International Journal of Simulation and Process Modelling (38 papers in press)
Modelling and application for eclampsia with SimMom
by Xue Wang, Ying Pan, Liyou Song, Xiaochen Huang, Ming Liu, Anqi Liu
Abstract: In this paper, the issue of simulation-based education with SimMom is dealt with for training of the students and young doctors in obstetrics and gynaecology in the case of eclampsia in hypertensive disorders during pregnancy, together with the reasonable and standard drug treatment. The model is built and the practical training results are analysed and compared for the performance of two groups of students under model-based training and conventional training, respectively. The results show that there was no significant difference in the theoretical knowledge test and crossover test for the two groups of students, whereas practice test scores increased significantly (P<0.05), with the group using the model of SimMom scoring higher than the other group. It proves that the SimMom application in obstetrics eclampsia will help to improve medical students' and young doctors' clinical skills. The advanced product makes a great contribution to reducing the medical accidents, improving medicinal level and doctor-patient relationship and promoting medical education.
Keywords: SimMom; eclampsia; simulation-based education; medical modeling; clinical skill.
Cost models for improved vehicle assembly line performance
by Arun Rane
Abstract: The viability of any manufacturing plant is a function of time and cost. Automobile manufacturing is the most competitive sector. The objective of this paper is to provide a detailed description of the development of the relationship between: cost of failure and time lost due to equipment failure; cost of inventory and time lost due to shortages of material; cost of setup and time lost due to set up; cost of absenteeism and time lost due to absenteeism; and cost of material handling and time lost due to material handling. Relationships are established scientifically using regression modelling, simulation and discussions with domain experts. Results are validated in a reputable vehicle assembly line. In this contribution, it is demonstrated that established models follow a cubic relationship rather than hyperbolic as reported in the literature. Further, an improved model with strong 17 constraints is presented, which may be useful for managers in taking cost-based decisions to improve the throughput.
Keywords: cost of inventory; cost of failure; cost of setup; throughput; vehicle assembly line.
An analytic model to investigate the demand propagation in EOI supply networks
by Eleonora Bottani, Roberto Montanari
Abstract: This paper builds upon the study by Montanari et al. (2015). These authors presented a probabilistic approach, named M.DPA.eoq, to predict the demand seen by an upper-tier echelon (e.g. a distribution centre) of a supply network, serving several lower-tier echelons (e.g. retail stores) operating according to an economic order quantity (EOQ) policy. In this paper, we investigate the case of the economic order interval (EOI) policy and thus formulate the M.DPA.eoi (Montanari Demand Probabilistic Approach in the EOI scenario) framework. The M.DPA.eoi aims at determining the distribution of the demand seen by the upper-tier echelon of the supply network. Although its analytic formulation is not so simple, the approach is quite easy to understand and can be implemented without difficulties in general-purpose software, such as Microsoft ExcelTM. Therefore, the M.DPA.eoi is expected to be directly exploited by supply network managers, to estimate the distribution of the demand the upper-tier echelon will face in a defined network structure. Students and researchers could also benefit from such a model, given its ease of use. The model is tested on four scenarios, to derive the distribution of the demand seen by the upper-tier echelon under different network structures and different behaviours of the lower-tier echelons.
Keywords: supply network; economic order interval; demand propagation; demand distribution; M.DPA.eoi; bullwhip effect
A multi-measure and hybrid iterative procedure for marine ports (re)design
by Letizia Nicoletti, Antonio Padovano
Abstract: In view of the high costs of terminal construction and maintenance, environmental impacts and risk of shipping accidents, public bodies, port authorities, and terminal operators all around the world are looking for new decision support methodologies, especially in the case of large-scale marine port (re)design projects. The authors propose a multi-measure, hybrid, and iterative procedure, which benefits from the use of real-time simulation to drive the design engineers through a continuous and gradual improvement of the design solution. After having defined multiple performance metrics (margins for safety, pollutant emissions) as well as having designed and implemented a realistic virtual test environment, the design solutions can be generated according to throughput and traffic requirements, and then tested by key nautical experts. Criticalities as well as potential improvements of the design solution are visually reported according to a set of results statistically collected at the end of each testing session.
Keywords: marine port; (re)design; decision support; simulation; risk-based analysis.
An innovative simulation model for the operations of a multipurpose seaport: a case study from Port of Wilmington, USA
by Mir Wahed, Ardeshir Faghri, Mingxin Li
Abstract: The analysis of potential operating problems in a port facility is an enduring theoretical and practical problem. These issues are much more acute for multipurpose ports, where different types of cargo operate at the same time by using the same resources of the port and the same labour forces, making it difficult and complex for management to make proper decisions about the operation and management of a multipurpose seaport. Because of the complexity of the problem, many existing methods have difficulties in providing a fast and reliable analysis of potential operating problems in a multipurpose port facility. In this study, a simulation model is developed to overcome this difficulty by analysing the operation of a multipurpose regional seaport in Delaware, USA. The model is implemented to identify the possible bottlenecks and optimise the operation of the port. The simulation model generates different "what if" scenarios based on the change of different input, which shows port performance under different conditions. The "what if" scenario then tries to find the significant elements of the multipurpose terminal operation which, if changed, could most reduce the turnaround time of the vessels. The results of the simulation model are used to choose the optimal change in the significant elements (ship turnaround time, waiting time for bulk cargoes, containers, and trucks) of the terminals operation.
