Spatial distribution of site-effects and wave propagation properties in Thessaloniki (N. Greece) using a 3D finite difference method

Scientists from the Geophysical Laboratory (Department of Geophysics, School of Geology of the Aristotle Univ. of Thessaloniki) have studied the site effects of seismic motion in the metropolitan area of the city of Thessaloniki (Northern Greece) for various seismic earthquake scenarios with a 3D finite-difference modeling approach, using the HellasGrid Infrastructure and the EGI with the support of the Scientific Computing Center at A.U.Th.

The city of Thessaloniki (Northern Greece) was selected since it is located in a moderate-to-high seismicity region (Papazachos et al., 1983), with the Servomacedonian massif and Northern Aegean through areas exhibiting the highest seismicity (Figure 1). The city suffered several large earthquakes throughout its history, many of them causing significant damages and human losses (Papazachos and Papazachou, 2002).

Thessaloniki Earthquake Map

Figure 1: Map of known earthquakes with M≥3.0 which occurred in the broader area of central–northern Greece from the historical times (550 BC) till 2007 (Figure after Skarlatoudis et al., 2011a).

 

An explicit 3D 4th-order velocity-stress finite-difference scheme with discontinuous spatial grid was used to produce synthetic waveforms with numerical simulations. The scheme solves the equation of motion and Hooke’s law for viscoelastic medium with rheology described by the generalized Maxwell body model. Details on the scheme, its grid and material parameterization are provided by Moczo et al. (2002), Kristek & Moczo (2003), Moczo & Kristek (2005), Moczo et al. (2007) and Kristek et al. (2009b).

The computational model used for the simulations is based on the geophysical-geotechnical model and the dynamic characteristics of the soil formations proposed by Anastasiadis et al. (2001) and covers an area of 22 x 16 Km2 (dotted rectangle in Figure 1) (Skarlatoudis et al., 2007; 2008b; Skarlatoudis et al., 2010).

Numerical simulations were performed for six seismic scenarios, corresponding to three different hypocentral locations and two different focal mechanisms for each one. Seismic scenarios with E-W trending normal faults are referred as scenarios (a), while the ones with NW-SE trending normal faults as scenarios (b) (Figure 2). Both types of normal faults (E-W and NW-SE) are the dominant types of faults in the vicinity of the broader Thessaloniki area (e.g. Vamvakaris et al., 2006). Synthetic waveforms were produced for a coarse grid of receivers, in order to study the spatial variation of site-effects on seismic motion in the broader metropolitan area of Thessaloniki (Figure 2).

Earthquake Simulation Scenarios          

Figure 2: Earthquake locations used for the examined seismic scenarios (red stars) and the focal mechanisms used for each scenario. The coarser grid of receivers used for studying the spatial variation of various waveform and site-effect parameters for the six earthquake scenarios is also shown (black diamonds). The location of site OBS, used as a reference station in computations, is denoted with a yellow triangle (Figure after Skarlatoudis et al., 2011a).

 

The application that implements the 3DFD method is using the MPI libraries for inter-process communications, namely the mpich2 implementation. The compilation and execution of the code was tested in different types of machines and different Fortran90 compilers (commercial and free). The most accurate results and the minimum execution time in each system were achieved with the use of the commercial compiler Pathscale (version 3.0) (Skarlatoudis et al., 2008a). The execution of the 3DFD code is demanding in terms both of CPU power and computer memory. For the aforementioned computational model the memory demands reached 20 GB and the time of computation (per model) was approximately 15 on the HellasGrid Infrastructure with the synchronous usage of 40 Intel Xeon processors.

The implemented workflow relies mainly on gLite middleware (Figure 3). Also a large number of test runs for checking the compatibility of the results on the Grid with the ones obtained from other computational infrastructures have been performed. Moreover the scaling of the execution of the code on the HellasGrid Infrastructure was examined (Skarlatoudis et al., 2008a).

