Circuit simulation 7 2

Simulation Lab 2 Manual. Instrumentation Laboratory. Marking scheme for the practical exam 8. The main function of engineering profession is to.

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• 7 segment display simulator online
• On the Thermal Models for Resistive Random Access Memory Circuit Simulation
• Semiconductor Device Modeling and Simulation for Electronic Circuit Design
• Catálogo Colectivo de las Universidades de Catalunya
• PartSim Circuit Simulator
• Mixed-signal Circuit Simulation in Altium NEXUS
• Circuit simulation and schematics.
• Volume 7 (2) 2001, 91-109

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7 segment display simulator online

Circuit simulation is a powerful methodology to generate differential mathematical models. Due to its highly accurate modeling capability, circuit simulation can be used to investigate interactions between the parts and processes of a cellular system. Circuit simulation has become a core technology for the field of electrical engineering, but its application in biology has not yet been fully realized.

As a case study for evaluating the more advanced features of a circuit simulation tool called Advanced Design System ADS , we collected and modeled laboratory data for iron metabolism in mouse kidney cells for a H ferritin HFt receptor, T cell immunoglobulin and mucin domain-2 TIM The internal controlling parameters of TIM-2 associated iron metabolism were extracted and the ratios of iron movement among cellular compartments were quantified by ADS.

The differential model processed by circuit simulation demonstrated a capability to identify variables and predict outcomes that could not be readily measured by in vitro experiments.

An average of 8. The endosome containing HFt lasted roughly 2 h. Both experimental data and the model showed that TIM-2 was not involved in the process of iron export. The extracted internal controlling parameters successfully captured the complexity of TIM-2 pathway and the use of circuit simulation-based modeling across a wider range of cellular systems is the next step for validating the significance and utility of this method.

There have been both classical and advanced uses of analogous electronic circuit concepts in evaluating biological systems. For more than several decades, both animal and plant physiologists have used models such as Ohm's Law to model environmental response Janes, ; Meier et al. A modern challenge has been to discover and interrelate cellular dynamics with higher-level outcomes Kitano, a. Biochemical systems theory BST provides a conceptual foundation for differential analysis of the functional requirements and design principles of a viable cell Savageau, , , Electrical circuits are also subject to differential analysis of their linear and nonlinear components McAdams and Shapiro, We propose that circuit simulation may be a powerful technique for realizing the potential of BST within the 21 st century discipline of computational systems biology, a field that aspires to evaluate complex biological systems through the use of computers Kitano, b.

Circuit simulation software has been extensively developed by semiconductor and electronics industries to handle circuit topologies having complex objectives for optimization and having many diverse interconnected components. Circuit simulation for biological systems was attempted several decades ago in the early years of the digital age Thomas and Mikulecky, , but usage has been infrequent. Its relevance may be renewed now both by a strong community effort to extensively crowd source the computer modeling of cells Helikar et al.

After new experimental findings go beyond the original knowledge for the modeled system, there is a need to model the newly discovered subsystem and integrate it into the prior model. Contemporary circuit simulation software provides an agile platform for inputting a differential model and extending it with a rich feature set of advanced numerical and optimization methods. To test a circuit simulation approach, we sought to examine iron, a cellular micronutrient for which both modeling and a new wave of experimental data exists.

Outside of cells, sources of iron in the bloodstream include both transferrin Tf and ferritin Ft. There are complex multicellular conditions of disease associated with increased serum levels of iron-loaded Tf and iron-loaded Ft Konijn et al. Recently, a mouse-specific T cell immunoglobulin and mucin domain containing TIM protein receptor, T cell immunoglobulin and mucin domain-2 TIM-2 , has been found to process iron delivery.

Regulatory effects of TIM-2 have been identified in both mouse brain glial cells Watanabe et al. Han et al. Ferritin is an iron storage and delivery protein made of both H and L subunits Han et al.

Although a mathematical model of iron metabolism in mammalian cells has been recently proposed Chifman et al. It is based upon iron uptake through the classical transferrin-transferrin receptor pathway and storage of iron within ferritin Klausner et al. State variables account for the movement of iron between a labile iron pool LIP and four types of proteins—transferrin receptor 1 TfR1 , exporter ferroportin Fpn , HFt, and active iron regulatory proteins IRPs Chifman et al.

In this study, we extended this model by developing governing equations for an additional set of TIM-2 dynamics and comparing outcomes of a differential model-based circuit simulation to laboratory data.

The outcome of the comparison between simulation data and laboratory data showed circuit simulation to be a valuable tool for quantifying emerging knowledge of the integral and complex role that micronutrients have in cellular physiology. Data and the experimental procedures for iron uptake and iron storage analysis are from Han et al. Brief summaries of iron uptake and storage methods are described below. The radio-activity of 55 Fe was measured.

The experiment was performed in triplicate. Collection times were at 0, 2, 4, 8, 24, and 48 h after incubation. The radio-activity of 55 Fe from extracts depleted of biotinylated ferritin was also measured.

