Application of A Monte Carlo Approach to Surface Complexation Modelling

2004 ◽  
Vol 824 ◽  
Author(s):  
M.M. Askarieh ◽  
T.G. Heath ◽  
W.M. Tearle
Keyword(s):  
Monte Carlo ◽  
Model Parameters ◽  
Surface Complexes ◽  
Monte Carlo Approach ◽  
Ion Sorption ◽  
Wide Range ◽  
Complex Models ◽  
Chemical Conditions ◽  
Parameter Values

AbstractA Monte Carlo-based approach has been adopted for development of a chemical thermodynamic model to describe the goethite surface in contact with sodium nitrate solutions. The technique involves the calculation of the goethite surface properties for the chemical conditions corresponding to each experimental data point. The representation of the surface was based on a set of model parameters, each of which was either fixed or was randomly sampled from a specified range of values. Thousands of such model representations were generated for different selected sets of parameter values with the use of the standard geochemical speciation computer program, HARPHRQ. The method allowed many combinations of parameter values to be sampled that might not be achieved with a simple least-squares fitting approach. It also allowed the dependence of the quality of fit on each parameter to be analysed. The Monte Carlo approach is most appropriate in the development of complex models involving the fitting of several datasets with several fitting parameters.Introduction of selenate surface complexes allowed the model to be extended to represent selenate ion sorption, selenium being an important radioelement in evaluation of the long-term safety of ILW disposal. The sorption model gave good agreement with a wide range of experimental sorption datasets for selenate.

scholarly journals Monte Carlo ice flow modeling projects a new stable configuration for Columbia Glacier, Alaska, by c. 2020

2012 ◽  
Vol 6 (2) ◽  
pp. 893-930 ◽  
Author(s):  
W. Colgan ◽  
W. T. Pfeffer ◽  
H. Rajaram ◽  
W. Abdalati
Keyword(s):  
Monte Carlo ◽  
Dynamic Equilibrium ◽  
Stable Configuration ◽  
Ice Flow ◽  
Wide Range ◽  
Ensemble Mean ◽  
Iceberg Calving ◽  
Calving Rate ◽  
Parameter Values

Abstract. Due to the abundance of observational datasets collected since the onset of its retreat (c. 1983), Columbia Glacier, Alaska, provides an exciting modeling target. We perform Monte Carlo simulations of the form and flow of Columbia Glacier, using a 1-D (depth-integrated) flowline model, over a wide range of parameter values and forcings. An ensemble filter is imposed following spin-up to ensure that only simulations which accurately reproduce observed pre-retreat glacier geometry are retained; all other simulations are discarded. The selected ensemble of simulations reasonably reproduces numerous highly transient post-retreat observed datasets with a minimum of parameterizations. The selected ensemble mean projection suggests that Columbia Glacier will achieve a new dynamic equilibrium (i.e. "stable") ice geometry c. 2020, by which time iceberg calving rate will have returned to approximately pre-retreat values. Comparison of the observed 1957 and 2007 glacier geometries with the projected 2100 glacier geometry suggests that, by 2007, Columbia Glacier had already discharged ∼83 % of its total sea level rise contribution expected by 2100. This case study therefore highlights the difficulties associated with the future extrapolation of observed glacier mass loss rates that are dominated by iceberg calving.

Simulation of Freeway Weaving Areas

2002 ◽  
Vol 1802 (1) ◽  
pp. 115-124 ◽  
Author(s):  
Alexander Skabardonis
Keyword(s):  
Operating Conditions ◽  
Model Parameters ◽  
Sensitivity Factor ◽  
Microscopic Simulation ◽  
Lane Changing ◽  
Wide Range ◽  
Design Characteristics ◽  
Predicted Values ◽  
Demand Patterns ◽  
Parameter Values

The operation of freeway weaving sections is characterized by intense lane-changing maneuvers and complex vehicle interactions that often create bottlenecks along freeway facilities. The CORSIM microscopic simulation model was applied to simulate the operation of eight realworld weaving sites in California under a wide range of operating conditions. The results indicate that CORSIM with default parameter values underpredicts the speeds in the weaving section by about 19% on average. Numerous simulation runs were made with different values of the model parameters. The following parameters were found to significantly affect the CORSIM results: ( a) car-following sensitivity factor, ( b) lane-changing aggressiveness factor, and ( c) percentage of freeway through vehicles that yield to merging traffic. The calibrated CORSIM model reasonably replicated observed traffic operations at all test sites. The predicted average speeds were within ±5 mph for most test sites. Good agreement between measured and predicted values was obtained for all the combinations of design characteristics and demand patterns.

