Environmental and Imaging Sciences

WEB Services: from Research to Industrial Applications

Ernesto BonomiErnesto Bonomi

Energy and Environment

CRS4

ernesto@crs4.it

Motivation for Doing

Environment is going to be a major issue.Since 50 years, environmental problems are aggravated by

• overpopulation,• increases in agricultural productivity,• fast industrial development.

Problems include

• starvation and malnutrition,• demand for resources such as fresh water and food, • consumption of natural resources faster than the rate of

Environmental engineering must grow rapidly from basic research and deal with the activities of monitoring and managing natural resources on an industrial scale.

• consumption of natural resources faster than the rate of regeneration (such as fossil fuels),

• rising levels of atmospheric carbon dioxide, • global warming, and pollution.

Strain on the environment causes a decrease in living conditions.

Promoting an interdisciplinary view of energy andenvironmental problems, in which the mechanisms,

be they physical, chemical, biological, or economic, are no longer analyzed and modeled as independent, but are investigated together with the support of

• robust theoretical frameworks• accurate numerical tools• reliable reference data

Objective

• reliable reference data• large computing infrastructures• motivated funding partners

Organizing the efficient use our collective intelligence to study solution strategies and design innovative applications

From Modeling to Innovative Services

Problem formalization Application planning Programming and optimization

HPC application as a Cloud service

Critical Issues

An integrated vision that requires high level skills for:

• The development of software tools for collaborative activities allowing a transparent access to• network resources • data acquisition systems• storage and computing platforms• application software

within a unique infrastructure

• The fundamental understanding of physical, chemical and biological processes operating at different scales

• Programming and implementing on HPC clusters with architectures in continuous evolution (multicore CPUs, GPUs and FPGAs)

• Conceptualizing the data analysis process and development of tools for problem solving and decision support

Real Collaborations and Virtual Organizations

Working Group 2: monitoringWorking Group 2: monitoringWorking Group 2: monitoringWorking Group 2: monitoring, , , , and sustainable water resource and sustainable water resource and sustainable water resource and sustainable water resource managementmanagementmanagementmanagement

Working Group 3: information systems Working Group 3: information systems Working Group 3: information systems Working Group 3: information systems for the analysis for the analysis for the analysis for the analysis of of of of environmental and environmental and environmental and environmental and

Working Group 1: short Working Group 1: short Working Group 1: short Working Group 1: short term prediction of extreme term prediction of extreme term prediction of extreme term prediction of extreme eventseventseventseventsA Cloud/Grid is an

infrastructure that allows the integrated and collaborative use of virtualized resources� Data servers Data servers Data servers Data servers � Computational serversComputational serversComputational serversComputational servers� Connecting networksConnecting networksConnecting networksConnecting networks for the analysis for the analysis for the analysis for the analysis of of of of environmental and environmental and environmental and environmental and

territorial dataterritorial dataterritorial dataterritorial data� Connecting networksConnecting networksConnecting networksConnecting networks� Numerical applicationsNumerical applicationsNumerical applicationsNumerical applications� Information systemsInformation systemsInformation systemsInformation systemsowned and managed by one or more entities

On the infrastructure, each virtual organization acts as a services provider while each partner, researcher or engineer, becomes the recipient

Site 2Site 2Site 2Site 2

Environmental Environmental Environmental Environmental engineerengineerengineerengineer

Application Application Application Application developerdeveloperdeveloperdeveloper

Site 1Site 1Site 1Site 1

Compute Compute Compute Compute infrastructureinfrastructureinfrastructureinfrastructurevia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portal

Project Planning and Management: the Developers

Numerical applications� GIS GIS GIS GIS ((((input&outputinput&outputinput&outputinput&output))))� PrePrePrePre----processingprocessingprocessingprocessing� Simulation Engine Simulation Engine Simulation Engine Simulation Engine and and and and OptimizerOptimizerOptimizerOptimizer� PostPostPostPost----processingprocessingprocessingprocessing� VisualizationVisualizationVisualizationVisualization

Services for the decision support� WEB Collaborative WEB Collaborative WEB Collaborative WEB Collaborative EEEEnvironment nvironment nvironment nvironment � Data Data Data Data assimilation and Analysis Tools assimilation and Analysis Tools assimilation and Analysis Tools assimilation and Analysis Tools � Problem Problem Problem Problem Solving Solving Solving Solving driven by physical modelsdriven by physical modelsdriven by physical modelsdriven by physical models� Web GIS Web GIS Web GIS Web GIS (solver output, field data, maps…) (solver output, field data, maps…) (solver output, field data, maps…) (solver output, field data, maps…)

via the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portal

Data Data Data Data infrastructureinfrastructureinfrastructureinfrastructurevia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portal

Site 3Site 3Site 3Site 3Site 3Site 3Site 3Site 3

Compute infrastructureCompute infrastructureCompute infrastructureCompute infrastructurevia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portal

Compute infrastructureCompute infrastructureCompute infrastructureCompute infrastructurevia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portal

EnvironmentalEnvironmentalEnvironmentalEnvironmentalmanagermanagermanagermanager

EnvironmentalEnvironmentalEnvironmentalEnvironmentalmanagermanagermanagermanager

Project Planning and Management: the End Users

Collaborative problem-solving platform as a decision support system� Interactive simulation toolsInteractive simulation toolsInteractive simulation toolsInteractive simulation tools based on based on based on based on

physicsphysicsphysicsphysics� Web GIS environmentWeb GIS environmentWeb GIS environmentWeb GIS environment for datafor datafor datafor data� StorageStorageStorageStorage� Retrieval Retrieval Retrieval Retrieval � RenderingRenderingRenderingRendering

Analysis and decision instrumentsAnalysis and decision instrumentsAnalysis and decision instrumentsAnalysis and decision instruments for for for for