3D FDTD Application Workflow          

Figure 3: Schematic representation of the workflow in HellasGrid infrastructure (Figure after Skarlatoudis et al., 2008a)

 

Various measures, estimated from the 3D synthetic waveforms that can provide a more detailed evaluation of site-effects, such as spectral ratios, Peak Ground Velocity (PGV), cumulative kinetic energy and Housner Intensity, were used to probe the site-effects spatial distribution and ground motion variability. In Figure 4 the Peak Ground Velocity (PGV) ratio is shown for the 3D over the corresponding 1D bedrock reference model [(PGV3D)/(PGV1D)], estimated for the coarser grid of receivers and for the two horizontal components of ground motion, for all scenarios studied (Skarlatoudis et al. 2011a). The observed relative PGV distribution from the six scenarios, exhibits high values along the coastal zone, with the highest value (~4) shown in the area near the city harbor for the E-W component. High values of relative PGV are also observed in the western parts of the model for the E-W component.

3DFD_Thessaloniki

Figure 4: Spatial variation of the average, from the six seismic scenarios, ratio [(PGV3D/PGV1D)], for the horizontal components of ground motion (Figure after Skarlatoudis et al., 2011a)

 

The 3D wave propagation characteristics of the 4th July, 1978 aftershock (M5.1) of the 20th June, 1978 strong mainshock (M6.5) that struck the city of Thessaloniki were also studied using the 3D finite-difference approach. In Figure 5 the spatial distribution of damages in the metropolitan area of Thessaloniki after the 1978 mainshock is presented (left figure) (Leventakis, 2003), together with the corresponding distribution of the RotD50 ground motion measure of the (PGV3D)/(PGV1D) ratio, for the frequency band 0.2Hz-3Hz (Skarlatoudis et al., 2011b). According to Leventakis, (2003) the largest damage was recorded in the city harbor area and parts of the eastern area of the Thessaloniki. Despite the various limitations of the comparison, a quite good correlation is observed between the damage distribution and the PGV spatial variation, suggesting that the role of local site amplifications studies here is much more important than other factors (e.g. differences in source radiation pattern, non-linearity, etc.).

Thessaloniki Damage Distribution

Figure 5: (Left) Spatial distribution of damage distribution in Thessaloniki caused by the mainshock of July 1978 according to Leventakis (2003). (Right) Spatial distribution of the RotD50 measure of relative PGV values (amplifications) from filtered (0.2Hz-3Hz) horizontal components (Figure after Skarlatoudis et al., 2011b).

 

This work has been partly performed in the framework of PENED-2003 (measure 8.3, action 8.3.4 of the 3rd EU Support Programme) and the Greek-Slovak Cooperation Agreement (EPAN 2004-2006). Most of the computations were realized on the EGI and HellasGrid infrastructureσ with the support of the Scientific Computing Center at the Aristotle University of Thessaloniki (AUTH). A significant part of the results presented here have been published in peer-review journals (see inline references) and/or presented in national and international conferences (see references at the end of this document).

 

Contact details:

  • Papazachos C.B., Professor, AUTH, kpapaza (at) geo.auth.gr
  • Skarlatoudis A.A, Dr. Seismologist, AUTH, askarlat (at) geo.auth.gr
  • Scientific Computing Center, AUTH, contact (at) grid.auth.gr

 

References:

  1. Papazachos, B. C., Tsapanos, T. M. and Panagiotopoulos, D., (1983). The time, magnitude and space distribution of the 1978 Thessaloniki seismic sequence. The Thessaloniki northern Greece earthquake of June 20, 1978 and its seismic sequence. Technical chamber of Greece, section of central Macedonia, 117-131, 1983.
  2. Skarlatoudis A.A., C.B. Papazachos, P. Moczo, J. Kristek, N. Theodoulidis and P. Apostolidis, (2007). Evaluation of ground motions simulations for the city of Thessaloniki, Greece using the FD method: the role of site effects and focal mechanism at short epicentral distances, European Geosciences Union (EGU) General Assembly, Vienna, Austria.
  3. Skarlatoudis A.A., Korosoglou, P., Kanellopoulos, C. and Papazachos C.B, (2008a). Interaction of a 3D finite-difference application for computing synthetic waveforms with the HellasGrid infrastructure, 1st HellasGrid User Forum, Athens, Greece, 3rd EGEE User Forum, Clermont-Ferrand, France.
  4. Skarlatoudis A.A., C.B. Papazachos, P. Moczo, J. Kristek and N. Theodoulidis, (2008b). Ground motions simulations for the city of Thessaloniki, Greece, using a 3-D Finite-Difference wave propagation method, European Geosciences Union (EGU) General Assembly, Vienna, Austria and 31st European General Assembly of the European Seismological Commission, Chania, Greece.
  5. Skarlatoudis A.A., C.B. Papazachos and N. Theodoulidis, (2011b). Site response study of the city of Thessaloniki (N. Greece), for the 04/07/1978 (M5.1) aftershock, using a 3D Finite-Difference wave propagation method, accepted for publication in Bull. Seism. Soc. Am.

Grid Computing for Long Time Propagations in Molecular Dynamics of Biomolecules and Extended Phase Space Sampling

Scientists from Department of Chemistry, University of Crete (UoC) and 
Institute of Electronic Structure and Laser, 
FOundation for Research and Technology Hellas (FORTH)  have used the HellasGrid Infrastructure and the EGI Grid infrastructure in order to solve problems coming from the area of Computational Chemistry.

More specific, the scientists made studies on dynamics and spectroscopy of proteins and other biomolecules, enzymatic reactions, and free energy hypersurface calculations for protein – ligand interactions by integrating very long time trajectories and making extended sampling of the classical phase space [1-3].

For problems which exhibit ergodicity in a submanifold of the phase space manifold of the system, time averages are converted to phase space averages, and thus to high throughput problems. The algorithm that have been developed is based on the principle to run short jobs, store intermediate results, and resubmit the jobs as many times as needed to achieve a predetermined total integration time [1]. This approach cures shortcomings of the current productive Grid.

The production of a free energy hypersurface, requires one to run thousands or even millions of jobs, a task which can be fulfilled if thousands of CPUs are available in a reasonable amount of time [2,3]. Scripts based on the gLite middleware have been developed and tested at the HellasGrid and EGI infrastructure which can handle such tasks.

Quantum molecular dynamics for intermediate size biomolecules require a interoperability of high throughput and high performance computing. This is scientists’ plan for solving problems involving proton-coupled electron transfer (PCET), which are encountered in enzyme reactions, fuel cells, chemical sensors and electrochemical devices.

Contact details

Members of the Theoretical and Computational Chemistry group in Crete (TCCC):

  • Prof. Stavros C. Farantos, Theoretical and Computational Chemistry, farantos (at) iesl.forth.gr
  • Mr. Manos Giatromanolakis, IT Manager and Systems Analyst, gmanos (at) iesl.forth.gr
  • Prof. Vangelis Daskalakis, Computational Biochemistry, chem487 (at) edu.uoc.gr
  • Dr. Osvaldo Gervasi, Computer scientist, administrator of Compchem Virtual Organization,  osvaldo (at) unipg.it
  • Dr. Massimiliano Porrini, Theoretical and Computational Chemistry, maxp (at) iesl.forth.gr
  • Dr. Jaime Suarez, Theoretical and Computational Chemistry, jaime.suarez (at) iesl.forth.gr

References

  1. V. Daskalakis, M. Giatromanolakis, M. Porrini, S. C. Farantos, and O. Gervasi, Computer Physics, Chapter: Grid computing multiple shooting algorithms for extended phase space sampling and long time propagation in Molecular Dynamics, Nova Science Publishing Co., 2011.
  2. M. Porrini, V. Daskalakis, and S. C. Farantos, Thermodynamic Perturbation Calculations on Cytochrome c Oxidases interacting with small ligands, Phys. Chem. Chem. Phys., submitted, 2011.
  3. Massimiliano Porrini, Vangelis Daskalakis, S. C. Farantos, and Constantinos Varotsis, Heme Cavity Dynamics of Photodissociated CO from ba3-Cytochrome c Oxidase: the Role of Ring-D Propionate, J. Phys. Chem. B, 113(35):12129-12135, 2009.

