scholarly journals MuMax: A new high-performance micromagnetic simulation tool

2011 ◽  
Vol 323 (21) ◽  
pp. 2585-2591 ◽  
Author(s):  
A. Vansteenkiste ◽  
B. Van de Wiele
2018 ◽  
Vol 201 ◽  
pp. 02004
Author(s):  
Shao-Ming Yang ◽  
Gene Sheu ◽  
Tzu Chieh Lee ◽  
Ting Yao Chien ◽  
Chieh Chih Wu ◽  
...  

High performance power device is necessary for BCD power device. In this paper, we used 3D Synopsis TCAD simulation tool Sentaurus to develop 120V device and successfully simulated. We implemented in a conventional 0.35um BCDMOS process to present of a novel high side 120V LDMOS have reduced surface field (RESURF) and Liner p-top structure with side isolation technology. The device has been research to achieve a benchmark specific on-resistance of 189 mΩ-mm2 while maintaining horizontal breakdown voltage and vertical isolation voltage both to target breakdown voltage of 120V. In ESOA, we also proposed a better performance of both device without kirk effect.


2021 ◽  
Vol 134 (19) ◽  
Author(s):  
David Miguel Susano Pinto ◽  
Mick A. Phillips ◽  
Nicholas Hall ◽  
Julio Mateos-Langerak ◽  
Danail Stoychev ◽  
...  

ABSTRACT Custom-built microscopes often require control of multiple hardware devices and precise hardware coordination. It is also desirable to have a solution that is scalable to complex systems and that is translatable between components from different manufacturers. Here we report Python-Microscope, a free and open-source Python library for high-performance control of arbitrarily complex and scalable custom microscope systems. Python-Microscope offers simple to use Python-based tools, abstracting differences between physical devices by providing a defined interface for different device types. Concrete implementations are provided for a range of specific hardware, and a framework exists for further expansion. Python-Microscope supports the distribution of devices over multiple computers while maintaining synchronisation via highly precise hardware triggers. We discuss the architectural features of Python-Microscope that overcome the performance problems often raised against Python and demonstrate the different use cases that drove its design: integration with user-facing projects, namely the Microscope-Cockpit project; control of complex microscopes at high speed while using the Python programming language; and use as a microscope simulation tool for software development.


2021 ◽  
Author(s):  
Herve Gross ◽  
Antoine Mazuyer

Abstract Evaluating large basin-scale formations for CO2 sequestration is one of the most important challenges for our industry. The technical complexity and the quantification of risks associated with these operations call for new reservoir engineering and reservoir simulation tools. The impact of multiple coupled physical phenomena, the century timescale, and basin-sized models in these operations force us to completely take apart and revisit the numerical backbone of existing simulation tools. We need a reservoir simulation tool designed for scalability and portability on high-performance computing architectures. To achieve this, we are proposing a new, open-source, multiphysics, and multilevel physics simulation tool called GEOSX. This tool is jointly created by Lawrence Livermore National Laboratory, Stanford University, and Total. It is designed for scalability on multiple CPUs and multiple GPUs and offers a suite of physical solvers that can be extended easily while achieving a balance between performance and portability. GEOSX is initially targeting multiphysics simulations with coupled geomechanics, flow, and transport mechanics but with its open architecture, it allows access to high-performance physical solvers as building blocks of other multiphysics problems and provides users with a suite of tools for numerical optimization across platforms. In this paper, we introduce GEOSX, expose its fundamental architecture principles, and show an example of geological sequestration of CO2 modeling on real data. We demonstrate our ability to simulate fluid and rock poromechanical interactions over long periods and basin-scale dimensions. GEOSX demonstrates its usefulness for such complex and large problems and proves to be scalable and portable across multiple high-performance systems.


2021 ◽  
Author(s):  
David Miguel Susano Pinto ◽  
Mick A Phillips ◽  
Nicholas Hall ◽  
Julio Mateos–Langerak ◽  
Danail Stoychev ◽  
...  

AbstractBespoke microscopes often require control of multiple hardware devices and precise hardware coordination. It is also desirable to have a control solution that is scalable to more complex systems and translatable between components from different manufacturers. Here we report Python-Microscope, a free and open source Python library for high performance control of arbitrarily complex and scalable bespoke microscopes. Python-Microscope offers an elegant pythonic software platform to control microscopes, abstracting differences between physical devices by providing a defined interface for different device types. These include cameras, filter wheels, light sources, deformable mirrors, and stages. Concrete implementations are provided for a range of specific hardware and a framework is in place for further expansion. Python-Microscope supports the distribution of devices over multiple computers while maintaining synchronisation via highly precise hardware triggers. We discuss the architecture choices of Python-Microscope that overcome the performance problems often raised against Python and demonstrate the different use cases that drove its design: its integration in user facing projects, namely in the Microscope-Cockpit project; in controlling complex microscopes at high speed while using the Python programming language; and as a microscope simulation tool for software development.


2012 ◽  
Vol 233 ◽  
pp. 17-23 ◽  
Author(s):  
Yun Jiang Cheng ◽  
Shu Han Wang ◽  
Xiang Yang Xu ◽  
Wen Yong Li

The jet pipe electro-hydraulic servo valve is a typical two-stage flow control servo valve, its static and dynamic characteristics are analyzed in this paper. The interaction of the mechatronic and hydraulic system is considered by multidomain simulation tool, the all key parameters are tunable and this provides the optimal possibility to develop a high-performance jet pipe electro-hydraulic servo valve.


2021 ◽  
Author(s):  
Virgile Baudrot ◽  
Sandrine Charles

AbstractPredictive environmental risk scenarios are today of major interest for environmental risk assessment as they provide plausible and consistent descriptions of possible effects of chemical in natura. In particular, they can be used for predictions of the future as consistent descriptions of pathways towards desired targets to protect. One single scenario would therefore be meaningless, as it could not capture all the variability and uncertainty involved in natural phenomenon combined with socio-economical events. A set of environmental risk scenarios is then a key asset to address sustainable and collaborative decision making associated with appropriate actions.Toxicokinetics-Toxicodynamics (TKTD) models are increasingly used for the assessment and the prediction of environmental risk assessment due to chemical products. This mechanistic modelling approach offers many advantages as the possibility to perform simulations under non-observed realistic situations with time-variable exposure profiles embedded in environmental risk scenarios. TKTD simulations can also be linked with other types of models (e.g., Individual Based Model) within a pipeline of computing inference as for example Bayesian inference or Machine Learning. To handle such challenges within the particular framework of TKTD models for survival, we present an innovative simulation tool written in the new programming language Julia, called TKTDsimulations.jl. Given that TKTD models for survival usually require high performance computing due to the numerical integration of differential equations, our tool strongly benefits from Julia’s facilities, in particular a code that is fast to compile and easy to maintain. In addition, to ease the link with the already developed R-package morse dedicated to the statistical handling of ecotoxicity data, we also developed a new R-package, called tktdjl2r, interfacing morse with our new simulation tool TKTDsimulations.jl that considerably faster predictions with the corresponding ready-to-use morse functions.


2017 ◽  
Vol 68 ◽  
pp. 59-73 ◽  
Author(s):  
Francisco Borges ◽  
Albert Gutierrez-Milla ◽  
Emilio Luque ◽  
Remo Suppi

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