Special simumlation issue : S.O.S Planet

8/18/2019 Special simumlation issue : S.O.S Planet

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S.o.S.planetspecialsimulation issue

3464 Supplement . april14 2016. not to be Sold Separately

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CEAandBullare co-designingexascale technologies1

CEAboosts industrial innovation

Harnessing exascale computinganddataprocessingwill openunexploredperspectives for thenumerical

simulation ofcomplexphysicalphenomenaandindustrial objects,by2020 andbeyond.

Inorderto tacklethis challenge, CEA, inpartnership

withAtos, isco-designing technologiesto:

Reduceenergyconsumption

Process andmanagemassive flowsofdata

Increaseperformance,efficiencyandmodularityof

supercomputerarchitectures

Design fault-tolerant architectures TERA1000,developed inpartnershipwithAtos/BullaccordingtoCEA requirementsandinstalled in2016,

is foreshadowingexascale supercomputers.

LocatedatCEABruyères-

le-Châtel site,TGCC(CEAVeryLargeComputing

Centre) hostsCCRT(ComputingCentrefor

ResearchandTechnology), a shared infrastructureoptimized forHPC.CCRTpartnersreceive1.4Pflops of

computing power, aswell asservicesandexpertise

supported byCEAHPC teamskills– anessential asset fortheirnumericalsimulations.

CCRTpartnersasofMarch2016

AirbusD&S, Areva,Cerfacs,EDF, Herakles,Ineris,L’Oréal,SafranTech,Snecma,TechspaceAero, Turbomeca,

Thales, ThalesAleniaSpace,Valeo, CEA aswellasFranceGénomiqueconsortium (supportedbyFrench

governmentPIA).

Numericalsimulationofcombusion inanhelicopterturbo-engine- TURBOMECA

Simulation ofsurfacecurrentson anaircraftnoseradome- THALES

Aero-acousticnumerical simulationofa carinterior airconditioningsystem-VALEO

1 - At the scale of a billion of billions of operations per second (exaFlops) and memory bytes (exaBytes).

CEAat theheart of innovationforextremecomputing

andBigData

To know more www-ccrt.cea.fr Contact [email protected]


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W

e are going to need more than the good inten-

tions of governments if we are to limit global warmingto lessthan 2°nowandfeed9billion

humans in the future. Public-sector and economicplayers must do everything in their power to meet thesechallenges. Although it is no miracle solution, simula-tion enables us to be good diagnosticians by predicting

changes, especially climate change. Simulation also

provides invaluable decision-making tools to improvehowwemanageresourcesanddealwithnaturalhazards.

By modeling living organisms, simulation will facilitatehuman existence on the only planet we’ve got.Scientists alreadyknowhowtomodelcrop andmicro-

algae growth. And models can be created in every domain, as Antoine Petit, INRIA’s CEO, explains. Wecan use the same corpus of mathematics to simulate

physical and biological phenomena, such as bioche-mical reactions and cell migration. Fluid mechanicstechniques used to calculate

planes’ air penetration have

been reused to model bloodflow around the body. Other

techniques adapted to thepharmaceuticals industrywillsoonhelpussimulate clinical

trials, thus reducing how long it takes for treatments

to come onto the market. Coupling patient data withgeneral models is leading the way for patient-specificmedicine and more reliable diagnoses.

Combined with artificial intelligence technology,

models will become better adapted and more able to berebuilt from huge amounts of data. This means scien-tists will have an even greater responsibility. Just as theparameters chosen for climate models determines how

close they come to real conditions, so too the quality of modeling living organisms is the key to renewing

medical science and even human existence. Despitespace exploration, 9 billion human beings will have tolive on a single planet with limited resources. ❚❚

“Cmbid wihrifici

iigc chgy,mds

wi bcmbrdd.”

9 Billion Humans,onE planEt

AURÉLIEBARBAUXassistantEDitoR,

l’usinE DiGitalE

3

Président-directeur général: ChristopheCzajkaDirecteurgénéraldélégué: Julien ElmalehDirecteurdu pôleindustrie: Pierre-Dominique LucasDirectrice de larédaction: ChristineKerdellantDirectrice adjointede larédaction: AnneDebrayCoordinatrice éditoriale: AurélieBarbaux

Chefd’édition : GuillaumeDessaixDirectionartistique: EudesBulardOntparticipé à cenuméro: ClaireLabordeetRebeccaLecauchois (secrétariatde rédaction) ;LaurentPennec (maquette)Supplémentde «L’UsineNouvelle» n° 3464du 14avril 2016(commission paritairen° 0712T81903)Ne peutêtrevendu séparément.Unepublication du groupeGisi,AntonyParcII -10 place duGénéral-de-Gaulle - BP20156 - 92186AntonyCedex.Directeurde publication: ChristopheCzajkaImpression: Roto FranceImpression77185LognesPhotode couverture: Julien Aubert/Finlay, Jackson,Olson,Gillet,UniversitéParis Diderot/IPGP/CNRS

ESSENTIALS

ayrf simuli p.4

INTERVIEW

ai pi, Ceo f Iri p.6

DOSSIER

Wd simul hlw p.8

aFrchsvir fir p.10Krs f hl p.16

INTERVIEW

olivirGu,MééFrc’s duydircrgrl p.18

MARKETS

SMeS, urllmxrs p.20

A REALSTAR

Cybltch, umricl frmig p.26

DIGITAL TRANSFORMATION

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PORTFOLIO

nurrvld p.34

VIRTUALREALITY

affrdbl immrsi fr vry p.38DESIGNOFFICE

thqus fr fully umusvhicls p.42

INNOVATION

nwrksf ccd bjcs,i’s chllg p.44

AERONAUTICS

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Smmir

SIMUlatIon

L’USINENOUVELLE i n°3464 supplEmEnt i apRil14 2016

Representationofthemagnetic

fieldintheearth’s core.

