Applications In Engineering Systems Research Articles

Stability Analysis of Electromagnetic Suspension Systems Coupled with Flexible Frames: Modeling, Control, Analysis and Experimentation

The stability of the suspension is a key challenge for the application and promotion of electromagnetic suspension technology, especially when it operates in conjunction with a flexible structure, which significantly increases the system's complexity. This paper abstracts the characteristics of the coupling conditions between an electromagnetic suspension system and a flexible structure and designs and constructs an experimental apparatus that includes an electromagnet and a simulated flexible structure with adjustable stiffness and inertia. Based on the Lyapunov method, the central manifold theorem, and the Poincaré method, the stability of the electromagnetic suspension system and the conditions for Hopf bifurcations are derived. Finally, through reasonable experimental design and data analysis, the correctness of the theoretical analysis conclusions is validated, providing references for the engineering applications of electromagnetic suspension systems.

A reinforcement learning agent for maintenance of deteriorating systems with increasingly imperfect repairs

Efficient maintenance has always been essential for the successful application of engineering systems. However, the challenges to be overcome in the implementation of Industry 4.0 necessitate new paradigms of maintenance optimization. Machine learning techniques are becoming increasingly used in engineering and maintenance, with reinforcement learning being one of the most promising. In this paper, we propose a gamma degradation process together with a novel maintenance model in which repairs are increasingly imperfect, i.e., the beneficial effect of system repairs decreases as more repairs are performed, reflecting the degradational behavior of real-world systems. To generate maintenance policies for this system, we developed a reinforcement-learning-based agent using a Double Deep Q-Network architecture. This agent presents two important advantages: it works without a predefined preventive threshold, and it can operate in a continuous degradation state space. Our agent learns to behave in different scenarios, showing great flexibility. In addition, we performed an analysis of how changes in the main parameters of the environment affect the maintenance policy proposed by the agent. The proposed approach is demonstrated to be appropriate and to significatively improve long-run cost as compared with other common maintenance strategies.

Research on lightning strike location by OPGW optical sensing based on extreme sliding window and wavelet

Abstract Lightning strikes usually affect the safe use and normal operation of the power grid. It is crucial to accurately identify and position the lightning strikes. The lightning current on OPGW near the lightning strike point and the modulated lightning intensity signal waveform were simulated. The polarization state signal of Faraday optical fiber will mutate when it is struck by lightning. The extreme value unit sliding window energy method was used to extract the initial time window of the signal after a lightning strike, and the three alternative windows with the maximum energy were determined. Then the maximum wavelet coefficient is determined to be the first wave time point of the struck signal. Simulation analysis and engineering field application show that the optical polarization signal characteristic of OPGW can be used to accurately locate the lightning strike point, which can meet the needs of practical engineering applications of power systems.

Model‐Based Systems Engineering (MBSE) Application in Nuclear Power Plants (NPP)

AbstractCompanies in the nuclear power sector are constantly being challenged to improve their safety and reliability due to increasing complexity arise from evolving safety regulations, long production life, interdisciplinary collaboration, and the need for analyzing the impact of the changes in an operational life cycle. Recognizing these challenges, the paper proposes a transition to Model‐Based Systems Engineering (MBSE) as a transformative solution to improve the management of such complex systems. With this objective, this paper presents a workflow implementation that demonstrates the MBSE methodologies to define a concept model, system architecture, impact analysis, safety and reliability analysis, and operational decision‐making of Nuclear Power Plants (NPP). The paper concludes that MBSE provides a potent approach to managing NPP by employing graphical models to develop interrelated systems that has strong adaptability to heterogeneous environments and regulatory changes. The simulation results demonstrated an NPP life cycle, impact analysis, and a test case for model‐based safety and reliability analysis for regulatory compliance, operational efficiency, balance safety, and informed decision‐making in NPP. The study also leads to a number of interesting directions of future work such as synchronization through Product Lifecycle Management, integration with Building Information Modeling, Model‐Based Commissioning/Decommissioning, and Model‐Based Cyber System Security tailored for nuclear power systems.

