Predicting airborne pollutant concentrations and events in a commercial building using low-cost pollutant sensors and machine learning: A case study
A Mohammadshirazi, VA Kalkhorani, J Humes… - Building and …, 2022 - Elsevier
Prediction of indoor airborne pollutant concentrations can enable a smart indoor air quality
control strategy that potentially reduces building energy use and improves occupant comfort …
control strategy that potentially reduces building energy use and improves occupant comfort …
Neural network method for solving parabolic two-temperature microscale heat conduction in double-layered thin films exposed to ultrashort-pulsed lasers
Simulation of the micro/nanoscale heat conduction induced by ultrashort-pulsed laser
heating has been attracting great attention. Additionally, machine and deep learning …
heating has been attracting great attention. Additionally, machine and deep learning …
Neural network method for solving nonlocal two-temperature nanoscale heat conduction in gold films exposed to ultrashort-pulsed lasers
Recently, we have presented an artificial neural network (ANN) method for solving the
parabolic two-temperature heat conduction equations (PTTM) in double-layered thin films …
parabolic two-temperature heat conduction equations (PTTM) in double-layered thin films …
Physics-informed mta-unet: prediction of thermal stress and thermal deformation of satellites
Z Cao, W Yao, W Peng, X Zhang, K Bao - Aerospace, 2022 - mdpi.com
The rapid analysis of thermal stress and deformation plays a pivotal role in the thermal
control measures and optimization of the structural design of satellites. For achieving real …
control measures and optimization of the structural design of satellites. For achieving real …
A physics and data co-driven surrogate modeling approach for temperature field prediction on irregular geometric domain
K Bao, W Yao, X Zhang, W Peng, Y Li - Structural and Multidisciplinary …, 2022 - Springer
In the whole aircraft structural optimization loop, thermal analysis plays a very important role.
But it faces a severe computational burden when directly applying traditional numerical …
But it faces a severe computational burden when directly applying traditional numerical …
GPU-basierte Verfahren zur Segmentierung biomedizinischer Bilddaten
PD Lösel - 2022 - archiv.ub.uni-heidelberg.de
Die Analyse medizinischer und biologischer Bilddaten erfordert häufig die Isolierung
einzelner Strukturen aus einem 3D-Volumen durch Segmentierung. Trotz einer Vielzahl …
einzelner Strukturen aus einem 3D-Volumen durch Segmentierung. Trotz einer Vielzahl …
[图书][B] Deep Learning-based Forward Modeling and Inversion Techniques for Computational Physics Problems
This book investigates in detail the emerging deep learning (DL) technique in computational
physics, assessing its promising potential to substitute conventional numerical solvers for …
physics, assessing its promising potential to substitute conventional numerical solvers for …
Deep-Learning Temperature Field Prediction Method for Vehicle Domain Control Unit with Multiple Variables and Changeable Geometry
L Liang, L Lu, L Huang, Y Xie, S Yang, Y Huang… - Available at SSRN … - papers.ssrn.com
In this work, a novel deep learning-based approach for efficient thermal analysis in vehicle
Domain Control Units (DCUs) is developed. Conventional numerical simulation methods …
Domain Control Units (DCUs) is developed. Conventional numerical simulation methods …
DiffusionNet: Accelerating the solution of Time-Dependent partial differential equations using deep learning
M Asem - arXiv preprint arXiv:2011.10015, 2020 - arxiv.org
We present our deep learning framework to solve and accelerate the Time-Dependent
partial differential equation's solution of one and two spatial dimensions. We demonstrate …
partial differential equation's solution of one and two spatial dimensions. We demonstrate …