Electro-thermal circuit simulation using simulator coupling

Wunsche, S.; Clauß, Christoph; Schwarz, Peter; Winkler, F.

doi:10.1109/92.609870

Cited by 104 publications

(42 citation statements)

References 19 publications

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“…For small sized problems the more general approach of directly coupling a 2D or 3D thermal solver and a circuit simulator was pursued, see e.g. [19]. Finally, a general PDAE oriented framework for coupling thermal and circuit problems was developed in [3].…”

Section: State Of the Artmentioning

confidence: 99%

The COMSON Project

Günther

Feldmann²

2015

Mathematics in Industry

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This chapter serves as an introduction into the outcome of the COMSON project, and links the subsequent chapters to the overall idea of COMSON and its objectives. We start with a discussion of the state-of-the-art and open problems in nanoelectronics simulation at the timepoint when the COMSON Project was started. Therefrom the main scientific objectives of the COMSON project are derived. Special attention is devoted to a uniform methodology for both testing the new achievements and simultaneously educating young researchers: All mathematical codes are linked into a new Demonstrator Platform (Chap. 8), which itself is embedded into an E-Learning environment (Chap. 9). Subsequently the scientific objectives are shortly reviewed. They comprise: (i) Development of new coupled mathematical models, capturing the mutual interactions between the physical domains of interest in nanoelectronis. These are based on the PDAE approach (Chap. 2). (ii) Investigation of numerical methods to simulate these models. Our focus is on dynamic iteration schemes (Chap. 3) and for efficiency on MOR techniques (Chaps. 4-6). (iii) Usage of models and simulation tools for optimal design of nanoelectronic circuits by means of multi-objective optimisation in a compound design space (Chap. 7). Trends in MicroelectronicsThe design of complex integrated circuits ICs requires adequate simulation and optimisation tools. The current design approach involves simulations and optimisations in different physical domains (device, circuit, thermal, electromagnetic) as well as in electrical engineering disciplines (logic, timing, power, crosstalk, signal M. Günther ( ) Chair

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Section: State Of the Artmentioning

confidence: 99%

The COMSON Project

Günther

Feldmann²

2015

Mathematics in Industry

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“…Once the decision to pursue a 1-chip system has been made, a coupled iterative simulation process is required, such as the one introduced in [30] for electro-thermal circuit simulation, or the method demonstrated in [29] that utilizes the results from physics simulations and empirical validation to create behavioral SPICE models of RF-MEMS devices. Fig.…”

Section: ) Mems Modeling and Simulationmentioning

confidence: 99%

System-on-Chip Considerations for Heterogeneous Integration of CMOS and Fluidic Bio-Interfaces

Datta-Chaudhuri

Smela

Abshire

2016

IEEE Trans. Biomed. Circuits Syst.

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Abstract-CMOS chips are increasingly used for direct sensing and interfacing with fluidic and biological systems. While many biosensing systems have successfully combined CMOS chips for readout and signal processing with passive sensing arrays, systems that co-locate sensing with active circuits on a single chip offer significant advantages in size and performance but increase the complexity of multi-domain design and heterogeneous integration. This emerging class of lab-on-CMOS systems also poses distinct and vexing technical challenges that arise from the disparate requirements of biosensors and integrated circuits (ICs). Modeling these systems must address not only circuit design, but also the behavior of biological components on the surface of the IC and any physical structures. Existing tools do not support the cross-domain simulation of heterogeneous lab-on-CMOS systems, so we recommend a two-step modeling approach: using circuit simulation to inform physics-based simulation, and vice versa. We review the primary lab-on-CMOS implementation challenges and discuss practical approaches to overcome them. Issues include new versions of classical challenges in system-on-chip integration, such as thermal effects, floor-planning, and signal coupling, as well as new challenges that are specifically attributable to biological and fluidic domains, such as electrochemical effects, non-standard packaging, surface treatments, sterilization, microfabrication of surface structures, and microfluidic integration. We describe these concerns as they arise in lab-on-CMOS systems and discuss solutions that have been experimentally demonstrated.Index Terms-Biosensor, heterogeneous integration, lab-on-achip, lab-on-CMOS, microfluidics, system on a chip.

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“…In this way e.g. the ANSYS-Saber simulator coupling was realized [3], [17]. Sometimes, simulator coup ling is the ultima ratio in simulating multi-physics effects.…”

Section: To Support These Different Modeling and Simulation Approachementioning

confidence: 99%

“…We gained practical experiences in the simulation of electro-mechanical systems like electronically-controlled acceleration sensors [3], [14], valve-less micro-fluidic pumps, electro-thermal systems [17] and electro-magnetic-mechanical relays. Fig.…”

Section: To Support These Different Modeling and Simulation Approachementioning

confidence: 99%

A tool-box approach to the simulation of multi-physics systems

Schwarz¹

2001

Computational Fluid and Solid Mechanics

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In many cases, modeling and simulation of multi-physics systems cannot be carried out with one simulator or one class of models. Typically, for complex heterogeneous systems a combination of different modeling approaches, sometimes combined with simulator coupling, is the most appropriate method. A tool-box containing different modeling tools and software for simulator coupling is presented which could be applied successfully in the simulation of MEMS. Keywords:MEMS, microsystems, modeling, simulation, multi-domain, order reduction, model generation Micro-electro-mechanical systems (MEMS) and other microsystems are often complex heterogeneous. Multi-domain description, coupled field problems, stiffness, nonlinearities, and an increasing role of electronic signal processing (analog and digital) are characteristic properties of such devices and systems. Therefore, modeling and simulation is a difficult task in the design process. Due to the complexity of MEMS, there is no commonly accepted modeling and simulation approach. We prefer a tool-box oriented approach to cover most of the different requirements: a collection of modeling, simulation, and optimization tools, together with a "canonical" description of the elements as the basis for libraries from which models of complex system may be build-up.In Fig. 1, the combination of • modeling by abstraction (from lower to higher modeling levels), • modeling by equivalence transformation between the different physical domains (e.g. to apply the most suitable system simulator), • simulator coupling for those problems which can not be modeled for a single simulator is shown. On the component or device level, FEM/FDM/BEM simulation [18], [2] is the most appropriate and widely used analysis method. But for the overall system simulation the underlying models are too complex. Therefore, the generation of more compact models (sometimes called "macromodels") is necessary. In Fig. 2, different approaches to construct compact models for system simulation are summarized [12].To support the physically-oriented approach, generalized KIRCHHOFFian networks [15], [10], [4] could be applied very successfully. Special attention has to be directed to the multi-port aspect to handle 3-dimensional translational and rotational effects, also in non-inertial systems [9], [14]. The analytical description of the basic elements may be based also on FEM formulas [7]. Geometrically complex or inhomogeneous systems may be composed of an appropriate number of parameterized elements (Fig. 3). It is a main advantage of this approach that also multi-domain problems (as arising e.g. in transducer modeling) can be handled and also some nonlinearities (as usual e.g. in electro-mechanical systems) may be included into the behavioral models. The elements have to model only the "local" behavior, while the "global" behavior is calculated numerically by the system simulator based on the interconnections of the elements and the elements' behavioral models.Another modeling approach uses the internal mode...

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Electro-thermal circuit simulation using simulator coupling

Cited by 104 publications

References 19 publications

The COMSON Project

The COMSON Project

System-on-Chip Considerations for Heterogeneous Integration of CMOS and Fluidic Bio-Interfaces

A tool-box approach to the simulation of multi-physics systems

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