Applied Physics Department

Department Head

Principal Researchers

Objetives

• CINI’s Department of Applied Physics is concerned with the analysis of physical phenomena that underlie production processes in the steel industry. The ultimate aim is the development of methodologies and tools that contribute to achieving high standards of quality for the manufactured goods with an efficient use of the available resources.
• The sequence of steps that leads to the above objectives includes the development of analytical and numerical models of the physical processes involved, the incorporation of the relevant material properties, model validation by laboratory and plant measurements, and, finally, plant implementation in collaboration with production lines.

Research areas

Nondestructive Testing

• Laboratory measurements of NDT signals

Device for the laboratory measurement of the magnetic field which leaks because of the presence of defects or machined notches in steel tubes

Three dimensional representation of the radial component of the measured leaked field from a tube on which four notches were machined, including a slanted one

• Cerbero system for digital processing of NDT signals

• A/D conversion
• IIR filtering
• Fourier analyzing
• Alarm Triggering
• Tracking by position

View of the control area of Dalmine Linea Qualità

Snapshot of the main screen of the Cerbero system installed at SIDERCA’s Laco 2 inspection line. A user friendly interface allows the operator to fine tune the equipment parameters according to the client’s specifications

• Reliability (it gives consistent answers)
• Robustness (it requires minimal support around the clock)
• Universality (it is usable with different equipment)
• Effectiveness (it is as good as, or better than, the analog system)
• Real-time (operates at the production speed)
• Ease of use (non-specifically trained operators)
• Flexibility (it accepts different client requirements)

• NDT signal processing

Original data string recorded at a SIDERCA / Laco 2 inspection line, showing a large external defect and noise that interferes with the detection of smaller signals

Final data string, which shows a significant improvement in the signal-to-noise ratio. This aims at the detection of defects that give rise to small signals, which otherwise remain undetected, and at decreasing the number of false calls

• Inclusion Detection by Ultrasonic Testing

Study of the presence of macro-inclusions in rolled samples of slabs from Siderar. continuous casting that was carried out using an immersion tank. Maps of the peak amplitude of the ultrasonic signal and the time of flight are shown

• Ray tracing analysis of ultrasound signals

A shipment of DALMINE Premium joint connections PJD 2 7/8” was delayed because of spurious signals that appeared during UT inspection.An ad-hoc geometrical model showed that multiple reflections on the internal walls triggered the false alarms. The shipment was released based on that analysis.

Electromagnetic stirring

• Modeling electromagnetic stirring in continuous casting of steel rounds

Mesh used to calculate by Finite Elements the electromagnetic forces acting on the liquid steel column in the continuous casting operation

Color map showing the instantaneous acceleration in the liquid steel caused by the electromagnetic forces. These results are used as input to the fluid mechanical calculations performed at CINI Computational Mechanics Department

Hot dip galvanizing

• Modeling the continuous annealing furnace

In order to predict the heating of a load inside a furnace, an accurate computation of the radiation exchanges is required. For complex geometries, this can be achieved by means of a Monte Carlo method, as was done to generate the accompanying picture. In it, the inner wall temperature in °C of a section of a galvanizing line furnace is shown, using the color scale displayed to the right.

Productivity analysis of HDG lines based on a mathematical model. The maximum predicted productivity is shown as a function of the strip thickness and width. For thin strips, the productivity is limited by the maximum strip velocity, while for thicker strips the limiting factor depends on the strip width: if it is smaller than 1200 mm, the limiting factor is the maximum permissible furnace wall temperature, while for widths larger than 1200 mm, the furnace is limited by the maximum firepower.

Induction heating

The model was used for the basic design of induction coils and the determination of operating settings of various Siderca production lines where tube ends are reheated prior to upsetting.