1

S.o.S.planètespécialsimulation

Supplémentdu3464.14avril2016.ne peutêtrevenduSéparément

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simulation

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Training

FRanCE’s FiRstRiVERsimulatoR

A consortium run by the Compagnie Natio-

nale du Rhône took delivery of France’s firstriver navigation simulator in mid-March.This3D simulatorwasdesigned byAlyotech

and is used for training and improving theskills of boat pilots navigating the RiversRhône andSaöne,especially the trickiest sec-

tions. The device has a 10-metre cylindricalscreen with a 240° angle of vision, together with a helm station that can be configured

into five types of boat. The pilot’s cabinequipment, as well as the signaling system,currents andwater-columndensity,weather

conditions, river traffic, time of day, etc. are

also modular. The scenarios include variotypes ofbreakdown and alerts to replicate

many situations as possible. ❚❚ J.B.

Aftmbfaabttmptafty.

Solar System

CalCulatinGPlanEtninE

Usingmathematicalmodels, resear-chers at the California Institute of

Technology (Caltech) believe they have discovered a ninth planet inthe solar system. They reached this

conclusion while trying to explainthe behavior of celestial objects in

the Kuiper Belt, beyond Neptune’sorbit. Six of these objects have an

elliptical orbit converging to thesame point and on the same 30°tilt, suggesting that they are “attrac-ted” by an invisible mass. Since the

probability of this being coincidenceis only 0.007%, the data could beexplained by the influenceof a ninth

planet’s gravity. This hypotheticplanet could have an extraordina

mass – ten times that of Earthand orbit twenty times farther frothe sun on average than Neptun

Planet Nine couldalso take 10,0020,000 years to rotate around thsun. ❚❚ JulienBergounhoux

Patnbttmataeat.

Industry

a nEW 3DsimulationClustER

The it3D event, organized in autumn by the Bordeaux-based company Im

mersion, boostedthe local 3D simulation industry. It even generated an idfor a cluster bringing together companies such as ESI Group, LumiscaphandDiodasoft. Usedintensively in theaeronautics andautomobile industri

for the past decade, 3D simulation now needs to be assimilated by thesub-contractors over the next five years. The hardware has become accesible and «the ‘Factory of the Future’ plan launched by the French state

a fantastic opportunity to introduce this technology,» explains ChristophChartier, Immersion’s CEO. ❚❚ nicolAscésAr

theFrnercstrphe

In2015,TERATECorganizedthefirstnumerical simulation trophies.Thesixprizewinnerswererevealedon23JuneattheTERATECForum,heldattheÉcolePolytechnique in Palaiseau (Essonne).Therewere fivecategories, showcasingthe simulation expertise of start-upsandSMEs,aswellastheabilityoftheFrenchpublic-sector research ecosystemto collaborate with private companies.SincethesimulationexpertiseofbigFrenchcompaniesisnowwell-established,theywerenotincludedintheseawards.Thestart-up

trophywasawardedtoCybeleTech,whichissimulatingplantgrowth[seepage26].TheSMEtrophy,showcasingacompany

thathasusednumericalcalculationtechnologytodevelopnew productsorserviceswas

awardedtoPrincipia,whichissimulatingseabed-surfacelinks in offshore systems.TheEuropeanCenterforResearchand

Advanced Trainingin Scientific Computation(CERFACS)wasthejointwinner(withTurbomeca) of the collaboration trophy,which rewards groupingsbetween a bigcompanyandanSME.Thisawardwasgivenfor collaborative simulation work on a turbojetcombustionchamberandfirst-stageturbine.TheinnovationtrophywasawardedtoHydrOcean,astart-upthathasindustrializeditsSPH(SmoothParticleHydrodynamic) simulationmethodforapplicationtofast,complexfluidflows[seepage24].Finally,thefirstjuryprizeforSMEprojects displaying exemplary innovation

andpromotingtheuseofnumericalcomputation was awarded to Disteneforitsmeshgenerationtool,MeshGems.TERATECalsomadespecialmentionofDanielsonEngineering,anSMEthatdesignsand manufacturesprototype thermal enginesfortheautomobile,aeronautics,anddefenseindustries.Thecompanyisusingnumericalsimulationtodevelopdigitalmodelswithverysimilarperformancetorealengines. ❚❚JeAn-FrAnçoisPrevérAud

D . R . ; C A l T E C H

e v e n T s

FvecegrehwceheexperefFrechr-pdsmE.


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simulation

The European Center for Research and Ad-

vanced Training in Scientific Computation(Cerfacs) took delivery of a new supercom-puter. Built by the Chinese company Leno- vo, with 240 teraflops of computing power(1 teraflop is equivalent to 1 trillion floating

point operations per second), and will triplethe computingpower at this Toulouse-basedresearch center.Some1.2million Euroshave

been invested in this new computer, whichreplacesa20-teraflopHPsupercomputerand

completesanother53-teraflopsupercomputer

built by Bull. The Cerfacs is a fundamentaland applied research center specializing innumerical modeling and simulation. It deals

with technical and scientific topics in variousfieldsofpublic-sectorandindustrial research:

aeronautics, the automobile industry, space,climate studies, etc. Approximately 150 re-

searchers, engineers, andadministrative staff work at the Cerfacs. ❚❚ RidhaLoukiL

5

Cnseqences f 100-yer Fl nPrs

Computing

240tERaFloPs at tHE CERFaCs

240x 1 trllnpertns persecn.

