Archivos diarios: marzo 17, 2018

Simulation on Physical Systems

I take a long time writing many post about the simulation. Main reason is because I have learned for many years the value of using computers for physical system analysis. Without these tools, I would never be able to get reliable results, because of the amount of calculations I would have to do. Modern simulators, able to solve complex calculations using the computers capacity, allow us to get a more realistic behavior for a complex system, knowing its structures. Physics and Engineering work every day with simulations to get better predictions and take decisions. In this post, I am going to show what are the most important parts we should be kept in mind about the simulation.

In 1982, physicist Richard Feynman published an article where he talked about the analysis of physical systems using computers (1). In those years, computer technology had progressed to a high level that it was possible to achieve a greater calculation capacity. New programming languages worked with complex formulas, such as FORTRAN, and allowed the calculations on systems by complex integro-differential equations, which resolution usually needed numerical methods. So, in those first years, physicists began to do simulations with programs able to solve the constitutive system equations, although not always with simple descriptions.

A great step forward in electronics was the SPICE program, at the beginning of 70s (2). This program, FORTRAN-based, was able to compute non-linear electronic circuits, removing the radiation effects, and solve the time-domain integral-differential equations. Over the years, the Berkeley’s SPICE became the first reference on simulation programs and its success being such that almost all the simulation programs developed along last years have its base on the Nagel and Pederson algorithms, developed in 70s.

From 80s, and searching to solve three-dimensional problems, the method of moments (MoM) was developed. It was come to solve systems raised as integral equations in the boundaries (3), being very popular. It was used in Fluid Mechanics, Acoustic Waves and Electromagnetism. Today, this one is still used to solve two-dimensional electromagnetic structures.

But the algorithms have got a huge progress, with the emergence of new finite element methods (FEM, frequency-domain) and time-domain finite differences (FDTD, time-domain) in 90s, based on the resolution of systems formulated by differential equations, important benchmarks on the generation of new algorithms able to solve complex systems (4). And with these new advances, the simulation contribution in Physics came to take spectacular dimensions.

WHAT IS THE VALUE OF AN ACCURATE MODEL?

When we are studying any physical phenomenon, we usually invoke a model. Whether an isolated phenomenon or within an environment, whether in Acoustic Waves, Electromagnetism or Quantum Mechanics, having a well-characterized model is essential to get its behavior, in terms of its variables. Using an accurate model increases our certainty on the results.

However, modeling is complex. It is needed to know what are the relationships between variables and from here, determine a formulation system that defines the behavior within a computer.

A model example is a piezoelectric material. In Electronics, piezoelectric materials are commonly used as resonators and it is usually to see these electronic devices (quartz or any other resonant material based on this property).

A piezoelectric model, very successful in the 40s, was developed by Mason (5). Thanks to the similarity between the Electromagnetic and Acoustic waves, he got to join both properties using transmission lines, based in the telegraphist’s equations, writing the constitutive equations. In this way, he developed a piezoelectric model which is still used today. This model can be seen in Fig. 1 and it has already been studied in previous posts.

Fig.1 - Mason Model

Fig.1 – Modelo de piezoeléctrico de Mason

This model practically solved the small signal analysis in frequency domain, getting an impedance resonance trace as it is shown in Fig. 2

Fig.2 – Resultados del análisis del modelo de Mason

However, the models need to expand their predictive capacity.

The Mason model describes the piezoelectric behavior rightly when we are working in a linear mode. But it has faults when we need to know the large signal behavior. So new advances in the piezoelectric material studies included the non-linear relationships in its constitutive equations (6).

Fig. 3 – Modelo tridimensional de una inducción

In three-dimensional models, we must know well what are the characteristics that define the materials to have an optimal results. In the induction shown in Fig. 3, CoFeHfO is being used as a magnetic material. It has a frequency-dependent complex magnetic permeability that must be defined in the libraries.

The results will be better as the model is defined better, and this is the fundamental Physicist task: getting a reliable model from the studies on the phenomena and the materials.

The way to extract a model is usually done by direct measurement or through the derived magnitudes, using equations systems. With a right model definition, the simulation results will be more reliable.

ANALYSIS USING SIMULATION

Once the model is rightly defined, we can perform an analysis by simulation. In this case, we will study the H-field inside the inductor, at 200 MHz, using the FEM analysis, and we are going to draw this one, being shown in Fig. 4.

Fig. 4 – Excitación magnética en el interior del inductor

The result is drawn in a vector mode, since we have chosen that representation to see the H-field direction inside the inductor. We can verify, first, that the maximum H-field is inside the inductor, to the positive section on Y axis in the upper area, while in the lower part the orientation the inverse. The maximum H-field level obtained is 2330 A/m with 1 W excitation between the inductor electrodes.

