Nautical Operations (USN)
Virtual Reality (VR)
Project title: Effective Utilization of Virtual Reality (VR) affordances in Maritime Simulator Training
Brief description: Virtual Reality (VR) has emerged as a potential alternative form of technology which could assist the contemporary training goals of full-mission maritime simulators. VR has already been used as a training intervention in different levels of training in several safety-critical domains (aviation, maritime, health, education etc.). The integration of immersive technologies in Maritime Education and Training (MET) could pave new ways for skill training for the operators working with manned, unmanned, remote or future autonomous technologies in differing maritime workplaces constituting complex socio-technical systems. Research to create, validate and improve VR training intervention will open doors to more innovative solutions to be integrated in MET practices.
The aim of the PhD project is two-fold. During the first phase, the current state-of-the-art of VR simulators will be explored in maritime education and training contexts. A literature review has been conducted to get an overview of VR simulators for education and differing skill training purposes. In addition, a hybrid Multi-Criteria Decision-Making method (MCDM) have been utilized to evaluate the current state of maritime VR simulators compared to others.
On the second phase, novel methods for training and assessment will be proposed to increase the efficiency of VR simulators. Data collection methods include surveys, interviews, and simulated experiments. Artificial Neural Network (ANN) modelling will be utilized to develop a novel assessment framework for the trainees in VR. Exploring differing constructs such as motivation, self-efficacy and technology acceptance of the maritime trainees to get better insights into their immersive learning process are some of the potential scopes of the project. The remaining duration for this PhD project is three (03) years.
Nautical Operations (USN)
Trust in Automation
Project title: Systems approach to human-autonomy interaction (HAI), case of Trust in Automation.
Brief description: My Ph.D. is focused on modeling human-automation interaction for Maritime Autonomous Surface Ships (MASS). More specifically, I am engaged in modeling “trust in automation” to understand how an operator’s trust mediates reliance on automation, which may affect the overall system’s performance. I am applying the principles of systems engineering and system dynamics modeling to address such complexity as an inherent characteristic of today’s socio-technical systems. Moreover, I aim to explore the psychophysiological measurements to validate my proposed model via an eye-tracking experimental study.
Background: I am a doctoral candidate at the Department of Maritime Operations (IMA), University of South-Eastern Norway (USN). I have completed my master’s degree in System Dynamics from the University of Bergen (UiB) and a bachelor’s degree in Industrial and System engineering from Azad University (IAU).
Project title: Cyber-physical convergent information communication technologies (ICT) for virtualised protection and control functionalities in energy systems
Brief description: Comparison between traditional and proposed approaches. (a) Traditional control and protection functionalities are applied to a power converter-based resource. (b) Proposed omnipresence cyber-physical convergent-purpose (PhD project) is applied to power converter-based resources. The physical system sends the measurement via sensors to cyber system, then cyber system with 3C (communication, control, computation) features will return feedback signal to physical system. The objectives of the study is to:
- Create a methodology for virtualisation of the control and protection functionalities in the energy system.
- Create a methodology that can have convergence possibilities of independent technologies (protection/controllers, power electronics devices, digital communication technologies, etc.)
- Carry out experiments using laboratory-based real-time simulations, to test and validate the most promising solution and generate the project outcomes that can be disseminated and exploited.
- OBJ1: The methodology of constructing SCADA system is applied. Digital twin, which is a virtual representation of a real-world physical system or product, can be applied in this objective.
- OBJ2: The object-oriented modelling approach is used. With this method, the control and protection functionalities or more can be merged into one-for-all purposes that can be inherited advantages and eliminate disadvantages of these technologies.
- OBJ3: The real-time simulation and the use of Hardware-in-the-loop (HIL) can fulfil the requirements. The execution of the simulator should have the small time steps in accordance to the real-time constraints of the physical target. The testing experiments for the proposed method are performed mainly at the real-time hardware-in-the-loop laboratory of DIgEnSys-Lab  (Digital Energy Systems and Lab) at University of South-Eastern Norway.
- Non-directional Overcurrent Protection Relay Testing Using Virtual Hardware-in-the-Loop Device (Book chapter – submitted).
