scholarly journals On the modeling of MMC for use in large scale dynamic simulations

2016 ◽  
Author(s):  
Julian Freytes ◽  
Lampros Papangelis ◽  
Hani Saad ◽  
Pierre Rault ◽  
Thierry Van Cutsem ◽  
...  
Keyword(s):  
Large Scale ◽  
Dynamic Simulations

The Design and Comparison Study on the Large-Scale End-Effector of Large Space Manipulator

2011 ◽  
Vol 308-310 ◽  
pp. 2095-2103
Author(s):  
Fei Feng ◽  
Yi Wei Liu ◽  
Hong Liu ◽  
He Gao Cai
Keyword(s):  
Large Scale ◽  
Space Structure ◽  
Comparison Study ◽  
Residual Vibration ◽  
Steel Cable ◽  
Dynamic Simulations ◽  
Large Space ◽  
Space Manipulator ◽  
End Effector ◽  
Large Space Manipulator

The space manipulator which is mounted on a space structure or spacecraft to manipulate space payloads is important for the on-orbit-servicing. Its manipulation tasks depend on its end-effector. The flexibility of the large space manipulator will result in residual vibration on its tip, and let the manipulator have poor capability of end positioning. To overcome the drawbacks mentioned-above, the end-effector needs strong capability of misalignment tolerance and soft capturing. On the base of these requirements and analysis, two kinds of end-effector schemes are presented and designed in detail. The essential performances are in comparison based on the results of dynamic simulations and experiments. Consequently, the conclusion is drawn that the steel cable-snared end-effector which captures the interface by winding the grapple fixture probe, is the best scheme that can combine the ability of soft capturing and great misalignment tolerance perfectly.

Use of a Central Pattern Generator for Control of a Muscle-Actuated Simulation of Pedaling

2009 ◽  
Author(s):  
Martin Schultze ◽  
Darryl G. Thelen
Keyword(s):  
Central Pattern Generator ◽  
Large Scale ◽  
Pattern Generator ◽  
Open Loop ◽  
Dynamic Simulations ◽  
Short Time ◽  
Time Frames ◽  
Large Scale Simulations ◽  
Clinical Problems

Muscle actuated forward dynamic simulations have provided tremendous insights into the mechanics of locomotion. However, the controllers used for large scale simulations have often been open-loop, with the muscle excitations prescribed as a function of time [1]. Due to the inherently unstable nature of bipedal movement, this means that perturbation-type analyses are often limited to short time frames after the perturbation is introduced [2]. However for many clinical problems, it would be desirable to predict how periodic locomotion reestablishes following a change to the system or perturbation from the environment.

VIBRATION ANALYSIS OF A GRAPHENE NANORIBBON UNDER HARMONIC LORENTZ FORCE USING A HYBRID MODAL-MOLECULAR DYNAMICS METHOD

2014 ◽  
Vol 14 (02) ◽  
pp. 1350057 ◽  
Author(s):  
R. D. FIROUZ-ABADI ◽  
H. MOHAMMADKHANI ◽  
H. AMINI
Keyword(s):  
Molecular Dynamics ◽  
Vibration Analysis ◽  
Large Scale ◽  
Nonlinear Vibrations ◽  
Graphene Nanoribbon ◽  
Molecular Dynamics Method ◽  
Dynamic Simulations ◽  
Resonance Frequencies ◽  
Dynamics Method ◽  
Good Agreement

An efficient hybrid modal-molecular dynamics method is developed for the vibration analysis of large scale nanostructures. Using the reduced order method, presented in this paper, linear and nonlinear vibrations of a suspended graphene nanoribbon (GNR) carrying an electric current in a harmonic magnetic field are investigated. The resonance frequencies as well as the nonlinear vibration response obtained by the present technique and direct molecular dynamic simulations are in very good agreement. Also, the obtained results illustrate the hardening behavior of nonlinear vibrations which is diminished by stretching the GNR.

scholarly journals Mapping the Intramolecular Communications among Different Glutamate Dehydrogenase States Using Molecular Dynamics

Biomolecules ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 798
Author(s):  
Shaherin Basith ◽  
Balachandran Manavalan ◽  
Tae Hwan Shin ◽  
Gwang Lee
Keyword(s):  
Network Analysis ◽  
Glutamate Dehydrogenase ◽  
Conformational Changes ◽  
Large Scale ◽  
Structural Information ◽  
System Development ◽  
Enzyme Regulation ◽  
Nervous System Development ◽  
Dynamic Simulations ◽  
Carbon And Nitrogen

Glutamate dehydrogenase (GDH) is a ubiquitous enzyme that catalyzes the reversible oxidative deamination of glutamate to α-ketoglutarate. It acts as an important branch-point enzyme between carbon and nitrogen metabolisms. Due to the multifaceted roles of GDH in cancer, hyperinsulinism/hyperammonemia, and central nervous system development and pathologies, tight control of its activity is necessitated. To date, several GDH structures have been solved in its closed form; however, intrinsic structural information in its open and apo forms are still deficient. Moreover, the allosteric communications and conformational changes taking place in the three different GDH states are not well studied. To mitigate these drawbacks, we applied unbiased molecular dynamic simulations (MD) and network analysis to three different GDH states i.e., apo, active, and inactive forms, for investigating their modulatory mechanisms. In this paper, based on MD and network analysis, crucial residues important for signal transduction, conformational changes, and maps of information flow among the different GDH states were elucidated. Moreover, with the recent findings of allosteric modulators, an allosteric wiring illustration of GDH intramolecular signal transductions would be of paramount importance to obtain the process of this enzyme regulation. The structural insights gained from this study will pave way for large-scale screening of GDH regulators and could support researchers in the design and development of new and potent GDH ligands.