Keywords: multipurpose seaport; port management; seaports operation; simulation model; transportation planning; performance evaluation.
LabVIEW implementation of chaotic masking with adaptively synchronised forced Van der Pol oscillators and its application in real time image encryption
by Sundarapandian Vaidyanathan, Karthikeyan Rajagopal
Abstract: Chaotic oscillators find many applications in the field of cryptography and secure communication engineering. This paper first details one such approach of applying a forced Van der Pol chaotic oscillator and its synchronised slave model in chaotic masking and image encryption. This approach applies the chaotic masking to the secondary image, thus changing the image pixels, and the masked image is used for encoding the original image. We have developed a real time image encryption algorithm by capturing pictures through the NI IMAQdx tools. The proposed model is implemented in LabVIEW and experimentally verified for the efficiency of the encryption algorithm.
Keywords: chaos; Van der Pol oscillator; chaos synchronisation; adaptive control; image encryption; chaotic masking.
Accurate and rapid modelling of AFM tip morphology through scanning sphere nanoparticles
by Shuai Yuan, Xiao Yao, Fangjun Luan, Jingang Shi, Yuanwei Qi, Wei Gong
Abstract: Atomic force microscopy (AFM) images are severely distorted owing to the convolution of tip shape on the sample morphology. It is necessary to know the tip shape in advance for reducing the broadening effect by using a deconvolution operation. Recently, a tip blind modelling algorithm has become the most common method owing to estimation from the image of an unknown sample surface with protruding features. However, the efficiency of this method is decreased, since the noise suppression parameters in the algorithm have great influence on the tip modelling results, and sample surface features can be easily contaminated in the tip scanning. To solve these problems, this paper proposes a new approach to estimate tip morphology. First, deposit some regular spherical nanoparticles on a flat surface for scanning AFM images. Then calculate the diameter of the nanoparticles by constructing a base plane with the least squares method. Nanoparticle diameter in this paper is estimated as the maximum distance from the top points of the nanoparticle to this base plane. Moreover, use the nanoparticle morphology as 'tip' to erode the AFM scanning image for estimating the tip shape. The effectiveness of this proposed method is illustrated by comparing the calculated tip morphology with its SEM images. It is proved to take less time than the tip blind modelling algorithm by simulation validation. Finally, the experimental results show that the nanoparticle widths of the reconstructed images are closer to the nanoparticles' actual diameter. It illustrates that the proposed method can improve image quality and measurement precision.
Keywords: atomic force microscopy; mathematical morphology; tip modelling; nano-manipulation; modelling simulation.
Taxi carpooling model and carpooling effects simulation
by Wei Zhang, Ruichun He, Qiang Xiao, Changxi Ma
Abstract: This paper built the models of two passengers and multiple passengers sharing a taxi. Advantages and effects of taxi carpooling mode are analysed by simulation. The influences of payment ratio and carpool ratio on taxi carpooling effects are analysed, and relevant conclusions are obtained. Simulation results show that taxi carpooling mode can improve driver income, decrease passenger payment and increase passenger capacity. Payment ratio and carpool ratio have great influence on carpooling effects. Driver income and passenger capacity increase with increase of carpool ratio. Change of payment ratio influences driver income and passenger payment simultaneously. The increase of carpooling ratio can help to develop carpooling advantages better. Appropriate payment ratio is the key to obtain good carpooling effects. When ρis larger, appropriateθcan be found to ensure win-win for drivers and passengers, and improve taxi passenger capacity. When ρis so small that no existed θcan ensure these effects, it needs to increase the number of taxi. These conclusions have a certain guiding significance to formulating taxi policy.
Keywords: urban traffic; taxi; carpooling effects; modelling; simulation.
Establishment of cure kinetic model and study on reaction mechanism of resin-based thermal insulation coatings
by Li Wei, Andong Du, Yuan Fang
Abstract: This paper deals with the preparation of epoxy resin-based thermal insulation coatings using epoxy resin as the matrix, in which a suitable amount of inorganic filler and fibre is added. The curing reaction rate versus time curves were obtained by analysing the isothermal curing process of the coating using the Differential Scanning Calorimetry (DSC) method. The phenomenological method was used to study its curing kinetics, the data fitting method was adopted to get some kinetic parameters of the n-order curing model, autocatalytic model and Kamal model, and the optimal kinetic model for curing reactions was determined according to the sum of squares due to error and correlation coefficient R2 of the fitted data. The dynamic DSC method and Fourier transform infrared spectroscopy were used to discuss the curing mechanism. Results show that the isothermal process of this coating conforms to the Kamal model, with a total reaction order m+n of 1.3-2.14. Both of the two curing reaction rate constants increase with the rise in temperature, corresponding to an apparent activation energy of 90.5832 kJ/mol and 68.3733 kJ/mol, respectively, with a pre-exponential factor of 6.521
Keywords: epoxy resin; thermal insulation coating; curing kinetics; reaction mechanism.