Chemicals and cell cultures were purchased and handled as previously described Han et al. Selection for stable transfectants of TIM-2 was as previously described Han et al. The biotin-labeled apo-HFt was added to the cells. Biotin-HFt and 55 Fe in media were examined as exported products. The product was dialyzed in 0. Media were collected at 0, 2, 4, 24, and 48 h.

Activity of 55 Fe was counted from streptavidin pulling down solution. A mathematical model of iron homeostasis developed by Chifman et al. Time derivatives for the governing equations of this model are described in Equations 6—9. The concentration of TIM-2 active on cell membrane is not only affected by the combination reaction with exogenous ferritin, but also by the process of recycling them back to cell membrane. The rate of recycling is assumed to be equal to the rate of decrease of TIM-2 in the endosome.

Figure 1. Iron is subsequently either stored in endogenous HFt or exported to the media. Iron uptake by the TIM-2 receptor occurs at the cellular membrane. Unshaded ovals are for external HFt, and shaded ovals are for endogenous HFt. The question marks? The endocytosis of TIM-2 and the bounding of TIM-2 on the membrane with H-ferritin are hindered by the presence of ferritin and are expressed in Equations 7 and 8.

The endosome formation saturation factor K 47 is the threshold value of ferritin concentration when the endocytosis rate is reduced by half. Equation 9 expresses the surviving exogenous iron loaded ferritin after the endosome is dissolved and its decay rate in normal cell solution. Equations 2 through 10 describe therefore the TIM-2 iron uptake and metabolism model.

Simulation relied upon the quantified activity of 55 Fe where concentrations from in vitro experiments are inferred from the strength of radiation. Assumptions were that the ratios of concentration to strength of radiation were each constant for various iron-loaded proteins.

Other assumptions were that initial conditions were related to the preparation process, and that the system reaches equilibrium states before and after external experimental conditions treatments perturbed the system. For simplicity, this work assumed that all three iron metabolic processes uptake, storage, and export are in equilibrium and the level of iron concentration is below the nonlinear threshold.

For this simulation, the nonlinear effects which are not related to TIM-2 are ignored. Output parameters to be compared with experimental measurements were the sum of different iron-containing components. The ordinary differential equations ODEs for the TIM-2 pathway of iron uptake and metabolism were mapped to an equivalent electrical circuit to be implemented within a circuit simulator. Electric circuit components were mapped to the variables and equations of the TIM-2 pathway model Figure 2.

Nonlinear relations can be implemented by nonlinear-equation based sub-circuit blocks. Figure 2. An example circuit generated by ODE-to-circuit conversion. The component on the left is a current-control current source CCCS , an ideal element for current scaling.

The current inputs into a capacitor are to model the state of iron accumulation. At a linear release condition, the stored charge in capacitor leaks through the resistor RR7, modeling the release of iron. Figure 3. Example circuits of nonlinear behavior.

A Linear to saturation model; B Constant to suppression model. With proper conversion, mathematical equations can be mapped to equivalent circuits and solved through transient simulation for dynamic process or direct current DC simulation for stable states. Conversion consists of three parts: mathematical equation conversion, initial condition conversion, and output parameter conversion. Controlling parameters were extracted from in vitro experiments of iron uptake, storage and export as were performed in TCMK-1 vector and TIM-2 containing cells.

Although the experiments were performed independently, the underlying mechanisms for iron metabolism would be the same since the same cell line was used.

Therefore, the model with the same internal controlling parameters should be able to describe the underlying mechanisms for these three experiments. The goal of optimization for the overall model is to find a set of internal controlling parameters that will minimize error which is modeled by the sum of squares due to normalized error SSNE as shown in Equation N is the total number of data points collected from three in vitro experiments.

The means and standard deviations are determined from repetitions in each point. Figure 4. A Simulation setup defines the time duration and resolution; B Variable setup defines parameters and their range for optimization or tuning; C Initial condition and environment external source as applied to the cell subcircuit through wire connections; D Optimization setup of optimization methods and iteration time; E Goals for optimization.

In this study, multiple TIM-2 associated iron metabolic processes: iron uptake, storage, and export were modeled simultaneously based on a direct implementation from the Agilent ADS circuit simulator software. The model demonstrated a capability to identify variables and predict outcomes that could not be readily measured by in vitro experiments. Circuit simulation of iron uptake accurately modeled an increase in a time-dependent manner in TIM-2 transfectants, but not for vector controls Figure 5.

The iron uptake rate starts at 1. The initial rising within 10 min of iron concentration is due to the combination of TIM-2 in cell membranes with Fe-HFt. The turning point at around 10 min indicates the saturation of the TIM-2 combining process, i. The uptake curve is not flattened out; instead it keeps rising at a slower rate.

This indicates the appearance of a new TIM-2 unit on the cell membranes, which may occur from either TIM-2 recycling or new synthesis. Figure 5. Comparison of iron uptake rates between laboratory data and simulation. Cells were harvested at different time points over a 2-h period and 55 Fe amounts in cytosol fractions were counted. Data shown are means and standard deviations for triplicate replication of the experiment.

