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A geometric method for analysis of elastic and elastic-plastic solids is proposed. It involves operators on naturally discrete domains representing a material’s microstructure, rather than the classical discretisation of domains for solving continuum boundary value problems. Discrete microstructures are considered as general cell complexes, which are circumcentre-dual to simplicial cell complexes. The proposed method uses the separation of the total deformation energy into volumetric and distortional parts as a base for introducing elastoplastic material behaviour. Volumetric parts are obtained directly from volume changes of dual cells, and the distortional parts are calculated from the distance changes between primal and dual nodes. First, it is demonstrated that the method can accurately reproduce the elastic behaviour of solids with Poisson’s ratios in the thermodynamically admissible range from -0.99 to 0.49. Further verification of the method is demonstrated by excellent agreement between analytical results and simulations of the elastic deformation of a beam subjected to a vertical displacement. Second, the Prandtl operator approach is used to simulate the behaviour of the solid during cyclic loading, considering its elastoplastic material properties. Results from simulations of cyclic behaviour during alternating and variable load histories are compared to expected macroscopic behaviour as further support to the applicability of the method to elastic-plastic problems.

Purpose of Review This paper assesses social science research relating to BECCS and considers the applicability of research on CCS to BECCS. Recent Findings In recent years, social science research on CCS and BECCS has gone beyond an evaluation of public acceptance to provide a more nuanced analysis of the wider social political, ethical, and governance contexts in which large-scale deployment might be achieved. This raises issues at global, local, and regional scales, requiring a wide array of methods and approaches. Summary Awareness of the scale and urgency needed to act on climate change is growing and the role of BECCS in delivering carbon dioxide removal forms a central argument for the use of this family of technologies. Here, framing becomes a critical factor in how society responds to BECCS technologies and we argue that making the case for BECCS as a means of extending mitigation to make a ‘net zero’ goal achievable could be the key to its acceptable and sustainable deployment.

A semi-submersible wind platform with four floats of equal diameter, damping plates and relatively small drafts has been designed to support a 5 MW wind turbine at full scale. Motion and mooring forces from wave basin measurements have been compared with time domain linear diffraction modelling accounting for drag forces, mooring forces and mean forces due to zero-difference frequency components, as is standard, and due to damping associated with radiation and drag forces, not previously considered. The platform response in the form of rms acceleration is quite well predicted although peak values can be underestimated. The mean mooring forces are underestimated and peak values are considerably underestimated. In large waves moorings experience high snatch loads. The measured mean forces were applied in the model for further comparison. The mooring was primarily designed to prevent drift of the floater and improved designs could eliminate or reduce snatch loads. However, it is shown that hub acceleration is quite moderate, with peak values less than 4 m/s2 in even the largest waves. The rms platform acceleration is largely decoupled from the mooring forces, as shown by corresponding spectra. In extreme conditions hydrodynamic mooring forces require nonlinear effects due to steep, sometimes breaking, waves to be accounted for. The wind thrust is included in the model using a coefficient from blade element momentum theory based on relative wind velocity. The peak hydrodynamic force would be significantly larger than the maximum wind thrust although the mean hydrodynamic force is significantly smaller. A practical conclusion is that a semi-sub floater with damping plates giving sufficiently low accelerations for operation in large waves may be of relatively shallow draft, less than the depths of many ports which is convenient for deployment.

This work describes a local approach to cleavage fracture (LAF) incorporating the statistics of microcracks to characterize the cleavage fracture toughness distribution in structural steels. Fracture toughness testing conducted on standard compact tension C(T) specimens for a 22NiMoCr37 pressure vessel steel provides the cleavage fracture resistance data needed to determine the measured toughness distribution. Metallographic examination of etched surfaces for the tested steel also provides the distribution of carbides, which are assumed as the Griffith fracture-initiating particles, dispersed in the material from which the cleavage fracture toughness distribution is predicted. Overall, the analyses conducted in the present work show that LAFs incorporating the statistics of microcracks are a viable engineering procedure to describe the dependence of fracture toughness on temperature in the DBT region for ferritic steels.

Graphite is a candidate material for Generation IV concepts and is used as a moderator in Advanced Gas-cooled Reactors (AGR) in the UK. Spatial material variability is present within billets causing different material property values between different components. Variations in material properties and irradiation effects can produce stress concentrations and diverse mechanical responses in a nuclear reactor graphite core. In order to characterise the material variability, geostatistical techniques called variography and random field theory were adapted for studying the density and Young's modulus of a billet of Gilsocarbon and NBG-18 graphite grades. Variography is a technique for estimating the distance over which material property values have significant spatial correlation, known as the scale of fluctuation or spatial correlation length. The paper uses random field theory to create models that mimic the original spatial and statistical distributions of the original data set. This study found different values of correlation length for density and Young's modulus around the edges of a Gilsocarbon billet, while in the case of NBG-18, similar correlation lengths where found across the billet. Examples of several random fields are given to reproduce the spatial patterns and values found in the original data.

