Design Of Physical Systems Research Articles

A physics-driven sensor placement optimization methodology for temperature field reconstruction

Perceiving the global field from sparse sensors has been a grand challenge in the monitoring, analysis, and design of physical systems. In this context, sensor placement optimization is a crucial issue. Most existing works require large and sufficient data to construct data-based criteria, which are intractable in data-free scenarios without numerical and experimental data. To this end, we propose a novel physics-driven sensor placement optimization (PSPO) method for temperature field reconstruction using a physics-based criterion to optimize sensor locations. In our methodological framework, we firstly derive the theoretical upper and lower bounds of the reconstruction error under noise scenarios by analyzing the optimal solution, proving that error bounds correlate with the condition number determined by sensor locations. Furthermore, the condition number, as the physics-based criterion, is used to optimize sensor locations by the genetic algorithm. Finally, the best sensors are validated by reconstruction models, including non-invasive end-to-end models, non-invasive reduced-order models, and physics-informed models. Experimental results, both on a numerical and an application case, demonstrate that the PSPO method significantly outperforms random and uniform selection methods, improving the reconstruction accuracy by nearly an order of magnitude. Moreover, the PSPO method can achieve comparable reconstruction accuracy to the existing data-driven placement optimization methods.

Improving the Step Response of Flexible Systems in the Presence of Real Nonminimum Phase Zeros

Abstract It is well known that real nonminimum phase (RNMP) zeros impose a tradeoff between the settling time and undershoot in the step response of flexible systems. Existing methods to alleviate this tradeoff predominantly rely on various advanced control strategies without delving into a broader mechatronic approach that combines physical system and control system design. To address this gap, this article proposes a proportional viscous damping-based physical system design in combination with feedback control and prefilter design. First, the effect of proportional viscous damping on RNMP zeros of flexible systems is established to propose a damping strategy that pushes all the RNMP zeros further away from the imaginary axis. Then, a step-by-step mechatronic system design process is presented to apply this damping strategy along with a full-state feedback control strategy and prefilter to a multi-degree-of-freedom (DoF) flexible system. The application of this design process yields simultaneous improvement in the settling time and undershoot in the step response of this flexible system.

A model-based approach for self-adaptive security in CPS: Application to smart grids

Security risk assessment is an important challenge in the design of Cyber Physical Systems (CPS). Even more importantly, the intrinsically dynamical nature of these systems, due to changes in their environment, as well as evolutions in their infrastructures, makes them self-adaptive systems, where security aspects have to be considered in terms of management of detections and reactions for self-protection. In this work, we propose an approach to autonomously mitigate the threats in each reconfiguration at application or infrastructure levels of CPS. We propose and implement a framework for self-adaptive security: software architecture, design method, and integration with model-based decision. We use Attack-Defense Trees for modeling threats, and our approach involves security risk assessment, taking into account its balancing and coordination with quality-of-service aspects. We formulate and formalize the on-line decision problem to be solved at each cycle of the self-adaptation control loop in terms of Constraint Programming (CP) modeling and resolution. The CP model implements a set of constraints that allow to specify secure configurations, evaluated regarding their impact on system performance to pinpoint the most relevant one portraying a good balance between the security and quality of service. We perform validation of our approach with its application to Smart Grids, more particularly to an industrial case study from RTE (the French Energy Transmission company).

A Consequence-Informed Licensing Path Selection for the Design of Physical Protection Systems at Commercial Nuclear Power Facilities

The survivability of the domestic nuclear power industry depends on the cost-competitiveness of safe and secure nuclear power generation. Advanced reactor design concepts aim to have increased safety margins over traditional large light water reactors (LWRs). With increased safety margins comes the potential for a corresponding decrease in off-site risk to the general public from a hypothetical release of radioactivity due to sabotage or theft. Without sacrificing safety or security, advanced reactor designers may be able to achieve operational cost improvements over current LWRs in part by designing less burdensome physical protection systems (PPSs) and by replacing on-site response forces with off-site response forces. To accommodate these developments, the U.S. Nuclear Regulatory Commission is drafting new rulemakings for physical security when licensing through the current frameworks in 10 CFR 50 or 10 CFR 52 along with drafting an entirely new licensing framework: 10 CFR 53. A novel technology-inclusive consequence-informed methodology for the selection of the optimal licensing path for the design of PPSs at advanced fixed-site commercial nuclear power facilities is presented herein. This methodology proposes integrating security considerations at the beginning of a reactor facility design effort to streamline the licensing process. Off-site total effective dose equivalents at the exclusion area and low population zone boundaries were identified as the key metrics when determining a design’s most appropriate licensing path that in turn affects the design requirements placed upon the PPS. Given these metrics, source-term generation of potential adversary-induced physics-based sabotage actions utilizing severe accident modeling software and off-site plume dispersal modeling were identified as appropriate for determining siting constraints, potential target sets for hypothetical sabotage events, and their subsequent off-site dose consequences. The methodology proposes using the consequence results from the sabotage modeling, in combination with desired cost-saving PPS characteristics, to help inform the licensing path selection. Once a licensing path is chosen, the methodology utilizes the Design and Evaluation Process Outline to evaluate an effective PPS following the licensing requirements placed on the facility. This paper also presents examples of hypothetical commercial nuclear power facilities with varying consequence levels and demonstrations of how to select the optimal licensing pathways for each.

