Integrated Simulation Environment Research Articles

A Survey of Integrated Simulation Environments for Connected Automated Vehicles: Requirements, Tools, and Architecture

A Survey of Integrated Simulation Environments for Connected Automated Vehicles: Requirements, Tools, and Architecture

FAULT DETECTION AND DIAGNOSIS BY SUPPORT VECTOR MACHINES: APPLICATION TO VINYL-CHLORIDE-MONOMER PROCESS

Monitoring process status and identifying process operational faults are essential for improving the process safety in petrochemical plants that interactions between various process streams and units are associated. This paper presents a deployment of a support vector machine technique for detecting and identifying operational fault cases with a case study of a vinyl chloride monomer plant. An integrated simulation environment between MATLAB and UniSim Design dynamic simulator is utilized for evaluating the performance of the proposed fault detection and identification framework. Under the real-time software-in-the-loop simulation, the confusion matrix results and receiver operating characteristics supported that the proposed framework provides high accuracy of fault classification.

Time-space consistency strategy for live-virtual-constructive (LVC) integrated simulation environment

Constructing a unified Live-Virtual-Constructive (LVC) integrated simulation environment has always been a major goal in the modeling and simulation (M&S) field, and ensuring the time-space consistency is the foundation of its construction. That is, the inconsistency of time and space expression between integrated subsystems must be solved to achieve accurate and effective information interaction. To this end, this paper analyzes the specific causes of time-space inconsistency of LVC system, and gives the overall solution and the corresponding strategies or algorithms involved, including clock synchronization strategy, space coordinate conversion algorithm, time description conversion algorithm, dead reckoning (DR) algorithm and event causality control method. The relevant research has been verified in the integrated simulation system of missile attacking surface targets, and can provide technical support for the construction of large-scale LVC system.

Implementing a Simulation Model for the Evaluation of BGP Updates Impact on Real-Time Applications

Abstract Border Gateway Protocol (BGP) is the actual routing inter-domain protocol in the Internet. The size, heterogenity and changebility that characterize todays Internet put always increasing requirements on BGP performance. The research community has already reported the unwanted characteristics of BGP like low integrity and slow convergence through theoretichal analyzes andd empirical measurements. Simulations allow for more realistic and flexible experiments than the theoretichal approach and also lower costs than the measurements in real life environments. The first part of this work describe theoretically characteristics and problems related to BGP nd also expectations of the today Internet users to real time applications (like VoIP). The second part concentrates in identifying and implementing of the elements for creating an integrated simulation environment for evaluating dhe effects of slowconvergence of BGP in these applications. At last it is evaluated the created environement through some small scale simmulations that try to model the now days Internet Structure.

FERMI: Fusion Energy Reactor Models Integrator

The Fusion Energy Reactor Models Integrator (FERMI) is an integrated simulation environment under development for the coupled simulation of the plasma, first wall, and blanket of fusion reactor designs. The FERMI goals are to shorten the overall design cycle while guaranteeing unprecedented accuracy, thus integrating fusion design activities, facilitating an optimal reactor design, and reducing development risks. These goals are achieved by coupling single-physics solvers into a multiphysics simulation environment (FERMI). The Integrated Plasma Simulator (IPS)–FASt TRANsport (IPS-FASTRAN) simulation framework is used for the following: plasma physics, MCNP/Shift codes for neutron and photon transport, OpenFoam for computational fluid dynamics and magnetohydrodynamics (MHD), HyPerComp Incompressible MHD solver for Arbitrary Geometry (HIMAG) for dual-coolant lead-lithium (DCLL) blankets, and DIABLO for structural mechanics simulations. These codes are coupled using the open-source library named precise Code Interaction Coupling Environment (preCICE). FERMI’s features are tested with the analysis of the liquid immersion blanket (LIB) [proposed in the Affordable Robust Compact (ARC)–class tokamak design], the DCLL blanket [proposed in the Fusion Pilot Plant (FPP) design], and other benchmark cases. The calculated figures of merit are the tritium breeding ratio, material activation, displacements per atom, shutdown dose rate, heat deposited in the vacuum vessel and blanket, temperature hot spots, and displacements caused by swelling and creep. A critical technical problem is multiphysics code coupling, which is tackled here, and the first three-dimensional (3D) simulations of the DCLL-FPP and LIB-ARC blankets are presented. To the authors’ knowledge, FERMI represents the first effort to perform 3D simulations of nuclear fusion first wall and blankets in a fully coupled multiphysics manner.

