1,690 research outputs found
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<sup>−1</sup>. 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
Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail
Severe hailstorms have the potential to damage buildings and crops. However, important processes for the prediction of hailstorms are insufficiently represented in operational weather forecast models. Therefore, our goal is to identify model input parameters describing environmental conditions and cloud microphysics, such as the vertical wind shear and strength of ice multiplication, which lead to large uncertainties in the prediction of deep convective clouds and precipitation. We conduct a comprehensive sensitivity analysis simulating deep convective clouds in an idealized setup of a cloud-resolving model. We use statistical emulation and variance-based sensitivity analysis to enable a Monte Carlo sampling of the model outputs across the multi-dimensional parameter space. The results show that the model dynamical and microphysical properties are sensitive to both the environmental and microphysical uncertainties in the model. The microphysical parameters lead to larger uncertainties in the output of integrated hydrometeor mass contents and precipitation variables. In particular, the uncertainty in the fall velocities of graupel and hail account for more than 65 % of the variance of all considered precipitation variables and for 30 %–90 % of the variance of the integrated hydrometeor mass contents. In contrast, variations in the environmental parameters – the range of which is limited to represent model uncertainty – mainly affect the vertical profiles of the diabatic heating rates
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