Computing

tERa 1000 insERViCEat tHE CEa-Dam

Atos has just delivered the first phase of thenewTERA1000supercomputer totheFrench

Atomic Energy and Alternative EnergiesCommission, Military Applications Division(CEA-DAM).Thissupercomputerhasdouble

the theoretical computing power of the pre-

vious generation TERA 100 supercompu-ter and is five times more energy efficient.

“The TERA 1000 is the third generationof supercomputer resulting from the Bull/CEA-DAM partnership, which started inthe early 2000s. The computing power has

been increased 5,000-fold,” says FrançoisGeleznikoff, the CEA’s director of military applications. The first phase of TERA 1000

comprisestwocomputing systems: onebasedonanIntelXeonE5v3processor andanotheronan IntelXeonPhiprocessor. This installa-

tion is a forerunner of the future generationexascale (1,018 flops) supercomputers that will come into service by 2020. ❚❚ J.-F.P.

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Fluid Mechanics

siEmEnsaCQuiREsCD-aDaPCoSieenshscqired CD-dco

for 970 iion dorstocoeteitsortfoioofnericsitiontoosforrodcts nd indstrirocesses. CD-dco seciizesin fid echnics (Str-CD),soid echnics,eectrocheistry, nd costics.The conygenertes trnoverof roxitey 200iiondors,nincreseof12%yeroverthestthreeyers,ndeoys ore thn900 eoe.

Environment

HYDRoCEanatBuREauVERitasBreVerits recenty cqiredHydrOcen,sin-offoftheÉcoe Centre de Nntesseciizing in nericsition of fid dynicsfor the ritiesector.HydrOcenwssetin2007byErwnJcqinndtheÉcoeCentre de Nntes. It rovides

design ndotiiztionservicesforshis, offshore strctres,rcing ychts,nd rine-energyrecoverysystes.

Sound andLight

oPtissWalloWsuP

GEnEsisThe French softwre vendorOtis thtseciizesin ightsition hscqired Genesis,notherFrenchsoftwre vendorwithexertiseinsond

sitionnd ercetion.Bothconies shre coonsition hiosohy bsed onsingthehysicsofhenoenthey site.Toos sitinghnsightndheringwihebothconies’ designers tkeccontof“serexeriences”to deveotheir rodcts.

D . R .

L’uSiNENouvELLE I N° 3464SupplEmENT I apRIl 142016


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Simulation, especially modeling, is a core activity at the French National Institute for Researchin Computer Science and Automation (INRIA),as its CEO, Antoine Petit, explains.INTERVIEWEDBY AURÉLIEBARBAUX

INTERVIEW

“moDElinG isacorEactivity

at inria”

What typef imulatin wrk de INRIAd?Modeling is a long-standing coreactivity at INRIA since w

simulate models, which are needed in every field. But the b

difficulty lies in designing appropriate models. For exampclimate modeling is extremelydifficultsince there aresever

models rather than just one. Climate change controversihave all focused on whether or not these models are valiIt’shard toknow whether ornot a model is correct, especia

since no singlemodel can take into account every parametYou have to omit someof the less important parameters, anthis causes disagreements.

Yuaythateverythingcanbemdeled,butINRIAcan’tbeatthecuttingedgefeveryfield.

The French school of mathematics is regarded as one

the best in the world. In some sense, we’re intrinsicagood at modeling. What’s good about modeling exercis

is that they require the cooperation of mathematicians ancomputer scientists with people working in applied sectorTherefore, we are not better in any specific appliedfieldtha

in another. We’ve developed our programs in response


7/48L’UsINE NoUVELLE i n°3464 suPPLEmEnt i aPriL14 2016 7

“the Fehhfhe egded

e f he be he wd. ieee,

we’e gd deg.”

interest in modeling from variousdisciplines, it happened in

healthcare twelve years ago. But we work with every sectorand, on the whole, the techniques are always the same.

What envirnmental reearch i INRIAcarrying utand whare yuwrking with?We’reworking with institutionssuch as Météo France, Ins-

titut Pierre-Simon-Laplace, and the University of Versailleson climate modeling – more specifically on air quality – andin partnership with companies such as EDF, modeling wind

circulation to help position wind turbines. Environmentalresearch is not limited to climate issues.

Have yudevelpedthereult f thi reearch yet?Generallyspeaking,I don’t like theterm «development» since

it’s often putinto thesame categoryas financialspin-offs.This

isn’tnecessarily the caseand other types ofvalue can takepre-cedenceover monetary value.For example,over thepastthirty

years INRI has initiated 120 start-ups, which have created3,000 jobs. Several start-upsa year arelaunched in thehealth-care sector. It’s a bitearly forthis in theenvironmental sector,even thoughsome topics lend themselves to development.In

collaboration with the citiesof ParisandSanFrancisco, we’vedesigned a smartphone application called SoundCity, whichmeasurescity noisepollutionandenables users tocollect data.

We also have a project looking at microalgae as a protein andenergy source,modeling howenvironmental conditions affectgrowth according to microalgae type. This project is part of

the BIOCORE program in Montpellier.

D yuneed newmdel t imulateliving rganim

r canyu adapt exiting mdel?There’s often a common basis. For example, fluid mecha-nicstechniques usedto simulate aeroplanes’air penetration

are now being usedto model blood flow aroundthe body. Wecan reuse an entire corpus of mathematics when we switchfrom one application to another.

Hw many team wrk nmdeling?INRIA employs 2,700 people, including 1,800 researchers

(600 of whom have permanent contracts). Modeling couldpotentially interest any of our teams, especially life-science

research groups (25% of our total teams). Part of our work

involvesrunning calculation codeson increasinglypowerfulcomputers. To move from petaflops to exaflops, we have

dedicated simulation (rather than modeling) teams writing software stacks to get the best use out of these new super-computers. We’re working with manufacturers – especially Bull and Hewlett Packard – as well as on virtual supercom-

puters to take into account processor-failure probabilities.

