Modeling and simulation

About: Modeling and simulation is a research topic. Over the lifetime, 10273 publications have been published within this topic receiving 111550 citations.

Modeling, simulation, and verification of large DC power electronics systems

Abstract: This paper describes the modeling and simulation of large DC power electronics systems consisting of distributed DC/DC power converters. These systems have become very popular in aerospace power systems due to their high reliability. Modularized modeling approaches and averaging techniques for power converters have allowed the modelling of large, complex DC power systems. Methods for analyses of these system are discussed. Design of experiments (DoE) is used as an analysis tool for verification of these large systems. DoE reduces the number of computer runs which are necessary to analyze the performance of complex power systems consisting of hundreds of DC/DC power converters. DoE also provides valuable information about the effect of changes in system parameters on the performance of the system. DoE provides information about various operating scenarios and identification of the ones with potential for instability. Examples using applications of DoE to the analysis and verification of large DC systems are provided.

Knowledge-based simulation : methodology and application

Abstract: Methodology - the application of artificial intelligence techniques to simulation the DEVS-SCHEME modeling and simulation environment methods for qualitative modelling in simulation dynamic templates and semantic rules and facts in a simulation advisor and certifier a rule-based approach to the generation of model structures automatic models generation for trouble-shooting from CAD/CAM to simulation - automatic model generation for mechanical devices applications - knowledge-based simulation at Rand an architecture for high-level human task animation control the acquisition of cognitive simulation models strategic automatic discovery system (STRADS) uncertainty management in battle-planning software.

Soft Errors : From Particles to Circuits

Abstract: Foreword Preface Acknowledgments Authors Editor Introduction Glossary ENVIRONMENTS: DEFINITION AND METROLOGY Terrestrial Cosmic Rays and Atmospheric Radiation Background Primary Cosmic Rays Historical Background Extragalactic and Galactic Cosmic Rays (GCRs) Solar Wind and Solar Energetic Particles Magnetospheric Cosmic Rays Secondary Cosmic Rays in the Atmosphere and at Ground Level Development of Air Showers Modulation Factors of Particle Production in the Atmosphere and at Ground Level Radiation Environment at Ground Level (Particles, Flux, Variations, Shielding) Particle Fluxes at Sea Level Flux Variations Shielding Issues Synthesis Tools, Codes, and Models to Simulate Atmospheric and Terrestrial CRs SEUTEST EXPACS (PARMA Model) QARM CORSIKA PLANETOCOSMICS CRY References Detection and Characterization of Atmospheric Neutrons at Terrestrial Level: Neutron Monitors Neutron Monitors (NM) Historical Background Neutron Monitor Design and Operation Neutron Monitor Detection Response Plateau de Bure Neutron Monitor PdBNM Design PdBNM Installation and Operation Connection to the Neutron Monitor Database PdBNM Monte Carlo Simulation Concluding Remarks References Natural Radioactivity of Electronic Materials Radioactivity Radioactive Decay Alpha-Particle Emission Radioactive Nuclides in Nature Primordial Radionuclides Uranium Decay Chain Thorium Decay Chain Cosmic-Ray-Produced Radionuclides Radon Radionuclides and Radioactive Contamination in Advanced CMOS Technologies Alpha Radiation from Interconnect Metallization and Packaging Materials Emissivity Model Analytical Model for Monolayers Analytical Model for Multilayer Stack Universal Nomogram for Bulk Silicon References Alpha-Radiation Metrology in Electronic Materials Introduction Alpha-Particle Detection Techniques: Terms and Definitions Gas-Filled Counters Principle of Operation Ionization Counters Proportional Counters Ultralow-Background Alpha Counter Design and Operation of the UltraLo-1800 Signal Generation and Rejection Pulse and Event Classification Cosmogenics and Radon Issues Example of Measurements Multicenter Comparison of Alpha-Particle Measurements Other Techniques Silicon Alpha Detectors Liquid and Solid-State Scintillators ICP-MS and VPD ICP-MS References SOFT ERRORS: MECHANISMS AND CHARACTERIZATION Particle Interactions with Matter and Mechanisms of Soft Errors in Semiconductor Circuits Interactions of Neutrons with Matter Cross Section Types of Neutron-Matter Interactions Recoil Products Interaction of Thermal Neutrons with 10B Atmospheric Neutron-Silicon Interaction Databases Interactions of Charged Particles with Matter Ionization Stopping Power Range Alpha Particles Heavy Ions Electrons Interaction of Protons with Matter Interaction of Pions with Matter Interaction of Muons with Matter Basic Mechanisms of Single-Event Effects on Microelectronic Devices Charge Deposition (or Generation) Charge Transport Charge Collection SEU Mechanisms in Memories (Single-Bit Upset and Multiple-Cell Upset) SEE Mechanisms in Digital Circuits Sequential Logic Combinational Logic References Accelerated Tests Introduction Methodology and Test Protocols SEU Cross Section Test Equipment Requirements Test Plan Test Conditions Experiments Using Intense Beams of Particles High-Energy Neutrons Thermal Neutrons Protons Muons Alpha-Particle Accelerated Tests Using Solid Sources Evaluation of Various Neutron Broad-Spectrum Sources from a Simulation Viewpoint Simulation Details Nuclear Event Analysis Implications for the Soft-Error Rate References Real-Time (Life) Testing Introduction Real-Time Testing Methodology Instrumentation Issues Differentiation of the SER Components Statistics for RTSER: Typical Example Metrology of Atmospheric Neutron Flux Survey of a Few Recent RTSER Experiments IBM Intel Sony Tohoku University, Hitachi, and Renesas Electronics Cypress Xilinx NXP RTSER Experiments Conducted at ASTEP and LSM ASTEP and LSM Test Platforms RTSER Experiments Comparison with Accelerated Tests References SOFT ERRORS: MODELING AND SIMULATION ISSUES Modeling and Simulation of Single-Event Effects in Devices and Circuits Interest in Modeling and Simulation Main Approaches of Electrical Simulation at Device Level Main Simulation Approaches at Circuit Level Device-Level Simulation Transport Models Emerging Physical Effects TCAD Simulation Analytical and Compact Model Approaches Circuit-Level Simulation Approaches SPICE-Like Circuit Simulation Mixed-Mode Approach Full Numerical Simulation in the 3D Device Domain References Soft-Error Rate (SER) Monte Carlo Simulation Codes General-Purpose Monte Carlo Radiation-Transport Codes Review of Recent Monte Carlo Codes Dedicated to the SER Issue Intel Radiation Tool (IRT) PHITS-HyENEXSS Code System TIARA-G4 Detailed Description of the TIARA-G4 Code Circuit Architecture Construction Module Radiation-Event Generator Interaction, Transport, and Tracking Module SRAM Electrical-Response Module Soft-Error Rate Calculation Module Experimental versus Simulation Results: Discussion Impact of Thermal and Low-Energy Neutrons on a 40 nm SRAM Circuit Comparison between TIARA and TIARA-G4: Impact of the BEOL on the SER SER Estimation of a 65 nm SRAM under High-Energy Atmospheric Neutrons Effects of Low-Energy Muons on a 65 nm SRAM Circuit References SOFT ERRORS IN EMERGING DEVICES AND CIRCUITS Scaling Effects and Their Implications for Soft Errors Introduction Feature-Size Scaling Geometric Scaling Ion-Track Spatial Structure versus Device Dimensions Carrier Channeling in Wells and Electrical Related Effects Variability and SEE Critical Charge Increasing Sensitivity to Background Radiation Low-Energy Protons Atmospheric Muons Low-Alpha-Material Issue Trends and Summary for Ultrascaled Technologies References Natural Radiation in Nonvolatile Memories: A Case Study Introduction Flash Memory Architectures and Electrical Operation NOR Architecture NAND Architecture Radiation Effects in Floating-Gate Memories Modeling and Simulation of Nonvolatile Memories Using TIARA-G4 Platform Description of TIARA-G4 NVM Platform Physical Model Considered Simulation Results Experimental Characterization Experimental versus Simulation Results: Discussion References SOI, FinFET, and Emerging Devices Introduction Silicon-on-Insulator (SOI) Technologies SEE Mechanisms in SOI Technologies 3D Simulation Study of Radiation Response of 50 nm FDSOI Devices SEU Sensitivity of FDSOI SRAM Cells Multiple-Gate Devices Impact of Quantum Effects Transient Response of Multiple-Gate Devices Radiation Hardness of Circuits Based on Multiple-Gate Devices Bulk and SOI FinFET Multichannel Architectures with Multiple-Gate Devices Multiple-Gate and Multichannel Devices with Independent Gates Simulation Details FinFET Devices MC-NWFET Devices Comparison between FinFET and MC-NWFET Devices Junctionless Devices Simulation Details Radiation Sensitivity of Individual Devices SEU Sensitivity of SRAM Cells III-V FinFET and Tunnel FET References

