30 results found
Funke SW, Farrell PE, Piggott MD, 2014, Tidal turbine array optimisation using the adjoint approach, Renewable Energy, Vol: 63, Pages: 658-673
Oceanic tides have the potential to yield a vast amount of renewable energy. Tidal stream generators are one of the key technologies for extracting and harnessing this potential. In order to extract an economically useful amount of power, hundreds of tidal turbines must typically be deployed in an array. This naturally leads to the question of how these turbines should be configured to extract the maximum possible power: the positioning and the individual tuning of the turbines could significantly influence the extracted power, and hence is of major economic interest. However, manual optimisation is difficult due to legal site constraints, nonlinear interactions of the turbine wakes, and the cubic dependence of the power on the flow speed. The novel contribution of this paper is the formulation of this problem as an optimisation problem constrained by a physical model, which is then solved using an efficient gradient-based optimisation algorithm. In each optimisation iteration, a two-dimensional finite element shallow water model predicts the flow and the performance of the current array configuration. The gradient of the power extracted with respect to the turbine positions and their tuning parameters is then computed in a fraction of the time taken for a flow solution by solving the associated adjoint equations. These equations propagate causality backwards through the computation, from the power extracted back to the turbine positions and the tuning parameters. This yields the gradient at a cost almost independent of the number of turbines, which is crucial for any practical application. The utility of the approach is demonstrated by optimising turbine arrays in four idealised scenarios and a more realistic case with up to 256 turbines in the Inner Sound of the Pentland Firth, Scotland.
Farrell PE, Cotter CJ, Funke SW, 2014, A framework for the automation of generalised stability theory, SIAM Journal on Scientific Computing, Vol: 36, Pages: C25-C48
Buchan AG, Farrell PE, Gorman GJ, et al., 2014, The immersed body supermeshing method for modelling reactor physics problems with complex internal structures, ANNALS OF NUCLEAR ENERGY, Vol: 63, Pages: 399-408, ISSN: 0306-4549
Hiester HR, Piggott MD, Farrell PE, et al., 2014, Assessment of spurious mixing in adaptive mesh simulations of the two-dimensional lock-exchange, Ocean Modelling, Vol: 73, Pages: 30-44, ISSN: 1463-5003
Maddison JR, Cotter CJ, Farrell PE, 2013, Geostrophic balance preserving interpolation in mesh adaptive linearised shallow-water ocean modelling (vol 37, pg 35, 2011), OCEAN MODELLING, Vol: 68, Pages: 106-106, ISSN: 1463-5003
Farrell PE, Ham DA, Funke SW, et al., 2013, Automated derivation of the adjoint of high-level transient finite element programs, SIAM Journal on Scientific Computing, Vol: 35, Pages: C369-C393, ISSN: 1064-8275
Baker CMJ, Buchan AG, Pain CC, et al., 2013, Multimesh anisotropic adaptivity for the Boltzmann transport equation, Annals of Nuclear Energy, Vol: 53, Pages: 411-426
This article presents a new adaptive finite element based method for the solution of the spatial dimensions of the Boltzmann transport equation. The method applies a curvature based error metric to locate the under and over resolved regions of a solution and this, in turn, is used to guide the refinement and coarsening of the spatial mesh. The error metrics and re-meshing procedures are designed such that they enable anisotropic resolution to form in the mesh should it be appropriate to do so. The adaptive mesh enables the appropriate resolution to be applied throughout the whole domain of a problem and so increase the efficiency of the solution procedure. Another new approach is also described that allows independent adaptive meshes to form for each of the energy group fluxes. The use of independent meshes can significantly improve computational efficiency when solving problems where the different group fluxes require high resolution over different regions. The mesh to mesh interpolation is made possible through the use of a ‘supermeshing’ procedure that ensures the conservation of particles when calculating the group to group scattering sources. Finally it is shown how these methods can be incorporated within a solver to resolve both fixed source and eigenvalue problems. A selection of both fixed source and eigenvalue problems are solved in order to demonstrate the capabilities of these methods.
Viré A, Xiang J, Milthaler F, et al., 2012, Modelling of fluid–solid interactions using an adaptive mesh fluid model coupled with a combined finite–discrete element model, Ocean Dynamics
Maddison JR, Farrell PE, 2012, Directional integration on unstructured meshes via supermesh construction, Journal of Computational Physics
Gorman GJ, Southern J, Farrell PE, et al., 2012, Hybrid OpenMP/MPI anisotropic mesh smoothing, International Conference on Computational Science (ICCS), Publisher: ELSEVIER SCIENCE BV, Pages: 1513-1522, ISSN: 1877-0509
Farrell PE, Funke SW, Ham DA, et al., 2012, dolfin-adjoint
The dolfin-adjoint project automatically derives the discrete adjoint and tangent linear models from a forward finite element model written in the Python interface to Dolfin.
