SIMULTECH 2023 Abstracts

Area 1 - Modeling and Simulation Methodologies
Full Papers Short Papers
Area 2 - Simulation Technologies, Tools and Platforms
Full Papers Short Papers
Area 3 - Application Domains
Full Papers Short Papers

Area 1 - Modeling and Simulation Methodologies

Full Papers
Paper Nr: 6
Title:

Consensus Simulator for Organisational Structures
Authors:

Johannes S. Vorster and Louise Leenen
Abstract: In this paper we present a new simulator to investigate consensus within organisations, based on organisational structure, team dynamics, and artefacts. We model agents who can interact with each other and with artefacts, as well as the mathematical models that govern agent behaviour. We show that for a fixed problem size, there is a maximum time within which all agents will reach consensus, independent of number of agents. We present the results from simulating wide ranges of problem sizes and agent group sizes and report on two significant statistics; the time to reach consensus and the effort to reach consensus. The time to reach consensus has implications for project delivery timelines, and the effort relates to project economics.
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Paper Nr: 7
Title:

Performance of a K-Means Algorithm Driven by Careful Seeding
Authors:

Libero Nigro and Franco Cicirelli
Abstract: This paper proposes a variation of the K-Means clustering algorithm, named Population-Based K-Means (PB-K-MEANS), which founds its behaviour on careful seeding. The new K-Means algorithm rests on a greedy version of the K-Means++ seeding procedure (g_kmeans++), which proves effective in the search for an accurate clustering solution. PB-K-MEANS first builds a population of candidate solutions by independent runs of K-Means with g_kmeans++. Then the reservoir is used for recombining the stored solutions by Repeated K-Means toward the attainment of a final solution which minimizes the distortion index. PB-K-MEANS is currently implemented in Java through parallel streams and lambda expressions. The paper first recalls basic concepts of clustering and of K-Means together with the role of the seeding procedure, then it goes on by describing basic design and implementation issues of PB-K-MEANS. After that, simulation experiments carried out both on synthetic and real-world datasets are reported, confirming good execution performance and careful clustering.
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Paper Nr: 19
Title:

Metrics and Metamodels for Mission-Based Assessment of Multi-Aircraft Force Compositions
Authors:

Julian Seethaler, Michael Strohal and Peter Stütz
Abstract: In this work, metric vectors for the fair quantitative assessment and comparison of multi-aircraft force compositions with unmanned aerial vehicles (UAV) and/or manned-unmanned teaming (MUM-T) are proposed for specific representative missions in the form of imaging intelligence (IMINT) and close air support (CAS) vignettes. General advantages and disadvantages of force compositions combined with common mission tasks lead to a hierarchically structured pool of possible metrics, which are also known as performance indicators, from which suitable measures are selected for the respective mission type(s). These are tested on data from agent-based constructive simulation. Combining simulation results and the associated expert-derived criteria weights, which represent the importance of the respective items, yields insights about systems effectiveness potentials. Additionally, vignette-specific linear regression, support vector regression (SVR), and neural network regression (NNR) metamodels are derived to enable estimation of mission performance of multi-aircraft force compositions without explicit simulation. These are compared among each other and trialed against test data.
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Paper Nr: 40
Title:

Optimization of a Deep Reinforcement Learning Policy for Construction Manufacturing Control
Authors:

Ian Flood and Xiaoyan Zhou
Abstract: The paper is concerned with the optimization of a deep learning approach for the intelligent control of a factory process that produces precast reinforced concrete components. The system is designed and optimized to deal with the unique challenges associated with controlling construction work, such as high customization of components and the need to produce work to order. A deep reinforcement learning strategy is described for training an artificial neural network to act as the factory control policy. The performance of the approach is maximized via a sensitivity analysis that ranges key modelling parameters such as the structure of the neural network and its inputs. This set of experiments is conducted on data acquired from a real factory. The study shows that the performance of the policy can be significantly improved by an appropriate selection of the modelling parameters. The paper concludes with suggestions for potential avenues for future research that could build upon the current work and further advance the approach.
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Paper Nr: 52
Title:

Modeling & SMC Based Trajectory Tracking for a Tilt-Rotor Convertible UAV
Authors:

Mohamed Z. Mimouni, Oualid Araar, Abdelkader Ouadda and Moussa Haddad
Abstract: Convertible UAVs combine the vertical takeoff and landing (VTOL) capabilities of multi-rotors with the endurance and high speed of fixed-wing drones. This work is concerned with a particular category of convertible UAVs, commonly termed Tilt-rotor UAVs (TRUAVs). First, a detailed dynamic model for a Quad-TRUAV is developed. This model features strong non-linearities and coupling, making its control a challenging task. The second contribution of this work is the design of a sliding mode controller (SMC) to ensure trajectory tracking. Simulations conducted on the full non-linear model of the famous Zagi-wing UAV show very promising results.
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Paper Nr: 60
Title:

Learning Heuristics for Topographic Path Planning in Agent-Based Simulations
Authors:

Henrique L. Krever, Thiago S. Leão, Juliano M. Pasa, Edison P. de Freitas, Raul C. Nunes and Luis L. Silva
Abstract: Path planning algorithms with Deep Neural Networks (DNN) are fundamental to Agent-Based Modeling and Simulation (ABMS). Pathfinding algorithms use various heuristic functions while searching for a route with a low cost according to different criteria. When such algorithms are applied to compute agent routes in simulated terrain maps represented by large numbers of nodes and where topographic movement constraints are present, the problem is that traditional heuristic functions lose quality since they do not capture important characteristics for target simulation problems. To approach this issue, this work investigates the training of DNNs with large numbers of (i) topographic path costs and (ii) correction factors for standard Euclidean distance heuristic estimations. The aim is to use these DNNs as heuristic functions to guide the execution of different A∗ -based topographic path planning algorithms in agent-based simulations. The work approaches the heuristic learning and computation of agent routes in topographic terrain maps of different natures. To assess the performance of the proposed techniques, experimental results with path planning algorithms and alternative topographic maps are analyzed according to statistical models.
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Paper Nr: 71
Title:

Developing a Framework for Multi-Scale Modeling of the Digital Patient: Insights from Current Status and Future Directions
Authors:

C. D. Combs, Lubna Pinky, Chathurani Ranathunge, Sagar S. Patel, Taryn Cuper, Robert K. Armstrong and Robert J. Alpino
Abstract: The Digital Patient is an analytic platform that has the potential to transform personal and public healthcare, pharmaceutical research, medical device development, and patient and professional education. It is the ultimate big data project in healthcare; however, its power will derive not from the volume of data, but from the successful and efficient integration of disparate sources of data into a validated and reliable computational model of combined biological processes, social context and treatment efficacy. That integration, successively, is largely dependent on the evolving theoretical approaches known as systems biology and physics-based modeling that lead to the successful meshing of multi-scale models.
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Short Papers
Paper Nr: 3
Title:

There is More than Mean and Variance on Waiting
Authors:

Dominik Berbig
Abstract: Processes in material flow systems, which can be regarded as queuing systems, are discrete in time. Nevertheless, the main research work considering queuing theory focuses on time-continuous modelling. However, for G/G/m-queues in continuous time, analysis relevant parameters can only be estimated and not exactly calculated anymore. These approximations are based on the first two central moments of the inter-arrival and service time distribution only and can be arbitrarily wrong. Considering discrete-time approach, the parameters can be calculated exactly. This means that also other central moments of according distributions may have an effect that is not to be neglected. Thus, in this paper we investigate the effect of skewness and kurtosis of service time distributions on the expected waiting times for queuing customers. In order to do so, we modelled queuing systems in a discrete-time manner and calculated resulting waiting times for distributions having the same mean and variance. In continuous time approximation, the result is always the same. Exact calculations following a discrete-time approach show differences of more than 15 %. Afterwards, we investigated on the effect the skewness and kurtosis of the according distributions have. First findings and need for further research are presented in this position paper.
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Paper Nr: 11
Title:

A Topic-Based Data Distribution Management for HLA
Authors:

Alberto Falcone and Alfredo Garro
Abstract: Modeling and Simulation (M&S) represents a fundamental technology for designing and studying complex systems in various industrial and scientific domains, when real-world testing is too costly to perform in terms of safety, time, and other resources. To promote the reusability and interoperability of simulation models allowing them to interoperate without geographic constraints, distributed simulation has been introduced. One of the most widely adopted standards for distributed simulation is IEEE 1516-2010 - High Level Architecture (HLA). Among the services provided by HLA, a key one is the Data Distribution Management (DDM) that allows to reduce the transmission and reception of unnecessary data in order to improve communication effectiveness among simulation models. Although many matching algorithms have been proposed in the literature, the upcoming HLA 4.0 standard defines a DDM that still relies on performing matching verification by calculating the overlap between regions using their dimensions. In this paper, a novel topic-based publish-subscribe messaging system is proposed to improve the performance, reliability, and scalability of DDM services. Experiments show that the proposed topic-based approach achieves better performance than the standard one.
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Paper Nr: 14
Title:

Project Management Information System Data Model Development and Explanation
Authors:

Filippo M. Ottaviani, Massimo Rebuglio and Alberto De Marco
Abstract: The Project Management (PM) discipline is evolving towards the adoption of digital technologies, which are to be integrated into a project management information system (PMIS). Despite the fact that many PMIS solutions are already available, there is no standard data model for PMIS development, nor is the logic underlying PMIS. Therefore, organizations struggle to integrate other business applications into the PMIS and cannot leverage the data collected to improve both project management and execution. To address these issues, this paper aims to provide a standard PMIS model as a foundation for database design and software development. The PM objects are first identified and then represented in a data model that outlines their attributes and methods and the relationships between the classes. All classes are structured to accommodate in their interface the core PM processes, such as task and resource management, project scheduling, risk management, and progress control. The study evaluates the impact and benefits of implementing this standard model while acknowledging its limitations and providing recommendations for practical implementation.
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Paper Nr: 23
Title:

The Features of Design Calculation Stages of Parameters of Flow Path of Cascade Compressor of Twin Shaft Gas Turbine Engine Core on Base of 1D and 2D Dimensional Models of Their Working Process
Authors:

V. N. Matveev, E. S. Goriachkin, G. M. Popov, O. V. Baturin and I. A. Kudryashov
Abstract: The features of the stages of the design calculation of the parameters for the formation of the initial design of the flow path of the compressor cascade of a twin-shaft engine core of gas turbine engine are presented and described. The article describes recommendations for choosing values of load coefficient, efficiency and other important parameters for stages of medium-pressure and high-pressure cascades at the stage of thermodynamic calculation. At the stage of design gas-dynamic calculation of the compressor at the middle diameter, typical distributions of axial velocity component and reaction rate along the flow path of compressor cascades should be taken into consideration. At the same time, it is necessary to provide requirements for the level of flow braking and static pressure coefficients in the rotor wheels and stator blades, load and Stepanov’s coefficients. The features of the design gas-dynamic calculation of the compressor along the radius of the flow path are a variety of flow twist laws at the inlet to the rotor wheels, distributions of the pressure increase and efficiency by the height of the blades. In conclusion, an example of three-dimensional model of compressor flow path formed taking into consideration features of design calculation of parameters of cascade compressors of twin-shaft engine core of gas turbine engine on the basis of the corresponding flow path scheme in the meridional plane is presented.
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Paper Nr: 24
Title:

Improving the Thermal Condition of the High-Pressure Turbine Blade
Authors:

V. M. Zubanov, G. M. Popov, S. A. Melnikov, A. I. Sherban and Liu Xin
Abstract: An increase in the temperature of the gases forces the cooling system of the turbine blades to become more and more complex. The presented article describes a complex and computer-intensive numerical model of a working blade of a modern high-pressure turbine of a civil aviation aircraft gas turbine engine, which includes a flow region, a blade body, internal cooling channels and coolant supply channels. Using this model, the thermal state of the blade was determined and potential problem areas were found: hot gas leakage, coolant stagnation and overheating. Based on the analysis, several options were proposed for changing the configuration of the internal channels of the blade, which reduce the negative effects found. Although the proposed design options did not fully achieve all the requirements for the blade, they made it possible to find promising ways for further improvement. Also, the authors have practically worked out conjugate numerical models to study the thermal state of the turbine.
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Paper Nr: 25
Title:

Simulation of Steady and Transient 3D Flows via Physics-Informed Deep Learning
Authors:

Philipp Moser, Wolfgang Fenz, Stefan Thumfart, Isabell Ganitzer and Michael Giretzlehner
Abstract: Physics-Informed deep learning methods are attracting increased attention for modeling physical systems due to their mesh-free approach, their straightforward handling of forward and inverse problems, and the possibility to seamlessly include measurement data. Today, most learning-based flow modeling reports rely on the representational power of fully-connected neural networks, although many different architectures have been introduced into deep learning, each with specific benefits for certain applications. In this paper, we successfully demonstrate the application of physics-informed neural networks for modeling steady and transient flows through 3D geometries. Our work serves as a practical guideline for machine learning practitioners by comparing several popular network architectures in terms of accuracy and computational costs. The steady flow results were in good agreement with finite element-based simulations, while the transient flows proved more challenging for the continuous-time PINN approaches. Overall, our findings suggest that standard fully-connected neural networks offer an efficient balance between training time and accuracy. Although not readily supported by statistical/practical significance, we could identify a few more complex architectures, namely Fourier networks and Deep Galerkin Methods, as attractive options for accurate flow modeling.
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Paper Nr: 27
Title:

