Implementation of an Efficient Algorithm for Virtual Prototyping of Dynamics of Molecular Conformation

2009 ◽  
Author(s):  
Shanzhong Shawn Duan ◽  
Andrew Ries
Keyword(s):  
High Frequency ◽  
Efficient Algorithm ◽  
Molecular Conformation ◽  
Molecular System ◽  
Molecular Model ◽  
Virtual Prototyping ◽  
Molecular Chain ◽  
Integration Step ◽  
Computational Performance ◽  
Macro Scale

This paper presents an O(N) algorithm and its preliminary computer simulation results for virtual prototyping of molecular systems with a simple chain structure. The algorithm is based on proper integration between an internal coordinate method (ICM) and a multibody molecular model. ICM method makes the use of recursive relations possible between two adjacent subsets within a molecular system. The multibody molecular model takes the benefits of freezing degrees of freedom of some lightly excited high frequency bonds. Because these high frequency bonds would force the use of very small integration step sizes, which severely limits the time scales for virtual prototyping of dynamics of molecular conformation over long periods of time. Thus a new multiscale model and efficient algorithm is produced to increase computational efficiency for virtual prototyping of dynamical behaviors of molecular confirmation. This paper will be initially directed towards introduction of the new model and algorithm. Then attention will be turned to the implementation of the algorithm at macro scale, which can be used to demonstrate the validity of the procedure and algorithm. Final focus will be turned to the implementation of the algorithm to a simple molecular chain at micro scale. The algorithm gives an O(N) computational performance for formation/solution of equations of motion for a molecular chain system.

An Emerging O(N) Model and Algorithm for Virtual Prototyping of Dynamics of Molecular Conformation

2008 ◽  
Author(s):  
Andrew Ries ◽  
Shanzhong Shawn Duan
Keyword(s):  
Degrees Of Freedom ◽  
Molecular Conformation ◽  
Molecular System ◽  
Equations Of Motion ◽  
Integration Step ◽  
Computational Costs ◽  
System A ◽  
Hard Constraints ◽  
Solution Of Equations ◽  
Computationally Intensive

Molecular dynamics is effective for nano-scale phenomenon analysis. There are two major computational steps associated with computer simulation of dynamics of molecular conformation and they are the calculation of the interatomic forces and the formation and solution of the equations of motion. Currently, these two computational steps are treated separately, but in this paper an O(N) (order N) procedure is presented for an integration between these computational steps. For computational costs associated with calculating the interatomic forces, an internal coordinate method (ICM) approach is used for determining potentials due to both the bonding and non-bonding interactions. Thus, the potential gradients can be expressed as a combination of the potential in absolute and relative coordinates. For computational costs associated with the formation and solution of the equations of motion for the system, a constraint method that is used in computational multibody dynamics is utilized. This frees some degrees of freedom so that Kane’s method can be applied for the recursive formation and solution of equations of motion for the atomistic molecular system. Because the inclusion of lightly excited high frequency degrees of freedom, such as inter-atomic oscillations and rotation about double bonds would force the use of very small integration step sizes, holonomic constraints are introduced to freeze these “uninteresting” degrees of freedom. By introducing these hard constraints the time scale can be appropriately sized for to provide a less computationally intensive dynamic simulation of molecular conformation. The algorithm developed improves computational speed significantly when compared with any traditional O(N3) procedure.

Recent Developments of the Multiphysics Discrete Element Method for Additive Manufacturing Modeling and Simulation

2017 ◽  
Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos
Keyword(s):  
Additive Manufacturing ◽  
Discrete Element Method ◽  
Discrete Element ◽  
Additive Manufacture ◽  
Computational Tools ◽  
Computational Performance ◽  
Macro Scale ◽  
Recent Developments ◽  
Am Processes ◽  
Element Method

