Sequencing Punch Operations In A Flexible Manufacturing Cell A Three-Dimensional Space-Filling Curve Approach

1987 ◽  
Vol 25 (1) ◽  
pp. 26-45 ◽  
Author(s):  
F. Chauny ◽  
A. Haurie ◽  
E. Wagneur ◽  
R. Loulou
2011 ◽  
Vol 19 (2) ◽  
pp. 81 ◽  
Author(s):  
Guoquan Liu ◽  
Haibo Yu

Serial sectioning technique provides plenty of quantitative geometric information of the microstructure analyzed, including those unavailable from stereology with one- and two-dimensional probes. This may be why it used to be and is being continuously served as one of the most common and invaluable methods to study the size and the size distribution, the topology and the distribution of topology parameters, and even the shape of three-dimensional space filling grains or cells. On the other hand, requiring tedious lab work, the method is also very time and energy consuming, most often only less than one hundred grains per sample were sampled and measured in almost all reported practice. Thus, a question is often asked: for typical microstructures in engineering materials, are so many grains or cells sampled adequate to obtain reliable results from this technique? To answer this question, experimental data of 1292 contiguous austenite grains in a low-carbon steel specimen obtained from the serial sectioning analysis are presented in this paper, which demonstrates the effect of sampling on the measurement of various parameters of grain size distribution and of the grain topology distribution. The result provides one of rules of thumb for grain stereology of similar microstructures.


1987 ◽  
Vol 2 (2) ◽  
pp. 93-108 ◽  
Author(s):  
Haresh Lalvani

An interesting class of two- and three-dimensional space structures can be derived from projections of higher-dimensional structures. Regular polygons and regular-faced polyhedra provide the geometry of families of n-stars from which two- and three-dimensional projections of n-dimensional grids can be derived. These projections are rhombic space grids composed of all-space filling rhombi and rhombohedra with edges parallel to n directions. An infinite class of single-, double- and multi-layered grids can be derived from n-sided polygons and prisms, and a finite class of multi-directional grids from the polyhedral symmetry groups. The grids can be periodic, centrally symmetric or non-periodic, and act as skeletons to generate corresponding classes of space-filling, packings and labyrinths.


1996 ◽  
Vol 118 (2) ◽  
pp. 210-215 ◽  
Author(s):  
E. Denny ◽  
R. C. Schroter

A computational method is proposed for the construction of a three-dimensional space-filling model of an acinar ventilatory unit. Its geometry consists of truncated octahedra arranged in a cuboidal block. The ducts and alveoli are formed by opening specific common faces between polyhedra. The branching structure is automatically computed using algorithms solely to maximise the number of alveoli and minimise the average path lengths; it is not formed with reference to published experimental data. Properties of the model such as the total alveolar and ductal volumes, the distribution of individual path lengths to the alveolar sacs, and the average number of ducts per generation are calculated. The predicted morphology of the model compares well with published data for rat lungs.


2019 ◽  
Vol 8 (4) ◽  
pp. 7379-7383

In two dimensions, tiling the plane plays a vital role. Many picture generative models were attempted to tile the three dimensional space. A. Dharani et al. [6] introduced a new theoretical picture generative model to tile a three dimensional space using tetrahedral tile in two different ways namely Sequential Space Filling Grammar (SSFG) and Parallel Space Filling Grammar (PSFG). Local and recognizable tetrahedral picture languages are introduced in this paper and some of its properties are studied.


2018 ◽  
Vol 7 (1.9) ◽  
pp. 129
Author(s):  
Sushma T.V ◽  
Roopa M

Space filling curve is used widely for linear mapping of multi-dimensional space. This provides a new line of thinking for various applications in image processing, Image compression being the most widely used. The paper highlights the locality preserving property of Hilbert Space filling curve which is essential in numerous applications such asin image compression, numerical analysis of a large aray of data, parallel processing and so on. A simplistic approach forusingHilbert Space filling curve using Scilab code has been presented.


1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.


2019 ◽  
Author(s):  
Jumpei Morimoto ◽  
Yasuhiro Fukuda ◽  
Takumu Watanabe ◽  
Daisuke Kuroda ◽  
Kouhei Tsumoto ◽  
...  

<div> <div> <div> <p>“Peptoids” was proposed, over decades ago, as a term describing analogs of peptides that exhibit better physicochemical and pharmacokinetic properties than peptides. Oligo-(N-substituted glycines) (oligo-NSG) was previously proposed as a peptoid due to its high proteolytic resistance and membrane permeability. However, oligo-NSG is conformationally flexible and is difficult to achieve a defined shape in water. This conformational flexibility is severely limiting biological application of oligo-NSG. Here, we propose oligo-(N-substituted alanines) (oligo-NSA) as a new peptoid that forms a defined shape in water. A synthetic method established in this study enabled the first isolation and conformational study of optically pure oligo-NSA. Computational simulations, crystallographic studies and spectroscopic analysis demonstrated the well-defined extended shape of oligo-NSA realized by backbone steric effects. The new class of peptoid achieves the constrained conformation without any assistance of N-substituents and serves as an ideal scaffold for displaying functional groups in well-defined three-dimensional space, which leads to effective biomolecular recognition. </p> </div> </div> </div>


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