Water quality impacts and palaeohydrogeology in the East Yorkshire Chalk Aquifer, UK

A large hydrochemical data-set for the East Yorkshire Chalk has been assessed. Controls on the distribution of water qualities within this aquifer reflect: water-rock interactions (affecting especially the carbonate system and associated geochemistry); effects of land-use change (especially where the aquifer is unconfined); saline intrusion and aquifer refreshening (including ion exchange effects); and aquifer overexploitation (in the semi-confined and confined zones of the aquifer). Both Sr and I prove useful indicators of groundwater ages, with I/Cl ratios characterising two sources of saline waters. The hydrochemical evidence clearly reveals the importance of both recent management decisions and palaeohydrogeology in determining the evolution and distribution of groundwater salinity within the artesian and confined zones of the aquifer. Waters currently encountered in the aquifer are identified as complex (and potentially dynamic) mixtures between modern recharge waters, modern seawater, and old seawaters which entered the aquifer many millennia ago.

Quantum-state transfer in imperfect artificial spin networks

High-fidelity quantum computation and quantum state transfer are possible in short spin chains. We exploit a system based on a dispersive qubit-boson interaction to mimic XY coupling. In this model, the usually assumed nearest-neighbor coupling is no longer valid: all the qubits are mutually coupled. We analyze the performances of our model for quantum state transfer showing how preengineered coupling rates allow for nearly optimal state transfer. We address a setup of superconducting qubits coupled to a microstrip cavity in which our analysis may be applied.

Performance of a Sequential Reactive Barrier for Bioremediation of Coal Tar Contaminated Groundwater

Following a thorough site investigation, a biological Sequential Reactive Barrier (SEREBAR), designed to remove Polycyclic Aromatic Hydrocarbons (PAHs) and BTEX compounds, was installed at a Former Manufactured Gas Plant (FMGP) site. The novel design of the barrier comprises, in series, an interceptor and six reactive chambers. The first four chambers (2 nonaerated-2 aerated) were filled with sand to encourage microbial colonization. Sorbant Granular Activated Carbon (GAC) was present in the final two chambers in order to remove any recalcitrant compounds. The SEREBAR has been in continuous operation for 2 years at different operational flow rates (ranging from 320 L/d to 4000 L/d, with corresponding residence times in each chamber of 19 days and 1.5 days, respectively). Under low flow rate conditions (320-520 L/d) the majority of contaminant removal (>93%) occurred biotically within the interceptor and the aerated chambers. Under high flow rates (1000-4000 L/d) and following the installation of a new interceptor to prevent passive aeration, the majority of contaminant removal (>80%) again occurred biotically within the aerated chambers. The sorption zone (GAC) proved to be an effective polishing step, removing any remaining contaminants to acceptable concentrations before discharge down-gradient of the SEREBAR (overall removals >95%).

Modelling the correlation between processing parameters and properties of maraging steels using artificial neural network

An artificial neural network (ANN) model is developed for the analysis and simulation of the correlation between the properties of maraging steels and composition, processing and working conditions. The input parameters of the model consist of alloy composition, processing parameters (including cold deformation degree, ageing temperature, and ageing time), and working temperature. The outputs of the ANN model include property parameters namely: ultimate tensile strength, yield strength, elongation, reduction in area, hardness, notched tensile strength, Charpy impact energy, fracture toughness, and martensitic transformation start temperature. Good performance of the ANN model is achieved. The model can be used to calculate properties of maraging steels as functions of alloy composition, processing parameters, and working condition. The combined influence of Co and Mo on the properties of maraging steels is simulated using the model. The results are in agreement with experimental data. Explanation of the calculated results from the metallurgical point of view is attempted. The model can be used as a guide for further alloy development.