Hybrid phenomenological/ANN-PSO modelling of a deformable material in spouted bed drying process

Veloso, Yago Matheus da Silva; Almeida, Marcello Maia de; Alsina, Odelsia Leonor Sánchez de; Passos, M. L.; Mujumdar, Arun S.; Leite, Manuela Souza

doi:10.1016/j.powtec.2019.12.047

Cited by 21 publications

(4 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An ANN is a computational model based on the mode of learning of biological neurons in the human brain 25. An ANN contains a series of layers of connected nodes named artificial neurons 26.…”

Section: Methodsmentioning

confidence: 99%

Multiple‐Output Artificial Neural Network to Estimate Solid Cycle Times in Conical Spouted Beds

et al. 2021

View full text Add to dashboard Cite

Knowledge of cycle times is essential to design spouted beds. Although experiments for determining cycle times are time‐consuming, there is hardly any mechanistic or empirical model for their prediction. Two types of artificial neural networks, namely, single‐ and multiple‐output ones, have been developed to estimate particle cycle times in conical spouted beds. They provide satisfactory cycle time predictions under different configurations. A comparison of single‐output neural networks with multiple‐output ones proves that, although the former fit slightly better the experimental data, the latter provide a reasonable prediction of all cycle times, and therefore, only one neural network is sufficient for their prediction. The maximum cycle is the one of highest sensitivity to all the parameters analyzed.

show abstract

Section: Methodsmentioning

confidence: 99%

Multiple‐Output Artificial Neural Network to Estimate Solid Cycle Times in Conical Spouted Beds

et al. 2021

View full text Add to dashboard Cite

show abstract

“…It is employed for estimation (Xie et al, 2019;Zivkovic et al, 2021), fault detection (Huang et al, 2020), control system optimization (Fan et al, 2019), and cooperative and constrained control design (Ejigu and Liu, 2022b). Recently, the GA, PSO, and BAS algorithms have given more attention to training ANN algorithms for different applications (Li, 2020;Vasumathi and Moorthi, 2012;da Silva Veloso et al, 2020;Yadav and Anubhav, 2020;Jamali et al, 2019). However, the BAS algorithm faces several shortcomings as reported in Ref.…”

Section: Beetle Antennae Searchmentioning

confidence: 99%

Application of artificial intelligence technologies and big data computing for nuclear power plants control: a review

Ejigu,

Tuo,

Liu

2024

Front. Nucl. Eng.

View full text Add to dashboard Cite

Nuclear power plants produce a massive amount of clean energy and necessitate safe operation through intelligence technologies. Recently, the rapid advancements in communication infrastructures including artificial intelligence, big data computing, and Internet of Things devices moving the nuclear industries towards digitalization and intelligence to improve safety. The integration of these technologies into the nuclear sector offers effective tactics in addressing several challenges in the control and safe operation of nuclear power plants. This can be achieved through the insights generated from massive amounts of data. This paper comprehensively reviews the literature on artificial intelligence technologies and big data, seeking to provide a holistic perspective on their relations and how they can be integrated with nuclear power plants. The utilization of computing platforms boosts the deployment of artificial intelligence and big data analytics effectively in nuclear power plants. Further, this review also points out the future opportunities as well as challenges for applying artificial intelligence and big data computing in the nuclear industry.

show abstract

“…The spouted bed is a special fluidized bed that is regarded as a highly efficient particle–fluid contactor. , It was originally used in the drying process for large particles. With the development of technology, spouted beds have been applied in drying, − pyrolysis, , gasification, − oxidation, , coating, and desulfurization . The gas phase is injected from the bed inlet, which drives the particles to move up.…”

Section: Introductionmentioning

confidence: 99%

Numerical Study on the Effect of Three Novel Strengthening Components on Water Evaporation in 3D Spouted Beds

et al. 2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

The hydrodynamics of the gas–solid two-phase flow and vaporization of the water phase in an integral multijet spout-fluidized bed (IMJSFB) and spouted beds with spherical longitudinal vortex generators (LVGs) and an integral swirling blade nozzle (ISBN) was numerically simulated. These three novel strengthening components are adopted for the strengthening of the radial mixing of particles, promoting the uniformity of the flow field velocity distribution, and increasing the water vaporization rate. The simulation results show that the three novel strengthening components can promote the uniformity of fluid flow velocity distribution in beds, and the promotion effect is arranged in descending order as follows: LVGs > swirling blades > multijet. In the case of water vaporization, the LVGs, swirling blade, and multijet mainly promote the vaporization of water near the generators, in the spout zone, and the zone near the side nozzles, respectively. Among them, the swirling blade contributes the most to water vaporization, followed by the multijet and then LVGs. In addition, when the gas inlet velocity and temperature are 11.2 m/s and 520 K, respectively, water vaporization is most obviously boosted.

show abstract

Hybrid phenomenological/ANN-PSO modelling of a deformable material in spouted bed drying process

Cited by 21 publications

References 40 publications

Multiple‐Output Artificial Neural Network to Estimate Solid Cycle Times in Conical Spouted Beds

Multiple‐Output Artificial Neural Network to Estimate Solid Cycle Times in Conical Spouted Beds

Application of artificial intelligence technologies and big data computing for nuclear power plants control: a review

Numerical Study on the Effect of Three Novel Strengthening Components on Water Evaporation in 3D Spouted Beds

Contact Info

Product

Resources

About