On the changing seasonal cycles and trends of ozone at Mace Head, Ireland

A seasonal-trend decomposition technique based on a locally-weighted regression smoothing (Loess) approach has been used to decompose monthly ozone concentrations at Mace Head (Ireland) into trend, seasonal and irregular components. The trend component shows a steady increase from 1990–2004, which is confirmed by statistical testing which shows that ozone concentrations at Mace Head have increased at the p=0.06 level by 0.18±0.04 ppb yr^−1. By considering different air mass origins using a trajectory analysis, it has been possible to separate air masses into 'polluted' and 'unpolluted' origins. The seasonal-trend decomposition technique confirms the different seasonal cycles of these air mass origins with unpolluted air mass maxima in April and polluted air mass maxima in July/August. A detailed consideration of the seasonal component reveals different behaviour depending on the air mass origin. For baseline unpolluted air arriving at Mace Head there has been a gradual increase in the seasonal amplitude, driven by a declining summertime component. The amplitude of the seasonal component of baseline air is controlled by a maximum in April and a minimum in July. For polluted air mass trajectories, there was a substantial reduction in the amplitude of the seasonal component from 1990–1997. However, post-1997 results indicate that the seasonal amplitude in polluted air masses arriving at Mace Head is increasing. Furthermore, there has been a shift in the months controlling the size of the seasonal amplitude in polluted air from a maximum in May and minimum in January in 1990 to a maximum in April and a minimum in July by 2001. This finding suggests that there has been a steadily decreasing influence of polluted air masses arriving from Europe. These air masses have therefore increasingly taken on the attributes of baseline air

Modelling trends in OH radical concentrations using generalized additive models

During the TORCH campaign a zero dimensional box model based on the Master Chemical Mechanism was used to model concentrations of OH radicals. The model provided a close overall fit to measured concentrations but with some significant deviations. In this research, an approach was established for applying Generalized Additive Models (GAM) to atmospheric concentration data. Two GAM models were fitted to OH radical concentrations using TORCH data, the first using measured OH data and the second using MCM model results. GAM models with five smooth functions provided a close fit to the data with 78% of the deviance explained for measured OH and 83% for modelled OH. The GAM model for measured OH produced substantially better predictions of OH concentrations than the original MCM model results. The diurnal profile of OH concentration was reproduced and the predicted mean diurnal OH concentration was only 0.2% less than the measured concentration compared to 16.3% over-estimation by the MCM model. Photolysis reactions were identified as most important in explaining concentrations of OH. The GAM models combined both primary and secondary pollutants and also anthropogenic and biogenic species to explain changes in OH concentrations. Differences identified in the dependencies of modelled and measured OH concentrations, particularly for aromatic and biogenic species, may help to understand why the MCM model predictions sometimes disagree with measurements of atmospheric species

Comment on Photothermal radiometry parametric identifiability theory for reliable and unique nondestructive coating thickness and thermophysical measurements, J. Appl. Phys. 121(9), 095101 (2017)

A recent paper [X. Guo, A. Mandelis, J. Tolev and K. Tang, J. Appl. Phys., 121, 095101 (2017)] intends to demonstrate that from the photothermal radiometry signal obtained on a coated opaque sample in 1D transfer, one should be able to identify separately the following three parameters of the coating: thermal diffusivity, thermal conductivity and thickness. In this comment, it is shown that the three parameters are correlated in the considered experimental arrangement, the identifiability criterion is in error and the thickness inferred therefrom is not trustable.Comment: 3 page

Fourier mode dynamics for the nonlinear Schroedinger equation in one-dimensional bounded domains

We analyze the 1D focusing nonlinear Schr\"{o}dinger equation in a finite interval with homogeneous Dirichlet or Neumann boundary conditions. There are two main dynamics, the collapse which is very fast and a slow cascade of Fourier modes. For the cubic nonlinearity the calculations show no long term energy exchange between Fourier modes as opposed to higher nonlinearities. This slow dynamics is explained by fairly simple amplitude equations for the resonant Fourier modes. Their solutions are well behaved so filtering high frequencies prevents collapse. Finally these equations elucidate the unique role of the zero mode for the Neumann boundary conditions

Quantum optomechanics of a multimode system coupled via photothermal and radiation pressure force

We provide a full quantum description of the optomechanical system formed by a Fabry-Perot cavity with a movable micro-mechanical mirror whose center-of-mass and internal elastic modes are coupled to the driven cavity mode by both radiation pressure and photothermal force. Adopting a quantum Langevin description, we investigate simultaneous cooling of the micromirror elastic and center-of-mass modes, and also the entanglement properties of the optomechanical multipartite system in its steady state.Comment: 11 pages, 7 figure

Source apportionment advances using polar plots of bivariate correlation and regression statistics