Measuring residual dirt on steel plates

View of the ELMES device at SIDERAR plant

Measurement corresponding to a coil with two regions of very different cleanliness

Publications in the open literature (1995-2002)

1. P. Marino, A. Pignotti and D. Solís, “Numerical model of steel slab reheating in pusher furnaces”, Latin American Applied Research, 32, 257-261,2002
2. G. Bilmes, O. Martínez, R. Musso, D. Orzi, A. Pignotti, and P. Seré, “Laser instrument for determination of the degree of cleanliness in cold-rolled steel plate manufacturing”, Latin American Applied Research, 32, 263-266, 2002
3. P. Sekulic, R. K. Shah, and A. Pignotti, “A Review of Solution Methods for Determining Effectiveness-Ntu Relationships for Heat Exchanger Complex Flow Arrangements”, Applied Mechanics Review, 52, 97-117, 1999
4. H. Gavarini, R. P. J. Perazzo, S. L. Reich, E. Altschuler, and A. Pignotti, “Automatic assessment of the severity of cracks in steel tubes using neural networks”, Insight, 40, 92-100, 1998
5. G. D. Garbulsky, P. Marino, and A. Pignotti, “Numerical model of induction heating of steel-tube ends”, IEEE Transactions on Magnetics, 33, 746-52 , 1997
6. R. K. Shah and A. Pignotti, “Influence of a Finite Number of Baffles on Shell-and-Tube Heat Exchanger Performance”, Heat Transfer Engineering, 18, 82-94, 1997
7. E. Altschuler, J. Paiuk, and A. Pignotti, "Monte Carlo Simulation of False Alarms and Detection Reliability in MFL Inspection of Steel Tubes", Materials Evaluation, 54, 1032-4, 1996
8. H. Gavarini, R. P. J. Perazzo, S. L. Reich, E. Altschuler, and A. Pignotti, "Neural network classifier of cracks in steel tubes", Insight-Non-Destructive Testing and Condition Monitoring, 38, 108-111, 1996
9. E. Altschuler and A. Pignotti, "Nonlinear Model of Flaw Detection in Steel Pipes by Magnetic Flux Leakage", NDT&E International, 28, 35-40, 1995

