GPU accelerated MCMC for modelling terrorist activity

The use of graphical processing unit (GPU) parallel processing is becoming a part of mainstream statistical practice. The reliance of Bayesian statistics on Markov Chain Monte Carlo (MCMC) methods makes the applicability of parallel processing not immediately obvious. It is illustrated that there are substantial gains in improved computational time for MCMC and other methods of evaluation by computing the likelihood using GPU parallel processing. Examples use data from the Global Terrorism Database to model terrorist activity in Colombia from 2000 through 2010 and a likelihood based on the explicit convolution of two negative-binomial processes. Results show decreases in computational time by a factor of over 200. Factors influencing these improvements and guidelines for programming parallel implementations of the likelihood are discussed.

Sub-modelling for the ratchetting failure of insulated rail joints

Insulated rail joints are critical for train safety as they control electrical signalling systems; unfortunately they exhibit excessive ratchetting of the railhead near the endpost insulators. This paper reports a three-dimensional global model of these joints under wheel–rail contact pressure loading and a sub-model examining the ratchetting failures of the railhead. The sub-model employs a non-linear isotropic–kinematic elastic–plastic material model and predicts stress/strain levels in the localised railhead zone adjacent to the endpost which is placed in the air gap between the two rail ends at the insulated rail joint. The equivalent plastic strain plot is utilised to capture the progressive railhead damage adequately. Associated field and laboratory testing results of damage to the railhead material suggest that the simulation results are reasonable.

Structural and material characterisation of insulated rail joints

Insulated rail joints are designed in a similar way to butt jointed steel structural systems, the difference being a purpose made gap between the main rail members to maintain electrical insulation for the proper functioning of the track circuitry at all times of train operation. When loaded wheels pass the gap, they induce an impact loading with the corresponding strains in the railhead edges exceeding the plastic limit significantly, which lead to metal flow across the gap thereby increasing the risk of short circuiting and impeding the proper functioning of the signalling and broken rail identification circuitries, of which the joints are a critical part. The performance of insulated rail joints under the passage of the wheel loading is complex due to the presence of a number of interacting components and hence is not well understood. This paper presents a dynamic wheel-rail contact-impact modelling method for the determination of the impact loading; a brief description of a field experiment to capture strain signatures for validating the predicted impact loading is also presented. The process and the results of the characterisation of the materials from virgin, in-service and damaged insulated rail joints using neutron diffraction method are also discussed.

Mapping, monitoring, and modelling of hazardous waste sites

Management of the industrial nations' hazardous waste is a current and exponentially increasing, global threatening situation. Improved environmental information must be obtained and managed concerning the current status, temporal dynamics and potential future status of these critical sites. To test the application of spatial environmental techniques to the problem of hazardous waste sites, as Superfund (CERCLA) test site was chosen in an industrial/urban valley experiencing severe TCE, PCE, and CTC ground water contamination. A paradigm is presented for investigating spatial/environmental tools available for the mapping, monitoring and modelling of the environment and its toxic contaminated plumes. This model incorporates a range of technical issues concerning the collection of data as augmented by remotely sensed tools, the format and storage of data utilizing geographic information systems, and the analysis and modelling of environment through the use of advance GIS analysis algorithms and geophysic models of hydrologic transport including statistical surface generation. This spatial based approach is evaluated against the current government/industry standards of operations. Advantages and lessons learned of the spatial approach are discussed.

Eigenstrain boundary integral equations with local Eshelby matrix for stress analysis of ellipsoidal particles

Aiming at the large scale numerical simulation of particle reinforced materials, the concept of local Eshelby matrix has been introduced into the computational model of the eigenstrain boundary integral equation (BIE) to solve the problem of interactions among particles. The local Eshelby matrix can be considered as an extension of the concepts of Eshelby tensor and the equivalent inclusion in numerical form. Taking the subdomain boundary element method as the control, three-dimensional stress analyses are carried out for some ellipsoidal particles in full space with the proposed computational model. Through the numerical examples, it is verified not only the correctness and feasibility but also the high efficiency of the present model with the corresponding solution procedure, showing the potential of solving the problem of large scale numerical simulation of particle reinforced materials.

