Selection of simulation tools for improving supply chain performance

Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach.

Simulation in the supply chain context:matching the simulation tool to the problem

The supply chain can be a source of competitive advantage for the firm. Simulation is an effective tool for investigating supply chain problems. The three main simulation approaches in the supply chain context are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). A sample from the literature suggests that whilst SD and ABM have been used to address strategic and planning problems, DES has mainly been used on planning and operational problems., A review of received wisdom suggests that historically, driven by custom and practice, certain simulation techniques have been focused on certain problem types. A theoretical review of the techniques, however, suggests that the scope of their application should be much wider and that supply chain practitioners could benefit from applying them in this broader way.

Modelling and simulation of biomass gasification in a circulating fluidized bed reactor

Computational Fluid Dynamics (CFD) has found great acceptance among the engineering community as a tool for research and design of processes that are practically difficult or expensive to study experimentally. One of these processes is the biomass gasification in a Circulating Fluidized Bed (CFB). Biomass gasification is the thermo-chemical conversion of biomass at a high temperature and a controlled oxygen amount into fuel gas, also sometime referred to as syngas. Circulating fluidized bed is a type of reactor in which it is possible to maintain a stable and continuous circulation of solids in a gas-solid system. The main objectives of this thesis are four folds: (i) Develop a three-dimensional predictive model of biomass gasification in a CFB riser using advanced Computational Fluid Dynamic (CFD) (ii) Experimentally validate the developed hydrodynamic model using conventional and advanced measuring techniques (iii) Study the complex hydrodynamics, heat transfer and reaction kinetics through modelling and simulation (iv) Study the CFB gasifier performance through parametric analysis and identify the optimum operating condition to maximize the product gas quality. Two different and complimentary experimental techniques were used to validate the hydrodynamic model, namely pressure measurement and particle tracking. The pressure measurement is a very common and widely used technique in fluidized bed studies, while, particle tracking using PEPT, which was originally developed for medical imaging, is a relatively new technique in the engineering field. It is relatively expensive and only available at few research centres around the world. This study started with a simple poly-dispersed single solid phase then moved to binary solid phases. The single solid phase was used for primary validations and eliminating unnecessary options and steps in building the hydrodynamic model. Then the outcomes from the primary validations were applied to the secondary validations of the binary mixture to avoid time consuming computations. Studies on binary solid mixture hydrodynamics is rarely reported in the literature. In this study the binary solid mixture was modelled and validated using experimental data from the both techniques mentioned above. Good agreement was achieved with the both techniques. According to the general gasification steps the developed model has been separated into three main gasification stages; drying, devolatilization and tar cracking, and partial combustion and gasification. The drying was modelled as a mass transfer from the solid phase to the gas phase. The devolatilization and tar cracking model consist of two steps; the devolatilization of the biomass which is used as a single reaction to generate the biomass gases from the volatile materials and tar cracking. The latter is also modelled as one reaction to generate gases with fixed mass fractions. The first reaction was classified as a heterogeneous reaction while the second reaction was classified as homogenous reaction. The partial combustion and gasification model consisted of carbon combustion reactions and carbon and gas phase reactions. The partial combustion considered was for C, CO, H2 and CH4. The carbon gasification reactions used in this study is the Boudouard reaction with CO2, the reaction with H2O and Methanation (Methane forming reaction) reaction to generate methane. The other gas phase reactions considered in this study are the water gas shift reaction, which is modelled as a reversible reaction and the methane steam reforming reaction. The developed gasification model was validated using different experimental data from the literature and for a wide range of operating conditions. Good agreement was observed, thus confirming the capability of the model in predicting biomass gasification in a CFB to a great accuracy. The developed model has been successfully used to carry out sensitivity and parametric analysis. The sensitivity analysis included: study of the effect of inclusion of various combustion reaction; and the effect of radiation in the gasification reaction. The developed model was also used to carry out parametric analysis by changing the following gasifier operating conditions: fuel/air ratio; biomass flow rates; sand (heat carrier) temperatures; sand flow rates; sand and biomass particle sizes; gasifying agent (pure air or pure steam); pyrolysis models used; steam/biomass ratio. Finally, based on these parametric and sensitivity analysis a final model was recommended for the simulation of biomass gasification in a CFB riser.

