THEORY OF YARN STRUCTURE by Prof. Bohuslav Neckář, Textile Department, IIT Delhi, New Delhi. Compression of fibrous assemblies

Similar documents
Calculation of the received voltage due to the radiation from multiple co-frequency sources

antenna antenna (4.139)

Uncertainty in measurements of power and energy on power networks

Sensors for Motion and Position Measurement

Comparative Analysis of Reuse 1 and 3 in Cellular Network Based On SIR Distribution and Rate

To: Professor Avitabile Date: February 4, 2003 From: Mechanical Student Subject: Experiment #1 Numerical Methods Using Excel

NATIONAL RADIO ASTRONOMY OBSERVATORY Green Bank, West Virginia SPECTRAL PROCESSOR MEMO NO. 25. MEMORANDUM February 13, 1985

Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms

Evaluate the Effective of Annular Aperture on the OTF for Fractal Optical Modulator

Control Chart. Control Chart - history. Process in control. Developed in 1920 s. By Dr. Walter A. Shewhart

熊本大学学術リポジトリ. Kumamoto University Repositor

ANNUAL OF NAVIGATION 11/2006

Walsh Function Based Synthesis Method of PWM Pattern for Full-Bridge Inverter

Modeling the Properties of Core-Compact Spun Yarn Using Artificial Neural Network

Webinar Series TMIP VISION

Modeling of cotton yarn hairiness using adaptive neuro-fuzzy inference system

Design Data 20M. Circular Precast Concrete Manholes

Adaptive Modulation for Multiple Antenna Channels

POLYTECHNIC UNIVERSITY Electrical Engineering Department. EE SOPHOMORE LABORATORY Experiment 1 Laboratory Energy Sources

Journal of Chemical and Pharmaceutical Research, 2016, 8(4): Research Article

ECE315 / ECE515 Lecture 5 Date:

High Speed ADC Sampling Transients

Generalized Incomplete Trojan-Type Designs with Unequal Cell Sizes

Performance Testing of the Rockwell PLGR+ 96 P/Y Code GPS receiver

Analysis and Optimization of the Performance of OFDM on Frequency- Selective Time-Selective Fading Channels

PRACTICAL, COMPUTATION EFFICIENT HIGH-ORDER NEURAL NETWORK FOR ROTATION AND SHIFT INVARIANT PATTERN RECOGNITION. Evgeny Artyomov and Orly Yadid-Pecht

Satellite Attitude Determination Using GPS Receiver Based on Wahba Cost Function

MTBF PREDICTION REPORT

Unit 1. Current and Voltage U 1 VOLTAGE AND CURRENT. Circuit Basics KVL, KCL, Ohm's Law LED Outputs Buttons/Switch Inputs. Current / Voltage Analogy

COMPARATIVE STUDY OF 4(8)-PATH AND 5(10)-PATH CONFIGURATIONS FOR ATT FLOW MEASUREMENTS IN CIRCULAR CONDUITS INTRODUCTION

Figure 1. DC-DC Boost Converter

Development of an UWB Rescue Radar System - Detection of Survivors Using Fuzzy Reasoning -

THE GENERATION OF 400 MW RF PULSES AT X-BAND USING RESONANT DELAY LINES *

Figure 1. DC-DC Boost Converter

CHAPTER 29 AN EXAMPLE OF THE MONTECARLO SIMULATIONS: THE LANGEVIN DYNAMICS

A Novel GNSS Weak Signal Acquisition Using Wavelet Denoising Method

Traffic balancing over licensed and unlicensed bands in heterogeneous networks

Beam quality measurements with Shack-Hartmann wavefront sensor and M2-sensor: comparison of two methods

1 GSW Multipath Channel Models

Research of Dispatching Method in Elevator Group Control System Based on Fuzzy Neural Network. Yufeng Dai a, Yun Du b

Effective Parameters for Helical Pole Climbing of the Wheel-based Modular Snake Robot

Ring Spun Yarn Parameters Impact on Composite Yarn Quality Model

N( E) ( ) That is, if the outcomes in sample space S are equally likely, then ( )

Tensile Behavior Simulation of Woven Fabric with Different Weave Pattern Based on Finite Element Method

Equivalent Circuit Model of Electromagnetic Behaviour of Wire Objects by the Matrix Pencil Method

