Automated Quantification of the Impact of Defects on the Mechanical Behavior of Deoxyribonucleic Acid Origami Nanoplates

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Bowen Liang ◽  
Anand Nagarajan ◽  
Michael W. Hudoba ◽  
Ricardo Alvarez ◽  
Carlos E. Castro ◽  
...  
Keyword(s):  
Mechanical Behavior ◽  
Self Assembly ◽  
Adaptive Mesh Refinement ◽  
Deoxyribonucleic Acid ◽  
Structural Integrity ◽  
Adaptive Mesh ◽  
Dna Origami ◽  
Structured Adaptive Mesh Refinement ◽  
Dna Strands ◽  
The Impact

Deoxyribonucleic acid (DNA) origami is a method for the bottom-up self-assembly of complex nanostructures for applications, such as biosensing, drug delivery, nanopore technologies, and nanomechanical devices. Effective design of such nanostructures requires a good understanding of their mechanical behavior. While a number of studies have focused on the mechanical properties of DNA origami structures, considering defects arising from molecular self-assembly is largely unexplored. In this paper, we present an automated computational framework to analyze the impact of such defects on the structural integrity of a model DNA origami nanoplate. The proposed computational approach relies on a noniterative conforming to interface-structured adaptive mesh refinement (CISAMR) algorithm, which enables the automated transformation of a binary image of the nanoplate into a high fidelity finite element model. We implement this technique to quantify the impact of defects on the mechanical behavior of the nanoplate by performing multiple simulations taking into account varying numbers and spatial arrangements of missing DNA strands. The analyses are carried out for two types of loading: uniform tensile displacement applied on all the DNA strands and asymmetric tensile displacement applied to strands at diagonal corners of the nanoplate.

scholarly journals AMReX: Block-structured adaptive mesh refinement for multiphysics applications

2021 ◽  
pp. 109434202110228
Author(s):  
Weiqun Zhang ◽  
Andrew Myers ◽  
Kevin Gott ◽  
Ann Almgren ◽  
John Bell
Keyword(s):  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Computational Cost ◽  
Adaptive Mesh ◽  
Uniform Mesh ◽  
Physical Processes ◽  
Structured Adaptive Mesh Refinement ◽  
Core Elements ◽  
Accelerator Design ◽  
Block Structured

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.

3-Dimensional Hybrid Continuum-Atomistic Simulations for Multiscale Hydrodynamics

2003 ◽  
Author(s):  
H. S. Wijesinghe ◽  
R. Hornung ◽  
A. L. Garcia ◽  
N. G. Hadjiconstantinou
Keyword(s):  
Adaptive Mesh Refinement ◽  
Hybrid Methods ◽  
Lawrence Livermore National Laboratory ◽  
National Laboratory ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Scale Model ◽  
Structured Adaptive Mesh Refinement ◽  
Flow Gradients ◽  
The Continuum

We present an adaptive mesh and algorithmic refinement (AMAR) scheme for modeling multi-scale hydrodynamics. The AMAR approach extends standard conservative adaptive mesh refinement (AMR) algorithms by providing a robust flux-based method for coupling an atomistic fluid representation to a continuum model. The atomistic model is applied locally in regions where the continuum description is invalid or inaccurate, such as near strong flow gradients and at fluid interfaces, or when the continuum grid is refined to the molecular scale. The need for such “hybrid” methods arises from the fact that hydrodynamics modeled by continuum representations are often under-resolved or inaccurate while solutions generated using molecular resolution globally are not feasible. In the implementation described herein, Direct Simulation Monte Carlo (DSMC) provides an atomistic description of the flow and the compressible two-fluid Euler equations serve as our continuum-scale model. The AMR methodology provides local grid refinement while the algorithm refinement feature allows the transition to DSMC where needed. The continuum and atomistic representations are coupled by matching fluxes at the continuum-atomistic interfaces and by proper averaging and interpolation of data between scales. Our AMAR application code is implemented in C++ and is built upon the SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) framework developed at Lawrence Livermore National Laboratory. SAMRAI provides the parallel adaptive gridding algorithm and enables the coupling between the continuum and atomistic methods.

scholarly journals Dynamic Load Balancing of Samr Applications on Distributed Systems

2002 ◽  
Vol 10 (4) ◽  
pp. 319-328 ◽  
Author(s):  
Zhiling Lan ◽  
Valerie E. Taylor ◽  
Greg Bryan
Keyword(s):  
Distributed Systems ◽  
Load Balancing ◽  
Dynamic Load ◽  
Adaptive Mesh Refinement ◽  
Heuristic Method ◽  
Adaptive Mesh ◽  
Dynamic Load Balancing ◽  
Dynamic Features ◽  
Structured Adaptive Mesh Refinement ◽  
Two Phases

Dynamic load balancing(DLB) for parallel systems has been studied extensively; however, DLB for distributed systems is relatively new. To efficiently utilize computing resources provided by distributed systems, an underlying DLB scheme must address both heterogeneous and dynamic features of distributed systems. In this paper, we propose a DLB scheme for Structured Adaptive Mesh Refinement(SAMR) applications on distributed systems. While the proposed scheme can take into consideration (1) the heterogeneity of processors and (2) the heterogeneity and dynamic load of the networks, the focus of this paper is on the latter. The load-balancing processes are divided into two phases: global load balancing and local load balancing. We also provide a heuristic method to evaluate the computational gain and redistribution cost for global redistribution. Experiments show that by using our distributed DLB scheme, the execution time can be reduced by 9%- to using parallel DLB scheme which does not consider the heterogeneous and dynamic features of distributed systems.

scholarly journals The impact of AGN feedback on the 1D power spectra from the Ly α forest using the Horizon-AGN suite of simulations

2020 ◽  
Vol 495 (2) ◽  
pp. 1825-1840 ◽  
Author(s):  
Solène Chabanier ◽  
Frédéric Bournaud ◽  
Yohan Dubois ◽  
Nathalie Palanque-Delabrouille ◽  
Christophe Yèche ◽  
...  
Keyword(s):  
Galaxy Evolution ◽  
Adaptive Mesh Refinement ◽  
Power Spectra ◽  
Adaptive Mesh ◽  
Processing Stage ◽  
Galactic Winds ◽  
Upper Limits ◽  
Feeding Parameters ◽  
Future Work ◽  
The Impact

ABSTRACT The Lyman-α forest is a powerful probe for cosmology, but it is also strongly impacted by galaxy evolution and baryonic processes such as active galactic nucleus (AGN) feedback, which can redistribute mass and energy on large scales. We constrain the signatures of AGN feedback on the 1D power spectrum of the Lyman-α forest using a series of eight hydro-cosmological simulations performed with the adaptive mesh refinement code ramses. This series starts from the Horizon-AGN simulation and varies the subgrid parameters for AGN feeding, feedback, and stochasticity. These simulations cover the whole plausible range of feedback and feeding parameters according to the resulting galaxy properties. AGNs globally suppress the Lyman-α power at all scales. On large scales, the energy injection and ionization dominate over the supply of gas mass from AGN-driven galactic winds, thus suppressing power. On small scales, faster cooling of denser gas mitigates the suppression. This effect increases with decreasing redshift. We provide lower and upper limits of this signature at nine redshifts between z = 4.25 and 2.0, making it possible to account for it at post-processing stage in future work given that running simulations without AGN feedback can save considerable amounts of computing resources. Ignoring AGN feedback in cosmological inference analyses leads to strong biases with 2 per cent shift on σ8 and 1 per cent shift on ns, which represents twice the standards deviation of the current constraints on ns.

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