Since some computer codes use much more electricity than others, we’re designing algorithms to minimize powerconsumption and are also working on dedicated hardware.

Reearchi a lng-term effrtwherea digital technlgy mveveryquickly. Hwd yu recncile theedifferentpace?

It’s a popular misconception that digital technology moves very quickly, although it’s true that this technology

can come onto the market very quickly. In 2003, the FrenchNational Science Fund, which was replaced by the NationalResearch Agency (ARN), launched three new areas of acti-

vity: computer security, bulk data, and new mathematicalinterfaces. These are today’s research topics. But it would

be a mistake to think that some amazing new research topicis going to emerge in six months’ time that will put all ourresearchers out of a job. They know what the topics of thefuture will be.

What areyurmain current area f reearch?Everything relating to modeling and simulation, of course.

We’re conducting research on the Internet of Things, dataandbigdata, developing newalgorithms fordata processing,

display, encoding, and transport. Another major researcharea is cybersecurity, cryptography, and protocols. Roboticsis also a key topic and we’re very interested in autonomous

cars.Wealsorun manymulti-disciplinary researchprogramsat the interface of various disciplines.

WhathappenedttheinitiativegivingsMEaccetyurlabratrie?

We cooperate with companies in several ways. First, com-

paniesbenefit from skills transferswhenever ourresearchersmove into the business world. We’ve also set up a dozen joint laboratories with the main industrialgroups: Microsoft,

Alcatel-Nokia, Total, EDF, Orange, Alstom, Airbus Group,etc. What’smore, we’ve established many start-ups. Finally,our INRIA innovation labs collaborate with SMEs– on muchshorter deadlines than with big groups – to change inno-

vations into products. We’ve already set up a dozen suchinnovation labs and another is currently being established

with Safety Line, to reduce airplanes’ fuel consumption. In2015, we also launched INRIA Tech in Lille, with support

from EuraTechnologie Center of Excellence. Although itsname is inspired by CEA Tech, we’re not doing the samething. INRIA Tech has a dozen engineers – and not resear-chers – providing initial responses to industrial needs. It’s

got off to an encouraging start. ❚❚


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weneedtoSIMULAtetHePLAnetnow

Even if global warming slows down, it will continue to radically change our environment.Numerical simulation is helping predict these changes.BYALAINCLAPAUD,THIERRYLUCAS, ANDJEAN-FRANÇOISPREVÉRAUD

C D - a D a p C o


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SIMULAtIon

9

Modelingthebehaviour

ofindustrialbuildingsbeforeconstructionhelpsassessandlimitthe dispersionof pollutantsintothe atmosphere.

t

heagreement signedby195 countries at the COP21conference in December 2015 is historic, imper-

fect, and very ambitious. Working towards global warming of less than 2°C – with an aim of 1.5°C to meetthe needs of the most vulnerable states – was not easy

to negotiate. Furthermore, funding for energy transition

in developing countries is far from certain after 2020.Nevertheless, thingsseem tobe inmotion. Apart from their

financial resources,Western countries havesomething elseto share and promote in the fight against global warming:

their technological expertise in numerical simulation.Modeling natural systems helps understand and predictclimate change, of course, as well as the consequences of climate disruption (flooding, rising sea levels, and catas-

trophes) and ways to optimize natural resources. In the

race to calculate natural resources under threat – such as water– and resources thatneeddeveloping– suchas solar,

wind, tidal, and other renewable energy sources – France, with its long tradition of applied mathematics teaching,is in a strong position. French researchers, industrialists,

and a start-up incubator are working on new simulation

models. They areaiming to reproduceevermore advancedphenomena on their computer displays and study new

approaches to numerical simulation making it easier foreveryone to take up. ❚❚

L’USINENOUVELLE i n°3464 supplEmEnt i april14 2016


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French laboratories have become experts atsimulating our environment – whether air-conditioning systems, storms or major industrialcatastrophes – as demonstrated below.ByAlAinClApAud

environment

aFREnCHsavoiRFaiRE

iBax, hrassscsa fa cf waswa aas.

Just when we are seeing the first consequences of

climate change – including in France – simulation isplaying an increasingly important role in protecting

our environment andcombatingglobal warming. Simulation

calculations are used on all fronts to protect the environ-ment: optimizing human infrastructures and water/energy resources, predicting coastal erosion in the face of rising

sea levels, forecasting catastrophes, modeling pollutionphenomena, etc. And French experts – at EDF, Suez, Veolia,the CNRS, the National Institute for Research in ComputerScience and Automation (INRIA), the Scientific and Tech-

nical Center for Building (CSTB), and the National Researchand Safety Institute (INRS) – are often at the cutting edge of innovation, providing original solutions.

proteCtion FromClimAteHAZArdSThe worldwide agreement signed at the COP21 confe-

rence in December 2015 set nations new targets to limitCO2 discharged into the atmosphere. Many countries

are already facing climate change. France – especially itscoastline – has not been spared, as Antoine Rousseau, anINRIA researcher in charge of theLEMON team (coastline,environment, models, and numerical tools), underlines:“Coastlines face three risks: storms and tsunamis, erosion

and flooding. We need to design mathematical models tounderstand what’s happening long term, as well as ‘real-time’ risk-management simulation tools to evacuate floodzones in time,” he explains.