Analytical Assessment of the Q-factor due to Cross-Phase Modulation (XPM) in Multispan WDM Transmission Systems

DETERMINATION OF WIND SPEED PROFILE PARAMETERS IN THE SURFACE LAYER USING A MINI-SODAR

STUDY ON LINK-LEVEL SIMULATION IN MULTI- CELL LTE DOWNLINK SYSTEM

Passive Filters. References: Barbow (pp ), Hayes & Horowitz (pp 32-60), Rizzoni (Chap. 6)

3. Pat t er n, Mold and Cor e Des ign

Range-Based Localization in Wireless Networks Using Density-Based Outlier Detection

The Selectivity of Halibut Gill Nets. Introduction

A Comparison of Two Equivalent Real Formulations for Complex-Valued Linear Systems Part 2: Results

A MODIFIED DIRECTIONAL FREQUENCY REUSE PLAN BASED ON CHANNEL ALTERNATION AND ROTATION

Laser Velocimetry. Biasing Errors and Corrections. von Karman Institute for Fluid Dynamics. Lecture Series

A MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM IN SPARSE LINEAR ANTENNA ARRAY SYNTHESIS

Micro-grid Inverter Parallel Droop Control Method for Improving Dynamic Properties and the Effect of Power Sharing

Circular(2)-linear regression analysis with iteration order manipulation

CELLULAR SYSTEM CAPACITY and PERFORMANCE IMPROVEMENT with SDMA

Calculation model for SFN reception and reference receiver characteristics of ISDB-T system

Electricity Network Reliability Optimization

On High Spatial Reuse Broadcast Scheduling in STDMA Wireless Ad Hoc Networks

Introduction to Coalescent Models. Biostatistics 666 Lecture 4

ph fax

A Current Differential Line Protection Using a Synchronous Reference Frame Approach

Insertion/Extraction Tool and Replacement Tip Kits [ ]

Modeling Power Angle Spectrum and Antenna Pattern Directions in Multipath Propagation Environment

@IJMTER-2015, All rights Reserved 383

STAR POWER BOM/BOQ SETTING IDEA 1 - TWIST & SHOUT

Chain Codes. Shape Representation and Description. Signatures. Polygonal Approximations

A New Type of Weighted DV-Hop Algorithm Based on Correction Factor in WSNs

Review: Our Approach 2. CSC310 Information Theory

An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks

Kinematics of a dedicated 6DOF Robot for Tele-echography

IIR Filters Using Stochastic Arithmetic

Cooperative Multicast Scheduling Scheme for IPTV Service over IEEE Networks

Robustness of the Prediction Filter in Differential Pulse Code Modulation System

NewYork. the 107th Convention 1999 September AN AUDIO ENGINEERING SOCIETY PREPRINT

Coverage Maximization in Mobile Wireless Sensor Networks Utilizing Immune Node Deployment Algorithm

AN ALGORITHM TO COMBINE LINK ADAPTATION AND TRANSMIT POWER CONTROL IN HIPERLAN TYPE 2

[Type text] [Type text] [Type text] Wenjing Yuan Luxun Art Academy of Yan an University Xi an, , (CHINA)

Impact of Interference Model on Capacity in CDMA Cellular Networks. Robert Akl, D.Sc. Asad Parvez University of North Texas

TECHNICAL NOTE TERMINATION FOR POINT- TO-POINT SYSTEMS TN TERMINATON FOR POINT-TO-POINT SYSTEMS. Zo = L C. ω - angular frequency = 2πf

Optimization Frequency Design of Eddy Current Testing

Particle Filters. Ioannis Rekleitis

IEE Electronics Letters, vol 34, no 17, August 1998, pp ESTIMATING STARTING POINT OF CONDUCTION OF CMOS GATES

An Accurate UWB Radar Imaging Method Using Indoor Multipath Echoes for Targets in Shadow Regions

JOURNAL OF TEXTILES AND POLYMERS, VOL. 6, NO. 1, JANUARY

Introduction to Coalescent Models. Biostatistics 666

Digital Transmission

Application of Intelligent Voltage Control System to Korean Power Systems

29. Network Functions for Circuits Containing Op Amps

Product Information. Gripper for small components EGP

Characterization of GPS Carrier Phase Multipath

New Measurement Methods for Anechoic Chamber Characterization

Dynamic Optimization. Assignment 1. Sasanka Nagavalli January 29, 2013 Robotics Institute Carnegie Mellon University

