609,299 research outputs found
Physics Informed Recurrent Neural Networks for Seismic Response Evaluation of Nonlinear Systems
Dynamic response evaluation in structural engineering is the process of
determining the response of a structure, such as member forces, node
displacements, etc when subjected to dynamic loads such as earthquakes, wind,
or impact. This is an important aspect of structural analysis, as it enables
engineers to assess structural performance under extreme loading conditions and
make informed decisions about the design and safety of the structure.
Conventional methods for dynamic response evaluation involve numerical
simulations using finite element analysis (FEA), where the structure is modeled
using finite elements, and the equations of motion are solved numerically.
Although effective, this approach can be computationally intensive and may not
be suitable for real-time applications. To address these limitations, recent
advancements in machine learning, specifically artificial neural networks, have
been applied to dynamic response evaluation in structural engineering. These
techniques leverage large data sets and sophisticated algorithms to learn the
complex relationship between inputs and outputs, making them ideal for such
problems. In this paper, a novel approach is proposed for evaluating the
dynamic response of multi-degree-of-freedom (MDOF) systems using
physics-informed recurrent neural networks. The focus of this paper is to
evaluate the seismic (earthquake) response of nonlinear structures. The
predicted response will be compared to state-of-the-art methods such as FEA to
assess the efficacy of the physics-informed RNN model
Regenerative life support system research and concepts
Life support systems that involve recycling of atmospheres, water, food and waste are so complex that models incorporating all the interactions and relationships are vital to design, development, simulations, and ultimately to control of space qualified systems. During early modeling studies, FORTRAN and BASIC programs were used to obtain numerical comparisons of the performance of different regenerative concepts. Recently, models were made by combining existing capabilities with expert systems to establish an Intelligent Design Support Environment for simpliflying user interfaces and to address the need for the engineering aspects. Progress was also made toward modeling and evaluating the operational aspects of closed loop life support systems using Time-step and Dynamic simulations over a period of time. Example models are presented which show the status and potential of developed modeling techniques. For instance, closed loop systems involving algae systeMs for atmospheric purification and food supply augmentation, plus models employing high plants and solid waste electrolysis are described and results of initial evaluations are presented
A Generalized Options-based Approach to Mitigate Perturbations in a Maritime Security System-of-Systems
Due to the complex and highly dynamic contexts in which systems operate nowadays, it has become crucial that, early in the architecting phase, System Architects take into account options to be utilized throughout the system's lifecycle to improve performance and lifecycle properties, such as flexibility. This paper introduces a preliminary approach that allows for the identification of relevant options, which are capable of mitigating perturbations negatively impacting a system of interest. The approach consists of the generation, evaluation and selection of relevant generalized options (enabling both changeability and robustness), and is demonstrated by application to a Maritime Security SoS case study. The inputs to the process are a list of desired design principles to implement in the system, and a list of perturbations that may affect the delivery of value to stakeholders (options are meant to mitigate perturbations). Four different metrics for option evaluation are proposed, together with techniques that can help during the process of selection of options.Massachusetts Institute of Technology. Systems Engineering Advancement Research Initiativ
Structural performance evaluation and optimization through cyber-physical systems using substructure real-time hybrid simulation
Natural hazards continue to demonstrate the vulnerability of civil infrastructure worldwide. Engineers are dedicated to improving structural performance against natural hazards with improved design codes and computational tools. These improvements are often driven by experiments. Experimental testing not only enables the prediction of structural responses under those dynamic loads but also provide a reliable way to investigate new solutions for hazard mitigation. Common experimental techniques in structural engineering include quasi-static testing, shake table testing, and hybrid simulation. In recent years, real-time hybrid simulation (RTHS) has emerged as a powerful alternative to drive improvements in civil infrastructure as the entire structure’s dynamic performance is captured with reduced experimental requirements. In addition, RTHS provides an attractive opportunity to investigate the optimal performance of complex structures or components against multi-hazards by embedding it in an optimization framework. RTHS stands to accelerate advancements in civil engineering, in particular for designing new structural systems or devices in a performance-based design environment.
