2063 research outputs found
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A Novel Parametric benchmark generator for dynamic multimodal optimization
Get PDFIn most existing studies on dynamic multimodal optimization (DMMO), numerical simulations have been performed using the Moving Peaks Benchmark (MPB), which is a two-decade-old test suite that cannot simulate some critical aspects of DMMO problems. This study proposes the Deterministic Distortion and Rotation Benchmark (DDRB), a method to generate deterministic DMMO test problems that can simulate more diverse types of challenges when compared to existing benchmark generators for DMMO. DDRB allows for controlling the intensity of each type of challenge independently, enabling the user to pinpoint the pros and cons of a DMMO method. DDRB first develops an existing approach for generation of static multimodal functions in which the difficulty of global optimization can be controlled. Then, it proposes a scaling function to dynamically change the relative distribution, shapes, and sizes of the basins. A deterministic technique to control the regularity of the pattern in the change is also proposed. Using these components, a parametric test suite consisting of ten test problems is developed for DMMO. Mean Robust Peak Ratio for measuring the performance of DMMO methods is formulated to overcome the sensitivity of the conventional peak ratio indicator to the predefined threshold and niche radius. Numerical results of a successful multimodal optimization method, when augmented with a simple strategy to utilize previous information, are provided on the proposed test problems in different scenarios with the aim of serving as a reference for future studies
Pointwise Convergence of the Schr\"odinger Flow
Get PDFIn this paper we address the question of the pointwise almost everywhere limit of nonlinear Schr\"odinger flows to the initial data, in both the continuous and the periodic settings. Then we show how, in some cases, certain smoothing effects for the non-homogeneous part of the solution can be used to upgrade to a
uniform convergence to zero of this part, and we discuss the sharpness of the results obtained. We also use randomization techniques to prove that with much less regularity of the initial data, both in continuous and the periodic settings, almost surely one obtains uniform convergence of the nonlinear solution to the initial data, hence showing how more {\it generic} results can be obtained
Cones with convoluted geometry that always scatter or radiate
Get PDFWe investigate fixed energy scattering from conical potentials having an irregular cross-section. The incident wave can be an arbitrary non-trivial Herglotz wave. We show that a large number of such local conical scatterers scatter all incident waves, meaning that the far-field will always be non-zero. In essence there are no incident waves for which these potentials would seem transparent at any given energy. We show more specifically that there is a large collection of star-shaped cones whose local geometries always produce a scattered wave. In fact, except for a countable set, all cones from a family of deformations between a circular and a star-shaped cone will always scatter any non-trivial incident Herglotz wave. Our methods are based on the use of spherical harmonics and a deformation argument. We also investigate the related problem for sources. In particular if the support of the source is locally a thin cone, with an arbitrary cross-section, then it will produce a non-zero far-field
Fire-spotting modelling in operational wildfire simulators based on cellular automata: a comparison study.
No full textOne crucial mechanism in the spread of wildfires is the so-called fire-spotting:
a random phenomenon which occurs when embers are transported over large
distances. Fire-spotting speeds up the Rate of Spread and starts new igni-
tions which constitute a menace for fire fighting operations. Unfortunately,
operational fire-spread simulators may not account for spotting e↵ects, thus
overlooking the harmful consequences associated with this phenomenon. In
this work, several fire spotting methods are integrated in the operational
wildfire simulator PROPAGATOR based on Cellular Automata (CA). Ran-
domFront, a physics-based parametrization of fire-spotting, is tested for the
first time in the context of CA simulators. RandomFront is compared with
other two parametrizations already adopted in CA based simulators, the
ones of Alexandridis et al. and Perryman et al. A wildfire occurred in the
summer of 2021 in the municipality of Campomarino (Molise, Italy), and
where spotting e↵ects were clearly reported, has been used as a study case.
RandomFront parametrization produced a more complex burnt probability
pattern than the other models. Moreover, it predicted higher burning proba-
bility in the area of the domain a↵ected by spotting e↵ects in the real wildfire
event
Extensions of the John-Nirenberg theorem and applications
Get PDFThe John–Nirenberg theorem states that functions of bounded mean oscillation are
exponentially integrable. In this article we give two extensions of this theorem. The first one
relates the dyadic maximal function to the sharp maximal function of Fefferman–Stein, while
the second one concerns local weighted mean oscillations, generalizing a result of Muckenhoupt
and Wheeden. Applications to the context of generalized Poincaré type inequalities and to the
context of the class of weights are given. Extensions to the case of polynomial BMO type
spaces are also given.Basque Government: IT1247-19 and "Ayuda para la formación de personal investigador no doctor
Stochastic resetting by a random amplitude
Get PDFStochastic resetting, a diffusive process whose amplitude is reset to the origin at random times, is a vividly studied strategy to optimize encounter dynamics, e.g., in chemical reactions. Here we generalize the resetting step by introducing a random resetting amplitude such that the diffusing particle may be only partially reset towards the trajectory origin or even overshoot the origin in a resetting step. We introduce different scenarios for the random-amplitude stochastic resetting process and discuss the resulting dynamics. Direct applications are geophysical layering (stratigraphy) and population dynamics or financial markets, as well as generic search processes.Predoc Severo Ochoa 2018 grant PRE2018-084427;
DFG Grant No. ME 1535/12-
Double layered solutions to the extended Fisher–Kolmogorov P.D.E.
