Polymer brushes under shear: molecular dynamics simulations compared to experiments

Surfaces coated with polymer brushes in a good solvent are known to exhibit excellent tribological properties. We have performed coarse-grained equilibrium and nonequilibrium molecular dynamics (MD) simulations to investigate dextran polymer brushes in an aqueous environment in molecular detail. In a first step, we determined simulation parameters and units by matching experimental results for a single dextran chain. Analyzing this model when applied to a multichain system, density profiles of end-tethered polymer brushes obtained from equilibrium MD simulations compare very well with expectations based on self-consistent field theory. Simulation results were further validated against and correlated with available experimental results. The simulated compression curves (normal force as a function of surface separation) compare successfully with results obtained with a surface forces apparatus. Shear stress (friction) obtained via nonequilibrium MD is contrasted with nanoscale friction studies employing colloidal-probe lateral force microscopy. We find good agreement in the hydrodynamic regime and explain the observed leveling-off of the friction forces in the boundary regime by means of an effective polymer–wall attraction.

Velocities of compressional and shear waves in limestones

Carbonate rocks are important hydrocarbon reservoir rocks with complex textures and petrophysical properties (porosity and permeability) mainly resulting from various diagenetic processes (compaction, dissolution, precipitation, cementation, etc.). These complexities make prediction of reservoir characteristics (e.g. porosity and permeability) from their seismic properties very difficult. To explore the relationship between the seismic, petrophysical and geological properties, ultrasonic compressional- and shear-wave velocity measurements were made under a simulated in situ condition of pressure (50 MPa hydrostatic effective pressure) at frequencies of approximately 0.85 MHz and 0.7 MHz, respectively, using a pulse-echo method. The measurements were made both in vacuum-dry and fully saturated conditions in oolitic limestones of the Great Oolite Formation of southern England. Some of the rocks were fully saturated with oil. The acoustic measurements were supplemented by porosity and permeability measurements, petrological and pore geometry studies of resin-impregnated polished thin sections, X-ray diffraction analyses and scanning electron microscope studies to investigate submicroscopic textures and micropores. It is shown that the compressional- and shear-wave velocities (V-p and V-s, respectively) decrease with increasing porosity and that V-p decreases approximately twice as fast as V-s. The systematic differences in pore structures (e.g. the aspect ratio) of the limestones produce large residuals in the velocity versus porosity relationship. It is demonstrated that the velocity versus porosity relationship can be improved by removing the pore-structure-dependent variations from the residuals. The introduction of water into the pore space decreases the shear moduli of the rocks by about 2 GPa, suggesting that there exists a fluid/matrix interaction at grain contacts, which reduces the rigidity. The predicted Biot-Gassmann velocity values are greater than the measured velocity values due to the rock-fluid interaction. This is not accounted for in the Biot-Gassmann velocity models and velocity dispersion due to a local flow mechanism. The velocities predicted by the Raymer and time-average relationships overestimated the measured velocities even more than the Biot model.

Ice internal friction: Standard theoretical perspectives on friction codified, adapted for the unusual rheology of ice, and unified

Sea ice contains flaws including frictional contacts. We aim to describe quantitatively the mechanics of those contacts, providing local physics for geophysical models. With a focus on the internal friction of ice, we review standard micro-mechanical models of friction. The solid's deformation under normal load may be ductile or elastic. The shear failure of the contact may be by ductile flow, brittle fracture, or melting and hydrodynamic lubrication. Combinations of these give a total of six rheological models. When the material under study is ice, several of the rheological parameters in the standard models are not constant, but depend on the temperature of the bulk, on the normal stress under which samples are pressed together, or on the sliding velocity and acceleration. This has the effect of making the shear stress required for sliding dependent on sliding velocity, acceleration, and temperature. In some cases, it also perturbs the exponent in the normal-stress dependence of that shear stress away from the value that applies to most materials. We unify the models by a principle of maximum displacement for normal deformation, and of minimum stress for shear failure, reducing the controversy over the mechanism of internal friction in ice to the choice of values of four parameters in a single model. The four parameters represent, for a typical asperity contact, the sliding distance required to expel melt-water, the sliding distance required to break contact, the normal strain in the asperity, and the thickness of any ductile shear zone.

