Description
Materials Selection for Natural Fiber Composites covers the use of various tools and techniques that can be applied for natural fiber composite selection to expand the sustainable design possibilities and support cleaner production requirements. These techniques include the analytical hierarchy process, knowledge-based system, Java based materials selection system, artificial neural network, Pugh selection method, and the digital logic technique. Information on related topics, such as materials selection and design, natural fiber composites, and materials selection for composites are discussed to provide background information to the main topic.
Current developments in selecting the natural fiber composite material system, including the natural fiber composites and their constituents (fibers and polymers) is the main core of the book, with in detailed sections on various technical, environmental and economic issues to enhance both environmental indices and the industrial sustainability theme.
Recent developments on the analytical hierarchy process in natural fiber composite materials selection, materials selection for natural fiber composites, and knowledge based system for natural fiber composite materials selection are also discussed.
- Focuses on materials selection for natural fiber composites
- Covers potential tools and techniques, such as analytical hierarchy process, knowledge-based systems, Java-based materials selection syste
Chapter
Chapter 2: Natural fiber composites
2.2. Advantages and disadvantages of natural fiber composites
2.3. Mechanical properties of natural fiber composites
2.4. Other properties of natural fiber composites
2.5. Applications of natural fiber composites
2.5.1. Automotive and aerospace applications
2.5.2. Medical applications
2.5.3. Electrical and electronic market
2.5.5. Other applications
2.6. Challenges in developing natural fiber composites for wide industrial applications
Chapter 3: Materials selection
3.1. Materials selection and design
3.2. The needs for materials selection
3.3. Tools and techniques of material selection
3.3.1. Materials screening techniques
3.3.2. Materials comparing and choosing techniques
3.4. Conventional materials selection techniques
3.4.1. Cost per unit property method
3.4.2. Questionnaire method
3.4.3. Materials in products selection methods
3.6. Advanced materials selection techniques
3.6.1. Artificial intelligence methods
3.6.1.1. Computer-aided materials selection systems
3.6.1.2. Knowledge-based systems
3.6.1.3. Case-based reasoning
3.6.3. Genetic algorithm and neural network
3.6.4. Simple additive weighting method
3.6.5. Optimization methods
3.6.5.1. Mathematical programming
3.6.5.2. Computer simulation
3.6.5.3. Genetic algorithm
3.6.6. Multiple attribute decision making methods (MADM)
3.6.6.2. Fuzzy multi-criteria decision-making methods
3.6.6.3. Individual methods in MADM
3.6.7. Multiple objective decision making methods (MODMM)
3.6.7.1. Multi-attribute utility analysis (MAUA)
3.6.7.2. Individual methods in MODM
Chapter 4: Material selection for composites
4.1. Various issues in materials selection in composites
4.2. Selection of matrices
4.2.1. Selection of matrices for general composites
4.2.2. Selection of matrices for the natural fiber reinforced polymeric based composites
4.3.1. Selection of synthetic fibers
4.3.2. Selection of natural fibers
4.3.2.1. Sources of natural fibers
4.3.2.2. Quality of natural fibers
4.3.3. Nanocrystalline cellulose
4.3.4. Considering issues for selecting the natural fibers
4.4. Research work on materials selection for composites
4.5. Advanced techniques in composite materials selection
Chapter 5: Material selection of natural fiber composites
5.1. The need for materials selection of natural fiber composites
5.2. Traditional approaches
5.3. Proper assessment of natural fibers capabilities
5.3.1. Comparison of natural fibers for potential industrial use
5.3.2. Comparison criteria
5.3.2.2. (Length/diameter) ratio
5.3.2.3. Thermal conductivity
5.3.2.4. Cellulose and lignin content
5.3.2.5. Availability of natural fibers
5.3.2.7. Elongation to break
5.3.2.8. Specific modulus of elasticity to cost ratio
5.3.2.9. Governmental support and social positive view
5.4. Evaluating polymer matrices for natural fibers
5.5. Predicting the potential of new fiber types for industrial applications
5.5.1. Combined multicriteria evaluation stage technique
5.5.1.1. Single evaluation criterion comparison in the CMCEST approach
5.5.1.2. Combined double-evaluation criterion (CDEC) in the CMCEST approach
5.5.1.3. Combined triple-evaluation criterion in the CMCEST approach
5.5.2. Moisture content criterion approach
5.5.2.2. Results agreements with MCC method
5.6. Issues and challenges
5.6.1. Estimating the elastic properties of composites
5.6.2. Plant fiber processing
5.6.2.1. Plant growth and fiber extraction
5.6.2.2. Fiber surface modification
5.6.2.3. Fiber volume fraction
5.6.3. Reinforcement geometry and orientation
5.6.3.1. Length efficiency factors
5.6.3.2. Orientation distribution factors
5.6.4. Natural fiber/nanoclay hybrid composites
5.6.5. Bio-based resins as matrices
Chapter 6: Material selection of natural fiber composites using the analytical hierarchy process
6.1. Background of analytical hierarchy process
6.2. Appropriateness of analytical hierarchy process for natural fiber composite selection
6.3. Pairwise comparison under uncertainty environment for bio-based materials
6.4. Selecting natural fibers for a particular application under conflicting criteria using analytical hierarchy process
6.5. Selecting polymers for bio-based materials under conflicting criteria using analytical hierarchy process
6.6. Evaluating various natural fiber composites under conflicting criteria using analytical hierarchy process
6.7. Optimizing the reinforcement conditions of natural fiber composites using analytical hierarchy process
6.8. Sensitivity analysis of the selection models using analytical hierarchy process
Chapter 7: Material selection of natural fiber composites using other methods
7.1. Java-based materials selection
7.2. Knowledge-based system
7.3. Digital logic technique
7.4. Quality function deployment for environment
7.5. Pugh selection method
7.6. Artificial neural network
Materials Selection for Natural Fiber Composites
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