scholarly journals Numerical Analysis of Elastic Contact between Coated Bodies

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Sergiu Spinu
Keyword(s):  
Frequency Response Function ◽  
State Of The Art ◽  
Computational Tool ◽  
Efficient Tool ◽  
Analytical Functions ◽  
Substrate Protection ◽  
Contact Parameters ◽  
Advanced Computer ◽  
Layered Body ◽  
False Problem

Substrate protection by means of a hard coating is an efficient way of extending the service life of various mechanical, electrical, or biomedical elements. The assessment of stresses induced in a layered body under contact load may advance the understanding of the mechanisms underlying coating performance and improve the design of coated systems. The iterative derivation of contact area and contact tractions requires repeated displacement evaluation; therefore the robustness of a contact solver relies on the efficiency of the algorithm for displacement calculation. The fast Fourier transform coupled with the discrete convolution theorem has been widely used in the contact modelling of homogenous bodies, as an efficient computational tool for the rapid evaluation of convolution products that appear in displacements and stresses calculation. The extension of this technique to layered solids is tantalizing given that the closed-form analytical functions describing the response of layered solids to load are only available in the frequency domain. Whereas the false problem periodization can be treated as in the case of homogenous solids, the aliasing phenomenon and the handling of the frequency response function in origin require adapted techniques. The proposed algorithm for displacement calculation is coupled with a state-of-the-art contact solver based on the conjugate gradient method. The predictions of the newly advanced computer program are validated against existing results derived by a different method. Multiple contact cases are simulated aiming to assess the influence of coating thickness and of its elastic properties on the contact parameters and the strass state. The performed simulations prove that the advanced algorithm is an efficient tool for the contact analysis of coated bodies, which can be used to further understand the mechanical behavior of the coated system and to optimize its design.

A Numerical Study of the Partial Slip Elliptical Contact under Fretting Conditions

2013 ◽  
Vol 371 ◽  
pp. 576-580 ◽  
Author(s):  
Sergiu Spînu ◽  
Dorin Gradinaru
Keyword(s):  
Contact Area ◽  
State Of The Art ◽  
Numerical Study ◽  
Partial Slip ◽  
Elastic Materials ◽  
Elastic Mismatch ◽  
Numerical Tools ◽  
Elliptical Contact ◽  
Contact Parameters ◽  
Circular Contact

The technologically important elliptical contact undergoing fretting is simulated using previously advanced state-of-the-art numerical tools. The influence of contact ellipse eccentricity on various contact parameters is assessed. An analogy with the circular contact is found when tractions equations are written in dimensionless coordinates in case of similarly elastic materials. However, when an elastic mismatch is introduced, the stick area no longer follows proportionally the established contact area.

An Identification Approach of Dynamic Contact Parameters for Toolholder-Spindle Joint Base on Frequency Response Function

2012 ◽  
Vol 538-541 ◽  
pp. 748-753
Author(s):  
Guo Ping An ◽  
Xin Yu Liu ◽  
Yong Sheng Zhao ◽  
Li Gang Cai
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Dynamic Contact ◽  
Work Piece ◽  
Spindle System ◽  
Manufacturing Efficiency ◽  
Identification Approach ◽  
Contact Parameters

The joint of the toolholder-spindle is the most weakness structure in the system of toolholder-spindle. It affects the manufacturing efficiency and the surface quality of work piece. It is important to identify the dynamic contact parameters for evaluating the connectivity of the toolholder-spindle system. The article introduces an approach to identify the dynamic contact parameters of toolholder-spindle joint base on frequency response function (FRF). Using the BT40 toolholder-spindle system, we can get the dynamic contact parameters curve of toolholder-spindle by the previous approach. The translational and rotational contact parameters can be obtained by sensitivity analysis. By comparing the simulation results with those of experimentation, it can prove the validity of identified dynamic contact parameters. The research results can provide a theoretical basis for the optimization of toolholder.

scholarly journals Introduction to the JIPD Special Issue on Infrastructure

2019 ◽  
Vol 3 (2) ◽  
pp. 176
Author(s):  
Giuseppe Eusepi ◽  
Richard E. Wagner ◽  
Qingyang Gu
Keyword(s):  
Political Economy ◽  
State Of The Art ◽  
Public Private Partnerships ◽  
The Political ◽  
Demand Side ◽  
Special Issue ◽  
Public Infrastructure ◽  
Efficient Tool ◽  
The Public ◽  
Infrastructure Policy

