William Atherton

Mechanical Properties of an Upgrading Cold-Mix Asphalt Using Waste Materials

AbstractConsiderable advantages could be achieved if the cold bituminous emulsion mixtures (CBEMs) show comparable engineering properties to hot-mix asphalt (HMA), particularly because CBEMs require no heat within the manufacture and laying process. As a result, such pavement produces less environmental impact, is more cost effective, and requires less energy consumption. This paper focuses on upgrading the CBEMs to a stage whereby their mechanical properties are comparable to traditional HMA. Waste or by-product materials were used within the CBEMs to improve the mechanical properties, namely indirect tensile stiffness modulus and creep stiffness. Five percentages from 0 to 5.5% of aggregate mass in the mixture of the LJMU-FA1 that is waste or by-product material was incorporated in the CBEMs. The results have illustrated a comparative enhancement in the mechanical properties of the new cold mixtures attributable to the use of the specific waste materials. Thus, new CBEMs having superior mechanical prope...

Flood risk assessment for urban water system in a changing climate using artificial neural network

Changes in rainfall patterns due to climate change are expected to have negative impact on urban drainage systems, causing increase in flow volumes entering the system. In this paper, two emission scenarios for greenhouse concentration have been used, the high (A1FI) and the low (B1). Each scenario was selected for purpose of assessing the impacts on the drainage system. An artificial neural network downscaling technique was used to obtain local-scale future rainfall from three coarse-scale GCMs. An impact assessment was then carried out using the projected local rainfall and a risk assessment methodology to understand and quantify the potential hazard from surface flooding. The case study is a selected urban drainage catchment in northwestern England. The results show that there will be potential increase in the spilling volume from manholes and surcharge in sewers, which would cause a significant number of properties to be affected by flooding.

Mechanical Behavior of a New Base Material Containing High Volumes of Limestone Waste Dust, PFA, and APC Residues

AbstractThe results of research are reported in this work that evaluated the benefits of the stabilization of Type 1 subbase material to which had been added a high volume of limestone quarry waste dust. There is extensive interest in introducing large volumes of quarry waste dusts to the Type 1 subbase that is used in the construction of the vast majority of foundations for roads and other pavements in the United Kingdom. Previous experience has indicated that replacement of 10–30% of Type 1 subbase with limestone quarry waste dust made the mixture inadequate for pavement foundation purposes. When pulverized fuel ash (PFA) and lime were added to these materials, the new mixture improved to a level that made the materials suitable for use as subbase in pavements. However, lime was still a costly industrial product and a major CO2 emitter. The replacement of lime with another capable PFA activator of waste or recycled origin was sought. After examining several potential wastes, it was found that air pollut...

Quantitative assessment of sewer overflow performance with climate change in northwest England

Abstract Changes in rainfall patterns associated with climate change can affect the operation of a combined sewer system, with the potential increase in rainfall amount. This could lead to excessive spill frequencies and could also introduce hazardous substances into the receiving waters, which, in turn, would have an impact on the quality of shellfish and bathing waters. This paper quantifies the spilling volume, duration and frequency of 19 combined sewer overflows (CSOs) to receiving waters under two climate change scenarios, the high (A1FI), and the low emissions (B1) scenarios, simulated by three global climate models (GCMs), for a study catchment in northwest England. The future rainfall is downscaled, using climatic variables from HadCM3, CSIRO and CGCM2 GCMs, with the use of a hybrid generalized linear–artificial neural network model. The results from the model simulation for the future in 2080 showed an annual increase of 37% in total spill volume, 32% in total spill duration, and 12% in spill frequency for the shellfish water limiting requirements. These results were obtained, under the high emissions scenario, as projected by the HadCM3 as maximum. Nevertheless, the catchment drainage system is projected to cope with the future conditions in 2080 by all three GCMs. The results also indicate that under scenario B1, a significant drop was projected by CSIRO, which in the worst case could reach up to 50% in spill volume, 39% in spill duration and 25% in spill frequency. The results further show that, during the bathing season, a substantial drop is expected in the CSO spill drivers, as predicted by all GCMs under both scenarios. Editor Z.W. Kundzewicz; Associate editor L. See

Assessing combined sewer overflows with long lead time for better surface water management

During high-intensity rainfall events, the capacity of combined sewer overflows (CSOs) can exceed resulting in discharge of untreated stormwater and wastewater directly into receiving rivers. These discharges can result in high concentrations of microbial pathogens, biochemical oxygen demand, suspended solids, and other pollutants in the receiving waters. The frequency and severity of the CSO discharge are strongly influenced by climatic factors governing the occurrence of urban stormwater runoff, particularly the amount and intensity of the rainfall. This study attempts to assess the impact of climate change (change in rainfall amount and frequency) on CSO under the high (A1FI) and low (B1) Special Report on Emissions Scenarios of the greenhouse concentration derived from three global circulation models in the north west of England at the end of the twenty-first century.