Circuit simulation of iron storage was consistent with iron storage occurring by the release of iron from exogenous biotinylated ferritin to a cellular fraction.

On the Thermal Models for Resistive Random Access Memory Circuit Simulation

You can build and simulate circuits right on your phone or tablet, animate and understand how they work, check homework and test your designs. Best of all, you can join and interact with EveryCircuit's large online community of fellow circuit enthusiasts. Are you looking for a place to discover ideas and share your own? EveryCircuit user community has collectively created the largest library of circuits that you can explore. Use search feature to find virtually any circuit and use it as a foundation for your next project. Students differ in how they learn.

Semiconductor Device Modeling and Simulation for Electronic Circuit Design

Transistor-level circuit simulation is a fundamental computer-aided design technique that enables the design and verification of an extremely broad range of integrated circuits. With the proliferation of modern parallel processor architectures, leveraging parallel computing becomes a necessity and also an important avenue for facilitating large-scale circuit simulation. This monograph presents an in-depth discussion on parallel transistor-level circuit simulation algorithms and their implementation strategies on a variety of hardware platforms. While providing a rather complete perspective on historical and recent research developments, this monograph highlights key challenges and opportunities in developing efficient parallel simulation paradigms. The ability to predict circuit performance through simulation is at the core of any design process; it makes the implementation of complex integrated circuits technically feasible and economically viable while relaxing any heavy need for prototyping. Parallel Circuit Simulation: A Historical Perspective and Recent Developments presents an in-depth discussion on parallel transistor-level circuit simulation algorithms and their implementation strategies on a variety of hardware platforms. While providing a rather complete perspective on historical and recent research developments, it also highlights key challenges and opportunities in developing efficient parallel simulation paradigms. Export citation Select the format to use for exporting the citation.

Catálogo Colectivo de las Universidades de Catalunya

This chapter covers different methods of semiconductor device modeling for electronic circuit simulation. It presents a discussion on physics-based analytical modeling approach to predict device operation at specific conditions such as applied bias e. However, formulation of device model involves trade-off between accuracy and computational speed and for most practical operation such as for SPICE-based circuit simulator, empirical modeling approach is often preferred. Thus, this chapter also covers empirical modeling approaches to predict device operation by implementing mathematically fitted equations.

PartSim Circuit Simulator

Sarmiento-Reyes A. Recibido: 22 de septiembre de Aceptado: 27 de abril de On one side, the steady downscaling that CMOS technology has experienced in the last four decades has brought it near its fundamental limits due to the appearance of quantum effects which were not previously taken into account. It clearly results that in forthcoming years, mature nanometric CMOS devices will share scenario with single-electron devices and other nano-devices in a wide number of applications, yielding hybrid electronic systems. Therefore, it becomes imperative to develop design verification methods and tools specially suited for these hybrid systems. The methodology results in a piecewise linear representation of the static SET characteristic that can be easily combined with existing MOS models in a standard industry package for electrical simulation such a SPICE.

Mixed-signal Circuit Simulation in Altium NEXUS

According to this technology, each element of an electric circuit is represented in the form of a mathematical model, where the set of mathematical models of elements and their correlations form the electric circuit model. The circuit simulator contains tools for the mathematical calculation of electric circuits, which allow it to perform a number of computed experiments with high reliability. Circuit simulation capabilities cover both analog and discrete electrical domains, allowing calculations for mixed-signal electrical circuits. Additional modes must be performed together with one of the calculations , which expands the possibilities for the analysis of the electrical circuit design results. The Simulation Dashboard panel contains several areas, which are grouped by functional purpose. Figure 1. Simulation Dashboard panel. Figure 2.

Circuit simulation and schematics.

Master the analysis and design of electronic systems with CircuitLab's free, interactive, online electronics textbook. Easy-wire mode lets you connect elements with fewer clicks and less frustration. Mixed-mode circuit simulation lets you simulate analog and digital components side-by-side. SPICE-like component models give you accurate results for nonlinear circuit effects.

Volume 7 (2) 2001, 91-109

RELATED VIDEO: #7 Spectrum analysis Circuit Simulation

The paper presents a fully parallel transistor-level full-chip circuit simulation tool with SPICE accuracy for general circuit designs. The proposed overlapping domain decomposition approach partitions the circuit into a linear subdomain and multiple nonlinear subdomains based on circuit nonlinearity and connectivity. A parallel iterative matrix solver is used to solve the linear domain while nonlinear subdomains are parallelly distributed into different processors topologically and solved by a direct solver. To achieve maximum parallelism, device model evaluation is also done in parallel.

Included in the download of LTspice are macromodels for a majority of Analog Devices switching regulators, amplifiers, as well as a library of devices for general circuit simulation. Contact Technical Support for assistance. Our enhancements to SPICE have made simulating switching regulators extremely fast compared to normal SPICE simulators, allowing the user to view waveforms for most switching regulators in just a few minutes. This video provides an overview of the advantages of using LTspice in an analog circuit design and how easy it is to get started. Download our LTspice simulation software for the following operating systems:. Download for Mac View Demo Circuits.

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