The response and power capture of the multi-float wave energy converter M4 has been shown to be approximately predicted by linear diffraction-radiation modelling, giving relatively high capture widths. In this study we model a 6-float configuration which has been investigated experimentally in irregular waves and take account of the mooring system. Second-order mean forces are included due to excitation forces as is standard, but also due to the rate of energy extraction from mechanical damping and radiation damping resulting from body motion. There are also second order effects due to coupling between heave and surge. Operational conditions with mechanical damping and extreme conditions without mechanical damping (giving worst case response) are investigated. The motion is almost independent of mooring forces from a single point mooring, known as slack-moored. In operational conditions mean mooring forces are in approximate agreement with experiment except for larger periods and peak forces are similar. For extreme waves large rotational response is predicted reasonably by linear diffraction-radiation modelling with a small representative drag coefficient, as is horizontal acceleration, although peak values may be underestimated for the largest wave heights. However mean mooring forces are markedly underestimated and peak values generally overestimated. The overall conclusion is that linear modelling gives reasonable prediction of response in all wave conditions, and power capture when operational, but resulting second order mean forces only give approximate predictions for smaller wave heights.

Functional materials’ properties are influenced by microstructures which can be changed during manufacturing. A technique is presented which digitises graphite foam via X-ray tomography and converts it into image-based models to determine properties in silico. By simulating a laser flash analysis its effective thermal conductivity is predicted. Results show ~1 % error in the direction the foam was ‘grown’ during manufacturing but is significantly less accurate in plane due to effective thermal conductivity resulting from both the foam’s microstructure and graphite’s crystalline structure. An empirical relationship is found linking these by using a law of mixtures. A case study is presented demonstrating the technique’s use to simulate a heat exchanger component containing graphite foam with micro-scale accuracy using literature material properties for solid graphite. Compared against conventional finite element modelling there is no requirement to firstly experimentally measure the foam’s effective bulk properties. Additionally, improved local accuracy is achieved due to exact location of contact between the foam and other parts of the component. This capability will be of interest in design and manufacture of components using graphite materials. The software used was developed by the authors and is open source for others to undertake similar studies.

Two surface analysis techniques, dual polarization interferometry (DPI) and analysis by an electrochemical quartz crystal microbalance with dissipation capability (E-QCM-D), were paired to find the deposition conditions that give the highest and most stable electrocatalytic activity per adsorbed mass of enzyme. Layers were formed by adsorption from buffered solutions of bilirubin oxidase from Myrothecium verrucaria at pH 6.0 to planar surfaces, under high enzyme loading (≥1 mg mL(-1)) for contact periods of up to 2 min. Both unmodified and carboxylate-functionalized gold-coated sensors showed that a deposition solution concentration of 10-25 mg mL(-1) gave the highest activity per mass of adsorbed enzyme with an effective catalytic rate constant (k(cat)) of about 60 s(-1). The densification of adsorbed layers observed by DPI correlated with reduced bioactivity observed by parallel E-QCM-D measurements. Postadsorption changes in thickness and density observed by DPI were incorporated into Kelvin-Voigt models of the QCM-D response. The modeled response matched experimental observations when the adlayer viscosity tripled after adsorption.

Automatic sentiment analysis provides an effective way to gauge public opinion on any topic of interest. However, most sentiment analysis tools require a general sentiment lexicon to automatically classify sentiments or opinion in a text. One of the challenges presented by using a general sentiment lexicon is that it is insensitive to the domain since the scores assigned to the words are fixed. As a result, while one general sentiment lexicon might perform well in one domain, the same lexicon might perform poorly in another domain. Most sentiment lexica will need to be adjusted to suit the specific domain to which it is applied. In this paper, we present results of sentiment analysis expressed on Twitter by UK energy consumers. We optimised the accuracy of the sentiment analysis results by combining functions from two sentiment lexica. We used the first lexicon to extract the sentiment-bearing terms and negative sentiments since it performed well in detecting these. We then used a second lexicon to classify the rest of the data. Experimental results show that this method improved the accuracy of the results compared to the common practice of using only one lexicon.