Understanding the Socio-Economic Distribution and Consequences of Patterns of Multiple Deprivation: An Application of Self-Organising Maps. ESRI WP302. June 2009

In this paper we apply self organising maps (SOM) to a detailed set of material deprivation indicators from the Irish component of European Union Community Statistics on Income and Living Conditions (EU-SILC). The first stage of our analysis involves the identification and description of sixteen clusters of multiple deprivation that allow us to provide a detailed account of such deprivation in contemporary Ireland. In going beyond this mapping stage, we consider both patterns of socio-economic differentiation in relation to cluster membership and the extent to which such membership contributes to our understanding of the manner in which individuals experience their economic circumstances. Our analysis makes clear the continuing importance of traditional forms of stratification relating to factors such as income, social class and housing tenure in accounting for patterns of multiple deprivation. However, it also confirms the role of acute life events and life cycle and location influences. It suggests that debates relating to the extent to which poverty and social exclusion have become individualized should take particular care to distinguish between different kinds of outcomes. Further analysis demonstrates that the SOM approach is considerably more successful than a comparable latent class analysis in identifying those exposed to subjective economic stress. This finding, combined with those relating to the role of socio-economic factors in accounting for cluster membership, confirms that a focus on a set of eight SOM macro clusters seems most appropriate if our interest lies in broad patterns stratification. For other purposes differentiation within clusters, which clearly takes a systematic form, may prove to be crucial

Understanding the Socio-Economic Distribution and Consequences of Patterns of Multiple Deprivation: An Application of Self-Organising Maps

In this paper we apply self organising maps (SOM) to a detailed set of material deprivation indicators from the Irish component of European Union Community Statistics on Income and Living Conditions (EU-SILC). The first stage of our analysis involves the identification and description of sixteen clusters of multiple deprivation that allow us to provide a detailed account of such deprivation in contemporary Ireland. In going beyond this mapping stage, we consider both patterns of socio-economic differentiation in relation to cluster membership and the extent to which such membership contributes to our understanding of the manner in which individuals experience their economic circumstances. Our analysis makes clear the continuing importance of traditional forms of stratification relating to factors such as income, social class and housing tenure in accounting for patterns of multiple deprivation. However, it also confirms the role of acute life events and life cycle and location influences. It suggests that debates relating to the extent to which poverty and social exclusion have become individualized should take particular care to distinguish between different kinds of outcomes. Further analysis demonstrates that the SOM approach is considerably more successful than a comparable latent class analysis in identifying those exposed to subjective economic stress. This finding, combined with those relating to the role of socio-economic factors in accounting for cluster membership, confirms that a focus on a set of eight SOM macro clusters seems most appropriate if our interest lies in broad patterns stratification. For other purposes differentiation within clusters, which clearly takes a systematic form, may prove to be crucial.

Breaking degeneracy in jet dynamics: multi-epoch joint modelling of the BL Lac PKS 2155-304

Supermassive black holes can launch powerful jets which can be some of the most luminous multi-wavelength sources; decades after their discovery their physics and energetics are still poorly understood. The past decade has seen a dramatic improvement in the quality of available data, but despite this improvement the semi-analytical modelling of jets has advanced slowly: simple one-zone models are still the most commonly employed method of interpreting data, in particular for AGN jets. These models can roughly constrain the properties of jets but they cannot unambiguously couple their emission to the launching regions and internal dynamics, which can be probed with simulations. However, simulations are not easily comparable to observations because they cannot yet self-consistently predict spectra. We present an advanced semi-analytical model which accounts for the dynamics of the whole jet, starting from a simplified parametrization of Relativistic Magnetohydrodynamics in which the magnetic flux is converted into bulk kinetic energy. To benchmark the model we fit six quasisimultaneous, multi-wavelength spectral energy distributions of the BL Lac PKS 2155-304 obtained by the TANAMI program, and we address the degeneracies inherent to such a complex model by employing a state-of-the-art exploration of parameter space, which so far has been mostly neglected in the study of AGN jets. We find that this new approach is much more effective than a single-epoch fit in providing meaningful constraints on model parameters.Comment: Accepted for publication on MNRA

Ptychographic reconstruction of attosecond pulses

We demonstrate a new attosecond pulse reconstruction modality which uses an algorithm that is derived from ptychography. In contrast to other methods, energy and delay sampling are not correlated, and as a result, the number of electron spectra to record is considerably smaller. Together with the robust algorithm, this leads to a more precise and fast convergence of the reconstruction.Comment: 12 pages, 7 figures, the MATLAB code for the method described in this paper is freely available at http://figshare.com/articles/attosecond_Extended_Ptychographyc_Iterative_Engine_ePIE_/160187

A novel simulation methodology for orthogonal cryogenic machining with CFD spray cooling integration