Our intention in assembling this special issue of the Journal of Infrastructure, Policy and Development is to offer a state-of-the-art tour through the political economy issues associated with the provision of public infrastructure, and with the use of Public-Private Partnerships (PPPs) in particular. Anyone who is familiar with PPPs cannot fail to be impressed by the diversity of positions and claims regarding their properties. Some scholars maintain that PPPs are an efficient tool to enhance productivity due to their ability to manage demand-side risk. In contrast, other scholars see in PPPs a scheme whereby the public assumes the risk while the private partner takes the profit.

SPICE MODELING OF COMPOUND SEMICONDUCTOR DEVICES

1998 ◽  
Vol 09 (03) ◽  
pp. 725-781 ◽  
Author(s):  
BENJAMIN IÑIGUEZ ◽  
TOR A. FJELDLY ◽  
MICHAEL S. SHUR ◽  
TROND YTTERDAL
Keyword(s):  
Computer Aided Design ◽  
Resonant Tunneling ◽  
State Of The Art ◽  
Semiconductor Devices ◽  
Wide Bandgap ◽  
Design Tool ◽  
Tunneling Devices ◽  
Aided Design ◽  
Resonant Tunneling Devices ◽  
Advanced Computer

We review recent advances in the modeling of novel and advanced semiconductor devices, including state-of-the-art MESFET and HFETs, heterodimensional FETs, resonant tunneling devices, and wide-bandgap semiconductor transistors. We emphasize analytical, physics-based modeling incorporating the important effects present in modern day devices, including deep sub-micrometer devices. Such an approach is needed in order to accurately describe and predict both stationary and dynamic device behavior and to make the models suitable for implementation in advanced computer aided design tool including circuit simulators such as SPICE.

scholarly journals Deep Diffusion MRI Registration (DDMReg): A Deep Learning Method for Diffusion MRI Registration

2021 ◽  
Author(s):  
Fan Zhang ◽  
William M. Wells ◽  
Lauren J. O’Donnell
Keyword(s):  
Deep Learning ◽  
Diffusion Mri ◽  
State Of The Art ◽  
Brain Structures ◽  
Learning Method ◽  
Efficient Tool ◽  
Registration Method ◽  
Anatomical Structures ◽  
Learning Techniques ◽  
Local Fiber

AbstractIn this paper, we present a deep learning method, DDMReg, for fast and accurate registration between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align brain anatomical structures while ensuring that local fiber orientations remain consistent with the underlying white matter fiber tract anatomy. To the best of our knowledge, DDMReg is the first deep-learning-based dMRI registration method. DDMReg is a fully unsupervised method for deformable registration between pairs of dMRI datasets. We propose a novel registration architecture that leverages not only whole brain information but also tract-specific fiber orientation information. We perform comparisons with four state-of-the-art registration methods. We evaluate the registration performance by assessing the ability to align anatomically corresponding brain structures and ensure fiber spatial agreement between different subjects after registration. Experimental results show that DDMReg obtains significantly improved registration performance. In addition, DDMReg leverages deep learning techniques and provides a fast and efficient tool for dMRI registration.

Advances in Forensic Geophysics

2022 ◽  
pp. 15-36
Author(s):  
Elhoucine Essefi
Keyword(s):  
Magnetic Susceptibility ◽  
State Of The Art ◽  
The State ◽  
Efficient Tool ◽  
New Techniques ◽  
Buried Objects ◽  
Localization And Mapping ◽  
Pollution Detection ◽  
Environmental Crimes

Traditionally, forensic geophysics involves the study, search, localization, and mapping of buried objects or elements within soil, buildings, or water using geophysics tools for legal purposes. Recently, with the evolution of environmental crimes, forensic geophysics gave special care to detection, location, and quantification of polluting products. New techniques including the magnetic susceptibility have emerged to investigate this type of crimes. After discussing the state of the art of forensic geophysics, this chapter proposed the magnetic susceptibility as an efficient tool of environmental crimes detection. A case study of pollution detection was proposed from Tunisia. Being a fast and cheap technique, magnetic surveys represent a real promise for environmental forensic geophysics.

