Algorithms for the physical fabrication of shapes using 3

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Algorithms for the physical fabrication of shapes using 3

JavaScript is disabled for your browser. Some features of this site may not work without it. Algorithms and models for 3-D shape measurement using digital fringe projections. Date Advisor Gupta, Satyandra K. Metadata Show full item record. Abstract Many industrial applications require accurate and rapid measurement of the 3-D shapes of physical objects. Representative applications of 3-D shape measurement include mechanical reverse engineering, 3-D digital replication, and part inspection.

Traditional 3-D measurement techniques, such as coordinate measurement machines CMM and laser scanning, provide high accuracy but are generally slow and expensive. In recent years, shape measurement based on digital fringe projection SMDFP has been developed for non-contact shape measurements. However, the existing models and algorithms for SMDFP systems need to be significantly improved to fully exploit the potentials of this technique. Based on this model, three related algorithms for shape measurements were developed, namely the algorithm for construction of absolute phase map, algorithm for construction of point cloud, and algorithm for estimation of sensor parameters.

With the new model and algorithms, the measurement speed of existing SMDFP systems is improved and the calibration procedure is made easier. At the same time, high measurement accuracy is ensured. This dissertation also provides a framework for using adaptive projection patterns in SMDFP technique.

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A new algorithm was developed for automatic generation of projection patterns with variable fringe pitches to achieve improved measurement performance.

This capability is particularly important for ensuring the accuracy and speed when measuring surfaces with a large range of normal directions. Finally, this dissertation presents a comprehensive uncertainty model for describing the relations between various error sources and the resulting uncertainties in shape measurements.

Based on this model, measurement uncertainties can be estimated from the image data acquired in a measurement. The research results reported in this dissertation can be used to improve the performance and features of existing SMDFP systems in the following aspect: measurement accuracy, speed, ease of calibration, and estimation of measurement uncertainties. These improvements could make SMDFP technique more attractive to industrial 3-D shape measurement applications and to stimulate the wide spread use of this technique.

algorithms for the physical fabrication of shapes using 3

Search DRUM. This Collection. Login Register.A University of British Columbia computer scientist has created a new software that can create a design sketch of an everyday object, addressing the challenge of accurately describing shapes.

The easiest way to describe shapes is to sketch them. To create the program, Sheffer used insights from a field of psychology known as Gestalt psychology that explains how humans interpret visual content and understand depth from two-dimensional drawings.

The algorithms she developed based on these insights help turn diverse shapes like airplanes, cars, coffee makers and mugs into sketches. This research builds on earlier algorithms that Sheffer and her colleagues developed that can turn sketches and drawings into 3D shapes. Together, these methods can be used to recreate objects around us and has implications for fields like 3D printing and fabrication. Sheffer's program has worked well in user studies.

The sketches and 3D curves produced by the algorithm were deemed comparable to those produced by professional designers. Sheffer is now looking to explore additional applications of the system. Since the current algorithm is best suited for human-made rather than natural shapes, Sheffer is also looking into improvements that will allow the system to produce top quality sketches of natural shapes. Materials provided by University of British Columbia. Note: Content may be edited for style and length.

Science News. ScienceDaily, 1 August University of British Columbia. Algorithms that can sketch, recreate 3-D shapes. Retrieved October 11, from www. Helping Students Learn by Sketching Apr. A method called photogrammetry has now been Instead of using conventional computer-aided Running on a new type of tablet computer, the program generates 3-D maps in ScienceDaily shares links with sites in the TrendMD network and earns revenue from third-party advertisers, where indicated.A University of British Columbia computer scientist has created a new software that can create a design sketch of an everyday object, addressing the challenge of accurately describing shapes.

The easiest way to describe shapes is to sketch them. To create the program, Sheffer used insights from a field of psychology known as Gestalt psychology that explains how humans interpret visual content and understand depth from two-dimensional drawings. The algorithms she developed based on these insights help turn diverse shapes like airplanes, cars, coffee makers and mugs into sketches.

This research builds on earlier algorithms that Sheffer and her colleagues developed that can turn sketches and drawings into 3D shapes. Together, these methods can be used to recreate objects around us and has implications for fields like 3D printing and fabrication. Sheffer's program has worked well in user studies.