- Distance Protection Relay Testing Using Virtual Hardware-in-the-Loop Device (Book chapter – submitted).
- A Short-circuit Analysis in CIGRE European Medium Voltage Distribution Network (Journal – under Prof’s review).
- Exploring Cyber-Physical Energy and Power Systems: Applications, Challenges and Simulation Approaches (Review paper – under review).
- Real-time cyber-physical system for controlling reactive power using IEC 61850 communication protocol. (Target journal)
- Ethics in using AI
Background: Le Nam Hai Pham or Lee is currently PhD candidate at University of South-Eastern Norway, campus Porsgrunn.
I was educated at University of Technology in Ho Chi Minh city, Vietnam and graduated a bachelor’s degree in electrical and Electronics Engineering before spending nearly 4 years serving in technology consultant company in Vietnam.
In 2022, I received Master’s degree in Electrical Power Engineering at University of South-Eastern Norway and is recruited to become PhD Research Fellow, current position.
My interest is smart grids, cyber-physical systems, renewable energy, static and dynamic power grids.
Project title: Use of Automation Processes for Detection of Emergent Behavior during Systems Integration Testing
Brief description: A potential for improvement regarding test coverage for the company developed products is what triggered this PhD project. My research is about use of automation processes for detection of emergent behavior during systems integration testing. I will conduct action research using the industry-as-laboratory. The goal of my PhD project is to establish a set of "best practices" for detection og weak emergent behavior in engineered complicated systems using case studies as "proof of concepts". These guidelines can help an observer to a better understanding of the system-of-interest, reducing the perceived emergent behavior and complexity. Emergent behavior and complexity are related terms, scaled according to the difficulty of understanding the behavior of the system and the system itself. Design of experiments and automation will be the areas explored in different ongoing company projects. The value for the company will be to ensure more robust products through smarter testing, discovering more inherent undesired system behavior at an earlier stage, facilitating cheaper mitigation efforts. The timeframe of my PhD project is four years (01.01.2021-31.12.2024), where 75% of my time is allocated to research related work and the remaining 25% is anything related to company projects.
Background: Rune is an industrial-PhD candidate at the University of South-Eastern Norway (USN), campus Kongsberg. He holds a Master in Systems Engineering from USN and a Bachelor in Engineering within System Design from USN. He holds a position as a Senior System Engineer in the company Kongsberg Defence and Aerospace (KDA) with many years of experience within product development (system design and system test). Prior to his career in engineering, Rune was in operational service with the Royal Norwegian Air Force for six years, including graduation from the Air Force Academy.
Project title: Real-time estimation of the energy-mix-limit for the secure operation of converter dominated power system
Brief description: Most countries have created measures to increase the implication of renewable energy by incorporating a new form of renewable energy resources (RES) into the electricity grid. Power electronic converter (PEC) based technologies are quickly changing the generation, transmission, distribution, and utilization levels of the modern power system. Decreased rotational inertia immediately affects system frequency and operational security. A system with low inertia can cause unnecessary blackouts due to frequency variability. A decrease in system inertia raises the RoCoF and the nadir frequency. Voltage stability, rotor angle stability, and frequency control approaches have all been extensively studied in the past. However, real-time control stability has received little attention, despite being the principal cause of recent blackouts. The presented investigations do not produce tangible outputs with sufficient validation and have various limitations. There are still many research gaps in this field, which will be filled soon. Hence, this PhD project aims to develop a novel methodology for estimating real-time indicators and ensuring short-term frequency stability of the PEC-integrated power system in normal and emergency situations. It will include developing and testing a method to discover the optimal mix of energy resources and characteristics for a secure power system. The historical and off-line data will be used to construct an algorithm that can be tested in a real-time simulation environment. The tasks will be performed using deep learning, reinforcement learning, and probability programming. The final goal of this PhD thesis is to test and validate the proposed methodology and information model in a laboratory setting. Co-simulation with hardware in the loop will be used to assess the methodology's appropriateness. The system parameters will be evaluated using various standards and grid codes (especially focused on the Nordic grid).
