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Computer simulation has been in the toolkit of industrial engineers for over 50 years and its value has been enhanced by advances in research, including both modeling and analysis, and in application software, both commercial and open source. However, "advances" are different from paradigm shifts. Motivated by big data, big computing and the big consequences of model-based decisions, it is time to reboot simulation for industrial engineering. [ABSTRACT FROM AUTHOR]

Recently, the application fields using permanent magnet motors have been rapidly expanding. Consequently, research on the production technology of permanent magnet motors is actively progressing, with a particular emphasis on the importance of the magnetization process during assembly after inserting permanent magnets into motors. Traditional designs of post-magnetization systems are tailored to address the issue of increased leakage flux at the corners of permanent magnets in embedded permanent magnet synchronous machines, based on the rotor structure. This involves using more power and designing larger magnetizing yokes to reduce heat generation through compensatory design. This paper proposes a design process that analyzes the effects of incomplete magnetization on motor characteristics and can derive a design that does not adversely affect motor performance during localized incomplete magnetization. The process validated through simulations and experiments can reduce power consumption by approximately 40% compared to traditional methods.

In this paper, the results carried out about a study over the possibilities of the Predictive Functional Control (PFC) are presented. The French professor Jacques Richalet and his collaborators developed the PFC. The results presented were obtained, when PFC is applied to industrial processes with complex dynamics such as high order, integral effects in the direct step that make the process asymptotically unstable in open loop and the undesirable phenomena of delay and inverse response. The main objective of the study is to demonstrate the potential offered by the PFC algorithm, in its simplestform, for the control of such processes. To this end, a methodology for synthesizing the PFC controller is developed based on the postulates and principles proposed by the precursors of the method, applied to several real case studies. In all cases, completely satisfactory results were obtained by means of simulation in Simulink-MatLab and finally the results of applying the method to the temperature control of the TCLab minilaboratory developed at the University of Utah are compared. This verifies the real possibilities of the FPC as a prominent alternative to control of real process. [ABSTRACT FROM AUTHOR]

To date, scholars have only conducted theoretical research on pipeline robots with cylindrical shapes over bends. However, not all pipeline robots are cylindrical in shape. This paper presents a theoretical investigation of a rectangular pipeline robot’s bending-passing ability using geometric and vector approaches and addresses dimensional limitations. Considering the shortcomings of most existing pipeline robots, such as the limited range of pipe diameters that are allowed, the inability to climb vertical pipes, and the single purpose, this study suggests a multi-functional modular pipeline robot that can support a wide range of pipe diameters. The drive module was constructed as a rectangular structure, which confirmed the accuracy of the bend-through theory. The driving module, as the central component of the pipeline robot, can accommodate pipe diameters ranging from 250 to 450mm. It was demonstrated that it can generate a traction force of approximately 600N, which can be used to drive other working modules.

The growth of goods transported by ship affects the entire maritime industry, which is central to the global supply chain. Faced with an increased pressure from the industry, ports need greater visibility on the flow of goods and logistics operations. To tackle this challenge, improvement opportunities as well as weaknesses must be identified in order to define an efficient data acquisition strategy that will allow port authorities to enhance their current visibility within their port ecosystem. This article presents the simulation of a digital shadow based on a Canadian port case study. The study uses the simulation of a digital shadow to diagnose a Canadian port authority's current visibility, with an accent on data accuracy, in order to identify improvement opportunities aimed at overcoming weaknesses identified in a current practice scenario and then compare the performance of the current system with said improvements in a second scenario. To our knowledge, this is the first simulation study on visibility performance assessment in a port's digital shadow. [ABSTRACT FROM AUTHOR]

In this paper, possibilities for network traffic protection in future hybrid passive optical networks are presented, and reasons for realizing and utilizing advanced network traffic protection schemes for various network traffic classes in these networks are analyzed. Next, principles of the Prediction-based Fair Wavelength and Bandwidth Allocation (PFWBA) algorithm are introduced in detail, focusing on the Prediction-based Fair Excessive Bandwidth Reallocation (PFEBR) algorithm with the Early Dynamic Bandwidth Allocation (E-DBA) mechanism and subsequent Dynamic Wavelength Allocation (DWA) scheme. For analyzing various wavelength allocation possibilities in Hybrid Passive Optical Networks (HPON) networks, a simulation program with the enhancement of the PFWBA algorithm is realized. Finally, a comparison of different methods of the wavelength allocation in conjunction with specific network traffic classes is executed for future HPON networks with considered protection schemes. Subsequently, three methods are presented from the viewpoint of HPON network traffic protection possibilities, including a new approach for the wavelength allocation based on network traffic protection assumptions. [ABSTRACT FROM AUTHOR]

