Automated and Continuous Production of Microstructured Metallic Plates via Cold Embossing

Many critical issues need to be addressed when microstructured reactors are manufactured in large unit volumes. The most crucial of these are cost, ease of production, and reliability. The lack of breakthrough manufacturing technology to provide high‐efficiency, low‐cost, high‐precision plates is a hindrance to the early market implementation of systems requiring metallic microstructured plates. This contribution focuses on the development and optimization of a combined embossing and bending tool for the quick and continuous manufacture of easily machined plates.     

Influence of Ti Powder Characteristics on Combustion Synthesis of Porous NiTi Alloy

Porous NiTi shape memory alloy (SMA) is a novel biomedical material used for human hard tissue implant .The influence of elemental titanium powder characteristics such as powder morphology, particle size and specific surface area( SSA) on the minimal ignition temperature ,combustion temperature and final product of porous Ni-Ti SMA fabricated by combustion synthesis method was investigated in this paper by scanning electron microscopy (SEM) and laser diffraction.The preliminary data indicated that the titanium powder characteristics had a strong effect on combustion synthesis of porous NiTi SMA.     

Improvement of the engineering properties of asphalt pavements using a ‘soft’ compaction technique (AMIR-Compaction)

In most countries of the world asphalt pavement of road networks represents the biggest single investment in the transportation system. In Canada, asphalt pavement built over the past decade is worth more than 70 billion dollars (in 1984 dollars). In order to maintain the current road network at the present level of service and prevent it from further deterioration, over 6 billion dollars is needed anually.

Traditionally, asphalt overlays are widely used to rehabilitate existing deteriorated pavements. Unfortunately the new overlays have been observed to fail in a relatively short time. Thus the investment in overlays is lost.

Recent research based on the concept of relative rigidity has indicated that the rapid deterioration of new asphalt overlays is directly related to current construction equipment. It has been shown analytically and experimentally that steel rollers used in compacting the asphalt layer will result in surface cracks during construction. Traffic and environmental influences will accelerate the failure of the new layer.

This paper presents the results of a testing programme evaluating the engineering properties of asphalt slabs compacted by a new method using a compactor termed AMIR. The results showed that the AMIR compactor will prevent the formation of constitution cracks resulting in an increase of indirect tensile strength of 10% and an increase of direct tensile strength of up to 60% when compared to steel roller compacted asphalt slabs.     

Interactive quadrangulation with Reeb atlases and connectivity textures

Creating high-quality quad meshes from triangulated surfaces is a highly nontrivial task that necessitates consideration of various application specific metrics of quality. In our work, we follow the premise that automatic reconstruction techniques may not generate outputs meeting all the subjective quality expectations of the user. Instead, we put the user at the center of the process by providing a flexible, interactive approach to quadrangulation design. By combining scalar field topology and combinatorial connectivity techniques, we present a new framework, following a coarse to fine design philosophy, which allows for explicit control of the subjective quality criteria on the output quad mesh, at interactive rates. Our quadrangulation framework uses the new notion of Reeb atlas editing, to define with a small amount of interactions a coarse quadrangulation of the model, capturing the main features of the shape, with user prescribed extraordinary vertices and alignment. Fine grain tuning is easily achieved with the notion of connectivity texturing, which allows for additional extraordinary vertices specification and explicit feature alignment, to capture the high-frequency geometries. Experiments demonstrate the interactivity and flexibility of our approach, as well as its ability to generate quad meshes of arbitrary resolution with high-quality statistics, while meeting the user’s own subjective requirements.     

On the structure of polybutadiene: 4. 13C n.m.r. spectrum of polybutadienes with cis-1,4-, trans-1,4- and 1,2-units

¹³C n.m.r. spectra of polybutadienes with different contents of cis-1,4- and 1,2-units are assigned in the resonance region of the cis and trans carbon double bond. The observed signals are assigned to configurational triads.     

Interactive survival analysis with the OCDM system: From development to application

Medical data mining is currently actively pursued in computer science and statistical research but not in medical practice. The reasons therefore lie in the difficulties of handling and statistically analyzing medical data. We have developed a system that allows practitioners in the field to interactively analyze their data without assistance of statisticians or data mining experts. In the course of this paper we will introduce data mining of medical data and show how this can be achieved for survival data. We will demonstrate how to solve common problems of interactive survival analysis by presenting the Online Clinical Data Mining (OCDM) system. Thereby the main focus is on similarity based queries, a new method to select similar cases based on their covariables and the influence of these on their survival.     

Branching and circular features in high dimensional data

Large observations and simulations in scientific research give rise to high-dimensional data sets that present many challenges and opportunities in data analysis and visualization. Researchers in application domains such as engineering, computational biology, climate study, imaging and motion capture are faced with the problem of how to discover compact representations of high-dimensional data while preserving their intrinsic structure. In many applications, the original data is projected onto low-dimensional space via dimensionality reduction techniques prior to modeling. One problem with this approach is that the projection step in the process can fail to preserve structure in the data that is only apparent in high dimensions. Conversely, such techniques may create structural illusions in the projection, implying structure not present in the original high-dimensional data. Our solution is to utilize topological techniques to recover important structures in high-dimensional data that contains non-trivial topology. Specifically, we are interested in high-dimensional branching structures. We construct local circle-valued coordinate functions to represent such features. Subsequently, we perform dimensionality reduction on the data while ensuring such structures are visually preserved. Additionally, we study the effects of global circular structures on visualizations. Our results reveal never-before-seen structures on real-world data sets from a variety of applications.     

Feature-based statistical analysis of combustion simulation data

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion science; however, it is applicable to many other science domains.