This paper outlines the development of enhanced bivariate polar plots that allow the concentrations of two pollutants to be compared using pair-wise statistics for exploring the sources of atmospheric pollutants. The new method combines bivariate polar plots, which provide source characteristic information, with pair-wise statistics that provide information on how two pollutants are related to one another. The pair-wise statistics implemented include weighted Pearson correlation and slope from two linear regression methods. The development uses a Gaussian kernel to locally weight the statistical calculations on a wind speed-direction surface together with variable-scaling. Example applications of the enhanced polar plots are presented by using routine air quality data for two monitoring sites in London, United Kingdom for a single year (2013). The London examples demonstrate that the combination of bivariate polar plots, correlation, and regression techniques can offer considerable insight into air pollution source characteristics, which would be missed if only scatter plots and mean polar plots were used for analysis. Specifically, using correlation and slopes as pair-wise statistics, long-range transport processes were isolated and black carbon (BC) contributions to PM2.5 for a kerbside monitoring location were quantified. Wider applications and future advancements are also discussed

Rendering Non-Euclidean Space in Real-Time Using Spherical and Hyperbolic Trigonometry

We introduce a method of calculating and rendering shapes in a non-Euclidean 2D space in real-time using hyperbolic and spherical trigonometry. We record the objects’ parameters in a polar coordinate system and use azimuthal equidistant projection to render the space onto the screen. We discuss the complexity of this method, renderings produced, limitations and possible applications of the created software as well as potential future developments

Reaction-Diffusion Process Driven by a Localized Source: First Passage Properties

We study a reaction-diffusion process that involves two species of atoms, immobile and diffusing. We assume that initially only immobile atoms, uniformly distributed throughout the entire space, are present. Diffusing atoms are injected at the origin by a source which is turned on at time t=0. When a diffusing atom collides with an immobile atom, the two atoms form an immobile stable molecule. The region occupied by molecules is asymptotically spherical with radius growing as t^{1/d} in d>=2 dimensions. We investigate the survival probability that a diffusing atom has not become a part of a molecule during the time interval t after its injection and the probability density of such a particle. We show that asymptotically the survival probability (i) saturates in one dimension, (ii) vanishes algebraically with time in two dimensions (with exponent being a function of the dimensionless flux and determined as a zero of a confluent hypergeometric function), and (iii) exhibits a stretched exponential decay in three dimensions.Comment: 7 pages; version 2: section IV is re-written, references added, 8 pages (final version

A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing

This work introduces an innovative parallel, fully-distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well-known that virtual part design and qualification in additive manufacturing requires highly-accurate multiscale and multiphysics analyses. Only high performance computing tools are able to handle such complexity in time frames compatible with time-to-market. However, efficiency, without loss of accuracy, has rarely held the centre stage in the numerical community. Here, in contrast, the framework is designed to adequately exploit the resources of high-end distributed-memory machines. It is grounded on three building blocks: (1) Hierarchical adaptive mesh refinement with octree-based meshes; (2) a parallel strategy to model the growth of the geometry; (3) state-of-the-art parallel iterative linear solvers. Computational experiments consider the heat transfer analysis at the part scale of the printing process by powder-bed technologies. After verification against a 3D benchmark, a strong-scaling analysis assesses performance and identifies major sources of parallel overhead. A third numerical example examines the efficiency and robustness of (2) in a curved 3D shape. Unprecedented parallelism and scalability were achieved in this work. Hence, this framework contributes to take on higher complexity and/or accuracy, not only of part-scale simulations of metal or polymer additive manufacturing, but also in welding, sedimentation, atherosclerosis, or any other physical problem where the physical domain of interest grows in time

2D pattern evolution constrained by complex network dynamics

Complex networks have established themselves along the last years as being particularly suitable and flexible for representing and modeling several complex natural and human-made systems. At the same time in which the structural intricacies of such networks are being revealed and understood, efforts have also been directed at investigating how such connectivity properties define and constrain the dynamics of systems unfolding on such structures. However, lesser attention has been focused on hybrid systems, \textit{i.e.} involving more than one type of network and/or dynamics. Because several real systems present such an organization (\textit{e.g.} the dynamics of a disease coexisting with the dynamics of the immune system), it becomes important to address such hybrid systems. The current paper investigates a specific system involving a diffusive (linear and non-linear) dynamics taking place in a regular network while interacting with a complex network of defensive agents following Erd\"os-R\'enyi and Barab\'asi-Albert graph models, whose nodes can be displaced spatially. More specifically, the complex network is expected to control, and if possible to extinguish, the diffusion of some given unwanted process (\textit{e.g.} fire, oil spilling, pest dissemination, and virus or bacteria reproduction during an infection). Two types of pattern evolution are considered: Fick and Gray-Scott. The nodes of the defensive network then interact with the diffusing patterns and communicate between themselves in order to control the spreading. The main findings include the identification of higher efficiency for the Barab\'asi-Albert control networks.Comment: 18 pages, 32 figures. A working manuscript, comments are welcome