The evolution of Big Data in neuroscience and neurology
Neurological diseases are on the rise worldwide, leading to increased healthcare costs and
diminished quality of life in patients. In recent years, Big Data has started to transform the …
diminished quality of life in patients. In recent years, Big Data has started to transform the …
[HTML][HTML] Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems
Reinforced composite is a preferred choice of material for the design of industrial lightweight
structures. As of late, composite materials analysis and development utilizing machine …
structures. As of late, composite materials analysis and development utilizing machine …
FE: an efficient data-driven multiscale approach based on physics-constrained neural networks and automated data mining
Herein, we present a new data-driven multiscale framework called FE ANN which is based
on two main keystones: the usage of physics-constrained artificial neural networks (ANNs) …
on two main keystones: the usage of physics-constrained artificial neural networks (ANNs) …
Model identification in reactor-based combustion closures using sparse symbolic regression
Abstract In Large Eddy Simulations (LES) of combustion, the accuracy of predictions might
be heavily affected by deficiencies in traditional/simplified closure models, especially when …
be heavily affected by deficiencies in traditional/simplified closure models, especially when …
Machine Learning in Computer Aided Engineering
The extraordinary success of Machine Learning (ML) in many complex heuristic fields has
promoted its introduction in more analytical engineering fields, improving or substituting …
promoted its introduction in more analytical engineering fields, improving or substituting …
High-fidelity computational modeling of scratch damage in automotive coatings with machine learning-driven identification of fracture parameters
As one of the key components of a vehicle, automotive coating systems are typical micro-
size multilayer composites, which normally suffer from intricate scratch damage. Currently, it …
size multilayer composites, which normally suffer from intricate scratch damage. Currently, it …
White matter tract transcranial ultrasound stimulation, a computational study
Low-intensity transcranial ultrasound stimulation (TUS) is poised to become one of the most
promising treatments for neurological disorders. However, while recent animal model …
promising treatments for neurological disorders. However, while recent animal model …
[HTML][HTML] Multiscale analysis of composite pressure vessel structures wound with different fiber tensile force
The aim of this paper is the multiscale investigation of composite pressure vessel structures
wound with varying fibre tension. The paper explores the potential of” programming” the …
wound with varying fibre tension. The paper explores the potential of” programming” the …
Validation of a computational biomechanical mouse brain model for rotational head acceleration
Recent mouse brain injury experiments examine diffuse axonal injury resulting from
accelerative head rotations. Evaluating brain deformation during these events would provide …
accelerative head rotations. Evaluating brain deformation during these events would provide …
Numerically assisted calibration procedure of nonlinear in-plane shear properties of unidirectional composite laminae based on off-axis tensile experiments
L Kovács, G Romhány - Journal of Composite Materials, 2024 - journals.sagepub.com
In this paper, a novel methodology is presented to evaluate the true nonlinear shear
response of continuous fiber-reinforced plastic (CFRP) unidirectional laminae. It requires …
response of continuous fiber-reinforced plastic (CFRP) unidirectional laminae. It requires …