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The sketches and 3D curves produced by the algorithm were deemed comparable to those produced by professional designers. Sheffer is now looking to explore additional applications of the system.

Since the current algorithm is best suited for man-made rather than natural shapes, Sheffer is also looking into improvements that will allow the system to produce top quality sketches of natural shapes. Explore further. Your feedback will go directly to Tech Xplore editors. Thank you for taking your time to send in your valued opinion to Science X editors.

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By using our site, you acknowledge that you have read and understand our Privacy Policy and Terms of Use. Home Computer Sciences. August 1, FlowRep is a new software that can create a design sketch of an everyday object. Credit: Alla Sheffer. Provided by University of British Columbia. This document is subject to copyright.

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Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. New virtual reality software allows scientists to 'walk' inside cells 10 hours ago. Oct 11, Oct 09, Related Stories.Spectral methods are commonly used to construct geometric representations, due to their ability to capture global netlist information.

The book by Lengauer [] is noteworthy, especially for its complete developmentofcombinatorial algorithms network ow, Fortunately, in real designs, the number of this kind of blockages are relatively small. This is because that almost all complete routing block To facilitate understanding of the rest of the paper, we first introduce the mod Through the integration of multiple optimization techniques, design methods and high-performance CAD software for integrated circuits ICs were developed.

However, the ever-increasing size of ICs l A chip consists of a set of cells, a set of nets and a rectangular chip area. Each cell is given as a rectangular box of certain size s s, and each net connects a We have chosen to implement a concurrent hierarchical global router for 3-D integration. Our approach is based on that of [15]. The use of hierarchy allows the router to avoid computational comple The Feng Shui[17] placement tool utilizes an aspect ratio to determine cut direction: if the height of a region divided by its Documents: Advanced Search Include Citations.

Add To MetaCart. Alpert, Andrew B. Citation Context Spanning Trees and Spanners by David Eppstein We survey results in geometric network design theory, including algorithms for constructing minimum spanning trees and low-dilation graphs. Abstract - Cited by 2 self - Add to MetaCart We survey results in geometric network design theory, including algorithms for constructing minimum spanning trees and low-dilation graphs.

Increased die areas, cell densities, routing layers, and net count all contribute to complex interconnect requirements, which can significantly deteriorate perfo Increased die areas, cell densities, routing layers, and net count all contribute to complex interconnect requirements, which can significantly deteriorate performance, and sometimes lead to unroutable solutions.

Congestion analysis and optimization must be performed early in the design cycle to improve routability. This paper presents a congestion estimation algorithm for a placed netlist.

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We propose a net-based stochastic model for computing expected horizontal and vertical track usage, which considers routing blockages. The main advantages of this algorithm are accuracy and fast runtime.

We show that the congestion estimated by this algorithm correlates well with postroute congestion, and show experimental results of subsequent. Sakallah, Rob A. Boolean SAT-based routing transforms a routing problem into a Boolean SAT instance by rendering geometric routing constraints as an atomic Boolean function.

The generated Boolean function is satisfiable if and only if the corresponding routing is possible. Two different Boolean SAT-based routing models are analyzed: the track-based and the route-based routing constraint model.Monday, April 29th, to Opening Remarks.

Location: Fields Institute, Stewart Library. Large scale exhaustive correctness validation for geometry processing algorithms. Designing with data in architecture: Intention, performance, constructability. Black-Box Meshing and Simulation. Robot Ecologies: Cooperative making with larger groups of smaller machines.

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Alec Jacobson - University of Toronto. Fields Contact: Brittany Camp. Reimbursement Policies.

algorithms for the physical fabrication of shapes using 3

Read more here. Scheduled as part of Centre for Quantitative Analysis and Modelling. Stay up to date with our upcoming events and news by viewing our calendar. Mania Aghaei Meibodi. Christopher Batty. University of Waterloo. Mirela Ben Chen. Technion - Israel Institute of Technology. Francisca Gil-Ureta. Yotam Gingold. George Mason University.