The role of lateral ocean physics in the upper ocean thermal balance of a coupled ocean-atmosphere GCM

The sensitivity of the upper ocean thermal balance of an ocean-atmosphere coupled GCM to lateral ocean physics is assessed. Three 40-year simulations are performed using horizontal mixing, isopycnal mixing, and isopycnal mixing plus eddy induced advection. The thermal adjustment of the coupled system is quite different between the simulations, confirming the major role of ocean mixing on the heat balance of climate. The initial adjustment phase of the upper ocean (SST) is used to diagnose the physical mechanisms involved in each parametrisation. When the lateral ocean physics is modified, significant changes of SST are seen, mainly in the southern ocean. A heat budget of the annual mixed layer (defined as the “bowl”) shows that these changes are due to a modified heat transfer between the bowl and the ocean interior. This modified heat intake of the ocean interior is directly due to the modified lateral ocean physics. In isopycnal diffusion, this heat exchange, especially marked at mid-latitudes, is both due to an increased effective surface of diffusion and to the sign of the isopycnal gradients of temperature at the base of the bowl. As this gradient is proportional to the isopycnal gradient of salinity, this confirms the strong role of salinity in the thermal balance of the coupled system. The eddy induced advection also leads to increased exchanges between the bowl and the ocean interior. This is both due to the shape of the bowl and again to the existence of a salinity structure. The lateral ocean physics is shown to be a significant contributor to the exchanges between the diabatic and the adiabatic parts of the ocean.

Lateral phase separation in grafted diblock copolymer films

Tethered films of polystyrene-block-poly(methyl methacrylate) copolymers of varying composition and molecular weight were investigated using atomic force microscopy and the observed structures compared with theoretical predictions. Although the experimental results were in qualitative agreement with the theory, there was significant quantitative variation. This was attributed to the presence of solvent in the films prior to and during annealing, a hypothesis supported by new preliminary calculations reported here. Solvent exchange experiments (where a good solvent for both polymer blocks was gradually replaced by a selective solvent), were also performed on the films. This procedure generated textured films in which the structure was defined by miscibility of the polymer blocks with the second solvent.

Sustainable refurbishment: quantifying the impact of façade changes in multi-storey, multi-occupancy buildings

Building refurbishment is key to reducing the carbon footprint and improving comfort in the built environment. However, quantifying the real benefit of a facade change, which can bring advantages to owners (value), occupants (comfort) and the society (sustainability), is not a simple task. At a building physics level, the changes in kWh per m2 of heating / cooling load can be readily quantified. However, there are many subtle layers of operation and mainte-nance below these headline figures which determine how sustainable a building is in reality, such as for example quality of life factors. This paper considers the range of approached taken by a fa/e refurbishment consortium to assess refurbishment solutions for multi-storey, multi-occupancy buildings and how to critically evaluate them. Each of the applued tools spans one or more of the three building parameters of people, product and process. 'De-cision making' analytical network process and parametric building analysis tools are described and their potential impact on the building refurbishment process evaluated.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

Adaptive recursive control of a soil testing load frame

Recursive Learning Control (RLC) has the potential to significantly reduce the tracking error in many repetitive trajectory applications. This paper presents an application of RLC to a soil testing load frame where non-adaptive techniques struggle with the highly nonlinear nature of soil. The main purpose of the controller is to apply a sinusoidal force reference trajectory on a soil sample with a high degree of accuracy and repeatability. The controller uses a feedforward control structure, recursive least squares adaptation algorithm and RLC to compensate for periodic errors. Tracking error is reduced and stability is maintained across various soil sample responses.

Fast adaptive real-time classification for data streams with concept drift

An important application of Big Data Analytics is the real-time analysis of streaming data. Streaming data imposes unique challenges to data mining algorithms, such as concept drifts, the need to analyse the data on the fly due to unbounded data streams and scalable algorithms due to potentially high throughput of data. Real-time classification algorithms that are adaptive to concept drifts and fast exist, however, most approaches are not naturally parallel and are thus limited in their scalability. This paper presents work on the Micro-Cluster Nearest Neighbour (MC-NN) classifier. MC-NN is based on an adaptive statistical data summary based on Micro-Clusters. MC-NN is very fast and adaptive to concept drift whilst maintaining the parallel properties of the base KNN classifier. Also MC-NN is competitive compared with existing data stream classifiers in terms of accuracy and speed.