The current study examines the numerical simulation of the nanoliquid boundary layer flow comprising gyrotactic microbes with mass and energy transmission across a stretching inclined cylinder. The consequences of chemical reaction, heat generation/absorption, buoyancy force and Arrhenius activation energy is also considered on the nanofluid flow. The flow mechanism has been modeled in the form of system of nonlinear partial differential equations (PDEs). That system of PDEs is further transform into the dimensionless set of ordinary differential equations (ODEs) through the similarity substitutions. The obtained set of differential equations are numerically computed through the parametric continuation method (PCM). The effects of the distinct physical constraints on the energy, velocity, mass and the motile microbe profiles are discoursed and evaluated through Tables and Figures. It has been noticed that the velocity curve drops with the influence of inclination angle and Richardson number, while enhances against the variation of curvature factor. Furthermore, the energy field boosts with the upshot of inclination angle and heat source term, while declines with the influence of Prandtl number and Richardson number.
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http://dx.doi.org/10.1038/s41598-023-34886-2 | DOI Listing |
Environ Technol
January 2025
Centre for Biotechnology, Kalasalingam Academy of Research and Education, Krishnankoil, India.
Biokinetic models can optimise pollutant degradation and enhance microbial growth processes, aiding to protect ecosystem protection. Traditional biokinetic approaches (such as Monod, Haldane, etc.) can be challenging, as they require detailed knowledge of the organism's metabolism and the ability to solve numerous kinetic differential equations based on the principles of micro, molecular biology and biochemistry (first engineering principles) which can lead to discrepancies between predicted and actual degradation rates.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the generalized fluctuation-dissipation theorem. The methodology enables accurate estimation of system responses, including those with non-Gaussian statistics. We numerically validate our approach using time-series data from three different stochastic partial differential equations of increasing complexity: an Ornstein-Uhlenbeck process with spatially correlated noise, a modified stochastic Allen-Cahn equation, and the 2D Navier-Stokes equations.
View Article and Find Full Text PDFElectromagn Biol Med
January 2025
Department of Mathematics, University of Gour Banga, Malda, India.
In cardiovascular research, electromagnetic fields generated by Riga plates are utilized to study or manipulate blood flow dynamics, which is particularly crucial in developing treatments for conditions such as arterial plaque deposition and understanding blood behavior under varied flow conditions. This research predicts the flow patterns of blood enhanced with gold and maghemite nanoparticles (gold-maghemite/blood) in an electromagnetic microchannel influenced by Riga plates with a temperature gradient that decays exponentially, under sudden changes in pressure gradient. The flow modeling includes key physical influences like radiation heat emission and Darcy drag forces in porous media, with the flow mathematically represented through unsteady partial differential equations solved using the Laplace transform (LT) method.
View Article and Find Full Text PDFMed Phys
January 2025
Deparment of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Background: Stereotactic radiosurgery (SRS) is widely used for managing brain metastases (BMs), but an adverse effect, radionecrosis, complicates post-SRS management. Differentiating radionecrosis from tumor recurrence non-invasively remains a major clinical challenge, as conventional imaging techniques often necessitate surgical biopsy for accurate diagnosis. Machine learning and deep learning models have shown potential in distinguishing radionecrosis from tumor recurrence.
View Article and Find Full Text PDFFront Chem
January 2025
Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan.
This study investigates the significance of single-walled (SWCNTs) and multi-walled (MWCNTs) carbon nanotubes with a convectional fluid (water) over a vertical cone under the influences of chemical reaction, magnetic field, thermal radiation and saturated porous media. The impact of heat sources is also examined. Based on the flow assumptions, the fundamental flow equations are modeled as partial differential equations (PDEs).
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