The behavior is precisely that of an induction whose value can also be estimated by calculating its impedance and drawiing it on Smith’s chart, Fig. 5.

Fig. 5 – Impedancia del inductor sobre carta de Smith

The Smith’s chart trace clearly shows an inductive impedance, which value decreases when the frequency increases, because of losses of the CoFeHfO magnetic material. Besides, these losses contribute to the resistance increasing with frequency. There will be a maximum Q in the useful band

Fig. 6 – Factor de calidad del inductor

Having a induction with losses a quality factor Q, we can draw it as a function of the frequency in Fig. 6.

Therefore, with the FEM simulation we have been able to analyze the physical parameters on a modeled structure that would have cost us much more time and effort to get by means of complex calculations and equations. This shows, as Feynman pointed out in that 1982 conference, the simulation powerful when there are accurate models and proper software to perform these analyzes.

However, the simulation has not always had the chance to get the best results. Precisely is the previous step, the importance of having an accurate model, which faithfully defines the physical behavior of any structure, which will ensure the reliability of the results.

EXPERIMENTAL RESULTS

The best way to check if the simulation is valid is to resort getting experimental results. Fortunately, the simulation performed on the previous inductor is got from (7), and, in this reference, the authors show experimental results that validate the results of the inductor model. In Fig. 7 and 8 we can see the inductance and resistance values, and adding the quality factor, can be compared with the experimental results of the authors.

Fig. 7 – Valor de la inductancia en función de la frecuencia

Fig. 8 – Valor de la resistencia efectiva en función de la frecuencia

The results obtained by the authors, using HFSS for the simulation of the inductor, can be seen in Fig. 9. The authors have done the simulation on the structure with and without core, and show the simulation against the experimental result . Seeing the graphs, it can be concluded that the results got in the simulation have a high level of concordance with those obtained through the experimental measurements.

This shows us that the simulation is effective when the model is reliable, and that a model is accurate when the results obtained through the simulation converge with the experimental results. In this way, we have a powerful analysis tool that will allow us to know in advance the behavior of a structure and make decisions before moving on to the prototyping process.

Fig. 9 – Resultados experimentales

In any case, convergence is also important in a simulation. The FEM simulation needs that the mesh is so accurate as getting a good convergence. A low convergence level gives results far from the optimum, and very complex structures require a lot of processing speed, a high RAM use and, sometimes, must even perform a simulation on several processors. To more complex structures, the simulation time increases considerably, and that is one of its main disadvantages.

Although the FEM simulators allow the optimization of the values ​​and even today the integration with other simulators, they are still simulators that require, due to the complexity of the calculations to be carried out, powerful computers that allow to make those calculations with reliability.

CONCLUSIONS

Once again, we agree with Feynman when, in that 1982 seminar, he chose precisely a topic which seemed to have no interest for the audience. Since that publication, Feynman’s article has become a classic of Physics publications. The experience that I have got over the years with several simulators, shows me that the way opened by them will have a considerable advance when quantum computers are a reality and their processing speed raises, allowing that these tools get reliable results in a short space of time.

The simulation in the physical systems has been an important progress to get results without needing to realize previous prototypes and supposes an important saving in the research and development costs.

REFERENCES

  1. Feynman, R; “Simulating Physics with Computers”; International Journal of Theoretical Physics, 1982, Vols. 21, Issue 6-7, pp. 467-488, DOI: 10.1007/BF02650179.
  2. Nagel, Laurence W. and Pederson, D.O. “SPICE (Simulation Program with Integrated Circuit Emphasis)”, EECS Department, University of California, Berkeley, 1973, UCB/ERL M382.
  3. Gibson, Walton C., “The Method of Moments in Electromagnetics”, Segunda Edición, CRC Press, 2014, ISBN: 978-1-4822-3579-1.
  4. Reddy, J.N, “An Introduction to the Finite Element Method”, Segunda Edición,  McGraw-Hill, 1993, ISBN: 0-07-051355-4.
  5. Mason, Warren P., “Electromechanical Transducers and Wave Filters”, Segunda Edición, Van Nostrand Reinhold Inc., 1942, ISBN: 978-0-4420-5164-8.
  6. Dong, S. Shim and Feld, David A., “A General Nonlinear Mason Model of Arbitrary Nonlinearities in a Piezoelectric Film”, IEEE International Ultrasonics Symposium Proceedings, 2010, pp. 295-300.
  7. Li, LiangLiang, et al. 4, “Small-Resistance and High-Quality-Factor Magnetic Integrated Inductors on PCB”, IEEE Transactions on Advanced Packaging, Vol. 32, pp. 780-787, November 2009, DOI: 10.1109/TADVP.2009.2019845.
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