35 research outputs found

    Application of System-Theoretic Process Analysis (STPA) in Nuclear Instrumentation and Control systems

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    This thesis evaluates the application of System-Theoretic Process Analysis (STPA) in analyzing the Instrumentation and Control (I\&C) systems within Nuclear Power Plants (NPPs). Ensuring the safety of I\&C systems is crucial, as they play an important role in NPPs' operations. Most I\&C systems in NPPs are reaching their end of life and require upgrades. These upgrades will replace the older analog electromechanical systems with newer software-intensive digital I\&C systems. Traditional hazard analysis methods, such as Fault Tree Analysis (FTA) and Failure Modes and Effects Analysis (FMEA) are more suitable to be used when analyzing older analog electromechanical systems and they have limitations when applied to these newer digital I\&C systems. System-Theoretic Accident Model and Processes (STAMP) is a new accident model based on the System Theory. STPA is a tool based on STAMP that can be used to analyze complex systems that consist of software. This thesis uses a case study of a feedwater control system that is used to control the feedwater level inside the reactor pressure vessel of an NPP. The provided case study is analyzed using STPA and the results are presented in this thesis. In addition to the results of the STPA, the observations, and challenges throughout the process are discussed. The thesis also discusses the impact of the level of information used in conducting STPA

    Biologically Inspired Connected Advanced Driver Assistance Systems

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    Advanced Driver Assistance Systems (ADAS) have become commonplace in the automotive industry over the last few decades. Even with the advent of ADAS, however, there are still a significant number of accidents and fatalities. ADAS has in some instances been shown to significantly reduce the number and severity of accidents. Manufacturers are working to avoid ADAS plateauing for effectiveness, which has led the industry to pursue various avenues of investment to ascend the next mountain of challenges – vehicle autonomy, smart mobility, connectivity, and electrification – for reducing accidents and injuries. A number of studies pertaining to ADAS scrutinize a specific ADAS technology for its effectiveness at mitigating accidents and reducing injury severity. A few studies take holistic accounts of ADAS. There are a number of directions ADAS could be further progressed. Industry manufacturers are improving existing ADAS technologies through multiple avenues of technology advancement. A number of ADAS systems have already been improved from passive, alert or warning, systems to active systems which provide early warning and if no action is taken will control the vehicle to avoid a collision or reduce the impact of the collision. Studies about the individual ADAS technologies have found significant improvement for reduction in collisions, but when evaluating the actual vehicles driving the performance of ADAS has been fairly constant since 2015. At the same time, industry is looking at networking vehicle ADAS with fixed infrastructure or with other vehicles’ ADAS. The present literature surrounding connected ADAS be it with fixed systems or other vehicles with ADAS focuses on the why and the how information is passed between vehicles. The ultimate goal of ADAS and connected ADAS is the development of autonomous vehicles. Biologically inspired systems provide an intriguing avenue for examination by applying self-organization found in biological communities to connecting ADAS among vehicles and fixed systems. Biological systems developed over millions of years to become highly organized and efficient. Biological inspiration has been used with much success in several engineering and science disciplines to optimize processes and designs. Applying movement patterns found in nature to automotive transportation is a rational progression. This work strategizes how to further the effectiveness of ADAS through the connection of ADAS with supporting assets both fixed systems and other vehicles with ADAS based on biological inspiration. The connection priorities will be refined by the relative positioning of the assets interacting with a particular vehicle’s ADAS. Then based on the relative positioning data distribution among systems will be stratified based on level of relevance. This will reduce the processing time for incorporating the external data into the ADAS actions. This dissertation contributes to the present understanding of ADAS effectiveness in real-world situations and set forth a method for how to optimally connect local ADAS vehicles following from biological inspiration. Also, there will be a better understanding of how ADAS reduces accidents and injury severity. The method for how to structure an ADAS network will provide a framework for auto-manufacturers for the development of their proprietary networked ADAS. This method will lead to a new horizon for reducing accidents and injury severity through the design of connecting ADAS equipped vehicles.Ph.D

    Control of Proton Exchange Membrane Fuel Cell System

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    265 p.In the era of sustainable development, proton exchange membrane (PEM) fuel cell technology has shown significant potential as a renewable energy source. This thesis focuses on improving the performance of the PEM fuel cell system through the use of appropriate algorithms for controlling the power interface. The main objective is to find an effective and optimal algorithm or control law for keeping the stack operating at an adequate power point. Add to this, it is intended to apply the artificial intelligence approach for studying the effect of temperature and humidity on the stack performance. The main points addressed in this study are : modeling of a PEM fuel cell system, studying the effect of temperature and humidity on the PEM fuel cell stack, studying the most common used power converters in renewable energy systems, studying the most common algorithms applied on fuel cell systems, design and implementation of a new MPPT control method for the PEM fuel cell system

