Design of Heating Coils Based on Space-Filling Fractal Curves for Highly Uniform Temperature Distribution

MRS Advances ◽  
2020 ◽  
Vol 5 (18-19) ◽  
pp. 1007-1015
Author(s):  
Karnati Kumar Sai Charan ◽  
Seshadri Reddy Nagireddy ◽  
Sumana Bhattacharjee ◽  
Aftab M Hussain
Keyword(s):  
Performance Indicator ◽  
Target Area ◽  
Temperature Uniformity ◽  
Hilbert Curve ◽  
Space Filling ◽  
Element Analysis ◽  
Heating Coil ◽  
Peano Curve ◽  
Heating Coils ◽  
Highly Uniform

AbstractHeating coils utilize the concept of resistive heating to convert electrical energy into thermal energy. Uniform heating of the target area is the key performance indicator for heating coil design. Highly uniform distribution of temperature can be achieved by using a dense metal distribution in the area under consideration, however, this increases the cost of production significantly. A low-cost and efficient heating coil should have excellent temperature uniformity while having minimum metal consumption. In this work, space-filling fractal curves, such as Peano curve, Hilbert curve and Moore curve of various orders, have been studied as geometries for heating coils. In order to compare them in an effective way, the area of the geometries has been held constant at 30 mm × 30 mm and a constant power of 2 W has been maintained across all the geometries. Further, the thickness of the metal coils and their widths have been kept constant for all geometries. Finite Element Analysis (FEA) results show Hilbert and Moore curves of order-4, and Peano curve of order-3 outperform the typical double-spiral heater in terms of temperature uniformity and metal coil length.

scholarly journals The Effect of Space-filling Curves on the Efficiency of Hand Gesture Recognition Based on sEMG Signals

2021 ◽  
Vol 12 (1) ◽  
pp. 23-31
Author(s):  
Panagiotis Tsinganos ◽  
Bruno Cornelis ◽  
Jan Cornelis ◽  
Bart Jansen ◽  
Athanassios Skodras
Keyword(s):  
Computer Vision ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Network Architectures ◽  
Hilbert Curve ◽  
Space Filling ◽  
Space Filling Curve ◽  
Space Filling Curves ◽  
Semg Signals

Over the past few years, Deep learning (DL) has revolutionized the field of data analysis. Not only are the algorithmic paradigms changed, but also the performance in various classification and prediction tasks has been significantly improved with respect to the state-of-the-art, especially in the area of computer vision. The progress made in computer vision has produced a spillover in many other domains, such as biomedical engineering. Some recent works are directed towards surface electromyography (sEMG) based hand gesture recognition, often addressed as an image classification problem and solved using tools such as Convolutional Neural Networks (CNN). This paper extends our previous work on the application of the Hilbert space-filling curve for the generation of image representations from multi-electrode sEMG signals, by investigating how the Hilbert curve compares to the Peano- and Z-order space-filling curves. The proposed space-filling mapping methods are evaluated on a variety of network architectures and in some cases yield a classification improvement of at least 3%, when used to structure the inputs before feeding them into the original network architectures.

scholarly journals Approximation and Analytical Studies of Inter-clustering Performances of Space-Filling Curves

2003 ◽  
Vol DMTCS Proceedings vol. AC,... (Proceedings) ◽  
Author(s):  
Ho-Kwok Dai ◽  
Hung-Chi Su
Keyword(s):  
Random Walk ◽  
Dimensional Space ◽  
Hilbert Curve ◽  
Space Filling ◽  
Space Filling Curve ◽  
Space Filling Curves ◽  
Order Curve ◽  
Cluster Distance ◽  
The Mean ◽  
Curve Family

