Molecular dynamics simulation of nanoindentation of Fe3C and tetrahedral Fe4C

Study of nanomechanical response of iron carbides is important because presence of iron carbides greatly influences the performance and longevity of steel components. This work contributes to the literature by exploring nanoindentation of nanocrystalline Fe3C and tetrahedral-Fe4C using molecular dynamics simulation. The chemical interactions of iron and carbon were described through an analytical bond order inter-atomic potential (ABOP) energy function. The indentations were performed at an indentation speed of 50 m/sec and a repeat trial was performed at 5 m/sec. Load-displacement (P-h) curve for both these carbides showed residual indentation depth and maximum indentation depth (hf/hmax) ratio to be higher than 0.7 i.e. a circumstance where Oliver and Pharr method was not appropriate to be applied to evaluate the material properties. Alternate evaluation revealed Fe3C to be much harder than Fe4C. Gibbs free energy of formation and radial distribution function, coupled with state of the average local temperature and von Mises stresses indicate the formation of a new phase of iron-carbide. Formation of this newer phase was found to be due to deviatoric strain rather than the high temperature induced in the substrate during nanoindentation

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.

Engineering plasmonic nanorod arrays for colon cancer marker detection

Engineering plasmonic nanomaterials or nanostructures towards ultrasensitive biosensing for disease markers or pathogens is of high importance. Here we demonstrate a systematic approach to tailor effective plasmonic nanorod arrays by combining both comprehensive numerical discrete dipole approximations (DDA) simulation and transmission spectroscopy experiments. The results indicate that 200×50 nm nanorod arrays with 300×500 nm period provide the highest FOM of 2.4 and a sensitivity of 310 nm/RIU. Furthermore, we demonstrate the use of nanorod arrays for the detection of single nucleotide polymorphism in codon 12 of the K-ras gene that are frequently occurring in early stages of colon cancer, with a sensitivity down to 10 nM in the presence of 100-fold higher concentration of the homozygous genotypes. Our work shows significant potential of nanorod arrays towards point-of-care applications in diagnosis and clinical studies.

Experimental linear-optics simulation of multipartite non-locality in the ground state of a quantum Ising ring

Critical phenomena involve structural changes in the correlations of its constituents. Such changes can be reproduced and characterized in quantum simulators able to tackle medium-to-large-size systems. We demonstrate these concepts by engineering the ground state of a three-spin Ising ring by using a pair of entangled photons. The effect of a simulated magnetic field, leading to a critical modification of the correlations within the ring, is analysed by studying two- and three-spin entanglement. In particular, we connect the violation of a multipartite Bell inequality with the amount of tripartite entanglement in our ring.

Calibrated CFD simulation to evaluate thermal comfort in a highly-glazed naturally ventilated room

Natural ventilation is a sustainable solution to maintaining healthy and comfortable environmental conditions in buildings. However, the effective design, construction and operation of naturally ventilated buildings require a good understanding of complex airflow patterns caused by the buoyancy and wind effects.The work presented in this article employed a 3D computational fluid dynamics (CFD) analysis in order to investigate environmental conditions and thermal comfort of the occupants of a highly-glazed naturally ventilated meeting room. This analysis was facilitated by the real-time field measurements performed in an operating building, and previously developed formal calibration methodology for reliable CFD models of indoor environments. Since, creating an accurate CFD model of an occupied space in a real-life scenario requires a high level of CFD expertise, trusted experimental data and an ability to interpret model input parameters; the calibration methodology guided towards a robust and reliable CFD model of the indoor environment. This calibrated CFD model was then used to investigate indoor environmental conditions and to evaluate thermal comfort indices for the occupants of the room. Thermal comfort expresses occupants' satisfaction with thermal environment in buildings by defining the range of indoor thermal environmental conditions acceptable to a majority of occupants. In this study, the thermal comfort analysis, supported by both field measurements and CFD simulation results, confirmed a satisfactory and optimal room operation in terms of thermal environment for the investigated real-life scenario. © 2013 Elsevier Ltd.

