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.

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 Thermodynamic Impact of Mineral Surfaces on Amino Acid Polymerization: Aspartate Dimerization on Two-Line Ferrihydrite, Anatase, and γ-Alumina

Minerals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 234
Author(s):  
Norio Kitadai ◽  
Kumiko Nishiuchi ◽  
Wataru Takahagi
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Model Parameters ◽  
Mineral Surfaces ◽  
Adsorbed State ◽  
Interfacial Conditions ◽  
Wide Range ◽  
Evolution Of Life ◽  
Adsorption Data ◽  
Surface Liquid

The presence of amino acids in diverse extraterrestrial materials has suggested that amino acids are widespread in our solar system, serving as a common class of components for the chemical evolution of life. However, there are a limited number of parameters available for modeling amino acid polymerization at mineral–water interfaces, although the interfacial conditions inevitably exist on astronomical bodies with surface liquid water. Here, we present a set of extended triple-layer model parameters for aspartate (Asp) and aspartyl-aspartate (AspAsp) adsorptions on two-line ferrihydrite, anatase, and γ-alumina determined based on the experimental adsorption data. By combining the parameters with the reported thermodynamic constants for amino acid polymerization in water, we computationally demonstrate how these minerals impact the AspAsp/Asp equilibrium over a wide range of environmental conditions. It was predicted, for example, that two-line ferrihydrite strongly promotes Asp dimerization, leading to the AspAsp/Asp ratio in the adsorbed state up to 41% even from a low Asp concentration (0.1 mM) at pH 4, which is approximately 5 × 107 times higher than that attainable without mineral (8.5 × 10−6%). Our exemplified approach enables us to screen wide environmental settings for abiotic peptide synthesis from a thermodynamic perspective, thereby narrowing down the geochemical situations to be explored for life’s origin on Earth and Earth-like habitable bodies.

Additive-multiplicative description of extrathermodynamic relations: Application to solvent effect

1990 ◽  
Vol 55 (3) ◽  
pp. 634-643 ◽  
Author(s):  
Oldřich Pytela
Keyword(s):  
Solvent Effect ◽  
Additive Model ◽  
Multiplicative Model ◽  
Data Matrix ◽  
Statistical Parameters ◽  
Model Application ◽  
Mutual Correlation ◽  
Linear Free Energy ◽  
Cross Terms ◽  
Energy Relationships

The paper is focused on evaluation of significance of the additive-multiplicative model of extrathermodynamic relations (linear free energy relationships) as compared with the additive model. Application of the method of conjugated deviations to a data matrix describing manifestations of solvent effects in 367 processes in solutions (6 334 data) has shown that introduction of cross-terms into the additive model is statistically significant for a model with two and particularly three parameters. At the same time the calculation has provided a new set of statistical parameters for description of solvent effect with application of the additive-multiplicative model. Compared with an analogous set designated for the additive model, the new parameters show a lower mutual correlation, retaining the same nature of the properties described, i.e. polarity-acidity (PAC parameter), polarity-basicity (PBC), and polarity-polarizability (PPC).

scholarly journals Inferring Linkage Disequilibrium Between a Polymorphic Marker Locus and a Trait Locus in Natural Populations

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 457-467 ◽  
Author(s):  
Z W Luo ◽  
S H Tao ◽  
Z-B Zeng
Keyword(s):  
Linkage Disequilibrium ◽  
Allele Frequency ◽  
Random Mating ◽  
Natural Populations ◽  
Polymorphic Marker ◽  
Marker Locus ◽  
Model Parameters ◽  
Phenotypic Variance ◽  
Wide Range ◽  
Trait Locus

Abstract Three approaches are proposed in this study for detecting or estimating linkage disequilibrium between a polymorphic marker locus and a locus affecting quantitative genetic variation using the sample from random mating populations. It is shown that the disequilibrium over a wide range of circumstances may be detected with a power of 80% by using phenotypic records and marker genotypes of a few hundred individuals. Comparison of ANOVA and regression methods in this article to the transmission disequilibrium test (TDT) shows that, given the genetic variance explained by the trait locus, the power of TDT depends on the trait allele frequency, whereas the power of ANOVA and regression analyses is relatively independent from the allelic frequency. The TDT method is more powerful when the trait allele frequency is low, but much less powerful when it is high. The likelihood analysis provides reliable estimation of the model parameters when the QTL variance is at least 10% of the phenotypic variance and the sample size of a few hundred is used. Potential use of these estimates in mapping the trait locus is also discussed.

scholarly journals Antifungal Activity of Propyl Disulfide from Neem (Azadirachta indica) in Vapor and Agar Diffusion Assays against Anthracnose Pathogens (Colletotrichum gloeosporioides and Colletotrichum acutatum) in Mango Fruit

2021 ◽  
Vol 9 (4) ◽  
pp. 839
Author(s):  
Muhammad Rafiullah Khan ◽  
Vanee Chonhenchob ◽  
Chongxing Huang ◽  
Panitee Suwanamornlert
Keyword(s):  
Antifungal Activity ◽  
Mycelial Growth ◽  
Colletotrichum Gloeosporioides ◽  
Colletotrichum Acutatum ◽  
Model Parameters ◽  
Pathogenicity Test ◽  
Agar Diffusion ◽  
Wide Range ◽  
Significant Difference ◽  
Diffusion Assay

Microorganisms causing anthracnose diseases have a medium to a high level of resistance to the existing fungicides. This study aimed to investigate neem plant extract (propyl disulfide, PD) as an alternative to the current fungicides against mango’s anthracnose. Microorganisms were isolated from decayed mango and identified as Colletotrichum gloeosporioides and Colletotrichum acutatum. Next, a pathogenicity test was conducted and after fulfilling Koch’s postulates, fungi were reisolated from these symptomatic fruits and we thus obtained pure cultures. Then, different concentrations of PD were used against these fungi in vapor and agar diffusion assays. Ethanol and distilled water were served as control treatments. PD significantly (p ≤ 0.05) inhibited more of the mycelial growth of these fungi than both controls. The antifungal activity of PD increased with increasing concentrations. The vapor diffusion assay was more effective in inhibiting the mycelial growth of these fungi than the agar diffusion assay. A good fit (R2, 0.950) of the experimental data in the Gompertz growth model and a significant difference in the model parameters, i.e., lag phase (λ), stationary phase (A) and mycelial growth rate, further showed the antifungal efficacy of PD. Therefore, PD could be the best antimicrobial compound against a wide range of microorganisms.

scholarly journals A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Karim El-Laithy ◽  
Martin Bogdan
Keyword(s):  
Reinforcement Learning ◽  
Spike Timing ◽  
Neural Representation ◽  
Model Parameters ◽  
Learning Framework ◽  
Reference Target ◽  
Wide Range ◽  
Spiking Network ◽  
Dynamic Synapses ◽  
Exclusive Or

An integration of both the Hebbian-based and reinforcement learning (RL) rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

scholarly journals Modelling the Inflation and Elastic Instabilities of Rubber-Like Spherical and Cylindrical Shells Using a New Generalised Neo-Hookean Strain Energy Function

2021 ◽  
Author(s):  
Afshin Anssari-Benam ◽  
Andrea Bucchi ◽  
Giuseppe Saccomandi
Keyword(s):  
Experimental Data ◽  
Energy Function ◽  
Limit Point ◽  
Strain Energy ◽  
Cylindrical Shells ◽  
Strain Energy Function ◽  
Model Parameters ◽  
Wide Range ◽  
Cylindrical Tubes ◽  
Gent Model

AbstractThe application of a newly proposed generalised neo-Hookean strain energy function to the inflation of incompressible rubber-like spherical and cylindrical shells is demonstrated in this paper. The pressure ($P$ P ) – inflation ($\lambda $ λ or $v$ v ) relationships are derived and presented for four shells: thin- and thick-walled spherical balloons, and thin- and thick-walled cylindrical tubes. Characteristics of the inflation curves predicted by the model for the four considered shells are analysed and the critical values of the model parameters for exhibiting the limit-point instability are established. The application of the model to extant experimental datasets procured from studies across 19th to 21st century will be demonstrated, showing favourable agreement between the model and the experimental data. The capability of the model to capture the two characteristic instability phenomena in the inflation of rubber-like materials, namely the limit-point and inflation-jump instabilities, will be made evident from both the theoretical analysis and curve-fitting approaches presented in this study. A comparison with the predictions of the Gent model for the considered data is also demonstrated and is shown that our presented model provides improved fits. Given the simplicity of the model, its ability to fit a wide range of experimental data and capture both limit-point and inflation-jump instabilities, we propose the application of our model to the inflation of rubber-like materials.

scholarly journals Study on Friction in Automotive Shock Absorbers Part 1: Friction Simulation Using a Dynamic Friction Model in the Contact Zone of an FEM Model

Vehicles ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 212-232
Author(s):  
Ludwig Herzog ◽  
Klaus Augsburg
Keyword(s):  
Ride Comfort ◽  
Viscous Friction ◽  
Simulation Method ◽  
Friction Model ◽  
Model Parameters ◽  
Dynamic Friction ◽  
Friction Modeling ◽  
Shock Absorbers ◽  
Operation Conditions ◽  
Wide Range

The important change in the transition from partial to high automation is that a vehicle can drive autonomously, without active human involvement. This fact increases the current requirements regarding ride comfort and dictates new challenges for automotive shock absorbers. There exist two common types of automotive shock absorber with two friction types: The intended viscous friction dissipates the chassis vibrations, while the unwanted solid body friction is generated by the rubbing of the damper’s seals and guides during actuation. The latter so-called static friction impairs ride comfort and demands appropriate friction modeling for the control of adaptive or active suspension systems. In this article, a simulation approach is introduced to model damper friction based on the most friction-relevant parameters. Since damper friction is highly dependent on geometry, which can vary widely, three-dimensional (3D) structural FEM is used to determine the deformations of the damper parts resulting from mounting and varying operation conditions. In the respective contact zones, a dynamic friction model is applied and parameterized based on the single friction point measurements. Subsequent to the parameterization of the overall friction model with geometry data, operation conditions, material properties and friction model parameters, single friction point simulations are performed, analyzed and validated against single friction point measurements. It is shown that this simulation method allows for friction prediction with high accuracy. Consequently, its application enables a wide range of parameters relevant to damper friction to be investigated with significantly increased development efficiency.

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