It’s not easy. Every process brought into play – whether

winds, currents or ground motion – is very complex. Theequations require vast amounts of calculation, not tomention the difficulty of coupling these simulations wheneach process changes at its own pace. Erosion is causedby water/sediment interactions when seabeds influencecoastal currents and vice versa. “Currents change within

hours whereas modifications to sandy seabeds occur overseveral months or years. From a mathematical perspective,

coupling phenomena is very difficult,” says Rousseau. Bit’s not impossible. A program funded by the French Natinal Research Agency (ANR) enabled Rousseau’s researcteam to limit silting up in the Sète (Hérault) area. The teaused their calculation codes to place geotextile “socks” o

the seabed; these “socks” modify currents and hence limcoastal erosion.

While simulation is invaluable for long and medium-terenvironmental forecasting, it is also essential fordealing winatural catastrophes. TheLEMON team is collaboratingclsely with theUniversity ofMontpellieronreal-time modeli

of city flood scenarios. Their goal is to design tools for uby the Prefecture and firefighters during evacuations. “Thissue here is working out whether we need a rough, vequick forecast or should wait for a better quality forecasIt’s about finding a compromise. Mathematics has role play in improving the model (at constant calculation timand hence forecasting quality,” says Rousseau.


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Suez Environnement is also interested in this operationalsimulation. “Intheeventof storms, wehave tomanage waterarriving suddenly in thenetwork,” explains BertrandVanden

Bossche,who manages the R&D portfolio of the Smart Solu-tions business. In the Paris region, Vanden Bossche’s team

has started installing extremely complexcalculation modelscombining meteorological data and radar image analysisfrom Météo France. “This enables us to calculate runoff, i.e.the volume of water that is going to pour into our network.Once we know the water levels in our storage basins andnetworks, we can organize the correct pumping strategy toensure wastewater treatment plants are not sent any more

water they can actually accept. At the same time, we try toavoid dischargingpotentiallypollutedwater into the naturalenvironment,” saysVandenBossche. In Bordeaux, Suezhasgone even further using algorithms to control sluice-gateheight and launch pumping operations to absorb rainwateras effectively as possible.

“W’wkgc-faas”

KaRimaÏt-moKHtaR,Director of the Environmental

Engineering Laboratory

(LaSIE FRE CNRS3474)

Wha gsshaa

casa

sach?

We’re working onmaterials, especially onsimulating transfer of

aggressive agents. This will help work out how long structures suchas the Millau Viaduct willlast in relation to theirenvironment. The goal is todesign more eco-friendly coatings than those usedcurrently, which oftenconsist of chemicalcompounds with low

biodegradability. Anotherarea of research is focusing on buildings’ energy consumption and quality of life.

of as swkg

hca ascs,wh

s ha?

Our theorists are aiming tomake simulation cheaper

and faster by developing new calculation methods.Computational FluidDynamics (CFD) codes use alot of computing resources,especially for long-termsimulations. But if you usemore approximate models,such as zonal or empiricalmodels, you lose thesubtlety of meshing. ❚❚

BetteruSeoFnAturAlreSourCeSSimulation can also be used to act on the causes of global

warming,helping the main industrial countries reduce their

CO2emissions. In particular, simulationhelps increase thelevel of renewable energy sources in each country’s energy mixby making themmorecost-effective. Photovoltaics, wind

power, tidal turbines andnewenergysources require heavy investment. The five offshore wind farms authorized for

construction off theFrench coast representa 7-billionEuroinvestment. It is thereforeessential to have reliable calcula-tionsof each turbine’s potentialwind power, i.e. estimateas

accurately as possible how much energy it will produce overits life span. “Calculating wind turbines’potentialpowerover

their 20-25-year life span requires sophisticated statisticaland dynamics models to understand wind interactions

where turbines are located,” explains Pierre-Guy Thérond,director of new technology at EDF Énergies Nouvelles. Toachieve this, EDF is increasingly abandoning simple simu-lation models based on laminar flow. Instead, the company is turning to Navier-Stokes fluid mechanics equations (orCFDequations for fluid dynamics calculations),which haveuntil now been used in aeronautics. Thérond justifies thisfar more expensive choice in terms of computing power.“CFD models give a better representation of turbulenceeffects. In complex zones– i.e. very rugged terrain on which wind turbinesare surrounded by complexwind movements

l’uSinenouvelle i n° 3464supplement i apRil14 2016


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12

rsafw-fcsbawfa.

and vortexes – the laminar flow hypothesis is no longersufficient,” he states. EDF’s approach has optimized wind-turbine location in relation to relief and to one another.

This approach prevents the wake of the first wind turbinesfacing the wind from compromising the efficiency of thoseplaced behind them.

Water is another natural resourcethat must be optimized.As a result of rising average temperatures and the world’spopulation increasing to 8 billion people by 2025, theamountofwater availableper inhabitant will dropbyalmost

a third worldwide. France will notescapethis trendsince far-

mers in southernFrance arealready affectedbywatercoursepumping restrictions every summer. Here too, simulationhas a role to play, as the Astuce &Tic consortium – whichstudied water-table changes on theCrau Plain – hasshown.The triangle formed by Arles, Salon-de-Provence and Fos-

sur-Mer (south of the Alpilles) covers a water table that very important for this region and is subject to both climaconstraints andheavy demographicpressure. FabienneTr

lard, director of research at INRA, has assessed the impaof global warming and economic development on this areHer calculations show that a 14% reduction in grasslancombined with a 30% drop in irrigation water and a 30%rise in drinkingwater extraction would causea 1.5-13-metdrop in the water table, depending on the location studieThis key data must guide political decisions for urban devlopment in this area.

