Design and Analysis of Experiments on Nonconvex Regions

Modeling a response over a nonconvex design region is a common problem in diverse areas such as engineering and geophysics. The tools available to model and design for such responses are limited and have received little attention. We propose a new method for selecting design points over nonconvex regions that is based on the application of multidimensional scaling to the geodesic distance. Optimal designs for prediction are described, with special emphasis on Gaussian process models, followed by a simulation study and an application in glaciology. Supplementary materials for this article are available online.     

The design and assessment of bio-inspired additive manufactured stab-resistant armour

The performance of modern fibre-based or polycarbonate armour has significantly improved since their introduction, providing protection against a range of low- and high-velocity threats. While this is so, users of such armour frequently report of issues relating to their operational suitability resulting in impaired performance and physiological effects. Recently, researchers have focused on how naturally occurring protective mechanisms could be utilised to enhance the protective and operational performance of wearers of engineered body armour. The research presented within this paper therefore utilises a series of key design characteristics exhibited within naturally occurring elasmoid scale armour, coupled with established laser sintering manufacturing parameters, for the realisation and assessment of a scale-based stab-resistant armoured structure to internationally recognised test standards.     

Eurocorr 2016: linking science and engineering – part 4

The 2016 Eurocorr Meeting was held in Montpellier, France, from 12 to 15 September 2016. The focus of the meeting was Linking Science and Engineering. The meeting attracted over 1000 delegates from at least 53 countries with France, Germany, the UK and Japan providing around half the delegates between them. Over 400 oral presentations, more than 200 of which were full papers, and over 140 posters were presented during the sessions and workshops. Parts 1–4 of this report present a review of the technical sessions over four issues with sessions on Advanced Analytical Methods for Corrosion Research, CO₂-Corrosion in Industrial Capture Transportation and Utilisation Applications, Cathodic Protection of Steel in Concrete, Coatings for High Temperature, Corrosion Education, Improving Corrosion Control of Ships, Marine Corrosion, Corrosion Issues for Renewable Energies, Nuclear Corrosion, and Nuclear Corrosion Mechanisms being covered in this report.     

A physics informed emulator for laser-driven radiating shock simulations

This work discusses the uncertainty quantification aspect of quantification of margin and uncertainty (QMU) in the context of two linked computer codes. Specifically, we present a physics based reduction technique to deal with functional data from the first code and then develop an emulator for this reduced data. Our particular application deals with conditions created by laser deposition in a radiating shock experiment modeled using the Lagrangian, radiation-hydrodynamics code Hyades. Our goal is to construct an emulator and perform a sensitivity analysis of the functional output from Hyades to be used as an initial condition for a three-dimensional code that will compute the evolution of the radiating shock at later times. Initial attempts at purely statistical data reduction techniques, were not successful at reducing the number of parameters required to describe the Hyades output. We decided on an alternate approach using physical arguments to decide what features/locations of the output were relevant (e.g., the location of the shock front or the location of the maximum pressure) and then used a piecewise linear fit between these locations. This reduced the number of outputs needed from the emulator to 40, down from the O(1000) points in the Hyades output. Then, using Bayesian MARS and Gaussian process regression, we were able to build emulators for Hyades and study sensitivities to input parameters.