SIMULTECH 2022 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: 20
Title:

A Modified Polynomial Preserving Recovery Technique
Authors:

M. Barakat, W. K. Zahra and A. Elsaid
Abstract: In this work, the polynomial preserving recovery method is enhanced by increasing the order of the fitting polynomial within the same patch. This is achieved by adding more sample points inside the elements of the patch then substitute them in the discretized form of the differential equation. These sample points are the set of superconvergent points of the patch under consideration. Numerical results show that the recovered gradient at the nodes with linear elements is superconvergent. The proposed method improves the accuracy of the recovered gradient over the domain of the solution with the same rate of convergence of the polynomial preserving recovery technique.
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Paper Nr: 24
Title:

Household Structure Projection: A Monte-Carlo based Approach
Authors:

Wei P. Goh, Shu-Chen Tsai, Hung-Jui Chang, Ting-Yu Lin, Chien-Chi Chang, Mei-Lien Pan, Da-Wei Wang and Tsan-Sheng Hsu
Abstract: The kernel of an agent based simulation system for spreading of infectious disease needs a so called household structure (HSD) of the area being simulated which contains a list of households with the age of each member in the household being recorded. Such a household structure is available in a Census that is usually released every 10 years. Previous researches have shown the changing of the household structure has a great impact on disease spreading patterns. It is observed that the changing of the household structure e.g., the average citizen ages and household size, is at a faster speed. However, serious infectious diseases, such as SARS (year 2002), H1N1 (year 2009) and COVID-19 (year 2019), occur with a higher frequency now than previous eras. For example, it would be bad to use HSD2010 built using Census 2010 to simulate COVID-19. In view of this situation, we need a better way to obtain a good household structure in between the Census years in order for an agent-based simulation system to be effective. Note that though a detailed Census is not available every year, aggregated information such as the number of households with a particular size, and the number of people of a particular age are usually available almost monthly. Given HSDx, the household structure for year x, and the aggregated information from year y where y > x, we propose a Monte-Carlo based approach “patching” HSDx to get an approximated HSDy. To validate our algorithm, we pick x and y = x+10 which both Censuses are available and find out the root-mean-square error (RMSE) between Census’s HSDy and generated HSDy is fairly small for x = 1990 and 2000. The spreading patterns obtained by our simulation system have good matches. We hence obtain HSD2020 to be used in your system for studying the spreading of COVID-19.
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Paper Nr: 28
Title:

Attention for Inference Compilation
Authors:

William Harvey, Andreas Munk, Atılım G. Baydin, Alexander Bergholm and Frank Wood
Abstract: We present a neural network architecture for automatic amortized inference in universal probabilistic programs which improves on the performance of current architectures. Our approach extends inference compilation (IC), a technique which uses deep neural networks to approximate a posterior distribution over latent variables in a probabilistic program. A challenge with existing IC network architectures is that they can fail to capture long-range dependencies between latent variables. To address this, we introduce an attention mechanism that attends to the most salient variables previously sampled in the execution of a probabilistic program. We demonstrate that the addition of attention allows the proposal distributions to better match the true posterior, enhancing inference about latent variables in simulators.
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Paper Nr: 39
Title:

Modeling of Modified Vehicle Crashworthiness using a Double Compound Pendulum
Authors:

Gulshan Noorsumar, Svitlana Rogovchenko, Dmitry Vysochinskiy and Kjell G. Robbersmyr
Abstract: Vehicle crash modeling has been a challenge for researchers for several decades. Occupant injury prevention and prediction is a critical area within vehicle safety design. The modeling of material failure in structural members during a full frontal crash has been presented in this paper. This study presents a Lumped Parameter Model (LPM) with an elastic double compound pendulum replicating the impact kinematics. The model defined using Lagrangian formulation; presents a novel methodology to represent material fracture caused due to heat affected zones or welding in Ultra High Strength Steels (UHSS) in a non-linear crash event. The material fracture leads to rotation of the vehicle; presented in the form of torsional springs in the LPM developed in this study. The Simulink model has been validated with a finite element simulation and shows good correlation to predict parameters crucial to design for occupant protection in a vehicle crash.
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Paper Nr: 42
Title:

Intelligent Control of Construction Manufacturing Processes using Deep Reinforcement Learning
Authors:

Ian Flood and Paris L. Flood
Abstract: This paper is concerned with the development and evaluation of a reinforcement learning approach to the control of factory based construction operations. The unique challenges associated with controlling construction work is first discussed: uneven and uncertain demand, high customization, the need to fabricate work to order, and a lack of opportunity to stockpile work. This is followed by a review of computational approaches to this problem, specifically those based on heuristics and machine learning. A description is then given of a model of a factory for producing precast reinforced concrete components, and a proposed reinforcement learning strategy for training a neural network based agent to control this system. The performance of this agent is compared to that of rule-of-thumb and random policies for a series of protracted simulation production runs. The reinforcement learning method was found to be promising, outperforming the two competing strategies for much of the time. This is significant given that there is high potential for improvement of the method. The paper concludes with an indication of areas of proposed future research.
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Paper Nr: 43
Title:

Optimization of the Bottleneck Caused by Stacker Cranes in Dynamic Hybrid Pallet Warehouses and Investigation of the Influence of the Input/Output Area on Performance
Authors:

Giulia Siciliano, Anna Durek-Linn and Johannes Fottner
Abstract: The need for ever-higher performance in pallet storage systems has led to the development of Dynamic Hybrid Pallet Warehouses (DHPW). DHPWs are created by either hybridizing a stacker crane-based warehouse with shuttles, or by hybridizing a shuttle-based warehouse with stacker cranes. One limiting factor in both categories is the bottleneck caused by having multiple stacker cranes in a single aisle. In this paper, we demonstrate that, by using the proper control algorithms, the stacker crane bottleneck can be alleviated in relation to the second DHPW category – almost to the point of reaching the performance that would be obtained by introducing an additional stacker crane. Finally, we illustrate how the design of the loop on the base tier has an increasing influence on the range of bottleneck improvement as the number of shuttles increases.
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Paper Nr: 47
Title:

Generating a Multi-fidelity Simulation Model Estimating the Models’ Applicability with Machine Learning Algorithms
Authors:

Christian Hürten, Philipp Sieberg and Dieter Schramm
Abstract: Having access to large data sets recently gained increasing importance, especially in the context of automation systems. Whether for the development of new systems or for testing purposes, a large amount of data is required to satisfy the development goals and admission standards. This data is not only measured from real-world tests, but with growing tendency generated from simulations, facing a trade-off between computational effort and simulation model fidelity. This contribution proposes a method to assign individual simulation runs the simulation model that has the lowest computation costs while still being capable of producing the desired simulation output accuracy. The method is described and validated using support vector machines and artificial neural networks as underlying vehicle simulation model classifiers in the development of a lane change decision system.
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Paper Nr: 54
Title:

Analyzing Age of Information in Prioritized Status Update Systems using Probabilistic Hybrid Discipline
Authors:

Tamer E. Fahim, Sherif I. Rabia, Ahmed A. El-Malek and Waheed K. Zahra
Abstract: The ubiquitous deployment of the internet of things technology engenders great attention to the real-time status update systems. However, the real-life situation implies the service differentiation between sources according to their sensitivity, a problem that is rarely addressed in the literature. This situation is to be handled classically by adopting the preemption or non-preemption service disciplines. In any of these disciplines, an improvement is yielded for some specific classes with a severe degradation for the others. To address this paradox, we propose a probabilistic hybrid service discipline, by which the decision of preemption for each class is controlled by a probabilistic parameter. The stochastic hybrid system approach is employed to analyze the average age of information for each class. A numerical study of a three-class prioritized network demonstrates the significance of the proposed model to compromise the performance of all classes even in the worse traffic loading conditions. Moreover, three different approaches are proposed to adjust the probabilistic hybrid parameters for more promising results.
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Short Papers
Paper Nr: 10
Title:

SIS-ASTROS: An Integrated Simulation System for the Artillery Saturation Rocket System (ASTROS)
Authors:

Cesar T. Pozzer, João B. Martins, Lisandra M. Fontoura, Luis L. Silva, Mateus B. Rutzig, Raul C. Nunes and Edison Pignaton de Freitas
Abstract: Simulation is a valuable technique used by the military to support personnel training. A trend in current military training is the combination of different types of simulation in an integrated setup. Observing this trend, the Brazilian Army is making efforts to develop integrated simulation solutions. This paper presents the conception of an integrated simulation system of the Brazilian Army Artillery called SIS-ASTROS. Besides the integrated setup connecting different types of simulators, a major contribution in the scope of the SIS-ASTROS is the presentation of the virtual tactical simulator to train mid-rank officers in activities regarding the coordinated deployment of ASTROS artillery batteries on the battlefield. This simulator not only addresses constructive simulation aspects but also virtual ones. Due to its design, the conception of this simulator on its own is already an important innovation. This paper presents the key components of the integrated simulation system, highlighting the main contributions in the research and development of the virtual tactical simulator.
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Paper Nr: 12
Title:

Simulation Driven Development Process Utilizing Carla Simulator for Autonomous Vehicles
Authors:

Minseok Won and Shiho Kim
Abstract: We present a new approach to design the system of autonomous vehicles based on practical test scenarios in simulation. As the level of driving automation functions advances, various events and problems have occurred in many unexpected or unseen situations, so the design of autonomous driving systems is required to be more robust and sufficiently practical. We propose a Simulation Driven Development Process (SDDP) based on practical test scenarios in a simulation environment. We described the Euro NCAP test scenarios and harsh conditions using the ASAM OpenSCENARIO format and implemented them using the Carla simulator. We can verify how realistic and functional the system requirements are through the simulation results. It is also possible to derive numerical values optimized for Advanced Driver Assistance System (ADAS) function safety from the simulation results, and we can get the requirements robust and improve ADAS performance by applying them to V-model. We created the Euro NCAP AEB-VRU test scenario to design an effective AEB function. We used RoadRunner to build the test road and used ScenarioRunner to render the test scenario written by ASAM OpenSCENARIO format according to Euro NCAP test requirement. The result of AEB-VRU has been investigated under normal conditions and harsh environments as well. This work shows that we can extend the safety of the AEB function by changing the vehicle speed according to situation perception, which indicates the possibility of utilization of a simulator for autonomous vehicle system design.
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Paper Nr: 13
Title:

Assessment of the RSS Model Suitability using Graph Neural Network based on a Naturalistic Driving Dataset
Authors:

Sungmoon Ahn and Shiho Kim
Abstract: We propose a method to evaluate the RSS model using data obtained from real roads. Recently, the Responsibility-Sensitive Safety (RSS) model representing the minimum safety distance has been proposed. After that, there were studies to evaluate the RSS model using simulators. Most virtual simulation studies showed that the RSS model guarantees safety but adversely affects traffic flow by estimating the distance too long than necessary. We evaluated the RSS model using data obtained in natural situational environments, unlike previous studies. First, we found correlations representing distances between vehicles from the data using Graph Neural Networks. Using the obtained correlations, we expressed it as a mathematical model through symbolic regression. As a result of comparing the model we found with the RSS model, we verified that the RSS model has a significant trade-off between safety and traffic flow.
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Paper Nr: 15
Title:

Systematic Literature Review of Data Exchange Strategies for Range-limited Particle Interactions
Authors:

Theresa Werner, Ivo Kabadshow and Matthias Werner
Abstract: Molecular dynamics simulations (MDS), no matter in which form, have always spent a lot of effort on the time-consuming part of direct particle-to-particle interactions (O(N 2 )). Even if the interaction radius of each particle is limited, it remains the most time-critical part, especially when increasing the number of compute nodes to calculate on. This Systematic Literature Review (SLR) focuses on the spatial decomposition approach to MDS and ways to optimize its data exchange. We gathered and compared available concepts related to range-limited interactions and investigated whether they show similarities and how those can be categorized. Based on the findings, we can summarize that all communication schemes are derived from the same basic idea, the so-called shift communication. The concepts differ in which data is communicated and how nodes calculate the forces between particle pairs. Two categories can be distinguished here: home-box-centric and neutral territory methods.
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Paper Nr: 21
Title:

Design and Modeling of a Numerical Simulator of a Mini-hydropower for Performance Characterization of the Turbine Type of Francis, Cross-flow and Pelton
Authors:

Francis Kifumbi, Guyh D. Ngoma, Python Kabeya and Clement N. Umba-di-Mbudi
Abstract: This research work deals with the design of a numerical simulator which consists of an upstream reservoir, a penstock, a Francis turbine, a cross-flow turbine, a Pelton turbine, and a draft tube. This simulator can allow to better study the performance of a mini-hydroelectric plant while investigating the parameters involved with the cavitation phenomenon for the Francis turbine. From existing reference data of the gross head, the flow rate and the rotating speed for the Francis turbine, the cross-flow turbine and the Pelton turbine, the geometrical parameters of the turbine runners were calculated using inter alia the specific speeds, the turbines diagrams and the empirical equations. Moreover, the equations of continuity and Navier-Stokes are applied to obtain by means of the ANSYS-code the fields of the liquid flow velocity and the pressure. The numerical results achieved for the turbine output power and the efficiency were compared with the experimental results from the existing test benches of turbines in the turbomachinery facility of the Engineering School at the University of Quebec in Abitibi-Témiscamingue (UQAT). Also, the effect of the cavitation on the efficiency of the Francis turbine account for the draft tube height is analyzed. The impact of the draft tube height of the Francis turbine and the jet width of the cross-flow turbine on the output power and the efficiency is examined.
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Paper Nr: 22
Title:

Distributed Simulations of DNA Multi-strand Dynamics
Authors:

Frankie Spencer, Usman Sanwal and Eugen Czeizler
Abstract: In a recent study, Spencer et al. 2021, we have proposed a computational modeling framework for DNA multi-strand dynamics implemented using the agent- and rule-based modeling methodology. While this modeling methodology allows for compact representations for systems with large numbers of different species and complexes, such as the case of self-assembly systems, one of its main drawbacks concerns its scalability. Since each agent is individually represented and modeled in the system, the framework becomes slow when dealing with tens- and hundreds of thousands of individual components. In this study we introduce a method to parallelize the computational modeling process by distributing it over several CPU’s. We show that such multi-thread models remain equivalent to their sequential counterpart, while the speedup of the computational process can reach even a one-fold increase.
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Paper Nr: 23
Title:

A Novel Approach to Functional Equivalence Testing
Authors:

Ranjith Jayaram and Jetendra K. Borra
Abstract: In Model Based Software Development, sometimes it is required to transform the model and respective software code from one platform to another platform that is having different tool setup. For example, transforming a legacy model to the newly adapted architecture or transforming a model supplied from third party to production model and so on. Once the model is adapted to the new platform, there will be changes in the model, hence the code generated from the model can be different from that of legacy artifacts. After transformation activity, developers have to be sure that the new model and code is functionally equivalent to that of the old set. It is also important from quality standpoint that there are no deviations in the functionality after migration. With most of the compilation toolchains being closed source it is difficult to identify the issues during migration unlike in systems engineering. Achieving functional equivalence between the production artifacts and the reference/legacy artifacts provide conformity to the engineer of successful migration. In this paper, a methodology is proposed in which even with non-availability of few artifacts from legacy setup, functional equivalence is achieved using Model in loop and software in loop simulation results matchup. The method and the results are presented in the paper with two different use cases.
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Paper Nr: 25
Title:

Reduced CP Representation of Multilinear Models
Authors:

Niklas Jöres, Christoph Kaufmann, Leona Schnelle, Carlos C. Yáñez, Georg Pangalos and Gerwald Lichtenberg
Abstract: Large and highly complex systems can be found in various application areas. Modeling these systems requires appropriate representation of the underlying phenomena. Furthermore, due to the large dimensions efficient simulation and low memory requirements are needed for such models. Multilinear modeling is a promising approach to address these challenges. In this paper, we introduce a reduced canonical polyadic (CP) representation for implicit time-invariant multilinear (iMTI) models. This representation is capable of storing large models with very low memory requirements. This is particularly useful for efficient analyses of large systems with numerous inputs and states.
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Paper Nr: 26
Title:

Performance Enhancement of Formula One Drivers with the Use of Group Driven Learning
Authors:

A. A. Moghaddar, F. A. Bukhsh and G. J. Bruinsma
Abstract: Within motorsports less experienced drivers lack pace and performance compared to their peers. Training these drivers requires time, which, due to the regulations and resources, teams often do not have. Less experienced drivers are expected to perform at the same level as experienced drivers. This paper has the aim of analyzing the abilities and performances of both drivers within a Formula One team to redesign the driver training method. The focus is to provide drivers with real-time insights and feedback on their performance during a simulator training session. By using a combination of the principles of process mining and statistical analysis, data markers are created on the track. Based on the differences in telemetry, visual feedback is provided to the driver. Throughout the research, this manner of training has proven to be promising. Drivers showed an increase in their overall performance and an increase in car control and confidence. Despite these promising results more experiments need to be done to guarantee a consistent outcome and to prove the effectiveness of this training program. To continue developments, further research can be conducted on the topic of visualization and communication.
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Paper Nr: 27
Title:

SwarmFabSim: A Simulation Framework for Bottom-up Optimization in Flexible Job-Shop Scheduling using NetLogo
Authors:

M. Umlauft, M. Schranz and W. Elmenreich
Abstract: This paper models and simulates a semiconductor production plant organized by the job-shop principle as a self-organizing system using swarm intelligence algorithms in an agent-based simulation tool. We model a set of agents, including machines, workcenters, lots and processes. To simulate our model, we use NetLogo, one of the most widely used agent-based simulation platforms. The framework for the simulation was built as a structured system of code modules using a callback architecture that allows to exchange the used swarm algorithm easily. The user can configure their own fab model and simulations via the user interface and configuration files. The resulting log files include several key performance indicators: makespan, average flow factor, and lot tardiness. We offer the framework including sample swarm algorithms running on NetLogo version 6.1 and later as open source on GitHub.
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Paper Nr: 36
Title:

Designing Naturalistic Simulations for Evolving AGI Species
Authors:

Christian Hahm
Abstract: This paper identifies basic principles for designing and creating evolutionary simulations in the context of general-purpose AI (AGI). It is argued that evolutionary simulations which employ certain nature-inspired principles can be used to evolve increasingly intelligent AGI species. AGI frameworks are particularly suited for evolutionary experiments involving embodiment since they can operate arbitrary evolved bodies. Once a designer manually defines a simulation’s initial conditions, each run is an automated exploration of a novel subset of species. In this way, naturalistic simulations generate huge amounts of empirical data for evaluating the robustness of AGI frameworks, along with many promising species that can be later instantiated in other simulated environments or even physical robots for practical applications.
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Paper Nr: 37
Title:

Conceptual Approach for Optimizing Air-to-Air Missile Guidance to Enable Valid Decision-making
Authors:

Philippe Ruther, Michael Strohal and Peter Stütz
Abstract: In this paper, we briefly introduce a concept on how the workflow of a pilot in a beyond visual range mission can be divided into different tasks in order to mimic the workflow in the behavioural control of adversary computer generated forces in training simulations. An essential part of fighter pilots’ workflow is the decision-making process, in which they must weigh opportunities against risks. Particularly in the weapon delivery task, valid data are a basic prerequisite for making a confident decision when weighing one’s opportunities against potential risks. Concerning the applicability of artificial intelligence methods, the optimization of a missile's trajectory is used as an example to examine methods that allow an estimation of one’s chances based on valid data to enable valid decision-making. For this purpose, we briefly introduce methods of optimal control and in particular deep reinforcement learning. In the future, we intend to use data generated by optimal control to validate the data provided by deep reinforcement learning methods as a basis for explainable decision-making in training simulation and threat analysis.
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Paper Nr: 38
Title:

Analysis of Differential Algebraic Equation Systems for Connecting Energy Storages of Generally Valid Functional Mock-up Units
Authors:

Meik Ehlert, Christian Henke and Ansgar Trächtler
Abstract: Functional Mock-up Units (FMU) refer to tool-independent models exported from their original simulation tools. They enable component manufacturers and system integrators to exchange models across entire production chains to validate solutions virtually. However, since system equations cannot be accessed or modified in an FMU, numerical challenges can arise, especially when coupling similar energy storages. In this paper, therefore, Differential Algebraic Systems of Equations are analyzed for their suitability for FMU couplings. It is shown how such systems of equations can be described in a general way and how suitable coupling constraints for FMUs are chosen. Subsequently, three solution approaches are presented and analyzed for their feasibility with FMUs.
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Paper Nr: 40
Title:

Sampling Strategies for Static Powergrid Models
Authors:

Stephan Balduin, Eric M. Veith and Sebastian Lehnhoff
Abstract: Machine learning and computational intelligence technologies gain more and more popularity as possible solution for issues related to the power grid. One of these issues, the power flow calculation, is an iterative method to compute the voltage magnitudes of the power grid’s buses from power values. Machine learning and, especially, artificial neural networks were successfully used as surrogates for the power flow calculation. Artificial neural networks highly rely on the quality and size of the training data, but this aspect of the process is apparently often neglected in the works we found. However, since the availability of high quality historical data for power grids is limited, we propose the Correlation Sampling algorithm. We show that this approach is able to cover a larger area of the sampling space compared to different random sampling algorithms from the literature and a copula-based approach, while at the same time inter-dependencies of the inputs are taken into account, which, from the other algorithms, only the copula-based approach does.
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Paper Nr: 41
Title:

Behaviour Modelling of Computer-Generated-Forces in Beyond-Visual-Range Air Combat
Authors:

Fabian Reinisch, Michael Strohal and Peter Stütz
Abstract: Beyond-visual-range (BVR) engagements are getting more and more frequent in modern air combat. One of the key challenges for pilots here is manoeuvre planning, which reflects their decision-making capacity and can determinate success or failure. To ensure pilot training employing virtual BVR air combat simulations yields success, high accuracy levels of the computer-generated forces (CGFs) are essential. To achieve this, it is substantial to not only replicate and simulate the physical properties of the entities to a sufficient degree, but also to provide them with a close-to-human-like behaviour. In this paper, we propose a general concept to tackle these challenges: First, we introduce flight motion dynamic models (aircraft, missiles, chaff) as well as a jammer. Then, we analyse the workflow of a typical beyond-visual-range air combat engagement, separating it into attack, self-defence and decide. Within this context, we introduce Behaviour Trees as a method to model these tasks and explain its benefits. Further plans include the verification and validation of the CGF behaviour within future experimental campaigns that consist of human-controlled opponent aircrafts (pilots) flying against the CGFs. Finally, we provide an outlook to future work in where we intent to employ reinforcement learning for tasks containing many degrees of freedom.
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Paper Nr: 49
Title:

A Deep Learning Simulation Framework for Building Digital Twins of Wind Farms: Concepts and Roadmap
Authors:

Subodh M. Joshi, Thivin Anandh and Sashikumaar Ganesan
Abstract: Simulation-based Digital Twins are often limited by the difficulties encountered in the real-time simulation of continuous physical systems, for example, fluid flow simulations in complex domains. Classical methods used to simulate such systems, such as the mesh-based methods, typically require state-of-the-art computing infrastructure to get a rapid estimation of the trajectory of the system dynamics if the problem size is large. We propose a simulation framework comprising of a Physics Informed Neural Network (PINN) and a model order reduction strategy based on the Dynamic Mode Decomposition (DMD) technique for rapid simulation of fluid flows, such as air, in complex domains. This framework is primarily targeted at realizing a Digital Twin of a wind farm in terms of the aerodynamics aspects. However, the framework will be flexible and capable of creating simulation-based Digital Twins of other systems involving continuous physics. The reduced order model aims to make this framework lightweight, such that a trained model will be able to run even on compact edge devices. In this paper, we present the building blocks of this framework, a few key concepts, and a roadmap for completing the framework. We illustrate our approach with the help of an example in transient heat transfer.
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Paper Nr: 50
Title:

Extending LoRaEnergySim Simulator to Support Interference Management under Multi-Gateway IoT Scenarios
Authors:

Daniele Stumpo, Floriano De Rango and Francesco Buffone
Abstract: Internet of Things (IoT) is gaining more impact on our lives and has been increasingly used. It allows several wireless devices to be connected, and their distance can range from a few inches to many miles. New IoT technologies such as LoRa are emerging allowing energy efficient wireless communication over exceptionally long distances. So, it is particularly important to evaluate its performance through simulations. At this purpose, it is possible to find several tools and simulators for LoRa technology. All of them present distinctive features and are written with different programming languages with the possibility to enable and disable different features. In this paper it is analysed in detail the Simulator LoRaEnergySim, which allows the creation of a network with only one Gateway (GTW). In addition, the simulator is extended considering the case of Multi-GTW presence with very high IoT node density and considering all interference aspects that can be related to this new scenario. Besides, the extended simulator, considers now the imperfect orthogonality of the Spreading Factor (SF) not fully supported in the previous simulator version with the aim to consider more realistic simulations.
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Paper Nr: 53
Title:

Assistance System for the Interactive Machine Adjustment (of a Tufting Machine)
Authors:

Dominik Huesener and Jürgen Rossmann
Abstract: The paper illustrates how a digital twin, a virtual representation of a physical asset, and simulation software can be used to find best operating parameters and guide an operator through the adjustment process of the machine. The user interacts with the digital twin either through a 3D GUI or using augmented reality, which allows to display information of the digital twin next to the real twin. The machine is equipped with sensors that continuously measure the state of the machine and are connected to the digital twin through EtherCAT connection. The interactive system gives intuitive instructions that reduce the expert knowledge that is needed such that even trainees can operate the machine and digitizes the process for experienced workers.
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Paper Nr: 1
Title:

SNAP: Scalable Networkable ABM Platform for the Social Sciences
Authors:

Christopher M. Conway
Abstract: Agent-Based models (ABMs), although increasingly useful and widespread, are underused in social science. I show that extant “user-friendly” platforms are not well suited for social science research, while platforms that would support such research are not easy to use. I outline requirements for a sufficiently powerful, easy-to-use system, which requires no programming skills on the part of the user. I explain the design and development of an ABM which features a GUI and a menu of agents, statistics, and visualizations which are commonly desired. This system is robust enough for social science research; it is portable, flexible, and customizable. Users will have access to pre-designed complex and recursive agents, running distributed across all available processors, as well as user-selected geometries and time clocks. Progress and future work are discussed.
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Paper Nr: 4
Title:

On the Simulation of Electrochemistry Aspect of Electrochemical Spark Micromachining Process
Authors:

Anjali V. Kulkarni
Abstract: Electrochemical spark micromachining (ECSMM) process, an advanced machining process is investigated to understand process mechanism. The material removal mechanism in ECSMM is a complex phenomenon due to its multiphysics and transient nature. Experimental measurements of online current and voltage have been performed simultaneously. Different sequential operational stages in one single spark cycle have been identified in the light of the transient measurements. The Semiempirical electrical impedances during these identified operational stages have been formulated and compared with those derived by using measured online current and voltage data. Only the impedance results during electrochemical phase in a single spark cycle have been reported here. In case of ECS, considering the kinetics at the electrolyte and electrode interfaces, the effective equivalent circuit is derived. The charge transfer resistance in the equivalent circuit during the electrochemical phase is found by performing impedance spectroscopy using COMSOL multiphysics modeling software. For this 1-d model of the electrochemical process is developed using secondary current distribution. It is for the first time that COMSOL study has been attempted in analyzing the physics behind the material removal phenomenon mainly during the electrochemical operational phase of ECSMM. The modeled and measured impedances show close similarities.
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Paper Nr: 5
Title:

Principal Component Analysis in Gas Transport Simulation
Authors:

Anton Baldin, Kläre Cassirer, Tanja Clees, Bernhard Klaassen, Igor Nikitin, Lialia Nikitina and Sabine Pott
Abstract: In this paper, an analysis of the error ellipsoid in the space of solutions of stationary gas transport problems is carried out. For this purpose, a Principal Component Analysis of the solution set has been performed. The presence of unstable directions is shown associated with the marginal fulfillment of the resistivity conditions for the equations of compressors and other control elements in gas networks. Practically, the instabilities occur when multiple compressors or regulators try to control pressures or flows in the same part of the network. Such problems can occur, in particular, when the compressors or regulators reach their working limits. Possible ways of resolving instabilities are considered.
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Paper Nr: 9
Title:

An Innovative Partitioning Technology for Coupled Software Modules
Authors:

Bernhard Peters, Xavier Besseron, Alice Peyraut, Miriam Mehl and Benjamin Ueckermann
Abstract: Multi-physics simulation approaches by coupling various software modules is paramount to unveil the underlying physics and thus leads to an improved design of equipment and a more efficient operation. These simulations are in general to be carried out on small to massively parallelised computers for which highly efficient partitioning techniques are required. An innovative partitioning technology is presented that relies on a co-located partitioning of overlapping simulation domains meaning that the overlapping areas of each simulation domain are located at one node. Thus, communication between modules is significantly reduced as compared to an allocation of overlapping simulation domains on different nodes. A co-located partitioning reduces both memory and inter-process communication.
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Paper Nr: 33
Title:

An Interactive System for Capturing Users’ Qualitative Preferences in Recommender Systems
Authors:

Kushal Dave and Malek Mouhoub
Abstract: We propose a new interactive system for eliciting and learning users’ qualitative preferences. These preferences are modelled as a conditional preference network (CP-net). The CP-net is a known graphical model representing qualitative and conditional preferences in a compact form. User’s preferences are first captured through a learning method based on membership queries. These preferences are then compiled into a list of conditional preference statements. The CP-net is finaly generated from this list. We are also incorporating a collaborative technique so that when a CP-net of a given user is generated, the latter will receive suggestions based on similarities with other users.
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Paper Nr: 44
Title:

How Do We Know What We Don’t Know? Making Assumptions about Data in Simulation Studies
Authors:

Andrew Greasley
Abstract: The first activity of a simulation study is to define the problem situation which provides the context for the development of the conceptual model. This involves making assumptions about the real world and the outcome of this stage is a system description. In this article we discuss assumptions regarding data acquisition when we are faced with a lack of data about the real world, and data awareness, categorised here as explicit assumptions (assumptions regarding data that we are aware of) and implicit assumptions (assumptions regarding data that we are not aware of). The consequences of our ability to acquire and be aware of data is presented as a combination of our known and unknown knowledge of that data. The purpose is to highlight the issues surrounding making assumptions in discrete-event simulation studies and to suggest further work when considering implicit assumptions.
Paper Nr: 55
Title:

Simulating Theoretical Jerk by Numerical Modelling for Greyhound Racing
Authors:

Md. I. Hossain and David Eager
Abstract: This paper presents the jerk dynamics of a racing greyhound running alone by simulating the centrifugal acceleration for different race scenarios and track path design options. Simulation parameters were defined from the real-world greyhound track designs and greyhound race data to provide relevant results for race conditions. Virtual race scenarios were created to achieve maximum results. By simulating greyhound strides as discrete events, the theoretical jerk was calculated. The results show how different track design conditions and race scenarios can affect greyhound dynamics for the track bends. This can be applied to better understand and improve track design for improved dynamics with a view to reduce the frequency and severity of injuries.
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Paper Nr: 56
Title:

Monte Carlo Simulation of Pathogen Reduced Platelet Production
Authors:

John T. Blake and Ken McTaggart
Abstract: All blood products in Canada undergo testing for transmissible diseases and bacterial contamination. As a result, the risk of a transfusion related infection is estimated at less than 1 in 47,000. Nevertheless, there are infectious agents that are not screened for, as well as the potential for infection from emerging pathogens that are either unknown, or for which screening tests have not been developed. Thus, Canadian Blood Services is introducing pathogen reduction (PR) technologies to further increase the safety of the blood supply. The focus of this study is to identify key input parameters for the PR process and to estimate output dose parameters for the units produced. The unit volume and platelet yield from combining buffy coat platelets into a pool are estimated via Monte Carlo simulation. The value of sorting input buffy coat units according to estimated platelet yield, prior to illumination, is determined. Finally, the model estimates the effects of two different sorting algorithms on output quality control metrics. The results of the study found that no process changes were required to ensure input units meet input PR process guidelines. However, sorting input units according to platelet yield could significantly improve the proportion of units meeting quality control metrics.
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Area 2 - Simulation Technologies, Tools and Platforms

Full Papers
Paper Nr: 6
Title:

Hierarchical Terrain Representation and Flood Fill-based Computation of Large-Scale Terrain Changes for Agent-based Simulations
Authors:

Luis A. L. Silva, Evaristo J. Nascimento, Eliakim Zacarias, Raul C. Nunes and Edison P. Freitas
Abstract: Modern virtual training benefits from the recent advances in Agent-Based Modelling and Simulation (ABMS), making it possible to use real-world dynamic terrain scenarios that enhance the users learning from agent-based simulations. An important issue for distributed ABMS systems is the possibility of using terrain services that promptly compute large-scale terrain map changes as a result of natural phenomena such as river floods and wildfires. Performing the alterations in terrain maps is challenging since they depend on the combination of terrain features and terrain sizes. To address this problem, this work proposes the use flood fill-based techniques along with the hierarchical QuadTree approach for the terrain representation. We show that these techniques are essential to promptly compute the effects of the changes on a large number of nodes of the hierarchical map representation that captures the terrain features in different levels of detail. Also, a way to store and recover the QuadTree nodes in/from a dictionary-based memory is proposed, improving the nodes’ refinement and restoration process when the terrain changes are required on the simulations. Experiments with the proposed techniques show encouraging results, with reduced computing times considering terrains with different characteristics and numbers of alterations.
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Paper Nr: 11
Title:

Biodegradation Prediction and Modelling for Decision Support
Authors:

David F. Nettleton, Cristina Fernandez-Avila, Sara Sánchez-Esteva, Steven Verstichel, Maria B. Coltelli, Helena Marti-Soler, Laura Aliotta and Vito Gigante
Abstract: In this paper we describe the functionality of a decision support modelling approach to select appropriate biomaterial blends depending on their mechanical/chemical properties on the one hand, and their biodegradation behaviour, on the other. Firstly, a Case Based Reasoning (CBR) approach is applied to predict expected biodegradation behaviour over time, based on historical examples and using a weighted distance metric on the material properties in order to calculate the trend curve of the new case. Secondly, a Multi-Agent System (MAS) is applied to dynamically simulate the biodegradation curve, in which the two main agents, bacteria and plastic, interact to reproduce the biodegradation kinetics over time. The results of the interpolation are very promising with a good approximation to the real curve time series and % biodegradation, and the Multi-Agent System successfully simulates the different trend curves over time. The system has been confirmed as useful by materials expert end-users, who participated in the project, in order to evaluate a priori new blends “in silico”, and identify and select the most promising, before conducting the long duration biodegradation experiments in the real environment.
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Paper Nr: 17
Title:

Candle Flame Simulation Considering Temperature Change in the Environment
Authors:

Nobuhiko Mukai, Reina Arai and Youngha Chang
Abstract: Fire simulations are utilized in many scenes such as explosion and conflagration in movies or games, and a lot of techniques have been developed. Some are used to control the flame shape for animations, and others are for real and real-time visualizations. In fact, the flame color changes according to the combustion states: complete combustion, incomplete combustion, and non-combustion. Almost all previous studies, however, performed flame simulations considering only one state of incomplete combustion. Then, we have been researching the candle flame visualization considering three combustion states, and the color changed depending on the combustion state. However, the candle flame length was too short in the previous method. Therefore, we propose a method to consider the temperature change that affects the air density in the environment. The change of the environmental air density induces the external force, which makes the shape of the candle flame. As the result of the simulation, the candle flame shape has become thinner than before and has been similar to that of a real candle flame.
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Paper Nr: 51
Title:

Sitar: A Cycle-based Discrete-Event Simulation Framework for Architecture Exploration
Authors:

Neha Karanjkar and Madhav Desai
Abstract: Sitar is an open-source framework for modeling discrete-event, discrete-time systems. It consists of a modeling language and a lightweight simulation kernel. Sitar is specifically targeted for architecture-level modeling and fast simulation of computer systems, though it can be used for other kinds of discrete-time systems as-well. The modeling language allows the description of a system’s structure as an interconnection of hierarchical, concurrent entities. The behavior of each entity can be described in an imperative manner using constructs such as time-delays, conditional wait statements, fork-join concurrency and loops. C++ code can be embedded directly into the description in a well-defined manner, allowing the modeler to use the flexibility and object-oriented features of C++. A model written in this language gets translated to C++ code, which can in-turn be compiled with the simulation kernel to obtain a single simulation executable, or can be linked with external libraries for co-simulation. The simulation kernel uses a two-phase, cycle-based execution algorithm, and has been parallelized using OpenMP for fast and scalable simulation on modern multi-core systems. The framework provides several features to ease the modeling effort, such as in-built logging, syntax highlighting and systematic error reporting for the Sitar language. In this paper, we describe the design and architecture of Sitar, and briefly discuss our experience with its use for multi-core design exploration studies.
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Short Papers
Paper Nr: 29
Title:

The FischerTwin: An Experimentable Digital Twin Case Study
Authors:

Alexander Atanasyan, Felix Casser, Arthur Wahl and Juergen Rossmann
Abstract: Digital Twins are a rapidly maturing approach of transferring real assets into the digital domain. Experimentable Digital Twins (EDT) allow to not only visualise a digital model of an asset or display its current state, but allow to interact with the asset within the digital world - with the EDT behaving exactly like the real twin given analogous inputs from its (real or digital) environment. We created the FischerTwin, an EDT of a modular fischertechnik swivel arm robot, as our first demonstrator to enable the principles of the FeDiNAR project - displaying undesired or dangerous consequences of real actions in augmented reality. This paper presents the design, development and application of this EDT of a complex cyber-physical system including the steps a) function definition b) collection of requirements, c) structural design of the EDT, d) Implementation of its components and the entire robotic system and e) application of the EDT—highlighting its usage in all relevant product life cycle phases. We thus give answers to system-level questions like How can the EDT be applied throughout a real asset’s life cycle?, What are necessary components for the usage of an EDT? and What does the interplay between real and digital twins of a complex cyber-physical system look like?.
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Paper Nr: 48
Title:

A Computer Vision Approach to Predict Distance in an Autonomous Vehicle Environment
Authors:

Giuseppe Parrotta, Mauro Tropea and Floriano De Rango
Abstract: Autonomous vehicle (AV) is a kind of intelligent car, which is mainly based on the computer and sensor system inside the car to realize driverless guide. The AVs are cars that recognize the driving environment without human intervention, assess the risk, plan the driving route and operate on their own. These vehicles are integrated with a series of sensors and other devices and software like automatic control, artificial intelligence, visual computing in order to be able to perform driving inside a road. Calculate the correct distance between vehicle and objects inside its trajectory is important to allow an autonomous guide in safety. So, in this paper we describe our proposal of predicting this distance in a real scenario through an on-board camera and with the support of rover, arm platforms and sensors. The proposal is to use an interpolation technique that permits to predict distance with a good accuracy.
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Area 3 - Application Domains

Full Papers
Paper Nr: 18
Title:

Modelling and Simulation of an Aerosol-on-Demand Print Head with Computational Fluid Dynamics
Authors:

Martin Ungerer, David Zeltner, Achim Wenka, Ulrich Gengenbach and Ingo Sieber
Abstract: In this paper we present the functional validation of a newly developed concept of a print head for aerosol-on-demand printing using fluid dynamical modelling and simulation. In our concept of the aerosol-on-demand print head, the ink is atomised by ultrasonic excitation and focussed by a sheath gas in a converging nozzle. The special feature of this new concept is aerosol generation directly in the print head thus allowing for on-demand operation. Using computational fluid dynamics (CFD), a pre-manufacturing study is being carried out to validate the operation of the concept as well as to find a design-for-manufacture.
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Paper Nr: 19
Title:

Multilinear Modeling and Simulation of a Multi-stack PEM Electrolyzer with Degradation for Control Concept Comparison
Authors:

Aline Luxa, Niklas Jöres, Carlos C. Yáñez, Marina N. Souza, Georg Pangalos, Leona Schnelle and Gerwald Lichtenberg
Abstract: Hybrid energy systems, e.g., with wind energy and hydrogen production, have a high model complexity due to their multi-physics nature, which poses major control challenges for the optimization of plant operation. This work aims at addressing this issues by introducing a highly efficient modeling and simulation framework. A proton exchange membrane (PEM) electrolyzer stack, including degradation and controller, has been modeled using the multilinear class. This class enables the automatic append of individual models, which is used to stack a 100 multi-stack PEM electrolyzer model. Moreover, the multilinear class models can be represented as tensors, which allows for efficient decomposition methods and formats. This is used to considerably enhance the simulation performance of the system, making the simulation of a one year multi-stack electrolyzer operation possible, with a reasonable computational cost. In the simulation, two different high-level control modes are compared regarding overall degradation gain and electrolyzer efficiency. The developed modeling and simulation framework has proven its suitability for big-scale complex models, enabling efficient simulations for controller analysis.
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Paper Nr: 35
Title:

Fixed-wing UAV Kinematics Model using Direction Restriction for Formation Cooperative Flight
Authors:

Yuxuan Fang, Yiping Yao, Feng Zhu and Kai Chen
Abstract: Presently, existing fixed-wing UAV kinematics models typically require the planning algorithm to further smooth the results to meet the trajectory requirements of the starting direction, while the commonly used formation models often lead to track interference between formation members. In this paper, the formation cooperative flight of fixed-wing UAVs was modeled. First, the linear velocities in the three-dimensional direction of the traditional UAV model were changed to a linear velocity along the flight direction of the UAV, and the turning angular velocities and linear acceleration were set to establish the kinematics model. Then, based on the "Lead plane-Wingman" formation control structure, the order of friendly aircraft avoidance was defined by setting the priority of the formation members, and the target point of the wingman was dynamically calculated according to the target formation and real-time position of the leader plane. Finally, a UAV formation cooperative flight model was obtained. Considering the formation of five UAVs as an example, a simulation experiment was carried out, the results of which showed that the trajectory obtained based on the above model could meet the kinematics and collision avoidance requirements in formation flight of the fixed-wing UAVs.
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Short Papers
Paper Nr: 46
Title:

Modelling of the Influence of the Peer Environment on the Prevention of Caries Development in Schoolchildren using a Hybrid Simulation Approach
Authors:

Maria Hajłasz and Bożena Mielczarek
Abstract: Dental caries is a disease caused by medical and nonmedical factors. It can be prevented by taking conscious preventive action. In addition to the services provided by dentists and dental hygienists, awareness is very important in preventing the development of the disease. Awareness can be shaped, among other things, by the environment of peers. The aim of this paper is to use a hybrid simulation to investigate the impact of supportive, neutral, and non-supportive peer environments on strengthening or weakening the effectiveness of dental caries prevention in students of a sample primary school in southwestern Poland. Three experiments were carried out in which the effectiveness of preventive services varied. The effectiveness depended on the individual approach of the students to oral hygiene and dietary habits. Depending on the frequency of changing the closest peer environment, individual student attitudes change over time, which in turn affects the effectiveness of preventive services. Hybrid simulation, which combines discrete event simulation and agent-based simulation, used to model the effectiveness of caries prevention programs may be useful from the perspective of planning preventive care dedicated to children in schools.
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