Recent years have seen a sharp increase in the development and usage of Additive Manufacturing (AM) technologies for a broad range of scientific and industrial purposes. The drastic microstructural differences between materials produced via AM and conventional methods has motivated the development of computational tools that model and simulate AM processes in order to facilitate their control for the purpose of optimizing the desired outcomes. This paper discusses recent advances in the continuing development of the Multiphysics Discrete Element Method (MDEM) for the simulation of AM processes. This particle-based method elegantly encapsulates the relevant physics of powder-based AM processes. In particular, the enrichment of the underlying constitutive behaviors to include thermoplasticity is discussed, as are methodologies for modeling the melting and re-solidification of the feedstock materials. Algorithmic improvements that increase computational performance are also discussed. The MDEM is demonstrated to enable the simulation of the additive manufacture of macro-scale components. Concluding remarks are given on the tasks required for the future development of the MDEM, and the topic of experimental validation is also discussed.

scholarly journals An Efficient Algorithm for Calculating the Heat Capacity of a Large-Scale Molecular System

2001 ◽  
Vol 10 (8) ◽  
pp. 756-761 ◽  
Author(s):  
Chao Yang ◽  
Donald W. Noid ◽  
Bobby G. Sumpter ◽  
Danny C. Sorensen ◽  
Robert E. Tuzun
Keyword(s):  
Heat Capacity ◽  
Efficient Algorithm ◽  
Large Scale ◽  
Molecular System

scholarly journals MEMS energy harvesters with a wide bandwidth for low frequency vibrations

2015 ◽  
Author(s):  
◽  
Nuh Sadi Yuksek
Keyword(s):  
Resonance Frequency ◽  
High Frequency ◽  
Maximum Output Power ◽  
Low Frequency ◽  
Maximum Output ◽  
Wide Bandwidth ◽  
Electromagnetic Power ◽  
Wide Range ◽  
Macro Scale ◽  
Load Resistor

We have designed and built macro-scale wideband electrostatic and electromagnetic power harvesters for low frequency vibration. Initially, MEMS capacitive plates for power harvesting have been designed, modeled and fabricated, and characterized. It was designed with a 2 x 2 mm2 movable metallic plate with a thickness of 10 [mu]m suspended by four straight beams above a fixed electrode with a gap of 10 [mu]m to form a variable capacitor. The suspension beams are made with a width, thickness and total length of 20 [mu]m, 10 [mu]m and 1500 [mu]m, respectively. It was found that the single cavity device can harvest almost 180 nW peak power across a 100 k[omega] load resistor at 5g. The harvested power was dependent on excitation amplitude and supplied DC voltage. The MEMS capacitive energy harvester was integrated with two impact oscillators at 18 Hz and 25 Hz for transferring energy from low frequency structural vibration with varying mechanical spectra to high frequency vibration of a high resonance frequency cantilever at 605 Hz. The results demonstrate that the device was able to harvest power on a wide range from 14 to 39 Hz at 1g excitation. The harvested power was 96 nW on a 100 k[omega] load resistor. We also studied a macro-scale electromagnetic power harvester with multi-impact oscillations to achieve a broad bandwidth at low frequency vibrations. The device consists of three low frequency cantilever designed to resonate at 12 Hz, 19 Hz and 40 Hz, a high frequency cantilever with resonance frequency of 210 Hz and a pick-up coil fixed at the tip of the high frequency cantilever. This results in a wide bandwidth response from 11-62 Hz at 1 g. A maximum output power of 23.5 [mu]W can be harvested at 1 g acceleration on an optimum load resistor of 22 [omega].

scholarly journals Pricing of Arithmetic Asian Options under Stochastic Volatility Dynamics: Overcoming the Risks of High-Frequency Trading

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2251
Author(s):  
Chih-Chen Hsu ◽  
Chung-Gee Lin ◽  
Tsung-Jung Kuo
Keyword(s):  
Stochastic Volatility ◽  
High Frequency ◽  
Monte Carlo Model ◽  
Computation Time ◽  
Taylor Series Expansion ◽  
High Frequency Trading ◽  
Asian Options ◽  
Computational Performance ◽  
Proposed Model ◽  
Approximate Analytical Solutions

This research extended the model developed by Hull and White by integrating Taylor-series expansion into the model for deriving approximate analytical solutions for stochastic volatility forward-starting Asian options. Numerical experiments were performed to compare the proposed model with the Monte Carlo model over numerous simulations and demonstrated that the developed model has a pricing accuracy greater than 99%. Furthermore, the computation time was approximately 10−5 s for each simulation. The model’s outstanding computational performance demonstrates its capability to address the challenges of high-frequency trading.