Process simulation of co-firing torrefied biomass in a 220 MWe coal-fired power plant

Torrefaction based co-firing in a pulverized coal boiler has been proposed for large percentage of biomass co-firing. A 220 MWe pulverized coal-power plant is simulated using Aspen Plus for full understanding the impacts of an additional torrefaction unit on the efficiency of the whole power plant, the studied process includes biomass drying, biomass torrefaction, mill systems, biomass/coal devolatilization and combustion, heat exchanges and power generation. Palm kernel shells (PKS) were torrefied at same residence time but 4 different temperatures, to prepare 4 torrefied biomasses with different degrees of torrefaction. During biomass torrefaction processes, the mass loss properties and released gaseous components have been studied. In addition, process simulations at varying torrefaction degrees and biomass co-firing ratios have been carried out to understand the properties of CO₂ emission and electricity efficiency in the studied torrefaction based co-firing power plant. According to the experimental results, the mole fractions of CO ₂ and CO account for 69-91% and 4-27% in torrefied gases. The predicted results also showed that the electrical efficiency reduced when increasing either torrefaction temperature or substitution ratio of biomass. A deep torrefaction may not be recommended, because the power saved from biomass grinding is less than the heat consumed by the extra torrefaction process, depending on the heat sources. 

Python PSS/E Simulation to Test Efficacy of Proposed PMU Based WAMS and Potential WAMPAC Applications

A PSS/E 32 model of a real section of the Northern Ireland electrical grid was dynamically controlled with Python 2.5. In this manner data from a proposed wide area monitoring system was simulated. The area is of interest as it is a weakly coupled distribution grid with significant distributed generation. The data was used to create an optimization and protection metric that reflected reactive power flow, voltage profile, thermal overload and voltage excursions. Step changes in the metric were introduced upon the operation of special protection systems and voltage excursions. A wide variety of grid conditions were simulated while tap changer positions and switched capacitor banks were iterated through; with the most desirable state returning the lowest optimization and protection metric. The optimized metric was compared against the metric generated from the standard system state returned by PSS/E. Various grid scenarios were explored involving an intact network and compromised networks (line loss) under summer maximum, summer minimum and winter maximum conditions. In each instance the output from the installed distributed generation is varied between 0 MW and 80 MW (120% of installed capacity). It is shown that in grid models the triggering of special protection systems is delayed by between 1 MW and 6 MW (1.5% to 9% of capacity), with 3.5 MW being the average. The optimization and protection metric gives a quantitative value for system health and demonstrates the potential efficacy of wide area monitoring for protection and control.

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.

Engineering Simulations

Over recent years, ionic liquids have emerged as a class of novel fluids that have inspired the development of a number of new products and processes. The ability to design these materials with specific functionalities and properties means that they are highly relevant to the growing philosophy of chemical-product design. This is particularly appropriate in the context of a chemical industry that is becoming increasingly focussed on small-volume, high-value added products with relatively short times to market. To support such product and process development, a number of tools can be utilised. A key requirement is that the tool can predict the physical properties and activity coefficients of multi-component mixtures and, if required, model the process in which the materials will be used. Multi-scale simulations that span density functional theory (DFT) to process-engineering computations can address the relevant time and length scales and have increased in usage with the availability of cheap and powerful computers. Herein we will discuss the area of engineering calculations relating to the design of ionic liquid processes, that is, the computational tools that bridge this gap and allow for process simulation tools to utilise and assist in the design of ionic liquids. It will be shown that, at present, it is possible to use available tools to estimate many important properties of ionic liquids and mixtures containing them with a sufficient level of accuracy for preliminary design and selection.

A novel TRNSYS type for short-term borehole heat exchanger simulation: B2G model

Models of ground source heat pump (GSHP) systems are used as an aid for the correct design and optimization of the system. For this purpose, it is necessary to develop models which correctly reproduce the dynamic thermal behavior of each component in a short-term basis. Since the borehole heat exchanger (BHE) is one of the main components, special attention should be paid to ensuring a good accuracy on the prediction of the short-term response of the boreholes. The BHE models found in literature which are suitable for short-term simulations usually present high computational costs. In this work, a novel TRNSYS type implementing a borehole-to-ground (B2G) model, developed for modeling the short-term dynamic performance of a BHE with low computational cost, is presented. The model has been validated against experimental data from a GSHP system located at Universitat Politècnica de València, Spain. Validation results show the ability of the model to reproduce the short-term behavior of the borehole, both for a step-test and under normal operating conditions.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.