Water supply networkoperators arealsodirectlyconfront

with the need to protect water resources, especially fropollution threatening water quality. Suez Environnement simulating how pollutants spread through soil to assess timpact of agricultural fertilizer on groundwater.

i Fbrry 2010, Cyc Xycbd w gd cffc– cd brc f vr dkd fdg Vdé.s2 wr kd, d wrgd by méé Frc.“t Frc Ggc srvy(BRGm) b cv xg Cyc Xy’ ycc rr bd r. t wbd rgy rc,” yFbrcDr, BRGm’ d f g-rfrc

cg. t rcc mf, aXa d mffdd J rrc rjwc cr-cckd dwrc c. a d bdrw kg vry gr c fdg d(wr g, crr d) wbdgdg. td w ccrc rd rb dv rgrv cqc f ccr fr b. ❚❚

Cc Xha – Sa gs c


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simulation

13

improvinG inFrAStruCturedeSiGnWhile simulation promotes better use of renewable

energy, it can also be used to improve construction work

andmake buildingsmore energyefficient.“We’ve developeda simulation code called MATHIS (modeling buildings’aeraulics, thermics and unsteady humidity),” explainsMaxime Roger, director of climatology, aerodynamics,

pollution, and water purification at the CSTB. This is noconventional fluid mechanics code, such as those used tomodel wind, but rather a nodal code representing every room within a building in the form of nodes. Each node isinterconnected to models representing air vents and otheraccessories in systems. Buildings’ ventilation, hygrometry,and other parameters can also be represented over a year,taking into account many different usescenarios.”TheCSTB

believes this simplified simulation will facilitate its uptake

by architects and design offices, especially for compliance with RT 2012 thermal regulations.Nevertheless, CFDcalculations are still essential for simu-

lating more complex phenomena, e.g. studying the impactof buildings and infrastructures on their environment.

Cheaper access to computing capacity makes it possibleto simulate how wind acts on a structure and takes into

account the surrounding buildings within a several hun-dred-meter radius. More developed numerical models canalso simulate phenomena such as rain. “We know how tomodel driving rain in stadiumsor semi-open spaces, suchasshopping malls partly coveredby a canopy,” explainsSylvain

Aguinaga,head of theCSTB’snumerical modelingdivision.

It is impossible to carry out small-scale simulationof water

droplet dispersion in wind tunnels; such phenomena canonly be predicted via numerical simulation. “Our clients –design offices and architects – therefore use concomitantrain/wind scenarios to predict whether or not terraces andgangways will be in the rain. We thensuggest modificationsto a building’sgeometry before constructionandhence limit

these phenomena,” continues Aguinaga.Simulations of buildings’ microclimate are increasingly

sophisticated. The Center for Research in Architectural

Methods (CERMA) – a CNRS laboratory now merged intotheNantesCenter forResearch in Urban Architecture – has

developed solar simulation software called Solene. Thissoftware enables architects to view shadebuildings will cast

A fgsca la Fa-s-m(vé),bas agahf f sghbhs.

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14/48

simulation

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14

on theground, calculate howlong sunshine will last at apoint in a 3D scene, and estimate direct natural light leveoutside buildings and in their rooms. Although these tooarenowstandard in architects’ anddesignoffices’ palette

Solene has developed and integrated increasingly complfactors. The impact of grassyareas,pondsand trees plantaround buildings is now integrated into calculations. addition, for buildings’ thermo-aeraulic calculations, thSolene software can be coupled with fluid dynamics simlation tools such as those supplied by the software vendFluent. Simulating local microclimates means architeccan calculate as accurately as possible how comfortab

buildings will be (both inside and outside) for their userThis would avoid buildings such as the recently construct20 Fenchurch Street skyscraper in London, whose solglare dazzles strollersby andmelts theplastic componen

of vehicles parked in front of it.

ComBAtinG pollutionAlthougha lot of resourceshave been poured into simul

tingnatural phenomena, considerable investmenthas albeen made in simulating theeffectsof human activity. The

is nothing unusual these days about consulting pollutiomaps for major cities, in the same way as we check weath

forecasts. Vivien Mallet, an INRIA researcher, underlinthe progress made in forecasting since the 1980s: “Simlation and observations made using sensor networks nocorrelate more closely, which has really helped impro weather forecasts. This is especially true for air-qualiforecasts, which are often very uncertain,” explains MalleFor this reason, researchers improving these models ha

installed many new sensors. Data from weather and aiquality monitoring stations – e.g. AIRPARIF – is alreadsupplemented by satellite images and is increasingestablished using the Internet of Things. Smart pollutiosensors have been installed on Lyon’s tramways and aexpected to appear on public streetlights in more and mo

French cities. All these data sources will feed into numrical models to produce more reliable pollution forecastEven cell phones can serve as sensors. For example, thSoundCity application uses cell phones to measure cinoise pollution.

Besides forecasting atmospheric pollution levels severhours in advance, simulation also helps respond to catatrophes. For example, we can simulate how a dirty bom

would explode in Place de l’Hôtel-de-Ville in Paris; depeding on the weather, this will tell us the arrondissemenin which to raise the alarm. Numerical simulation is alsused when constructingnewpetrochemical facilities to s

the impactof toxic discharged into theatmosphere. DurintheFukishimadisaster, theFrenchInstitute forRadiologic

Protection and Nuclear Safety (IRSN) made operationforecasts to find out whether or not the population wgoing to be exposed to radionuclide emissions. “We neehigh-quality weather data for reliable forecasts,” say

Mallet.Radioactive smoke plumesmove according to windirection and the risk to the population varies according whether the wind is blowing inland or out to sea. “Weath

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simulation

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[email protected]