EasyAmber: A comprehensive toolbox to automate the molecular dynamics simulation of proteins

2020 ◽  
Vol 18 (06) ◽  
pp. 2040011 ◽  
Author(s):  
Dmitry Suplatov ◽  
Yana Sharapova ◽  
Vytas Švedas
Keyword(s):  
Molecular Dynamics ◽  
Model Building ◽  
Molecular System ◽  
Molecular Model ◽  
Protein Structures ◽  
Protein Flexibility ◽  
Dynamics Simulation ◽  
Factors Affecting ◽  
Production Run ◽  
Dynamics Simulations

Conformational plasticity of the functionally important regions and binding sites in protein/enzyme structures is one of the key factors affecting their function and interaction with substrates/ligands. Molecular dynamics (MD) can address the challenge of accounting for protein flexibility by predicting the time-dependent behavior of a molecular system. It has a potential of becoming a particularly important tool in protein engineering and drug discovery, but requires specialized training and skills, what impedes practical use by many investigators. We have developed the easyAmber — a comprehensive set of programs to automate the molecular dynamics routines implemented in the Amber package. The toolbox can address a wide set of tasks in computational biology struggling to account for protein flexibility. The automated workflow includes a complete set of steps from the initial “static” molecular model to the MD “production run”: the full-atom model building, optimization/equilibration of the molecular system, classical/conventional and accelerated molecular dynamics simulations. The easyAmber implements advanced MD protocols, but is highly automated and easy-to-operate to attract a broad audience. The toolbox can be used on a personal desktop station equipped with a compatible gaming GPU-accelerator, as well as help to manage huge workloads on a powerful supercomputer. The software provides an opportunity to operate multiple simulations of different proteins at the same time, thus significantly increasing work efficiency. The easyAmber takes the molecular dynamics to the next level in terms of usability for complex processing of large volumes of data, thus supporting the recent trend away from inefficient “static” approaches in biology toward a deeper understanding of the dynamics in protein structures. The software is freely available for download at https://biokinet.belozersky.msu.ru/easyAmber, no login required.

Microscopic Observation of Energy Propagation in Polymeric Fluids Crossing a Barrier

2008 ◽  
Author(s):  
Rashad Aouf ◽  
Vojislav Ilic
Keyword(s):  
Heat Transfer ◽  
Temperature Gradient ◽  
Large Scale ◽  
Complex Geometry ◽  
Molecular Model ◽  
Heat Transfer Process ◽  
Transfer Model ◽  
Energy Propagation ◽  
Lennard Jones ◽  
Macro Scale

A major challenge facing tumour treatment procedures, including hyperthermia, is the inadequate modelling of the bio-heat transfer process. Therefore, an accurate mathematical bio-heat transfer model has to precisely quantify the temperature distribution within a complex geometry of a tumour tissue, in order to help optimize unwanted side effects for patients and minimize (avoid) collateral tissue damage. This study examines the three-dimensional molecular dynamics (MDs) simulation of a Lennard-Jones fluid in the hope of contributing to the understanding of the propagation of a thermal wave in fluids causing phase change i.e. irreversible gelation. It is intended to establish, from such information, a useful benchmark for application to large scale phenomena involving macro scale heat transfer. Specifically, this study examines assemblies of N particles (N = 500 atoms) and analyses the microscopic simulation of double well interaction with permanent molecular bond formation at various temperatures within the range 1–2.5Kb/εT. The dynamics of the fluid is also being studied under the influence of a temperature gradient, dt/dx, where neighbouring particles (i.e. atoms/molecules) are randomly linked by permanent bonds to form clusters of different sizes. The atomic/molecular model consist of an isothermal source and sink whose particles are linked by springs to lattice sites to avoid melting, and a bulk of 500 atoms/molecules in the middle representing the Lennard-Jones fluid. Then, this study simulates the energy propagation following the temperature gradient between the heat source and heat sink at T1 = 2.5 and T2 = 1.5 respectively. The potential equation involved in this study is given by the Finitely Extensible Non Elastic (FENE) and Lennard-Jones (LJ) interaction potential. It is observed that the atoms of the bulk start to form a large cluster (∼ 300 atoms) with long time of simulation estimated by 106 time steps where τ = SQRT(ε/mσ2) and Δt = 10−3. It is also obtained that the potential energy of 13.65KbT across a barrier to establish permanent bonds giving rise to irreversible gel formation. All the parameters used in this study are expressed in Lennard-Jones units.

scholarly journals Exploration on molecular dynamics simulation methods of microscopic wetting process for coal dust

2021 ◽  
Author(s):  
Qi Zhang ◽  
Xinyi Chen ◽  
Hetang Wang ◽  
Chaohang Xu
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Molecular System ◽  
Molecular Model ◽  
Coal Dust ◽  
Molecular Layer ◽  
Dust Control ◽  
Dust Removal ◽  
Dynamics Simulation ◽  
Wetting Process

AbstractWet dust removal is one of the main technical measures in coal dust control, and coal dust wetting is the key factor to determine the effect of wet dust removal. In order to explore the micro-wetting process of coal dust, this paper uses molecular dynamics simulation to study the micro-wetting process of coal dust in different simulation conditions. The molecular dynamics simulation was carried out under different ensemble, thermodynamic states as well as relaxation pretreatment methods, then the H2O molecular layer and coal dust molecular layer in each simulation were quantitatively analyzed by relative concentration. The research results show that a method for establishing molecular model of lignite is proposed and the 2D periodic surface structure is more reasonable. The surface system of coal-H2O molecule is established by NVT aeration method, where the simulation result is close to the actual coal dust wetting process. The simulation effect of medium and large coal dust-H2O molecular system is better than that of small coal dust-H2O molecular system. This study provides a new solution for changing the empirical method of molecular dynamics simulation of coal system wetting and oversimplification of coal system.

scholarly journals Implementation Of Data Mining On Suzuki Motorcycle Sales In Gemilang Motor Prosperous With Apriori Algorithm Method

2020 ◽  
Vol 2 (1) ◽  
pp. 23-29
Author(s):  
Anju Eliarsyam Lubis ◽  
Paska Marto Hasugian
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Strong Correlation ◽  
High Frequency ◽  
Efficient Algorithm ◽  
Pattern Analysis ◽  
Apriori Algorithm ◽  
Frequency Pattern ◽  
One Stage ◽  
Confidence Value

The sale is part of the marketing that determine the survival of the company. With the sale, the company can achieve the goals or targets. To be a company that continues to grow in motorcycle sales, the company should be able to compete in increasing sales volume. Starting from the launch prodak the best in sophistication motorcycles, up to a very attractive price cuts the attention of consumers. Things like that already sanggat often do, so the company can still compete, Motorcycles is a two-wheeled transfortasi tool used more and more common people. From teenagers to old orag, not infrequently motorcycle including important sanggat needs. If we do not have it feels very hard in activity quickly. Make sales without any restriction of sales data accumulate, until finally overwhelmed the company in terms of taking care of customer files. To find the most sales required Apriori Algorithm. Apriori algorithm, including the type of association rules on Data Mining. One stage of association that can produce an efficient algorithm is with high frequency pattern analysis. In an association can be determined by two benchmarks, namely: Support and Confidence. Support "penunang value" is the percentage of combinations of items in a database, and Confidence "value certainty" is strong correlation between the items in an association's rules. Apriori algorithm, including the type of association rules on Data Mining. One stage of association that can produce an efficient algorithm is with high frequency pattern analysis. In an association can be determined by two benchmarks, namely: Support and Confidence. Support "penunang value" is the percentage of combinations of items in a database, and Confidence "value certainty" is strong correlation between the items in an association's rules. Apriori algorithm, including the type of association rules on Data Mining. One stage of association that can produce an efficient algorithm is with high frequency pattern analysis. In an association can be determined by two benchmarks, namely: Support and Confidence. Support "penunang value" is the percentage of combinations of items in a database, and Confidence "value certainty" is strong correlation between the items in an association's rules.

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