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Sistem inteligent de monitorizare multiparametric a unei zone seismogene ;

F. Munteanu, D. Zugravescu, C.Udriste

Catedra UNESCO de Geodinamica din cadrulInstitutului de Geodinamica Sabba S. Stefanescu al Academiei Romane

Evaluarea riscului seismic al unei zone este un obiectiv major in cercetarea geofizicamoderna. Studiile legate de intelegerea mecanismelor de cumulare a tensiunii in zone seismic activesi implicit responsabile de producerea cutremurelor de pamant, au fost revigorate de aparitia unuiansamblu de teorii si modele cunoscute sub denumirea de stiinta Complexitatii. Astfel, dupadescoperirea geometriei fractale, a teoriei haosului si a teoriei catastrofelor, evenimentele seismiceau fost reinterpretate ca exemple tipice ale dinamicii sistemelor neliniare. Procesul de auto-organizare a devenit cel mai uzitat si important model privitor la producerea cutremurelor de Pamant.

Studiile in baze de date ce contin toate evenimentele seismice cu magnitudini mai mari de 2 auevidentiat alternante intre perioade cu predictibilitate acceptabila si perioade cu evenimentedistribuite aleator, fapt ce a condus la ideea ca insasi gradul de predictibilitate al evenimentelorseismice se schimba in timp (J.D.Goltz,1997). Din aceasta perspectiva, cutremurul de pamant adevenit o expresie a geocomplexitatii (Rundle s.a. 2000), fapt ce a determinat orientarea cercetariistiintifice catre intelegerea fenomenelor complexe si valorificarea stiintifica - in domeniul geostiintelorin general si al seismologiei in special - a principalelor concepte, modele, teorii si tehnici puse ladispozitie de noua paradigma a Complexitatii.

Asimiland o zona seismic activa cu un sistem complex ierarhizat, putem face urmatoareleafirmatii: - un eveniment seismic modifica ireversibil structura sistemului, motiv pentru care estenecesara o permanenta adaptare a parametrilor unui model sau chiar o modificare a modelului; -

fiecare eveniment seismic descarca sistemul cu o valoare energetica proprie (magnitudinea) fapt cemodifica de fiecare data conditia initiala pentru noua etapa de incarcare, avand drept consecinta opredictibilitate redusa dar nu imposibila; -este de asteptat ca uneori sa se identifice precursori(dependent de conditia initala a sistemului dupa un eveniment seismic); -fiecare eveniment seismicdescarca sistemul local si transfera o parte din energie zonelor alaturate, motiv pentru care, ointelegere a evolutiei in timp a unei zone seismogene nu poate fi realizata in lipsa unei retele demonitorizare la o scara superiora sistemului monitorizat; -in stare critica, factorii declansatori potalterna cu factori inhibitori, reducand predictibilitatea unui model si punand accent pe doua obiectivediferite in cadrul monitorizarii unei zone seimogene: 1.evaluarea instalarii unei starii critice; 2.urmarirea proceselor de mica intensitate si rezonante cu zona hipocentrala, ce pot aduce informatiiprivitoare la formarea semnalului declansator ; -zona seismogena aflata sub observatie este partedintr-un sistem ierarhic superior si cuplata cu ansamblul dinamic/evolutiv GAIA planeta Vie, fapt ce

permite extragerea de informatii utile din sistemele adiacente si subiacente, vii si nevii; -schimbarilede structura in functie de variatii ale fluxurilor energo-informationale si materiale respecta legi deuniversalitate (pattern, constante alometrice) ce permit caracterizarea evolutiei unor sisteme reale.

Lucrarea sistematizeaza informatia extrem de vasta in acest nou domeniu al cercetariiteoretice si defineste cadrul in care devine utila o monitorizare inteligenta, avand la baza o reteaneurala. Ipoteza de lucru dezvoltata afirma ca, sub influenta unui flux de date convenabil ales,sistemul dotat cu inteligenta artificiala, si care manifesta el insusi proprietati auto-organizare, tindesa se apropie asimtotic catre (sa se sincronizeze cu) Realitatea monitorizata. In acest context, in

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locul unui model rigid si unic pentru orice zona geodinamic activa, derivat din teoria generala amecanicii ruperior, se obtine un model evolutiv auto-adaptabil la conditiile concrete determinate deevolutia specifica a zonei seismogene monitorizate, model ce poate oferi sanse sporite de evaluarea riscului seismic si de identificare a precursorilor evenimentelor seismice.