1. P. Marino, A. Pignotti, D. Solís and D. Wolter, “Relación entre la excentricidad de los tubos de acero sin costura y la homogeneidad de temperaturas en las barras”, 14ª Conferencia de Laminación y 4° Encuentro de la Sección Argentina de la Iron and Steel Society, Buenos Aires, Argentina, 2002
2. P. Marino, A. Pignotti, D. Solís, E. Ubici and A. Vigliocco, “Control automático de un horno de recalentamiento de planchones usando un modelo numérico”, 14ª Conferencia de Laminación y 4° Encuentro de la Sección Argentina de la Iron and Steel Society, Buenos Aires, Argentina, 2002
3. J. Etcheverry, A. Pignotti, G. Sánchez and P. Stickar, “MFL Benchmark problem II: laboratory measurements”, 29th Annual Review of Progress in Quantitative Nondestructive Evaluation, Bellingham, WA, USA, July 2002
4. J. Etcheverry, A. Pignotti, G. Sánchez, and P. Stickar, “Defect signal enhancement in MFL inspection lines”, 29th Annual Review of Progress in Quantitative Nondestructive Evaluation, Bellingham, WA, USA, July 2002
5. J. Etcheverry, J. Gazzarri, T. Pérez, M. Vicente Alvarez, F. Actis, P. Cantarelli, G. Cervellini and J. Von Bergen, “Analysis of Strip Thermal Cycle Differences in Continuous Galvanizing Lines for Steady State Processing Conditions”, 2001 Galvanizer's Conference, Portland, Oregon USA, September, 2001
6. A. Pignotti, Y. Li, Z. Zhang, Y. Sun, L. Udpa, S. Udpa, R. Schifini, and A.C. Bruno, “Numerical simulation results on a magnetic flux leakage benchmark problem”, Review of Progress in Quantitative NDE Conference, Brunswick, Maine, USA, July, 2001, Vol. 21B, pp. 1894-1901.
7. J. Príncipe, G. Sánchez, A. Pignotti and M. Goldschmit, “Numerical modeling of electromagnetic stirring used in the TENARIS group continuous casting facilities”, 13° Seminario de Acería del IAS y 3° Encuentro de la Sección Argentina de la Iron and Steel Society, Buenos Aires, Argentina, 2001.
8. P. Marino, E. Blangino and E. Brizuela, “Reducción de los tiempos de ejecución en el modelado numérico de la radiación de gases”, Mec. Comput., Vol.19, (Ed. F.Quintana et al.), 2000.
9. A. Pignotti, P. Stickar, R. Perazzo and S. Reich, “Feature extraction in MFL signals of machined defects in steel tubes”, 27th Annual Review of Progress in Quantitative Nondestructive Evaluation, Ames, Iowa, USA, July 2000, Vol. 20A, pp. 619-626.
10. G. M. Bilmes, O. E. Martínez, P.R. Seré, D. J. Orzi and A. Pignotti, “On-line photoacoustic measurement of residual dirt on steel plates” , 27th Annual Review of Progress in Quantitative Nondestructive Evaluation, Ames, Iowa, USA, July 2000, Vol. 20B, pp.1944-49.
11. M. Maldován, J. Príncipe, G. Sánchez, A. Pignotti and M. Goldschmit, “Numerical modeling of continuous casting of rounds with electromagnetic stirring”, European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2000, Barcelona, Spain, 2000.
12. P. Marino, “Numerical model of steel tube reheating in walking beam furnaces”, Fifth European Conference on Industrial Furnaces and Boilers, Porto, Portugal, 2000
13. E. Altschuler, P. Marino and A. Pignotti, “Numerical models of reheating gas furnaces in the steel industry”, Fourth ISHMT/ASME Heat and Mass Transfer Conference, Pune, India, 2000, Tata Mc Graw Hill Publishing House
14. F. Robiglio, A. Campos, J. Paiuk, M. Maldován, J. Príncipe, A. Pignotti and M. Goldschmit, “Design and Numerical Modeling of Siderca’s EMS” (in Spanish), Proceedings of the 12th Steelmaking Seminar and 2nd Iron and Steel Society Argentina Section Meeting, pp. 410-419, Buenos Aires, Argentina, November 2-5, 1999
15. E. Altschuler, P. Marino, A. Pignotti, D. Migliorino and A. Jacobsen, “Numerical model of #1 CGL furnace at Siderar”, Proceedings of the 91st Galvanizer’s Conference, Jackson, Mississippi, October 24-29, 1999
16. D. Comuzzi, F. Monti, A. Nicolini, and P. Stickar, “Digitized System for the Inspection of Steel Pipes”, Proceedings of the 26th Annual Review of Progress in Quantitative Nondestructive Evaluation, Montréal, Canada, July 26-30, 1999, by Kluwer Academic/Plenum Publishers
17. P. Marino and A. Pignotti, “On-line model for controlling an industrial rotary reheating gas furnace”, Fourth European Conference on Industrial Furnaces and Boilers, Porto, Portugal, 1-4 April, 1997
18. J. Cardenal, G. López Turconi, P. Marino, A. Pignotti, C. Saporiti and M. Zecchi, “Control de un horno de recalentamiento”, AADECA 96, Buenos Aires, Argentina, 1996
19. E. Altschuler, H. Gavarini, R. Perazzo, A. Pignotti and S. Reich, “Neural Network for MFL Inspection of Steel Tubes”, Proceedings of the 14th World Conference on NDT, New Delhi, India, December 8-13, 1996, pp. 1841-44.
20. P. Marino and A. Pignotti, "On-line Modeling and Control System for a Reheating Gas Furnace", Proceedings of the 4th Symposium on Low Cost Automation, International Federation for Automatic Control, pp. 329-334, 1995.

1. P. Marino and A. Pignotti, “Control inteligente de hornos industriales”, Ciencia Hoy, to be published in 2002
2. A. Pignotti, “Ensayar sin romper”, Ciencia Hoy, Vol. 10, N. 58, pp. 28-36, 2000.

1. Graduate thesis in Nuclear Engineering, Alejandro Ibáñez, “Detección de defectos en acero mediante ultrasonido”, Instituto Balseiro, June, 1997, Advisor: A. Pignotti
2. Graduate thesis in Physics, Pablo Marino, “Modelado numérico y optimización de estados estacionarios en un horno industrial”, University of Buenos Aires, March, 1993, Advisor: Dr. A. Pignotti

1. Doctoral thesis in Engineering, Pablo Marino, “Modelado de Hornos a Gas en la Industria Siderúrgica”, University of Buenos Aires, Advisor: Dr. A. Pignotti