Advances in Modeling and Simulation in Textile Engineering: New Concepts, Methods, and Applications

Cover
Recently Published and Upcoming Titles in The Textile Institute Book Series:
Advances in Modeling and Simulation in Textile Engineering: New Concepts, Methods, and
Applications
Copyright
Contents
Contributors
Preface
Acknowledgements
1. Overview of modeling and simulation in textile engineering
	1.1 Introduction
		1.1.1 Modeling
		1.1.2 Simulation
	1.2 The state of the art
		1.2.1 Textile engineering process chain
	1.3 Modeling and simulation in textile engineering
		1.3.1 Textile materials/processes
		1.3.2 Textile machinery
	1.4 Key steps and solution approach
		1.4.1 Step 1: numerical versus experimental data
		1.4.2 Step 2: establish important parameters
		1.4.3 Solution strategy; identify the model
		1.4.4 Simulation and postprocessing
		1.4.5 Validation and results analysis
	1.5 Typical challenges and limitations
	1.6 Further reading and reference
	References
2. Modeling classification of textile engineering problems
	2.1 Introduction
	2.2 Mathematical modeling
	2.3 Analytical modeling
	2.4 Computational and numerical modeling
		2.4.1 Theoretical and experimental studies of 3-D air flows
		2.4.2 Numerical modeling of fiber suspension flows
	2.5 Characterization of 3-D airflow dynamics in spinning technology
		2.5.1 Modeling the rotor spinning process
		2.5.2 Dimensional characteristics
			2.5.2.1 The rotor diameter
			2.5.2.2 The rotor slide wall angle
			2.5.2.3 The transfer channel dimensional characteristics
			2.5.2.4 Other geometrical dimensional characteristics
		2.5.3 Flow and spinning condition characteristics of the rotor spinning unit
			2.5.3.1 Velocity analysis
			2.5.3.2 Negative pressure
			2.5.3.3 Vortical structures and streamlines
			2.5.3.4 Rotor speed
	2.6 Characterization of turbulence and Reynolds number for flow-based problems in textile engineering
	2.7 Overview of turbulence models
		2.7.1 Classification of turbulent models
			2.7.1.1 Reynolds-averaged Navier–Stokes models
			2.7.1.2 Computation of fluctuating quantities
	2.8 Turbulence models
		2.8.1 Three main types of turbulence models
		2.8.2 Options for k–ϵ model
			2.8.2.1 Mixture turbulence model
			2.8.2.2 Per-phase turbulence model
			2.8.2.3 Dispersed turbulence model
	2.9 Case-based reasoning in textile engineering
		2.9.1 Case-based reasoning model development
	References
3. Neural networks in textile engineering
	3.1 Definition of artificial intelligence
	3.2 A brief history of artificial intelligence
	3.3 Biological background
		3.3.1 Buildup of a neuron
		3.3.2 Information transmission between neurons
	3.4 Models of artificial neural networks
		3.4.1 Perceptron
			3.4.1.1 Learning rule of a perceptron
			3.4.1.2 Perceptron convergence theorem
			3.4.1.3 Problem of linear divisibility
		3.4.2 Adaline and madaline networks
			3.4.2.1 Adaline network
			3.4.2.2 Madaline network
	3.5 Backpropagation algorithm
		3.5.1 Structure of the net
		3.5.2 Learning rule
		3.5.3 Structure and capacity
		3.5.4 Learning with the backpropagation algorithm
			3.5.4.1 Initialization of the weight factors
			3.5.4.2 Problems during the training
				Flat plateau
				Steep crevices
				Missing a minimum
			3.5.4.3 Optimizing the training
				Learning rate
				Momentum
				Constant factor added to derivative
				Weight decay
				Data submission
		3.5.5 Determination of suitable training parameters
			3.5.5.1 Learning rate σ
			3.5.5.2 Momentum factor
			3.5.5.3 Multistage training
			3.5.5.4 Example—texturing process
				Structure of the neural network
	3.6 Deep learning
		3.6.1 Feature engineering
		3.6.2 Network engineering
		3.6.3 Neural networks with graphic processing units
			3.6.3.1 Summary
	3.7 Other types of neural networks