Real time multimodal transport path planning based on a pulse neural network model
by Tongjuan Zhao, Jiuhe Wang, Jianhua Zhang
Abstract: A modified pulse-coupled neural network (MPCNN) model is designed for real-time collision-free path planning of multimodal transport choice in stationary or non-stationary environments. The proposed neural network is topologically organised with only local lateral connections among neurons. The optimisation networks model consists of transport distance, transport time, transit costs and transit time and other factors, and then all the factors are combined to weight of the networks to realise the transformation to solve the shortest path problem. It works in dynamic environments and requires no prior knowledge of transport model. The transport from start to target with neurons is like the propagation of a wave, in which the target neuron fires first, and then the firing event spreads out, through the lateral connections among the neurons. Each neuron records its parent, that is, the neighbour that caused it to fire. The real-time optimal path is then the sequence of parents from the start neuron to the target neuron. In both the static and dynamic cases, the algorithm of the generated wave in the network spreads outward with travel times proportional to the linking strength among neurons. Therefore, the generated path is always the global shortest path. In addition, each neuron in the proposed model can propagate a firing event to its neighboring neuron without any comparing computations. The effectiveness and efficiency of the proposed approach is demonstrated through simulation and comparison studies.
Keywords: neural networks; path planning; multimodal transport; wave propagation.
Implementation of XFEM in the study of gear crack propagation behaviour using the SIF on different moments
by Zen Hiung Fung, Haidar Al-Qrimli
Abstract: The application of gears, especially spur gears, is widely available in most engineering applications. Especially for high module steel spur gear, it is used extensively in heavy machinery such as cranes and metal crushers. Therefore, it is crucial to avoid catastrophic damage to the gear by understanding the crack behaviour. Provided the crack does not propagate into the rim, only minor accidents are likely to happen or else catastrophe may be expected again. Therefore, the effect of crack behaviour on stress intensity factor (SIF) with different magnitudes of moment was examined. This study had implemented the application of extended finite element method (XFEM) in ABAQUS to overcome the limitations of the conventional method, the finite element method (FEM). The need for re-meshing was avoided in this simulation. The crack propagation pathways were visualised using STATUSXFEM.
Keywords: crack propagation; stress intensity factor; XFEM; gear; moment; contact stress; FEM; AGMA; Hertzian.
Simulation modelling and analysis of a production line
by Mahmoud Heshmat, Mahmoud El-Sharief, Mohamed El-Sebaie
Abstract: Production lines modelling has many problems that are difficult to solve using analytical solutions, owing to uncertainty and/or variability in variables and parameters. This paper is targeting unreliable production lines with finite buffers with the objective of evaluating and analysing the current situation and identifying bottlenecks. We use discrete event simulation to model a real production line based on one-year historical data about the breakdowns of all the production lines machinery. This data is used to find appropriate probability distributions to represent each machinery downtime and uptime. The simulation model is built using AnyLogic software to abstract the actual production line, and the model is validated using the actual data and information about the production line. Improvement scenarios are proposed to resolve the observed bottlenecks, and therefore give managerial insights to increase the throughput according to the increasing demand. Finally, production plans are set for different demands along the year.
Keywords: production lines; simulation; cement production; AnyLogic.
Special Issue on: The Latest Technologies for Building a Smart City
A novel visible-infrared image fusion framework for smart cities
by Zhinqin Zhu, Guanqiu Qi, Yi Chai, Hongpeng Yin, Jian Sun
Abstract: Image fusion technology is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Image fusion technology, as an efficient way to integrate information from multiple images, plays a more and more important role in smart cities. The quality of the fused image affects the accuracy, efficiency, and robustness of the related applications. Existing sparse representation-based image fusion methods consist of overly complete and redundant dictionary learning and sparse coding. However, overly complete and redundant dictionary does not consider the discriminative ability of dictionaries that may seriously affect the image fusion. A good dictionary is the key to a successful image fusion technique. To construct a discriminative dictionary, a novel framework that integrates an image-patches clustering and online dictionary learning methods is proposed for visible-infrared image fusion. The comparison experiments with existing solutions are used to validate and demonstrate the effectiveness of the proposed solution for image fusion.
Keywords: image fusion; sparse representation; dictionary learning; sub-space clustering; smart city.
Container-as-a-service architecture for business workflow
by Ye Tao, Xiaodong Wang, Xiaowei Xu, Guozhu Liu
Abstract: The massive amount of data makes the work of building a smart city more and more data-driven. However, data collection and its analysis in such a large system are often separated and executed by different vendors. Owing to volume, security and privacy reasons, data migration can be difficult. To build a bridge between data owners and data analysers, service migration is applied, which forms the infrastructures, applications and services for different vendors. This paper presents a Container-as-a-Service (CaaS) framework for data processing in a smart city environment. We design and implement a multi-layered container service construction and deployment environment, and we employ the business workflow orchestration technologies in this environment. By using containers, local cluster resources are virtualised and isolated to simplify the creation and deployment of multiple applications autonomously across multiple vendor systems. Inside a container, computational tasks and worker processes are encapsulated into web services, in order to leverage service-based workflow technologies to develop timely and effective workflows for a smart city environment. A use case of smart transportation is studied to validate the usefulness and evaluate the performance of the presented architecture. Results show that the approach can be beneficial to the scientific tasks in regard to its flexibility and re-usability.
Keywords: container; service computing; scientific workflow; BPEL for web services; Hadoop.