Performance Evaluation of Free Space Optics Laser Communications for 5G and Beyond Secure Network Connections
Authors:

Peppino Fazio, Mauro Tropea, Miralem Mehic, Floriano De Rango and Miroslav Voznak
Abstract: Free Space Optics (FSO) represent a promising technology for secure communications in several types of architectures: from Quantum Key Distribution Networks (QKDNs) to satellite communications. In this paper, in particular, we take into account terrestrial point-to-point laser communications and evaluate the performance in terms of Signal-to-Noise Ratio (SNR) and Bit Error Rate (BER), taking into account different scenarios, that can reflect real situations in which long distances can be reached in a secure way, guaranteeing an acceptable level of BER. So, after a huge campaign of simulations, we would like to let the scientific community know which are the theoretical limits that such kind of communications can reach. We take into account standard telescopes parameters (available today in the market), while configuring several real situations, in function of, for example, bit-rate, visibility, link distance, etc. A brief survey of the existing works is given, then a clearer performance evaluation of terrestrial FSO links is proposed.
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Paper Nr: 29
Title:

A Flood Prediction Benchmark Focused on Unknown Extreme Events
Authors:

Dimitri Bratzel, Stefan Wittek and Andreas Rausch
Abstract: Global warming is causing an increase in extreme weather events, making flood events more likely. In order to prevent casualties and damages in urban areas, flood prediction has become an essential task. While machine learning methods have shown promising results in this task, they face challenges when predicting events that fall outside the range of their training data. Since climate change is also impacting the intensity of rare events (i.e. by heavy rainfall) this challenge gets more and more pressing. Thus, this paper presents a benchmark for the evaluation of machine learning-based flood prediction for such rare, extreme events that exceed known maxima. The benchmark includes a real-world dataset, the implementation of a reference model, and an evaluation framework that is especially suited analysing potential danger during an extreme event and measuring overall performance. The dataset, the code of the evaluation framework, and the reference models are publicated alongside this paper.
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Paper Nr: 41
Title:

Agent Based In-Situ Visualization by Guide Field
Authors:

Yan Wang and Akira Kageyama
Abstract: In situ visualization has become an important research method today in high performance computing. In our previous study, we proposed 4D Street View (4DSV), in which multiple visualization cameras are scattered in the simulation region for interactive analysis of visualization video files after the simulation. A challenge in the 4DSV approach is to increase the camera density around a local area of the simulation box for detailed visualizations. To make the cameras automatically identify such a local region or Volume of Interest (VOI), we propose introducing the concept of a swarm of visualization cameras, which is an application of agent-based modeling to in-situ visualization. The camera agents in the camera swarm are autonomous entities. They find VOIs by themselves and communicate with each other through a virtual medium called a visualization guide field that is distributed in the simulation space.
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Paper Nr: 48
Title:

Efficient Machine-Learning-Based Crypto Forecasting Analysis
Authors:

Sidra Hussain, Sheikh S. Mim and Doina Logofatu
Abstract: Cryptocurrency is the current evolving financial market that gives scope for many researchers and machine learning assets to be put into production. Cryptocurrency forecasting is a challenge as following financial assets is difficult due to their volatility and unscalable factor dependencies. This paper puts forward the data of fourteen different types of cryptocurrencies, which will be used to build machine learning (ML) models to forecast the crypto scores in the next fiscal year. For this, four different models are used, and their performance is evaluated and tested. The models are Linear Regression, Decision Tree, Random Forest, and Gradient Boosting. The results obtained from the models show a perfect fit and good hyperparameter tuning, giving evidence of good feature engineering and data scraping. Overall, the models are meant to benefit the financial market immensely by helping to forecast and help investments build in sales and purchasing.
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Paper Nr: 58
Title:

Numerical Investigation of a High-Capacity Vertical Submersible Two-Stage Pump and Realization of an Experimental Test Bench for Determining the Strains and the Stresses on a Pump Shaft
Authors:

Patrick Z. Malonda and Guyh D. Ngoma
Abstract: A vertical submersible two-stage pump is investigated in terms of the axial and the radial forces on its shaft due to the liquid flow through the pump while accounting for the different flow rates. Also, a preliminary experimental test bench is performed to achieve the strains and the stresses on a pump shaft supporting an impeller as a function of the rotating speed. In fact, from an existing vertical submersible two-stage pump, a pump model is developed. The continuity and the Navier-Stokes equations are applied to obtain by means of the ANSYS-codes the fields of the liquid flow velocity and the pressure, as well as the axial and the radial forces acting on the pump shaft. The numerical results obtained for the pump head are validated using the experimental results. Three available axial forces for three flow rates from industry are used for the comparison with the numerical axial forces. The achieved experimental results from the preliminary test bench reveal that the strains and the stresses on the pump shaft increase with the raising of the rotating speed.
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Paper Nr: 62
Title:

Intra-Vehicular Network Security Datasets Evaluation
Authors:

Achref Haddaji, Samiha Ayed and Lamia C. Fourati
Abstract: Vehicular networks are more and more connected to the outside world. Therefore they became highly vulnerable to different cyber-attacks by being an easy target. Consequently, intra-vehicular networks’ cybersecurity risk is raised too. As a solution, Artificial Intelligence (AI) based solutions were proposed to overcome these issues. On the other hand, their effectiveness relies mainly on the existing sources and datasets to ensure the networks’ security. However, there is a significant challenge to overcome: the studies of the existing datasets of intra-vehicular network security. To tackle this issue, this paper examines and assesses existing intra-vehicular network security datasets. In addition, we comprehensively provide a detailed resource on the existing datasets and elaborate a comparative study. This paper also presents outstanding research discussions on dataset preprocessing, usability, and strength points to guide and help researchers.
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Paper Nr: 64
Title:

Work in Progress: Extending Virtual Prototypes of Microprocessor Architectures with Accuracy Tracing
Authors:

Johannes Kliemt and Dietmar Fey
Abstract: Virtual Prototypes of microprocessor architectures (VPs) extensively support the software development process with the ability to build virtual Hardware in the Loop (vHIL) test benches. A physical hardware is not necessary since the VP is also a functional simulation model, although with reduced accuracy. The actual deviation to the physical hardware in the time domain is mostly unspecified and dependent on the executed application software. This leads to issues when used in the development of software with real time requirements. The authors propose a new way of determining this inaccuracy via a trace unit integrated into the VP. Accuracy is now determined for each application software on the fly taking its individual paths through the model and not by a unrelated general set of accuracy benchmarks. A more reliable statement on the later temporal behavior on the physical hardware can therefore be given.
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Paper Nr: 65
Title:

A Comparison of the Dynamic Temperature Responses of Two Different Heat Exchanger Modelling Approaches in Simulink Simscape for HVAC Applications
Authors:

Samuel F. Fux, Babak Mohajer and Stefan Mischler
Abstract: In the HVAC industry, the dynamic temperature response of water-to-air heat exchangers is of particular importance for control system design. In this paper, the dynamic temperature responses of two established thermal dynamic modelling approaches for heat exchangers, the single-segment modelling using the effectiveness-NTU method and the multi-segment modelling, are investigated. Both approaches are validated against experimental data recorded with two different heat exchangers used in HVAC systems. A quasi-static analysis reveals minor differences between the results of the two models considered. The dynamic analysis is performed with varying inlet conditions. First results show that the single-segment model may fail to properly reproduce the water outlet temperature dynamics of a heat exchanger under certain conditions. In the tests performed in this study, however, the multi-segment model captures the relevant dynamics. The influence of this difference in the dynamic behaviour of the single-segment model on the model-based development of control algorithms is subject of future studies.
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Paper Nr: 66
Title:

The E-Dossier as a Tool to Optimize Civil Courts: The Cuneo Case
Authors:

Ilaria A. Amantea, Marinella Quaranta, Marianna Molinari, Christine Peduto and Francesca Demarchi
Abstract: This article presents a framework to integrate Business Process Management and Simulation to Civil Court proceedings in order to support the telematization of the dossier, starting from the paper dossier. To speed up Civil proceedings while maintaining high level of efficiency of the Court, the introduction of the e-dossier has been fundamental in Italy. The article revolves around the virtuous case of the Court of Cuneo, analyzed through Process Analysis and Process Reorganization Models, to estimate which changes and improvements the telematization has brought.
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Paper Nr: 77
Title:

Network Structure Identification for Medium Transport in a Virtual Reality Environment
Authors:

Linh Tuan Mai and Heiko Werdin
Abstract: Building Information Modelling (BIM) in the Architecture, Engineering, and Construction(AEC) sector allows for significant improvements in working efficiency throughout the entire life cycle of a building and has become mandatory in many countries. This process necessitates a greater understanding of the entire system from engineers, technicians, and facility managers, resulting in a greater demand for appropriate educational methods involving system simulation. The simulation of building energy services includes determining the network structure for medium transport, which is often not included in the BIM-model. This paper describes a workflow for determining the structure of a component-based geometrical model of a building energy service involving medium transport automatically. The workflow can be divided into three stages: identifying connected components, determining valid connection paths from a starting point to an end point, and determining the initialized flow direction of the transport medium within the system as well as the network structure. The depicted solution includes the workflow’s implementation and integration into a virtual reality environment for educational purposes. This approach has been validated through various exemplary generated test systems and allows for the realization of flexible educational use cases.
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Paper Nr: 4
Title:

Managing Trade-off Between Cost and Time in Project Scheduling Problems Using Discrete Event Simulation
Authors:

Sena Senses and Mustafa Kumral
Abstract: Project Management is a key activity in engineering and business entities to achieve specific objectives (e.g., construction, expansion, supply chain, and replacement). Effective project management includes a detailed investigation of the project’s costs and benefits and examining the short- and long-term effects of project design and implementation. In the mining industry, due to the operations’ inherent complexity and uncertainty associated with geological and financial inaccuracies, there is a substantial risk that the project may run over budget and schedule. It is vital to consider the project’s uncertainties to meet the project’s goals. This paper proposes a combined simulation and optimization model for time-cost trade-off project scheduling problems under uncertainty. A numerical example is conducted to demonstrate the effectiveness of the developed model through an electrical substation construction project conducted in a mine. By introducing numerous crashing scenarios to quantify the impact of uncertainty on the entire project and to assess the risks, the trade-off between time and cost is achieved under the project budget and deadline constraints. The proposed research has a significant potential to improve the management of construction projects considering a detailed project management methodology.
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Paper Nr: 13
Title:

Simulation Structure for Simulation Model of MCFC–GT Hybrid System
Authors:

Jarosław Milewski, Jakub Skibinski and Piotr Biczel
Abstract: The control system of MCFC coupled with a gas turbine should be based on the multi–layer structure, (two or three–layers), wherein the third layer relates to the power output from the system and can be considered separately. Simulation model of MCFC–GT hybrid system was built. The simulator is based on a zero-dimensional modelling of the individual elements of the system. The simulator was used for mapping the main components behaviour (MCFC and GT separately). Based on the obtained maps of the performances and adopted restrictions on technical–operational nature the operation line for the first line of the control strategy was obtained. The presented results indicate that the analysed MCFC–GT Hybrid System possesses a high operation and control flexibility while at the same time maintaining stable thermal efficiency. Operation of the system is possible over a wide range of parameter changes.
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Paper Nr: 16
Title:

Designing an Agent-Based Model for a City-Level Simulation of COVID-19 Spread in Cyprus
Authors:

Philip Fayad, Stylianos Hadjipetrou, Georgios Leventis, Dimitris Kavroudakis and Phaedon Kyriakidis
Abstract: To date, several epidemiological agent-based models have been developed to study the spread of the highly infectious coronavirus (SARS-COV) disease in different countries. However, no extensive effort has been implemented for the Republic of Cyprus. In this research, we present the design framework of the EPIMO-LCA agent-based model that respects the SEIR epidemiological model and attempts to simulate human mobility to predict the spread of COVID-19 at a city-level of detail. More specifically, we fully describe the three main model components (agents, environment and interactions) and explain all anticipated functionalities, processes, input and output elements. The agent-based model envisaged is expected to contribute to a better understanding of the interactions between intervention measures and disease spread for the city of Larnaca, the Republic of Cyprus, and beyond.
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Paper Nr: 35
Title:

Building Commuting Flows for an Agent Based Disease Spreading Simulation System Based on Aggregated Information
Authors:

Hung-Jui Chang, Wei-Ping Goh, Shu-Chen Tsai, Ting-Yu Lin, Chien-Chi Chang, Mei-Lien Pan, Da-Wei Wang and Tsan-Sheng Hsu
Abstract: In the kernel of an agent-based disease-spreading simulation system, the key factor is the commuting flows of students and workers during weekdays, which gives the movement of people between their residents and offices/schools. During commuting, people who lived in different areas mixed, which increases the spatial spreading of the virus temporally. It is difficult to extract the exact flow from data such as the census. However, small-scale survey examples and aggregated information, such as the size of schools and dormitories and transportation utilization, are known. Using the above, together with information on transportation routes and public transits, in this paper, we give a method based on the well-known flow conservation principle to construct a commuting flow in Taiwan. Validations are given to show such constructed data to fairly describe the real flow by observing our simulation system’s behaviors against what happened in previous pandemics.
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Paper Nr: 36
Title:

Analytical Model of Communication Algorithm for Simulations with Range-Limited Interactions
Authors:

Theresa Werner, Christof Päßler, Ivo Kabadshow and Matthias Werner
Abstract: With the development towards strong-scaling in High Performance Computing (HPC), many HPC applications become communication-bound. One of them is the HPC Molecular Dynamics Simulation library FMSolvr, which we are currently revising. In order to optimize communication, one could improve or develop new communication protocols, but in this work we are focusing on problem-specific communication algorithms. We found two promising candidates, the so-called Shift and what we call the Team Shift algorithm. In this work we present an analytical model for the Shift algorithm and verify it. Our model is based on the Hockney communication model and therefore only needs the two Hockney parameters α and β as input, so it can be used on any network where the Hockney model is applicable.
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Paper Nr: 56
Title:

Doctrine-Based Multi-Resolution Conversion for Distributed Agent-Based Simulations
Authors:

Raul C. Nunes, Guilherme Miollo, Edison Pignaton de Freitas and Luis L. Silva
Abstract: The treatment of different levels of simulation detail is a relevant component for integrating simulators in various application domains. These levels vary in federated multi-resolution simulations, from low-information (low-resolution) to high-information (high-resolution). One of the challenges in this integration is the representation and conversion of simulation data exchanged between the simulators. This work explores the use of doctrine-based rules in the conversion to ensure correct simulation integration. These rules contain information on how the multi-resolution conversion handlers should operate. To avoid abrupt changes from one doctrine rule to another, this work also extends a doctrine description language to capture information for the smooth transition between these rules. Experimental results demonstrate that it is possible to achieve simulations that flexibly deal with the required dynamism of a multi-resolution simulation environment.
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Paper Nr: 57
Title:

Modeling of Naïve Lymphocyte Signaling Pathway
Authors:

Isaac Barjis, Aliyah Amin, Amber Barjis and Saif Amin
Abstract: The immune system in general and T cells, in particular, play a critical role in protecting the organism from infection and repairing damaged tissue. T cells are not only key components of the immune system but are also central in mobilizing the adaptive immune responses at all stages of fighting infection. Furthermore, studies have shown that subsets of T helper cells are critical for the activation of antitumor responses. T cells have been intensively studied by both experimental immunologists and modelers. However, none of the research papers represent the complete process that will show the link between antigen-presenting cells, subtypes of T cells, and other signaling pathways. In this paper, we illustrate the first steps of an automation process for quantitative modeling, of the naïve T lymphocytes activation pathway by discrete modeling language using colored Petri nets (CPN). Modeling, simulation, and analyzing T cell activation signaling pathways will improve our understanding of the structure and dynamics of these pathways considerably. Petri nets have been proposed as an effective formalism for Systems Biology and modeling of metabolic pathways.
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Area 2 - Simulation Technologies, Tools and Platforms

Full Papers
Paper Nr: 33
Title:

Lyapunov Function Computation for Linear Switched Systems: Comparison of SDP and LP Approaches
Authors:

Stefania Andersen, Elias August, Sigurdur Hafstein and Jacopo Piccini
Abstract: For a switched system, of which each subsystem is linear, the exponential stability of the origin is equivalent to the existence of a common Lyapunov function (CLF) for all the subsystems. A popular approach to search for the latter is by means of solving a linear matrix inequality (LMI) using semidefinite programming (SDP). Another approach is to use linear programming (LP). The contribution of this work is twofold. First, we compare the SDP approach to the LP approach, with and without a certain preconditioning of system matrices. And, second, we present a software tool to visualise the conditions for a CLF. As the problem of investigating the stability of the origin is a very difficult one and sufficient and necessary conditions using the system matrices are only known for exponential stability of planar systems, a tool to visualise the original data in some meaningful form is potentially of great use for the full understanding of the problem.
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Paper Nr: 37
Title:

LiDAR-GEiL: LiDAR GPU Exploitation in Lightsimulations
Authors:

Manuel P. Vogel, Maximilian Kunz, Eike Gassen and Karsten Berns
Abstract: We propose a novel Light Detection And Ranging (LiDAR) simulation method using Unreal Engine’s Niagara particle system. Instead of performing the ray traces sequentially on the CPU or transforming depth images into point clouds, our method performs this particle-based approach using GPU particles that execute one line trace each. Due to execution on the GPU, it is very fast-performing. In order to classify the results, the new implementation is compared to existing ray-tracing and camera-based LiDAR. In addition to that we implemented and compared common LiDAR approaches using ray-tracing as well as depth images using cameras. A general architecture for easy exchange between simulated sensors and their communication is given using the adapter pattern. As a benchmark, we evaluated real sensor data with a ray tracing-based virtual sensor.
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Short Papers
Paper Nr: 28
Title:

Expanding the Scope and Increasing the Functionality of Digital Twins by Integrating Thermal Simulations
Authors:

Dorit Kaufmann, Jannis B. Weid and Jürgen Rossmann
Abstract: The simulation of components, systems and processes is an established tool in research and development nowadays. When it comes to complex systems and the interaction of components and disciplines, it is crucial to consider all relevant aspects, thus creating a powerful Digital Twin (DT) of a technical asset. In this work, an existing simulation framework for DT will be extended by an interface to Thermal Simulations. The latter one are still widely used as a stand-alone tool due to difficulties on linking the respective models and methods. Thus, the developed approach has its access point in the DT simulation framework and conducts the thermal calculations to an external Finite Element Analysis (FEA) solver by exchanging only characteristic variables. This concept is used as a base for the development of extensions for the DT whose basic functions are the import and preparation of geometric structures for both models, the management of the calculations of the external FEA solver and the visual representation of determined temperature distributions and heat fluxes in the DT.
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Paper Nr: 30
Title:

DataFITR: An Open, Guided Input Modeling Tool for Creating Simulation-Based Digital Twins
Authors:

Lekshmi P., Tushar Lone and Neha Karanjkar
Abstract: Input Modeling (IM) is a critical step in the process of building simulation-based digital twins. It involves selecting a family of distributions to model the observed data and finding the distribution parameter values that best fit the data. Subsequently, random variates adhering to the selected distribution can be generated to create a simulation-based digital twin of the system. For complex systems, IM can be a nuanced process involving a series of decisions that require visual feedback at each step. There is currently a dearth of open, GUI-based tools for aiding the non-expert user in the process of IM. This paper presents DataFITR, a GUI-based, open Input Modeling tool we have developed for guiding the non-expert user through the steps of input modeling and automating several intermediate tasks. DataFITR is cloud-hosted with a web-based user interface. The user can upload data as a file and the tool guides the user through the IM process by suggesting types and suitable distributions for each observed variable. It generates multiple goodness-of-fit measures for a large set of standard discrete and continuous distributions and can also support arbitrary (non-standard) distributions using a Kernel Density Estimation approach. DataFITR also assists in exploratory data analysis by providing various statistical properties of the observed data and in finding correlations between output measures. Once a matching distribution is found, the tool generates Python code for producing random variates from the matching distribution, which can be directly inserted into a simulation model. In this paper, we describe the DataFITR tool and its features, and compare it with existing open libraries and tools for assisting IM. We present a simulation case study of a bottling plant to demonstrate the utility of the DataFITR tool in building simulation-based digital twins.
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Paper Nr: 32
Title:

Interaction-Based Task Group Scheduling for a Scalable and Real-Time Self-Driving Simulation
Authors:

Akihito Kohiga, Kei Hiroi, Takumi Kataoka, Sho Fukaya and Yoichi Shinoda
Abstract: We developed a self-driving test environment based on Virtual Machine (VM) technology. Our test environment enables us to test multiple types of self-driving Artificial Intelligences (AIs) in one simulation and import their self-driving software to an actual car without modification. Our test environment divides a map into several segments and assigns a physical machine to each segment. If a vehicle crosses a border, the VM that embodies the vehicle is moved to another physical machine. However, VM movement causes a load imbalance on the physical machines. We suggest a novel approach to assign high-priority processing to a group of vehicles. The group of vehicles consists of one target vehicle that we would like to test and other vehicles that may interact with the target vehicle. We create such a group by identifying interactions using a ” pre-simulation”. Our approach reduced the processing time of the jobs created by the self-driving AIs by more than 90 percent under an ideal condition . This result indicates that our approach contributes the real-time processing when the CPU was in an overcommitted state.
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Paper Nr: 34
Title:

Event-Oriented Simulation Module for Dynamic Elastic Optical Networks with Space Division Multiplexing
Authors:

Mirko Zitkovich, Gabriel Saavedra and Danilo Bórquez-Paredes
Abstract: It is well-known that creating Space Division Multiplexing-Elastic Optical Networks (SDM-EON) allocation algorithms can be challenging, especially without the right tools. This paper presents the development of a module of an event-oriented simulator designed to code C++ allocation algorithms in the context of Space Division Multiplexing-Elastic Optical Networks. The built module was tested and validated using an allocation algorithm previously published in the literature. The results were consistent with those in the original article, indicating that the module developed is effective and reliable. The use of specialized tools, such as the module being shown, can significantly increase the effectiveness and precision of this process and can stimulate additional developments in the telecommunications industry.
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Paper Nr: 67
Title:

An Open Tool-Set for Simulation, Design-Space Exploration and Optimization of Supply Chains and Inventory Problems
Authors:

Tushar Lone, Lekshmi P. and Neha Karanjkar
Abstract: This paper presents the design overview and work-in-progress status for InventOpt - a Python-based, open tool-set for simulation, design space exploration and optimization of supply chains and inventory systems. InventOpt consists of a Python library of component models that can be instantiated and connected together to model and simulate complex supply chains. In addition, InventOpt contains a GUI-based tool to assist the user in planning design of experiments, visualizing the objective functions over a multi-dimensional design space, building and tuning meta-models and performing meta-model assisted optimization to identify promising regions in the design space. We present a detailed case study that illustrates the current prototype implementation, planned features and utility of the tool-set. The case study consists of simulation-based optimization of inventory threshold levels in a particular supply chain system with 8 decision parameters. We present our observations from the case study that lead to design decisions for building InventOpt such as the choice of the meta-model type, number of simulation measurements for building the meta-model, the choice of optimizer and the trade-off between computational cost and quality of results. A significant aspect of this work is that each step of the process has been implemented using open Python libraries.
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Paper Nr: 73
Title:

A Novel OMNeT++-Based Simulation Tool for Vehicular Cloud Computing in ETSI MEC-Compliant 5G Environments
Authors:

Angelo Feraudo, Alessandro Calvio and Paolo Bellavista
Abstract: Vehicular cloud computing is gaining popularity thanks to the rapid advancements in next generation wireless communication networks. Similarly, Edge Computing, along with its standard proposals such as European Telecommunications Standards Institute (ETSI) Multi-access Edge Computing (MEC), will play a vital role in these scenarios, by enabling the execution of cloud-based services at the edge of the network. Together, these solutions have the potential to create real micro-datacenters at the network edge, favoring several benefits like minimal latency, real-time data processing, and data locality. However, the research community has not yet the opportunity to use integrated simulation frameworks for the easy testing of applications that exploit both the vehicular cloud paradigm and MEC-compliant 5G deployment environments. In this paper, we present our simulation tool as a platform for researchers and engineers to design, test, and enhance applications utilizing the concepts of vehicular and edge cloud. The tool implements our ETSI MEC-compliant architecture that leverages resources provided by vehicles. Moreover, the paper analyzes and reports performance results for our simulation platform, as well as provides a use case where our simulator is used to support the design, test, and validation of an algorithm to distribute MEC application components on vehicular cloud resources.
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Area 3 - Application Domains

Full Papers
Paper Nr: 17
Title:

Hemodynamic Characterization of Localized Aortic Valve Calcifications
Authors:

Reza Daryani, Cenk E. Ersan and M. S. Çelebi
Abstract: Different hemodynamic characteristics of the blood flow can be studied by numerical simulations of the blood flow around the heart valves, which are significantly useful in various fields such as recognition and prediction of cardiovascular diseases, valve surgery, replacement, and advanced design of patient-specific prosthetic valves. One of these common valvular diseases is aortic valve stenosis, which mainly occurs due to the decreased orifice area between the valves’ leaflets and leads to insufficient blood pumping. In the aortic valve, calcification is the main reason for stenosis in which calcium deposits on the leaflets increase their rigidity and consequently prevent them from fully opening and closing. Severe cases of this disease lead to morbidity and mortality. In this work, different localized calcifications of the aortic valve are studied for several grades of this disease and compared with the healthy case. For this purpose, single-phase FSI simulations of blood flow are performed for various degrees of localized calcification patterns and pertinent hemodynamic parameters are obtained. Critical flow parameters, transvalvular indexes and Wall Shear Stress (WSS) based indexes are discussed in detail.
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Paper Nr: 45
Title:

Practical Implementation of Diode SPICE Model with Reverse Recovery
Authors:

Denys I. Zaikin
Abstract: Peter O. Lauritzen and Cliff L. Ma proposed an approach for creating a physical model of reverse recovery for soft recovery diodes in 1991. The current paper demonstrates how to create the proper SPICE sub-circuit using only the specifications from the diode datasheet from the manufacturer. Software for characterization tools has been developed, tested, and is now openly accessible for use.
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Paper Nr: 55
Title:

Exploring the Effects of Subversive Agents on Consensus-Seeking Processes Using a Multi-Agent Simulator
Authors:

Johannes S. Vorster and Louise Leenen
Abstract: In this paper we explore the effects of subversive agents on the effectiveness of consensus-seeking processes. A subversive agent can try and commit industrial espionage, or, could be a disgruntled employee. The ability of an organisation to effectively execute projects, especially projects within large and complex organisation such as those found in large corporates, governments and military institutions, depend on team members reaching consensus on everything from the project vision through various design phases and eventually project implementation and realisation. What could the effect be of agents trying to subvert such a process in a way that does not raise suspicions? Such an agent cannot openly sabotage the project, but rather tries to influence others in a way that increases the time it takes to reach consensus, thus delaying projects in subtle ways. Here we explore the effect such agents could have on the time and effort to reach consensus though the use of a stochastic Multi-Agent-Simulation (MAS).
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Paper Nr: 61
Title:

Position Analysis of the Atomiser Unit of an Aerosol-on-Demand Jet-Printhead by means of Computational Fluid Dynamics
Authors:

Martin Ungerer, Tim P. Walter and Ingo Sieber
Abstract: In this paper we present position analysis of the atomiser unit of a newly developed concept of a printhead for Aerosol-on-Demand (AoD) jet-printing using fluid dynamical modelling and simulation. In our concept of the AoD printhead, the ink is atomised by ultrasonic excitation and focussed by a sheath gas in a converging nozzle. Critical for the functioning of the AoD printing process is a proper positioning of the atomiser unit inside the printhead. Using computational fluid dynamics (CFD), we present a position analysis of the atomiser unit with respect to axial misalignment and tilting.
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Paper Nr: 69
Title:

A Digital Twin Simulator Approach as a Support to Develop an Integrated Observatory of the Epidemic Risk in a Rural Community in Senegal
Authors:

Jean Le Fur, Moussa Sall and Jean-Marie Dembele
Abstract: Following the contemporary epidemiologic approach known as EcoHealth, the study of an epidemic risk must consider and integrate the whole set of actors, factors and environments bound to the transmission of infectious diseases. In this study, we propose using a mechanistically rich digital twin simulator as a tool to facilitate this integration with the addition of a functional and dynamic dimension. The selected case study is the monitoring of the risk associated with ticks and rodents in a rural community in the Sahelian region of Senegal. To construct the digital twin, we iteratively went back and forth between field data collection and computer transcription of knowledge. Thanks to the high resolution afforded by the digital twin approach, the simulator enables the study of city-scale activity patterns as well as interactions between ticks, rodents, cats, and humans that occur within habitation rooms and shops. In addition to (i) being able to provide dynamic integrated support for the collected multidisciplinary knowledge, the digital twin realism provides (ii) an appropriate medium for communicating results to non-expert populations and (iii) a useful tool for monitoring and adjusting the observatory’s data collection protocols. The model’s complexity presents calibration challenges that are discussed.
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Paper Nr: 76
Title:

Impact of Inventory Management Policies on Supply Chain Resilience at RiRiShun Logistics
Authors:

Edward Meredith, Nikolaos Papakostas and Vincent Hargaden
Abstract: Using one year’s transaction level data from a large logistics service provider, this paper employs discrete event simulation to assess various inventory policies for managing supply chain risks and developing resilience. Datasets from a large Chinese Business-To-Consumer firm (RiRiShun Logistics) specialising in the order fulfilment of household appliances were provided. Using the datasets, a discrete event simulation model of RiRiShun’s distribution supply chain in two customer regions was developed using anyLogistix™ simulation software. A series of experiments were carried out to analyse the impact of inventory management policies on the performance of its supply chain in the face of disruptions. Results showed that decentralised inventory performed better when dealing with disruptions, while centralised inventory performed better when dealing with demand uncertainty.
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Short Papers
Paper Nr: 12
Title:

Integrating a Multi-Agent System Simulator and a Network Emulator to Realistically Exercise Military Network Scenarios
Authors:

Dante C. Barone, Juliano A. Wickboldt, Maria R. Cavalcanti, David Moura, Julio C. Tesolin, André M. Demori, Julio D. Anjos, Leonardo B. Silva de Carvalho, João C. Gomes and Edison Pignaton de Freitas
Abstract: Modern battlefield scenario are complex environment in which a myriad of equipment and people interact to accomplish a given mission. Most of this interaction is performed by means of wireless communication via Command and Control Systems, which efficiency represent a critical factor the mission success. The assessment of these systems, and their supporting networks, is of primal interest to decide for the best equipment and military maneuver approach. However, there is a lack of tools that provide all the necessary behavioral and network features to perform the task. Observing this fact, this work presents an alternative to simulate a battlefield environment model by means of integrating a network emulator and a Multi-Agent System simulator. By combining both software, it is possible to assess specific characteristics of each area without limiting the model, thus providing the necessary data for an informed military network setup assessment.
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Paper Nr: 38
Title:

Mitigation of LLDP Topological Poisoning Attack in SDN Environments Using Mininet Emulator
Authors:

Mattia G. Spina, Mauro Tropea and Floriano De Rango
Abstract: Software-Defined Networking (SDN) paradigm permits to have scalability and flexibility in the network management throughout a centralized control that has the global view of the network topology, but it introduces new security issues. In this paper, the Link Layer Discovery Protocol (LLDP) topological poisoning attack has been studied and analysed in order to provide possible mitigation solutions through the use of Mininet emulator and the POX controller. In particular, it is added to the LLDP protocol the integrity check using three different types of cryptographic algorithms such as Hash-based message authentication code (HMAC), Digital Signature Algorithm (DSA) using RSA and Elliptic Curve DSA (ECDSA). The performance evaluation of the proposal is provided considering a network topology where an attacker hijacks/impersonates an host already connected to the network.
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Paper Nr: 47
Title:

Performance and Efficiency Improvement of an Axial Flow Fan by Combining the FANDAS and the PIAnO Codes
Authors:

Chan Lee, Hyun T. Byun, Sang Y. Lee and Sang H. Yang
Abstract: The present paper deals with the optimization study of a variable-pitch axial flow fan by combining fan design method of the FANDAS (FAN Design and Analysis System) code and optimization algorithm of the PIAnO (Process Integration, Automation and Optimization) code. The FANDAS code is used as fan design program to design 3D fan rotor blade geometry and to predict designed fan’s performance and efficiency, and it is also used as simulation engine for fan design optimization problem. The PIAnO code is used as optimization program to apply a function-based optimization algorithm to the FANDAS code and to find the optimal fan design solution for efficiency maximization. In this optimization study, spanwise camber, stagger angles and chord lengths of axial flow fan are selected as design variables and the design constraints are set to design flow capacity, total pressure, power and blade angles, solidities. Through the design optimization by combining the FANDAS and the PIAnO codes, optimal fan rotor blades are obtained and then they are coupled with existing outlet guide vanes to construct the final fan stage. Computational fluid dynamics (CFD) analyses are conducted to verify the performance and efficiency of the optimal fan design, and the CFD calculation results are matched well with the FANDAS predictions for performance and efficiency of optimal fan. The CFD results also show that the optimal fan design gives the efficiency improvement of about 6.7% compared to the initial design. Furthermore, the FANDAS performance predictions of the optimal fan under variable-pitch conditions show that the optimal fan can be operated with wide flow capacity range between 2000 and 5000 m 3/min and high efficiency above 80 % by adjusting fan rotor blade pitch angle.
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Paper Nr: 51
Title:

Joint Stiffness Adjustment of a Pneumatic Driven Exoskeleton
Authors:

Pavel Venev, Dimitar Chakarov and Ivanka Veneva
Abstract: The work studies an exoskeleton on the upper limb intended for rehabilitation and training. To meet the requirements of rehabilitation exoskeletons for transparency on the one hand and efficiency on the other, a pneumatic actuation with a wide range of control pressure is offered. The subject of the work is the development of a pneumatic drive that allows simultaneous adjustment of stiffness and torque in the joints of the exoskeleton. For this purpose, pressure in the cylinder chambers both higher and lower than atmospheric is used. The work presents the structure of the exoskeleton and a model of pneumatic actuation in the joints of the exoskeleton. Equations are derived for the torque and joint stiffness resulting from the elasticity of the air in the closed chambers of the pneumatic cylinders. The work proposes one approach to adjust the stiffness at certain joint position. In this position, the joint torque is varied by creating pressure profiles in the two chambers, so the joint stiffness is adjusted in addition to the joint torque. The change in joint torque due to elastic deviations from the set position is also evaluated. An example of compensating gravity loads and providing transparency through pneumatic actuation is shown.
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Paper Nr: 54
Title:

Towards a Digital Twin Simulation for Cycle Times Analysis in a Cyber-Physical Production System
Authors:

Vinicius Barbosa, Rui Pinto, João Pinheiro, Gil Gonçalves and Anabela Ribeiro
Abstract: The Digital Twin concept refers to the virtual representation of physical assets and is an emerging technology in the I4.0 paradigm for digital transformation. Digital Twin integration with discrete-event simulation models is the key enabler to create digital models of real dynamic manufacturing systems. Usually, simulation alone does not support optimization and advanced analytics, especially considering the lack of real-time data from the physical system. One of the biggest challenges for manufacturers is to enable integration between simulation models and Digital Twin technology for real-time data exchange, such as monitoring and optimization of cycle times and reducing waste. The lack of standards to build the Digital Twin concept explains this issue. This study addresses this problem by proposing a communication interface between a Python-based Digital Twin (DINASORE) and a Java-based AnyLogic simulation model. DINASORE supports Function Blocks compliant with the IEC 61499 standard and external communication using OPC UA. Cycle time data is collected automatically by the Digital Twin in the Edge layer of the Cyber-Physical Production System and made available to the simulation model via OPC UA. Results show that it is possible to analyse the production process and propose optimizations in real-time.
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Paper Nr: 70
Title:

Implicit Multilinear Modeling of Air Conditioning Systems
Authors:

Torben Warnecke and Gerwald Lichtenberg
Abstract: The publication explores the applicability of implicit multilinear model approaches in air conditioning systems. Implicit multilinear time-invariant models offer a structure that allows for the representation of most of the fundamental physical equations of HVAC systems. Since the implicit multilinear time-invariant model class is closed, it enables a component-based modeling approach to represent various types of HVAC systems with different combinations of components. Multilinear time-invariant models are usually represented by tensors. With HVAC-Systems having a large number of inputs and states, the models can be efficiently represented in a decomposed manner, resulting in a matrix representation. As an example, the model of a precision climatization hutch with a PI controller is derived and simulated.
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Paper Nr: 39
Title:

Robust Finite-Time Control of a Multirotor System via an Improved Optimized Homogeneous Twisting Control: Design and Validation
Authors:

Aimen A. Messaoui, Omar Mechali, Ali Z. Messaoui and Iheb E. Smaali
Abstract: This paper presents theoretical and practical aspects of finite-time tracking control of a multirotor attitude system. The vehicle is subjected to matched lumped disturbances. Inspired by the homogeneity theory, an Improved Optimized Homogeneous Twisting Control (IOHTC) is proposed to deal with the fast dynamics’ response of the attitude states. Within the designed control scheme, the chattering issue of discontinuous Sliding Mode Control (SMC) techniques can be mitigated due to the continuous control signal that is generated by a non-switching function in the form of 〖|x|〗^α sign(x),x ∈ R,α ∈ R+. Besides, finite-time convergence of the system’s states can be ensured to achieve accurate control. It is worth mentioning that the disturbance rejection does not require the design of an observer since the control law integrates a compensation term. Stability analysis of the closed-loop system is rigorously investigated by using a homogeneous Lyapunov function. From the practical aspect, the control algorithm is embedded onboard the quadrotor’s autopilot through a model-based design approach. A comparative study is made involving the proposed IOHTC strategy and three other controllers. The obtained results show that the suggested controller yields performance improvement regarding accuracy and robustness. Meanwhile, the chattering effect of conventional SMC is remarkably alleviated.
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Paper Nr: 46
Title:

Using Analytical Methods and Simulation to Estimate the Magnitude of Errors in Calculations for Recovery in Washed Red Blood Cells
Authors:

John Blake, Jason Acker and Cherie Mastronardi
Abstract: Canadian Blood Services produces a modified blood product, called washed red blood cells. RBCs are washed to reduce potential transfusion reactions in vulnerable populations. Quality control standards require that at least 75% of the red cells in a unit are retained through the washing process. However, field reports suggest that cell recovery values greater than 100% can be observed. The purpose of this study is to analyse the propagation of error in the washing process and to determine if values exceeding 100% are reasonable, given the accuracy of the equipment in use. Employing analytical techniques and simulation methods, it was found that recovery rates in excess of 100% are possible, but that any calculated value exceeding 102% is unlikely and should be investigate for process errors.
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