| 000 -LEADER |
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| fixed length control field |
03026nam a22001577a 4500 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
621 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Masud, Manzar |
| 245 ## - TITLE STATEMENT |
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| Title |
Investigation of Bio-Hybrid Fiber Reinforced Composites Under Impact Loading / |
| Statement of responsibility, etc. |
Manzar Masud |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
Islamabad : |
| Name of producer, publisher, distributor, manufacturer |
SMME- NUST; |
| Date of production, publication, distribution, manufacture, or copyright notice |
2025. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
224p. |
| Other physical details |
Soft Copy |
| Dimensions |
30cm |
| 500 ## - GENERAL NOTE |
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| General note |
The integration of natural and synthetic fibers in bio-hybrid fiber-reinforced polymer<br/>(HFRP) composites is gaining prominence in high-performance industries such as<br/>aerospace and automotive, driven by the demand for materials that balance mechanical<br/>performance, sustainability, and cost-effectiveness. This research adopts a dual approach,<br/>combining experimental testing with machine learning (ML) to investigate and optimize<br/>the mechanical performance of five composite laminates, including a pure carbon laminate<br/>and four carbon–flax HFRP configurations with symmetric and asymmetric stacking<br/>sequences. All laminates were evaluated through uniaxial tensile, compressive, lowvelocity impact (LVI) at energies from 30 to 75 J, and compression-after-impact (CAI)<br/>testing. The symmetric BH3 layup, with evenly distributed flax layers, demonstrated<br/>superior performance with only a 9% reduction in tensile strength compared to the carbon<br/>baseline while showing a 37.71% increase in failure strain, indicating enhanced energy<br/>absorption. Under compression, BH3 retained 86% of the carbon laminate’s strength and<br/>81% of its modulus. In impact resistance, BH3 withstood energies up to 75 J, surpassing<br/>the carbon configuration. To evaluate performance and economic trade-offs, two indices<br/>were introduced i.e., the Impact Performance Index (IPI) and the Cost-Effectiveness Index<br/>(CEI). BH3 achieved the highest impact performance and a CEI comparable to that of the<br/>carbon laminate. Complementing the experimental work, an ML framework was employed<br/>using stacking sequence and impact energy as inputs, and peak impact force, damage area,<br/>and damage extension as outputs. Six algorithms were assessed, including decision tree<br/>(DT), random forest (RF), deep neural networks (DNN) with Adam and stochastic gradient<br/>descent (SGD) optimizers, and recurrent neural networks (RNN) with the same optimizers.<br/>The DT model with depth 8 and 28 leaf nodes performed best for peak force prediction,<br/>while the model with depth 6 and 23 leaf nodes was most accurate for damage area. An<br/>RNN with SGD and four hidden layers containing 70 neurons achieved the highest<br/>accuracy for damage extension. This integrated methodology demonstrates the potential of<br/>HFRP laminates to deliver high mechanical performance, improved damage tolerance, and<br/>enhanced sustainability for structural and impact-critical applications across automotive,<br/>aerospace, sporting, and construction sectors. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
PhD in Mechanical Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Supervisor : Dr. Aamir Mubashar |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
<a href="http://10.250.8.41:8080/xmlui/handle/123456789/54809">http://10.250.8.41:8080/xmlui/handle/123456789/54809</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
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| Koha item type |
Thesis |