Complex infrastructure systems analysis and management: the theory of faults

PurposeThe purpose of this research is to provide a theoretical and practical theory and application that provides understanding and means to manage complex infrastructures.Design/methodology/approachIn this research, complexity, nonlinear, noncontinuous effects and aleatoric and data unknowns are bypassed by directly addressing systems' responses. Graph theory, statistics and digital signal processing (DSP) tools are applied within a theoretical framework of the theory of faults (ToF). Motivational complex infrastructure systems (CISs) are difficult to model. Data are often missing or erroneous, changes are not well documented and processes are not well understood. On top of it, under complexity, stalwart analytical tools have limited predictive power. The aleatoric risk, such as rain and risk cascading from interconnected infrastructures, is unpredictable. Mitigation, response and recovery efforts are adversely affected.FindingsThe theory and application are presented and demonstrated by a step-by-step development of an application to a municipal drainage system. A database of faults is analyzed to produce system statistics, spatio-temporal morphology, behavior and traits. The gained understanding is compared to the physical system's design and to its modus operandi. Implications for design and maintenance are inferred; DSP tools to manage the system in real time are developed.Research limitations/implicationsSociological systems are interest driven. Some events are intentionally created and directed to the benefit and detriment of the opposing parties in a project. Those events may be explained and possibly predicted by understanding power plays, not power functions. For those events, sociological game theories provide better explanatory value than mathematical gain theories.Practical implicationsThe theory provides a thematic network for modeling and resolving aleatoric uncertainty in engineering and sociological systems. The framework may be elaborated to fields such as energy, healthcare and critical infrastructure.Social implicationsToF provides a framework for the modeling and prediction of faults generated by inherent aleatoric uncertainties in social and technological systems. Therefore, the framework and theory lay the basis for automated monitoring and control of aleatoric uncertainties such as mechanical failures and human errors and the development of mitigation systems.Originality/valueThe contribution of this research is in the provision of an explicatory theory and a management paradigm for complex systems. This theory is applicable to a wide variety of fields from facilities and construction project management to maintenance and from academic studies to commercial use.

Signal detection of large scale MIMO physical layer space optical communication system based on genetic algorithm

In order to understand the signal detection design of large-scale MIMO physical layer spatial optical communication systems, the author proposes a research on signal detection of large-scale MIMO physical layer spatial optical communication systems based on genetic algorithms. Firstly, the author introduces the basic principles of large-scale MIMO physical layer spatial optical communication systems, analyzes signal detection issues and their challenges. Secondly, a nitty gritty acquaintance was given with hereditary calculation and its application in signal recognition. A genetic algorithm-based signal detection technology scheme was developed for MIMO-OFDM systems. The GA algorithm was contrasted with the ML algorithm and the BLAST algorithm to comprehend its performance. The following parameters served as the foundation for the outcomes of the simulation: The quantity of subcarriers in OFDM is K = 18, and the quantity of images sent per transporter is 165; Additionally, simulation was used to demonstrate how the genetic algorithm affected the MIMO-OFDM system's signal detection. Subsequent to concentrating on the location calculations in MIMO-OFDM frameworks, hereditary calculations are applied to flag discovery in MIMO-OFDM frameworks, to accomplish a decent split the difference among execution and computational intricacy.