Southern J, Gorman GJ, Piggott MD, et al., 2011, Parallel anisotropic mesh adaptivity with dynamic load balancing for cardiac electrophysiology, Journal of Computational Science, Vol: 3, Pages: 8-16
Farrell PE, Micheletti S, Perotto S, 2011, An anisotropic Zienkiewicz-Zhu error estimator for 3D applications, International Journal for Numerical Methods in Engineering, Vol: 85, Pages: 671-692
Maddison JR, Cotter CJ, Farrell PE, 2011, Geostrophic balance preserving interpolation in mesh adaptive linearised shallow-water ocean modelling, Ocean Modelling
Farrell PE, Maddison JR, 2011, Conservative interpolation between volume meshes by local Galerkin projection, Computer Methods in Applied Mechanics and Engineering, Vol: 200, Pages: 89-100
Farrell PE, Piggott MD, Gorman GJ, et al., 2011, Automated continuous verification for numerical simulation, Geoscientific Model Development, Vol: 4, Pages: 435-449
Milthaler F, Xiang J, Pavlidis D, et al., 2011, The immersed body method combined with mesh adaptivity for solid-fluid coupling, 6th International Conference on Coastal Structures
Farrell PE, 2011, The addition of fields on different meshes, Journal of Computational Physics
Southern J, Gorman GJ, Piggott MD, et al., 2010, Simulating cardiac electrophysiology using anisotropic mesh adaptivity, Journal of Computational Science, Vol: 1, Pages: 82-88
The simulation of cardiac electrophysiology requires small time steps and a fine mesh in order to resolve very sharp, but highly localized, wavefronts. The use of very high resolution meshes containing large numbers of nodes results in a high computational cost, both in terms of CPU hours and memory footprint. In this paper an anisotropic mesh adaptivity technique is implemented in the Chaste physiological simulation library in order to reduce the mesh resolution away from the depolarization front. Adapting the mesh results in a reduction in the number of degrees of freedom of the system to be solved by an order of magnitude during propagation and 2–3 orders of magnitude in the subsequent plateau phase. As a result, a computational speedup by a factor of between 5 and 12 has been obtained with no loss of accuracy, both in a slab-like geometry and for a realistic heart mesh with a spatial resolution of 0.125 mm.
Southern J, Gorman GJ, Piggott MD, et al., 2010, Anisotropic mesh adaptivity for cardiac electrophysiology, Pages: 929-938-929-938
Piggott MD, Farrell PE, Wilson CR, et al., 2009, Anisotropic mesh adaptivity for multi-scale ocean modelling, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, Vol: 367, Pages: 4591-4611, ISSN: 1364-503X
Ham DA, Farrell PE, Gorman GJ, et al., 2009, Spud 1.0: generalising and automating the user interfaces of scientific computer models, Geoscientific Model Development, Vol: 2, Pages: 33-42
The interfaces by which users specify the scenarios to be simulated by scientific computer models are frequently primitive, under-documented and ad-hoc text files which make using the model in question difficult and error-prone and significantly increase the development cost of the model. In this paper, we present a model-independent system, Spud, which formalises the specification of model input formats in terms of formal grammars. This is combined with an automated graphical user interface which guides users to create valid model inputs based on the grammar provided, and a generic options reading module, libspud, which minimises the development cost of adding model options. Together, this provides a user friendly, well documented, self validating user interface which is applicable to a wide range of scientific models and which minimises the developer input required to maintain and extend the model interface.
Fang F, Pain CC, Navon IM, et al., 2009, A POD reduced order unstructured mesh ocean modelling method for moderate Reynolds number flows, Ocean Modelling, Vol: 28, Pages: 127-136, ISSN: 1463-5003
Fang F, Pain CC, Navon IM, et al., 2009, A POD reduced-order 4D-Var adaptive mesh ocean modelling approach, Int. J. Numer. Meth. Fluids, Vol: 60, Pages: 709-732
This paper presents a novel approach for inverting a complex ocean model via a proper orthogonal decomposition. The inversion is achieved through the construction of an adjoint model and used to assimilate data in a similar manner to that used in weather forecasting. This is an incredibly important capability for an ocean model, however it is both complex to construct and also can be computationally expensive. The approach proposed here addresses both of these important issues by constructing an efficient and easy to compute adjoint directly from the reduced order model. The approach is demonstrated by inverting for initial conditions in an ocean gyre simulation. The methodology proposed here led directly to the award of a £1M EPSRC grant (EP/I00405X) to develop reduced order and adjoint models for coastal oceanography. Cited 11 times.
Gorman GJ, Pain CC, Piggott MD, et al., 2009, Interleaved parallel tetrahedral mesh optimisation and dynamic load-balancing, Publisher: CINME, Pages: 101-104-101-104
Farrell PE, Maddison JR, 2009, Interpolation between discontinuous volume meshes by local Galerkin projection, Publisher: CINME, Pages: 73-76-73-76
Farrell PE, Piggott MD, Pain CC, et al., 2009, Conservative interpolation between unstructured meshes via supermesh construction, Computer Methods in Applied Mechanics and Engineering, Vol: 198, Pages: 2632-2642
Ham D, Farrell P, Gorman G, et al., 2008, Spud
Spud is a generic system for defining, writing and processing options files for scientific computer models.The interfaces to scientific computer models are frequently primitive, under-documented and ad-hoc text files. This makes using and developing the model in question difficult and error-prone.With Spud, the model developer need only write a rules file (schema) which defines the options which the model takes and the relationship between them. The Spud component Diamond then provides an automatically generated graphical user interface which guides the user and validates the user's input against the schema. Diamond writes out an xml options file for use in Spud.The developer then uses libspud to read the options file into the model. Libspud can read any valid options file without further code modifications and makes the options available at any point in the model code at which they are required.Spud further provides the facility for the schema to be self-documenting and Diamond presents this documentation to the model user in a context-sensitive manner.
Farrell PE, Gorman GJ, Piggott MD, 2008, Automated continuous code verification for the Imperial College Ocean Model, Halifax, Nova Scotia, Canada
Farrell PE, Gorman GJ, Piggott MD, et al., 2007, Some problems with the quadratic fitting algorithm for Hessian recovery in the context of anisotropic mesh optimisation, Publisher: CINME, Pages: 101-104-101-104
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