Multilayered folding with voids

In the deformation of layered materials such as geological strata, or stacks of paper, mechanical properties compete with the geometry of layering. Smooth, rounded corners lead to voids between the layers, while close packing of the layers results in geometrically-induced curvature singularities. When voids are penalized by external pressure, the system is forced to trade off these competing effects, leading to sometimes striking periodic patterns. In this paper we construct a simple model of geometrically nonlinear multi-layered structures under axial loading and pressure confinement, with non-interpenetration conditions separating the layers. Energy minimizers are characterized as solutions of a set of fourth-order nonlinear differential equations with contact-force Lagrange multipliers, or equivalently of a fourth-order free-boundary problem. We numerically investigate the solutions of this free boundary problem, and compare them with the periodic solutions observed experimentally

Complexity in phase transforming pin-jointed auxetic lattices

This is the author accepted manuscript. The final version is available from The Royal Society via the DOI in this record.We demonstrate the complexity that can exist in the modelling of auxetic lattices. By introducing pin-jointed members and large deformations to the analysis of a re-entrant structure, we create a material which has both auxetic and non-auxetic phases. Such lattices exhibit complex equilibrium behaviour during the highly nonlinear transition between these two states. The local response is seen to switch many times between stable and unstable states, exhibiting both positive and negative stiffnesses. However, there is shown to exist an underlying emergent modulus over the transitional phase, to describe the average axial stiffness of a system comprising a large number of cells.Engineering and Physical Sciences Research Council (EPSRC

Operational Variables for improving industrial wind turbine Yaw Misalignment early fault detection capabilities using data-driven techniques

This is the author accepted manuscript. The final version is available from the Institute of Electrical and Electronics Engineers via the DOI in this recordOffshore wind turbines are complex pieces of engineering and are, generally, exposed to harsh environmental conditions that are making them to susceptible unexpected and potentially catastrophic damage. This results in significant down time, and high maintenance costs. Therefore, early detection of major failures is important to improve availability, boost power production and reduce maintenance costs. This paper proposes a SCADA data based Gaussian Process (GP) (a data-driven, machine learning approach) fault detection algorithm where additional model inputs, called operational variables (pitch angle and rotor speed) are used. Firstly, comparative studies of these operational variables are carried out to establish whether the parameter leads to improved early fault detection capability; it is then used to construct an improved GP fault detection algorithm. The developed model is then validated against existing methods in terms of capability to detect in advance (and by how much) signs of failure with a low false positive rate. Failure due to yaw misalignment results in significant down time and a reduction in power production was found to be a useful case study to demonstrate the effectiveness of the proposed algorithms. Historical SCADA 10-minute data obtained from pitch-regulated turbines were used for models training and validation purposes. Results show that (i) the additional model inputs were able to improve the accuracy of GP power curve models with rotor speed responsible for a significant improvement in performance; (ii) the inclusion of rotor speed enhanced early failure detection without any false positives, in contrast to the other methods investigated.U.S. Department of Commerc

A probabilistic peridynamic framework with an application to the study of the statistical size effect

This is the final version. Available from Elsevier via the DOI in this record. Data availability: No data was used for the research described in the article.The high computational expense of peridynamic models remains a major limitation, hindering ‘outer-loop’ applications that require a large number of simulations, for example, uncertainty quantification. This contribution presents a framework that makes such computations feasible. By employing a Multilevel Monte Carlo framework, where the majority of simulations are performed using a coarse mesh, and performing relatively few simulations using a fine mesh, a significant reduction in computational cost can be realised, and statistics of structural failure can be estimated. The maximum observed speed-up factor is 16 when compared to a standard Monte Carlo estimator, thus enabling the efficient forward propagation of uncertain parameters in a computationally expensive peridynamic model. Furthermore, the multilevel method provides an estimate of both the discretisation error and sampling error, thereby improving confidence in numerical predictions. The performance of the approach is demonstrated through an examination of the statistical size effect in quasi-brittle materials.Turing Fellowshi

Shared understanding in psychiatrist–patient communication: Association with treatment adherence in schizophrenia

Objective Effective doctor–patient communication, including a shared understanding, is associated with treatment adherence across medicine. However, communication is affected by a diagnosis of schizophrenia and reaching a shared understanding can be challenging. During conversation, people detect and deal with possible misunderstanding using a conversational process called repair. This study tested the hypothesis that more frequent repair in psychiatrist–patient communication is associated with better treatment adherence in schizophrenia. Methods Routine psychiatric consultations involving patients with (DSM-IV) schizophrenia or schizoaffective disorder were audio-visually recorded. Consultations were coded for repair and patients’ symptoms and insight assessed. Adherence was assessed six months later. A principal components analysis reduced the repair data for further analysis. Random effects models examined the association between repair and adherence, adjusting for symptoms, consultation length and the amount patients spoke. Results 138 consultations were recorded, 118 were followed up. Patients requesting clarification of the psychiatrist's talk and the clarification provided by the psychiatrist was associated with adherence six months later (OR 5.82, 95% CI 1.31–25.82, p = 0.02). Conclusion The quality of doctor–patient communication also appears to influence adherence in schizophrenia. Practice implications Future research should investigate how patient clarification can be encouraged among patients and facilitated by psychiatrists’ communication