突出的鱼眼视图的同时,能够有效地解决Focus Context交互式可视化的上下文感知问题.上述方法应用于文件系统海量层次信息的交互式可视化问题,提供了交互式可视化工具.     

Large‐Scale Pixel‐Precise Deferred Vector Maps

Rendering vector maps is a key challenge for high‐quality geographic visualization systems. In this paper, we present a novel approach to visualize vector maps over detailed terrain models in a pixel‐precise way. Our method proposes a deferred line rendering technique to display vector maps directly in a screen‐space shading stage over the 3D terrain visualization. Due to the absence of traditional geometric polygonal rendering, our algorithm is able to outperform conventional vector map rendering algorithms for geographic information systems, and supports advanced line anti‐aliasing as well as slope distortion correction. Furthermore, our deferred line rendering enables interactively customizable advanced vector styling methods as well as a tool for interactive pixel‐based editing operations.     

Visualizing large-scale uncertainty in astrophysical data

Visualization of uncertainty or error in astrophysical data is seldom available in simulations of astronomical phenomena, and yet almost all rendered attributes possess some degree of uncertainty due to observational error. Uncertainties associated with spatial location typically vary signicantly with scale and thus introduce further complexity in the interpretation of a given visualization. This paper introduces effective techniques for visualizing uncertainty in large-scale virtual astrophysical environments. Building upon our previous transparently scalable visualization architecture, we develop tools that enhance the perception and comprehension of uncertainty across wide scale ranges. Our methods include a unified color-coding scheme for representing log-scale distances and percentage errors, an ellipsoid model to represent positional uncertainty, an ellipsoid envelope model to expose trajectory uncertainty, and a magic-glass design supporting the selection of ranges of log-scale distance and uncertainty parameters, as well as an overview mode and a scalable WIM tool for exposing the magnitudes of spatial context and uncertainty.     

ProbExplorer: Uncertainty‐guided Exploration and Editing of Probabilistic Medical Image Segmentation

In this paper, we develop an interactive analysis and visualization tool for probabilistic segmentation results in medical imaging. We provide a systematic approach to analyze, interact and highlight regions of segmentation uncertainty. We introduce a set of visual analysis widgets integrating different approaches to analyze multivariate probabilistic field data with direct volume rendering. We demonstrate the user's ability to identify suspicious regions (e.g. tumors) and correct the misclassification results using a novel uncertainty‐based segmentation editing technique. We evaluate our system and demonstrate its usefulness in the context of static and time‐varying medical imaging datasets.     

A novel spark erosion technique for the fabrication of high aspect ratio micro-grooves

Micro groove is an important geometrical feature of components used in microsystem technology (MST). Straight micro grooves are the predominant features in microsystem components such as micro heat exchangers and diffraction gratings. Micro Electrical Discharge Machining (micro EDM) is a complementary microfabrication technique adopted from the conventional EDM machining process for the purpose of micro machining. Using micro EDM it is possible to machine all electrically conductive materials irrespective of their hardness. High aspect ratio microgroove machining for length as high as 20 mm is a formidable task for the conventional micro EDM. In the present work, a novel spark erosion technique has been described wherein a graphite foil has been used instead of the traditional pin shaped tool electrode, for the purpose of making straight grooves. In a single setup microgroove of 20 mm length and an aspect ratio of about 2.3 has been achieved on hardened tool steel by this technique. This process is further refined by using the gravitational effect for the effective debris removal, which has improved the aspect ratio to about 8.Accepted: September 2003     

Execution trace analysis through massive sequence and circular bundle views

An important part of many software maintenance tasks is to gain a sufficient level of understanding of the system at hand. The use of dynamic information to aid in this software understanding process is a common practice nowadays. A major issue in this context is scalability: due to the vast amounts of information, it is a very difficult task to successfully navigate through the dynamic data contained in execution traces without getting lost.In this paper, we propose the use of two novel trace visualization techniques based on the massive sequence and circular bundle view, which both reflect a strong emphasis on scalability. These techniques have been implemented in a tool called Extravis. By means of distinct usage scenarios that were conducted on three different software systems, we show how our approach is applicable in three typical program comprehension tasks: trace exploration, feature location, and top-down analysis with domain knowledge.     