 

 

Reinforcement Learning Game – RLGame


Scientists from Hellenic Open University and Computer Technology Institute and Press “Diophantus” have used the HellasGrid Infrastructure and the EGI Grid infrastructure in order to solve problems coming from the area of Machine Learning and Algorithms in Games.

When using machine learning to learn how to play a game, vast amounts of experiments may be required to adequately explore the space of alternative tactics and strategies. To cover this need, grid was a technology which was exploited by the researchers.

The scientists have identified a curious phenomenon in game playing, which they term “the pendulum effect”. Therein, they use a tutor to provide playing advice to one player (A) of a zero-sum two-player game. It seems that the player (B) who does not receive tutoring is also able to enormously benefit just by being forced to play against a better player (A, as advised by the tutor). This is reinforced when the tutor abstains; player B seems to be able to win more often as compared to when the tutor is present directing A to more wins.

By using the HellasGrid and EGI infrastructure, the scientists conducted a range of experiments across hundreds of game configurations and across several learning schemes; some of them employed game tree look-ahead search which is pretty expensive (but not yet optimized for grid computing). These experiments may have consumed several tens of thousands of CPU hours on the grid; such availability of resources simply does not exist at stand-alone venues.

Future plans include the continuation of this line of research to verify this type of learning behavior, across more configurations and actions to verify it across other games as well. The scientists are also currently looking into workflows (hopefully, grid-aware workflow systems) to better organize data collection and analysis.

Contacts

  • Dimitris Kalles, Hellenic Open University, kalles (at) eap.gr
  • Panagiotis Kanellopoulos, Computer Technology Institute and Press “Diophantus”, kanellop (at) ceid.upatras.gr
References
  1. D. Kalles, and I. Fykouras. “Examples as Interaction: On Humans Teaching a Computer to Play a Game”, International Journal on Artificial Intelligence Tools, 2010.
  2. D. Kalles and P. Kanellopoulos. “A Minimax Tutor for Learning to Play a Board Game”, Workshop on Artificial Intelligence in Games, a workshop of the 18th European Conference on Artificial Intelligence, 2008.
  3. D. Kalles and P. Kanellopoulos. “A Pendulum Effect in Co-evolutionary Learning in Games”, European Workshop in Reinforcement Learning, 2011.

 

Evaluating the impact of climate change on European air quality

Scientists from the Laboratory of Atmospheric Physics (School of Physics) and the Department of Meteorology and Climatology (School of Geology) have simulated the regional climate-air quality over Europe for two future decades (2041-2050 and 2091-2100) using the HellasGrid Infrastructure and the EGI Grid, with the support of the Scientific Computing Center at A.U.Th..

The computational models used for these simulations are the regional climate model RegCM3 and the air quality model CAMx, which have been off line coupled in this case (Figure 1). The control simulation for the decade 1991-2000 was performed twice, once externally forced by the ERA40 reanalysis and once using the global circulation model ECHAM5, in order to investigate the importance of external meteorological forcing on air quality (Katragkou et al., 2010). The RegCM3 model was forced by ECHAM5 under the A1B emission scenario for two future time slices, namely 2041-2050 and 2091-2100. These simulations served as a theoretical experiment of evaluating the impact of climate change on air pollution (Katragkou et al., 2011).

For each decadal simulation the computation consumed approximately 1000 CPU hours. CAMx simulations were performed on SMP machines as the model has been intrinsically parallelized with the OpenMP library. Using this feature of the CAMx model a significant reduction on the overall computation time was feasible.

In terms of storage, the resources required for archiving the CAMx output files are estimated to slightly more than 5TB.

