scholarly journals SPATIALLY-AVERAGED DIFFUSIVITIES FOR POLLUTANT TRANSPORT IN VEGETATED FLOWS

2016 ◽  
Vol 42 ◽  
pp. 1660170
Author(s):  
JUN HUANG ◽  
XIAOFENG ZHANG ◽  
VIVIEN P. CHUA
Keyword(s):  
Experimental Data ◽  
Least Squares ◽  
Cross Sections ◽  
Least Squares Method ◽  
Pollutant Transport ◽  
Longitudinal Direction ◽  
Environmental Benefits ◽  
Reliable Estimate ◽  
Injection Point ◽  
Shoreline Stabilization

Vegetation in wetlands can create complicated flow patterns and may provide many environmental benefits including water purification, flood protection and shoreline stabilization. The interaction between vegetation and flow has significant impacts on the transport of pollutants, nutrients and sediments. In this paper, we investigate pollutant transport in vegetated flows using the Delft3D-FLOW hydrodynamic software. The model simulates the transport of pollutants with the continuous release of a passive tracer at mid-depth and mid-width in the region where the flow is fully developed. The theoretical Gaussian plume profile is fitted to experimental data, and the lateral and vertical diffusivities are computed using the least squares method. In previous tracer studies conducted in the laboratory, the measurements were obtained at a single cross-section as experimental data is typically collected at one location. These diffusivities are then used to represent spatially-averaged values. With the numerical model, sensitivity analysis of lateral and vertical diffusivities along the longitudinal direction was performed at 8 cross-sections. Our results show that the lateral and vertical diffusivities increase with longitudinal distance from the injection point, due to the larger size of the dye cloud further downstream. A new method is proposed to compute diffusivities using a global minimum least squares method, which provides a more reliable estimate than the values obtained using the conventional method.

scholarly journals Determination of parameters for Cauchy’s problem for systems of ODEs with application to biological modelling

BIOMATH ◽  
2016 ◽  
Vol 5 (1) ◽  
pp. 1604231
Author(s):  
A.N. Pete ◽  
Peter Mathye ◽  
Igor Fedotov ◽  
Michael Shatalov
Keyword(s):  
Experimental Data ◽  
Mathematical Models ◽  
Least Squares ◽  
Numerical Method ◽  
Least Squares Method ◽  
Algebraic Equations ◽  
Systems Of Odes ◽  
Determination Of Parameters ◽  
Biological Modelling

An inverse numerical method that estimate parameters of dynamic mathematical models given some information about unknown trajectories at some time is applied to examples taken from Biology and Ecology. The method consisting of determining an over-determined system of algebraic equations using experimental data. The solution of the over-determined system is then obtained using, for example the least-squares method. To illustrate the effectiveness of the method an analysis of examples and corresponding numerical example are presented.

Photoneutron Cross Sections for Au Revisited: Measurements with Laser Compton Scattering γ-Rays and Data Reduction by a Least-Squares Method

2011 ◽  
Vol 48 (5) ◽  
pp. 834-840 ◽  
Author(s):  
Osamu ITOH ◽  
Hiroaki UTSUNOMIYA ◽  
Hidetoshi AKIMUNE ◽  
Takeo KONDO ◽  
Masaki KAMATA ◽  
...  
Keyword(s):  
Least Squares ◽  
Compton Scattering ◽  
Cross Sections ◽  
Data Reduction ◽  
Least Squares Method ◽  
Γ Rays ◽  
Laser Compton Scattering

Calibration of stormwater quality regression models: a random process?

2010 ◽  
Vol 62 (4) ◽  
pp. 875-882 ◽  
Author(s):  
A. Dembélé ◽  
J.-L. Bertrand-Krajewski ◽  
B. Barillon
Keyword(s):  
Experimental Data ◽  
Least Squares ◽  
Regression Models ◽  
Linear Models ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Data Sets ◽  
Data Set ◽  
Urban Catchments

Regression models are among the most frequently used models to estimate pollutants event mean concentrations (EMC) in wet weather discharges in urban catchments. Two main questions dealing with the calibration of EMC regression models are investigated: i) the sensitivity of models to the size and the content of data sets used for their calibration, ii) the change of modelling results when models are re-calibrated when data sets grow and change with time when new experimental data are collected. Based on an experimental data set of 64 rain events monitored in a densely urbanised catchment, four TSS EMC regression models (two log-linear and two linear models) with two or three explanatory variables have been derived and analysed. Model calibration with the iterative re-weighted least squares method is less sensitive and leads to more robust results than the ordinary least squares method. Three calibration options have been investigated: two options accounting for the chronological order of the observations, one option using random samples of events from the whole available data set. Results obtained with the best performing non linear model clearly indicate that the model is highly sensitive to the size and the content of the data set used for its calibration.

scholarly journals Route 93, Arizona’s IRI estimation using least squares method and fuzzy logic

2017 ◽  
Vol 7 (3) ◽  
pp. 157-162
Author(s):  
Sebnem Sargin Karahancer ◽  
Ekinhan Eriskin ◽  
Buket Capali ◽  
Serdal Terzi ◽  
Mehmet Saltan
Keyword(s):  
Experimental Data ◽  
Fuzzy Logic ◽  
Least Squares ◽  
Least Squares Method ◽  
International Roughness Index ◽  
Freeze Thaw ◽  
Roughness Index ◽  
Subjective Opinion

AbstractServiceability was found to be influenced by longitudinal and transverse profiles as well as the extent of cracking and patching. The amount of weight to assign to each element in the determination of the overall serviceability is a matter of subjective opinion. International roughness index of highway pavements has been estimated by least squares and fuzzy logic methods and compared. For these models, Route 93, Arizona experimental data have been used. Annual freeze –thaw occurring days, depending on years, ha ve been used for modelling. The developed model with least squares method has a high regression value. This approach can be easily and realistically performed to solve problems that do not have a formulation or function for the solution.Keywords: International roughness index, least squares method, modelling, estimation, fuzzy logic.

An Application of Least Squares Method to the Solution of the Inverse Problem of Heat Conduction

1963 ◽  
Vol 85 (4) ◽  
pp. 378-379 ◽  
Author(s):  
Irving Frank
Keyword(s):  
Experimental Data ◽  
Inverse Problem ◽  
Heat Conduction ◽  
Least Squares ◽  
Heat Input ◽  
Least Squares Method ◽  
Least Square Method ◽  
The Body ◽  
Least Square

When the temperature of a body at some point is known, it is generally possible to determine the rate of heat input to the surface of the body. However, when the temperatures are determined experimentally, it will be found that there is some uncertainty in the solution for the rate of heat input. It is suggested that a least square method be used to determine the rate of heat input which best fits the experimental data.

scholarly journals Resonance Parameters for Uranium 233

1967 ◽  
Vol 20 (6) ◽  
pp. 617 ◽  
Author(s):  
AR de L Musgrove
Keyword(s):  
Least Squares ◽  
Cross Sections ◽  
Least Squares Method ◽  
The Other ◽  
Resonance Parameters ◽  
Single Level ◽  
Channel Theory ◽  
Good Agreement

Single-level and multilevel resonance parameters are given for 233U below 11 e V_ The total and fission cross sections were fitted simultaneously and good agreement was obtained. Spin assignments determined by the least squares method support the prediction of the channel theory of fission that 233U has two level populations; one with predominantly large fission widths and the other with much narrower widths.

‘Least squares’ method—theorem or law?

1980 ◽  
Vol 59 (9) ◽  
pp. 8
Author(s):  
D.E. Turnbull
Keyword(s):  
Least Squares ◽  
Least Squares Method
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