International audience A discrete space-filling curve provides a linear traversal/indexing of a multi-dimensional grid space.This paper presents an application of random walk to the study of inter-clustering of space-filling curves and an analytical study on the inter-clustering performances of 2-dimensional Hilbert and z-order curve families.Two underlying measures are employed: the mean inter-cluster distance over all inter-cluster gaps and the mean total inter-cluster distance over all subgrids.We show how approximating the mean inter-cluster distance statistics of continuous multi-dimensional space-filling curves fits into the formalism of random walk, and derive the exact formulas for the two statistics for both curve families.The excellent agreement in the approximate and true mean inter-cluster distance statistics suggests that the random walk may furnish an effective model to develop approximations to clustering and locality statistics for space-filling curves.Based upon the analytical results, the asymptotic comparisons indicate that z-order curve family performs better than Hilbert curve family with respect to both statistics.

scholarly journals Tag-systems for the Hilbert curve

2007 ◽  
Vol Vol. 9 no. 2 ◽  
Author(s):  
Patrice Séébold
Keyword(s):  
Hilbert Space ◽  
Hilbert Curve ◽  
Space Filling ◽  
Space Filling Curve ◽  
Finite Approximations ◽  
Infinite Word ◽  
International Audience ◽  
Filling Curve

International audience Hilbert words correspond to finite approximations of the Hilbert space filling curve. The Hilbert infinite word H is obtained as the limit of these words. It gives a description of the Hilbert (infinite) curve. We give a uniform tag-system to generate automatically H and, by showing that it is almost cube-free, we prove that it cannot be obtained by simply iterating a morphism.

On the Behaviour of p-Adic Scaled Space Filling Curve Indices for High-Dimensional Data

2020 ◽  
Author(s):  
Patrick Erik Bradley ◽  
Markus Wilhelm Jahn
Keyword(s):  
Gray Code ◽  
High Dimensional ◽  
Affine Transformations ◽  
Hilbert Curve ◽  
Space Filling ◽  
Real World Data ◽  
Space Filling Curve ◽  
Indexing Method ◽  
Filling Curve ◽  
Hilbert Curves

Abstract Space filling curves are widely used in computer science. In particular, Hilbert curves and their generalizations to higher dimension are used as an indexing method because of their nice locality properties. This article generalizes this concept to the systematic construction of $p$-adic versions of Hilbert curves based on special affine transformations of the $p$-adic Gray code and develops a scaled indexing method for data taken from high-dimensional spaces based on these new curves, which with increasing dimension is shown to be less space consuming than the optimal standard static Hilbert curve index. A measure is derived, which allows to assess the local sparsity of a dataset, and is tested on some real-world data.

A Novel Z-Axis Capacitance Accelerometer with Highly Symmetrical 16-Beam Structure

2013 ◽  
Vol 562-565 ◽  
pp. 412-416
Author(s):  
Wei Li ◽  
Lu Feng Che ◽  
Xiao Lin Li ◽  
Jian Wu ◽  
Yue Lin Wang
Keyword(s):  
Proof Mass ◽  
Differential Capacitance ◽  
Wet Etching ◽  
Beam Structure ◽  
Element Analysis ◽  
Bias Stability ◽  
Maximum Range ◽  
Cross Axis ◽  
Highly Uniform ◽  
Micro Accelerometer

A novel highly symmetrical 16-beam sandwich structure Z-axis differential capacitance accelerometer is presented. In this design, the proof mass is suspended symmetrically by double-side of 16 straight beams with highly uniform dimension which can reduce the cross-axis sensitivity and rotational influences dramatically. Parameters of the beam-mass structure were analyzed and optimized by finite element analysis (FEA) software. The micro accelerometer is based on bulk-micromachining by DRIE and KOH anisotropic wet etching technologies. The beam-mass structure was released by anisotropic wet etching on both device layer sides simultaneously. The fabricated accelerometer was measured over the maximum range of 30g gravity field, results of measurement show that the close-loop sensitivity is 80mV/g, the nonlinearity is 0.27%, and the bias stability is 0.63mg for an hour.

