Showing papers on "Modeling and simulation published in 2017"

Software toolkit for modeling, simulation, and control of soft robots

Abstract: The technological differences between traditional robotics and soft robotics have an impact on all of the modeling tools generally in use, including direct kinematics and inverse models, Jacobians, and dynamics. Due to the lack of precise modeling and control methods for soft robots, the promising concepts of using such design for complex applications (medicine, assistance, domestic robotics...) cannot be practically implemented. This paper presents a first unified software framework dedicated to modeling, simulation and control of soft robots. The framework relies on continuum mechanics for modeling the robotic parts and boundary conditions like actuators or contacts using a unified representation based on Lagrange multipliers. It enables the digital robot to be simulated in its environment using a direct model. The model can also be inverted online using an optimization-based method which allows to control the physical robots in the task space. To demonstrate the effectiveness of the approach, we present various soft robots scenarios including ones where the robot is interacting with its environment. The software has been built on top of SOFA, an open-source framework for deformable online simulation and is available at https://project.inria.fr/softrobot/

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

Abstract: GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc.

Channel Measurements, Modeling, Simulation and Validation at 32 GHz in Outdoor Microcells for 5G Radio Systems

Abstract: In this paper, based on outdoor microcellular channel measurements at 32 GHz for 5G radio systems, a comprehensive channel modeling, simulation, and validation are performed. The directional-scan-sounding measurements using a horn antenna rotated with an angular step at the receiver are carried out, which constitutes a virtual array to form a single-input multiple-output radio channel. The directional- and omni-directional path-loss models are developed by using close-in and floating-intercept methods. Non-parametric and parametric methods are applied to extract large-scale channel parameters (LSPs). The non-parametric method is based on the definition of a channel parameter, whereas the parametric method is derived by the space-alternating generalized expectation–maximization (SAGE) algorithm, which can de-embed an antenna pattern. It is found that the LSPs in the angular domain are significantly different by using the two methods; however, the LSPs in the delay domain almost stay the same. By comparing the LSPs with the parameter table at 32 GHz with 3GPP standard, it is found that 3GPP LSPs should be corrected at the International Telecommunications Union-assigned millimeter wave (mmWave) frequencies for 5G. In this paper, the channel simulation is implemented by using the quasi-deterministic radio channel generator (QuaDRiGa) platform recommended by 3GPP. By comparing the LSPs with the simulated and measured results, it is found that QuaDRiGa is a good platform at the mmWave band, even if it is originally developed for channel simulation below 6 GHz. The results of this paper are important and useful in the simulations and design of future 5G radio systems at 32 GHz.

Modeling and simulation of solar water heater: A TRNSYS perspective

Abstract: Product design and optimization is a process of interpolation through iteration. Rating and certification process involves thorough testing of the product in standard test conditions. But real world experiments are full of variations and uncertainties. Moreover it is not feasible to create extreme testing environments in laboratory experiments. In many cases physical experiments are not possible at all due to excessive run duration, trade off and socio-financial implications. In such cases simulation is a promising alternate for performance analysis and design optimization. Professionals and researchers also face similar problems while working on solar energy system. There is a fast growing market of solar water heater worldwide. Solar water heating system is transient in nature and its performance depends on dynamic parameters. TRNSYS is transient system simulation software which provides good agreement within error ranging from 5% to 10%. Critical review of simulation of solar water heating system including early works, comparative analysis of popular simulation tools and their architecture in perspective of TRNSYS is presented. Assumptions, modeling of different components, merits and limitations of simulation are also discussed.

Mathematical Modeling of THz Point Spread Function and Simulation of THz Imaging Systems

Abstract: This paper presents a comprehensive theory for cohesive mathematical modeling and simulation of THz imaging systems. For mathematical modeling of the point spread function (PSF), system and transmission variables such as spectrum, absorption coefficient, beam divergence, and depth of focus are incorporated into the Gaussian beam distribution. The raster scanning process is mathematically modeled as the convolution of the object function and the PSF. Simulated transmission THz images are achieved as a result. The simulated THz images, compared to the experimental THz images, show great accuracy in terms of the location of the details and structural similarity.

Deep Learning the Physics of Transport Phenomena.