scholarly journals Surrogate Model-Based Uncertainty Quantification for a Helical Gear Pair

2021 ◽  
pp. 191-207
Author(s):  
Thomas Diestmann ◽  
Nils Broedling ◽  
Benedict Götz ◽  
Tobias Melz
Keyword(s):  
Uncertainty Quantification ◽  
Large Scale ◽  
Early Stage ◽  
Gaussian Process Regression ◽  
System Size ◽  
Transmission Systems ◽  
Dynamic Simulations ◽  
Drive State ◽  
Early Stage Design ◽  
Noise Vibration

AbstractCompetitive industrial transmission systems must perform most efficiently with reference to complex requirements and conflicting key performance indicators. This design challenge translates into a high-dimensional multi-objective optimization problem that requires complex algorithms and evaluation of computationally expensive simulations to predict physical system behavior and design robustness. Crucial for the design decision-making process is the characterization, ranking, and quantification of relevant sources of uncertainties. However, due to the strict time limits of product development loops, the overall computational burden of uncertainty quantification (UQ) may even drive state-of-the-art parallel computing resources to their limits. Efficient machine learning (ML) tools and techniques emphasizing high-fidelity simulation data-driven training will play a fundamental role in enabling UQ in the early-stage development phase.This investigation surveys UQ methods with a focus on noise, vibration, and harshness (NVH) characteristics of transmission systems. Quasi-static 3D contact dynamic simulations are performed to evaluate the static transmission error (TE) of meshing gear pairs under different loading and boundary conditions. TE indicates NVH excitation and is typically used as an objective function in the early-stage design process. The limited system size allows large-scale design of experiments (DoE) and enables numerical studies of various UQ sampling and modeling techniques where the design parameters are treated as random variables associated with tolerances from manufacturing and assembly processes. The model accuracy of generalized polynomial chaos expansion (gPC) and Gaussian process regression (GPR) is evaluated and compared. The results of the methods are discussed to conclude efficient and scalable solution procedures for robust design optimization.

scholarly journals ReacNetGenerator: an Automatic Reaction Network Generator for Reactive Molecular Dynamic Simulations

2019 ◽  
Author(s):  
Jinzhe Zeng ◽  
Liqun Cao ◽  
John ZH Zhang ◽  
Chih-Hao Chin ◽  
Tong Zhu
Keyword(s):  
Large Scale ◽  
Reaction Network ◽  
Md Simulations ◽  
Dynamic Simulations ◽  
New Approach ◽  
Molecular Systems ◽  
Reactive Molecular Dynamics ◽  
Analysis Process ◽  
Network Generator ◽  
Complex Trajectories

The reactive molecular dynamics is widely used in the field of computational chemistry to study the reaction mechanisms in molecular systems. However, complex trajectories that are difficult to analyze have become a major obstacle to its application in large-scale systems. In this work, a new approach named ReacNetGen is developed to obtain reaction networks based on reactive MD simulations. Molecular species can be automatically generated from the 3D coordinates of atoms in the trajectory. The hidden Markov model is used to filter the noises in the trajectory, which makes the analysis process easier and more accurate. Compared with manual analysis, the advantage of this method in terms of efficiency is very obvious for large-scale simulation trajectories. It has been successfully used in the analysis of the simulated oxidation of 4-component RP-3 and methane.

Equipment Representations for Shock Calculations: Time Domain Dirichlet to Neumann Maps

1995 ◽  
Author(s):  
Paul E. Barbone
Keyword(s):  
Time Domain ◽  
High Frequency ◽  
Large Scale ◽  
Dynamic Simulations ◽  
Naval Vessel ◽  
System Parameters ◽  
Equivalent Time ◽  
Modal Density ◽  
Modal Summation ◽  
High Modal Density

Abstract Large scale dynamic simulations can often be simplified by appropriately replacing large portions of the domain by a Dirichlet to Neumann, or DtN map (Givoli, 1992). Here we consider the problem of representing a dynamical subsystem, a piece of equipment aboard a naval vessel for example, in terms of an equivalent time domain DtN map. The exact DtN map is computed as a modal summation. The exact map is then approximated in both the low and high modal density regimes. The approximate DtN in the high modal density limit is computed utilizing fuzzy-structures concepts recently developed by Pierce, Sparrow and Russel (1993) and others. The resulting DtN map depends on just two easily determined system parameters: the total mass and the high-frequency stiffness.

Molecular dynamic simulations of plasticity and phase transition in Mg polycrystalline under shock compression

2021 ◽  
Author(s):  
Zhiyong Jian ◽  
Yangchun Chen ◽  
Shifang xiao ◽  
Liang Wang ◽  
Xiaofan Li ◽  
...  
Keyword(s):  
Phase Transition ◽  
Grain Boundaries ◽  
Large Scale ◽  
Local Stress ◽  
The Body ◽  
Nonequilibrium Molecular Dynamics ◽  
Dynamic Simulations ◽  
Hexagonal Close Packed ◽  
Dynamics Simulations ◽  
Bcc Phase

Abstract We have investigated the shock-induced plasticity and phase transition in the hexagonal columnar nanocrystalline (HCN) Mg by large-scale nonequilibrium molecular dynamics simulations (NEMD). The preexisting grain boundaries (GBs) induce the nucleation of the {10-12} twins for the local stress relaxation. The twins grow up in grains leading to the orientation rotation. The phase transition from the hexagonal close-packed (HCP) phase to the body-centered cubic (BCC) phase begins when the migrating twin grain boundaries (TGBs) meet in A- and C-type grains, and continues in the plastic deformation regions. The phase-transition pathway involves two steps: the reorientation and phase transformation.

Sign in / Sign up

Export Citation Format

Share Document