Search

Non-stationary methods of flood frequency analysis are widespread in research but rarely implemented by practitioners. One reason may be that research papers on non-stationary statistical models tend to focus on model fitting rather than extracting the sort of results needed by designers and decision makers. It can be difficult to extract useful results from non-stationary models that include stochastic covariates for which the value in any future year is unknown. We explore the motivation for including such covariates, whether on their own or in addition to a covariate based on time. We set out a method for expressing the results of non-stationary models as an integrated flow estimate, which removes the dependence on the covariates. This can be defined either for a particular year or over a longer period of time. The methods are illustrated by application to a set of 375 river gauges across England and Wales. We find annual rainfall to be a useful covariate at many gauges, sometimes in conjunction with a time-based covariate. For estimating flood frequency in future conditions, we advocate exploring hybrid approaches that combine the best attributes of non-stationary statistical models and simulation models that can represent changes in climate and river catchments. [ABSTRACT FROM AUTHOR]

The following paper reiterates the importance of studying past visibility patterns within the context of landscape archaeology. In spite of the many difficulties and criticisms revolving around this topic, efforts aimed at reconstructing these patterns and exploring their possible roles are considered to be central to the reconstruction of social landscapes. This paper extends previous GIS work done on inter-visibility by making reference to the concept of "co-visibility," by exploring the way in which visibility of any monument or set of monuments is shared with that of other monuments. A subset of round barrows from the Yorkshire Wolds (northern England) is used to illustrate this work. The study also underlines the need to address the variability which is often present in archaeological data, variability, in this case, of visibility patterns associated with the barrows due to our lack of precise chronological information. [ABSTRACT FROM AUTHOR]

Abstract: London is expected to experience more frequent periods of intense rainfall and tidal surges, leading to an increase in the risk of flooding. Damp and flooded dwellings can support microbial growth, including mould, bacteria, and protozoa, as well as persistence of flood-borne microorganisms. The amount of time flooded dwellings remain damp will depend on the duration and height of the flood, the contents of the flood water, the drying conditions, and the building construction, leading to particular properties and property types being prone to lingering damp and human pathogen growth or persistence. The impact of flooding on buildings can be simulated using Heat Air and Moisture (HAM) models of varying complexity in order to understand how water can be absorbed and dry out of the building structure. This paper describes the simulation of the drying of building archetypes representative of the English building stock using the EnergyPlus based tool ‘UCL-HAMT’ in order to determine the drying rates of different abandoned structures flooded to different heights and during different seasons. The results are mapped out using GIS in order to estimate the spatial risk across London in terms of comparative flood vulnerability, as well as for specific flood events. Areas of South and East London were found to be particularly vulnerable to long-term microbial exposure following major flood events. [Copyright &y& Elsevier]

Abstract: A computer based building simulation model was developed to examine the energy load and environmental management in The National Archives Q1 repository building in Kew, UK to optimise environmental management and examine the impacts of climate change. The need to accurately simulate the hygrothermal environment inside the archive building which houses mainly paper-based records led to the choice of EnergyPlus as the modelling software. The study presents the simulation results of five environmental strategies which predict energy saving potential as high as 43% without significantly affecting the quality of the preservation environment. The effect of climate change is predicted to have little impact on the archive environment due to the filtering effect of the air conditioning system. On the other hand, an increase in total energy load by 15% and 24% is predicted under the worst case climate change scenario in 2050 and 2080, respectively, if the current environmental management practice is continued into the future. However, the identified energy saving strategies could represent possible mitigative solutions in reducing future energy load against the impact of climate change. [Copyright &y& Elsevier]