Power system simulations with long-term data typically have large time steps, varying from one second to a few minutes. However, for PV inverter semiconductors in grid-connected applications, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be approximately 100 μs. This small time step requires long computation times to process yearly power production profiles. In this paper, we propose a fast fatigue simulation for inverter semiconductors using the quasi-static time-series simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature using a fast Fourier transform. The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 min, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. The error of the proposed method is significantly less than the conventional averaged thermal profile. A PV inverter that responds to a transactive energy system is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to cosimulate with system-level simulation tools that also adopt the quasi-static time-series concept. [ABSTRACT FROM AUTHOR]

Existing solid state drive (SSD) simulators unfortunately lack hardware and/or software architecture models. Consequently, they are far from capturing the critical features of contemporary SSD devices. More importantly, while the performance of modern systems that adopt SSDs can vary based on their numerous internal design parameters and storage-level configurations, a full system simulation with traditional SSD models often requires unreasonably long runtimes and excessive computational resources. In this work, we propose SimpleSSD, a high-fidelity simulator that models all detailed characteristics of hardware and software, while simplifying the nondescript features of storage internals. In contrast to existing SSD simulators, SimpleSSD can easily be integrated into publicly-available full system simulators. In addition, it can accommodate a complete storage stack and evaluate the performance of SSDs along with diverse memory technologies and microarchitectures. Thus, it facilitates simulations that explore the full design space at different levels of system abstraction.

The growth of goods transported by ship affects the entire maritime industry, which is central to the global supply chain. Faced with an increased pressure from the industry, ports need greater visibility on the flow of goods and logistics operations. To tackle this challenge, improvement opportunities as well as weaknesses must be identified in order to define an efficient data acquisition strategy that will allow port authorities to enhance their current visibility within their port ecosystem. This article presents the simulation of a digital shadow based on a Canadian port case study. The study uses the simulation of a digital shadow to diagnose a Canadian port authority’s current visibility, with an accent on data accuracy, in order to identify improvement opportunities aimed at overcoming weaknesses identified in a current practice scenario and then compare the performance of the current system with said improvements in a second scenario. To our knowledge, this is the first simulation study on visibility performance assessment in a port’s digital shadow.

The development of evaluation methods that allow improving the capture of quality data regarding software architectures is a topic of interest in Software Engineering. However, the dynamic of the traditional methods used for architecture evaluation is not enough to deal with the architectural complexity exhibit in new types of software products (such as cloud and web applications). In this paper, we present a model-to-model mapping based on modeling and simulation techniques that can be used as a complement of the traditional evaluation methods to improve the architecture design of complex systems. Using the set of elements that compose the architecture design of web applications, an abstraction model is designed with the aim to define the basic structure for the equivalent simulation model. Such a simulation model is detailed using two discrete-event formalisms: Discrete Event System Specification and Routed DEVS. In each case, a mapping is proposed to capture the full structure of the architecture with all its complexity. We compare both solutions to judge their applicability. Hence, the main advantages and disadvantages of both approaches are analyzed with the aim to evaluate their use in the architecture design stage of Software Engineering projects related to web applications. [ABSTRACT FROM AUTHOR]

While soft robotics is an emerging frontier of the robotics field, accurate modeling of large deformations for soft hyperelastic materials remains a challenge. Herein, we build on the existing open-source Multiphysics Object Oriented Simulation Environment (MOOSE) to accurately model neo-Hookean hyperelastic materials under user-defined loads and large strains. Excellent agreement between the simulated and theoretical results is obtained for simple geometries. Next, we show that our application can accurately model and predict the response of a real soft pneumatic actuator. To conclude, we demonstrate that the open-source nature of our simulation environment enables direct control over simulation parameters, allowing users to tailor the accuracy, convergence, and speed of their simulations.

