Tellus B ◽  
2011 ◽  
Vol 63 (4) ◽  
Author(s):  
Bernd Heinold ◽  
Ina Tegen ◽  
Kerstin Schepanski ◽  
Matthias Tesche ◽  
Michael Esselborn ◽  
...  

1988 ◽  
Author(s):  
A. T. Hopkins ◽  
Darrell L. Palmer ◽  
Jeffrey R. Brown

1997 ◽  
Vol 62 ◽  
Author(s):  
R. Samson ◽  
S. Follens ◽  
R. Lemeur

A  multi-layer model (FORUG) was developed, to simulate the canopy  photosynthesis of a mixed deciduous forest during the growing season.  Measured photosynthesis parameters, for beech (Fagus  sylvatica), oak (Quercus  robur) and ash (Fraxinus  excelsior), were used as input to the model. This  information at the leaf level is then scaled up to the level of the canopy,  taking into account the radiation profiles (diffuse and direct PAR) in the  canopy, the vertical LAI distribution, the evolution of the LAI and the  photosynthesis parameters during the growing season, and the temperature  dependence of the latter parameters.


2013 ◽  
Vol 23 (2) ◽  
Author(s):  
Maja Atanasijevic-Kunc ◽  
Joze Dinovec ◽  
Tina Sentocnik
Keyword(s):  

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 93
Author(s):  
Alessandro Di Pretoro ◽  
Francesco D’Iglio ◽  
Flavio Manenti

Fouling is a substantial economic, energy, and safety issue for all the process industry applications, heat transfer units in particular. Although this phenomenon can be mitigated, it cannot be avoided and proper cleaning cycle scheduling is the best way to deal with it. After thorough literature research about the most reliable fouling model description, cleaning procedures have been optimized by minimizing the Time Average Losses (TAL) under nominal operating conditions according to the well-established procedure. For this purpose, different cleaning actions, namely chemical and mechanical, have been accounted for. However, this procedure is strictly related to nominal operating conditions therefore perturbations, when present, could considerably compromise the process profitability due to unexpected shutdown or extraordinary maintenance operations. After a preliminary sensitivity analysis, the uncertain variables and the corresponding disturbance likelihood were estimated. Hence, cleaning cycles were rescheduled on the basis of a stochastic flexibility index for different probability distributions to show how the uncertainty characterization affects the optimal time and economic losses. A decisional algorithm was finally conceived in order to assess the best number of chemical cleaning cycles included in a cleaning supercycle. In conclusion, this study highlights how optimal scheduling is affected by external perturbations and provides an important tool to the decision-maker in order to make a more conscious design choice based on a robust multi-criteria optimization.


2021 ◽  
Vol 9 (5) ◽  
pp. 467
Author(s):  
Mostafa Farrag ◽  
Gerald Corzo Perez ◽  
Dimitri Solomatine

Many grid-based spatial hydrological models suffer from the complexity of setting up a coherent spatial structure to calibrate such a complex, highly parameterized system. There are essential aspects of model-building to be taken into account: spatial resolution, the routing equation limitations, and calibration of spatial parameters, and their influence on modeling results, all are decisions that are often made without adequate analysis. In this research, an experimental analysis of grid discretization level, an analysis of processes integration, and the routing concepts are analyzed. The HBV-96 model is set up for each cell, and later on, cells are integrated into an interlinked modeling system (Hapi). The Jiboa River Basin in El Salvador is used as a case study. The first concept tested is the model structure temporal responses, which are highly linked to the runoff dynamics. By changing the runoff generation model description, we explore the responses to events. Two routing models are considered: Muskingum, which routes the runoff from each cell following the river network, and Maxbas, which routes the runoff directly to the outlet. The second concept is the spatial representation, where the model is built and tested for different spatial resolutions (500 m, 1 km, 2 km, and 4 km). The results show that the spatial sensitivity of the resolution is highly linked to the routing method, and it was found that routing sensitivity influenced the model performance more than the spatial discretization, and allowing for coarser discretization makes the model simpler and computationally faster. Slight performance improvement is gained by using different parameters’ values for each cell. It was found that the 2 km cell size corresponds to the least model error values. The proposed hydrological modeling codes have been published as open-source.


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