Chip-level charged-device modeling and simulation in CMOS integrated circuits

Abstract: Electrostatic discharge (ESD) accounts for over 30% of chip failure which occurred during chip manufacturing. Inadvertent touching by human body or contact with assembler tray can lead to such ESD failures. The most dominant ESD model is the charged-device model (CDM) wherein energy-destructive failure is incorporated resulting from rapid inflow, or outflow, of high current. Conventional modeling and simulations of the CDM are engineered to describe the behavior of ESD protection circuits, hence have a limitation to account for chip-level charge transfer. This paper presents a new methodology to simulate CDM behavior at chip level. A hierarchical approach associated with a CDM macromodel is developed to model a full-chip structure comprised of several functional subsystems and multiple power supplies. Full-chip CDM simulation provides the analysis of chip-level discharge paths and failure mechanisms, especially focusing on the gate oxide reliability. The proposed method can easily be applied to the CDM failure analysis of any product ICs in the early design stage. As an example, simulation results of a mixed-signal application-specific integrated circuit processed in a 0.25-/spl mu/m CMOS technology show high correlation with the measurement data.

System Blocks: A Physical Interface for System Dynamics Learning

Abstract: We present System Blocks, a physical interface that makes it easier for children to model and explore dynamic systems. A set of computationally enhanced blocks, made of wood and electronics, System Blocks can assist K-6 educators to teach the complex concepts of system dynamics and causalities. Learning to understand dynamic systems is an essential step in understanding the world around us. However, learning it at university, high school or even middle school level might be too late. By this age children have already developed their own models of how the world works. In this paper we will show how a set of physical objects can be used as a modeling and simulation tool, merging hands-on tinkering with computer simulation. Using blocks that behave as stocks, flows, variables and constants, our hope is that System Blocks will enable children younger than sixth grade to model, simulate and analyze systems that are meaningful to them.