Design of Cyber Bio-analytical Physical Systems: Formal methods, architectures, and multi-system interaction strategies

Integration of the Cyber–Physical System (CPS) concept with bio-analytical devices is highly desirable to enable device automation as well as to improve diagnostic and analytical capabilities. However, the modeling must account for entity interactions, system dynamics, and non-functional aspects required for proper device functionality.This paper presents a model-based system architecture that builds upon an extended timed automata-based formal technique. In contrast to prior works that utilized SysML or UML-based models, this allows for the wireless control of bio-analytical instruments. Using this formal method, the UPPAAL tool is used to model and test a case study called “A droplet flow cytometer for testing bacteria’s susceptibility to antibiotics”. The study shows the implications of formal techniques for the design and verification of wireless automation of high-throughput laboratory setups in Model-Based System Engineering (MBSE). Moreover, the paper extends the above aspects by adding the possibility to model multi-system interaction. This is used to analyze the trade-off between centralized and decentralized information flow strategies for better system performance under delay and bandwidth constraints. UPPAAL Stratego is used to analyze strategies for achieving specific delays and bandwidth consumption while avoiding packet losses in the event of network congestion. The results show that under strict delay constraints and high traffic, the use-case system selects the decentralized strategy over the centralized strategy. In low-traffic scenarios, the centralized strategy is more effective at ensuring the reliable operation of systems.

Effective physical protection system design and implementation at a radiological facility: an integrated and risk management approach

Abstract Lives are threatened whenever there is an act of theft or destruction against a nuclear and radiological facility thus, physical protection systems are effectively employed to prevent or mitigate loss of valuable assets. Health facilities that provide radiotherapy services have in their facility a temporary storage unit where disused radioactive sources 60Co, 137Cs and 192Ir are kept and this raises concerns for effective physical protection. An integrated physical protection System was considered to consolidate of all sub systems, sensors and elements related to protection system for an effectively secured environment at a radiological facility. Sequence adversary diagram (ASD) was developed to depict the paths that enemies can take to achieve sabotage or stealing objectives and analyze flews in the paths. The approach to this security system effectiveness focuses on using probabilistic statistical methods for risk evaluation considering detection, delays and response. This paper considers the basic and effective elements required for physical protection system for a radiological center and makes risk evaluation as an approach of security system effectiveness which can serve as fundamental guiding principle for decision makers in the establishment of an effective physical protection for a radiological center.

Network Uncertainty Quantification for Analysis of Multi-Component Systems

Abstract In order to impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

A screen-based or physical computing unit? Examining secondary students’ attitudes toward coding

In recent years there has been a growing emphasis placed on access to computational thinking (CT) instruction for every K-12 student in the United States (U.S.). Concurrently, calls for integrating CT concepts within authentic science, technology, engineering, and mathematics (STEM) contexts have also increased. This is reflected by the inclusion of CT in the Next Generation Science Standards and the Standards for Technological and Engineering Literacy. However, methods for teaching CT concepts within secondary level STEM courses vary drastically. Physical computing, the design and programming of physical systems or devices using computational thinking skills, has become increasingly popular in the U.S. in attempts to integrate CT within authentic STEM problem-solving contexts. Despite this rise in popularity, there remains a limited but growing body of research investigating physical computing pedagogy and student learning. A mixed methods design was used in this study to examine 170 middle school students’ attitudes toward coding and after participating in either a screen-based or physical computing unit. The results indicated that students who completed the screen-based unit reported statistically greater attitudes toward the classroom applications and career/future use of computing concepts. Students in the treatment group believed that physical computing made learning computing concepts more difficult, but they preferred the hands-on learning opportunities provided by physical computing. Furthermore, male students reported higher attitudinal ratings than females regarding the influence computing would have on their future academic and career choices. This study provides implications for improving physical computing instruction and integration within STEM education contexts.

Artificial Intelligence Control System Applied in Smart Grid Integrated Doubly Fed Induction Generator-Based Wind Turbine: A Review

Wind-driven turbines utilizing the doubly-fed induction generators aligned with the progressed IEC 61400 series standards have engrossed specific consideration as of their benefits, such as adjustable speed, consistent frequency mode of operation, self-governing competencies for voltage and frequency control, active and reactive power controls, and maximum power point tracking approach at the place of shared connection. Such resource combinations into the existing smart grid system cause open-ended problems regarding the security and reliability of power system dynamics, which needs attention. There is a prospect of advancing the art of wind turbine-operated doubly-fed induction generator control systems. This section assesses the smart grid-integrated power system dynamics, characteristics, and causes of instabilities. These instabilities are unclear in the wind and nonlinear load predictions, leading to a provisional load-rejection response. Here, machine learning computations and transfer functions measure physical inertia and control system design’s association with power, voltage, and frequency response. The finding of the review in the paper indicates that artificial intelligence-based machine and deep learning predictive diagnosis fields have gained prominence because of their low cost, less infrastructure, reduced diagnostic time, and high level of accuracy. The machine and deep learning methodologies studied in this paper can be utilized and extended to the smart grid-integrated power context to create a framework for developing practical and accurate diagnostic tools to enhance the power system’s accuracy and stability, software requirements, and deployment strategies.