Software behaviour analysis method based On behaviour template
by Yingxu Lai, Zenghui Liu, Tao Ye
Abstract: This paper proposes a software behaviour analysis method based on behaviour template (SABT) which, according to the context of source code, builds a behaviour template to detect software malicious behaviour based on a function transfer map and minimum function blocks. Many methods use state transfer diagrams to build software behaviour models. Our method is based on the corresponding relationship between the functions and system call sequence, which ensures accurate detection of malicious behaviour. Compared with traditional methods, such as N-gram, FSA, and Var-gram, SABT can get higher cover rate of code and detect abnormal behaviour more effectively and efficiently.
Keywords: software behaviour, software interrupt, behaviour template, minimum function block
Boundary estimating of urban road network for traffic impact analysis when reconstructing intersections: methodology and evaluation
by Yingying Ma, Ying Zeng
Abstract: Intersections are major points of conflict for road users and the key parts of urban road networks. It is necessary to reconstruct some intersections to improve capacity and safety. A methodology to estimate the boundary of a road network for traffic impact analysis of intersection improvements is discussed in this paper. Firstly, models are presented for two types of degree of correlation. The degree of saturation and free-flow travel time are considered in the model for the degree of correlation between two adjacent intersections, and the degree of correlation between any two intersections in the network is analysed using a Laplacian matrix algorithm. Secondly, a new method to estimating a road network boundary is proposed. Thirdly, two measures are adopted to evaluate the boundary of road networks: the minimum average cut degree of correlation and the minimum traffic influence on intersections outside the boundary. Finally, the method is demonstrated using a city road network. The results of the case study confirm the validity of the proposed approach.
Keywords: boundary estimating, traffic impact analysis, intersection reconstruction, Laplacian matrix
Knowledge extraction based on linked open data for clinical documentation
by Mazen Alobaidi, Khalid Mahmood, Susan Sabra
Abstract: Smart cities are becoming a reality in the near future to transform many sectors and activities in our lives. Smart city systems, such as healthcare systems, will have new functionality to improve the quality of life of its citizens. Electronic health records are an essential component of healthcare systems. They are valuable for medical research, but much of the information is recorded as unstructured free text. Knowledge extraction from unstructured text in electronic health records is a problem that is well-documented but still not totally resolved. Knowledge extraction is very challenging because medical language has ungrammatical and fragmented constructions. We have implemented a unique framework knowledge extraction based on linked open data for clinical documentation (KE-LODC) that generates accurate and high quality triples transforming unstructured text from clinical documentation into well-defined and ready-to-use linked open data for diagnosis and treatment. We used Name Entity Recognition and Disambiguation (NERD) because it proved to be highly more precise than other available tools in entity recognition. Our framework proved to produce highly qualified big number of triple candidates, which improves the likelihood of better classification. Also, we evaluate our framework by comparing its precision and recall with two benchmark algorithms. The results show that KE-LODC performs better.
Keywords: healthcare, smart city, linked open data; semantic web; knowledge extraction;
Special Issue on: ACECS-2016 Advances and Applications of Process Modelling and Simulation
Modelling and hardware co-simulation of a quadrotor unmanned aerial vehicle
by Soufiene Bouallegue, Rabii Fessi
Abstract: This paper deals with the modelling and hardware (HW) co-simulation of a Quadrotor Vertical Take-Off and Landing (VTOL) type of Unmanned Aerial Vehicle (UAV). The developed HW co-simulation platform is based on a reconfigurable I/O (RIO) board of National Instruments (NI) Company, called sbRIO-9636, and a host PC with a Real-Time Operating System (RTOS). The Control Design and Simulation (CDSim) module of LabVIEW environment, as well as an established Network Streams data communication protocol, are used to emulate and co-simulate all flight dynamics within a Processor-In-the-Loop (PIL) framework. The flight motion principle of the quadrotor, i.e. lift, rotation and translation, is firstly described as a function of changes in the angular speed of the rotors. All aerodynamic forces and moments of such a vehicle are then described within an inertial earth frame, and a nonlinear dynamical model is established thanks to the Newton-Euler formalism. The dynamics of the propellers' brushless DC motors, accelerometer and gyroscope types of sensor are also modelled and co-simulated in order to complete the established model of the studied VTOL rotorcraft. HW simulations are carried out and compared with those obtained with software (SW) simulations in order to show the effectiveness of the proposed PIL co-simulation strategy.
Keywords: quadrotor UAV; modelling; aerodynamic effects; rotors and sensors dynamics; Newton-Euler equations; PIL co-simulation; NI single-board RIO; LabVIEW.
Artificial neural networks for acquisition and processing of sensors data in a radiotherapy application
by Kheireddine Lamamra
Abstract: This paper presents a practical aspect of work that we have planned for several steps. It describes the acquisition and processing of coded data from temperature sensors of type MS6503 used in radiotherapy rooms of the hospital PMCC (Hospital Pierre and Marie Curie Centre). The aim is to acquire and check remotely the temperatures of rooms to trigger alarms and their control thereafter in order to avoid mistakes of manipulation which are deadly for patients if they happen or arise. For this, a system modelling is made before proceeding to the implementation in practice. During the implementation, several problems have occurred such as the legibility of the received data that has been encrypted. To overcome this problem, an artificial neural networks type of Multi-Layer Perceptron (MLP) is used to acquire and decrypt the temperature data received from the sensors placed in the treatment rooms. The obtained results show that the neural network used has decrypted well the received data, hence this technique has been implemented in the realised solution.
Keywords: data acquisition and processing; temperature sensor; radiotherapy room control; artificial neural network; modelling.