Eitan Grinspun. Columbia University. Alec Jacobson. University of Toronto. Farhad Javid. Danny Kaufman.

algorithms for the physical fabrication of shapes using 3

David Levin. Jesse Louis-Rosenberg. Caitlin Mueller. Massachusetts Institute of Technology. Daniele Panozzo. New York University. Washington University. Jessica Rosenkrantz. Elissa Ross. Mesh Consultants. Ryan Schmidt.A fractal is a never-ending pattern. Fractals are infinitely complex patterns that are self-similar across different scales. They are created by repeating a simple process over and over in an ongoing feedback loop.

Driven by recursion, fractals are images of dynamic systems — the pictures of Chaos. Turtle graphics is a popular way for introducing programming to kids. It was part of the original Logo programming language developed by Wally Feurzig and Seymour Papert in Imagine a robotic turtle starting at 0, 0 in the x-y plane.

After an import turtle, give it the command turtle. Give it the command turtle. By combining together these and similar commands, intricate shapes and pictures can easily be drawn. The turtle module is an extended reimplementation of the same-named module from the Python standard distribution up to version Python 2.

This means in the first place to enable the learning programmer to use all the commands, classes and methods interactively when using the module from within IDLE run with the -n switch. The turtle module provides turtle graphics primitives, in both object-oriented and procedure-oriented ways.

algorithms for the physical fabrication of shapes using 3

Because it uses Tkinter for the underlying graphics, it needs a version of Python installed with Tk support. This code creates 20 you can change it in the source code snowflakes randomly of random size and color in random position of the screeen. This article is contributed by Subhajit Saha. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above. Writing code in comment?

Please use ide. To create Snowflake fractals using Python programming What are fractals A fractal is a never-ending pattern.In integrated circuit designphysical design is a step in the standard design cycle which follows after the circuit design. At this step, circuit representations of the components devices and interconnects of the design are converted into geometric representations of shapes which, when manufactured in the corresponding layers of materials, will ensure the required functioning of the components.

This geometric representation is called integrated circuit layout.

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This step is usually split into several sub-steps, which include both design and verification and validation of the layout. The inputs to physical design are i a netlist, ii library information on the basic devices in the design, and iii a technology file containing the manufacturing constraints. Physical design is usually concluded by Layout Post Processingin which amendments and additions to the chip layout are performed.

Each of the phases mentioned above has design flows associated with them. The physical design flow uses the technology libraries that are provided by the fabrication houses. These technology files provide information regarding the type of silicon wafer used, the standard-cells used, the layout rules like DRC in VLSIetc.

Typically, the IC physical design is categorized into full custom and semi-custom design. The main steps in the ASIC physical design flow are:. These steps are just the basics. A more detailed physical design flow is shown below. Here you can see the exact steps and the tools used in each step outlined. The ASIC physical design flow uses the technology libraries that are provided by the fabrication houses.

Technologies are commonly classified according to minimal feature size. They may be also classified according to major manufacturing approaches: n-Well process, twin-well process, SOI process, etc. Physical design is based on a netlist which is the end result of the Synthesis process. This netlist contains information on the cells used, their interconnections, area used, and other details.

Typical synthesis tools are:. During the synthesis process, constraints are applied to ensure that the design meets the required functionality and speed specifications. Only after the netlist is verified for functionality and timing it is sent for the physical design flow. The second step in the physical design flow is floorplanning. Floorplanning is the process of identifying structures that should be placed close together, and allocating space for them in such a manner as to meet the sometimes conflicting goals of available space cost of the chiprequired performance, and the desire to have everything close to everything else.

Based on the area of the design and the hierarchy, a suitable floorplan is decided upon. Floorplanning takes into account the macros used in the design, memory, other IP cores and their placement needs, the routing possibilities, and also the area of the entire design. Floorplanning also determines the IO structure and aspect ratio of the design. A bad floorplan will lead to wastage of die area and routing congestion. In many design methodologies, area and speed are the subjects of trade-offs.

This is due to limited routing resources, as the more resources used, the slower the operation. Optimizing for minimum area allows the design both to use fewer resources, and for greater proximity of the sections of the design. This leads to shorter interconnect distances, fewer routing resources used, faster end-to-end signal paths, and even faster and more consistent place and route times.

Done correctly, there are no negatives to floorplanning. As a general rule, data-path sections benefit most from floorplanning, whereas random logic, state machines, and other non-structured logic can safely be left to the placer section of the place and route software.


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