Realization of quantum secure direct communication over 100\u2009km fiber with time-bin and phase quantum states

Rapid progress has been made in quantum secure direct communication in recent years. For practical application, it is important to improve the performances, such as the secure information rate and the communication distance. In this paper, we report an elaborate physical system design and protocol with much enhanced performance. This design increased the secrecy capacity greatly by achieving an ultra-low quantum bit error rate of <0.1%, one order of magnitude smaller than that of existing systems. Compared to previous systems, the proposed scheme uses photonic time-bin and phase states, operating at 50 MHz of repetition rate, which can be easily upgraded to over 1 GHz using current on-the-shelf technology. The results of our experimentation demonstrate that the proposed system can tolerate more channel loss, from 5.1 dB, which is about 28.3 km in fiber in the previous scheme, to 18.4 dB, which corresponds to fiber length of 102.2 km. Thus, the experiment shows that intercity quantum secure direct communication through fiber is feasible with present-day technology.

Digital engineering: expanding the advantage

ABSTRACT Digital transformation – the pervasive incorporation of digital technology into virtually every process and system – is arguably the greatest force of change within the naval engineering community. Digital innovation is disrupting traditional ship design paradigms and giving rise to new ways of modernising and sustaining a future integrated force structure. This paper highlights digital transformation as a core strategic initiative that is aligned with the U.S. Department of Defense Digital Engineering Strategy. Recognising the need to expand the U.S. Navy’s advantage over its competitors, this paper identifies foundational elements required to transform current engineering design and development processes. Next, a multi-factor framework is introduced to align traditional processes employed for physical system design and development with a new digital paradigm in recognition of the highly integrated nature of Model Based Systems Engineering (MBSE). Finally, discussion will focus on efforts underway to leverage advanced computational models and highlight the digital engineering use case for Naval Power and Energy Systems (NPES).

BPMN++ to support managing organisational, multiteam and systems engineering aspects in cyber physical production systems design and operation

Abstract Interdisciplinary engineering of cyber physical production systems (CPPS) are often subject to delay, cost overrun and quality problems or may even fail due to the lack of efficient information exchange between multiple interdisciplinary teams working in complex networks within and across companies. We propose a direct integration of multiteam and organisational aspects into the graphical notation of the systems engineering workflow. BPMN++, with eight new notational elements and two subdiagrams, enables the modelling of the required cooperation aspects. BPMN++ provides an improved overview, uniform notation, more compact presentation and easier modifiability from an engineering point of view. We also included a first set of empirical studies and historical qualitative and quantitative data in addition to subjective expert-based ratings to increase validity. The use case introduced to explain the procedure and the notation is derived from surveys in plant manufacturing focussing on the start-up phase and decision support at site. This, in particular, is one of the most complex and critical phases with potentially high economic impact. For evaluation purposes, we compare two alternative solutions for a short-term management decision in the start-up phase of CPPS using the BPMN++ approach.

Design of Secure Microcontroller-Based Systems: Application to Mobile Robots for Perimeter Monitoring.

This paper describes an original methodology for the design of microcontroller-based physical security systems and its application for the system of mobile robots. The novelty of the proposed methodology lies in combining various design algorithms on the basis of abstract and detailed system representations. The suggested design approach, which is based on the methodology, is modular and extensible, takes into account the security of the physical layer of the system, works with the abstract system representation and is looking for a trade-off between the security of the final solution and the resources expended on it. Moreover, unlike existing solutions, the methodology has a strong focus on security. It is aimed at ensuring the protection of the system against attacks at the design stage, considers security components as an integral part of the system and checks if the system can be designed in accordance with given requirements and limitations. An experimental evaluation of the methodology was conducted with help of its software implementation that consists of Python script, PostgreSQL database, Tkinter interface and available for download on our GitHub. As a use case, the system of mobile robots for perimeter monitoring was chosen. During the experimental evaluation, the design time was measured depending on the parameters of the attacker against which system security must be ensured. Moreover, the software implementation of the methodology was analyzed in compliance with requirements and compared with analogues. The advantages and disadvantages of the methodology as well as future work directions are indicated.