Continuous Petri nets and hybrid automata: two bisimilar models for the simulation of positive systems
by Latefa Ghomri, Hassane Alla
Abstract: Petri nets (PNs) are a well-known modelling tool for discrete event systems. Continuous PN were introduced in order to avoid the combinatory explosion of the number of states, when considering real life systems. The constant speed continuous Petri nets (CCPN) where constant maximal firing speeds are associated with transitions allow very fast simulations. They can be used to model discrete events systems; in that case, they constitute an approximation, which is often satisfactory. They can also model positive continuous systems. Hybrid automata (HA) are a less compact and expressive model, but, they can be used to perform powerful analysis. In this paper, we first present the continuous PN and its modelling advantages. Then we present the main contribution of this paper, that is a structural translation algorithm from a CCPN into a HA. The goal of this translation algorithm is to combine advantages of both tools. The first one is an elegant modelling tool; with the second one, it is possible to compute the reachable state space. The translation algorithm is structural in the sense that it does not depend on the initial marking of the Petri net. We present the principal characteristics of the CCPN and the HA, and we prove the timed bisimilarity between the two models. Then it will be possible to deduce properties of the CCPN from the HA. An example of a manufacturing system is used throughout the paper to illustrate the different results, and a water supply system is presented as a more complex example.
Keywords: discrete event systems modelling; constant speed continuous Petri nets; hybrid automata; bisimulation.
Modelling and simulation of analytical approach to handle real-time traffic in VoIP network
by Sakshi Kaushal, Harish Kumar, Sarbjeet Singh, Sundarapandian Vaidyanathan, Jasleen Kaur, Shubhani Aggarwal
Abstract: In recent years, Internet Protocol (IP) has become a good choice over Public Switched Telephone Network (PSTN). A Voice over IP (VoIP) communication supports a number of users with an acceptable voice quality. VoIP implementation uses hard IP phones and soft IP phones, does not rely on a traditional PBX and uses Softswitch for call signalling, access control, etc. The Erlang B model is used to determine the number of trunks in a circuit-switched network and find traffic intensity and grade of service. This paper uses an extension of the Erlang B model for traffic engineering of VoIP, i.e., Extended Erlang B model. The main purpose for Extended Erlang B is that has better efficiency to handle the percentage of blocked calls by choosing a threshold value (). We propose a new measurement scheme based on an extended Erlang B model using FreeSWITCH to simulate and analyse VoIP traffic. Simulations are done in the QualNet 7.3 Network simulator using SIP protocol for VoIP traffic. We compare our version with the original definition of the Erlang B model and present further results from simulations. Experiments are conducted based on different voice codecs such as G.711, G.729A and G.723.1 for measuring packetisation intervals and for calculating bandwidth. The proposed scheme is also analysed for other QoS parameters, i.e, jitter, end-to-end delay and mean opinion score.
Keywords: VoIP; SIP; Softswitch; call admission control; traffic load measurement; Erlang B model.
Special Issue on: Integrating Modelling and Simulation Tools and Methodologies in Real-World Complex Systems for Solving Multidisciplinary Problems
Computer-aided support for the temperature control in buildings
by Borut Zupančič
Abstract: The paper briefly describes the Modelica model of a cubic room with one window. The 'physical' model was then implemented as a Modelica (Dymola) block in Matlab-Simulink environment. Simulink was used for the realisation of different control schemes, which were 'manually' and 'automatically' optimised. The experiments show that the synergetic combination of Matlab-Simulink and Dymola-Modelica environments is an efficient and powerful approach giving the possibility to realise several important goals: realisation preserving modelling in Modelica, efficient simulation with Simulink and many possibilities for control system design and optimisation using basic Matlab and appropriate Matlab toolboxes. However, the experiences with Modelica modelling taught us that Modelica models become rather complex, and therefore model reduction techniques in order to obtain usable and efficient models are desired. The last part of the paper briefly describes some research activities in this area and also our contributions.
Keywords: object oriented modelling; multi-domain modelling; thermal flows; radiation flows; temperature control; control design; PID control; optimisation; model reduction; Modelica
A divide and conquer approach for simulating an airport system
by Paolo Maria Scala, Miguel Mujica Mota, Nico Ed Bock
Abstract: Airport capacity, expressed as the maximum number of air traffic movements
that can be accommodated during a given period of time under given conditions, has
become a hard constraint to the air transportation, owing to the scarcity of resources on the ground and restrictions in the airspace. Usually the problem of capacity at airports is studied by separating airspace operations from ground operations, but it is evident that the two areas are tied to each other. This work aims at developing a simulation model that takes into account both airspace and ground operations. The approach used is a divide and conquer approach, which allows the combination of four different models. The four models refer to the airside, and airspace operations. This approach allows to evaluate the system from different angles depending on the scope of the study, the results show the analytic potential of this approach.
Keywords: simulation model; airport ground operations; airspace operations; divide and conquer approach; data driven decisions.
Extending Sim# for simulation-based optimisation of semi-automated machinery
by Johannes Karder, Andreas Scheibenpflug, Andreas Beham, Stefan Wagner, Michael Affenzeller
Abstract: Model building is a fundamental task in simulation-based optimisation. In this paper we demonstrate the application of Sim# in combination with HeuristicLab to optimise semi-automated machinery. On top of Sim#, custom simulation extensions have been implemented and are used to create a simulation model of real world machinery. These extensions enable the design of simulation components that can be reused within different simulation models. This allows to easily create multiple model implementations that reflect different designs of a machine by using a combination of already existing and adapted components. The resulting model is used as an evaluation function for single- and multi-objective optimisation using HeuristicLab. Results for different optimisation targets, e.g. job order, and quality criteria such as set-up time are compared.