Data infrastructureData infrastructureData infrastructureData infrastructurevia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portalData infrastructureData infrastructureData infrastructureData infrastructurevia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portal

via the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portalvia the Cloud portalRenderingRenderingRenderingRendering

� Analysis and decision instrumentsAnalysis and decision instrumentsAnalysis and decision instrumentsAnalysis and decision instruments for for for for � Management Management Management Management � PlanningPlanningPlanningPlanning� Costs evaluationCosts evaluationCosts evaluationCosts evaluation� Editing of results and disseminationEditing of results and disseminationEditing of results and disseminationEditing of results and dissemination

Ocean Ocean Ocean Ocean DynamicsDynamicsDynamicsDynamics

Ocean Ocean Ocean Ocean DynamicsDynamicsDynamicsDynamics

MeteorologyMeteorologyMeteorologyMeteorologyHydrologyHydrologyHydrologyHydrology

Earth ScienceEarth ScienceEarth ScienceEarth ScienceEarth ScienceEarth ScienceEarth ScienceEarth Science

Site Site Site Site RemediationRemediationRemediationRemediation

Site Site Site Site RemediationRemediationRemediationRemediation

Forest FireForest FireForest FireForest Fire

GeophysicalGeophysicalGeophysicalGeophysicalImagingImagingImagingImaging

GeophysicalGeophysicalGeophysicalGeophysicalImagingImagingImagingImaging

Subsurface Imaging Services for Environmental Geophysics

Zeno Heilmann, Guido Satta, Andrea Piras

CRS4, Department of Energy and Environment

Paolo Maggi

NICE s.r.l., Department of Research and Development

Gianpiero Deidda

University of Cagliari, Department of Civil and Environmental Engineering and Architecture

Environmental Geophysical Imaging: a Cloud Solution

Creating a Cloud infrastructure for environmental geophysics

• In-field Quality Control

• Optimization of SR/GPR data acquisition/processing

• Providing a browser-based user interfaceeasily accessible from the acquisition field

• On-the-fly processing of seismic data on• On-the-fly processing of seismic data onthe remote infrastructure

• Running data-driven and highly parallelimaging and velocity analysis numericaltools

• Enabling remote collaboration andmonitoring of data acquisition

Environmental Geophysical: Data Acquisition

Environmental Geophysical: Data Processing

Seismic Records

InputInputInputInput

Processing Phases

SystemSystemSystemSystem

Environmental Geophysical: Quality Control

On-site-acquisition quality control is difficult when strongly variable near-surface conditions are encountered

• Success depends on acquisition parameters such as • recording time • sampling interval • source strength• maximum offset • maximum offset • receivers spacing

It is impossible to optimize in the field the acquisition

Cloud services from on-site tablets and PCs using

Wireless data transmission + remote HPC processing

Acquisition Quality Control

Preprocessing and visualization using SU• Basic preprocessing steps can be applied fast and

conveniently without locally installed processing package.

Time imaging using CRS technology• Data-driven CRS imaging technology ---state-of-the-art in oil

exploration--- enables highly automated data processing.

Workflow editor:• Fast construction and processing of different workflows to

find optimum processing parameters.

exploration--- enables highly automated data processing.

• Velocity model building based on CRS results and timemigration provide complementary subsurface information.

The Cloud Portal

The Cloud Portal: Dataset Uploading and Data Conversion

The Cloud Portal: Creating a Project Using Uploaded Data

The Cloud Portal: Preprocessing the Uploaded Data

The Cloud Portal: Data Visualization tool

The Cloud Portal: CRS Imaging Tools

The Cloud Portal: CRS Imaging Running Jobs

The Cloud Portal: CRS Seismic Time Imaging

Deidda, G. P., Ranieri, G, Uras, G., Cosentino, P., Martorana, R., 2006: Geophysical investigations in the Flumendosa River Delta, Sardin ia (Italy) --- Seismic reflection imaging: Geophysics, 71, B121–B128.

The Cloud Portal: Velocity Model Builder

The Cloud Portal: Time Migration

The Cloud Portal: GPR Data Time Imaging

CRS Stacking

Perroud, H., and Tygel, M., 2005, Velocity estimati on by the common-reflection-surface (CRS) method: Using ground-penetrating radar: Geoph ysics, 70, 1343–1352.

• The best set of parameters ξ=(R, α0) provides reliable traveltimes

• In the image space, the content of each pixel results from the signal averaged along a traveltime trajectory

Time Imaging without Velocity Model: a Data-Driven Solution

along a traveltime trajectory (green)

Time imaging Sigsbee2ALayers, faults and diffractors Semblance

(Potential) Services for Forest Fires Behavior Prediction

Antioco Vargiu, Luca Massidda, Gianni Pagnini e Marino Marrocu

CRS4, Department of Energy and Environment

A Web portal to the Ensemble Meteorological ForecastRun of the simulation chain

Selection of a date and an initial time

Run of the simulation chain: Large scale (20Km)Run of the simulation chain: Medium scale (10Km)Run of the simulation chain: Small scale (2Km)Forest fire: integration with a CFD solver

GIS providing orography, boundary conditions and fuel distribution on the ground

Environmental Sciences

A collection of services

Forest Fire service Selection of a site

Environmental Sciences & Process Engineering and Co mbustion

Forest fire simulation: Budoni, 24 August 2004

Environmental issues make necessary a strong integration of expertise from different disciplines, made possible through the development of virtual organizations of federated entities

Conclusion

Today SW technology makes almost transparent the operability of a Cloud infrastructure (network, compute and data resources) for the data sharing and the exploitation of complex applications via Internet

Web services and Cloud portal technology makes man-Cloud interaction as much as possible close to man-desktop interaction