Bibliografie

1. Pak,P., Tang, C., Earthquakes as a self-organized critical phenomenon , J. Geophys. Res.,1994, 15635-15637;2. Rundle, J., Turcotte, D. L., Rundle, P.B., Yakovle, G., Shcherbakov, R., Pattern dynamics,pattern hierarchies, and forecasting in complex mu lti-scale earth syst ems, Hydrol.EarthSyst.Sci.Discuss., 2006, 3, 1045-1069 3. Prigogine, I., Dewel, G., Kondepudi, D., Chemistry Far from Equilibrium: Thermodynamics,Order and Chaos , Cambridge University Press, 20014. Lovejoy S., Schertzer , D., Scaling and mu ltifractal fields in the solid earth and topography, Nonlin. Processes Geophys., 14, 465502, 20075. A. Bejan, Advanced Engineer ing Th ermodyn amics , Wiley-Interscience, 3rd edition, 20066. Savageau M.A.,Allometric Morphogenesis of Complex Systems: Derivation of the BasicEquations f rom First Principl es , Proc.Natl.Acad.Sci.USA, 1979,vol 76,12,pp.6023-60257. Munteanu, F., Zugravescu, D., Rusu, M., Suteanu, C., On The synergy of ruptures , RevueRomaine de Geophysique, T 38, 1994 ;8. Wolfram, S., A new ki nd of sc ien ce , Wolfram Media, Inc., 20029. Chua, L.O., Lin, G.-N.; Canonical realization of Chuas circ uit f amily, IEEE transactions onCircuits and Systems, July 1990, vol. 37, (no. 7): 885-902.10. Dogaru, R.; Murgan, A.T. Chaotic Resonance Theory, a New Approach for Pattern Stor ageand Retrieval in Neural Netwo rks, Neural Networks, 1995. Proceedings., IEEE InternationalConference on Volume 6, Issue , Nov/Dec 1995 Page(s):304811. Strogatz. S., Sync: The Emerging Science of Spon taneous Order , Hyperion, New York, 200312 . Munteanu, F., Zugravescu, D.,Ioana, C., Suteanu, C., On the possibility to use theFeigenbaum scenario in modelling certain geodynamic phenomena, Revue Roumaine degeologie geophysique et geographie, serie de Geophysique, Tome 38, 199413. Munteanu F., Ioana C., Suteanu C., Zugravescu D, Discriminating transient dynamics andcritical states in active geodynamic areas . Studii si cercetari de Geofizica, Tomul 33, 1995 14. Handbook of Chaos Control, Schll, E.,(Editor), Schuster, H.G. (Editor), Wiley,200715. Gassmann, F., Noise-induced chaos-order transitions, Physical Review E, volume 55, Nr.3,199716 . Yang, T., Chua, L.O., Chaotic im pulse radio: a novel chaotic secure communicationsystem, International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, Feb.2000, vol. 10, (no. 2): 345-357.17. Lovelock, J. E.. Gaia: A New Look at Life on Earth , Oxford University Press, Oxford NewYork,198718. Planeta Pamant- Planeta Vie, Vol 1, Ed Eagle 2011, coord. D. Zugravescu, F. Munteanu,

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the theoretical frame for the use of the intelligent monitoring, based on a neural network. Developedworking hypothesis states that, under the influence of particularly convenient data flow, a systemequipped with artificial intelligence, that manifests itself self-organizing properties, tends to approachasymptotic (to sync with) to the monitored reality. In this context, instead of a single rigid model forany geodynamic active area, derived from the general theory of fracture mechanics, we obtain anevolutionary model self-adaptable to specific condition determined by the specific evolution ofseismogenic monitored zone, model that can provide better opportunities for seismic riskassessment and identification of precursor seismic events.

Bibliography

1. Pak,P., Tang, C., Earthquakes as a self-organized critical phenomenon , J. Geophys. Res.,1994, 15635-15637;2. Rundle, J., Turcotte, D. L., Rundle, P.B., Yakovle, G., Shcherbakov, R., Pattern dynamics,pattern hierarchies, and forecasting in complex mu lti-scale earth syst ems, Hydrol.EarthSyst.Sci.Discuss., 2006, 3, 1045-1069 3. Prigogine, I., Dewel, G., Kondepudi, D., Chemistry Far from Equilibrium: Thermodynamics,Order and Chaos , Cambridge University Press, 20014. Lovejoy S., Schertzer , D., Scaling and mu ltifractal fields in the solid earth and topography, Nonlin. Processes Geophys., 14, 465502, 20075. A. Bejan, Advanced Engineer ing Th ermodyn amics , Wiley-Interscience, 3rd edition, 20066. Savageau M.A.,Allometric Morphogenesis of Complex Systems: Derivation of the BasicEquations f rom First Principl es , Proc.Natl.Acad.Sci.USA, 1979,vol 76,12,pp.6023-60257. Munteanu, F., Zugravescu, D., Rusu, M., Suteanu, C., On The synergy of ruptures , RevueRomaine de Geophysique, T 38, 1994 ;8. Wolfram, S., A new ki nd of sc ien ce , Wolfram Media, Inc., 20029. Chua, L.O., Lin, G.-N.; Canonical realization of Chuas circ uit f amily, IEEE transactions onCircuits and Systems, July 1990, vol. 37, (no. 7): 885-902.10. Dogaru, R.; Murgan, A.T. Chaotic Resonance Theory, a New Approach for Pattern Stor ageand Retrieval in Neural Netwo rks, Neural Networks, 1995. Proceedings., IEEE InternationalConference on Volume 6, Issue , Nov/Dec 1995 Page(s):304811. Strogatz. S., Sync: The Emerging Science of Spon taneous Order , Hyperion, New York, 200312 . Munteanu, F., Zugravescu, D.,Ioana, C., Suteanu, C., On the possibility to use theFeigenbaum scenario in modelling certain geodynamic phenomena, Revue Roumaine degeologie geophysique et geographie, serie de Geophysique, Tome 38, 199413. Munteanu F., Ioana C., Suteanu C., Zugravescu D, Discriminating transient dynamics andcritical states in active geodynamic areas . Studii si cercetari de Geofizica, Tomul 33, 1995 14. Handbook of Chaos Control, Schll, E.,(Editor), Schuster, H.G. (Editor), Wiley,200715. Gassmann, F., Noise-induced chaos-order transitions, Physical Review E, volume 55, Nr.3,199716 . Yang, T., Chua, L.O., Chaotic im pulse radio: a novel chaotic secure communicationsystem, International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, Feb.2000, vol. 10, (no. 2): 345-357.17. Lovelock, J. E.. Gaia: A New Look at Life on Earth , Oxford University Press, Oxford NewYork,198718. Planeta Pamant- Planeta Vie, Vol 1, Ed Eagle 2011, coord. D. Zugravescu, F. Munteanu,