Applying GMDH neural network to estimate the thermal resistance and thermal conductivity of pulsating heat pipes

Autor: Mohammad Hossein Ahmadi, Milad Sadeghzadeh, Amir Hossein Raffiee, Kwok-wing Chau

Publikováno v: Engineering Applications of Computational Fluid Mechanics, Vol 13, Iss 1, Pp 327-336 (2019)

Thermal performance of pulsating heat pipes (PHPs) is dependent to several factors. Inner and outer diameter of tube, filling ratio, thermal conductivity, heat input, inclination angle, and length of each section are the most influential factors in t

Externí odkaz: https://doaj.org/article/7b5f776705e74776b418060dca4732c0

Elasto-Inertial migration of particles and capsules in viscoelastic microchannels

Autor: Amir Hossein Raffiee (8071673)

The motion of synthetic capsules and living cells in microchannels has been the subject of numerous studies in the last decade due to its significance in engineer- ing and biomedical applications. Cell sorting and separation are common processes that

GarmentGAN: Photo-realistic Adversarial Fashion Transfer

Autor: Michael Sollami, Amir Hossein Raffiee

Publikováno v: ICPR

The garment transfer problem comprises two tasks: learning to separate a person's body (pose, shape, color) from their clothing (garment type, shape, style) and then generating new images of the wearer dressed in arbitrary garments. We present Garmen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef979e08f2e0ae3e618a27f67d2cd3a7
https://doi.org/10.1109/icpr48806.2021.9412908

Raman spectra-based deep learning: A tool to identify microbial contamination

Autor: Arezoo M. Ardekani, Mohit S. Verma, Murali Kannan Maruthamuthu, Denilson Mendes de Oliveira, Amir Hossein Raffiee

Publikováno v: MicrobiologyOpen
MicrobiologyOpen, Vol 9, Iss 11, Pp n/a-n/a (2020)

Deep learning has the potential to enhance the output of in‐line, on‐line, and at‐line instrumentation used for process analytical technology in the pharmaceutical industry. Here, we used Raman spectroscopy‐based deep learning strategies to d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::599c9aad0b6616f78ca8b54874a64860
https://pubmed.ncbi.nlm.nih.gov/33063423

Thermal conductivity prediction of nanofluids containing CuO nanoparticles by using correlation and artificial neural network

Autor: Amir Hossein Raffiee, Mostafa Safdari Shadloo, Mohammad Alhuyi Nazari, Ali Komeilibirjandi, Akbar Maleki

Publikováno v: Journal of Thermal Analysis and Calorimetry
Journal of Thermal Analysis and Calorimetry, Springer Verlag, 2019, ⟨10.1007/s10973-019-08838-w⟩

Nanofluids are employed in different thermal devices due to their enhanced thermophysical features which lead to noticeable heat transfer augmentation. One of the major reasons of the heat transfer improvement by using the nanofluids is their increas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::383289c2d8a8eb04d8b7bca51681c074
https://hal.archives-ouvertes.fr/hal-02344357