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simulation

16

how much confidence we can have in these forecasts. W want to quantify models’ uncertainty in order to make thbest possible decisions,” explains Mallet.Numerical simlation is about aiding humans make the best decisions

protect their environment. Equations developed in Frenclaboratories help achieve this goal. ❚❚

forecasts can be very uncertain, especially in light winds.During the Fukishima disaster, Japanese scientists usedoperational simulation to predict smoke-plumemovementsand decide when they could discharge gas into the atmos-

phere to stop the reactor chamber exploding. Wenowwantto calculate not only where smoke plumes will go, but also

KEEpERsoFtHEplanEt

Climate simulation models served as the basis for the conclusions of the IPCC report.Teams of researchers around the world are striving to complete and improve their models.BytHierry luCAS

none of them appeared on the podium at COP21 or

madeany decisions affecting the future ofour planet.And yet without them nothing can be done. We’re

referring to the hundreds of researchers and engineers

throughout the world who are modeling climate change,i.e. converting global climate phenomena into equations.The goal, after lengthy calculations using the world’s mostpowerful computers, is to predict likely temperature andprecipitation changes over the next twenty, fifty, and evenone hundred years.

prediCtinGClimAteCHAnGe–CollABorAtiveWorKThis enormoustask, couplingvast amounts of simulation,

is largely collaborative.Global atmosphere, landmasses(withtheir relief and vegetation), oceans, pack ice, clouds, atmos-pheric dust, CO2 and other greenhouse gases have all beensimulated. Experts are now striving to validate and coupletheir models. “The first atmospheremodels appeared in the1960s and were derived from those developed for weatherforecasting.Simplified ocean models have been aroundsincethe 1970s, but only became 3D from the 1990s onwards,”says Michel Déqué, a researcher at the French NationalCenter for Meteorological Research (Météo France).

ComBininG20-30modelSIncreasingly powerful computers mean that atmosphere

and ocean models can now be coupled. Demand from the

Intergovernmental Panel on Climate Change (IPCC) h

boosted developmentof this technology since it is impossibto calculate CO2-linked global warming without a coupleatmosphere/ocean model. This core climate simulation central to the world’s 20-30 climate models.

TheFrench research communityhas focused on twoglobmodels: one produced by Météo France and another by thInstitut Pierre-Simon-Laplace (IPSL), a federation of nispecialist environmental laboratories. Other major researgroupshave been formed: theNational Center forAtmosphricResearch (Colorado) and theGeophysical Fluid Dynami

Laboratory (Princeton University, NewJersey) in theUSA; tHadleyCentre for Climate Prediction andResearchin theU

and the Max-Planck Institute for Meteorology in German

diSCrepAnCieSBetWeen reSeArCHerS’“meSHeS”There are no fundamental discrepancies between researc

teams’ core models, even though each team has its ow

method of dividing up the atmosphere for calculations. Fexample, each “mesh” in one type of meshing deviseda parallelepiped,100-200 kmlongonboth sidesbutbecomi

thinner as it approaches the earth’s surface. The paramete(temperature, wind speed,etc.) withineach mesh areavera values,which arevariedovertimeto simulateclimatechang

Laboratories are also developing many specific models fglaciers, aerosol impact, changes in vegetation, etc. Themodelshave eithernotyetbeen integrated into climate mode

aGlobaltEstbEd

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17/4817

Sacaas fthHag,whchsckhphs2014.

or have been done so in simplified form. “It’s not necessarily worthwhile integratingeverything since this isn’t thebest useof computing resources or budgets,” says Déqué.

empiriCAl eQuAtionSForSuB-meSH pHenomenAThe regularly observed discrepancies between climate

models –especially during international atmosphericmodelintercomparison projects [see box opposite]– have already

given researchers a lot to do. The cause of this problem hasbeen identified by researchers as “sub-mesh” phenomena,

which play a key role at a sub-mesh (i.e. smaller) scale. Sub-meshphenomenaincluderadiation exchanges, air turbulencein the atmospheric layer near the earth’s surface, the role of clouds and sulfate-containing aerosols, etc.Basing calculationson theoryalone isnotenough. Resear-

chers need to fine-tune their models using empirical equa-tions, which are gradually being improved by the results of measurements andobservations. Clouds in particular, whichcover large areas above oceans, play a key role. “Althoughclouds have a significant impact on global temperature

changes, their role remains poorly understood. Clouds are

responsible for many of the discrepancies between variousclimate models’ results,” says Jean-Yves Grandpeix, aresearcher at the Dynamic Meteorology Laboratory (LMD),a joint research unit on three sites: the École Polytechniquein Palaiseau (Essonne), the École Normale Supérieure, andUniversité Pierre-et-Marie-Curie in Paris.

improvinGdAtA ACCurACy

Climate-modeldiscrepancies led to projectsusingsatellitestomeasurecloudsin2007,the results ofwhichare startingtobe taken into account. As with other sub-mesh phenomena,each research team is fine-tuning its models by moving backand forth between actual results and expected values.

Anotherchallenge forclimatologists is to fine-tune their cal-

culations, i.e. reducemeshsize. Thispresupposessimulationprograms that can use supercomputer power to maximumadvantage by distributing calculations over many parallelprocessors. For this reason, teams of computer scientists(20-30 people at the Institut Pierre-Simon-Laplace) workalongside physicists and now play a key role transforming climate models into effective simulation codes. ❚❚

simulation



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18

“a gfc f cp

e deved zg de

rher h c weher

frecg. We d h g d

grh.”

