arXiv subjects

Mehmet Basaran

Publications and source records attributed to Mehmet Basaran.

3 recordsLinked to original sources

arXiv2025

Optimal Sizing and Material Choice for Additively Manufactured Compact Plate Heat Exchangers

Advances in additive manufacturing (AM) enable new opportunities to design compact heat exchangers (cHEXs) by leveraging flexible geometries to improve energy and material efficiency. However, it is well known that reducing size in counterflow cHEXs can degrade effectiveness due to axial heat conduction through the solid material, which depends strongly on material thermal conductivity and wall thickness. Understanding the interaction between fundamental heat transfer mechanisms and manufacturing constraints is essential for designing next generation compact thermal systems that fully exploit AM's shaping flexibility. This study investigates how material selection and AM thin wall limitations influence the maximum achievable power density in compact plate heat exchangers. An optimization framework evaluates six materials including plastic, austenitic steel, Al2O3, AlN, aluminum, and copper under fixed pressure drop and effectiveness, while accounting for AM specific thickness constraints and a minimum plate spacing to address fouling risks. Results show that copper consistently yields the lowest power density despite having the highest thermal conductivity, whereas plastic achieves the highest power density across most optimization scenarios. Without manufacturing or fouling constraints, plastic outperforms the baseline steel design by nearly three orders of magnitude. With uniform plate thickness or fouling constraints, the performance gap narrows, making plastic and austenitic steel comparable. When material specific thickness limits are applied, plastic again leads in compactness due to its superior thin wall manufacturability. These findings highlight that AM constraints strongly affect cHEX compactness and that lower conductivity materials can outperform metals such as copper in power dense heat exchanger designs.

cs.CE↗

arXiv2025

A Unit-Cell Shape Optimization Approach for Maximizing Heat Transfer in Periodic Fin Arrays at Constant Solid Temperature

Periodic fin structures are often employed to enhance heat transfer in compact cooling solutions and heat exchangers. Adjoint-based optimization methods are able to further increase the heat transfer by optimizing the fin geometry. However, obtaining optimal geometries remains challenging in general because of the high computational cost of full array simulations. In this paper, a unit cell optimization approach is presented that starts from recently developed macro-scale models for isothermal solid structures. The models exploit the periodicity of the problem to reduce the computational cost of evaluating the array heat transfer to that of a single periodic unit cell. By combining these models with a geometrically-constrained free-shape optimization approach, optimal fin geometries are obtained for the periodic fin array that maintain a minimal fin distance. Moreover, using an augmented Lagrangian approach, also the average pressure gradient and barycenter of the fin can be fixed. On a fictitious use-case, heat transfer increases up to 104 \% are obtained. When also flow rate is constrained in addition to maintain a high effectiveness, only up to 8 \% heat transfer increase is observed. Finally, the errors of the unit-cell optimization approach are investigated, indicating that with a good choice of cost functional formulation, errors of the approach as low as 1-2 \% can be obtained for the periodically developed part of the array. Finally, the entrance effect to the heat transfer is found to be non-negligible with a contribution of 10-15 \% for the considered fin array. This advocates for further research to extend the unit-cell models towards improved modeling of entrance effects.

cs.CE↗

arXiv2024

Fast Network Recovery from Large-Scale Disasters: A Resilient and Self-Organizing RAN Framework

Extreme natural phenomena are occurring more frequently everyday in the world, challenging, among others, the infrastructure of communication networks. For instance, the devastating earthquakes in Turkiye in early 2023 showcased that, although communications became an imminent priority, existing mobile communication systems fell short with the operational requirements of harsh disaster environments. In this article, we present a novel framework for robust, resilient, adaptive, and open source sixth generation (6G) radio access networks (Open6GRAN) that can provide uninterrupted communication services in the face of natural disasters and other disruptions. Advanced 6G technologies, such as reconfigurable intelligent surfaces (RISs), cell-free multiple-input-multiple-output, and joint communications and sensing with increasingly heterogeneous deployment, consisting of terrestrial and non-terrestrial nodes, are robustly integrated. We advocate that a key enabler to develop service and management orchestration with fast recovery capabilities will rely on an artificial-intelligence-based radio access network (RAN) controller. To support the emergency use case spanning a larger area, the integration of aerial and space segments with the terrestrial network promises a rapid and reliable response in the case of any disaster. A proof-of-concept that rapidly reconfigures an RIS for performance enhancement under an emergency scenario is presented and discussed.

eess.SP↗