The performance of cryogenic machining depends on the effectiveness of the heat transfer between the coolant jet and the chip in the cutting area because it affects the material temperature and the mechanical properties of the chip. This is a complex multi-physics problem because the solid deformation depends on the thermal and fluid–dynamic interaction with the cryogenic droplets generated by the atomization of the coolant jet. Within this context, this work applies an innovative methodology based on computational fluid dynamics to simulate the cutting process accounting for the interaction with the cryogenic jet. The proposed approach does not require empirical correlations since it integrates a predictive machining analytical model with Conjugate Heat Transfer CFD simulation and spray modelling to accurately estimate the heat transfer process accounting for the cooling effect of the impinging droplets. Complete Ti6Al4V dry and cryogenic cooled orthogonal cutting simulations were performed and results were compared with literature experimental data and state-of-the-art Finite Element Modelling simulations. The proposed methodology correctly estimates the cutting forces to vary cutting velocity and depth. Average errors in the resultant force estimation are 11.85% in dry and 14.4% in cryogenic cutting. Moreover, the experimental increase of the cutting force due to cooling is better estimated by the proposed approach with respect to FEM simulations. Thanks to the results accuracy and reduced computational costs, the proposed methodology could improve the understanding and the design of this innovative machining technology

Mapping Patterns of Multiple Deprivation Using Self-Organising Maps: An Application to EU-SILC Data for Ireland. ESRI WP286. March 2009

The development of conceptual frameworks for the analysis of social exclusion has somewhat out-stripped related methodological developments. This paper seeks to contribute to this process through the application of self-organising maps (SOMs) to the analysis of a detailed set of material deprivation indicators relating to the Irish case. The SOM approach allows us to offer a differentiated and interpretable picture of the structure of multiple deprivation in contemporary Ireland. Employing this approach, we identify 16 clusters characterised by distinct profiles across 42 deprivation indicators. Exploratory analyses demonstrate that position in the income distribution varies systematically by cluster membership. Moreover, in comparison with an analogous latent class approach, the SOM analysis offers considerable additional discriminatory power in relation to individuals’ experience of their economic circumstances. The results suggest that the SOM approach could prove a valuable addition to a ‘methodological platform’ for analysing the shape and form of social exclusion

Effects of fuel cetane number on the structure of diesel spray combustion: An accelerated Eulerian stochastic fields method

An Eulerian stochastic fields (ESF) method accelerated with the chemistry coordinate mapping (CCM) approach for modelling spray combustion is formulated, and applied to model diesel combustion in a constant volume vessel. In ESF-CCM, the thermodynamic states of the discretised stochastic fields are mapped into a low-dimensional phase space. Integration of the chemical stiff ODEs is performed in the phase space and the results are mapped back to the physical domain. After validating the ESF-CCM, the method is used to investigate the effects of fuel cetane number on the structure of diesel spray combustion. It is shown that, depending of the fuel cetane number, liftoff length is varied, which can lead to a change in combustion mode from classical diesel spray combustion to fuel-lean premixed burned combustion. Spray combustion with a shorter liftoff length exhibits the characteristics of the classical conceptual diesel combustion model proposed by Dec in 1997 (http://dx.doi.org/10.4271/970873), whereas in a case with a lower cetane number the liftoff length is much larger and the spray combustion probably occurs in a fuel-lean-premixed mode of combustion. Nevertheless, the transport budget at the liftoff location shows that stabilisation at all cetane numbers is governed primarily by the auto-ignition process

Development of a CFD methodology for fuel-air mixing and combustion modeling of GDI Engines

Simulation of GDI engines represents a very challenging task for CFD modeling. In particular, many sub-models are involved since the evolution of the fuel spray and liquid film formation should be modeled. Furthermore, it is necessary to account for both the influence of mixture and flow conditions close to the spark plug to correctly predict the flame propagation process. In this work, the authors developed a CFD methodology to study the air-fuel mixing and combustion processes in direct-injection, spark-ignition engines. A set of sub-models was developed to describe injection, atomization, breakup and wall impingement for sprays emerging from multi-hole atomizers. Furthermore, the complete evolution of the liquid fuel film was described by solving its mass, energy and momentum equations on the cylinderw wall boundaries. To model combustion, the Extended Coherent Flamelet Model (ECFM) was used in combination with a Lagrangian ignition model, describing the evolution of the flame kernel and accounting for both for flow, mixture composition and properties of the electrical circuit. The proposed approach has been implemented into the Lib-ICE code, which is based on the OpenFOAMR technology. In this paper, examples of application are provided, including the simulation of the fuel-air mixing process in a real GDI engine and the prediction of the premixed turbulent combustion process in a constant-volume vessel for different operating conditions

Particle Flow with a Hybrid Segmented Crystal and Fiber Dual-Readout Calorimeter

In the reconstruction of physics events at future e$^+$e$^-$ colliders the calorimeter design has a crucial role in the overall detector performance. The reconstruction of events with many jets in their final state sets stringent requirements on the jet energy and angular resolutions. The energy resolution for jets with energy of about 45 GeV is required to be at the 4-5\% level to enable an efficient separation of the W and Z boson invariant masses. We demonstrate in this paper how such a performance can be achieved by exploiting a particle flow algorithm tailored for a hybrid dual-readout calorimeter made of segmented crystals and fibers. The excellent energy resolution and linearity of such calorimeter for both photons and neutral hadrons ($3\%/\sqrt{E}$ and $26\%/\sqrt{E}$, respectively), inherent to the homogeneous crystals and dual-readout technological choices, provides a powerful handle for the development of a new approach for particle identification and jet reconstruction. While the dual-readout particle flow algorithm (DR-PFA) presented in this paper is at its early stage of development, it already demonstrates the potential of a hybrid dual-readout calorimeter for jet reconstruction by improving the jet energy resolution with respect to a calorimeter-only reconstruction from 6.0\% to about 4.5\% for 45 GeV jets