		3.7.1 Simulated annealing
	3.8 Applications
		3.8.1 Pattern recognition
		3.8.2 Draw frame
		3.8.3 Hairiness of worsted yarns
		3.8.4 Draw-winding process
		3.8.5 Weaving process
		3.8.6 Yarn breakage rate during weaving
		3.8.7 Yarn shrinkage
		3.8.8 Spirality of cotton fabrics
		3.8.9 Textile fabric appearance
		3.8.10 Fabric inspection
		3.8.11 Design of airbag fabrics
		3.8.12 Thermal resistance and thermal conductivity of textile fabrics
		3.8.13 Protective textiles
		3.8.14 Emotion-based textile indexing
		3.8.15 Drapability of textiles
		3.8.16 Color prediction
		3.8.17 Smart carpet
		3.8.18 Applications in composites
		3.8.19 Other applications
	3.9 Practical advice
		3.9.1 Significance of input parameters
		3.9.2 Network structure and size—under- and overfitting
		3.9.3 Data base
		3.9.4 Recall stage
	3.10 Summary
	3.11 Web references of software tools
		3.11.1 Comprehensive lists of neural network software
		3.11.2 Free neural network software
		3.11.3 Commercial neural network software
		3.11.4 Other sources
	References
4. Genetic algorithms and evolution strategy in textile engineering
	4.1 Introduction
	4.2 Biological background
		4.2.1 Basics of genetics
		4.2.2 Evolution theory
		4.2.3 Chemical basics of inheritance
		4.2.4 Genotype and phenotype
	4.3 Mathematical model of the evolution strategy
		4.3.1 Basics
		4.3.2 Evolution strategies
			4.3.2.1 (1+1) – evolution strategy
			4.3.2.2 (μ+λ) – evolution strategy
			4.3.2.3 (μ, λ) – evolution strategy
			4.3.2.4 (μ/ρ λ) – evolution strategy
		4.3.3 Recombination
		4.3.4 Mutation
			4.3.4.1 Self-regulating mutative increment control
		4.3.5 Selection pressure and population waves
			4.3.5.1 Population size and life span
		4.3.6 Summary
	4.4 Genetic algorithms
	4.5 Comparison of evolutionary algorithms and iteration processes
		4.5.1 Speed
		4.5.2 Accuracy
		4.5.3 Reproducibility
		4.5.4 Boundary conditions
	4.6 Applications of evolutionary algorithms
		4.6.1 Texturing process
			4.6.1.1 Genotype and phenotype
			4.6.1.2 Number of individuals and life span
			4.6.1.3 Recombination factor
			4.6.1.4 Size of the gene pool
			4.6.1.5 Mutation increment
			4.6.1.6 Number of mutants
			4.6.1.7 Importance of mutants for the evolutionary progress
			4.6.1.8 Final algorithm and settings
			4.6.1.9 Reproducibility of the results
			4.6.1.10 Robustness
		4.6.2 Weaving machine
		4.6.3 Degumming of kenaf
		4.6.4 Assessing cotton quality
		4.6.5 Staple fiber spinning
		4.6.6 Smart production with optimized settings
		4.6.7 Carpet pattern design
		4.6.8 Reducing the weight of composite structures
		4.6.9 Determining optimum machining parameters for composite processing
		4.6.10 Optimizing model parameters for textile surface friction
		4.6.11 Improving the structure of an ANN
		4.6.12 Spinning of staple fiber yarns
		4.6.13 Other applications
	4.7 Practical advice
	References
	Web references of software tools
5. Turbulence models for simulation and modeling in textile engineering
	5.1 Introduction
		5.1.1 Analysis of the forces generating vorticity
		5.1.2 Introduction to turbulent flow
		5.1.3 Main characteristics and parameters associated to turbulent flow
		5.1.4 The Kolmogorov hypotheses and the energy cascade
		5.1.5 A general view of some different turbulence models
	5.2 Differential equations for turbulent flow
		5.2.1 Reynolds averaged Navier–Stokes K–ε turbulence model
		5.2.2 Large eddy simulation turbulence model
	5.3 Computational fluid dynamics simulation approach in textile engineering
		5.3.1 Examples of real problems of the textile world solved using computational fluid dynamics simulations
			5.3.1.1 Computational fluid dynamics simulations designed to optimize the transfer channel shape and dimensions used in rotor spinn ...
