Multi-scale Modelling of the Heart

2009 ◽  
pp. 83-177 ◽  
Author(s):  
H. Schmid ◽  
P. J. Hunter
Keyword(s):  
Multi Scale ◽  
Scale Modelling

Multi-scale modelling of woven carbon fibre reinforced epoxy

2021 ◽  
Author(s):  
Alexandru Szabo ◽  
Radu Negru ◽  
Alexandru-Viorel Coşa ◽  
Liviu Marşavina ◽  
Dan-Andrei Şerban
Keyword(s):  
Carbon Fibre ◽  
Multi Scale ◽  
Scale Modelling

scholarly journals Multi-scale modelling of a large scale shell-and-tube latent heat storage system for direct steam generation power plants

2020 ◽  
Author(s):  
Clément Beust ◽  
Erwin Franquet ◽  
Jean-Pierre Bédécarrats ◽  
Pierre Garcia ◽  
Jérôme Pouvreau ◽  
...  
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Storage System ◽  
Steam Generation ◽  
Latent Heat Storage ◽  
Multi Scale ◽  
Direct Steam ◽  
Scale Modelling ◽  
Shell And Tube ◽  
Generation Power

Multi-Scale Modelling of 1000 MW S-CO2 Coal-Fired Power System and a Comprehensive Design

2021 ◽  
Author(s):  
Yuanhong Fan ◽  
Danlei Yang ◽  
Guihua Tang ◽  
X. L. Li
Keyword(s):  
Power System ◽  
Multi Scale ◽  
Scale Modelling

Design of Novel Hybrid Adsorption Processes for CO 2 Capture Using an Integrated Multi-Scale Modelling

2021 ◽  
Author(s):  
Ahmed Alhajaj ◽  
Hammed Balogun ◽  
Daniel Bahamon ◽  
Nour Alkhatib ◽  
Lourdes F. Vega
Keyword(s):  
Multi Scale ◽  
Scale Modelling ◽  
Adsorption Processes

Multi-scale modelling of arterial tissue: Linking networks of fibres to continua

2018 ◽  
Vol 341 ◽  
pp. 740-787
Author(s):  
Felipe Figueredo Rocha ◽  
Pablo Javier Blanco ◽  
Pablo Javier Sánchez ◽  
Raúl Antonino Feijóo
Keyword(s):  
Multi Scale ◽  
Arterial Tissue ◽  
Scale Modelling

scholarly journals Tropospheric Emission Spectrometer (TES) satellite observations of ammonia, methanol, formic acid, and carbon monoxide over the Canadian oil sands: validation and model evaluation

2015 ◽  
Vol 8 (12) ◽  
pp. 5189-5211 ◽  
Author(s):  
M. W. Shephard ◽  
C. A. McLinden ◽  
K. E. Cady-Pereira ◽  
M. Luo ◽  
S. G. Moussa ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Air Quality ◽  
Formic Acid ◽  
Model Evaluation ◽  
Oil Sands ◽  
Field Campaign ◽  
Infrared Observations ◽  
Multi Scale ◽  
Global Environmental ◽  
Scale Modelling

Abstract. The wealth of air quality information provided by satellite infrared observations of ammonia (NH3), carbon monoxide (CO), formic acid (HCOOH), and methanol (CH3OH) is currently being explored and used for a number of applications, especially at regional or global scales. These applications include air quality monitoring, trend analysis, emissions, and model evaluation. This study provides one of the first direct validations of Tropospheric Emission Spectrometer (TES) satellite-retrieved profiles of NH3, CH3OH, and HCOOH through comparisons with coincident aircraft profiles. The comparisons are performed over the Canadian oil sands region during the intensive field campaign (August–September, 2013) in support of the Joint Canada–Alberta Implementation Plan for Oil Sands Monitoring (JOSM). The satellite/aircraft comparisons over this region during this period produced errors of (i) +0.08 ± 0.25 ppbv for NH3, (ii) +7.5 ± 23 ppbv for CO, (iii) +0.19 ± 0.46 ppbv for HCOOH, and (iv) −1.1 ± 0.39 ppbv for CH3OH. These values mostly agree with previously estimated retrieval errors; however, the relatively large negative bias in CH3OH and the significantly greater positive bias for larger HCOOH and CO values observed during this study warrant further investigation. Satellite and aircraft ammonia observations during the field campaign are also used in an initial effort to perform preliminary evaluations of Environment Canada's Global Environmental Multi-scale – Modelling Air quality and CHemistry (GEM-MACH) air quality modelling system at high resolution (2.5 × 2.5 km2). These initial results indicate a model underprediction of ~ 0.6 ppbv (~ 60 %) for NH3, during the field campaign period. The TES/model CO comparison differences are ~ +20 ppbv (~ +20 %), but given that under these conditions the TES/aircraft comparisons also show a small positive TES CO bias indicates that the overall model underprediction of CO is closer to ~ 10 % at 681 hPa (~ 3 km) during this period.

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