Two-scale computational modelling of unsaturated flow in soils exhibiting small scale heterogeneities

Unsaturated water flow in soil is commonly modelled using Richards’ equation, which requires the hydraulic properties of the soil (e.g., porosity, hydraulic conductivity, etc.) to be characterised. Naturally occurring soils, however, are heterogeneous in nature, that is, they are composed of a number of interwoven homogeneous soils each with their own set of hydraulic properties. When the length scale of these soil heterogeneities is small, numerical solution of Richards’ equation is computationally impractical due to the immense effort and refinement required to mesh the actual heterogeneous geometry. A classic way forward is to use a macroscopic model, where the heterogeneous medium is replaced with a fictitious homogeneous medium, which attempts to give the average flow behaviour at the macroscopic scale (i.e., at a scale much larger than the scale of the heterogeneities). Using the homogenisation theory, a macroscopic equation can be derived that takes the form of Richards’ equation with effective parameters. A disadvantage of the macroscopic approach, however, is that it fails in cases when the assumption of local equilibrium does not hold. This limitation has seen the introduction of two-scale models that include at each point in the macroscopic domain an additional flow equation at the scale of the heterogeneities (microscopic scale). This report outlines a well-known two-scale model and contributes to the literature a number of important advances in its numerical implementation. These include the use of an unstructured control volume finite element method and image-based meshing techniques, that allow for irregular micro-scale geometries to be treated, and the use of an exponential time integration scheme that permits both scales to be resolved simultaneously in a completely coupled manner. Numerical comparisons against a classical macroscopic model confirm that only the two-scale model correctly captures the important features of the flow for a range of parameter values.

Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware

Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

Numerical modelling of an imping jet

Impinging flow occurs when a fluid impacts a comparatively solid boundary upon which divergence occurs. A perfect example of an impinging flow is the impact and divergence of air at ground level during a thunderstorm outflow. The importance of modelling thunderstorm outflows, and in particular the downburst is now well-known to the wind engineering community and research into many of its characteristics is underway throughout the world. The reader is directed to the text by Fujita [I] for an introduction to downburst concepts and theory.

CFD and experimental modelling of an impinging jet for thunderstorm downburst simulation

A thunderstorm downburst in its simplest form can be modelled as a steady flow impinging air jet. Although this simplification neglects some important atmospheric and physical parameters it has proven to be a useful tool for understanding the kinematics of these events. Assuming this simple impinging jet model also allows numerical models to be developed which can be directly compared with experimental results to validate the use of CFD. Confidence gained from these simulations will allow the use of more complex atmospheric impinging jet models that cannot be directly validated. Thunderstorm downbursts are important for wind engineers because in many parts of the world they produce the design wind speeds used in design standards, but are not structurally represented in these documents.

Numerical modelling and analysis of the blast performance of laminated glass panels and the influence of material parameters

This paper presents a comprehensive numerical procedure to treat the blast response of laminated glass (LG) panels and studies the influence of important material parameters. Post-crack behaviour of the LG panel and the contribution of the interlayer towards blast resistance are treated. Modelling techniques are validated by comparing with existing experimental results. Findings indicate that the tensile strength of glass considerably influences the blast response of LG panels while the interlayer material properties have a major impact on the response under higher blast loads. Initially, glass panes absorb most of the blast energy, but after the glass breaks, interlayer deforms further and absorbs most of the blast energy. LG panels should be designed to fail by tearing of the interlayer rather than failure at the supports to achieve a desired level of protection. From this aspect, material properties of glass, interlayer and sealant joints play important roles, but unfortunately they are not accounted for in the current design standards. The new information generated in this paper will enhance the capabilities of engineers to better design LG panels under blast loads and use better materials to improve the blast response of LG panels.

A coupled SPH-DEM model for micro-scale structural deformations of plant cells during drying