			5.3.1.2 Computational fluid dynamics study of flow around drafting cylinders used in pneumatic spinning
	5.4 Machine design modification
		5.4.1 Machine design and modification from machine perspective
		5.4.2 Machine design and modification from material processing perspective
		5.4.3 Ring spinning technology
			5.4.3.1 Simple steps to implement a successful spinning simulation using computational fluid dynamics approach
			5.4.3.2 Computational fluid dynamics simulations on ring spinning
		5.4.4 Open-end spinning technology
		5.4.5 Computational fluid dynamics model assumptions of the dual-feed rotor spinning unit
	5.5 Conclusion
	References
	Further reading
6. Modeling and simulation applications in yarn formation technology
	6.1 Introduction
	6.2 Twist propagation simulation
		6.2.1 Sliver model generation
		6.2.2 Sliver generation
		6.2.3 Algorithm implementation process
		6.2.4 Sliver generation flowchart
	6.3 Step-by-step model generation and simulation
		6.3.1 Twisting method
		6.3.2 Simulation results
		6.3.3 Configurational comparison and simulation verification
	6.4 Comparison and verification of staple yarn shape
		6.4.1 Twisting device
		6.4.2 Analysis of twisting process
	6.5 Yarn formation optimization on a compact spinning with lattice apron
		6.5.1 Three-dimensional model of the condensing zone
		6.5.2 Creating the geometry
		6.5.3 Mesh and setup and solution
		6.5.4 Design evaluation
			6.5.4.1 Design A-type and B-Type
			6.5.4.2 Boundary conditions
		6.5.5 Results analysis
		6.5.6 Possible ways to proceed with design optimization
	References
7. Fiber motion and fibrous material processes—modeling and simulation
	7.1 Introduction
	7.2 Fiber model overview
	7.3 A forced-based fiber model
	7.4 Fiber–wall and fiber–fiber interaction
	7.5 Fiber–air interaction
	7.6 Solution algorithm for fiber–air interaction
	7.7 Application of the fiber–air interaction model on a bended channel
	References
8. Classical challenges in modeling and simulation in textile engineering
	8.1 Introduction
	8.2 Three-dimensional modeling with computational fluid dynamics
	8.3 Modeling of chemical reactions in fibers
		8.3.1 Stabilization process in carbon fiber manufacturing
		8.3.2 Setup of a simulation model for the chemical reactions
		8.3.3 Solving the equations
	8.4 Conclusion
	References
	Further reading
9. Modeling of the electrospinning process
	9.1 Electrospinning
	9.2 Modeling of the spinning process
		9.2.1 Modeling of the electric field
		9.2.2 Solving method for obtained model
	9.3 Experimental setup
		9.3.1 Electric field
		9.3.2 Fiber model
	9.4 Validation
	References
10. Case studies of modeling and simulation in textile engineering
	10.1 Case study 1—modeling and simulation of nonwoven cards
		10.1.1 Nonwoven cards
		10.1.2 Model parameters
		10.1.3 Data acquisition
		10.1.4 Training and simulation
	10.2 Case study 2—simulation of heat transfer of heat protection textiles made of 3D spacer fabrics using latent heat accumulators
		10.2.1 Modeling of the simulation model/solution approach
		10.2.2 Evaluation of the simulation
	10.3 Summary
	Acknowledgments
	References
11. Modeling of reinforcement fibers and textiles
	11.1 Fiber-reinforced composites
	11.2 Simulation scales for reinforcement fibers and textiles
	11.3 Microscale simulations
	11.4 Beam element models
	11.5 Continuum element models
	11.6 Multichain digital element models
	11.7 Representative volume element at the microscale
	11.8 Mesoscale simulations
	11.9 Application of mesoscale modeling
	11.10 Mesoscale model for the acquisition of material properties
	11.11 Macroscale models
	11.12 The challenges of draping
	11.13 The goal of draping simulations
	11.14 Current models and approaches for the simulation of draping
	11.15 Preparation of the material data for the simulation model
	11.16 Kinematic draping simulation
	11.17 Finite element based draping simulations
	11.18 Example and evaluation for a finite element draping simulation
	Acknowledgment
	References
	Further reading
