Scalable algorithm for solving 3D contact problems with friction

In this paper, we study the steady-state rolling contact of a linear viscoelastic layer of finite thickness and a rigid indenter made of a periodic array of equally spaced rigid cylinders. The viscoelastic contact model is derived by means of Green’s function approach, which allows solving the contact problem with the sliding velocity as a control parameter. The contact problem is solved by means of an accurate numerical procedure developed for general two-dimensional contact geometries. The effect of geometrical quantities (layer thickness, cylinders radii, and cylinders spacing), material properties (viscoelastic moduli, relaxation time) and operative conditions (load, velocity) are all investigated. Physical quantities typical of contact problems (contact areas, deformed profiles, etc.) are calculated and discussed. Special emphasis is dedicated to the viscoelastic friction force coefficient and to the energy dissipated per unit time. The discussion is focused on the role played by the deformation localized at the contact spots and the one in the bulk of the thin layer, due to layer bending. The model is proposed as an accurate solution for engineering applications such as belt conveyors, in which the energy dissipated on the rolling contact of idle rollers can, in some cases, be by far the most important contribution to their energy consumption.

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Two contact problems in anisotropic thermoelasticity

Journal of Elasticity ◽

10.1007/bf00041782 ◽

1976 ◽

Vol 6 (2) ◽

pp. 137-147 ◽

Cited By ~ 11

Author(s):

D. L. Clements ◽

G. D. Toy

Keyword(s):

Contact Problems

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Topology optimization of elastic contact problems using B-spline parameterization

Structural and Multidisciplinary Optimization ◽

10.1007/s00158-020-02837-4 ◽

2021 ◽

Vol 63 (4) ◽

pp. 1669-1686

Author(s):

Jiajia Li ◽

Weihong Zhang ◽

Cao Niu ◽

Tong Gao

Keyword(s):

Topology Optimization ◽

Contact Problems ◽

Elastic Contact ◽

B Spline

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FastSK: fast sequence analysis with gapped string kernels

Bioinformatics ◽

10.1093/bioinformatics/btaa817 ◽

2020 ◽

Vol 36 (Supplement_2) ◽

pp. i857-i865

Author(s):

Derrick Blakely ◽

Eamon Collins ◽

Ritambhara Singh ◽

Andrew Norton ◽

Jack Lanchantin ◽

...

Keyword(s):

Sequence Analysis ◽

Dna Sequences ◽

English Language ◽

Computation Time ◽

Entity Recognition ◽

Supplementary Information ◽

Support Vector ◽

Homology Detection ◽

Scalable Algorithm ◽

String Kernels

Abstract Motivation Gapped k-mer kernels with support vector machines (gkm-SVMs) have achieved strong predictive performance on regulatory DNA sequences on modestly sized training sets. However, existing gkm-SVM algorithms suffer from slow kernel computation time, as they depend exponentially on the sub-sequence feature length, number of mismatch positions, and the task’s alphabet size. Results In this work, we introduce a fast and scalable algorithm for calculating gapped k-mer string kernels. Our method, named FastSK, uses a simplified kernel formulation that decomposes the kernel calculation into a set of independent counting operations over the possible mismatch positions. This simplified decomposition allows us to devise a fast Monte Carlo approximation that rapidly converges. FastSK can scale to much greater feature lengths, allows us to consider more mismatches, and is performant on a variety of sequence analysis tasks. On multiple DNA transcription factor binding site prediction datasets, FastSK consistently matches or outperforms the state-of-the-art gkmSVM-2.0 algorithms in area under the ROC curve, while achieving average speedups in kernel computation of ∼100× and speedups of ∼800× for large feature lengths. We further show that FastSK outperforms character-level recurrent and convolutional neural networks while achieving low variance. We then extend FastSK to 7 English-language medical named entity recognition datasets and 10 protein remote homology detection datasets. FastSK consistently matches or outperforms these baselines. Availability and implementation Our algorithm is available as a Python package and as C++ source code at https://github.com/QData/FastSK Supplementary information Supplementary data are available at Bioinformatics online.

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A Unified Abaqus Implementation of the Phase Field Fracture Method Using Only a User Material Subroutine

Materials ◽

10.3390/ma14081913 ◽

2021 ◽

Vol 14 (8) ◽

pp. 1913

Author(s):

Yousef Navidtehrani ◽

Covadonga Betegón ◽

Emilio Martínez-Pañeda

Keyword(s):

Phase Field ◽

Crack Nucleation ◽

Crack Density ◽

Contact Problems ◽

Element Mesh ◽

Robust Implementation ◽

Current Implementation ◽

User Material Subroutine ◽

Complex Crack ◽

Monolithic Solution

We present a simple and robust implementation of the phase field fracture method in Abaqus. Unlike previous works, only a user material (UMAT) subroutine is used. This is achieved by exploiting the analogy between the phase field balance equation and heat transfer, which avoids the need for a user element mesh and enables taking advantage of Abaqus’ in-built features. A unified theoretical framework and its implementation are presented, suitable for any arbitrary choice of crack density function and fracture driving force. Specifically, the framework is exemplified with the so-called AT1, AT2 and phase field-cohesive zone models (PF-CZM). Both staggered and monolithic solution schemes are handled. We demonstrate the potential and robustness of this new implementation by addressing several paradigmatic 2D and 3D boundary value problems. The numerical examples show how the current implementation can be used to reproduce numerical and experimental results from the literature, and efficiently capture advanced features such as complex crack trajectories, crack nucleation from arbitrary sites and contact problems. The code developed is made freely available.

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