This dissertation focuses on the use of cyber-physical systems (CPS) to evaluate structural performance and achieve optimal designs for seismic protection. This dissertation presents systematic studies on the development and validation of the dynamic substructuring RTHS technique using shake tables, novel techniques in increasing RTHS stability by introducing artificial damping to an under-actuated physical specimen, and the optimal design of the structure or supplemental control devices for seismic protection through a cyber-physical substructure optimization (CPSO) framework using substructure RTHS
Large scale modeling, model reduction and control design for a real-time mechatronic system
Mechatronics is the synergistic integration of the techniques from mechanical engineering, electrical engineering and information technology, which influences each other mutually. As a multidisciplinary domain, mechatronics is more than mechanical or electronics, and the mechatronic systems are always composed of a number of subsystems with various controllers. From this point of view, a lot of such systems can be defined as large scale system. The key element of such systems is integration. Modeling of mechatronic system is a very important step in developing control design of such products, so as to simulate and analyze their dynamic responses for control design, making sure they would meet the desired requirements. The models of large scale systems are always resulted in complex form and high in dimension, making the computation for modeling, simulation and control design become very complicated, or even beyond the solutions provided by conventional engineering methods. Therefore, a simplified model obtained by using model order reduction technique, which can preserve the dominant physical parameters and reveal the performance limiting factor, is preferred. In this dissertation, the research have chosen the two-wheeled self-balancing scooter as the subject of the study in research on large scale mechatronic system, and efforts have been put on developing a completed mathematical modeling method based on a unified framework from varitional method for both mechanical subsystem and electrical subsystem in the scooter. In order to decrease the computation efforts in simulation and control design, Routh model reduction technique was chosen from various model reduction techniques so as to obtain a low dimensional model. Matlab simulation is used to predict the system response based on the simplified model and related control design. Furthermore, the final design parameters were applied in the physical system of two-wheeled self-balancing scooter to test the real performance so as to finish the design evaluation. Conclusion was made based on these results and further research directions can be predicte
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Ultra-fast Imaging of Two-Phase Flow in Structured Monolith Reactors; Techniques and Data Analysis
This thesis will address the use of nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) techniques to probe the “monolith reactor”, which consists of a structured catalyst over which reactions may occur. This reactor has emerged as a potential alternative to more traditional chemical engineering systems such as trickle bed and slurry reactors. However, being a relatively new design, its associated flow phenomena and design procedures are not rigorously understood, which is retarding its acceptance in industry. Traditional observations are unable to provide the necessary information for design since the systems are opaque and dynamic. Therefore, NMR is proposed as an ideal tool to probe these systems in detail.
The theory of NMR is summarised and the development of novel NMR techniques is presented. Novel techniques are validated in simple systems, and tested in more complex systems to ascertain their quantitative nature, and to find their limitations. These techniques are improvements over existing techniques in that they either decrease the acquisition time (allowing the observation of dynamically-changing systems) or allow us to probe systems in different ways to extract useful information. The goal of this research is to better understand the flow phenomena present in such systems, and to use this information to design better, more efficient, more controllable industrial reactors.
The analysis of the NMR data acquired is discussed in detail, and several novel image-processing techniques have been developed to aid in the quantification of features within the images, and also to measure quantities such as holdup and velocity. These novel techniques are validated, and then applied to the systems of interest.
Various configurations of monolith reactor, ranging from low flow rate systems to more challenging (and more industrially relevant) turbulent systems, are probed using these methods, and the contrasting flow phenomena and performance of these systems are discussed, with a view to optimisation of the choice of design parameters
International Space Station Centrifuge Rotor Models A Comparison of the Euler-Lagrange and the Bond Graph Modeling Approach
The assembly and operation of the International Space Station (ISS) require extensive testing and engineering analysis to verify that the Space Station system of systems would work together without any adverse interactions. Since the dynamic behavior of an entire Space Station cannot be tested on earth, math models of the Space Station structures and mechanical systems have to be built and integrated in computer simulations and analysis tools to analyze and predict what will happen in space. The ISS Centrifuge Rotor (CR) is one of many mechanical systems that need to be modeled and analyzed to verify the ISS integrated system performance on-orbit. This study investigates using Bond Graph modeling techniques as quick and simplified ways to generate models of the ISS Centrifuge Rotor. This paper outlines the steps used to generate simple and more complex models of the CR using Bond Graph Computer Aided Modeling Program with Graphical Input (CAMP-G). Comparisons of the Bond Graph CR models with those derived from Euler-Lagrange equations in MATLAB and those developed using multibody dynamic simulation at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) are presented to demonstrate the usefulness of the Bond Graph modeling approach for aeronautics and space applications
Advanced Techniques for Assets Maintenance Management
16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018
Bergamo, Italy, 11–13 June 2018. Edited by Marco Macchi, László Monostori, Roberto PintoThe aim of this paper is to remark the importance of new and advanced techniques supporting decision making in different business processes for maintenance and assets management, as well as the basic need of adopting a certain management framework with a clear processes map and the corresponding IT supporting systems. Framework processes and systems will be the key fundamental enablers for success and for continuous improvement. The suggested framework will help to define and improve business policies and work procedures for the assets operation and maintenance along their life cycle. The following sections present some achievements on this focus, proposing finally possible future lines for a research agenda within this field of assets management
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