Impact Analysis of using Natural Language Processing and Large Language Model on Automated Correction of Systems Engineering Requirements

AbstractThe increasing complexity of Electronic Control Units (ECUs) in the Automotive Industry due to the integration of more sophisticated vehicle features has made the Systems Engineering (SE) application a necessity to define and implement efficient solutions. In this context, requirements emerge as a critical part of the communication between cross‐functional teams. Thus, the more complex systems become, the more requirements are needed to define them. However, lack of information, misalignment and ambiguity on requirements impact the entire development process, resulting in issues later, harder to be fixed. Some studies are being applied to evaluate techniques using Natural Language Processing (NLP) and how it can replace extensive peer reviews, identifying weaknesses in requirements earlier in the process, avoiding wasted time and large financial losses. Normally, NLP is combined with templates such as Easy Approach Requirements to Syntax (EARS), or other rule‐based techniques such as INCOSE's requirements writing best practice rules to define metrics and assess the compliance of the requirements syntax automatically. The focus of this work is to enhance the use of requirements syntax assessment algorithm by combining NLP techniques with Large Language Models (LLMs) to provide automatically corrected requirements.

Systems Engineering Application for Better Design and Analysis of an Assembly Process

AbstractThe use of systems engineering has proven effective in managing complexity and improving system design. Model based system engineering utilizing the Systems Modeling Language (SysML) especially helps in multidisciplinary environments where engineering data needs to be transformed and integrated between environments. Manufacturing is another discipline same as systems engineering is on active digitalization transformation. In the paper, we propose method and solution to apply Model based system engineering (MBSE) for improvement of process planning of assembly lines leveraging model based approach. SysML modeling and execution enable automation of analysis activities as trade‐off, where the behavior of various assembly scenarios of an assembly line can be captured using SysML behavioral diagrams and compared based on various evaluation criteria. However, relying solely on descriptive SysML system models without integrating the virtual representation of the assembly line is insufficient to verify all aspects of system behavior, such as ergonomics and collision avoidance. The main objective of this work is to present a concept for transforming SysML assembly scenarios into the process and resources models of the computer‐aided design and manufacturing (CAD/CAM) environment. This yields a holistic view that serves as a foundation for further production‐related simulations and analyses, enhancing efficiency, ergonomic design, factory layout, and material flow, ensuring effective assembly workstation design optimized at systems engineering level.

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

Study on the evaluation model of the contribution of power industry expansion considering the influencing factors of new energy consumption

In the application of new energy consumption system engineering, in order to evaluate the contribution of electric power industry expansion, an evaluation model of electric power industry expansion contribution considering the influencing factors of new energy consumption is constructed. In the process of power industry expansion, the growth of new energy installed capacity, power system regulation ability, power grid interconnection and electricity demand are the core factors that affect the change of power contribution to power industry expansion. Using the characteristic extraction method of power consumption behavior of users with industrial expansion, after extracting two characteristics, namely, the utilization hours of user’s industrial expansion capacity and the proportion of new energy load put into operation under the change of four major factors, the monthly industrial expansion power consumption of typical users is predicted by the monthly industrial expansion power consumption forecasting method of users considering industrial expansion capacity, and then the growth curve of user’s industrial expansion power consumption is drawn. Based on the forecast method of monthly industry expansion electricity generated by industry expansion quantity, the industry expansion quantity of typical individual users is calculated, and the industry expansion quantity is input into RBF network model trained by particle swarm optimization algorithm to complete the forecast of monthly industry expansion electricity; Finally, the contribution ratio of each influencing factor is calculated, and the evaluation of power industry expansion contribution considering the influencing factors of new energy consumption is completed. After testing, this model can be used as an available model for evaluating the contribution of electric power industry under the condition of considering the influencing factors of new energy consumption.

Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises

Multiple-input multiple-output (MIMO) systems have extensive applications in industrial processes and systems engineering. This letter applies the filtering identification idea to establish a filtered identification model and investigate a filtered auxiliary model-based recursive least squares (F-AM-RLS) algorithm for parameter identification of MIMO systems with colored noises. To improve the computational efficiency, this work further proposes a four-stage filtered auxiliary model-based recursive least squares (4S-F-AM-RLS) algorithm by means of the hierarchical identification principle. Then, by incorporating the forgetting factor, a four-stage filtered auxiliary model-based forgetting factor recursive least squares (4S-F-AM-FF-RLS) algorithm is given to improve the convergence speed and the estimation accuracy. Additionally, the computational complexity analysis of the proposed algorithms indicates that the 4S-F-AM-RLS algorithm effectively reduces the computational burden and improves computational efficiency. Finally, the effectiveness of the F-AM-RLS, 4S-F-AM-RLS and 4S-F-AM-FF-RLS algorithms is validated through a numerical example.

Construction of Universal Approximators for Multi-Input Single-Output Hierarchical Fuzzy Systems

As an important branch of fuzzy systems, hierarchical fuzzy system (HFS) has a wide range of applications in system science, medical science and engineering. Using the semi-tensor product of matrices, this paper investigates the universal approximation of multi-input single-output HFSs, and develops the construction algorithms of universal approximators. Initially, based on the fuzzy relation matrices of fuzzy logic units with Mamdani-type fuzzy rules, the algebraic formulation of HFSs consisting of fuzzy logic units is proposed. After that, the universal approximation of HFSs is explored via the algebraic formulation, and some effective algorithms are presented to construct the universal approximators of HFSs with respect to different scenarios of approximated functions. Finally, the effectiveness of obtained results is verified by the on-ramp metering of freeway.

Investigating an amplitude amplification-based optimization algorithm for model predictive control

The potential for greater algorithmic efficiency for some problems on quantum computers compared to classical computers is appealing in many fields including, for example, the process systems engineering field. While quantum algorithms have been studied for a variety of applications related to optimization, molecular modeling, and machine learning, there remain many applications in process systems engineering, including process control, where it is not clear how quantum computing algorithms would be beneficial. One idea for attempting to understand when a quantum algorithm might provide benefits for control is to start with algorithms that would be expected to benefit “similar” problems (e.g., optimization problems) and to see if controllers can be implemented within those algorithmic frameworks. Therefore, in this work, we study the use of a quantum computing algorithm related to Grover’s algorithm, which is an amplitude amplification strategy that can search an unordered list with improved efficiency compared to a classical algorithm for the task. It has been extended to perform a search for optimal paths over a graph. Given its potential utility for search and optimization, this is an example of an algorithm where we might wonder if it could be adjusted or used to provide speed-ups for large control problems if the controller could function within this algorithmic framework. This work provides the first steps toward attempting to address this question by investigating how optimization-based control problems would fit into this framework. A process described by ẋ=x+u is considered as a test case. The modified Grover’s algorithm requires the optimization problem to be mapped into quantum gates. We discuss ideas for attempting to represent an optimization-based controller known as model predictive control (MPC) in the modified Grover’s algorithm framework. We test how various parameters of the control and quantum algorithm designs, including fundamental parameters in MPC such as the number of sampling periods and length of the sampling periods, impact the success of using the quantum algorithm for the MPC. We provide analyses regarding why the results are what they are to give perspective on how quantum computing algorithms work and intersect with engineering problems.

Opportunities to apply systems engineering to healthcare interprofessional education.