Abstract: We have developed a new data-driven paradigm for the rapid inference, modeling and simulation of the physics of transport phenomena by deep learning. Using conditional generative adversarial networks (cGAN), we train models for the direct generation of solutions to steady state heat conduction and incompressible fluid flow purely on observation without knowledge of the underlying governing equations. Rather than using iterative numerical methods to approximate the solution of the constitutive equations, cGANs learn to directly generate the solutions to these phenomena, given arbitrary boundary conditions and domain, with high test accuracy (MAE$<$1\%) and state-of-the-art computational performance. The cGAN framework can be used to learn causal models directly from experimental observations where the underlying physical model is complex or unknown.

Contact Dynamics Modeling and Simulation of Tether Nets for Space-Debris Capture

Abstract: A proposed method for containing the growth of space debris, which jeopardizes operation of spacecraft, is the active debris removal of massive derelict spacecraft and launcher upper stages by means of tether nets. The behavior of nets in space is not well known; therefore, numerical simulation is needed to gain understanding of deployment and capture dynamics. In this paper, a lumped-parameter approach for modeling the net and different models of contact dynamics are presented. A continuous compliant approach for the normal contact force and a modified damped bristle model for the friction force are chosen. The capability of the developed simulation tool to represent multiple dynamic conditions is demonstrated in this paper, and the results of a deployment dynamics simulation are presented; this reveals a snapping behavior of tension. Simulation of net-based capture of cylindrical debris in microgravity and vacuum conditions is performed with the presented tool. The effect of employing different contact ...

Research Challenges in Modeling and Simulation for Engineering Complex Systems

Abstract: ion layer Function Model layer The code of a particular model (or component) Model framework layer Collection of model classes, components, and libraries for a single application area, such as network simulation or PDE solution Simulator layer Provides a single paradigm for simulation time, space, naming, parallelism, and synchronization for use in one component of a (possibly) federated simulation Component federation layer Provides interface code to allow independently created submodels, possibly written in different languages, to communicate, synchronize, and interoperate in various ways to become a single federated model Load management layer Within one parallel model execution, measures resource utilization (time, energy, bandwidth, memory) at runtime and dynamically manages or migrates loads to optimize some performance metric Ensemble layer Runs many instances of the same model as an ensemble in a single large job, for such purposes as parameter sensitivity studies, parameter optimization, variance estimation. Handles scheduling, failures, accounting, and time estimates, allocates file directories, decides on ensemble termination, etc. Operating system /job scheduler layer Runs independent jobs in parallel. Provides processes, interprocess communication, I/O, files systems, etc. 62 C. Carothers et al.

Tolerance analysis — Form defects modeling and simulation by modal decomposition and optimization

Abstract: Tolerance analysis aims on checking whether specified tolerances enable functional and assembly requirements The tolerance analysis approaches discussed in literature are generally assumed without the consideration of parts’ form defects This paper presents a new model to consider the form defects in an assembly simulation A Metric Modal Decomposition (MMD) method is henceforth, developed to model the form defects of various parts in a mechanism The assemblies including form defects are further assessed using mathematical optimization The optimization involves two models of surfaces: real model and difference surface-base method, and introduces the concept of signed distance The optimization algorithms are then compared in terms of time consumption and accuracy To illustrate the methods and their respective applications, a simplified over-constrained industrial mechanism in three dimensions is also used as a case study

A Simple-to-Use BDI Architecture for Agent-Based Modeling and Simulation

Abstract: With the increase of computing power and the development of user-friendly multi-agent simulation frameworks, social simulations have become increasingly realistic. However, most agent architectures in these simulations use simple reactive models. Cognitive architectures face two main obstacles: their complexity for the field-expert modeler, and their computational cost. In this paper, we propose a new cognitive agent architecture based on the Belief-Desire-Intention paradigm integrated into the GAMA modeling platform. Based on the GAML modeling language, this architecture was designed to be simple-to-use for modelers, flexible enough to manage complex behaviors, and with low computational cost. This architecture is illustrated with a simulation of the evolution of land-use in the Mekong Delta.

