Soil–pile interaction of pile embedded in deep-layered marine sediment under seismic excitation

This paper investigates the soil–pile interaction of a pile embedded in a deep multi-layered soil under seismic excitation considering both kinematic and inertial interaction effects. A comprehensive three-dimensional finite element model is developed and validated using existing results in the literature. The response of the pile in the deep multi-layered soil profile is investigated with respect to pile head response, deflection modes and maximum deflections along the pile. Results show that the pile exhibits complex deflection patterns and that the pile response is influenced by the properties of both the soil profile and the seismic excitation. It is also evident that kinematic interaction effects have a greater influence on the pile response than the inertial interaction effects.

A preliminary OSL chronology for coastal dunes on Moreton island, Queensland, Australia – Marginal deposits of A large-scale quaternary shelf sediment system

Moreton Island and several other large siliceous sand dune islands and mainland barrier deposits in SE Queensland represent the distal, onshore component of an extensive Quaternary continental shelf sediment system. This sediment has been transported up to 1000 km along the coast and shelf of SE Australia over multiple glacioeustatic sea-level cycles. Stratigraphic relationships and a preliminary Optically Stimulated Luminance (OSL) chronology for Moreton Island indicate a middle Pleistocene age for the large majority of the deposit. Dune units exposed in the centre of the island and on the east coast have OSL ages that indicate deposition occurred between approximately 540 ka and 350 ka BP, and at around 96±10 ka BP. Much of the southern half of the island has a veneer of much younger sediment, with OSL ages of 0.90±0.11 ka, 1.28±0.16 ka, 5.75±0.53 ka and <0.45 ka BP. The younger deposits were partially derived from the reworking of the upper leached zone of the much older dunes. A large parabolic dune at the northern end of the island, OSL age of 9.90±1.0 ka BP, and palaeosol exposures that extend below present sea level suggest the Pleistocene dunes were sourced from shorelines positioned several to tens of metres lower than, and up to few kilometres seaward of the present shoreline. Given the lower gradient of the inner shelf a few km seaward of the island, it seems likely that periods of intermediate sea level (e.g. ~20 m below present) produced strongly positive onshore sediment budgets and the mobilisation of dunes inland to form much of what now comprises Moreton Island. The new OSL ages and comprehensive OSL chronology for the Cooloola deposit, 100 km north of Moreton Island, indicate that the bulk of the coastal dune deposits in SE Queensland were emplaced between approximately 540 ka BP and prior to the Last Interglacial. This chronostratigraphic information improves our fundamental understanding of long-term sediment transport and accumulation on large-scale continental shelf sediment systems.

Open and closed-loop recycling of textile and apparel products

Textile waste is a significant contributor to landfill yet the majority of textiles can be recycled, allowing for the energy and fibre to be reclaimed. This chapter examines the open-loop and closed loop recycling of textile products with particular reference to the fashion and apparel context. It describes the fibres used within apparel, the current mechanical and chemical methods for textile recycling, LCA findings for each method, and applications within apparel for each. Barriers for more effective recycling include ease of integration into existing textile and apparel design methods as well as coordinated collection of post-consumer waste. The chapter concludes with a discussion of innovations that point to future trends in both open-loop and closed-loop recycling within the apparel industry.

Determination of refractive and volatile elements in sediment using laser ablation inductively coupled plasma mass spectrometry

Wet-milling protocol was employed to produce pressed powder tablets with excellent cohesion and homogeneity suitable for laser ablation (LA) analysis of volatile and refractive elements in sediment. The influence of sample preparation on analytical performance was also investigated, including sample homogeneity, accuracy and limit of detection. Milling in volatile solvent for 40 min ensured sample is well mixed and could reasonably recover both volatile (Hg) and refractive (Zr) elements. With the exception of Cr (−52%) and Nb (+26%) major, minor and trace elements in STSD-1 and MESS-3 could be analysed within ±20% of the certified values. Comparison of the method with total digestion method using HF was tested by analysing 10 different sediment samples. The laser method recovers significantly higher amounts of analytes such as Ag, Cd, Sn and Sn than the total digestion method making it a more robust method for elements across the periodic table. LA-ICP-MS also eliminates the interferences from chemical reagents as well as the health and safety risks associated with digestion processes. Therefore, it can be considered as an enhanced method for the analysis of heterogeneous matrices such as river sediments.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.