    Multi-Robot Systems: Challenges, Trends and Applications

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    This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics

    Modular Omni-directional AGV Developmental Platform with Integrated Suspension, Power-plant and Control Systems

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    The thesis focuses on the development of an industrial automatic guided vehicle (AGV) with omni-directional capabilities. The omni-directional strategy used was the "swerve drive" system, a system whereby a wheel can be rotated about both its y axis (rolling axis) and z axis (vertical axis). Unlike most commonly used swerve drive systems that have swerve capabilities on each wheel attached to the body of the vehicle, this research seeks to reduce cost by only having swerve capabilities on two diagonal wheels. The remaining two wheels will act as castor units. AC drives are used on the system in place of more traditional DC drives, due to their cost vs capability advantage over DC and their prevalence in the industrial environment. Since an AGV is a mobile platform any power source found on it is usually derived from batteries, a DC source. Usage of DC introduces several limitations including difficulty transforming voltage levels for different systems, inability to run AC drives directly from the power source and comparably larger conduction wires. These limitations were overcome by adding a stand-alone power-plant on the AGV in the form of an inverter. The inverter transformed the DC power supplied by a battery bank from 48 volts DC to 230 volts AC. Thus, the primary focus of this research is on the development and validation of a novel two wheel omni-directional drive system that makes use of inexpensive and readily available components that have already been proven to work in industry.Thesis (PhD) -- Faculty of Engineering, the Built Environment, and Technology, 202

    Mathematical Modeling and Simulation in Mechanics and Dynamic Systems

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    The present book contains the 16 papers accepted and published in the Special Issue “Mathematical Modeling and Simulation in Mechanics and Dynamic Systems” of the MDPI “Mathematics” journal, which cover a wide range of topics connected to the theory and applications of Modeling and Simulation of Dynamic Systems in different field. These topics include, among others, methods to model and simulate mechanical system in real engineering. It is hopped that the book will find interest and be useful for those working in the area of Modeling and Simulation of the Dynamic Systems, as well as for those with the proper mathematical background and willing to become familiar with recent advances in Dynamic Systems, which has nowadays entered almost all sectors of human life and activity

    Machine Learning Approach for Modeling and Control of a Commercial Heliocentris FC50 PEM Fuel Cell System

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    In recent years, machine learning (ML) has received growing attention and it has been used in a wide range of applications. However, the ML application in renewable energies systems such as fuel cells is still limited. In this paper, a prognostic framework based on artificial neural network (ANN) is designed to predict the performance of proton exchange membrane (PEM) fuel cell system, aiming to investigate the effect of temperature and humidity on the stack characteristics and on tracking control improvements. A large part of the experimental database for various operating conditions has been used in the training operation to achieve an accurate model. Extensive tests with various ANN parameters such as number of neurons, number of hidden layers, selection of training dataset, etc., are performed to obtain the best fit in terms of prediction accuracy. The effect of temperature and humidity based on the predicted model are investigated and compared to the ones obtained from real-time experiments. The control design based on the predicted model is performed to keep the stack operating point at an adequate power stage with high-performance tracking. Experimental results have demonstrated the effectiveness of the proposed model for performance improvements of PEM fuel cell system.This research was funded by the Basque Government, Diputación Foral de Álava and UPV/EHU, respectively, through the projects EKOHEGAZ (ELKARTEK KK-2021/00092), CONAVANTER and GIU20/063

    Integrated Thermal Systems and Controls Modelling for AUTO Mode Simulation and Optimization

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    Virtual product development has become the preferred approach for vehicle A/C system development. The advantages provided by virtual modelling compared to traditional approach are accelerated development pace and reduced cost. The thesis focuses on virtual modelling of the A/C system on a SUV vehicle based on experimental data. A virtual model of the A/C system is constructed and calibrated in Simcenter Amesim. The model includes a vapour-compression refrigeration cycle and a cabin air model. The components are modelled and calibrated based on supplier data. The two thermal systems interact thermally at the evaporator level. The cabin air blower unit with a PI controller and a small DC motor is also modelled in MATLAB/Simulink. The virtual thermal model is able to simulate the cabin air temperature development during High Ambient AUTO mode drive cycle. The controlled DC motor system tracks reference speed to provide adequate air flow for the cabin. The virtual models can be used for A/C system and components performance analysis and optimization. The modelling process provides deeper understanding on thermal and control systems design
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