Biography: Ashish Shrestha received a Bachelor's degree in Electrical and Electronics Engineering from School of Engineering, Pokhara University, Nepal, and a Master's degree in Planning and Operation of Energy System from School of Engineering, Kathmandu University, Nepal. He was also an Erasmus Mundus candidate at the Department of Electrical Engineering, Frederick University, Cyprus, funded by European Union. Currently, he is doing his PhD at the Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, Porsgrunn Campus, Norway. Before his PhD, he was working as a Lecturer at the Department of Electrical and Electronics Engineering, and a Researcher (Activity Leader) at Center for Electric Power Engineering (CEPE), Kathmandu University, Nepal for three and half years. He was also involved in the problem-based-learning project funded by Erasmus+ program of EU, and was leading a project under the funding of Ministry of Foreign Affairs (MFA), Norway, as the Project Co-Principal Investigator. Till today, he published 48 peer-reviewed journal articles and international conference papers and was assigned as a reviewer for numerous international conferences and peer-reviewed journals from IEEE, Springer, Elsevier, IET and so on. His research interests include Power System Dynamics, Distributed Generation Resources, Planning and Operation of Energy System and so on.
Project title: Process Technology in real time data verification and reconciliation for optimal oil production under the presence of uncertainties
Brief description: The purpose of this research project is to improve existing oil well models by using collected data and use them for dynamic data reconciliation and gross error detection. Data for this study can be collected from both simulation and petroleum industry. This study follows the casestudy design for models of artificial lifting oil wells, with indepth analysis of the uncertainty in the dynamic model. By employing these firstprinciples models, process model constraints are adopted for data validation and data reconciliation
Project title: Human Systems Integration in unmanned systems through conceptual modeling and data sense-making
Brief description: Systems are becoming increasingly complex. Having human operators integrated with autonomous solutions imposes challenges for engineers developing such socio-technical systems. This research examines how the industry can utilize conceptual models and data sense-making techniques during a human systems integration approach in the early product development phase. Through conceptual modeling, we create static and dynamic models with an abstraction of complex systems. In data sense-making, we utilize technical, organizational, and human systems data to explore and support the models. The combination can enhance the exploration and insight in a format that is understandable and shareable with key stakeholders. This project uses action research methodology with case studies and industry as the laboratory in collaboration with companies working towards manned-unmanned-teaming. There is a need for the industry to understand how their unmanned systems interact with human operators, how to model the complexity, and how to utilize data suitably.
Background: Tommy is a Ph.D. candidate at the University of South-Eastern Norway (USN), campus Kongsberg. He holds a Master of Science in Systems Engineering with Industrial Economics and a bachelor's in mechanical engineering with Product Development from USN. He has several years of experience in the Subsea Oil & Gas and the Defence industry, working from early concept to testing of complex systems.
Project Title: Improvement and development of new equipment for automatic sampling and processing of environmental DNA (eDNA).
Brief Description: Micro Total Analysis Systems (μTAS) are devices that automate and include all necessary steps for a chemical analysis of a sample. These miniaturized fluidic systems or lab-on-a-chip (LOC) platforms can perform laboratory operations (preparation, separation, detection) on a single device. One of their beneficiaries is small size and channel dimensions of the order of tens of micrometers, μTAS platforms feature negligible sample consumption, reduced cost of the process, and short analysis time.
The focused research will be on micro- and nanotechnologies to improve and develop new equipment for automatic sampling and processing of environmental DNA (eDNA). Many different micropumps, microvalves, optical systems, microchannels, microreactors, micromechanical devices, microelectronic devices, heating elements and fabrication methods have been developed over all these years in the SALICO instrument. These to be tested in proximity at each component during the execution of experiment. Automatic environmental monitoring equipment provides a unique opportunity to monitor the presence of different biological indicator species like pike in rivers and lakes. Because it is an invasive species in fresh water and easily prey upon the small community fish species and destroy. The SALICO cassette with microfluidic chip is designed in a way of performing the molecular assay of Loop mediated Isothermal Amplification (LAMP), Nucleic acid sequence-based amplification (NASBA) together with extraction of DNA/RNA and could be used in the fields (i) the aquaculture industry, (ii) molecular eDNA environmental monitoring and (iii) home-based primary health monitoring of humans and animals. The source of samples are water, mucosa and salvia and have been tested inside the SALICO cassettes with different methods such as LAMP and NASBA. Viruses, bacteria, salmon, and pike have been detected both manually and automatically in the prototype technology. Automatic purification of DNA and RNA from all these samples has been repeatedly demonstrated in our laboratory. Another inconvenience in field monitoring is, the bio reagents could not be stored at room temperature, due to enzyme degradation.