A single plant cell was modeled with smoothed particle hydrodynamics (SPH) and a discrete element method (DEM) to study the basic micromechanics that govern the cellular structural deformations during drying. This two-dimensional particle-based model consists of two components: a cell fluid model and a cell wall model. The cell fluid was approximated to a highly viscous Newtonian fluid and modeled with SPH. The cell wall was treated as a stiff semi-permeable solid membrane with visco-elastic properties and modeled as a neo-Hookean solid material using a DEM. Compared to existing meshfree particle-based plant cell models, we have specifically introduced cell wall–fluid attraction forces and cell wall bending stiffness effects to address the critical shrinkage characteristics of the plant cells during drying. Also, a moisture domain-based novel approach was used to simulate drying mechanisms within the particle scheme. The model performance was found to be mainly influenced by the particle resolution, initial gap between the outermost fluid particles and wall particles and number of particles in the SPH influence domain. A higher order smoothing kernel was used with adaptive smoothing length to improve the stability and accuracy of the model. Cell deformations at different states of cell dryness were qualitatively and quantitatively compared with microscopic experimental findings on apple cells and a fairly good agreement was observed with some exceptions. The wall–fluid attraction forces and cell wall bending stiffness were found to be significantly improving the model predictions. A detailed sensitivity analysis was also done to further investigate the influence of wall–fluid attraction forces, cell wall bending stiffness, cell wall stiffness and the particle resolution. This novel meshfree based modeling approach is highly applicable for cellular level deformation studies of plant food materials during drying, which characterize large deformations.

Modelling of a magnetocaloric system for cooling in the kilowatt range

A numerical time-dependent model of an active magnetic regenerator (AMR) was developed for cooling in the kilowatt range. Earlier numerical models have been mostly developed for cooling power in the 0.4 kW range. In contrast, this paper reports the applicability of magnetic refrigeration to the 50 kW range. A packed bed active magnetic regenerator was modelled and the influence of parameters such as geometry and operating parameters were studied for different geometries. The pressure drop for AMR bed length and particle diameter was also studied. High cooling power and coefficient of performance (COP) were achieved by optimization of the diameter of the magnetocaloric powder particles and operating frequency. The optimum operating conditions of the AMR for a cooling capacity of 50 kW was determined for a temperature span of 15 K. The predicted coefficient of performance (COP) was found to be ∼6, making it an attractive alternative to vapour compression systems.

Engineering the mechanical properties of graphene nanotube hybrid structures through structural modulation

The excellent multi-functional properties of carbon nanotube (CNT) and graphene have enabled them as appealing building blocks to construct 3D carbon-based nanomaterials or nanostructures. The recently reported graphene nanotube hybrid structure (GNHS) is one of the representatives of such nanostructures. This work investigated the relationships between the mechanical properties of the GNHS and its structure basing on large-scale molecular dynamics simulations. It is found that increasing the length of the constituent CNTs, the GNHS will have a higher Young’s modulus and yield strength. Whereas, no strong correlation is found between the number of graphene layers and Young’s modulus and yield strength, though more graphene layers intends to lead to a higher yield strain. In the meanwhile, the presences of multi-wall CNTs are found to greatly strengthen the hybrid structure. Generally, the hybrid structures exhibit a brittle behavior and the failure initiates from the connecting regions between CNT and graphene. More interestingly, affluent formations of monoatomic chains and rings are found at the fracture region. This study provides an in-depth understanding of the mechanical performance of the GNHSs while varying their structures, which will shed lights on the design and also the applications of the carbon-based nanostructures.

Assessing uncertainty in pollutant wash-off modelling via model validation

Stormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.

Three-dimensional off-design numerical analysis of an organic Rankine cycle radial-inflow turbine

Optimisation of organic Rankine cycles(ORCs for binary cycle applications could play a major role in determining the competitiveness of low to moderate renewable sources. An important aspect of the optimisation is to maximise the turbine output power for a given resource. This requires careful attention to the turbine design notably through numerical simulations. Challenges in the numerical modelling of radial-inflow turbines using high-density working fluids still need to be addressed in order to improve the turbine design and better optimise ORCs. Thispaper presents preliminary 3D numerical simulations of a high-density radial-inflow ORC turbine in sensible geothermal conditions. Following extensive investigation of the operating conditions and thermodynamic cycle analysis, therefrigerant R143a is chosen as the high-density working fluid. The 1D design of the candidate radial-inflow turbine is presented in details. Furthermore, commercially-available software Ansys-CFX is used to perform preliminary steady-state 3D CFD simulations of the candidate R143a radial-inflow turbine for a number of operating conditions including off-design conditions. The real-gas properties are obtained using the Peng–Robinson equations of state.The thermodynamic ORC cycle is presented. The preliminary design created using dedicated radial-inflow turbine software Concepts-Rital is discussed and the 3D CFD results are presented and compared against the meanline analysis.