Guest Editors’ Introduction: Cross-Layer Design of Cyber–Physical Systems

Cyber–physical system (CPS) design is characterized by modeling a computer (or cyber) system <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">together</i> with the physical system that the computer controls. This approach differs from both classical control systems design and also embedded systems design. In the former case, given properties of the physical system or the “plant” to be controlled, a control law or strategy is derived, that when applied to the plant enforces the desired behavior on it. Such control laws are described mathematically, and their implementations in software already result in a CPS, viz., the plant together with the software implementation of the controller. But traditionally, the design of the control law did not take into account all the peculiarities of software implementation—such as delays involved in computing the control input based on the state of the plant, or numerical limitations of the processor running the software, or how faithfully the software implements the mathematical description of the controller. When these issues are not accounted for when designing the controller, there might be a deviation in the behavior of the system when analyzing the mathematical description of the controller, versus what would be observed with the software implementation.

A novel design on polymeric material recycling technology

The necessity for recycling of wastes has increased nowadays and there are various solutions according to the types of wastes which are presented accordingly. By observing these solutions, the recycling system from the waste collection and separation system of the long-term disappearing of polymer waste to the additive manufacturing design stage has been indicated. Waste collection and separation systems have been reviewed and systems to be used effectively in the systematic way have been exemplified. Among four different separating systems which are with rotating, rail and fixed containers, fixed container four-sorting waste separation systems were chosen and developed as a mechatronic system design. The mechatronic system design is very prominent in order to create efficient and economical mechanisms in fixed-container four-sorting waste separation collection system (FCWS) applications. In addition, physical mechatronic system design (MSD), mechanical design, material selection, electrical electronic design sub-heading and cost analysis were made. In this study, the necessity and importance of the waste separation plants are revealed

A Deep Learning Approach to Predict the Flow Field and Thermal Patterns of Nonencapsulated Phase Change Materials Suspensions in an Enclosure

The flow and heat transfer of a novel type of functional phase change nanofluids, nano-‎encapsulated phase change suspensions, is investigated in the present study using a deep neural ‎networks framework. A deep neural network was used to learn the natural convection flow and ‎heat transfer of the phase change nanofluid in an enclosure. A dataset of flow and heat transfer ‎samples containing 3290 samples of the flow field and temperature distributions was used to ‎train the deep neural network. The design variables were fusion temperature of nanoparticles, ‎Stefan number, and Rayleigh number. The results showed that the proposed combination of a ‎feed-forward neural network and a convolutional neural network as a deep neural network could ‎robustly learn the complex physics of flow and heat transfer of phase change nanofluids. The ‎trained neural network could estimate the flow and heat transfer without iterative and costly ‎numerical computations. The present neural network framework is a promising tool for the design ‎and prediction of complex physical systems‎.

Mechanistic basis of transport in unconfined swirling flows

Swirling flows constitute several physical systems, such as the lift-enhancers on the flapping wings in animal flight and mechanical blood pumps. Swirls are stable due to inhibited mixing. However, the modulation of mixing in the swirl due to ambience is not known. Here, we study the transport phenomena in a non-reacting unconfined constant-density Newtonian axisymmetric swirling flow using a two-dimensional model. The objective is to investigate how diffusive amplification varies with radial distance from the geometric center of the swirl. The present work generates feedback on the extent of mixing and has implications in an integrative design of physical systems.

Performance-based control co-design of building structures with controlled rocking steel braced frames via neural dynamic model

Controlled rocking steel braced frames (CRSBFs) are modern systems for resilient building structures known for their effective energy dissipation and self-centering features. In a CRSBF, post-tensioned (PT) strands and shear fuses are the distinct features providing the self-centering and energy dissipation mechanisms. As a relatively new structural system, there is a need to study this system’s optimal design. Control co-design has gained interest in recent years as a class of integrated engineering system design methods as an alternative to the traditional approach of optimizing the structural design and sequentially optimizing the control system’s design. It considers the direct relationship between physical and control system design decisions to discover non-obvious design solutions that enable new performance and functionality levels. This paper proposes a performance-based control co-design methodology for building structures integrating CRSBFs that concurrently minimizes the mainframe weight and determines the CRSBF design parameters subject to design code requirements as the optimization constraints. The patented neural dynamic model of Adeli and Park is used in this research to solve the nonlinear optimization problem. The seismic performance evaluation of the proposed methodology includes a shear frame and a nonlinear 6-story 3D building structure. The 6-story building model consists of 282 nodes with 1,692 degrees of freedom. A total of 610 frame elements, 8 PT strands with nonlinear material, and 32 nonlinear links are determined without requiring high-performance computing. Results show that the energy dissipation mechanism effectively reduces the seismic demand in structural members. The proposed performance-based control co-design methodology can lead to 21% reduction in the total weight of the 6-story frame structure.