In medical settings, interprofessional education (IPE) plays an important role by bringing students from multiple disciplines together to learn how to collaborate effectively and coordinate safe patient care. Yet developing effective IPE is complex, considering that stakeholders from different schools and programs are involved, each with varying curriculum requirements and interests. Given its critical importance and inherent complexity, innovative approaches to address these challenges are needed to effectively develop and sustain effective IPE programs. Systems engineering (SE) combines a lifecycle perspective with established interdisciplinary processes to develop and sustain large complex systems. The need for SE approaches to manage healthcare complexity has been recognized, but the application of SE to IPE programs has been limited. We believe that there is a significant opportunity for IPE programs to benefit from the application of SE. The common themes running through SE and IPE led us to ask if SE can be used to address IPE complexity and achieve desired IPE outcomes. We believe that SE could facilitate further development and sustainability of a recently developed healthcare curriculum. We also propose to use SE to accelerate and manage future IPE curriculum development, while better understanding the states of vital IPE-related components. We discuss a framework that considers transitions of key IPE elements. We believe that use of interdisciplinary SE processes and holistic perspectives and methods such as system thinking will improve the management of system challenges while addressing IPE's inherent complexity and leading to better patient outcomes and more effective interprofessional collaboration.

Lessons Learned and Recommendations for the Application of Systems Engineering as an Emerging Discipline in Transportation & Infrastructure Projects

AbstractWhile systems engineering (SE) has been a well‐established discipline focusing on interdisciplinary systems and engineering management of complex systems over their life cycles, SE is still widely unknown in the U.S. infrastructure industry.The U.S. has recently passed a $1 trillion infrastructure bill (H.R. 3684), calling for investments in roads, bridges, rail, ports, airports, power, water, broadband, and other major projects. It is the intent of this paper to provide practical guidance to infrastructure owners and operators who are interested in reaping the benefits of applying SE to their transportation and infrastructure projects.This paper memorializes the lessons learned from over a of decade of real‐world, hands‐on experience of introducing and gradually increasing the application of systems engineering to building the civil infrastructure of the California High‐Speed Rail System (CHSRS), starting with the environmental impact review, preliminary engineering, final design, construction, inspection and testing, and finally the certification and planned handover of 119 miles of civil work and over 225 individual structures to the following track and systems contracts.As the first three CHSRS civil works construction packages (CP) are currently nearing completion, three new civil work and passenger station procurement contracts have recently been awarded, extending CHSRS to 171 miles and close to 300 structures, including four passenger stations, with additional track and systems, trainset, and train operator contracts planned in the near future.The extension of the CHSRS presented a timely opportunity to incorporate the SE lessons learned during the first three construction packages and update the systems engineering process requirements for the new CHSRS extension projects going forward. The SE requirements are presented in form of Systems Development Life Cycle (SDLC) requirements and have been prepared as tailored requirements for both civil infrastructure and track and systems contracts.This paper intends to share the lessons learned and present them as specific and actionable recommendations, providing practical guidance for the application of SE to transportation and/or infrastructure projects.

Phased Demonstrations of MBSE in Small Demonstration Satellite Series: Development of System Model and Environment for Full Application of MBSE

AbstractThe Japan Aerospace Exploration Agency (JAXA) has been implementing phased and progressive demonstrations of the Model‐Based Systems Engineering (MBSE) applications, using small demonstration satellite series, so called the Rapid Innovative Payload Demonstration Satellite (RAISE), as a demonstration pre‐cursor. The purpose of the activity is to establish a practical methodology of the MBSE application to satellite projects, to promote its practices, and to infuse MBSE to the Japanese space community. These RAISE satellites are 100kg‐class flagships in the Innovative Satellite Technology Demonstration Program, which provides on‐orbit demonstration opportunities for new technologies and key‐components. This paper presents the phased demonstration strategy, an overall approach, and the technology development of a system model being built for the full application of MBSE to RAISE‐4. For the technology development, the paper covers framework, modeling scope, system model building, system model collaboration with analysis/simulation tool, introduction of design rationale and concerns, information sharing through OpenMBEE, for our full application of MBSE.