On the influence of elasticity on propeller performance: a parametric study

The aerodynamic performance of propellers strongly depends on their geometry and, consequently, on aeroelastic deformations. Knowledge of the extent of the impact is crucial for overall aircraft performance. An integrated simulation environment for steady aeroelastic propeller simulations is presented. The simulation environment is applied to determine the impact of elastic deformations on the aerodynamic propeller performance. The aerodynamic module includes a blade element momentum approach to calculate aerodynamic loads. The structural module is based on finite beam elements, according to Timoshenko theory, including moderate deflections. Several fixed-pitch propellers with thin-walled cross sections made of both isotropic and non-isotropic materials are investigated. The essential parameters are varied: diameter, disc loading, sweep, material, rotational, and flight velocity. The relative change of thrust between rigid and elastic blades quantifies the impact of propeller elasticity. Swept propellers of large diameters or low disc loadings can decrease the thrust significantly. High flight velocities and low material stiffness amplify this tendency. Performance calculations without consideration of propeller elasticity can lead to decreased efficiency. To avoid cost- and time-intense redesigns, propeller elasticity should be considered for swept planforms and low disc loadings.

Application of integrated simulation environment SIEMNED to the analysis of the MEPHIST-0 tokamak operation

This paper presents the results of numerical simulation of plasma equilibrium and stability in the MEPHIST-0 tokamak with SIEMNED software and comparison of simulation results with experiments. The determined characteristics of the vacuum chamber show that it significantly affects the entire discharge. For various scenarios of the inductor operation, a comparison of experimental data and simulated currents and magnetic fields induced in the chamber was carried out. For steady-state tokamak operation, a numerical study of equilibrium plasma configurations was carried out depending on the currents in the poloidal magnetic field coils and plasma current. The vertical plasma instability was investigated. The limiting values of plasma ellipticity preventing the vertical plasma instability were numerically determined. Numerical simulations show that plasma equilibrium is supported by induced currents. It was shown numerically that magnetic configuration with ‘zero of higher order’ were obtained before the plasma shot, suggesting consistency between the simulation results and observations.

CARESim: An integrated agent-based simulation environment for crime analysis and risk evaluation (CARE)

It requires innovations to accurately predict crimes and offending risks due to the complex nature of human behaviors within different social contexts. In recent years, theory-based and data-driven agent-based models have become useful tools in computational criminology with the abundance of public data, the rise of computing powers, and extensive explorations of related theories and modeling tools. In this paper, we present CARESim, an integrated simulation environment to predict the risks of high-risk individuals committing street violent crimes. The simulation environment combines agent-based modeling with a real geographical information system and incorporates public data (e.g., environmental data, crime data, census data, and transportation data) to reproduce authentic human mobility. This simulation environment is capable of replicating crime patterns and evaluating policies. We demonstrate the use of this environment and illustrate how key factors, such as social networks, the neighborhood, the weather, police patrol strategies, the population, and citizens’ behaviors, impact the risk of street-level violent offending. Furthermore, the environment can support the optimization of patrol strategies and offer evaluations of different social setups that could be unfeasible or expensive to test in real life.

Implementation of Digital Twin-based Virtual Commissioning in Machine Tool Manufacturing

Virtual commissioning is not a new concept; However, it is all the rage with the introduction of Industry 4.0, in the field of product lifecycle management, computer-aided design (CAD), computer-aided manufacturing (CAM), and within the industrial automation programming frameworks. Although, this is a very active area of research and innovation, these technologies have little implementation in the machine tool industry [11]. There is still no integrated simulation environment for virtual commissioning in the market. In this context, digitalisation is a key driver. The aim of this paper is to describe the practice of virtual commissioning in the machine tool manufacturing industry by identifying available solutions in the market and addressing the challenges faced within the machine tool sector. As a result, a digital twin based virtual commissioning solution has been developed at Danobatgroup, the leading machine tool builder in Spain, which is a step forward towards the digitalisation of machine tool manufacturing.

