scholarly journals High-Performance Computational and Information Technologies for Numerical Models and Data Processing

2018 ◽  
Author(s):  
Darkhan Akhmed-Zaki ◽  
Madina Mansurova ◽  
Timur Imankulov ◽  
Danil Lebedev ◽  
Olzhas Turar ◽  
...  
Keyword(s):  
Data Processing ◽  
High Performance ◽  
Information Technologies ◽  
Numerical Models

FORMATION OF METASUBJECT COMPETENCIES IN THE COURSE “INFORMATION TECHNOLOGIES” BY MEANS OF THE BIG DATA PROCESSING LANGUAGE R

2019 ◽  
pp. 12-22
Author(s):  
D. M. Nazarov
Keyword(s):  
Data Processing ◽  
Information Technologies ◽  
Data Sets ◽  
Training Methods ◽  
Economic Knowledge ◽  
R Language ◽  
Currency Exchange ◽  
Business Informatics ◽  
Exchange Data ◽  
Processing Language

The article describes the training methods in the course “Information Technologies” for the future bachelors of the directions “Economics”, “Management”, “Finance”, “Business Informatics”, the development of metasubject competencies of the student while his use of tools for data processing by means of the language R. The metasubject essence of the work is to update traditional economic knowledge and skills through various presentation forms of the same data sets. As part of the laboratory work described in the article, future bachelors learn to use the basic tools of the R language and acquire specific skills and abilities in R-Studio using the example of processing currency exchange data. The description of the methods is presented in the form of the traditional Key-by-Key technology, which is widely used in teaching information technologies.

Design and evaluation of a wedge-type anchor for fibre reinforced polymer tendons

2000 ◽  
Vol 27 (5) ◽  
pp. 985-992 ◽  
Author(s):  
T I Campbell ◽  
N G Shrive ◽  
K A Soudki ◽  
A Al-Mayah ◽  
J P Keatley ◽  
...  
Keyword(s):  
High Performance ◽  
High Performance Concrete ◽  
Numerical Models ◽  
Ultra High Performance Concrete ◽  
Reinforced Polymer ◽  
Anchorage System ◽  
Fibre Reinforced Polymer ◽  
Load Tests ◽  
Tendon Tension ◽  
Post Tensioning

The development of a wedge-type anchorage system for fibre reinforced polymer (FRP) tendons, as part of an overall corrosion-free post-tensioning system, is outlined in this paper. A stainless steel anchor is described, and results from numerical models and load tests to evaluate its behaviour under loads from anchor set, as well as static and repeated tendon tension, are presented. An alternative wedge-type anchorage system made from ultra-high performance concrete is also described. It is shown that, although significant progress has been made in development of the anchorage, further work is required to make it more robust.Key words: FRP tendons, post-tensioning, anchorage, corrosion-free, mathematical models, load tests, concrete.

scholarly journals Modeling of Spray Combustion with a Steady Laminar Flamelet Model in an Aeroengine Combustion Chamber Based on OpenFOAM

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Yinli Xiao ◽  
Zupeng Wang ◽  
Zhengxin Lai ◽  
Wenyan Song
Keyword(s):  
Combustion Chamber ◽  
High Performance ◽  
Numerical Models ◽  
Spray Combustion ◽  
Combustion Chambers ◽  
Flamelet Model ◽  
Steady Laminar ◽  
Good Agreement ◽  
Laminar Flamelet ◽  
Laminar Flamelet Model

The development of high-performance aeroengine combustion chambers strongly depends on the accuracy and reliability of efficient numerical models. In the present work, a reacting solver with a steady laminar flamelet model and spray model has been developed in OpenFOAM and the solver details are presented. The solver is firstly validated by Sandia/ETH-Zurich flames. Furthermore, it is used to simulate nonpremixed kerosene/air spray combustion in an aeroengine combustion chamber with the RANS method. A comparison with available experimental data shows good agreement and validates the capability of the new developed solver in OpenFOAM.

Ensemble-based data assimilation of volcanic aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Andrew Prata ◽  
Federica Pardini
Keyword(s):  
Data Assimilation ◽  
Information Transfer ◽  
High Performance ◽  
Volcanic Ash ◽  
Numerical Models ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Eruption Column ◽  
Operational Environment ◽  
Assimilation System

<p>Modelling atmospheric dispersion and deposition of volcanic ash is becoming increasingly valuable for understanding the potential impacts of explosive volcanic eruptions on infrastructures, air quality and aviation. The generation of high-resolution forecasts depends on the accuracy and reliability of the input data for models. Uncertainties in key parameters such as eruption column height injection, physical properties of particles or meteorological fields, represent a major source of error in forecasting airborne volcanic ash. The availability of nearly real time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context. Data assimilation (DA) is one of the most effective ways to reduce the error associated with the forecasts through the incorporation of available observations into numerical models. Here we present a new implementation of an ensemble-based data assimilation system based on the coupling between the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The implementation is based on the last version release of FALL3D (versions 8.x) tailored to the extreme-scale computing requirements, which has been redesigned and rewritten from scratch in the framework of the EU Center of Excellence for Exascale in Solid Earth (ChEESE). The proposed methodology can be efficiently implemented in an operational environment by exploiting high-performance computing (HPC) resources. The FALL3D+PDAF system can be run in parallel and supports online-coupled DA, which allows an efficient information transfer through parallel communication. Satellite-retrieved data from recent volcanic eruptions were considered as input observations for the assimilation system.</p>

Quantum-Dot Transistor Based Multi-Bit Multiplier Unit for In-Memory Computing

2020 ◽  
Vol 29 (01n04) ◽  
pp. 2040007
Author(s):  
Yang Zhao ◽  
Fengyu Qian ◽  
Faquir Jain ◽  
Lei Wang
Keyword(s):  
Quantum Dot ◽  
Data Processing ◽  
High Performance ◽  
Memory Cell ◽  
Process Variations ◽  
High Energy ◽  
Data Movement ◽  
Neuron Networks ◽  
Fast Processing ◽  
Dot Product

In-memory computing is an emerging technique to fulfill the fast growing demand for high-performance data processing. This technique provides fast processing and high throughput by accessing data stored in the memory array rather than dealing with complicated operation and data movement on hard drive. For data processing, the most important computation is dot product, which is also the core computation for applications such as deep learning neuron networks, machine learning, etc. As multiplication is the key function in dot product, it is critical to improve its performance and achieve faster memory processing. In this paper, we present a design with the ability to perform in-memory multi-bit multiplications. The proposed design is implemented by using quantum-dot transistors, which enable multi-bit computations in the memory cell. Experimental results demonstrate that the proposed design provides reliable in-memory multi-bit multiplications with high density and high energy efficiency. Statistical analysis is performed using Monte Carlo simulations to investigate the process variations and error effects.

High-Performance Computing for Big Data Processing

2018 ◽  
Vol 88 ◽  
pp. 693-695 ◽  
Author(s):  
Yulei Wu ◽  
Yang Xiang ◽  
Jingguo Ge ◽  
Peter Muller
Keyword(s):  
Big Data ◽  
Data Processing ◽  
High Performance Computing ◽  
High Performance ◽  
Big Data Processing ◽  
Performance Computing

MITK Diffusion Imaging

2012 ◽  
Vol 51 (05) ◽  
pp. 441-448 ◽  
Author(s):  
P. F. Neher ◽  
I. Reicht ◽  
T. van Bruggen ◽  
C. Goch ◽  
M. Reisert ◽  
...  
Keyword(s):  
Data Processing ◽  
Open Source ◽  
High Performance ◽  
Diffusion Imaging ◽  
Software Tool ◽  
Brain Anatomy ◽  
Sustainable Evaluation ◽  
Imaging Research ◽  
Interactive Data

SummaryBackground: Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets.Objectives: This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field.Methods: In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITKDI, are demonstrated using in-vivo datasets.Results: MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use in stallable application.Conclusions: The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.

Sign in / Sign up

Export Citation Format

Share Document