scholarly journals Impact of model parameters on Monte Carlo simulations of backscattering Mueller matrix images of colon tissue

2011 ◽  
Vol 2 (7) ◽  
pp. 1836 ◽  
Author(s):  
Maria-Rosaria Antonelli ◽  
Angelo Pierangelo ◽  
Tatiana Novikova ◽  
Pierre Validire ◽  
Abdelali Benali ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Mueller Matrix ◽  
Model Parameters ◽  
Colon Tissue

scholarly journals A new sewage exfiltration model – parameters and calibration

2011 ◽  
Vol 63 (10) ◽  
pp. 2294-2299 ◽  
Author(s):  
Christian Karpf ◽  
Peter Krebs
Keyword(s):  
Waste Water ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Experimental Studies ◽  
Model Parameters ◽  
Potential Danger ◽  
Detailed Consideration ◽  
Sewer Systems ◽  
The Law ◽  
Groundwater Infiltration

Exfiltration of waste water from sewer systems represents a potential danger for the soil and the aquifer. Common models, which are used to describe the exfiltration process, are based on the law of Darcy, extended by a more or less detailed consideration of the expansion of leaks, the characteristics of the soil and the colmation layer. But, due to the complexity of the exfiltration process, the calibration of these models includes a significant uncertainty. In this paper, a new exfiltration approach is introduced, which implements the dynamics of the clogging process and the structural conditions near sewer leaks. The calibration is realised according to experimental studies and analysis of groundwater infiltration to sewers. Furthermore, exfiltration rates and the sensitivity of the approach are estimated and evaluated, respectively, by Monte-Carlo simulations.

SIMULATIONS OF GLYCOLYTIC OSCILLATIONS IN CELLS WITH COMPARTMENTS

2002 ◽  
Vol 12 (07) ◽  
pp. 1643-1652 ◽  
Author(s):  
VLADIMIR P. ZHDANOV
Keyword(s):  
Monte Carlo ◽  
Cell Membrane ◽  
Monte Carlo Simulations ◽  
Cell Size ◽  
Elementary Reaction ◽  
Model Parameters ◽  
Typical Size ◽  
Glycolytic Oscillations ◽  
Glucose Supply ◽  
In Cells

We present Monte Carlo simulations of glycolytic oscillations inside the cell with a chemically inactive compartment. The model employed takes into account the glucose supply to the cell via the cell membrane and a few elementary reaction steps running inside the cell in the area between the external membrane and the compartment. The model parameters are chosen so that the typical size of oscillatory patterns is comparable with the cell size. Although the compartment does not directly participate in the reaction, its presence is found to amplify irregular oscillations provided that the compartment size is appreciable and it is located in the center of the cell.

Specifying Weights in Spatial Forecasting Models: The Results of Some Experiments

1982 ◽  
Vol 14 (5) ◽  
pp. 571-584 ◽  
Author(s):  
F Stetzer
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Weight Function ◽  
Effective Area ◽  
Space Time ◽  
Distance Decay ◽  
Model Parameters ◽  
Sample Sizes ◽  
Forecasting Models ◽  
Estimation Of Model Parameters

The application of space-time forecasting models requires the specification of a set of place-to-place weights. The existing literature contains several recommendations for this specification. By a series of Monte Carlo simulations, various weighting rules are compared in terms of estimation of model parameters and accuracy of forecasts. It is shown that specification of the weights is important, especially when sample sizes are small and the data autocorrelated. Generally, the effective area of the weight function is more important than its distance decay.

scholarly journals Uncertainty analysis of rising sewer models with respect to input parameters and model structure using Monte Carlo simulations and computational fluid dynamics

2021 ◽  
Author(s):  
Ahmed Khalil ◽  
Domenico Santoro ◽  
Damien J. Batstone ◽  
Christopher T. DeGroot
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Model Parameters ◽  
Model Structure ◽  
Mathematical Form ◽  
Homogeneous Surface ◽  
Simple Flows ◽  
D Model

Abstract Modelling conversion processes in sewers can help minimize odour and pipe corrosion issues, but model uncertainties and errors must be understood. In this study, the Wastewater Aerobic/Anaerobic Transformation in Sewers (WATS) model is implemented in two different frameworks; 1-D (CSTR-in-series) and computational fluid dynamics (CFD) to study the uncertainties due to model parameters and its mathematical form. The 1-D model is used to conduct uncertainty/sensitivity analysis using Monte Carlo simulations. Time-averaged outputs were represented using a general linearized model to quantify the importance of specific parameters. The sulfide formation rate per unit area of the biofilm is the most influential parameter. Parameters controlling anaerobic hydrolysis and fermentation are also significant. Uncertainty due to model structure is studied using CFD to explore the influences of non-homogeneous surface reactions and solids settling. These showed that the 1-D model provides a reasonable characterisation of the process for simple flows in pressure mains.