Keywords: simulation-based optimisation, genetic algorithms, machinery, Sim#, HeuristicLab
Modular construction of compact Petri net models
by Juan Ignacio Latorre-Biel, Emilio Jimenez-Macias, Jorge Luis Garcia-Alcaraz, Juan Carlos Saenz-Díez Muro, Julio Blanco-Fernandez, Mercedes Perez De La Parte
Abstract: The use of modelling formalisms for the design of discrete event systems presents many advantages, such as the possibility of structural analysis of the model or performance evaluation. However, the difficulty of the process to obtain an appropriate model of the system requires the use of methodologies to ease the work of the designers. In this paper, two main subjects are discussed. On the one hand, the modular construction of Petri nets alleviates the design process by the use of blocks that can be assembled to build up a complete Petri net model. On the other hand, the development of decision support systems may require the assessment of the performance and properties of complete models obtained from different combinations of modular blocks. The formalism of the alternatives aggregation Petri net may help in the development of compact and efficient models that may reduce the use of scarce computer resources.
Keywords: modular Petri nets; alternatives aggregation Petri nets; decision support systems; performance evaluation.
The Industrial Internet of Things and technological innovation in its applications for resources optimisation
by Albino Ribeiro Neto, Maira Fernanda Gizotti Ribeiro, Gerson Gomes Cunha, Luiz Landau
Abstract: This paper presents a study on the use of the Industrial Internet of Things (IIoT), the use of IIoT in the current Brazilian industry context, its basic differences from the Internet of Things (IoT) and its expansion possibilities, pointing out some challenges related to a new approach within industry. The complex interconnection that is made possible through the IIoT is able to optimise resources and reduce exponentially the costs of production processes in most stages and is gradually changing the direction of society in labour relations. These advances in manufacturing processes are feasible as the IIoT is not simply inserting intelligence into equipment, but allowing interconnection, reconfiguring functions and anticipating loss of productivity or failures that might occur in real time. Within this context, the IIoT can be understood as a broad and complex concept that encompasses asset and performance management areas, availability of increased data and intelligent corporate control. To implement this, it is necessary to integrate the most diverse devices, standards, technologies and systems efficiently. All this automation is called 'smart manufacturing' and enables continuous improvement in processes, increased productivity by eliminating gaps and through the use of modelling and simulation, which enables operators to test and optimise processes and products still in the design phase, consequently decreasing costs and time of creation.
Keywords: Industrial Internet of Things; Internet of Things; radiofrequency identification; interconnection; network; sensors; industry; devices; big analogue data; wireless; cloud computing; digital services; smart manufacturing.
An intelligent serious game for a multi-device cultural heritage experience
by Francesco Longo, Letizia Nicoletti, Antonio Padovano, Marco Vetrano
Abstract: To date, digital technologies applied to cultural heritage have been mainly devoted to the reconstruction of the original appearance of artefacts and of the museum itself, thus implementing the mere concept of a virtual museum. Apart from some isolated cases, museums, and cultural institutions in general, are not so inclined to open out to virtual reality (VR) technologies because they offer the user a detached look at the art collection without actually delivering any cultural and educational content. This research work aims at presenting an innovative multi-device application based on the concept of Intelligent Serious Games (ISG). The combination of the educational potential of Serious Games (SG) with Intelligent Agents (IA), which will drive the evolution of the played scenario in accordance with the initial users' profiling and to the sequence of events generated during the museum tour, will create new patterns and promote new strategies for cultural content dissemination and fruition.
Keywords: cultural heritage; serious games; intelligent agents; museums; virtual reality; education.
Special Issue on: New Trends of Simulation and Process Modelling in Multiple Domains From Business and Production to Healthcare, Defence and Environmental Sustainability
Factors affecting human error: representations of mental models for emergency management
by Antonella Petrillo, Fabio De Felice, Francesco Longo, Agostino Bruzzone
Abstract: Human reliability is a crucial element in ensuring plant performance during an emercency condition. This is even more true as technology has been evolving exponentially in recent times. In fact, it is evident that technological developments imply a decrease of accidents due to the use of redundancy and protection. But at the same time, the high technology complexity requires a sophisticated safety management systems and a high level of safety culture. The classical approaches are not sufficient to prevent the occurrence of extraordinary incidents and accidents in which the key element is represented by the human factor. Thus, in this context it is necessary to face the problem considering the human factor in an holist way as the causation of several incidents and accidents. The analysis of human factors constitute a highly interdisciplinary field of study not yet well defined. This paper deals with various aspects of human behavior that can influence operator reliability. The aim of the research is to propose a novel methodological approach to simulate human errors in emergency condition. The new model is based on an integration of fuzzy cognitive maps techniques and Analytic Hierarchy Process (AHP), a multicriteria technique for organising and analysing complex decisions.
Keywords: human error, risk analysis, fuzzy cognitive maps, cognitive model, AHP.
