Numerical simulation of a patent technology for sealing of deep-sea oil wells using nonlinear finite element method

For over 50 years bridge plugs and cement have been used for well abandonment and work over and are still the material of choice. However the failures of cement abandonments using bridge plugs has been reported on many occasions, some of which have resulted in fatal consequences. A new patented product is designed to address the shortcomings associated with using bridge plugs and cement. The new developed tools use an alloy based on bismuth that is melted in situ using Thermite reaction. The tool uses the expansion properties of bismuth to seal the well. Testing the new technology in real field under more than 2 km deep sea water can be expensive. Virtual simulation of the new device under simulated thermal and mechanical environment can be achieved using nonlinear finite element method to validate the product and reduce cost. Experimental testing in the lab is performed to measure heat generated due to thermite reaction. Then, a sequential thermal mechanical explicit/implicit finite element solver is used to simulate the device under both testing lab and deep water conditions.

Application of a mechanobiological simulation technique to stents used clinically

Many cardiovascular diseases are characterised by the restriction of blood flow through arteries. Stents can be expanded within arteries to remove such restrictions; however, tissue in-growth into the stent can lead to restenosis. In order to predict the long-term efficacy of stenting, a mechanobiological model of the arterial tissue reaction to stress is required. In this study, a computational model of arterial tissue response to stenting is applied to three clinically relevant stent designs. We ask the question whether such a mechanobiological model can differentiate between stents used clinically, and we compare these predictions to a purely mechanical analysis. In doing so, we are testing the hypothesis that a mechanobiological model of arterial tissue response to injury could predict the long-term outcomes of stent design. Finite element analysis of the expansion of three different stent types was performed in an idealised, 3D artery. Injury was calculated in the arterial tissue using a remaining-life damage mechanics approach. The inflammatory response to this initial injury was modelled using equations governing variables which represented tissue-degrading species and growth factors. Three levels of inflammation response were modelled to account for inter-patient variability. A lattice-based model of smooth muscle cell behaviour was implemented, treating cells as discrete agents governed by local rules. The simulations predicted differences between stent designs similar to those found in vivo. It showed that the volume of neointima produced could be quantified, providing a quantitative comparison of stents. In contrast, the differences between stents based on stress alone were highly dependent on the choice of comparison criteria. These results show that the choice of stress criteria for stent comparisons is critical. This study shows that mechanobiological modelling may provide a valuable tool in stent design, allowing predictions of their long-term efficacy. The level of inflammation was shown to affect the sensitivity of the model to stent design. If this finding was verified in patients, this could suggest that high-inflammation patients may require alternative treatments to stenting.

The p-hub Model with Hub-catchment Areas, Existing Hubs, and Simulation: A Case Study of Serbian Intermodal Terminals

This paper addresses the problem of optimally locating intermodal freight terminals in Serbia. To solve this problem and determine the effects of the resulting scenarios, two modeling approaches were combined. The first approach is based on multiple-assignment hub-network design, and the second is based on simulation. The multiple-assignment p-hub network location model was used to determine the optimal location of intermodal terminals. Simulation was used as a tool to estimate intermodal transport flow volumes, due to the unreliability and unavailability of specific statistical data, and as a method for quantitatively analyzing the economic, time, and environmental effects of different scenarios of intermodal terminal development. The results presented here represent a summary, with some extension, of the research realized in the IMOD-X project (Intermodal Solutions for Competitive Transport in Serbia).

Monte Carlo simulation of complex cohesive fracture in random heterogeneous quasi-brittle materials

A numerical method is developed to simulate complex two-dimensional crack propagation in quasi-brittle materials considering random heterogeneous fracture properties. Potential cracks are represented by pre-inserted cohesive elements with tension and shear softening constitutive laws modelled by spatially varying Weibull random fields. Monte Carlo simulations of a concrete specimen under uni-axial tension were carried out with extensive investigation of the effects of important numerical algorithms and material properties on numerical efficiency and stability, crack propagation processes and load-carrying capacities. It was found that the homogeneous model led to incorrect crack patterns and load–displacement curves with strong mesh-dependence, whereas the heterogeneous model predicted realistic, complicated fracture processes and load-carrying capacity of little mesh-dependence. Increasing the variance of the tensile strength random fields with increased heterogeneity led to reduction in the mean peak load and increase in the standard deviation. The developed method provides a simple but effective tool for assessment of structural reliability and calculation of characteristic material strength for structural design.

Diamond machining of silicon: A review of advances in molecular dynamics simulation

Molecular dynamics (MD) simulation has enhanced our understanding about ductile-regime machining of brittle materials such as silicon and germanium. In particular, MD simulation has helped understand the occurrence of brittle–ductile transition due to the high-pressure phase transformation (HPPT), which induces Herzfeld–Mott transition. In this paper, relevant MD simulation studies in conjunction with experimental studies are reviewed with a focus on (i) the importance of machining variables: undeformed chip thickness, feed rate, depth of cut, geometry of the cutting tool in influencing the state of the deviatoric stresses to cause HPPT in silicon, (ii) the influence of material properties: role of fracture toughness and hardness, crystal structure and anisotropy of the material, and (iii) phenomenological understanding of the wear of diamond cutting tools, which are all non-trivial for cost-effective manufacturing of silicon. The ongoing developmental work on potential energy functions is reviewed to identify opportunities for overcoming the current limitations of MD simulations. Potential research areas relating to how MD simulation might help improve existing manufacturing technologies are identified which may be of particular interest to early stage researchers.