An Integrated Simulation Environment to test the effectiveness of GLOSA services under different working conditions

The Green Light Optimal Speed Advisory (GLOSA) system is a Cooperative Intelligent Transportation System (C-ITS) that is supposed to reduce the energy consumption and travel time associated with a vehicle trip by providing an optimal speed profile to avoid unnecessary stops at an intersection, based on Traffic Light Signals (TLSs) information. It is expected that GLOSA solutions will be widely deployed on transportation networks, thanks to the rapid spread of increasingly effective and pervasive communication technologies. Thus, appropriate methodologies and tools should be adopted to test sustainability objectives and evaluate the effects of such systems on the performance of traffic networks. In this perspective, this paper proposes an enhanced testing approach of GLOSA services based on an Integrated Simulation Environment that combines custom models developed in Matlab/Simulink with the SUMO traffic simulation environment, allowing both the traffic environment and vehicle dynamics to be represented with a suitable level of detail. The proposed approach can be used to cover several aspects which, in the existing technical literature, are: (i) not considered (traffic signal phase condition); (ii) rarely considered (electric engine); (iii) considered in a non-integrated way (traffic condition, TLS cycle duration, communication distance and minimum speed). Indeed, the considered factors pertain to different subsystems of the mobility environment (network and vehicles), and the proposed testing framework allows an equally detailed simulation of all, thus enhancing the accuracy of the results. To show the validity of the proposed approach, this study considers one controlled vehicle, equipped with a GLOSA system, travelling along a single route through a city centre including many TLSs. The simulation analysis deals with different levels of considered factors, assessed through Key Performance Indicators (KPIs) related to mobility and environmental indicators. Numerical results confirm that the proposed Integrated Simulation Environment can give valuable insights and suggestions to design a GLOSA system aiming to enhance both mobility and environmental performance. They also show that the factors in question affect system performance differently.

Dynamic Simulations of Manufacturing Processes: Hybrid-Evolving Technique

Hybrid physical-data-driven modeling techniques have steadily been developed to address the multi-scale and multi-physical aspects of dynamic process simulations. The analytical and computational features of a new hybrid-evolving technique for these processes are elaborated herein and its industrial applications are highlighted. The authentication of this multi-physical and multi-scale framework is carried out by developing an integrated simulation environment where multiple solver technologies are employed to create a reliable industrial-oriented simulation framework. The goal of this integrated simulation framework is to increase the predictive power of material and process simulations at the industrial scale.

Integrated Simulation of Virtual Prototypes and Control Algorithms of Unmanned Surface Vehicles Based on a Robot Operating System

Unmanned surface vehicles (USVs) require autonomous software with a high level of liberalization and automation to complete various missions. Therefore, experimental verification and validation of this software at the initial design stage are essential. However, such experiments are impossible before the actual hardware is developed, and the creation of an external environment for the mission requires substantial cost and time. In this study, virtual prototypes of the mission environment and hardware for the USV are developed. Then, a simulation environment for testing the control algorithms in the autonomous software is constructed. Data communication with the USV hardware is necessary for the autonomous software to acquire information from the sensors and to operate the actuators. Similarly, data communication between the programs of the virtual prototypes and the autonomous software is required for the integrated simulation environment. In this study, the robot operating system (ROS) software platform is adopted to construct the interface for this data communication. Finally, the integrated simulation environment of the control algorithms and the virtual prototypes are constructed based on ROS to verify the autonomous software of the USV. The applicability of the suggested simulation environment is evaluated by application to three scenarios: mine detection, path following, and port entry.

