Hybrid Framework for Structural Analysis: Integrating Topology Optimization, Adjacent Element Temperature-Driven Pre-Stress, and Greedy Algorithms

Basit Öğe Kaydı
dc.contributor.authorTeke, Ibrahim T.
dc.contributor.authorErtas, Ahmet H.
dc.date.accessioned2026-02-08T15:15:53Z
dc.date.available2026-02-08T15:15:53Z
dc.date.issued2025
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractThis study presents a novel hybrid topology optimization and mold design framework that integrates process fitting, runner system optimization, and structural analysis to significantly enhance the performance of injection-molded parts. At its core, the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles, leading to improvements in both mechanical strength and material efficiency. The design optimization is validated through a series of rigorous experimental tests, including three-point bending and torsion tests performed on key-socket frames, ensuring that the optimized designs meet practical performance requirements. A critical innovation of the framework is the development of the Adjacent Element Temperature-Driven Prestress Algorithm (AETDPA), which refines the prediction of mechanical failure and strength fitting. This algorithm has been shown to deliver mesh-independent accuracy, thereby enhancing the reliability of simulation results across various design iterations. The framework's adaptability is further demonstrated by its ability to adjust optimization methods based on the unique geometry of each part, thus accelerating the overall design process while ensuring structural integrity. In addition to its immediate applications in injection molding, the study explores the potential extension of this framework to metal additive manufacturing, opening new avenues for its use in advanced manufacturing technologies. Numerical simulations, including finite element analysis, support the experimental findings and confirm that the optimized designs provide a balanced combination of strength, durability, and efficiency. Furthermore, the integration challenges with existing injection molding practices are addressed, underscoring the framework's scalability and industrial relevance. Overall, this hybrid topology optimization framework offers a computationally efficient and robust solution for advanced manufacturing applications, promising significant improvements in design efficiency, cost-effectiveness, and product performance. Future work will focus on further enhancing algorithm robustness and exploring additional applications across diverse manufacturing processes.
dc.identifier.doi10.32604/cmc.2025.066086
dc.identifier.endpage264
dc.identifier.issn1546-2218
dc.identifier.issn1546-2226
dc.identifier.issue1
dc.identifier.scopus2-s2.0-105007805377
dc.identifier.scopusqualityQ1
dc.identifier.startpage243
dc.identifier.urihttps://doi.org/10.32604/cmc.2025.066086
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6021
dc.identifier.volume84
dc.identifier.wosWOS:001511597700001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTech Science Press
dc.relation.ispartofCmc-Computers Materials & Continua
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzWOS_KA_20260207
dc.subjectPlastic injection molding
dc.subject3D printing
dc.subjectthree-point bending
dc.subjecttensile test
dc.subjectadjacent element temperature-driven pre-stress algorithm
dc.subjectD-S-ER
dc.subjectS-D-S-ER
dc.subjectthermal expansion
dc.subjectgreedy algorithm
dc.titleHybrid Framework for Structural Analysis: Integrating Topology Optimization, Adjacent Element Temperature-Driven Pre-Stress, and Greedy Algorithms
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu