scholarly journals MC-PHS: A Monte Carlo Implementation of the Primary Hydration Shell for Protein Folding and Design

2003 ◽  
Vol 84 (2) ◽  
pp. 805-815 ◽  
Author(s):  
Alex Kentsis ◽  
Mihaly Mezei ◽  
Roman Osman
2016 ◽  
Vol 18 (18) ◽  
pp. 13052-13065 ◽  
Author(s):  
Emanuel K. Peter ◽  
Joan-Emma Shea ◽  
Igor V. Pivkin

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC).


Biopolymers ◽  
1989 ◽  
Vol 28 (6) ◽  
pp. 1059-1095 ◽  
Author(s):  
Jeffrey Skolnick ◽  
Andrzej Kolinski ◽  
Robert Yaris

2019 ◽  
Vol 25 (4) ◽  
pp. 329-340 ◽  
Author(s):  
Preston Hamlin ◽  
W. John Thrasher ◽  
Walid Keyrouz ◽  
Michael Mascagni

Abstract One method of computing the electrostatic energy of a biomolecule in a solution uses a continuum representation of the solution via the Poisson–Boltzmann equation. This can be solved in many ways, and we consider a Monte Carlo method of our design that combines the Walk-on-Spheres and Walk-on-Subdomains algorithms. In the course of examining the Monte Carlo implementation of this method, an issue was discovered in the Walk-on-Subdomains portion of the algorithm which caused the algorithm to sometimes take an abnormally long time to complete. As the problem occurs when a walker repeatedly oscillates between two subdomains, it is something that could cause a large increase in runtime for any method that used a similar algorithm. This issue is described in detail and a potential solution is examined.


Author(s):  
Michael Ford ◽  
Peter James

The need to predict changes in fracture toughness for materials where the tensile properties change through life, such as with irradiation, whilst accounting for geometric constraint effects, such as crack size, are clearly important. Currently one of the most likely approaches by which to develop such ability are through application of local approach models. These approaches appear to be sufficient in predicting lower shelf toughness under high constraint conditions, but may fail when attempting to predict toughness in the transition region, for low constraint geometries or for different irradiation states, when using the same parameters, making reliable predictions impossible. Cleavage toughness predictions in the transition regime are here made with a stochastic, Monte Carlo implementation of the recently proposed James-Ford-Jivkov model. This implementation is based around the creation of individual initiators following the experimentally observed distribution for specific reactor pressure vessel steel, and determining if these initiators form voids or cause cleavage failure using the model’s improved criterion for particle failure. This implementation has been presented previously in PVP2015-45905, where it was successfully applied across different constraint conditions; in the work presented here it is applied across different irradiation conditions for a second type of steel. The model predicts the fracture toughness in a large part of the transition region, demonstrates an ability to predict the irradiation shift and shows a level of scatter similar to that observed experimentally. All results presented, for a given material, are obtained without changes in the model parameters. This suggests that the model can be used predicatively for assessing toughness changes due to constraint-, irradiation- and temperature-driven plasticity changes.


Author(s):  
Michael Ford ◽  
Peter James

The need to predict changes in fracture toughness for materials where the tensile properties change through life, such as with irradiation, whilst accounting for geometric constraint effects, such as crack size, are clearly important. Currently one of the most likely approaches by which to develop such ability are through application of local approach models. These approaches appear to be sufficient in predicting lower shelf toughness under high constraint conditions, but may fail when attempting to predict toughness in the transition region or for low constraint geometries when using the same parameters, making predictions impossible. Cleavage toughness predictions in the transition regime that are then extended to low constraint conditions are here made with a stochastic, Monte Carlo implementation of the recently proposed James-Ford-Jivkov model. This implementation is based around the creation of individual initiators following the experimentally observed distribution for specific RPV steel, and determining if these initiators form voids or cause cleavage failure using the model’s improved criterion for particle failure. The model has shown to predict experimentally measured locations of cleavage initiators. Further, initial results from the Monte Carlo implementation of the model predicts the fracture toughness in a large part of the transition region, demonstrates an ability to predict the constraint shift and shows a level of scatter similar to that observed experimentally. All results presented, for a given material, are obtained without changes in the model parameters. This suggests that the model can be used predicatively for assessing toughness changes due to constraint- and temperature-driven plasticity changes.


2018 ◽  
Vol 12 (3) ◽  
pp. 1628-1654
Author(s):  
Samuel W. K. Wong ◽  
Jun S. Liu ◽  
S. C. Kou

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