Modeling and simulation of planar multibody systems considering multiple revolute clearance joints

Abstract: This paper presents a general procedure for dynamic modeling and simulation of planar multibody systems considering multiple revolute clearance joints The normal contact force is evaluated by a hybrid continuous contact force model, established on the base of the Lankarani–Nikravesh (L–N) model and the elastic foundation model The LuGre friction law is employed to describe the tangential effect The effectiveness of the presented methodology is demonstrated through the comparisons with the MSC ADAMS software simulation results of a slider–crank mechanism with clearance joints Then, the system behavior affected by dynamic interaction of three revolute clearance joints is analyzed and some kinds of 27 combination modes are presented Additionally, a comprehensive analysis of the system responses in a wide range of dynamic simulation parameters is conducted to find out some inner rules existed in the mechanical system with revolute clearance joints Results show that there exists a strong dynamic interaction between different clearance joints, indicating that all joints should be modeled as imperfect to achieve a further understanding of multibody system behavior Also, the clearance joint nearer to the input link is found to suffer more serious contact effects, require more input torque and cost longer computational time Furthermore, the system dynamics relies on many factors, even a small change of which may lead to different system responses, changing from periodic to chaotic and the other way around In addition, several characteristic values have been captured from the simulation results, which need to be paid more attention in use

Unbiased simulation of near-Clifford quantum circuits

Abstract: Modeling and simulation is essential for predicting and verifying the behavior of fabricated quantum circuits, but existing simulation methods are either impractically costly or require an unrealistic simplification of error processes. We present a method of simulating noisy Clifford circuits that is both accurate and practical in experimentally relevant regimes. In particular, the cost is weakly exponential in the size and the degree of non-Cliffordness of the circuit. Our approach is based on the construction of exact representations of quantum channels as quasiprobability distributions over stabilizer operations, which are then sampled, simulated, and weighted to yield unbiased statistical estimates of circuit outputs and other observables. As a demonstration of these techniques we simulate a Steane [[7,1,3]]-encoded logical operation with non-Clifford errors and compute its fault tolerance error threshold. We expect that the method presented here will enable studies of much larger and more realistic quantum circuits than was previously possible.

Modeling, Simulation, and Comparison of Control Techniques for Energy Storage Systems

Abstract: This paper describes the modeling and formulation of a variety of deterministic techniques for energy storage devices, namely the PI, H-infinity, and sliding mode controllers. These techniques are defined based on a general, yet detailed, energy storage device model, which is accurate for transient stability analysis. The paper also presents a thorough statistical comparison of the performance and robustness of the considered control techniques, using stochastic dynamic models and a variety of disturbances and scenarios. The case study is based on a 1479-bus model of the all-island Irish transmission system and an energy storage device actually installed in the system.

Modeling and simulation practices for a computational thinking-enabled engineering workforce

Abstract: Computational thinking has been recognized as a collection of understandings and skills required for new generations of students not only proficient at using tools, but also at creating them and understanding the implication of their capabilities and limitations. This study proposes the combination of modeling and simulation practices along with disciplinary learning as a way to synergistically integrate and take advantage of computational thinking in engineering education. This paper first proposes a framework that identifies different audiences of computing and related computational thinking practices at the intersection of computer science and engineering. Then, based on a survey with 37 experts from industry and academia, this paper also suggests a series of modeling and simulation practices, methods, and tools for such audiences. Finally, this paper also reports experts’ identified challenges and opportunities for integrating modeling and simulation practices at the undergraduate level. © 2016 Wiley Periodicals, Inc. Comput Appl Eng Educ 25:62–78, 2017; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21779

Physics-based modeling approaches of resistive switching devices for memory and in-memory computing applications.

Abstract: The semiconductor industry is currently challenged by the emergence of Internet of Things, Big data, and deep-learning techniques to enable object recognition and inference in portable computers. These revolutions demand new technologies for memory and computation going beyond the standard CMOS-based platform. In this scenario, resistive switching memory (RRAM) is extremely promising in the frame of storage technology, memory devices, and in-memory computing circuits, such as memristive logic or neuromorphic machines. To serve as enabling technology for these new fields, however, there is still a lack of industrial tools to predict the device behavior under certain operation schemes and to allow for optimization of the device properties based on materials and stack engineering. This work provides an overview of modeling approaches for RRAM simulation, at the level of technology computer aided design and high-level compact models for circuit simulations. Finite element method modeling, kinetic Monte Carlo models, and physics-based analytical models will be reviewed. The adaptation of modeling schemes to various RRAM concepts, such as filamentary switching and interface switching, will be discussed. Finally, application cases of compact modeling to simulate simple RRAM circuits for computing will be shown.