Investigating the role of cholesterol in the formation of non-ionic surfactant based bilayer vesicles:thermal analysis and molecular dynamics

The aim of this research was to investigate the molecular interactions occurring in the formulation of non-ionic surfactant based vesicles composed monopalmitoyl glycerol (MPG), cholesterol (Chol) and dicetyl phosphate (DCP). In the formulation of these vesicles, the thermodynamic attributes and surfactant interactions based on molecular dynamics, Langmuir monolayer studies, differential scanning calorimetry (DSC), hot stage microscopy and thermogravimetric analysis (TGA) were investigated. Initially the melting points of the components individually, and combined at a 5:4:1 MPG:Chol:DCP weight ratio, were investigated; the results show that lower (90 C) than previously reported (120-140 C) temperatures could be adopted to produce molten surfactants for the production of niosomes. This was advantageous for surfactant stability; whilst TGA studies show that the individual components were stable to above 200 C, the 5:4:1 MPG:Chol:DCP mixture show ∼2% surfactant degradation at 140 C, compared to 0.01% was measured at 90 C. Niosomes formed at this lower temperature offered comparable characteristics to vesicles prepared using higher temperatures commonly reported in literature. In the formation of niosome vesicles, cholesterol also played a key role. Langmuir monolayer studies demonstrated that intercalation of cholesterol in the monolayer did not occur in the MPG:Chol:DCP (5:4:1 weight ratio) mixture. This suggests cholesterol may support bilayer assembly, with molecular simulation studies also demonstrating that vesicles cannot be built without the addition of cholesterol, with higher concentrations of cholesterol (5:4:1 vs 5:2:1, MPG:Chol:DCP) decreasing the time required for niosome assembly. © 2013 Elsevier B.V.

Molecular dynamics simulations:bring biomolecular structures alive on a computer

The molecular dynamics (MD) simulations play a very important role in science today. They have been used successfully in binding free-energy calculations and rational design of drugs and vaccines. MD simulations can help visualize and understand structures and dynamics at an atomistic level when combined with molecular graphics programs. The molecular and atomistic properties can be displayed on a computer in a time-dependent way, which opens a road toward a better understanding of the relationship of structure, dynamics, and function. In this chapter, the basics of MD are explained, together with a step-by-step description of setup and running an MD simulation.

Molecular dynamics simulations of the adsorption and diffusion behavior of pure and mixed alkanes in silicalite

The adsorption and diffusion of mixed hydrocarbon components in silicalite have been studied using molecular dynamic simulation methods. We have investigated the effect of molecular loadings and temperature on the diffusional behavior of both pure and mixed alkane components. For binary mixtures with components of similar sizes, molecular diffusional behavior in the channels was noticed to be reversed as loading is increased. This behavior was noticeably absent for components of different sizes in the mixture. Methane molecules in the methane/propane mixture have the highest diffusion coefficients across the entire loading range. Binary mixtures containing ethane molecules prove more difficult to separate compared to other binary components. In the ternary mixture, however, ethane molecules diffuse much faster at 400 K in the channel with a tendency to separate out quickly from other components. © 2005 Elsevier Inc. All rights reserved.