The Use of Laboratory Adsorption Data and Models to Predict Radionuclide Releases from a Geological Repository: a Brief History

1996 ◽  
Vol 465 ◽  
Author(s):  
Donald Langmuir
Keyword(s):  
Model Parameters ◽  
Total System ◽  
Linear Free Energy ◽  
Rock Types ◽  
Wide Range ◽  
Geological Repository ◽  
Adsorption Data ◽  
Complex Models ◽  
Energy Relationships ◽  
Diffuse Layer Model

ABSTRACTRadionuclide (RN) adsorption has long been recognized as important to assure the isolation of nuclear wastes in a geological repository [1]. Laboratory measured RN adsorption data have generally been expressed as distribution coefficient (Kd) values or adsorption isotherms. The proper application of these models is to site conditions nearly identical to those used in the laboratory adsorption experiments. This has required that multiple Kd's and isotherms be determined in a wide range of experiments designed to bracket expected repository conditions.The surface complexation (SC) adsorption models were introduced in the late 1970's. The best known of these models incorporate electrical double layer (EDL) theory [2]. Their use requires that the water chemistry and surface properties of adsorbing rocks and minerals be fully characterized. Adsorption is then studied as reactions involving specific aqueous RN species (often complexes) and specific surface sites. Because the SC models are relatively mechanistic, they may allow extrapolation of adsorption results to repository conditions that lie outside the limited experimental range used to parameterize a given model. Turner [3] has shown that the diffuse layer model (the simplest SC model) fits a wide range of RN adsorption data as well as the more complex models. Others have suggested ways to generalize and estimate SC model parameters for a variety of minerals, rocks and engineered materials (cf. [4,5,6,7,8,9,10,11,12]. Degueldre and Werlni [12] and Degueldre et al. [13] have proposed a simplified SC model for RN adsorption that avoids EDL theory, in which the adsorption of RN species is estimated from linear free energy relationships.It is appropriate to ask how accurately RN adsorption behavior must be known or understood for total system performance analysis (TSPA). In most geological settings now being considered for repository development globally, it may suffice to select bounding Kd values for the different rock types (cf. [14,15]). Use of the SC models to describe RN adsorption can provide us with increased confidence that minimum Kd's and the distribution of Kd values we might propose for TSPA are in fact conservative.

scholarly journals Limits of long-term selection against Neandertal introgression

2019 ◽  
Vol 116 (5) ◽  
pp. 1639-1644 ◽  
Author(s):  
Martin Petr ◽  
Svante Pääbo ◽  
Janet Kelso ◽  
Benjamin Vernot
Keyword(s):  
Negative Selection ◽  
Modern Human ◽  
Model Parameters ◽  
Human Populations ◽  
Modern Humans ◽  
High Coverage ◽  
Protein Coding ◽  
The Past ◽  
Wide Range

Several studies have suggested that introgressed Neandertal DNA was subjected to negative selection in modern humans. A striking observation in support of this is an apparent monotonic decline in Neandertal ancestry observed in modern humans in Europe over the past 45,000 years. Here, we show that this decline is an artifact likely caused by gene flow between modern human populations, which is not taken into account by statistics previously used to estimate Neandertal ancestry. When we apply a statistic that avoids assumptions about modern human demography by taking advantage of two high-coverage Neandertal genomes, we find no evidence for a change in Neandertal ancestry in Europe over the past 45,000 years. We use whole-genome simulations of selection and introgression to investigate a wide range of model parameters and find that negative selection is not expected to cause a significant long-term decline in genome-wide Neandertal ancestry. Nevertheless, these models recapitulate previously observed signals of selection against Neandertal alleles, in particular the depletion of Neandertal ancestry in conserved genomic regions. Surprisingly, we find that this depletion is strongest in regulatory and conserved noncoding regions and in the most conserved portion of protein-coding sequences.