Nonlocal elasticity theory for graphene modeling and simulation: prospects and challenges

Abstract: Abstract: This paper presents a literature review of recent research studies on the applications of nonlocal elasticity theory in the modeling and simulation of graphene sheets (GSs). The history, development and excellent properties of GSs are introduced. The details of nonlocal elasticity theory are also presented. A systematic introduction to the application of nonlocal elasticity on linear modeling and nonlinear modeling for single-layer graphene sheets (SLGSs) and multilayered graphene sheets (MLGSs) is also provided. The necessity of determining mechanical parameters and nonlocal parameters is discussed. Recommendations for future work are particularly presented. This work is intended to review the development of GSs, give an introduction to the research studies on nonlocal elasticity theory in the modeling of GSs, and provide recommendations for future research.

High-Fidelity Multi-Rotor Unmanned Aircraft System Simulation Development for Trajectory Prediction Under Off-Nominal Flight Dynamics

Abstract: The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description of recent NASA wind tunnel testing of multi-rotor propulsion and airframe components will be presented illustrating important experimental and data acquisition methods, and a description of preliminary propulsion and airframe models will be presented. Lastly, examples of predicted off-nominal flight dynamics and trajectories from the simulation will be presented.

Modeling and simulation of a hybrid system solar panel and wind turbine in the locality of Molleturo in Ecuador

Abstract: The modeling, simulation and analysis of the energy conversion equations describing the behavior of a hybrid system PV and wind turbine, hybrid system for electrical power generation. A numerical model based on the aforementioned equations was developed, coded and results were compared to experimental data. The model is intended to be used as an optimization and design tool for such hybrid systems. The model predicted results fairly compared to experimental data under various conditions. It is also announced the mathematical modeling of the hybrid system to perform a stability analysis. It is important to indicate that this analysis has been carried out in order that in the near future one or two of these energy generation systems can be massively exploited depending on the economic allocations that the Municipal GAD of Molleturo can carry out for these purposes.

Modeling and Simulation of Data Flow for VLAN-Based Communication in Substations

Abstract: IEC 61850, the standard for communication in substations, has resolved the interoperability between intelligent electronic devices (IEDs) from different vendors. Thus, the IEDs' uniform communication standard contributes to the realization of more sophisticated functionality in substation automation systems. However, there are still several issues unsolved for the simulation, planning, and extension of substation communication network (SCN). This paper proposes three kinds of mathematical models for typical data flow within substations according to IEC 61850, which are cyclic data, stochastic data, and burst data. Thereby, a quantitative analysis of data flow is carried out for a typical substation based on the proposed data models. The advantage of virtual local area network (VLAN) and impacts of system faults, as well as network topologies, on a VLAN-based network are evaluated and simulated by OPNET Modeler. The data flow models are beneficial for the acquisition of more convincing results to assess network performance. Thus, the simulation results for a sample substation can be used to support power utility personnel with the planning and construction process of SCN.

On the Pore-Scale Modeling and Simulation of Reactive Transport in 3D Geometries

Abstract: Pore-scale modeling and simulation of reactive flow in porous media has a range of diverse applications, and poses a number of research challenges. It is known that the morphology of a porous medium has significant influence on the local flow rate, which can have a substantial impact on the rate of chemical reactions. While there are a large number of papers and software tools dedicated to simulating either fluid flow in 3D computerized tomography (CT) images or reactive flow using porenetwork models, little attention to date has been focused on the pore-scale simulation of sorptive transport in 3D CT images, which is the specific focus of this paper. Here we first present an algorithm for the simulation of such reactive flows directly on images, which is implemented in a sophisticated software package. We then use this software to present numerical results in two resolved geometries, illustrating the importance of pore-scale simulation and the flexibility of our software package.