Preface

These proceedings are based on the program of the workshop dedicated to New Energy System and Electrical Engineering. Understanding the path from New Energy Systems to Electrical and Power Engineering will involve a strong interdisciplinary interaction among experts in theory and applications. In this workshop a particular attention was devoted to applications in New Energy System and Electrical Engineering.2022 4th International Conference on New Energy System and Electrical Engineering (NESEE 2022) took place virtually in Chongqing, China from December 9th to 11th, 2022. It can be expected that with the recent developments in the fields towards more user-friendly new energy system and electrical engineering, new energy and electrical will become a vital link in the chain of sustainable development and highly automation in the near future.Many scientists and researchers all over the world have contributed to the emerging technology of new energy and electrical engineering. At this meeting we had a comprehensive overview of these fascinating fields and of future scenarios thanks to the participation of leaders of the most important projects. Fushuan Wen, a renowned professor from Zhejiang University, China, made a keynote speech and shared his research Restoring a Faulted Power System Having Rich Renewable Energy Generation in Electricity Market Environment with us. His research domains include: a) power economics and electricity markets; b) power system investment, planning and operation optimization; c) smart grids and electric vehicles; d) power system alarm processing, fault diagnosis and system restoration; e) artificial intelligence.The plenary sessions covered a broad range of topics, as we considered it important to promote communication between the communities pursuing research in different areas of new energy and electrical engineering. The topics discussed included Energy Saving Technologies, Energy Storage Technologies, Thermal and Power Engineering, Electrical Automation and Power Engineering, Smart Grid / Power IC, Power Machinery and Engineering, etc.The NESEE conferences in the past have proven to be an important forum at which energy scientists, chemists, electrical specialists brought together a critical mass of thoughts, findings and considerations and have been endorsed by many international and national energy and electrical organizations and publishers.We hope that this NESEE 2022 conference has been a useful contribution to the fields of new energy and electrical engineering, and that it may encourage the organization of subsequent NESEE conferences on these diverse, challenging and fascinating fields.Last but not the least is our acknowledgement. We would like to thank all the participants, especially those who contributed speeches, posters and manuscripts, for making NESEE 2022 such an exciting and memorable conference. We thank the Technical Program Committee members, for putting together an outstanding program. We gratefully acknowledge the support of editors and members of the Journal of Physics: Conference Series, for their efforts in making this volume published.The Committee of NESEE 2022List of Committee Member is available in this Pdf.

Application of Model-Based Systems Engineering for the Integration of Electric Engines in Electrified Aircraft

The objective of green, carbon-neutral flights is propelling the innovation of newer propulsion systems. With this increased development of an interdisciplinary form of propulsion for aircraft, the integration burdens and efforts intensify. In literature, it is estimated that it takes 10-15 years to design and develop an aircraft. The expected date of entry for any hybrid electric aircraft is 2035-2040. Any innovation and effort to cut this time by any degree should be explored and analysed. One of the techniques that have the potential to help fast-track the research and development of interdisciplinary systems is Model-based System Engineering (MBSE). Various studies have shown the benefit of employing a model-based design strategy. The focus case study relates to the integration of the electric machine and the propeller, along with related sub-systems. For Hybrid Electric Propulsion (HEP), the electric machine and propeller need to be integrated and their interaction to be analysed. MBSE is proposed as a methodology that would help streamline the process of design and integration of the two systems. This study documents the exploration of connecting MBSE with current simulation and modelling of sub-systems in order to ensure the fulfilment of stakeholder needs and full system effectiveness. This paper establishes the research problem, and the approach to be pursued, and gives notice of first developments and expected follow-up work.