A New Modeling Approach for Low-Carbon District Energy System Planning

Designing district-scale energy systems with renewable energy sources is still a challenge, as it involves modeling of multiple loads and many options to combine energy system components. In the current study, two different energy system scenarios for a district in Montreal/Canada are compared to choose the most cost-effective and energy-efficient energy system scenario for the studied area. In the first scenario, a decentral energy system comprised of ground-source heat pumps provides heating and cooling for each building, while, in the second scenario, a district heating and cooling system with a central heat pump is designed. Firstly, heating and cooling demand are calculated in a completely automated process using an Automatic Urban Building Energy Modeling System approach (AUBEM). Then, the Integrated Simulation Environment Language (INSEL) is used to prepare a model for the energy system. The proposed model provides heat pump capacity and the number of required heat pumps (HP), the number of photovoltaic (PV) panels, and AC electricity generation potential using PV. After designing the energy systems, the piping system, heat losses, and temperature distribution of the centralized scenario are calculated using a MATLAB code. Finally, two scenarios are assessed economically using the Levelized Cost of Energy (LCOE) method. The results show that the central scenario’s total HP electricity consumption is 17% lower than that of the decentral systems and requires less heat pump capacity than the decentral scenario. The LCOE of both scenarios varies from 0.04 to 0.07 CAD/kWh, which is cheaper than the electricity cost in Quebec (0.08 CAD/kWh). A comparison between both scenarios shows that the centralized energy system is cost-beneficial for all buildings and, after applying the discounts, the LCOE of this scenario decreases to 0.04 CAD/kWh.

Influence of Complex Occupant Behavior Models on Cooling Energy Usage Analysis

The behavior of building occupants has been studied by researchers for building control as well as for predicting energy use. In this study, we analyzed the effect of the application of single and complex behavior models on the simulation results of residential buildings. Two occupant behaviors—window opening and closing and air conditioner (AC) usage—were simulated, which are known to be interconnected. This study had two purposes: The first was to integrate data analysis tools (R in this study) and building simulation tools (EnergyPlus in this study) so that two behaviors with interconnectivity could be reflected in building simulation analysis. The second purpose was to apply the behavior models in residential buildings to an integrated simulation environment in stages to analyze their relative influence on the building energy and indoor environment. The results of the study prove that the application of complex behavior is important for research regarding the prediction of actual energy consumption. The results help identify the gap between reality and the existing simulation methods; thereby, they can help improve methods related to energy consumption analysis. We hope that this study and its results will serve as a guide for researchers looking to study occupants’ behavior in the future.

Wastewater Treatment Plant: Modelling and Validation of an Activated Sludge Process

The aim of the present paper is to develop a reliable and accurate model of the wastewater biochemical treatment process and to explore the behaviour through a general dynamic simulation environment, namely the INtegrated Simulation Environment Language (INSEL), for the analysis of the energy demand of the whole wastewater treatment plant. In particular, the presented model pays special attention to the chemical kinetics involved in the activated sludge process for the reduction of nitrogen and carbon compounds. According to the best practices, the plant configuration considered in this work includes the denitrification-nitrification process, performed by completely mixed reactors. In particular, the process analysed in this paper is based on the Ludzak-Ettinger process. The biological process is simulated according to the well-known method widely used in the literature, namely the Activated Sludge Model No 1 (ASM1). The model includes a set of equations for the calculation of aerobic growth of heterotrophs, anoxic growth of heterotrophs, aerobic growth of autotrophs, decay of autotrophs, ammonification of soluble nitrogen, hydrolysis of entrapped organics, and hydrolysis of entrapped organic nitrogen. All these equations, along with energy and mass balances, are solved by the explicit Euler method. The developed model is validated using literature data, showing a great accuracy (deviation below 1%). As for the temperature, results show that, between 15 and 25 °C, in the initial part of the process, transport effects dominate the consumption ones. When the temperature is higher than 30 °C, nitrate consumption is so fast that biomass growth is limited by this effect. Conversely, in case of low temperatures (5–10 °C), biomass growth is not limited by nitrate availability. Finally, results also showed that temperature significantly affects the denitrification process, whereas the effect on the oxygen is lower.