The article presents a successful implementation of the milling process simulation at the Field-Programmable Gate Array (FPGA). By using FPGA, very rigorous Real-Time (RT) simulation requirements can be met. The response time of the FPGA simulations is significantly reduced, and the time synchronization is better than in a typical RT system implemented in software. The FPGA-based approach is characterized by enormous flexibility when it comes to input and output operations that can be implemented deterministically in RT. Complex simulation software has been implemented using the High Level Synthesis technique, which is a relatively easy and fast approach for FPGA programming without using complex Hardware Description Languages. The hardware functions are based on procedures written in high-level C programming language. The mathematical descriptions of simulations, results of computer simulations, Hardware-in-the-Loop Simulation experiments, and real experiments are presented. The approach presented in this paper can be used to simulate the dynamics of various mechatronic systems.

Power system simulations with long-term data typically have large time steps, varying from one second to a few minutes. However, for PV inverter semiconductors in grid-connected applications, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be approximately 100 μs. This small time step requires long computation times to process yearly power production profiles. In this paper, we propose a fast fatigue simulation for inverter semiconductors using the quasi-static time-series simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature using a fast Fourier transform. The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 min, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. The error of the proposed method is significantly less than the conventional averaged thermal profile. A PV inverter that responds to a transactive energy system is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to cosimulate with system-level simulation tools that also adopt the quasi-static time-series concept.

The rapid growth and widespread availability of technology has allowed enemies to dynamically develop countermeasures to military systems. Therefore, it is imperative that military systems be designed to account for these countermeasures. As such, technology roadmapping should be a critical activity in the acquisition of defense systems. Technology roadmaps provide a strategic vision for a system that accounts for the operational context, including evolving needs and technology changes. However, the operational context can be difficult to predict. This article suggests using wargaming coupled with combat simulation to better understand the operational context to allow for testing and refining technology roadmaps. Wargaming requires teams to roleplay friendly and enemy units to determine how each side adapts with the implementation of a new military system. Computer-based simulations can then convert the qualitative results from the wargame into quantitative metrics that further inform the roadmap. A case study is presented for a technology roadmap associated with an armored exoskeleton. Wargaming forecasted the countermeasures implemented by the enemy and the associated responses. The wargame results were coupled with models to quantitatively forecast the change in the warfighter's survivability and lethality. The wargame was then used to inform the technology roadmap. [ABSTRACT FROM AUTHOR]

As system dynamic behaviors are difficult to capture and analyze in model-based systems engineering, executable architectures, and simulation methods are widely studied to understand the behaviors that result from interactions amongst system components. However, most current studies often strive for analyzing independently specific aspects of architecture rather than capturing simultaneously the structural, behavioral, and performance related features, leading to failures of understanding the whole system from a global perspective. Accordingly, an interactive model-driven simulation that includes meta-model mapping and collaborative engine capabilities specific to DoDAF, Rhapsody, and STK simulations is first proposed to integrate the full advantages of different analytical tools. Then, a synergic engine is developed to provide synchronized control between time-driven and event-driven execution through the dynamic analysis process. Two executable techniques communicate with each other throughout the entire execution cycle to provide complementary necessary process information. The events occurred in the STK simulation scenario are used as the trigger of the executable state machine model that describes only the logical procedure of system behaviors without timeand space-related constraints. Last, an illustrative example of the Russian-Turkish Plane Incident is carried out to demonstrate the feasibility of the foregoing approach.

