Optimal Expansion of Interface Dynamics for Substructure Coupling / (Record no. 613930)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01943nam a22001577a 4500 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Ali, Muhammad Junaid |
| 245 ## - TITLE STATEMENT | |
| Title | Optimal Expansion of Interface Dynamics for Substructure Coupling / |
| Statement of responsibility, etc. | Muhammad Junaid Ali |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Islamabad : |
| Name of producer, publisher, distributor, manufacturer | Islamabad : |
| Date of production, publication, distribution, manufacture, or copyright notice | 2025 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 251p. |
| Other physical details | soft copy |
| Dimensions | 30 |
| 500 ## - GENERAL NOTE | |
| General note | This thesis introduces a novel methodology for optimal interface expansion in dynamic<br/>substructuring, focusing on inaccessible and continuous interfaces. Unlike traditional<br/>approaches relying on modal parameters from Frequency Response Functions (FRFs), it<br/>employs a direct frequency-based method targeting interface Degrees of Freedom (DoFs),<br/>bypassing errors linked to modal identification. The System Equivalent Model Mixing<br/>(SEMM) technique is utilized to expand dynamics at the interface by integrating numerical<br/>and experimental models into a mixed model. Coherence is employed as a robust<br/>correlation metric, evaluating both phase and magnitude of FRFs. This research addresses<br/>optimal sensor placement (OSP) for effective expansion, testing nineteen stochastic<br/>metaheuristics categorized into swarm intelligence, surrogate algorithms, and physicsinspired methods to alleviate computational challenges of exhaustive searches. The<br/>Mountain Gazelle Optimizer (MGO) algorithm proved highly efficient for larger systems,<br/>while exhaustive search was effective for smaller cases. Validation involved cantilevered<br/>beam models and experimental setups, demonstrating strong correlation at interface DoFs.<br/>MGO proved to be 49 times faster than exhaustive search in identifying optimal sensor<br/>locations. The proposed methodology showcases practical applicability in achieving<br/>accurate dynamic expansions. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | MS Mechanical Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervisor: Dr. Muhammad Safdar |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="http://10.250.8.41:8080/xmlui/handle/123456789/53336">http://10.250.8.41:8080/xmlui/handle/123456789/53336</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Permanent Location | Current Location | Shelving location | Date acquired | Full call number | Barcode | Koha item type |
|---|---|---|---|---|---|---|---|
| School of Mechanical & Manufacturing Engineering (SMME) | School of Mechanical & Manufacturing Engineering (SMME) | E-Books | 06/26/2025 | 621 | SMME-TH-1138 | Thesis |