scholarly journals Mueller matrix imaging of human colon tissue for cancer diagnostics: how Monte Carlo modeling can help in the interpretation of experimental data

2010 ◽  
Vol 18 (10) ◽  
pp. 10200 ◽  
Author(s):  
Maria-Rosaria Antonelli ◽  
Angelo Pierangelo ◽  
Tatiana Novikova ◽  
Pierre Validire ◽  
Abdelali Benali ◽  
...  
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Human Colon ◽  
Mueller Matrix ◽  
Cancer Diagnostics ◽  
Colon Tissue ◽  
Monte Carlo Modeling

scholarly journals A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations

2017 ◽  
Vol 36 (1) ◽  
pp. 195-217 ◽  
Author(s):  
Adam S. Ward ◽  
Christa A. Kelleher ◽  
Seth J. K. Mason ◽  
Thorsten Wagener ◽  
Neil McIntyre ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Software Tool ◽  
Transient Storage ◽  
Model Parameters ◽  
Storage Model ◽  
Transient Storage Model

scholarly journals The Generalized Transmuted Poisson-G Family of Distributions: Theory, Characterizations and Applications

2018 ◽  
pp. 759-779 ◽  
Author(s):  
Haitham Yousof ◽  
Ahmed Z Afify ◽  
Morad Alizadeh ◽  
G. G. Hamedani ◽  
S. Jahanshahi ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Order Statistics ◽  
Real Data ◽  
Model Parameters ◽  
Data Sets ◽  
Continuous Distributions ◽  
New Class ◽  
Mathematical Properties ◽  
Family Of Distributions

In this work, we introduce a new class of continuous distributions called the generalized poissonfamily which extends the quadratic rank transmutation map. We provide some special models for thenew family. Some of its mathematical properties including Rényi and q-entropies, order statistics andcharacterizations are derived. The estimations of the model parameters is performed by maximumlikelihood method. The Monte Carlo simulations is used for assessing the performance of the maximumlikelihood estimators. The ‡exibility of the proposed family is illustrated by means of two applicationsto real data sets.

Impact of sewer condition on urban flooding: an uncertainty analysis based on field observations and Monte Carlo simulations on full hydrodynamic models

2012 ◽  
Vol 65 (12) ◽  
pp. 2219-2227 ◽  
Author(s):  
M. van Bijnen ◽  
H. Korving ◽  
F. Clemens
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Surface Damage ◽  
Model Parameters ◽  
Field Observations ◽  
Sewer System ◽  
Sewer Systems ◽  
Calculation Results ◽  
Urban Pluvial Flooding ◽  
The Impact

In-sewer defects are directly responsible for affecting the performance of sewer systems. Notwithstanding the impact of the condition of the assets on serviceability, sewer performance is usually assessed assuming the absence of in-sewer defects. This leads to an overestimation of serviceability. This paper presents the results of a study in two research catchments on the impact of in-sewer defects on urban pluvial flooding at network level. Impacts are assessed using Monte Carlo simulations with a full hydrodynamic model of the sewer system. The studied defects include root intrusion, surface damage, attached and settled deposits, and sedimentation. These defects are based on field observations and translated to two model parameters (roughness and sedimentation). The calculation results demonstrate that the return period of flooding, number of flooded locations and flooded volumes are substantially affected by in-sewer defects. Irrespective of the type of sewer system, the impact of sedimentation is much larger than the impact of roughness. Further research will focus on comparing calculated and measured behaviour in one of the research catchments.

scholarly journals Parameter Optimization, Uncertainty Estimation and Sensitivity Analysis in Hydrological Modeling

2018 ◽  
Vol 3 (11) ◽  
pp. 66-72
Author(s):  
Rajesh VijayKumar Kherde ◽  
Priyadarshi H. Sawant
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Parameter Optimization ◽  
Optimum Parameter ◽  
Performance Measure ◽  
Uncertainty Estimation ◽  
Model Parameters ◽  
Local Optimum ◽  
Local Optima

This paper describes the application of Monte-Carlo simulations for parameter optimization, uncertainty estimation and sensitivity analysis using hydrological model developed by author [8] for Wardha River basin, Maharashtra, India. The Monte Carlo simulations revealed that the average values of parameters for the local optima of the calibration period seem to give good fit to the data and performance measure (NSE) does not differ significantly from the local optima of the respective calibration years. It is interesting to notice that, if the Monte Carlo simulations are carried out all over again, it generate yet another set of random numbers as realizations of model parameters. However the model objective function (NSE) differs mere by 0.1% by running the new set of realizations and the local optimum parameter values are close to the earlier local optima. It seems that the model structure is in agreement with the ‘‘equifinality’’ or ‘‘non-uniqueness’’ concept as many different parameter sets give good fit to the data. However particular area of the parameter space is observed to be dominant in fitting the available observations, this is in contradiction to Beven’s theory behind rejecting the idea of optimum parameter set.

Sign in / Sign up

Export Citation Format

Share Document