..., automation, machine learning technologies, and the use of IIoT to innovate solutions. Researchers are focusing on ways to improve the rate and economy of implementing Industry 4.0 concepts in current manufacturing processes. This paper focuses on the implementation of a combination of specific industry 4.0...

... to evaluate the two types of locomotion that the mobile robot can utilize in each of these different environments. Corresponding simulations are conducted in the virtual environment and the results are analyzed. reinforcement learning digital twins mobile robots machine learning simulation...

... as to differentiate one from the other. In fruit-sorting process, manual classification is time-consuming, expensive, and requires experienced experts whose availability is often limited. To address these issues, various machine learning algorithms have been proposed to support the automated classification of fruits...

... properties from the surface strain fields calculated by digital image correlation (DIC) analysis. A machine learning algorithm is developed that can estimate the spatial variations in the elastic modulus. The model is trained on a dataset of simulated two-dimensional strain fields with known random...

...). Performance of machine learning algorithms depends on the training data and physical collected datasets are often limited to specific operating conditions, necessitating the use of training with many models using multi-fold cross-validated subsets. In this study we have used ten models using two-fold cross...

... = 0.89, Recall = 1.0.) It was also confirmed that the low-power laser irradiation trace did not affect the spectral data of the cutting for defect recognition. laser processes machine learning analytical methods quality control corrosion Proceedings of the ASME 2022 International Mechanical...

..., this study investigates how the car shapes, especially the angle of the front and back windows, could affect a car’s aerodynamic performance. In particular, a computational fluid dynamics approach combined with a machine-learning algorithm is adopted to investigate the aforementioned problem and determine...

... Abstract A feed forward machine-learning (ML) model is applied to study bubble induced turbulence and bubble mass transfer in a bubble column reactor. Using direct numerical simulation data for forced turbulence, bubble deformations and flow velocities are predicted. To predict mass transfer...

... that this method also has full potential to be applied in the fast inspection of plates made of composite materials, pipes, geophysical prospecting and medical imaging because all these inverse problems share similar physics. Lamb waves convolutional neural network DLIS machine learning corrosion...

... assessment by using this technical route in practice. creep-fatigue reliability analysis machine learning surrogate modelling probabilistic safety design Proceedings of the ASME 2022 International Mechanical Engineering Congress and Exposition IMECE2022 October 30-November 3, 2022, Columbus...

...-Stoke equation estimation which is prominent in many CFD softwares. machine learning fluid mechanics generative models auto-encoders turbulence flow generation Proceedings of the ASME 2021 International Mechanical Engineering Congress and Exposition IMECE2021 November 1-5, 2021, Virtual...

.... neural differential equations inverse problems unsteady combustion auto-differentiation machine learning Proceedings of the ASME 2021 International Mechanical Engineering Congress and Exposition IMECE2021 November 1-5, 2021, Virtual, Online IMECE2021-69657 NEURAL DIFFERENTIAL EQUATIONS FOR INVERSE...

.... Three machine learning methods are developed for automatically deriving a thermal network model from time series data. Link relationships between temperature nodes and parameter settings, such as thermal resistance and heat capacity, are automatically inferred by machine learning. Because the proposed...

... Abstract A machine learning model is developed to predict the crack propagation path in polycrystalline graphene sheets. The dataset used for training the machine learning (ML) model is obtained from the molecular dynamics (MD) simulations. A training set of 700 samples has been used to train...

... high-fidelity nature, which prevents it from being used as a computing engine for real-time applications. It is demonstrated in this paper that such challenges can be overcome with a newly developed computational framework by combining state-of-the art machine learning and nonlinear FEA for efficient...

... via machine learning tools is a well-established approach. In recent years, deep learning methods have received increasing attention from researchers and engineers because of their inherent capability of dealing with big data, mining complex representations, and overcoming the disadvantage...

... is best, with a root mean square error of 0.114°C. It reaches high prediction accuracy and can be used to guide the SLST control and primary loop valve opening (PLVO) regulation of heating substations. data-driven model machine learning secondary loop supply temperature prediction Proceedings...

...-end Machine learning techniques explicitly helpful in optimising and evaluating the still performance. Complete research on the implementation of ML models is made in this study to draw the feasibility of implementing the appropriate supervised or unsupervised machine learning methods. A comparison...

.... Furthermore, it is also concluded that for the medium filled with a relatively low viscous fluid such as air the longitudinal waves alone is able to estimate the biomarkers, which reduce significantly the computational efforts. acoustic waves biomimetic porous scaffold machine learning porous media...

... decision systems require complex infrastructures that make advanced feedback control possible. The motivation of this paper is exploring the paradigms such as Industrial Internet of Things (IIoT), Big Data collection, Cloud Manufacturing (CM), and Machine Learning (ML) to provide better manufacturing...