The prediction of process-induced deformation in a thermoplastic composite in support of manufacturing simulation

Digital manufacturing techniques can simulate complex assembly sequences using computer-aided design-based, as-designed' part forms, and their utility has been proven across several manufacturing sectors including the ship building, automotive and aerospace industries. However, the reality of working with actual parts and composite components, in particular, is that geometric variability arising from part forming or processing conditions can cause problems during assembly as the as-manufactured' form differs from the geometry used for any simulated build validation. In this work, a simulation strategy is presented for the study of the process-induced deformation behaviour of a 90 degrees, V-shaped angle. Test samples were thermoformed using pre-consolidated carbon fibre-reinforced polyphenylene sulphide, and the processing conditions were re-created in a virtual environment using the finite element method to determine finished component angles. A procedure was then developed for transferring predicted part forms from the finite element outputs to a digital manufacturing platform for the purpose of virtual assembly validation using more realistic part geometry. Ultimately, the outcomes from this work can be used to inform process condition choices, material configuration and tool design, so that the dimensional gap between as-designed' and as-manufactured' part forms can be reduced in the virtual environment.

Implementation of a non-orthogonal model for the finite element simulation of textile composite draping

In the pursuit of producing high quality, low-cost composite aircraft structures, out-of-autoclave manufacturing processes for textile reinforcements are being simulated with increasing accuracy. This paper focuses on the continuum-based, finite element modelling of textile composites as they deform during the draping process. A non-orthogonal constitutive model tracks yarn orientations within a material subroutine developed for Abaqus/Explicit, resulting in the realistic determination of fabric shearing and material draw-in. Supplementary material characterisation was experimentally performed in order to define the tensile and non-linear shear behaviour accurately. The validity of the finite element model has been studied through comparison with similar research in the field and the experimental lay-up of carbon fibre textile reinforcement over a tool with double curvature geometry, showing good agreement.

Influence of temperature on the anisotropic cutting behaviour of single crystal silicon: A molecular dynamics simulation investigation

Using molecular dynamics (MD) simulation, this paper investigates anisotropic cutting behaviour of single crystal silicon in vacuum under a wide range of substrate temperatures (300 K, 500 K, 750 K, 850 K, 1173 K and 1500 K). Specific cutting energy, force ratio, stress in the cutting zone and cutting temperature were the indicators used to quantify the differences in the cutting behaviour of silicon. A key observation was that the specific cutting energy required to cut the (111) surface of silicon and the von Mises stress to yield the silicon reduces by 25% and 32%, respectively, at 1173 K compared to what is required at 300 K. The room temperature cutting anisotropy in the von Mises stress and the room temperature cutting anisotropy in the specific cutting energy (work done by the tool in removing unit volume of material) were obtained as 12% and 16% respectively. It was observed that this changes to 20% and 40%, respectively, when cutting was performed at 1500 K, signifying a very strong correlation between the anisotropy observed during cutting and the machining temperature. Furthermore, using the atomic strain criterion, the width of primary shear zone was found to vary with the orientation of workpiece surface and temperature i.e. it remains narrower while cutting the (111) surface of silicon or at higher machining temperatures. A major anecdote of the study based on the potential function employed in the study is that, irrespective of the cutting plane or the cutting temperature, the state of the cutting edge of the diamond tool did not show direct diamond to graphitic phase transformation.

Low Fidelity Simulation as a Mechanism to Enhance Midwifery Students’ Confidence in Relation to Emergency Obstetric Training

Simulation offers a safe opportunity for students to practice clinical procedures without exposure and risk of harm to real patients (Partin et al, 2011). Simulation is recognised to increase students’ confidence in their ability to make critical decisions (McCaughey and Traynor, 2010). Within Queen’s University Belfast, simulation for obstetric emergency training based on the ethos of ‘Practical Obstetric Multi-Professional Training[PROMPT]’ (Draycott et al, 2008) has been developed for midwifery students and is now uniquely embedded within the pre-registration curriculum. An important aspect of the PROMPT training is the use of low fidelity simulation as opposed to high tech support (Crofts et al, 2008). Studies have reflected that low fidelity simulation can be an effective tool for promoting student confidence (Tosterud, 2013; Hughes et al, 2013). Students are given the opportunity to experience obstetric emergencies within a safe environment and evaluation has indicated that students feel safe and have an increase in confidence and self-efficacy. The immediacy of the feedback offered by simulated situations encourages an exploration of beliefs and attitudes, particularly with peers, promoting a deeper sense of learning (Stoneham and Feltham, 2009).This paper will discuss why low fidelity simulation can effectively enhance the student experience and promote self-efficacy.