Get PDFWe construct double layered solutions to the extended Fisher–Kolmogorov P.D.E., under the assumption that the set of minimal heteroclinics of the corresponding O.D.E. satisfies a separation condition. The aim of our work is to provide for the extended Fisher–Kolmogorov equation, the first examples of two-dimensional minimal solutions, since these solutions play a crucial role in phase transition models, and are closely related to the De Giorgi conjecture.BERC 2018-2021 program, BCAM Severo Ochoa accreditation SEV-2017-0718, MTM2017-82184- R, National Science Centre,
Poland (Grant No. 2017/26/E/ST1/00817)
Altered effective connectivity in sensorimotor cortices: a novel signature of severity and clinical course in depression
Get PDFFunctional neuroimaging research on depression has traditionally targeted neural networks associated with the psychological aspects of depression. In this study, instead, we focus on alterations of sensorimotor function in depression. We used resting-state functional MRI data and Dynamic Causal Modeling (DCM) to assess the hypothesis that depression is associated with aberrant effective connectivity within and between key regions in the sensorimotor hierarchy. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes we first established the architecture of effective connectivity in sensorimotor cortices. We found that in (interoceptive and exteroceptive) sensory cortices across participants, the backward connections are predominantly inhibitory whereas the forward connections are mainly excitatory in nature. In motor cortices these parities were reversed. With increasing depression severity, these patterns are depreciated in exteroceptive and motor cortices and augmented in the interoceptive cortex: an observation that speaks to depressive symptomatology. We established the robustness of these results in a leave-one-out cross validation analysis and by reproducing the main results in a follow-up dataset. Interestingly, with (non-pharmacological) treatment, depression associated changes in backward and forward effective connectivity partially reverted to group mean levels. Overall, altered effective connectivity in sensorimotor cortices emerges as a promising and quantifiable candidate marker of depression severity and treatment response
Frequency domain modelling of a coupled system of floating structure and mooring Lines: An application to a wave energy converter
Get PDFFloating structures for single offshore renewable energy devices, i.e. wave energy converters, tend to be significantly smaller than those of the traditional offshore industry and the interaction between floater motions and mooring line dynamics become important. Installation sites are generally subject to powerful waves and currents experiencing more dynamically excited motions. Water depths are also lower, ranging generally from 50 m to 200 m and mooring systems are to be designed to assure the station keeping of them while not interfering with the power conversion. However, floater motions may induce large dynamic tensions on mooring lines, making quasistatic analyses inaccurate in terms of design tension while non-linear time domain simulations too time consuming. This paper introduces a numerical model of lumped mass for mooring lines and rigid body motions for the floating structure coupled by means of kinematic relations, and its subsequent linearization, which is solved in the frequency domain. The linearized model is applied to a two-body floating spar type oscillating water column, subject to the 36 most occurrent sea states at the BIMEP site. Its accuracy is verified through a comparison with the equivalent time domain simulation and a review of the results and its limitations are also pointed out
Thermal conductivity of amorphous polymers and its dependence on molecular weight
Get PDFThermal conductivity is an important transport property governing the performance of polymers in non-isothermal conditions. Nevertheless, its dependence on molecular weight M has not been the subject of as much attention as other properties of polymeric materials. We determine the thermal conductivity of polystyrene and polyisobutylene for a wide range of molecular weight by measuring the density, heat capacity and thermal diffusivity. Using coarse-graining and reverse mapping methods, we were able to produce molecular melts to study the thermal conductivity of polystyrene using molecular dynamics simulations over a similar range of molecular weight. We find satisfactory agreement between the experimental and simulation results. However, all of our results show that thermal conductivity depends only slightly on molecular weight up the entanglement limit and it is independent thereafter. Our results put into question the few previous experimental studies on this topic by showing that the previously accepted proportionality to does not hold. Our findings could have significant implications for the understanding of complex phenomena such as anisotropic thermal conductivity in polymers subjected to flow.Marie Skłodowska-Curie IF MTCIATTP 750985