Monte Carlo and molecular dynamics simulations of methane in potassium montmorillonite clay hydrates at elevated pressures and temperatures

The structure and dynamics of methane in hydrated potassium montmorillonite clay have been studied under conditions encountered in sedimentary basin and compared to those of hydrated sodium montmorillonite clay using computer simulation techniques. The simulated systems contain two molecular layers of water and followed gradients of 150 barkm-1 and 30 Kkm-1 up to a maximum burial depth of 6 km. Methane particle is coordinated to about 19 oxygen atoms, with 6 of these coming from the clay surface oxygen. Potassium ions tend to move away from the center towards the clay surface, in contrast to the behavior observed with the hydrated sodium form. The clay surface affinity for methane was found to be higher in the hydrated K-form. Methane diffusion in the two-layer hydrated K-montmorillonite increases from 0.39×10-9 m2s-1 at 280 K to 3.27×10-9 m2s-1 at 460 K compared to 0.36×10-9 m2s-1 at 280 K to 4.26×10-9 m2s-1 at 460 K in Na-montmorillonite hydrate. The distributions of the potassium ions were found to vary in the hydrates when compared to those of sodium form. Water molecules were also found to be very mobile in the potassium clay hydrates compared to sodium clay hydrates. © 2004 Elsevier Inc. All All rights reserved.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

The challenges of representing human behaviour in simulation models:some case examples from supply chain, evacuation modelling and rail disruption

As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.

Encapsulated membrane proteins:a simplified system for molecular simulation

Over the past 50 years there has been considerable progress in our understanding of biomolecular interactions at an atomic level. This in turn has allowed molecular simulation methods employing full atomistic modeling at ever larger scales to develop. However, some challenging areas still remain where there is either a lack of atomic resolution structures or where the simulation system is inherently complex. An area where both challenges are present is that of membranes containing membrane proteins. In this review we analyse a new practical approach to membrane protein study that offers a potential new route to high resolution structures and the possibility to simplify simulations. These new approaches collectively recognise that preservation of the interaction between the membrane protein and the lipid bilayer is often essential to maintain structure and function. The new methods preserve these interactions by producing nano-scale disc shaped particles that include bilayer and the chosen protein. Currently two approaches lead in this area: the MSP system that relies on peptides to stabilise the discs, and SMALPs where an amphipathic styrene maleic acid copolymer is used. Both methods greatly enable protein production and hence have the potential to accelerate atomic resolution structure determination as well as providing a simplified format for simulations of membrane protein dynamics.

Geometrical optimization of a fast pyrolysis bubbling fluidized bed reactor using comutational fluid dynamics

This paper analyzes the physical phenomena that take place inside an 1 kg/h bubbling fluidized bed reactor located at Aston University and presents a geometrically modified version of it, in order to improve certain hydrodynamic and gas flow characteristics. The bed uses, in its current operation, 40 L/min of N2 at 520 °C fed through a distributor plate and 15 L/min purge gas stream, i.e., N2 at 20 °C, via the feeding tube. The Eulerian model of FLUENT 6.3 is used for the simulation of the bed hydrodynamics, while the k - ε model accounts for the effect of the turbulence field of one phase on the other. The three-dimensional simulation of the current operation of the reactor showed that a stationary bubble was formed next to the feeding tube. The size of the permanent bubble reaches up to the splash zone of the reactor, without any fluidizaton taking place underneath the feeder. The gas flow dynamics in the freeboard of the reactor is also analyzed. A modified version of the reactor is presented, simulated, and analyzed, together with a discussion on the impact of the flow dynamics on the fast pyrolysis of biomass. © 2010 American Chemical Society.

Interaction dynamics in small networks of nonlinear elements

We study a small circuit of coupled nonlinear elements to investigate general features of signal transmission through networks. The small circuit itself is perceived as building block for larger networks. Individual dynamics and coupling are motivated by neuronal systems: We consider two types of dynamical modes for an individual element, regular spiking and chattering and each individual element can receive excitatory and/or inhibitory inputs and is subjected to different feedback types (excitatory and inhibitory; forward and recurrent). Both, deterministic and stochastic simulations are carried out to study the input-output relationships of these networks. Major results for regular spiking elements include frequency locking, spike rate amplification for strong synaptic coupling, and inhibition-induced spike rate control which can be interpreted as a output frequency rectification. For chattering elements, spike rate amplification for low frequencies and silencing for large frequencies is characteristic