Supply chains efficiency increasing based on the modelling of logistics operations
by Valery Lukinskiy, Vladislav Lukinskiy, Yuri Merkuryev
Abstract: For evaluating the integrated supply chains (SC) effective functioning, some new criteria are frequently used apart from the total logistics costs (TLC). These criteria characterise the quality and reliability of accomplishing logistics operations and functions. It is obvious that these metrics are connected and their separate representation is a consequence of an underdeveloped theoretical model of supply chains and, accordingly, analytical tools allowing carrying out a comprehensive assessment of these metrics. The paper presents a critical analysis of the existing approaches to the TLC evaluation and SC reliability, the methodical approach which allows evaluating the total costs indexes and supply chain reliability. This approach includes, firstly, the equation of the total logistics costs; secondly, the reliability evaluation model of a simple supply chain which is a reserved system with a renewal; thirdly, a complex of models for the evaluation of the reliability of basic logistics operations (purchase, order processing, choice of intermediaries, transportation, warehouse placement and storage). Taking into account that most indicators which describe the chain functioning are random values, to obtain the required evaluations there is a developed algorithm based on simulation.
Keywords: supply chains, reliability, failure models, total logistics costs, simulation
Game-theoretic method for locating camera towers and scheduling surveillance
by Javier Salmeron, Kevin Wood
Abstract: We develop techniques to optimise the locations and surveillance scheduling of tower-mounted camera systems used by a military force in an urban setting. Using a game-theoretic foundation, we seek to minimise expected damage from attacks or other adversarial events (e.g., emplacement of an improvised explosive device). Assuming that at most one camera may surveil a single point of interest (POI) at any time, a mixed-integer program uses an additive-probability model to optimise the placement of towers, while allocating aggregate, normalised surveillance time between cameras and POIs. Linear-programming-based column generation then creates a probability distribution for camera-to-POI assignments to define implementable schedules. We prove that such schedules must exist, making the additive probability model exact. Computational examples on realistically sized problems produce high-quality solutions quickly, with quality suffering only when the number of cameras available nears the number of POIs to be surveilled. We show that an alternative game-theoretic model may produce better solutions when such a situation arises.
Keywords: camera tower; surveillance; column generation; integer programming; randomized algorithm.
Linear stability analysis for severe slugging: sensitivity to void fraction and friction pressure drop correlations
by Jorge Luis Baliño, Gabriel Romualdo Azevedo, Karl Peter Burr
Abstract: A numerical linear stability analysis has been performed with a mathematical model for the two-phase flow in a pipeline-riser system. Void fraction is a key variable, as it influences the mixture properties and slip between the phases. The friction two-phase pressure drop is also an important variable as it is necessary, for instance, to determine the pumping power in multiphase processes. For a correct prediction of the stability behaviour of a pipeline-riser flow, preventing the occurrence of severe slugging, it is important to assess the sensitivity of the system response to different void fraction and friction pressure drop correlations. Three void fraction (Bendiksen, 1984; Chexal et al., 1997; Bhagwat and Ghajar, 2014) and two friction pressure drop correlations (homogeneous and M
Keywords: severe slugging; pipeline-riser system; air-water flow; linear stability theory; petroleum production technology.
Trip-based transport travel demand model for intelligent transport system measure evaluation based on micro-simulation
by Nadezhda Zenina, Yuri Merkuryev, Andrejs Romanovs
Abstract: Nowadays, the systems developed to integrate real physical processes and virtual computational processes [cyber-physical systems, CPS] are used in multiple areas such as medicine, traffic management and security, automotive engineering, industrial and process control, energy saving, ecological monitoring and management, avionics and space equipment, industrial robots, technical infrastructure management, distributed robotic systems, protection target systems, nanotechnology and biological systems technology. This paper provides an overview of CPS, their applications in different fields of modern business, with main video recording accent on intelligent transport systems (ITS). Various transport travel demand models are considered: trip-based, extended trip-based, tour-based and activity-based. Strengths and weaknesses of each transport travel demand model are described. Strategies and their evaluation measures are considered for effective ITS management. An example of transport management solutions realisation process (problem definition, data collection, initial model development, verification, validation, ITS strategies developments, testing and evaluation) based on transport microscopic modelling is presented. The example is illustrated for a Latvian city, Adazi, where it was necessary to improve accessibility level for local drivers for a future period of three to five year by evaluating different ITS measures combined with traffic organisation scheme changes.
Keywords: cyber-physical systems; intelligent transport system; modelling; transport travel demand models.
Experimental development and bond graph dynamic modelling of a brazed plate heat exchanger
by Mohamed Kebdani, Geneviève Dauphin-Tanguy, Antoine Dazin, Patrick Dupont
Abstract: This article is devoted to the dynamic study of a brazed plate heat exchanger (BPHE). First, an introduction is given to the industrial context of the current FUI THERMOFLUIDE project. A succinct presentation of the heat exchanger technology is proposed. Afterward, a state of the art summary about BPHE modelling, heat transfer and pressure drop correlations is given. Then a detailed mathematical description of an original dynamic model is presented. The last section deals with a description of the experimental test rig and the performed validation tests.
Keywords: brazed plate heat exchanger; bond graph methodology; dynamic; transient; single-phase flow; heat transfer correlations; modelling.