The first objective of the project is to synthesize the lyophilized beads with primers and probes of pike-mitochondria Cyt b gene, confirm the beads are bio active and testing the performance for long term. This lyophilized bead could be stored in on site, where resources are limited and does not require cold chain for transportation. The suitable stabilizing agent and percentage is determining factor in protecting the bioactivity of enzyme and primers in lyophilized beads. Further, the bioactive beads will be tested on the new prototypes on instruments and Lab on Chip platform. The gene selection and primer designing is the vital step in setting the experiment. The second objective is to pretreat the eDNA sample in appropriate method (filtration), before entering the Lab on Chip. This work is performed in coordination with a consortium. The amplification rate of DNA and specificity are analyzed with the development of primers and probes.
Currently, there is no equipment available for on site, real time, environmental monitoring of eDNA. So, the output of this project will be better preventive in environmental technology.
About Me: I am PhD candidate at Department of Microsystems, University of South-Eastern Norway, Vestfold campus. I received a graduation in Master of technology - Biotechnology (six year integrated program), from Bharathidasan University, India. After an education, I got a research assistant position in one of the renowned research institutes named, CSIR- Central Electrochemical Research Institute, India and earned a research experience in various stream of approach. I took the opportunity to work with team members and publish 6 research papers, since I was engaged in Industry project.
Project Title: Utilizing Big data within early phase of the New Product Development Process (NPD).
Brief Description: The phd project strives to utilize feedback data in terms of failure data in the early phase product development process to enhance data-driven decision-making. The project also seeks to use conceptual modeling and data analysis to guide and support each other in an iterative and recursive manner.
Background: Haytham B. Ali is employed as PhD research fellow and Assistant Professor at the University of South-Eastern Norway (USN). He is working on connecting engineering with science, focusing on mathematics. Haytham focuses on his PhD at using a combination of conceptual modeling and data analysis to enhance the early design phase in the product development process. He holds a Master of Science in Systems Engineering with Industrial Economics degree and a Bachelor's degree in Mechanical Engineering with a specialization in Product Development, both from USN.
Mechanical Engineering (NTNU)
Project title: 5G Security for Critical Communications
Brief description: The introduction of 5G in mobile networks represents a paradigm shift which requires new approaches for dealing with security threats. The softwarization of network functions, the requirements to support less secure legacy networks, and the adoption of web-centric protocols give 5G an increasing attack surface which must be controlled. In the future, the Next Generation Critical Communication (NGCC) networks will be moving towards high-speed public 5G networks and eventually turning them into a part of national critical infrastructure. Also, security requirements are generally stricter for NGCC networks than for 5G, hence it is crucial to understand how this may influence the threat landscape. There is a need for new threat modelling methods and tools to effectively identify and address emerging risks in multi-generational 5G networks. Moreover, it is difficult to validate threat modelling approaches by performing security exercises and pen testing on operational 5G networks, as this could lead to unacceptable risk. The project objective is to improve the security of 5G-enabled NGCC networks (Nødnett in Norway) that emergency organizations such as police, health, fire, and rescue services use. The project seeks to investigate the application of threat modelling science together with a cyber range concept for simulating realistic 5G inherited risks to the NGCC network and validate countermeasures. The project aims to identify and analyze security vulnerabilities proactively in 5G to stay ahead of the attackers.
Mechanical Engineering (NTNU)
Project Title: Benchmarking Product Development Practices for De-Risking the Green Transition
Brief Description: The project aims at medium and large product development organizations in Denmark and Norway. The purpose is to understand how to accommodate for the uncertainties introduced by the green transition in the organizations product/services portfolio management practices. What are the uncertainties and how are they interdependent of each other? What can be done to resolve part of the inbound complexity of those systems where the uncertainty is related? The project is following the Design Research Mythology with high level of case study research.