A Finite Element Subproblem Method for Position Change Conductor Systems

Abstract Analyses of magnetic circuits with position changes of both massive and stranded conductors are performed via a finite element subproblem method. A complete problem is split into subproblems associated with each conductor and the magnetic regions. Each complete solution is then expressed as the sum of subproblem solutions supported by different meshes. The subproblem procedure simplifies both meshing and solving processes, with no need of remeshing, and accurately quantifies the effect of the position changes of conductors on both local fields, e.g. skin and proximity effects, and global quantities, e.g. inductances and forces. Applications covering parameterized analyses on conductor positions to moving conductor systems benefit from the developed approach

The Eurasian Modern Pollen Database (EMPD), version 2

The Eurasian (née European) Modern Pollen Database (EMPD) was established in 2013 to provide a public database of high-quality modern pollen surface samples to help support studies of past climate, land cover, and land use using fossil pollen. The EMPD is part of, and complementary to, the European Pollen Database (EPD) which contains data on fossil pollen found in Late Quaternary sedimentary archives throughout the Eurasian region. The EPD is in turn part of the rapidly growing Neotoma database, which is now the primary home for global palaeoecological data. This paper describes version 2 of the EMPD in which the number of samples held in the database has been increased by 60 % from 4826 to 8134. Much of the improvement in data coverage has come from northern Asia, and the database has consequently been renamed the Eurasian Modern Pollen Database to reflect this geographical enlargement. The EMPD can be viewed online using a dedicated map-based viewer at https://empd2.github.io and downloaded in a variety of file formats at https://doi.pangaea.de/10.1594/PANGAEA.909130 (Chevalier et al., 2019)Swiss National Science Foundation | Ref. 200021_16959

The Eurasian Modern Pollen Database (EMPD), version 2

The Eurasian (nee European) Modern Pollen Database (EMPD) was established in 2013 to provide a public database of high-quality modern pollen surface samples to help support studies of past climate, land cover, and land use using fossil pollen. The EMPD is part of, and complementary to, the European Pollen Database (EPD) which contains data on fossil pollen found in Late Quaternary sedimentary archives throughout the Eurasian region. The EPD is in turn part of the rapidly growing Neotoma database, which is now the primary home for global palaeoecological data. This paper describes version 2 of the EMPD in which the number of samples held in the database has been increased by 60% from 4826 to 8134. Much of the improvement in data coverage has come from northern Asia, and the database has consequently been renamed the Eurasian Modern Pollen Database to reflect this geographical enlargement. The EMPD can be viewed online using a dedicated map-based viewer at https://empd2.github.io and downloaded in a variety of file formats at https://doi.pangaea.de/10.1594/PANGAEA.909130 (Chevalier et al., 2019).Peer reviewe

Iterative finite element solution of multiple-scattering problems at high frequencies

peer reviewe

Acceleration of the Generalized Multipole Technique for studying the electromagnetic dispersion of large objects

peer reviewe

Localized iterative generalized multipole technique for large two-dimensional scattering problems

In this work, we propose a novel and efficient solution for the generalized multipole technique (GMT): the localized iterative generalized multipole technique (LIGMT). In LIGMT, an analytic constraint is imposed on the power radiated by the set of multipole sources sharing the same origin, rendering it minimum over a given angular sector. In this way, the power radiated by each set of multipoles is confined to a different section of the scatterer surface. It follows that each set of multipole coefficients can be solved step by step via an iterative process, which circumvents the need to solve the large and full matrix equation. This implies a significant reduction of the computational and storage cost, enhancing the scope of application of the GMT method to larger problems