Frequency-Domain Modeling and Simulation of DC Power Electronic Systems Using Harmonic State Space Method

Abstract: For the efficiency and simplicity of electric systems, the dc power electronic systems are widely used in a variety of applications such as electric vehicles, ships, and aircraft and in homes. In these systems, there could be a number of dynamic interactions and frequency coupling between network and loads and other converters. Hence, time-domain simulations are usually required to consider such a complex system behavior. However, simulations in the time domain may increase the calculation time and the utilization of computer memory. Furthermore, frequency coupling driven by multiple converters with different switching frequencies or harmonics from ac–dc converters makes that harmonics and frequency coupling are both problems of ac system and challenges of dc system. This paper presents the modeling and simulation methods of a large dc system by using the harmonic state space (HSS) modeling. Through this method, the required computation time and CPU memory can be reduced, where this faster simulation can be an advantage of a large network simulation. Besides, the achieved results show the same results as that of the nonlinear time-domain simulation. Furthermore, the HSS modeling can describe how the frequency components are coupled with each other through the different switching frequency of each converter.

Modeling and Simulation of a Grid-Integrated Photovoltaic System Using a Real-Time Digital Simulator

Abstract: This paper discusses the modeling and simulation of a grid-integrated photovoltaic (PV) system on a real-time digital simulator. The modeling of the PV array on the simulator, as well as, the power converter and controls for the PV system is discussed. An analysis of the real-time operation of the PV system, is presented. The benefits and considerations of power hardware in the loop simulations with a physical PV-grid converter are discussed.

Analysis and simulation of hybrid electric vehicles for sedan vehicle

Abstract: This paper presents a modeling and simulation of two different vehicles topologies (parallel hybrid electric vehicle and series hybrid electric vehicle) using the ADVISOR (ADvanced Vehicle SimulatOR). An accurate analysis of the performance of a hybrid electric vehicle, as well as of its consumption and pollution level, requires a dynamic analysis of its behavior. Two kinds of simulation tools for electric and hybrid electric vehicles exist: steady state and dynamic tools. An accurate analysis of the vehicle performance requires a dynamic model that includes many components such as its electric motor, its batteries and its motor controller. The central controller of this sedan consists of I/O Board, Adapter and Microcontroller of motor drive. In a first step, the vehicle components are sized, using a power flow analysis, to meet the requirements of energy and power of a typical “Sedan vehicle”. In a second step, simulation results are presented and discussed to analysis complexity and performance.

Semantics and Efficient Simulation Algorithms of an Expressive Multilevel Modeling Language

Abstract: The domain-specific modeling and simulation language ML-Rules is aimed at facilitating the description of cell biological systems at different levels of organization Model states are chemical solutions that consist of dynamically nested, attributed entities The model dynamics are described by rules that are constrained by arbitrary functions, which can operate on the entities’ attributes, (nested) solutions, and the reaction kinetics Thus, ML-Rules supports an expressive hierarchical, variable structure modeling of cell biological systems The formal syntax and semantics of ML-Rules show that it is firmly rooted in continuous-time Markov chains In addition to a generic stochastic simulation algorithm for ML-Rules, we introduce several specialized algorithms that are able to handle subclasses of ML-Rules more efficiently The algorithms are compared in a performance study, leading to conclusions on the relation between expressive power and computational complexity of rule-based modeling languages

Mercury: Performance and Dependability Evaluation of Systems with Exponential, Expolynomial, and General Distributions

Abstract: The evaluation of dependability or performance of general systems usually relies on the assistance of stochastic modeling and simulation tools. Those software packages enables the creation of models and computation of metrics quickly and accurately. This paper introduces the Mercury tool, which is an integrated software that enables creating and evaluating Reliability Block Diagrams, Stochastic Petri Nets, Continuous Time Markov Chains, and Energy Flow Models. Mercury provides a graphical user interface, a script language for command-line interface, and also an API (Application Programming Interface) that enables interaction through external applications. The evaluation of models is not restricted to the assumption of Exponential distributions, which is a common constraint in other similar tools. Mercury implements a simulation framework that allows more than 25 probability distributions, as well as a moment matching method that enables expolynomial —phase-type —distributions for models solved through numerical analysis. This paper presents the main features and methods available in Mercury to aid the dependability and performance evaluation of various systems, for both academy and industry. The accuracy and applicability of the tool is illustrated by a case study of packet loss and throughput for a Video on Demand (VoD) system.