A Four‐level Focus+Context Approach to Interactive Visual Analysis of Temporal Features in Large Scientific Data

In this paper we present a new approach to the interactive visual analysis of time‐dependent scientific data – both from measurements as well as from computational simulation – by visualizing a scalar function over time for each of tenthousands or even millions of sample points. In order to cope with overdrawing and cluttering, we introduce a new four‐level method of focus+context visualization. Based on a setting of coordinated, multiple views (with linking and brushing), we integrate three different kinds of focus and also the context in every single view. Per data item we use three values (from the unit interval each) to represent to which degree the data item is part of the respective focus level. We present a color compositing scheme which is capable of expressing all three values in a meaningful way, taking semantics and their relations amongst each other (in the context of our multiple linked view setup) into account. Furthermore, we present additional image‐based postprocessing methods to enhance the visualization of large sets of function graphs, including a texture‐based technique based on line integral convolution (LIC). We also propose advanced brushing techniques which are specific to the time‐dependent nature of the data (in order to brush patterns over time more efficiently). We demonstrate the usefulness of the new approach in the context of medical perfusion data.     

On Visualizing Continuous Turbulence Scales

Turbulent flows are multi‐scale with vortices spanning a wide range of scales continuously. Due to such complexities, turbulence scales are particularly difficult to analyse and visualize. In this work, we present a novel and efficient optimization‐based method for continuous‐scale turbulence structure visualization with scale decomposition directly in the Kolmogorov energy spectrum. To achieve this, we first derive a new analytical objective function based on integration approximation. Using this new formulation, we can significantly improve the efficiency of the underlying optimization process and obtain the desired filter in the Kolmogorov energy spectrum for scale decomposition. More importantly, such a decomposition allows a ‘continuous‐scale visualization’ that enables us to efficiently explore the decomposed turbulence scales and further analyse the turbulence structures in a continuous manner. With our approach, we can present scale visualizations of direct numerical simulation data sets continuously over the scale domain for both isotropic and boundary layer turbulent flows. Compared with previous works on multi‐scale turbulence analysis and visualization, our method is highly flexible and efficient in generating scale decomposition and visualization results. The application of the proposed technique to both isotropic and boundary layer turbulence data sets verifies the capability of our technique to produce desirable scale visualization results.     

Critical states of strongly interacting many-particle systems on a circle

Normally, two scales are considered in multicomponent systems, namely, macro and micro scales. Moreover, it is accepted that macro variables are completely defined by micro variables. We show that in the considered particle system with strong local (Coulomb) interaction this is not always the case. Namely, information concerning some macro variables can be encoded on a scale much finer than the micro scale.     

基于Focus+Context技术关联规则交互挖掘

可视化挖掘是数据挖掘的重要研究领域,但目前的研究还主要集中在挖掘结果的可视化,用户对挖掘过程仍然缺乏可控性.本文利用focus context技术实现探索型交互式数据挖掘.充分利用人类用户的认知能力与计算机的数据处理能力,实现用户对挖掘过程的参与从而利用用户领域知识于挖掘过程.适应人类的认知心理,便于帮助用户对挖掘结果的定位、聚焦、理解与评估,进而快速找到相对于当前应用上下文的有价值信息.并实现了一个原型系统IMARFC.     

Pressure-sensitive channel chip for visualization measurement of micro gas flows

We have developed a new pressure sensing tool named pressure-sensitive channel chip (PSCC) by combining the pressure-sensitive paint (PSP) technique with the poly(dimethylsiloxane) (PDMS) micro-molding technique. The PSP technique based on the oxygen quenching of luminescence is a potential diagnostic tool for pressure measurement of micro gas flows. However, the application of PSP to micro scale measurement is very difficult, because the thickness and the surface roughness of conventional PSPs cannot be neglected compared with the characteristic length of micro channels, and the spatial resolution is not enough for micro scale measurements due to the aggregations of luminophore. PSCC is fabricated with PDMS containing a pressure-sensitive luminophore; thus PSCC is a micro channel which itself works as a pressure “distribution” sensor. A micro converging-diverging nozzle with the throat width of 120 μm was demonstrated. The pressure distribution on the nozzle surface was successfully obtained by PSCC without the shortcomings of conventional PSPs.