Off-line coupling of RegCM3 and CAMx computational models

Figure 1: A schematic illustrating an outline of the modelling system RegCM3/CAMx applied in this study (from Zanis et al., 2011)

Surface ozone simulated by RegCM3/CAMx was evaluated against ground based measurements from the European database EMEP (Zanis et al., 2011). The air quality simulations available at AUTH for the three time slices (1991-2000, 2041-2050 and 2091-2100) over Europe with a resolution of 50 Km have been provided as air quality boundaries for higher resolution air quality simulations over sub-European grids (Huszar et al., 2011).

The results suggest that changes imposed by climate change until the 2040s in surface ozone concentration during summer will be below 1 ppbv (parts per billion by volume) . By the 2090s, however, changes are foreseen to be more significant especially over south-west Europe, where the median of near surface ozone has been found to increase by 6.2 ppbv.

Near surface ozone concentrations over Europe

Figure 2: Average summer surface ozone for the control simulation 1991-2000 (left). Differences in simulated average summer ozone between 2091-2100 and control simulation (right). The grey color corresponds to non-statistical significant differences (from Katragkou et al., 2011)

The median of summer near surface temperature for Europe at the end of the 21st century was calculated at 2.7K higher than the end of the 20th century with more intense temperature increase simulated for southern Europe. A prominent outcome was the decrease of cloudiness mostly over western Europe at the end of the 21st century associated with an anticyclonic anomaly which favours more stagnant conditions and weakening of the westerly winds (Katragkou et al., 2011).

Mean temperature differences

Figure 3: Mean differences between second future decade (2091-2100) and the present decade (1991-2000) for summer in the fields of surface temperature (left) and geopotential height at 500 hPa (right).The red contours correspond to geopotential height at 500 hPa during the control decade (from Katragkou et al., 2011).

This work has been accomplished in the framework of the FP6 European Project CECILIA (Central and Eastern Europe Climate Change Impact and Vulnerability Assessment, Contract Nr 037005). The results were produced on the EGI and HellasGrid infrastructure with the support of the Scientific Computing Center at the Aristotle University of Thessaloniki (AUTH). The results of this work have been published in peer-review journals (see references), presented in several national and international conferences and awarded by the Hellenic Meteorological Society (2008), the European Association for the Science of Air Pollution (2009) and the Research Committee of the Aristotle University of Thessaloniki (2010).

Contact details:

  • Dimitris Melas (PI), Associate Professor, AUTH, melas (at) auth.gr
  • Prodromos Zanis, Assistant Professor, AUTH, zanis (at) geo.auth.gr
  • Eleni Katragkou, Lecturer, AUTH, katragou (at) auth.gr
  • Scientific Computing Center, AUTH, contact (at) grid.auth.gr

References:

  1. Huszar P., K. Juda-Rezler, T. Halenka, H. Chervenkov, D. Syrakov, B. C. Krueger, P. Zanis, D. Melas, E. Katragkou, M. Reizer, W. Trapp, M. Belda, Potential climate change impacts on ozone and PM levels over Central and Eastern Europe from high resolution simulations, Climate Research (in press), 2011
  2. Katragkou Ε., P. Zanis, I. Tegoulias, D. Melas, I. Kioutsioukis, B. C. Krüger, P. Huszar, T. Halenka, S. Rauscher, Decadal regional air quality simulations over Europe in present climate: near surface ozone sensitivity to external meteorological forcing, Atmospheric Chemistry and Physics, 10, 11805-11821, 2010
  3. Κatragkou E., P. Zanis, I. Kioutsioukis, I. Tegoulias, D. Melas, B.C. Krüger, E. Coppola, Future climate change impacts on summer surface ozone from regional climate-air quality simulations over Europe, J Geophys Res (in press), 2011
  4. Zanis P., E. Katragkou, I. Tegoulias, A. Poupkou, D. Melas, Evaluation of near surface ozone in air quality simulations forced by a regional climate model over Europe for the period 1991-2000, Atmospheric Environment, 45, 6489-6500, 2011