Abstract: This paper presents a meanline model to predict the performance parameters of a turbocharger turbine under steady state conditions. The turbine was developed at Imperial College and the design was based on a commercial nozzleless unit that was modified into a variable geometry single-entry turbine. The wide range of tests data from the Imperial College Turbocharger Group dynamometer enabled the evaluation of the model in the areas of the turbine map where currently no previous comparison had been made in the literature. This facility is designed to allow testing over a wide range of velocity ratios (0.3–1.1) previously unavailable with conventional test stands. The nozzleless turbine model was validated against experimental results spanning an equivalent speed range of 27.9 and 53.8rev/s√K while for the nozzled case the model was validated against one single speed (43.0rev/s√K) and three different vane angle settings (40°, 60° and 70°). The results of the model simulation showed that the performance can be predicted with excellent accuracy for different turbine speeds and vane angles. Based on the model prediction, a breakdown aerodynamic loss was performed. [Copyright &y& Elsevier]

Abstract: Traditionally, researchers have employed statistical methods to model crime. However, these approaches are limited by being unable to model individual actions and behaviour. Brantingham and Brantingham (1993) described that in their opinion a useful and productive model for simulating crime would have the ability to model the occurrence of crime and the motivations behind it both temporally and spatially. This paper presents the construction and application of an agent-based model (ABM) for simulating occurrences of residential burglary at an individual level. It presents a novel framework that allows both human and environmental factors to be simulated. Although other agent-based models of crime do exist, this research represents the first working example of integrating a behavioural framework into an ABM for the simulation of crime. An artificial city, loosely based on the real city of Leeds, UK, and an artificial population were constructed, and experiments were run to explore the potential of the model to realistically simulate the main processes and drivers within this system. The results are highly promising, demonstrating the potential of this approach for both understanding processes behind crime and improving policies and developing effective crime prevention strategies. [Copyright &y& Elsevier]

Abstract: This study investigates Box–Jenkins (BJ), autoregressive with external inputs (ARX), autoregressive moving average with external inputs (ARMAX) and output error (OE) models to identify the thermal behaviour of an office positioned in a modern commercial building in London. These models can all be potentially used for improving the performance of the thermal environment control system. External and internal climate data, recorded over the summer, autumn and winter seasons, were used to build and validate the models. The paper demonstrates the potential of using linear parametric models to predict room temperature and relative humidity for different time scales (30min or 2h ahead). The prediction performance is evaluated using the criteria of goodness of fit, coefficient of determination, mean absolute error and mean squared error between predicted model output and real measurements. The results demonstrate that all models provide reasonably good predictions but the BJ model outperforms the ARMAX and ARX models. [Copyright &y& Elsevier]

Abstract: This paper demonstrates the application of Terrestrial Laser Scanning (TLS) to determine the full population of grain roughness in gravel-bed rivers. The technique has the potential to completely replace the need for complex, time-consuming manual sampling methods. Using TLS, a total of 3.8 million data points (mean spacing 0.01 m) were retrieved from a gravel bar surface at Lambley on the River South Tyne, UK. Grain roughness was extracted through determination of twice the local standard deviation (2σ z ) of all the elevations in a 0.15 m radius moving window over the data cloud. 2σ z values were then designated to each node on a 5 cm regular grid, allowing fine resolution DEMs to be produced, where the elevation is equivalent to the grain roughness height. Comparisons are made between TLS-derived grain roughness and grid-by-number sampling for eight 2 m2 patches on the bar surface. Strong relationships exist between percentiles from the population of 2σ z heights with measured a-, b-, and c-axes, with the closest matches appearing for the c-axis. Although strong relationships exist between TLS-derived grain roughness (2σ z ), variations in the degree of burial, packing and imbrication, results in very different slope and intercept exponents. This highlights that conventional roughness measurement using gravel axis length should be used with caution as measured axes do not necessarily represent the actual extent to which the grain protrudes into the flow. The sampling error inherent in conventional sampling is also highlighted through undertaking Monte Carlo simulation on a population of 2000 clasts measured using the grid-by-number method and comparing this with the TLS-derived population of grain roughness heights. Underestimates of up to −23% and overestimates of up to +50% were found to occur when considering the D 84, and −20% and overestimates of up to +36% were found to occur when considering the D 50. [Copyright &y& Elsevier]