scholarly journals Nubeam-dedup: a fast and RAM-efficient tool to de-duplicate sequencing reads without mapping

2020 ◽  
Vol 36 (10) ◽  
pp. 3254-3256 ◽  
Author(s):  
Hang Dai ◽  
Yongtao Guan
Keyword(s):  
Hash Function ◽  
Reference Genome ◽  
State Of The Art ◽  
Source Code ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Efficient Tool ◽  
Cpu Time ◽  
Products Of Matrices

Abstract Summary We present Nubeam-dedup, a fast and RAM-efficient tool to de-duplicate sequencing reads without reference genome. Nubeam-dedup represents nucleotides by matrices, transforms reads into products of matrices, and based on which assigns a unique number to a read. Thus, duplicate reads can be efficiently removed by using a collisionless hash function. Compared with other state-of-the-art reference-free tools, Nubeam-dedup uses 50–70% of CPU time and 10–15% of RAM. Availability and implementation Source code in C++ and manual are available at https://github.com/daihang16/nubeamdedup and https://haplotype.org. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A Unified Channel Charges Expression for Analytic MOSFET Modeling

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Hugues Murray ◽  
Patrick Martin
Keyword(s):  
Drain Current ◽  
Oxide Semiconductor ◽  
Short Channel Effects ◽  
Short Channel ◽  
Efficient Tool ◽  
Equation Resolution ◽  
Weak Inversion ◽  
Analytical Functions ◽  
Channel Effects ◽  
Effect Transistor

Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL). The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in submicronics MOSFET. All calculations are encoded with a simple C program and give instantaneous results that provide an efficient tool for microelectronics users.

scholarly journals An Improved Hierarchical Datastructure for Nearest Neighbor Search

2019 ◽  
Vol 33 ◽  
pp. 10001-10002
Author(s):  
Mengdie Nie ◽  
Zhi-Jie Wang ◽  
Chunjing Gan ◽  
Zhe Quan ◽  
Bin Yao ◽  
...  
Keyword(s):  
High Dimension ◽  
Nearest Neighbor ◽  
State Of The Art ◽  
Nearest Neighbor Search ◽  
Computational Tool ◽  
Neighbor Search ◽  
Art Methods ◽  
Speed Up ◽  
Run Time

Nearest neighbor search is a fundamental computational tool and has wide applications. In past decades, many datastructures have been developed to speed up this operation. In this paper, we propose a novel hierarchical datastructure for nearest neighbor search in moderately high dimension. Our proposed method maintains good run time guarantees, and it outperforms several state-of-the-art methods in practice.

scholarly journals Genome-wide discovery of hidden genes mediating known drug-disease association using KDDANet

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Hua Yu ◽  
Lu Lu ◽  
Ming Chen ◽  
Chen Li ◽  
Jin Zhang
Keyword(s):  
State Of The Art ◽  
Interaction Network ◽  
Drug Repurposing ◽  
Gene Interaction ◽  
Disease Association ◽  
Computational Tool ◽  
Gene Interaction Network ◽  
Disease Pathogenesis ◽  
Link Type ◽  
Genome Wide

AbstractMany of genes mediating Known Drug-Disease Association (KDDA) are escaped from experimental detection. Identifying of these genes (hidden genes) is of great significance for understanding disease pathogenesis and guiding drug repurposing. Here, we presented a novel computational tool, called KDDANet, for systematic and accurate uncovering the hidden genes mediating KDDA from the perspective of genome-wide functional gene interaction network. KDDANet demonstrated the competitive performances in both sensitivity and specificity of identifying genes in mediating KDDA in comparison to the existing state-of-the-art methods. Case studies on Alzheimer’s disease (AD) and obesity uncovered the mechanistic relevance of KDDANet predictions. Furthermore, when applied with multiple types of cancer-omics datasets, KDDANet not only recapitulated known genes mediating KDDAs related to cancer, but also revealed novel candidates that offer new biological insights. Importantly, KDDANet can be used to discover the shared genes mediating multiple KDDAs. KDDANet can be accessed at http://www.kddanet.cn and the code can be freely downloaded at https://github.com/huayu1111/KDDANet.

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