arXiv subjects

Musaddiq Al Ali

Publications and source records attributed to Musaddiq Al Ali.

4 recordsLinked to original sources

arXiv2026

Adaptive Time Windows for Discrete Adjoint Topology Optimization of Unsteady Flows

Rather than prescribing an evaluation interval a priori, the proposed framework characterizes each evolving unsteady flow using a sequence of time windows. A consecutive-window convergence criterion is introduced to automatically identify a representative time window within its fully developed stage. The objective evaluation and discrete adjoint analysis are then carried out consistently over the identified representative time window. The framework is implemented using a regularized lattice Boltzmann method-based large-eddy simulation (LBM-LES) solver together with a partial bounce-back fluid-solid model. The consecutive-window convergence criterion is first validated using the backward-facing step flow. Cylinder-flow applications are then employed to investigate the influence of different flow regimes on the proposed framework. The wake-flow recovery problem verifies its effectiveness for unsteady topology optimization, while U-bend optimization further demonstrates its capability to identify and reorganize complex vortical structures.

math.OC↗

arXiv2026

Distortion-minimized de-homogenization for optimization of cell-size distribution in TPMS structures

This paper presents a homogenized topology optimization (TO) method for spatially optimizing cell-size distribution of triply-periodic minimal surface (TPMS) structures, with high accuracy in the optimized structural response after de-homogenization. To achieve this, we introduce a novel de-homogenization technique that directly minimizes the difference between the wavenumbers obtained from the target and actual size distributions. This minimization problem is efficiently solved as a typical Poisson's equation utilizing the discrete cosine transform. We first verify the proposed de-homogenization method through numerical examples, showcasing its capability in significantly reducing the known distortion of the de-homogenized TPMS structures from the conventional periodic modulation (PM) method. Then, we apply the proposed method to a stiffness maximization problem, to demonstrate its effectiveness in improving the structural response compared to the PM method. The proposed method successfully reduced the distortion of the de-homogenized structures compared to the PM method, leading to 0.8% difference in the strain energy compared to the homogenized model, as opposed to 63.6% difference in the PM method. The optimized structure from the proposed method shows a significant improvement in the strain energy by 50.1% compared to the uniform case in the FE analysis on the de-homogenized models, while the PM method results in a significant decrease of 45.8%. The experimental validation shows that the effective stiffness of the optimized structure from the proposed method is 54.2% higher than that of the uniform case, while the PM method results in a significant decrease by 77.3%. These results exhibit the proposed method effectively increases the accuracy of the de-homogenization, thereby maximizing the potential of the homogenized TO for the spatial cell-size optimization of TPMS structures.

math.OC↗

arXiv2024

Concurrent Multiphysics and Multiscale Topology Optimization for Lightweight Laser-Driven Porous Actuator Systems

In this research, multi-physics topology optimization is employed to achieve the detailed design of a lightweight porous linear actuation mechanism that harnesses energy through laser activation. A multiscale topology optimization methodology is introduced for micro- and macroscale design, considering energy dissipation via heat convection and radiation. This investigation meticulously considers the impact of heat dissipation mechanisms, including thermal conduction, convection, and radiation. Through various numerical cases, we systematically explore the influence of micro-scale considerations on porous design and understand the effects on the topology optimization process by incorporating various microstructural systems. The results demonstrate that porous actuator designs exhibit superior performance compared to solid actuator designs. This study contributes to advancing the understanding of multiscale effects in topology optimization, paving the way for more efficient and lightweight designs in the field of laser-activated porous actuators.

eess.SY↗

arXiv2023

Investigation of Applying Quantum Neural Network of Early-Stage Breast Cancer Detection

Due to the heavy burden on medical institutes and computer-aided image diagnostics (CAD) have been gaining importance in diagnostic medicine to aid the medical staff to attain better service for the patients. Breast cancer is a fatal disease that can be treated successfully if it is detected early. Quantum neural network (QNN) has been introduced by many researchers around the world and presented recently by research corporations such as Microsoft, Google, and IBM. In this paper, we are trying to answer the question of: whether can the QNN be an effective method for mass-scale early breast cancer detection. This paper is dedicated to drawing a baseline for examining QNN, and the results showed a promising opportunity to use it for mass-scale screening using a fully functional quantum computer.

q-bio.QM↗