The quality of weather forecasts depends on how much computing power we have,as Météo France’s deputy director general, Olivier Gupta, explains.INTERVIEWEDBY JULIENBERGOUNHOUX

INTERVIEW

“WEatHERFoRCastinGREliEsComPlEtElY on simulation”

impactonmesh refinementfora territory andonhow sophticated atmospheric calculations can be. The other essentiparameter is algorithms, which vary in their effectiveness solving equationsand incorporatingobservations to initiali

models. A significant amount of computation time is devotto initializing models rather than to actual weather forecating. New data has to be integrated intelligently since it do

not cover the whole grid. We mix old and new data and the weight the two. The skill lies in choosing the right weightinfor the initial state to match reality as closely as possibl

Otherwise, the model will rapidly diverge from reality. Partour research involves fine-tuning these algorithms.

Whoworkon theemodel?The Météo France research center in Toulouse, which employs 300 people, or 10% of our workforce. For models, w

collaborate extensively with international centers, especiathe European Center for Medium-Range Weather Forecas(ECMWF). It is an inter-governmental organization. We’

co-developing an atmosphere model on a global scalARPEGE and the European model IFS are two versionAs a result of this collaboration, we exert a major leverag

effect and obtain excellent results even with a modest-sizteam. We’re theleading organizationin theALADIN conso

tium – which brings together twelve European countriethree North African countries and Turkey – on limited-armodels. This consortium is developing fine-mesh mode

for 24-hour forecasts.

Doyou tacklemore pecific field?

Absolutely. Our team in Grenoble is responsible for snow

pack simulation, to predict the risk of avalanches. Whichanother of ourroles.The team focuses on theatmosphere,

well as themechanicsof snow-layer accumulation, howsnolayers are configured by wind, the probability of creep, etThey’ve developed a specific model for this research. We

also committed to cutting-edge research on urban climamodeling. One of our research units is modeling town-spcific features, which helps local decision-makers assess th

need for green roofs, whitewashed roads, and dampen

WhatwaMétéoFrance’ role at theCOP21?Let’s put our role back into its proper place. The COP 21

was primarily a series of political and strategic negotiations whereas we were involved in its preparatory stages. Météo

France’s researchteams contributedto theIntergovernmentalPanel on Climate Change (IPCC) report, which served as abasis for political negotiations. Weprovidedsimulations for

the fifth IPCC reportthat were carriedout usingtheARPEGE-Climate model. The same modelused forweather forecasting

but set for climate simulation. Weather forecasting andclimate prediction are two aspects of the same science. Wealso initiated various COP 21 side events. In particular, we

werebehind theC3 Challenge hackathon thatran throughout

2015. There was also a scientific conference at UNESCO in Julyand the Climate Trainin collaboration withSNCF, which was the brainchild of one of our engineers. In addition, we

were planning various events for school children but they had to be cancelled for security reasons.

Whatroledoeimulation playin today’ weather forecating?

A central and increasingly important role. Weather fore-casting and climate prediction are both based on simulating

the atmosphere. People often think that weather forecasting is based on statistics. They imagine us making comparisons

with thepast andwith various situations todeducetomorrow’s weather by analogy. This idea, while widespread, is wrong.Weather forecasting has relied completely on simulation for

decades. The quality of forecasts therefore depends on how much computing power we have. This power has a direct


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19

“We’re he edg rgz he

alaDincr – whch brg

geher 16 cre – ed-re

de. thcr devepg

fe-ehde fr 24-hr frec.”

We run the model several times, slightly changing its initial

conditions to study various scenarios. We can now do thisfor the fine-mesh model rather than just the global model.Our contract runs until early 2019 and the supercomputer

willbe upgradedmid-termto approximately 5 petaflops. Thiscomputer is split into two units:thefirst is fortheoperationalsystem whereas the other is for climate simulation research

and for developing the weather forecasting operationalsystem of the future. Models must be tested before they are rolled out. Since it’s essential that we provide a conti-

nuous service, the research half of the computer can switchautomatically to production mode to ensure an operationalservice. Furthermore, the two halves of this configuration

are physically separated (by several kilometers) to guaranteeservice in the event of an accident. This supercomputer iscombined with a regularly upgraded storage system. We

reached 40 petabytes of storage capacity this year, and willachieve a hundred or so petabytes by the end of 2017.

Whydo yourent intead ofbuying?

Since the equipment is replaced every 5-6 years, it doesn’tmake much difference. It’s a formality more than anything.

We switchedto renting about tenyears ago(asdidequivalentorganizations) and only purchase computing power. Thesupercomputer is on our premises and we provide its power

supply and coolants. But we have it on a rental agreement.

What arethemain areaof imulation development

atMétéoFrance?

We have four areas of development for simulating atmos-pheric phenomena. First, we want to take more and more

observations into account. A lot of data now comes fromsatellites, with new instruments. Our first, and very complex,task is to invent new algorithms. We must then initialize

the model intelligently, reconciling observations with resultsfrom the previous model. Data assimilation algorithms area big project and we must choose the most promising tech-

nique. Our third area of development is physics (equationsfor models). Considering the full-scale experiments that are

now possible, we must improve our modeling. One area of research involvesprobing whathappens inside clouds. We’reusing instrumented planes to achieve better understanding

of phenomena such as Cévenol episodes, which is helping us improve our equations. Our fourth area of development isconnected with resolution. The global model’s resolution is

7.5 km whereas the resolution of the fine-mesh model overan extended metropolis (Western Europe and North Africa)

is 1.3 km. Once you go beyond a certain resolution, new problems appear. For example, if slopesbecome toosteep the

grid computing and numerical schemes must be modified.In addition, our code must be better optimized to hardware

architecture. One of our main current research projects is onmodel scalability and adapting models to massively parallelarchitecture. This is a no-degradation, gain factor. For this

research, we’re working with the ECMWF and the European

Center for Research and Advanced Training in ScientificComputation (CERFACS), which is located on our Toulouse

site and in which we are shareholders. ