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  • 1.
    Eriksson, Anders
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Mekanik, Strukturmekanik.
    Marti, K.
    Müller-Hannemann, M.
    Topping, BHV.
    Mota-Soares, CA.
    Engineering computational technology2007Ingår i: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 38, nr 11-12, s. 723-725Artikel i tidskrift (Refereegranskat)
  • 2. Innocenti, M. E.
    et al.
    Johnson, A.
    Markidis, Stefano
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Amaya, J.
    Deca, J.
    Olshevsky, V.
    Lapenta, G.
    Progress towards physics-based space weather forecasting with exascale computing2017Ingår i: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 111, s. 3-17Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Space weather is a rapidly growing field of science which studies processes occurring in the area of space between the Sun and the Earth. The development of space weather forecasting capabilities is a task of great societal relevance: space weather effects may damage a number of technological assets, among which power and communication lines, transformers, pipelines and the telecommunication infrastructure. Exascale computing is a fundamental ingredient for space weather forecasting tools based on physical, rather than statistical, models. We describe here our recent progresses towards a physics-based space weather forecasting tool with exascale computing. We select the semi-implicit, Particle In Cell, Implicit Moment Method implemented in the parallel, object-oriented, C++ iPic3D code as a promising starting point. We analyze the structure and the performances of the current version of the iPic3D code. We describe three algorithmic developments, the fully implicit method, the Multi-Level Multi-Domain method, and the fluid-kinetic method, which can help addressing the multiple spatial and temporal scales present in space weather simulations. We then examine, in a co-design approach, which requirements - vectorization, extreme parallelism and reduced communication - an application has to satisfy to fully exploit architectures such as GPUs and Xeon Phi's. We address how to modify the iPic3D code to better satisfy these requirements. We then describe how to port the iPic3D code to the DEEP architecture currently under construction. The FP7 project DEEP (www.deep-project.eu) aims at building an exascale-ready machine composed of a cluster of Xeon nodes and of a collection of Xeon Phi coprocessors, used as boosters. The aim of the DEEP project is to enable exascale performance for codes, such as iPic3D, composed of parts which exhibit different potential for extreme scalability. Finally, we provide examples of simulations of space weather processes done with the current version of the iPic3D code. © 2016 Elsevier Ltd.

  • 3.
    Jin, Junchen
    et al.
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Transportvetenskap, Transportplanering, ekonomi och teknik.
    Ma, Xiaoliang
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Transportvetenskap, Transportplanering, ekonomi och teknik.
    Kosonen, Iisakki
    A stochastic optimization framework for road traffic controls based on evolutionary algorithms and traffic simulation2017Ingår i: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 114, s. 348-360Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Traffic flow is considered as a stochastic process in road traffic modeling. Computer simulation is a widely used tool to represent traffic system in engineering applications. The increased traffic congestion in urban areas and their impacts require more efficient controls and management. While the effectiveness of control schemes highly depends on accurate traffic model and appropriate control settings, optimization techniques play a central role for determining the control parameters in traffic planning and management applications. However, there is still a lack of research effort on the scientific computing framework for optimizing traffic control and operations and facilitating real planning and management applications. To this end, the present study proposes a model-based optimization framework to integrate essential components for solving road traffic control problems in general. In particular, the framework is based on traffic simulation models, while the solution needs extensive computation during the engineering optimization process. In this work, an advanced genetic algorithm, extended by an external archive for storing globally elite genes, governs the computing framework, and in application it is further enhanced by a sampling approach for initial population and utilizations of adaptive crossover and mutation probabilities. The final algorithm shows superior performance than the ordinary genetic algorithm because of the reduced number of fitness function evaluations in engineering applications. To evaluate the optimization algorithm and validate the whole software framework, this paper illustrates a detailed application for optimization of traffic light controls. The study optimizes a simple road network of two intersections in Stockholm to demonstrate the model-based optimization processes as well as to evaluate the presented algorithm and software performance.

  • 4.
    Tisell, Claes
    et al.
    KTH, Tidigare Institutioner, Maskinkonstruktion.
    Orsborn, K
    A system for multibody analysis based on object-relational database technology2000Ingår i: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 31, s. 971-984Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An efficient support for computational technology and information management will be critical in future Engineering Information Systems (EIS). This paper shows how it is possible to provide efficient data management capabilities to the discipline of Multibody System (MBS) analysis. The MECHAMOS prototype of a MBS analysis tool has been developed that is based on an object-relational database management system, AMOS, which has been extended with additional mathematical functionality by the use of Matlab and MapleV as computational engines. The MBS model is represented as a database model in AMOS and the analysis is based on symbolic formulation of Kane's equations of motion. With this configuration, data is made fully accessible via the AMOSQL query language of AMOS. Furthermore, by providing the MBS application with general database technology, the data management will be more efficient in terms of handling large amounts of data and the development and maintenance of MBS analysis systems. Since MBS models are represented in a “neutral format”, the reusability of these models increases and they will be more persistent to changes in the EIS environment.

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