Browsing by Subject "molecular dynamics"

Now showing 1 - 3 of 3

Access status: Open Access ,
From quantity to quality: massive molecular dynamics simulation of nanostructures dunder plastic deformation in desktop and service grid distributed computing infrastructure
(Wydawnictwa AGH, 2013) Gatsenko, Olexander; Bekenev, Lev Valer'evič; Pavlov, Evgen Valerijovič; Gordienko, Ûri G.
The distributed computing infrastructure (DCI) on the basis of BOINC and EDGeS-bridge technologies for high-performance distributed computing is used for porting the sequential molecular dynamics (MD) application to its parallel version for DCIwith Desktop Grids (DGs) and Service Grids (SGs). The actual metrics of the working DG-SG DCI were measured, and the normal distribution of host performances, and signs of log-normal distributions of Rother characteristics (CPUs, RAM, and HDD per host) were found. The practical feasibility and high efficiency of the MD simulations on the basis of DG-SG DCI were demonstrated during the experiment with the massive MD simulations for the large quantity of aluminum nanocrystals (Statistical analysis (Kolmogorov-Smirnov test, moment analysis, and bootstrapping analysis) of the defect density distribution over the ensemble of nanocrystals had show that change of plastic deformation mode is followed by the qualitative change of defect density distribution type over ensemble of nanocrystals. Some limitations (fluctuating performance, unpredictable availability of resources, etc.) of the typical DG-SG DCI were outlined, and some advantages (high efficiency, high speedup, and low cost) were demonstrated. Deploying on DG DCI allows to get new scientific quality from the simulated quantity of numerous configurations by harnessing sufficient computational power to undertake MD simulations in a wider range of physical parameters (configurations) in a much shorter timeframe.
Access status: Open Access ,
Quantum-inspired evolutionary optimization of SLMoS2 two-phase structures
(Wydawnictwa AGH, 2022) Kuś, Wacław; Mrozek, Adam
The paper focuses on applying a Quantum Inspired Evolutionary Algorithm to achieve the optimization of 2D material containing two phases, 2H and 1T, of Molybdenum Disulphide (MoS$_{2}$ ). The goal of the optimization is to obtain a nanostructure with tailored mechanical properties. The design variables describe the shape of inclusion made from phase 1T in the 2H unit cell. The modification of the size of the inclusions leads to changes in the mechanical properties. The problem is solved with the use of computed mechanical properties on the basis of the Molecular Statics approach with ReaxFF potentials.
Access status: Open Access ,
Zastosowanie metod naturalnych w problemach poszukiwania optymalnego rozwiązania
(Wydawnictwa AGH, 2000) Jasińska-Suwada, Anna; Dzwinel, Witold; Rozmus, Krzysztof; Sołtysiak, Jacek
In the paper we present a new method, which can be used as a natural solver for searching the best solution in the multidimensional and multimodal parameter space. The method is based on a well-known simulation technique, i.e., molecular dynamics. To show advantages and disadvantages of the particle method in comparison to the standard genetic algorithm, we analyse efficiency of the methods in finding the global minimum of multi-dimensional and multi-modal test-bed functions and we calculate the evaluation indices. We analyse also the ways the solution space is explored and the parameters of algorithms adjusted. The optimal heuristics are proposed. The tests carried out show that the choice of the most appriopriate optimization method depends on type of a problem considered. We show that the particle method is more efficient for finding the optimal solution for multi-modal problems with distinct global extreme, while the genetic algorithm is better for deceptive functions with several locals extreme, which are placed far away from the global optimum. This comes from the different ways in which the particle method and genetic algorithm explore the solution space. The particle method can be used for initial analysis of functions, which character is unknown.