Hybridisation effect on operating costs and optimal sizing of components for hybrid electric vehicles
by Mauro Guido Carignano, Norberto Marcelo Nigro, Sergio Junco
Abstract: Reductions of fuel consumption and gas emissions count among the main advantages of hybrid electric vehicles (HEV). It is well known that the level of hybridisation has a large influence on the fuel consumption. On the other hand, the manufacturing cost and the battery lifetime are also affected by the level of hybridisation. Therefore, a proper selection of the size of components could be the result of a tradeoff between fuel consumption, battery lifetime and manufacturing cost. This paper provides models and a methodology to address the sizing of components of a HEV. Specifically, the work is focused on the series architecture, with an internal combustion engine and an electrochemical battery as thermal machine and storage system, respectively. The sizing criteria are oriented to reduce the operating costs, in which were included the fuel consumption and the battery-life consumption. Dedicated models are used to estimate the battery ageing and the lifetime of the internal combustion engine. Finally, both methodology and model presented are applied in a case study. It corresponds to a real hybrid electric bus operating in the urban transport system of the city of Buenos Aires. Simulation results under real driving conditions show that the best solutions are obtained by oversizing the battery with respect to power requirements.
Keywords: hybrid electric vehicle; hybridisation; optimisation; optimal sizing; lifetime.
Motivation and research in architectural intelligent tutoring
by Keith Brawner, Anne Sinatra, Robert Sottilare
Abstract: It is well known that personalised and adaptive training, such as from a human tutor, is dramatically more effective than traditional classroom training (Bloom, 1984; VanLehn, 2011). For a variety of reasons, however, tutoring systems are not yet ubiquitous within the training market. The US Army Research Laboratory is working to address this problem and has recently published a series of research vector outlines, which guide research in the various areas. The research within the architectural vector naturally exists to support the other vectors and to investigate, standardise, componentise, and commodise the processes and functions of the various tutoring system aspects. This paper serves as an expansion and companion to the similarly named 2015 International Defense and Homeland Security Simulation Workshop paper and yet-to-be-published ARL architectural research plan, expanded in order to discuss the progress made to date, clarify the role of the architecture in the research, and discuss some of the advantages of a unified system as part of measuring training effectiveness and overall system improvement.
Keywords: adaptive and predictive computer-based training; intelligent tutoring systems; architectural components; emerging standards.
DEv-PROMELA: an extension of PROMELA for the modelling, simulation and verification of discrete-event systems
by Aznam Yacoub, Maamar El Amine Hamri, Claudia Frydman, Chungman Seo, Bernard Zeigler
Abstract: PROMELA is a well-known formalism for the modelling and verification of concurrent systems. PROMELA deals with high-level specifications. As a result, PROMELA models are expressed in a high-level abstraction that does not consider explicit representation of time or events, for example. However, the efficiency of the processes of verification and validation relies on the accuracy of the models. That is why we propose in this paper to develop a new extension of PROMELA for the modelling of discrete-event systems. The verification of these models is then done by combining formal verification and simulation-based verification using SPIN and the tool DEv-PROMELA Studio, or using any existing DEVS simulators.
Keywords: DEv-PROMELA; simulation; formal verification; verification and validation.
A conversive hidden non-Markovian model based structure for discriminating spatio-temporal movement trajectories
by Tim Dittmar, Claudia Krull, Graham Horton
Abstract: We present a new modelling approach for spatio-temporal movement trajectories that is based on the stochastic model class called Conversive Hidden non-Markovian models (CHnMMs). The approach improves on previous work by facilitating the automatic creation of these models from examples. Created models can be used for trajectory classification and verification tasks, which is explained with a possible procedure. The use of CHnMMs allows for an explicit modelling of temporal dynamics, which allows the discrimination of trajectories by shape and execution speed. The presented approach is evaluated with touch gesture recognition experiments and compared with the $1 unistroke recogniser and the dynamic time-warping method. The results show better recognition rates for movements that are only discriminable by their temporal behaviour and very good recognition rates, especially regarding the discrimination of similar shaped trajectories that only differ in their temporal dynamics.
Keywords: touch gesture recognition; CHnMM; $1 recogniser; DTW; spatio-temporal; stochastic model; HMM; movement trajectories; non-Markovian model; pattern recognition.
Special Issue on: Integrating Modeling & Simulation tools and methodologies in real-world complex systems for solving multidisciplinary problems
An empirical investigation of comparative performance of approximate and exact corrections of the bias in Crostons method in forecasting lumpy demand
by Adriano Solis, Francesco Longo, Somnath Mukhopadhyay, Letizia Nicoletti
Abstract: A positive bias in Crostons method, which had been developed to forecast intermittent demand, was reported by Syntetos and Boylan. They proposed an approximate correction. Subsequently, Shale, Boylan, and Johnston proposed an exact correction. Both corrections were derived analytically. The mathematical analysis establishes the superiority of the exact correction over both Crostons method and the approximate correction. We empirically investigate whether or not there are significant improvements in statistical forecast accuracy as well as inventory control performance obtained by applying the approximate or exact correction when forecasting lumpy demand. Using extensive simulation experiments, we find overall superior forecast accuracy of the bias correction methods over both simple exponential smoothing and Crostons methods. However, the exact correction yielded the same or only marginally better accuracy measures compared with the approximate correction. Moreover, in terms of inventory control performance, we observe marginal differences in inventory on hand and backlogs.
Keywords: forecasting; time series; inventory; modelling and simulation; lumpy demand.