Analytical investigations of laminar separations using the ''Crocco-Lees mixing parameter'' method

Analytical studies of laminar separations using Crocco-Lees mixing parameter metho

The Role of Probe-Trial Distractors in the Production/Removal of the Spatial Negative Priming Effect

In spatial negative priming (SNP) tasks, trials are presented in pairs; first the ‘prime’, and then the ‘probe’. Target and/or distractor events appear on both trials and probe target reaction time is significantly lengthened when it arises at a former distractor-occupied location (ignored-repetition [IR] trial), relative to when it appears at a new location (control [CO] trial). This latency inequality, which is not inevitable, defines the SNP effect. Here, we examined the influence of prime and probe trial distractor identity similarity on restoring the SNP effect when its prevention was successfully motivated by the use of a .25 (distractor present)/.75 (distractor absent) condition. Two results were important: (1) the SNP effect was restored when the probe distractor identity fully matched that of the prime trial, but not when distractor identities partially or totally mismatched, showing a retrieval role for the probe distractor, and, (2) target-repeat trial facilitation showed the same pattern, present with full matches, otherwise being absent. These results showed that prime-trial processing representations are stored episodically in location tasks, and that event identities are part of the episode, making distractor event identity matches critical for prime representation retrieval. Additionally, event numbers were not part of the episode so that matching event numbers between prime and probe trials was not important for retrieval of stored prime representations

Exploratory spatiotemporal data analysis and modelling of public confidence in the police in central London

Improving public confidence in the police is one of the most important issues for the London Metropolitan Police Service (Met). Public confidence varies over geographic space and changes over time. Spatiotemporal analysis and modelling becomes more manageable with a thorough understanding of the underlying spatiotemporal autocorrelation structure of the phenomena under scrutiny. In this study, exploratory spatiotemporal analysis is conducted on repeated cross-sectional survey data from the Metropolitan Police Public Attitude Survey. This confirmed the presence of second order nonstationarity in public perceptions of the Met police

Predicting public confidence in the police with spatiotemporal Bayesian hierarchical modelling.

Public confidence in the police is crucial to effective policing. Estimating and predicting public confidence at the local level will better enable the police to conduct proactive confidence interventions to meet the concerns of the community. This work represents the first application of Bayesian spatiotemporal modelling to estimation and prediction of public confidence in the police at the local level. Three models of increasing spatiotemporal complexity were fitted by Markov chain Monte Carlo simulation using free software package WinBUGS. Public confidence was successfully predicted at the local level using a spatiotemporal model with an inseparable interaction structure

LES on unstructured deforming meshes: Towards reciprocating IC engines

A variable explicit/implicit characteristics-based advection scheme that is second-order accurate in space and time has been developed recently for unstructured deforming meshes (O'Rourke & Sahota 1996a). To explore the suitability of this methodology for Large-Eddy Simulation (LES), three subgrid-scale turbulence models have been implemented in the CHAD CFD code (O'Rourke & Sahota 1996b): a constant-coefficient Smagorinsky model, a dynamic Smagorinsky model for flows having one or more directions of statistical homogeneity, and a Lagrangian dynamic Smagorinsky model for flows having no spatial or temporal homogeneity (Meneveau et al. 1996). Computations have been made for three canonical flows, progressing towards the intended application of in-cylinder flow in a reciprocating engine. Grid sizes were selected to be comparable to the coarsest meshes used in earlier spectral LES studies. Quantitative results are reported for decaying homogeneous isotropic turbulence, and for a planar channel flow. Computations are compared to experimental measurements, to Direct-Numerical Simulation (DNS) data, and to Rapid-Distortion Theory (RDT) where appropriate. Generally satisfactory evolution of first and second moments is found on these coarse meshes; deviations are attributed to insufficient mesh resolution. Issues include mesh resolution and computational requirements for a specified level of accuracy, analytic characterization of the filtering implied by the numerical method, wall treatment, and inflow boundary conditions. To resolve these issues, finer-mesh simulations and computations of a simplified axisymmetric reciprocating piston-cylinder assembly are in progress

Pierced, looped and framed: the (re)use of gold coins in jewellery in sixth‐ and seventh‐century England

The early medieval coin‐using economy is traditionally conceptualized as a masculine sphere with minimal female involvement. This article examines a corpus of 135 gold and pale gold coins of the later sixth and seventh centuries that underwent modification as coin‐pendants, a form of jewellery that belongs almost exclusively to feminine contexts. Analysis of this corpus reveals that these coins were valued as coins, with their attendant symbolic and economic significance, and that this transformation into jewellery did not irreversibly remove them from circulation, offering important evidence for female engagement in the seventh‐century coin‐based economy

DNS and modeling of the interaction between turbulent premixed flames and walls

The interaction between turbulent premixed flames and walls is studied using a two-dimensional full Navier-Stokes solver with simple chemistry. The effects of wall distance on the local and global flame structure are investigated. Quenching distances and maximum wall heat fluxes during quenching are computed in laminar cases and are found to be comparable to experimental and analytical results. For turbulent cases, it is shown that quenching distances and maximum heat fluxes remain of the same order as for laminar flames. Based on simulation results, a 'law-of-the-wall' model is derived to describe the interaction between a turbulent premixed flame and a wall. This model is constructed to provide reasonable behavior of flame surface density near a wall under the assumption that flame-wall interaction takes place at scales smaller than the computational mesh. It can be implemented in conjunction with any of several recent flamelet models based on a modeled surface density equation, with no additional constraints on mesh size or time step

A spatiotemporal bayesian hierarchical approach to investigating patterns of confidence in the police at the neighbourhood level

Public confidence in the police is crucial to effective policing. Improving understanding of public confidence at the local l evel will better enable the police to conduct proactive confidence interventions to meet the concerns of local communities. Conventional approaches do not consider that public confidence varies across geographic space as well as in time. Neighbourhood leve l approaches to modelling public confidence in the police are hampered by the small number problem and the resulting instability in the estimates and uncertainty in the results. This research illustrates a spatiotemporal Bayesian approach for estimating an d forecasting public confidence at the neighbourhood level and we use it to examine trends in public confidence in the police in London, UK, for Q2 2006 to Q3 2013. Our approach overcomes the limitations of the small number problem and specifically , we inv estigate the effect of the spatiotemporal representation structure chosen on the estimates of public confidence produced. We then investigate the use of the model for forecasting by producing one - step ahead forecasts of the final third of the time - series . The results are compared with the forecasts from traditional time - series forecasting methods like naïve, exponential smoothing, ARIMA, STARIMA and others. A model with spatially structured and unstructured random effects as well as a normally distributed s patiotemporal interaction term was the most parsimonious and produced the most realistic estimates. It also provided the best forecasts at the London - wide, Borough and neighbourhood level