Several mathematical formalisms can be exploited to model complex systems, in order to capture different features of their dynamic behavior and leverage any available quantitative or qualitative data. Correspondingly, either quantitative models or qualitative models can be defined; bridging the gap between these two worlds would allow us to simultaneously exploit the peculiar advantages provided by each modeling approach. However, to date, the attempts in this direction have been limited to specific fields of research. In this paper, we propose a novel, general-purpose computational framework, named Fuzzy-mechanistic modeling of compleX systems (FuzzX), for the analysis of hybrid models consisting of a quantitative (or mechanistic) module and a qualitative module that can reciprocally control each other's dynamic behavior through a common interface. FuzzX takes advantage of precise quantitative information about the system through the definition and simulation of the mechanistic module. At the same time, it describes the behavior of components and their interactions that are not known in full details, by exploiting fuzzy logic for the definition of the qualitative module. We applied FuzzX for the analysis of a hybrid model of a complex biochemical system, characterized by the presence of positive and negative feedback regulations. We show that FuzzX is able to correctly reproduce known emergent behaviors of this system in normal and perturbed conditions. We envision that FuzzX could be employed to analyze any kind of complex system when quantitative information is limited, as well as to extend existing mechanistic models with fuzzy modules to describe those components and interactions of the system that are not fully characterized. [ABSTRACT FROM AUTHOR]

System-level electrostatic discharge (ESD) robustness design according to ISO10605 or IEC 61000-4-2 on printed circuit board (PCB) level is still a challenge). The blocking point is often the lack of accurate models of complete integrated circuits (ICs). Previously published methodologies to generate ESD models for ICs are all based on measurements of the complete IC, showing the drawback of complex, difficult and time-consuming measurements. This paper proposes a novel methodology to generate ESD models for complete ICs out of their design data. The proposed approach requires no measurements with the complete IC and hence can reduce the effort significantly. Furthermore, the methodology offers the possibility for automation, which further reduces the number of needed resources. It is based on the approach of black box modeling. This means simplified behavioral models are used, which contain solely the characteristic behavior in case of disturbance pulses. The methodology focuses on the transient behavior as well as the physical destruction limits of smart power products. Behavioral model in this context means the transient response due to disturbance pulse in terms of voltage drops and current drain. The procedure is explained and verified step by step on an exemplary product. It can be easily transferred to other products. System designers receive a powerful model for targeting certain robustness of their system against transient disturbances. Further enhancements of the methodology can enable also the soft failure assessment by simulation. [ABSTRACT FROM AUTHOR]

Stochastic methods can be used in problem solving and explanation of natural phenomena through the application of statistical procedures. The article aims to associate the regression analysis and systems simulation, in order to facilitate the practical understanding of data analysis. The algorithms were developed in Microsoft Office Excel software, using statistical techniques such as regression theory, ANOVA and Cholesky Factorization, which made it possible to create models of single and multiple systems with up to five independent variables. For the analysis of these models, the Monte Carlo simulation and analysis of industrial performance indicators were used, resulting in numerical indices that aim to improve the goals’ management for compliance indicators, by identifying systems’ instability, correlation and anomalies. The analytical models presented in the survey indicated satisfactory results with numerous possibilities for industrial and academic applications, as well as the potential for deployment in new analytical techniques.

Detecting faults on the anchor rods of power transmission line towers is an essential procedure for guaranteeing the safety, operability, and availability of the electric power system. Such a measure aims to minimize the risk of tower collapse and the associated costs due to the lack of energy, injuries to people, and damage to the reputation of the companies involved. In this letter, we report an alternative noninvasive and nondestructive detection technique through the acquisition of electromagnetic scattering parameters. A novel machine learning (ML) approach is proposed in order to achieve the advantages of such a technique and to deal with the respective drawbacks due to the complexity of signals acquired. A strategy to artificially increase the number of relevant samples in the dataset through the simulations of computational models is performed. Different ML classification algorithms are compared in the task of detecting structural faults in anchor rods in order to define the most suitable to this application. Finally, experimental results show that the methodology proposed achieves a high detection accuracy, surpassing other known methods. [ABSTRACT FROM AUTHOR]

In this paper, a system-of-systems (SoS) framework is proposed for bottom-up assessment of complex engineering projects. Two principles of SoS analysis (i.e., base-level abstraction and multilevel aggregation) are used to develop the proposed framework. At the base level, complex engineering projects are abstracted as various entities (i.e., human agents, resources, and information) whose attributes and interactions influence the dynamic behaviors of project systems. The performance of project systems at higher levels (i.e., activity level, process level, and project level) is then determined by aggregating entities at the levels below. Through the use of the proposed SoS framework, new dimensions of analysis for better understanding of the performance of engineering projects were explored. One application example of the proposed framework was demonstrated in a case study of a complex construction project. The findings highlight the capability of the proposed framework in providing a novel approach for bottom-up assessment of performance in engineering projects. [ABSTRACT FROM PUBLISHER]