Integrating tools for an effective testing of connected and automated vehicles technologies

The development of connected and automated driving functions involves that the interaction of autonomous/automated vehicles with the surrounding environment will increase. Accordingly, there is a necessity for an improvement in the usage of traditional tools of the automotive development process. This is a critical problem since the classic development process used in the automotive field uses a very simplified driver model and the traffic environment, while nowadays it should contemplate a realistic representation of these elements. To overcome this issue, the authors proposed an integrated simulation environment, based on the co-simulation of Matlab/Simulink environment with simulation of urban mobility, which allows for a realistic model of vehicle dynamic, control logics, driver behaviour and traffic conditions. Simulation tests have been performed to prove the reasoning for such a tool, and to show the capabilities of the instrument. By using the proposed platform, vehicles may be modelled with a higher level of details (with respect to microscopic simulators), while the autonomous/automated driving functions can be tested in realistic traffic scenarios where the features of the road traffic environment can be varied to verify in a realistic way the level of robustness of the on-board implemented functions.

Deep reinforcement learning to optimise indoor temperature control and heating energy consumption in buildings

In this work, Deep Reinforcement Learning (DRL) is implemented to control the supply water temperature setpoint to terminal units of a heating system. The experiment was carried out for an office building in an integrated simulation environment. A sensitivity analysis is carried out on relevant hyperparameters to identify their optimal configuration. Moreover, two sets of input variables were considered for assessing their impact on the adaptability capabilities of the DRL controller. In this context a static and dynamic deployment of the DRL controller is performed. The trained control agent is tested for four different scenarios to determine its adaptability to the variation of forcing variables such as weather conditions, occupant presence patterns and different indoor temperature setpoint requirements. The performance of the agent is evaluated against a reference controller that implements a combination of rule-based and climatic-based logics. As a result, when the set of variables are adequately selected a heating energy saving ranging between 5 and 12% is obtained with an enhanced indoor temperature control with both static and dynamic deployment. Eventually the study proves that if the set of input variables are not carefully selected a dynamic deployment is strictly required for obtaining good performance.

ROS와 픽스호크를 활용한 이기종 무인 이동체간 통합 시뮬레이션 환경 구축

Cooperative systems among various unmanned vehicles are widely used in various field and emerging. Unmanned vehicles are able to operate various missions without operator onboard and they are highly stable. Collaborative work of multiple unmanned vehicles is emphasized due to the difficulty of recent missions such as SEAD (Suppression of the Enemy Air Defenses), MUSIC (Manned Unmanned Systems Integration Capability), golden-time in the rescue mission. In this study, ROS and Pixhawk were proposed as a method of construction of a collaboration system and framework for an integrated simulation environment for heterogeneous unmanned vehicles is proposed. Totally 5 unmanned vehicles were set for the simulation for the observation of illegal fishing boats. This paper shows the feasibility of the cooperative system using ROS and Pixhawk through the simulation and the experiment.

Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities

Buildings account for 35% of the global final energy demand. Efficiency improvements and advanced control strategies have a significant impact in the reduction of energy costs and CO2 emissions. Building energy simulation is widely used to help planners, contractors, and building owners analyse diverse options regarding the planning and management of energy consumption in buildings. Furthermore, recent advances in data processing and computing have led to the development of sophisticated machine learning algorithms that can learn from large datasets, e.g., sensor data from buildings, and use them to develop building-specific adaptive and automatic energy controllers. Control algorithms, such as deep reinforcement learning can tune themselves, are model-free, and economical to implement. In this paper, we introduce an integrated simulation environment that combines CitySim, a fast building energy simulator, and TensorFlow, a platform for efficient implementation of advanced machine learning algorithms. The integration is achieved via Keras—an API for TensorFlow—and a set of text and csv files for data transfer between the applications. This new environment will allow researchers to investigate novel learning control algorithms, and demonstrate their robustness and potential for diverse applications in the built environment. We present two case studies for energy savings and demand response, respectively.

Access Point Deployment Optimization in CBTC Data Communication System

Communication-based train control (CBTC) systems are a new generation of metro signaling system dependent on wireless technology with appropriate access point (AP) deployment. Improved AP deployment can improve the reliability of wireless CBTC systems. This paper proposes a method for optimizing the AP deployment in the data communication system of CBTC. To validate the optimal AP deployment, an integrated simulation environment is used to test the performance of the optimized AP deployments.