Lecture

QUCS Parameter Sweeps

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In course

MICRO-470: Scaling laws in micro & nanosystems

This class adresses scaling laws in MEMS/NEMS. The dominant physical effects and scaling effects when downsizing sensors and actuators in microsystems are discussed, across a broad range of actuation principles. ...

Description

This lecture covers the process of doing parameter sweeps in QUCS, focusing on setting up and configuring the simulation type 'parameter sweep' with linear values, careful variable naming, and the importance of calling the right simulation. The slides provide detailed instructions on configuring the sweep parameters, including start and stop values, step size, and the number of points. Additionally, it explains how to nest sweeps and avoid unfortunate naming processes. The lecture also delves into simulations types such as DC, AC, S-parameter, and harmonic balance, showcasing practical examples and emphasizing the significance of proper simulation setup.

Instructors (3)

Niels Quack

Prof. Dr. Niels Quack received the M.Sc. degree from Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, in 2005, and the Dr.Sc. degree from Eidgenössische Technische Hochschule Zürich (ETH), Zürich, Switzerland, in 2010. From 2011 to 2015, he was Postdoctoral Researcher and Visiting Scholar with the Integrated Photonics Laboratory, Berkeley Sensor and Actuator Center, University of California, Berkeley, CA, USA. From 2014 to 2015, he was Senior MEMS Engineer with Sercalo Microtechnology, Neuchâtel, Switzerland. He is currently an SNSF Assistant Professor with Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. He has authored and co-authored more than 50 papers in leading technical journals and conferences. His research interests include photonic micro and nanosystems, with an emphasis on diamond photonics and silicon photonic MEMS. He is Steering Committee Member of the IEEE International Conference on Optical MEMS and Nanophotonics (OMN) and served as General Chair of the IEEE OMN 2018 and the Latsis Symposium 2019 on Diamond Photonics. He is a Senior Member of IEEE, Member of The Optical Society (OSA) and life member of SPIE.

Herbert Shea

Expertise soft robotics, wearable haptics, electrostatic actuators, EHD Mission My lab develops flexible polymer-based actuators for a wide range of applications including haptics and soft robotics. More info at https://www.epfl.ch/labs/lmts/ Links from EPFL-LMTS Lab webpage People Research ActivitiesPublications TeachingPublications and Conference papers Link to my lab Education PhD | Physics 1997 – 1997 Harvard University MA | Physics 1993 – 1993 Harvard University

Philippe Renaud

Philippe Renaud is Professor at the Microsystem Laboratory (LMIS4) at EPFL. He is also the scientific director of the EPFL Center of MicroNanoTechnology (CMI). His main research area is related to micronano technologies in biomedical applications (BioMEMS) with emphasis on cell-chips, nanofluidics and bioelectronics. Ph. Renaud is invloved in many scientifics papers in his research area. He received his diploma in physics from the University of Neuchâtel (1983) and his Ph.D. degree from the University of Lausanne (1988). He was postdoctoral fellow at University of California, Berkeley (1988-89) and then at the IBM Zürich Research Laboratory in Switzerland (1990-91). In 1992, he joined the Sensors and Actuators group of the Swiss Center for Electronics and Microtechnology (CSEM) at Neuchâtel, Switzerland. He was appointed assistant professor at EPFL in 1994 and full professor in 1997. In summer 1996, he was visiting professor at the Tohoku University, Japan. Ph. Renaud is active in several scientific committee (scientific journals, international conferences, scientific advisory boards of companies, PhD thesis committee). He is also co-founder of the Nanotech-Montreux conference. Ph. Renaud is committed to valorization of basic research through his involvement in several high-tech start-up companies.

Official source

Related concepts (32)

Computer simulation

Computer simulation is the process of mathematical modelling, performed on a computer, which is designed to predict the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics (computational physics), astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering.

Scattering parameters

Scattering parameters or S-parameters (the elements of a scattering matrix or S-matrix) describe the electrical behavior of linear electrical networks when undergoing various steady state stimuli by electrical signals. The parameters are useful for several branches of electrical engineering, including electronics, communication systems design, and especially for microwave engineering. The S-parameters are members of a family of similar parameters, other examples being: Y-parameters, Z-parameters, H-parameters, T-parameters or ABCD-parameters.

Simulation

A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation. Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games.

Simulation video game

Simulation video games are a diverse super-category of video games, generally designed to closely simulate real world activities. A simulation game attempts to copy various activities from real life in the form of a game for various purposes such as training, analysis, prediction, or entertainment. Usually there are no strictly defined goals in the game, and the player is allowed to control a character or environment freely. Well-known examples are war games, business games, and role play simulation.

Statistical parameter

In statistics, as opposed to its general use in mathematics, a parameter is any measured quantity of a statistical population that summarises or describes an aspect of the population, such as a mean or a standard deviation. If a population exactly follows a known and defined distribution, for example the normal distribution, then a small set of parameters can be measured which completely describes the population, and can be considered to define a probability distribution for the purposes of extracting samples from this population.

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