The Application of Model-Based Systems Engineering to Rural Healthcare System Disaster Planning: A Scoping Review

Disasters and other emergency events have complex effects on human systems, particularly if the events are severe or prolonged. When these types of events happen in rural communities, the resources of the local public health, healthcare, and emergency response organizations can be quickly depleted or overwhelmed. Planning for emergencies can help to mitigate their impact. Model-based systems engineering (MBSE) methods, including computer simulations, can provide insight on how best to prepare for these events and to explore the effects of varying approaches and resource utilization. To best apply these methods for improving disaster management in rural settings, a synthesis of the current body of evidence in this field is needed. The objective of this scoping review was to provide a descriptive overview of the application of computer simulation based on MBSE approaches to disaster preparedness and response for rural healthcare systems. Six studies met inclusion criteria, and varied in terms of MBSE method used, healthcare setting, and disaster type and context considered. We identified a gap in the research regarding the application of MBSE approaches to support rural healthcare disaster preparedness planning efforts. Model-based systems engineering and systems thinking, therefore, represent novel methods for developing tools and computational simulations that could assist rural communities better prepare for disasters.

Prescribed Performance Back-Stepping Tracking Control for a Class of High-Order Nonlinear Systems via a Disturbance Observer.

Due to the widespread presence of disturbances in practical engineering and widespread applications of high-order systems, this paper first pays attention to a class of high-order strict-feedback nonlinear systems subject to bounded disturbance and investigates the prescribed performance tracking control and anti-disturbance control problems. A novel composite control protocol using the technique of a disturbance observer-prescribed performance control-is designed using the back-stepping method. The disturbance observer is introduced for estimating and compensating for unknown disturbances in each step, and the prescribed performance specifications guarantee both transient and steady-state performance of the tracking error to improve the control performance and result in better disturbance rejection. Moreover, the technique of adding a power integrator is modified to tackle controller design problems for the high-order systems. The Lyapunov function method is utilized for rigorous stability analysis. It is revealed that while the control performance completely remains in the prescribed bound, all states in the closed-loop system are input-to-state stable, and the tracking error and the disturbances estimating error asymptotically converge to zero simultaneously. Then, the feasibility and effectiveness of the proposed control protocol are verified by a simulation result.

Practice and Enlightenment of China's Aerospace Complex System Management in the National System

Aerospace engineering is characterized by its huge scale, technological complexity, high standards of quality and reliability, tremendous cost, and long R&D cycle. It is closely tied with national politics and defense security, and may indirectly provide socioeconomic benefits. To organize and implement a complex aerospace project, it is necessary to make innovations in technologies, schedules, qualities, and facilit ies construction management measures and establish an aerospace engineering management system adaptive to the high-complexity feature, based on the management models of the traditional aerospace system engineering. Different types of participants play different functions in project decision-making. The expert group participates in the whole process of the formulation and decision-making of the schemes, providing decision support for each system and the general department. This study describes the implications for the space domain of China’s deployment of the state-owned enterprises (SOEs) as power projection vehicles to advance Beijing’s national strategy. In order to provide reference for the application of model-based systems engineering (MBSE) in the aerospace field, suggestions and conclusions on the development of MBSE application in China were provided.

A New Variable-Boostable 3D Chaotic System with Hidden and Coexisting Attractors: Dynamical Analysis, Periodic Orbit Coding, Circuit Simulation, and Synchronization

The study of hidden attractors plays a very important role in the engineering applications of nonlinear dynamical systems. In this paper, a new three-dimensional (3D) chaotic system is proposed in which hidden attractors and self-excited attractors appear as the parameters change. Meanwhile, asymmetric coexisting attractors are also found as a result of the system symmetry. The complex dynamical behaviors of the proposed system were investigated using various tools, including time-series diagrams, Poincaré first return maps, bifurcation diagrams, and basins of attraction. Moreover, the unstable periodic orbits within a topological length of 3 in the hidden chaotic attractor were calculated systematically by the variational method, which required six letters to establish suitable symbolic dynamics. Furthermore, the practicality of the hidden attractor chaotic system was verified by circuit simulations. Finally, offset boosting control and adaptive synchronization were used to investigate the utility of the proposed chaotic system in engineering applications.