12. Modeling and analysis of laminated composites: classical and contemporary approaches
	12.1 Design methodology for composites
	12.2 Nomenclature and definitions
		12.2.1 Coordinate systems
		12.2.2 Contracted notation
		12.2.3 Generalized Hooke’s law
		12.2.4 Transformation matrix
		12.2.5 Material symmetry and anisotropy
		12.2.6 Orthotropic materials
	12.3 Laminate nomenclature (some of the basic definitions)
	12.4 Conventional techniques used to analyze composite laminates
		12.4.1 Netting analysis
		12.4.2 Classical lamination theory
			12.4.2.1 Constitutive equations in classical lamination theory
		12.4.3 Carpet plots
	12.5 Advancements to classical lamination theory
	12.6 Failure analysis
		12.6.1 Failure theories
	12.7 Interlaminar failure analysis
		12.7.1 Delamination
		12.7.2 Linear elastic fracture mechanics
			12.7.2.1 Energy balance
			12.7.2.2 Griffith’s energy balance
			12.7.2.3 Stress intensity factor
		12.7.3 Elastic–plastic fracture mechanics
		12.7.4 J-integral: obtaining energy release rate (J) from experiment
		12.8.5 Derivation of the cohesive law from the J integral
		12.7.6 Experimental results
	12.8 Numerical implementation of damage and failure
	12.9 Special case: woven fabrics
	Acknowledgment
	References
13. Simulation and modeling of the braiding process
	13.1 Simulation of the braiding process
		13.1.1 Basics of the radial braiding process
		13.1.2 Simulation in product development
		13.1.3 State of the art in braiding process simulation approaches
			13.1.3.1 Analytical method
			13.1.3.2 Kinematic simulation
				Conclusion
			13.1.3.3 Finite element simulation
		13.1.4 Comparison of existing braiding process simulations using finite element method
	13.2 Time-efficient modeling and simulation
		13.2.1 Model simplification
			13.2.1.1 Roving model
				Element type
				Mass scaling
				Element size and number
				Modulus of elasticity
		13.2.2 Bobbin model
			13.2.2.1 Restoring force
			13.2.2.2 Thread reservoir
			13.2.2.3 Bobbin system
		13.2.3 Contact model
			13.2.3.1 Contact types and algorithms
			13.2.3.2 Contact discretization
			13.2.3.3 Slide formulation
			13.2.3.4 Contact friction
		13.2.4 Braided ring and braided core model
		13.2.5 Multithread model
	References
14. Prediction and modeling of fabric properties from yarn and fabric structure
	14.1 Introduction
	14.2 Differences in mechanical properties between continuous elastic bodies and fiber assemblies
	14.3 Mechanical properties of yarn and measuring method
	14.4 Prediction of isotropic bending properties of woven fabric
	14.5 Evaluation of fabric shear
	14.6 Fabric shear modeling
	14.7 Fabric weave and texture characterization and prediction based on yarn characteristics
	14.8 Main steps in texture characterization
		14.8.1 Image acquisition
		14.8.2 Image processing
		14.8.3 Implement dictionary learning algorithm (discrete cosine transform)
		14.8.4 Woven fabric texture representation
		14.8.5 Selection of dictionary size
	References
15. Theoretical formulation and modeling of textile-reinforced concrete
	15.1 Introduction
	15.2 Textile-reinforced concrete structural overview
	15.3 Factors to consider in textile-reinforced concrete theoretical formulation and modeling
		15.3.1 Structural geometry
		15.3.2 Global failure analytics
		15.3.3 Concrete crack behavior
		15.3.4 Load deflection behavior
		15.3.5 Numerical and analytical analysis tools
	15.4 Bonding behavior modeling
	15.5 Theoretical shear and axial compression mechanism of textile-reinforced concrete
	15.6 Heat transfer and temperature effects in textile-reinforced concretes
	15.7 Analytical modeling
	15.8 Existing models of different textile-reinforced concrete structures
	15.9 3D modeling of textile-reinforced concretes’ maximum deformation and stress
	15.10 Textile-reinforced concretes for different applications
	15.11 Conclusion and prospects
	References
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	K
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
	Y
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