Feasibility of an evolutionary artificial intelligence (AI) scheme for modelling of load settlement response of concrete piles embedded in cohesionless soil

ABSTRACT This investigation aimed to examine the load carrying capacity of piles embedded in sandy soil of various densities, and to develop a predictive model to determine pile settlement using a novel artificial intelligence (AI) method. Experimental pile load tests were conducted using three concrete piles, with aspect ratios of 12, 17 and 25. Evolutionary Levenberg–Marquardt MATLAB algorithms, enhanced by T-tests and F-tests, were used in this process. According to the statistical analysis and the relative importance study, pile length, applied load, pile flexural rigidity, pile aspect ratio and sand–pile friction angle were found to play a key role in pile settlement. Results revealed that the proposed optimum model algorithm precisely characterized pile settlement. There was close agreement between the experimental and predicted data (Pearsons R = 0.988, P = 6.28 × 10-31) with a relatively insignificant root mean square error of 0.002.

Application of the UKCP09 WG Outputs to Assess Performance of Combined Sewers System in a Changing Climate

AbstractIn many parts of the world, old sewer systems have been designed without consideration for change in climate, so probabilities and risks of sewer surcharge and flooding are elevated due to increase in extreme rainfall events as a consequence of global warming. The current paper is aiming to assess how the climate change on interannual to multidecadal timescale (2020s; 2050s; 2080s) will affect design standards of wastewater networks due to the presumed increase in rainfall intensity and frequency in the Northwest of England area (selected site). Design storms have been analyzed for future rainfall obtained from the UK Climate Projection version 2009 (UKCP09) weather generator (WG), which was applied to the existing urban drainage system to check the level of service in winter and summer seasons. Two emission scenarios (SRES) have been adopted to simulate the greenhouse gas concentration; high scenario (A1FI) and low scenario (B1). Results indicate that the impact of increase in the design storm of...

Possible source term of high concentrations of mecoprop-p in leachate and water quality: impact of climate change, public use and disposal

Mecoprop-p herbicide is often found in wells and water abstractions in many areas around Europe, the UK inclusive. There is a growing environmental and public health concern about mecoprop-p herbicide pollution in ground and surface water in England. Reviews suggest that extensive work has been carried out on the contribution of mecoprop-p herbicides from agricultural use whilst more work needs to be carried out on the contribution of mecoprop-p herbicide from non-agricultural use. The study covers two landfill sites in Weaver/Gowy Catchment. Mecoprop-p herbicide concentrations in the leachate quality range between 0.06 and 290 μg l−1 in cells. High concentration of mecoprop-p herbicide in the leachate quality suggests that there is a possible source term in the waste stream. This paper addresses the gap by exploring possible source terms of mecoprop-p herbicide contamination on landfill sites and evaluates the impact of public purchase, use and disposal alongside climate change on seasonal variations in mecoprop-p concentrations. Mecoprop-p herbicide was found to exceed the EU drinking water quality standards at the unsaturated zone/aquifer with observed average concentrations ranging between 0.005 and 7.96 μg l−1. A route map for mecoprop-p herbicide source term contamination is essential for mitigation and pollution management with emphasis on both consumer and producer responsibility towards use of mecoprop-p product. In addition, improvement in data collection on mecoprop-p concentrations and detailed seasonal herbicide sales for non-agricultural purposes are needed to inform the analysis and decision process.

THE MODELING OF SPILLS RESULTING FROM THE CATASTROPHIC FAILURE OF ABOVE GROUND STORAGE TANKS AND THE DEVELOPMENT OF MITIGATION

ABSTRACT The risk of accidents involving the catastrophic failure of storage tanks is estimated to be low, in the region of 5 × l0−6 per tank year. However, recent accidents involving major oil spills at storage facilities located in Belgium (2004) along with USA and England (2005) have shown that tank failures do nevertheless occur. Causalities of such events vary; the consequences however are ordinarily the same, incurring environmental, financial and infrastructure losses. The normal mitigation technique employed to prevent such losses is secondary containment, usually in the form of a bund wall or earthen dyke. Researchers have investigated the reliability of such methods, examining the effects of tank failure, both theoretically and experimentally in terms of loss of containment. A United Kingdom Health and Safety Executive (HSE) review conducted in 1997 concluded that the then available data was limited and focussed attention on the work of Greenspan and Johansson (1981) and the later work of Troboj...

Settlement Prediction of Model Piles Embedded in Sandy Soil Using the Levenberg–Marquardt (LM) Training Algorithm

This investigation aimed to examine the load carrying capacity of model piles embedded in sandy soil and to develop a predictive model to simulate pile settlement using a new artificial neural network (ANN) approach. A series of experimental pile load tests were carried out on model concrete piles, comprised of three piles with slenderness ratios of 12, 17 and 25. This was to provide an initial dataset to establish the ANN model, in attempt at making current, in situ pile-load test methods unnecessary. Evolutionary Levenberg–Marquardt (LM) MATLAB algorithms, enhanced by T-tests and F-tests, were developed and applied in this process. The model piles were embedded in a calibration chamber in three densities of sand; loose, medium and dense. According to the statistical analysis and the relative importance study, pile lengths, applied load, pile flexural rigidity, pile aspects ratio, and sand-pile friction angle were found to play a key role in pile settlement at different contribution levels, following the order: P > δ > lc/d > lc > EA. The results revealed that the optimum model of the LM training algorithm can be used to characterize pile settlement with good degree of accuracy. There was also close agreement between the experimental and predicted data with a root mean square error, (RMSE) and correlation coefficient (R) of 0.0025192 and 0.988, respectively.