Molecular dynamics simulation (MDS) to study nanoscale machining processes

Molecular Dynamics Simulations (MDS) are constantly being used to make important contributions to our fundamental understanding of material behaviour, at the atomic scale, for a variety of thermodynamic processes. This chapter shows that molecular dynamics simulation is a robust numerical analysis tool in addressing a range of complex nanofinishing (machining) problems that are otherwise difficult or impossible to understand using other methods. For example the mechanism of nanometric cutting of silicon carbide is influenced by a number of variables such as machine tool performance, machining conditions, material properties, and cutting tool performance (material microstructure and physical geometry of the contact) and all these variables cannot be monitored online through experimental examination. However, these could suitably be studied using an advanced simulation based approach such as MDS. This chapter details how MD simulation can be used as a research and commercial tool to understand key issues of ultra precision manufacturing research problems and a specific case was addressed by studying diamond machining of silicon carbide. While this is appreciable, there are a lot of challenges and opportunities in this fertile area. For example, the world of MD simulations is dependent on present day computers and the accuracy and reliability of potential energy functions [109]. This presents a limitation: Real-world scale simulation models are yet to be developed. The simulated length and timescales are far shorter than the experimental ones which couples further with the fact that contact loading simulations are typically done in the speed range of a few hundreds of m/sec against the experimental speed of typically about 1 m/sec [17]. Consequently, MD simulations suffer from the spurious effects of high cutting speeds and the accuracy of the simulation results has yet to be fully explored. The development of user-friendly software could help facilitate molecular dynamics as an integral part of computer-aided design and manufacturing to tackle a range of machining problems from all perspectives, including materials science (phase of the material formed due to the sub-surface deformation layer), electronics and optics (properties of the finished machined surface due to the metallurgical transformation in comparison to the bulk material), and mechanical engineering (extent of residual stresses in the machined component) [110]. Overall, this chapter provided key information concerning diamond machining of SiC which is classed as hard, brittle material. From the analysis presented in the earlier sections, MD simulation has helped in understanding the effects of crystal anisotropy in nanometric cutting of 3C-SiC by revealing the atomic-level deformation mechanisms for different crystal orientations and cutting directions. In addition to this, the MD simulation revealed that the material removal mechanism on the (111) surface of 3C-SiC (akin to diamond) is dominated by cleavage. These understandings led to the development of a new approach named the “surface defect machining” method which has the potential to be more effective to implement than ductile mode micro laser assisted machining or conventional nanometric cutting.

Molecular dynamics simulation investigation on the plastic flow behaviour of silicon during nanometric cutting

Molecular dynamics (MD) simulation was carried out to acquire an in-depth understanding of the flow behaviour of single crystal silicon during nanometric cutting on three principal crystallographic planes and at different cutting temperatures. The key findings were that (i) the substrate material underneath the cutting tool was observed for the first time to experience a rotational flow akin to fluids at all the tested temperatures up to 1200 K. (ii) The degree of flow in terms of vorticity was found higher on the (1 1 1) crystal plane signifying better machinability on this orientation in accord with the current pool of knowledge (iii) an increase in the machining temperature reduces the springback effect and thereby the elastic recovery and (iv) the cutting orientation and the cutting temperature showed significant dependence on the location of the stagnation region in the cutting zone of the substrate.

3D FEM simulation of helical milling hole process for titanium alloy Ti-6Al-4V

As an emerging hole-machining methodology, helical milling process has become increasingly popular in aeromaterials manufacturing research, especially in areas of aircraft structural parts, dies, and molds manufacturing. Helical milling process is highly demanding due to its complex tool geometry and the progressive material failure on the workpiece. This paper outlines the development of a 3D finite element model for helical milling hole of titanium alloy Ti-6Al-4V using commercial FE code ABAQUS/Explicit. The proposed model simulates the helical milling hole process by taking into account the damage initiation and evolution in the workpiece material. A contact model at the interface between end-mill bit and workpiece has been established and the process parameters specified. Furthermore, a simulation procedure is proposed to simulate different cutting processes with the same failure parameters. With this finite element model, a series of FEAs for machined titanium alloy have been carried out and results compared with laboratory experimental data. The effects of machining parameters on helical milling have been elucidated, and the capability and advantage of FE simulation on helical milling process have been well presented.

An Automated Design Framework for Assembly Task Simulation

This paper presents an automated design framework for the development of individual part forming tools for a composite stiffener. The framework uses parametrically developed design geometries for both the part and its layup tool. The framework has been developed with a functioning user interface where part / tool combinations are passed to a virtual environment for utility based assessment of their features and assemblability characteristics. The work demonstrates clear benefits in process design methods with conventional design timelines reduced from hours and days to minutes and seconds. The methods developed here were able to produce a digital mock up of a component with its associated layup tool in less than 3 minutes. The virtual environment presenting the design to the designer for interactive assembly planning was generated in 20 seconds. Challenges still exist in determining the level of reality required to provide an effective learning environment in the virtual world. Full representation of physical phenomena such as gravity, part clashes and the representation of standard build functions require further work to represent real physical phenomena more accurately.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.