Priority based Dynamic Multiple Robot Path Planning

Energy Efficiency Analysis of a Multichannel Wireless Access Protocol

A Perceptual Model for Sinusoidal Audio Coding Based on Spectral Integration

Safety and resilience of Global Baltic Network of Critical Infrastructure Networks related to cascading effects

Transcription:

THEORY OF YARN STRUCTURE by Prof. Bohuslav Neckář, Textle Department, IIT Delh, New Delh. Compresson of fbrous assembles Q1) What was the dea of fbre-to-fbre contact accordng to van Wyk? A1) Accordng to van Wyk, If 2 non-materal cylnders were penetrated mutually, then the materal fbers would create the contact. Q2) State the relatonshp between the densty of contacts and the packng densty of a fbrous assembly? A2) The densty of fbre-to-fbre contacts n a fbrous assembly s drectly proportonal to the square of the packng densty of the assembly. Q3) State the relatonshp between the mean dstance between adjacent contacts and the packng densty of a fbrous assembly? A3) The mean dstance between adjacent contacts n a fbrous assembly s nversely proportonal to the packng densty of the assembly. Q4) State the relatonshp between the compressve pressure and the packng densty of a fbrous assembly? A4) The compressve pressure s drectly proportonal to the cube of the packng densty of the fbrous assembly. Q5) What are the major problems of van Wyk s theory of compresson of fbrous assembly? A5) The two major problems of van Wyk s theory of compresson of fbrous assembly are 1) The packng densty cam be greater than one when the compressve pressure s greater than the coeffcent k p, whch s logcally non-sense and 2) The theory does not hold good for relatvely hgh values of packng densty. Q6) State the basc dea behnd generalzaton of C. M. van Wyk s theory. A6) C. M. van Wyk s theory assumes purely pont contact between fbres n a fbrous assembly, therefore, ts result could be accepted, but only for compressble 1

(deformable) part of volume. Ths compressble volume s the dfference between the total volume of the fbrous assembly and summaton of volumes of all noncompressble ( stones ) volumes. Pores among fbres Q1) State what are the parameters of pores n a fbrous assembly that are ndependent of the choce of fctve borders? A1) The three parameters are total pore volume, total pore surface area, and surface area per unt volume of pore Q2) Defne conventonal pore. A2) Conventonal pore has crcular cross-secton. Q3) Why conventonal pores are frequently used? A3) All parameters of conventonal pores are ndependent of the choce of fctve borders. Q4) What s the basc assumpton behnd dervng the expressons for pore parameters n terms of fbre parameters? A4) The basc assumpton s total pore surface area s equal to total fbre surface area n a fbrous assembly. Q5) What are the fbre parameters that decde the heght of wckng? A5) The fbre parameters are dameter of fbre and shape of fbre cross-secton. Orentaton of fbres Q1) What s the value of probablty densty functon of sotropc fbre orentaton n plane? A1) 1/ 2

Q2) What probablty dstrbuton does the tangent of fbre nclnaton angle follow? A2) Cauchy s dstrbuton. Q3) Defne coeffcent k n? A3) The coeffcent k n s defned by the rato of mean sectonal area of fbre to the cross-sectonal area of fbre. Q4) What s the value of mechancal utlzaton of fbre n a perfectly parallel fbre bundle? A4) 1 Mechancs of parallel fbre bundles Q1) Whch theory can explan the fact that after addton of fbers havng hgher tenacty, the tenacty of the resultng bundle can decrease? A1) Hamburger s theory of mechancs of blended fbre bundle can explan ths. Q2) Defne fbre strength utlzaton coeffcent. A2) The fbre strength utlzaton coeffcent s defned by the rato of the bundle strength related to one fbre to the mean fbre strength. Q3) Defne fbre breakng stran utlzaton coeffcent. A3) The fbre breakng stran utlzaton coeffcent s defned by the rato of the breakng stran of the bundle to the mean breakng stran of fbre. Q4) What s the fbre parameter that determnes both the fbre strength utlzaton coeffcent and fbre breakng stran utlzaton coeffcent? A4) The fbre parameter s the coeffcent of varaton of fbre breakng stran. Q1) Classfy yarn models as shown below. Modellng of nternal yarn geometry Functons m 0 m 0 z 0?? z const.?? z const.? 3?