Uncertainty analysis of calibrated parameter values of an urban storm water quality model using metropolis monte carlo algorithm

1997 ◽  
Vol 36 (5) ◽  
pp. 141-148 ◽  
Author(s):  
A. Mailhot ◽  
É. Gaume ◽  
J.-P. Villeneuve
Keyword(s):  
Monte Carlo ◽  
Uncertainty Analysis ◽  
Model Calibration ◽  
Monte Carlo Algorithm ◽  
Storm Water ◽  
Model Parameters ◽  
Calibration Data ◽  
Parameter Uncertainties ◽  
Metropolis Monte Carlo ◽  
Parameter Values

The Storm Water Management Model's quality module is calibrated for a section of Québec City's sewer system using data collected during five rain events. It is shown that even for this simple model, calibration can fail: similarly a good fit between recorded data and simulation results can be obtained with quite different sets of model parameters, leading to great uncertainty on calibrated parameter values. In order to further investigate the lack of data and data uncertainty impacts on calibration, we used a new methodology based on the Metropolis Monte Carlo algorithm. This analysis shows that for a large amount of calibration data generated by the model itself, small data uncertainties are necessary to significantly decrease calibrated parameter uncertainties. This also confirms the usefulness of the Metropolis algorithm as a tool for uncertainty analysis in the context of model calibration.

scholarly journals Monte Carlo ice flow modeling projects a new stable configuration for Columbia Glacier, Alaska, c. 2020

2012 ◽  
Vol 6 (6) ◽  
pp. 1395-1409 ◽  
Author(s):  
W. Colgan ◽  
W. T. Pfeffer ◽  
H. Rajaram ◽  
W. Abdalati ◽  
J. Balog
Keyword(s):  
Monte Carlo ◽  
Dynamic Equilibrium ◽  
Stable Configuration ◽  
Ice Flow ◽  
Wide Range ◽  
Ensemble Mean ◽  
Iceberg Calving ◽  
Calving Rate ◽  
Parameter Values

Abstract. Due to the abundance of observational datasets collected since the onset of its retreat (c. 1983), Columbia Glacier, Alaska, provides an exciting modeling target. We perform Monte Carlo simulations of the form and flow of Columbia Glacier, using a 1-D (depth-integrated) flowline model, over a wide range of parameter values and forcings. An ensemble filter is imposed following spin-up to ensure that only simulations that accurately reproduce observed pre-retreat glacier geometry are retained; all other simulations are discarded. The selected ensemble of simulations reasonably reproduces numerous highly transient post-retreat observed datasets. The selected ensemble mean projection suggests that Columbia Glacier will achieve a new dynamic equilibrium (i.e. "stable") ice geometry c. 2020, at which time iceberg calving rate will have returned to approximately pre-retreat values. Comparison of the observed 1957 and 2007 glacier geometries with the projected 2100 glacier geometry suggests that Columbia Glacier had already discharged ~82% of its projected 1957–2100 sea level rise contribution by 2007. This case study therefore highlights the difficulties associated with the future extrapolation of observed glacier mass loss rates that are dominated by iceberg calving.

scholarly journals Simulation of a long term memory device with a full bandstructure Monte Carlo approach

1995 ◽  
Vol 16 (8) ◽  
pp. 360-362 ◽  
Author(s):  
C.H. Lee ◽  
U. Ravaioli ◽  
K. Hess ◽  
C.A. Mead ◽  
P. Hasler
Keyword(s):  
Monte Carlo ◽  
Memory Device ◽  
Long Term Memory ◽  
Term Memory ◽  
Monte Carlo Approach

scholarly journals Off-Lattice Monte-Carlo Approach for Studying Nucleation and Evaporation Phenomena at the Molecular Scale

Materials ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2092
Author(s):  
Panagiotis E. Theodorakis ◽  
Yongjie Wang ◽  
Aiqiang Chen ◽  
Bin Liu
Keyword(s):  
Monte Carlo ◽  
Droplet Formation ◽  
Coarse Grained ◽  
Monte Carlo Approach ◽  
Lattice Monte Carlo ◽  
Research Areas ◽  
Droplet Nucleation ◽  
Proposed Model ◽  
Wide Range ◽  
Molecular Scale

Droplet nucleation and evaporation are ubiquitous in nature and many technological applications, such as phase-change cooling and boiling heat transfer. So far, the description of these phenomena at the molecular scale has posed challenges for modelling with most of the models being implemented on a lattice. Here, we propose an off-lattice Monte-Carlo approach combined with a grid that can be used for the investigation of droplet formation and evaporation. We provide the details of the model, its implementation as Python code, and results illustrating its dependence on various parameters. The method can be easily extended for any force-field (e.g., coarse-grained, all-atom models, and external fields, such as gravity and electric field). Thus, we anticipate that the proposed model will offer opportunities for a wide range of studies in various research areas involving droplet formation and evaporation and will also form the basis for further method developments for the molecular modelling of such phenomena.

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