Two new distributed speed advisory systems (SASs) are introduced in this paper. The systems implement consensus algorithms that guide a set of vehicles toward a common driving speed. A major innovation is that consensus is achieved over a multi-layer network, in which parallel network topologies of connected vehicles are superimposed. The reason for the use of these parallel networks is that, in this way, the state obfuscation is possible, with the benefit that common driving speed is attained with no vehicle knowing the exact state of other vehicles. Convergence of the SASs is formally proved and two new results for the consensus of multi-layer networks modeled via stochastic differential equations are introduced. The SASs are also validated via simulation and via a hardware-in-the-loop setup, in which a real vehicle interacts with simulated entities. [ABSTRACT FROM PUBLISHER]

Historically, robotics systems have not been built with an emphasis on security. Their main purpose has been to complete a specific objective, such as to deliver the correct dosage of a drug to a patient, perform a swarm algorithm, or safely and autonomously drive humans from point A to point B. As more and more robotic systems become remotely accessible through networks, such as the Internet, they are more vulnerable to various attackers than ever before. To investigate remote attacks on networked robotic systems we have leveraged HoneyPhy, a physics-aware honeypot framework, to create the HoneyBot. The HoneyBot is the first software hybrid interaction honeypot specifically designed for networked robotic systems. By simulating unsafe actions and physically performing safe actions on the HoneyBot we seek to fool attackers into believing their exploits are successful, while logging all the communication to be used for attacker attribution and threat model creation. In this paper, we present the HoneyBot and discuss our proof of concept implementation. Our HoneyBot prototype swaps between physical actuation and using prebuilt models of sensor behavior for simulation at runtime given user input commands. [ABSTRACT FROM PUBLISHER]

This paper addresses the simulation of the state of a discrete-time controlled cable-driven parallel robot (CDPR) with nondeformable or elastic cables over a given trajectory. Being given a CDPR, an arbitrary model for the coiling system and for the control strategy, we exhibit a simulation algorithm that allows one to determine, in a guaranteed way, the platform pose and the cable tensions at any time. We show that such a simulation may require a computing accuracy that imposes to use extended arithmetic and that discrete-time control may lead to drastic differences in the cable tensions as compared to usual continuous time simulation. Hence, the proposed simulation tool allows for a better estimation of the positioning accuracy together with safer estimation of the maximum of the cable tensions. [ABSTRACT FROM PUBLISHER]

We present a full system simulation framework for a network-on-chip (NoC)-based H.264 video decoder. By combining both the communication, i.e., the NoC and the processing, i.e., H.264 modules, components into the same simulation framework, we present for the first time the capability of simulating NoCs exercised with truly real traffic. Such a simulator can be utilized to evaluate performance metrics of systems-on-chip where the communication is done via NoCs, which are predicted to be the future communication paradigm of such systems. Because the NoC is exercised with real traffic instead of synthetic traffic such evaluations and optimizations can be more accurate and can lead to better design solutions. [ABSTRACT FROM PUBLISHER]

Cloud service providers are under constant pressure to improve performance, offer more diverse resource deployment options, and enhance application portability. To achieve these performance and cost objectives, providers need a comprehensive resource allocation system that handles both computational and network resources. A novel methodology is introduced to tackle the problem of allocating sufficient data center resources to client Virtual Machine (VM) reservation requests and connection scheduling requests. This needs to be done while achieving the providers' objectives and minimizing the need for VM migration. In this work, the problem of resource allocation in cloud computing data centers is formulated as an optimization problem and solved. Moreover, a set of heuristic solutions are introduced and used as VM reservation and connection scheduling policies. A relaxed suboptimal solution based on decomposing the original problem is also presented. The experimentation results for a diverse set of network loads show that the relaxed solution has achieved promising levels for connection request average tardiness. The proposed solution is able to reach better performance levels than heuristic solutions without the burden of long hours of running time. This makes it a feasible candidate for solving problems with a much higher number of requests and wider data ranges compared to the optimal solution. [ABSTRACT FROM AUTHOR]