A1) The yarn models are classfed as follows. Functons m 0 m 0 z 0 Parallel fbre bundle Entangled fbre bundle z const. Helcal model Radal mgraton z const. Twsted mgraton General mgraton Q2) State the assumptons of deal helcal model of fbres n yarn. A2) The assumptons are: 1) The fbres follow helcal path n yarn, 2) All helxes have the same sense of rotaton, 3) All helxes have the common axs, that s, yarn axs, 4) All fbres have the same col heght, and 5) The packng densty s constant at all places nsde the yarn. Q3) State whether t s true that the coeffcent k n ncreases wth the ncrease n twst angle of surface fbres. A3) False, the coeffcent k n decreases wth the ncrease n twst angle of surface fbres. Q4) What s the lmt value of yarn retracton accordng to deal helcal model under the assumpton that the fbre volume does not change wth twst? A4) 0.5 Q5) What s the lmt value of angle of twst of surface fbres accordng to deal helcal model under the assumpton that the fbre volume does not change wth twst? A5) 70.5 degree Q6) What are the parameters that determne the tensle force utlzaton coeffcent n twsted yarn? A6) Angle of twst of surface fbres and yarn contracton rato. Q7) Why Treloar s model of radal fbre mgraton n not consdered to be enough precse? 4

A7) Treloar s dea of regular path of fbres n yarn s not precse. The fbre path s n fact random. Hence the number of fbre elements ntersectng the yarn cylnder at any radus on one fber per unt length of yarn s not constant. Relaton between yarn count, twst, packng densty and dameter Q1) State the assumpton of Koechln s model? A1) Koechln studed the yarns produced from same fbrous materal usng same technology for analogcal end-uses. He assumed that 1) the packng densty s a functon of twst ntensty only and 2) the twst ntensty of yarns of dfferent fnenesses (counts) shall be same. Q2) Whch of the assumptons s consdered not to be enough precse? A2) Koechln s frst assumpton s not enough precse. The twst ntensty s not a functon of packng densty only, t depends on yarn count too. A stochastc model of yarn harness Q1) Why the sngle exponental model of yarn harness does not correspond well wth the results of experments? A1) In realty, there are two types of hars n yarn. One type of hars s composed of shorter fbers and s concentrated manly round the yarn surface (body); ths can be magned as moos on the yarn. Second type of hars s composed of longer flyng fbers. Ths ntutvely suggested dea would make the double exponental model of yarn harness closer to the realty. Bundle theory of yarn unevenness Q1) State the general assmptons of Martndale s model of slver unevenness. A1) The general assumptons are: 1) The fbres are straght and parallel to the slver axs, 2) They have the same length, and 3) They are postoned along the slver ndvdually and randomly. 5

Q2) Whch s hgher: coeffcent of varaton of fbre fneness or coeffcent of varaton of fbre dameter? A2) The coeffcent of varaton of fbre fneness s two tmes hgher than the coeffcent of varaton of fbre dameter. Q3) Why the model of Martndale s consdererd not to be enough correct? A3) The ndex of rregularty n actual slver s much hgher than that calculated from Martndale s model. The reason s that the assumpton of ndvdual postonng of fbres n slver s not correct. Yarn strength as a stochastc process Q1) What s the prncple of the weakest lnk theory? A1) Let us assume that a longer secton of yarn s dvded nto n number of smaller sectons. The prncple of the weakest lnk theory states that the longer secton must not break untl any of n shorter sectons breaks. Q2) State the assumptons of Perce s model of strength versus length of yarn. A2) Perce s model s based on the consderaton that a longer yarn secton s composed of many shorter sectons of equal length. The three assumptons are: 1) The probablty of breakage of one secton of length s ndependent of the probablty of breakage of any other secton, 2) The longer secton must not break untl any of the shorter sectons breaks, and 3) The strength of shorter secton follows normal dstrbuton. Q3) Why Perce s model s not consdered to be enough precse? A3) The strength versus length relaton n actual yarn does not correspond well to that of Perce s model. Ths s because the assumpton of strength ndependency s not true n realty. 6