A Novel Hybrid Heating Method for Elevated Temperature Mechanical Testing of Miniature Specimens

2016 ◽  
Author(s):  
Lin Li ◽  
Gracious Ngaile ◽  
Tasnim Hassan
Keyword(s):  
Elevated Temperature ◽  
Elevated Temperatures ◽  
Heating Process ◽  
Electric Resistance ◽  
Heating Method ◽  
Hybrid Heating ◽  
Testing Technology ◽  
Heating Coils ◽  
Highly Uniform ◽  
Material Tests

The lack of robust testing systems to generate uniform elevated temperatures on specimens in material tests is hindering the advancement of small specimen testing technology (SSTT). The purpose of this study is to develop a novel hybrid heating method combining coil heating and electric-resistance specimen heating to uniformly heat micro specimens in material tests. In a hybrid heating process, two heating coils are used to heat the local temperatures on the specimen ends, and electric current is conducted through the specimen to generate Joule heat and compensate the heat transfer effects of natural convection and radiation around the specimen center area. In this way, a highly uniform temperature distribution can be generated on the specimen between the heating coils. In this study, Thermal-Electrical and Transient Thermal FEA simulations are applied to analyze the temperature distributions and preheating times on the micro specimens under coil heating, electric-resistance specimen heating, and hybrid heating respectively. According to the simulation results, it can be concluded that hybrid heating method can provide the ability to generate highly uniform elevated temperature conditions on different micro tubular specimens with short preheating times.

Numerical Simulation of PC Steel Bar Induction Heating Process

2011 ◽  
Vol 228-229 ◽  
pp. 270-275
Author(s):  
Qian Zhe Zhao ◽  
Yi Bing Liu ◽  
Yan Ping Liu ◽  
Wei Song Zhou
Keyword(s):  
Numerical Simulation ◽  
Induction Heating ◽  
Active Power ◽  
Experimental Fact ◽  
Heating Process ◽  
Temperature Uniformity ◽  
Element Analysis ◽  
Heating Efficiency ◽  
Steel Bar ◽  
Main Factors

Based on electromagnetic and temperature field models of nonlinear ferromagnetic materials, this paper conducts a finite element analysis of the induction heating process of PC steel bar, thus obtaining the change curves of temperature, active power, heating efficiency and power density. The main factors and mechanisms affecting the heating efficiency and the temperature uniformity are analyzed systematically by a combination of the simulation result and the experimental fact. This work is expected to contribute significantly for optimizing the key parameters of induction heating production of PC steel bar.

Space Filling Curves: Its Design and Fabrication for Extrusion Based SFF Systems

2005 ◽  
Author(s):  
Binil Starly ◽  
Lauren Shor ◽  
Wei Sun ◽  
Andrew Darling
Keyword(s):  
Solid Freeform Fabrication ◽  
Feasibility Studies ◽  
Tissue Scaffolds ◽  
Layered Manufacturing ◽  
Hilbert Curve ◽  
Space Filling ◽  
Interior Space ◽  
Freeform Fabrication ◽  
Space Filling Curves

Scaffolds with designed interior pore architecture, predefined porosity and a well interconnected predetermined network has been the most favored design approach for tissue engineering applications. Solid freeform fabrication technologies have provided the capability of fabricating tissue scaffolds with desired characteristics due to its integration with CAD enabled tools. However, currently the interior macro pore design of scaffolds have been limited to simple regular shapes of either squares or circles due to limited CAD capability. In this paper we seek to enhance the design of the scaffold architecture by using space filling curves within its interior space. The process involves: definition and characterization of space filling curves such as the Hilbert Curve and Sierpinski Curves, applying the principle of layered manufacturing to determine the scaffold individual layered process planes and layered contours; Feasibility studies applying the curve generators to sample models and the generation of fabrication planning instructions for extrusion based SFF systems is presented.

Sign in / Sign up

Export Citation Format

Share Document