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Integrating artificial intelligence and machine learning with numerical simulation for enhanced thermal performance of ternary nano-fluid
Mohib Hussain and others
Journal of Computational Design and Engineering, qwaf041, https://doi.org/10.1093/jcde/qwaf041
The motivation for this investigation stems from a perceived gap in the vast literature on nanofluids, specifically in relation to their interactions with different surfaces and their numerical simulation. The main objective of this study is to effectively utilize novel machine learning (ML) and ...
Frequency-enhanced neural networks with a hybrid spall-size estimator for bearing fault diagnosis
Mikyung Hwang and others
Journal of Computational Design and Engineering, qwaf040, https://doi.org/10.1093/jcde/qwaf040
In the fault diagnosis of rolling element bearings (REBs), spall size is a typical indicator of fault severity. Conventionally, spall size estimation relies on expert-knowledge-based or data-driven approaches. Expert-knowledge-based approaches require accurate assumptions about spall-excited ...
BRAN2SAT: Redundant satisfiability logic in Lyapunov-based discrete Hopfield neural network
Binbin Yang and others
Journal of Computational Design and Engineering, Volume 12, Issue 4, April 2025, Pages 185–204, https://doi.org/10.1093/jcde/qwaf039
This study introduces a novel non-systematic logical structure, termed B-type Random 2-Satisfiability, which incorporates non-redundant first- and second-order clauses, as well as redundant second-order clauses. The proposed logical rule is implemented in the discrete Hopfield neural network using ...
Trajectory tracking of free-flying space manipulators using time-delay logarithmic sliding mode control
Muyuan Wang and others
Journal of Computational Design and Engineering, Volume 12, Issue 4, April 2025, Pages 167–184, https://doi.org/10.1093/jcde/qwaf038
In space operations, the requirements for control precision, stability, and robustness of free-flying space manipulators are critical for mission success. However, due to unknown system dynamics and external disturbances, control performance may degrade. To address these challenges, this paper ...
StitchingNet and deep transfer learning method for sewing stitch defect detection
Woo-Kyun Jung and others
Journal of Computational Design and Engineering, Volume 12, Issue 4, April 2025, Pages 140–154, https://doi.org/10.1093/jcde/qwaf037
The clothing manufacturing industry has been slow to adopt new technologies due to its labor-intensive nature, resulting in persistent defect rates averaging around 10%. Deep learning models offer a promising solution for automated sewing defect detection, but their effectiveness relies heavily on ...

Editor's Choice

Enhancing thermal stability in prismatic lithium-ion battery pack in electric vehicle through optimization for an indirect liquid-cooling system
Cheonha Park and others
Journal of Computational Design and Engineering, Volume 12, Issue 3, March 2025, Pages 51–64, https://doi.org/10.1093/jcde/qwaf020
In an electric vehicle battery pack, thermal stability degradation due to temperature differences is the cause of performance degradation and thermal runaway. Therefore, an effective battery cooling system design is essential to increase the thermal stability of the battery pack. In this study, ...
GazeSymCAT: A symmetric cross-attention transformer for robust gaze estimation under extreme head poses and gaze variations
Yupeng Zhong and Sang Hun Lee
Journal of Computational Design and Engineering, Volume 12, Issue 3, March 2025, Pages 115–129, https://doi.org/10.1093/jcde/qwaf017
With the rapid advancement of artificial intelligence, research on deep neural networks for estimating gaze from facial images captured by cameras has grown significantly. However, gaze estimation remains challenging due to the diversity of facial features, variability in head posture, partial ...
A multi-threshold image segmentation method based on arithmetic optimization algorithm: A real case with skin cancer dermoscopic images
Shuhui Hao and others
Journal of Computational Design and Engineering, Volume 12, Issue 2, February 2025, Pages 112–137, https://doi.org/10.1093/jcde/qwaf006
Multi-threshold image segmentation (MTIS) is a crucial technology in image processing, characterized by simplicity and efficiency, and the key lies in the selection of thresholds. However, the method's time complexity will grow exponentially with the number of thresholds. To solve this problem, an ...
Impact of considering bone remodelling in risk assessment of mandibular implant-supported bridges
Inyeong Kang and others
Journal of Computational Design and Engineering, Volume 12, Issue 2, February 2025, Pages 14–26, https://doi.org/10.1093/jcde/qwaf005
Efforts have been made to improve the prediction of implant treatment outcomes through biomechanical analyses using finite-element (FE) analysis. Particularly, a bone remodelling numerical model has been recently applied to forecast long-term stability. However, there is a scarcity of research on ...
Minimizing energy usage in multi-point manufacturing: a dimensional transfer learning strategy
Jie Liu and others
Journal of Computational Design and Engineering, Volume 12, Issue 1, January 2025, Pages 15–33, https://doi.org/10.1093/jcde/qwae106
With the increasing complexity of industrial manufacturing tasks, optimizing Multi-Point Manufacturing (MPF) operations, such as drilling and spot welding, has become essential for improving energy efficiency and execution speed. These tasks can be formulated as multi-dimensional Traveling Salesman ...
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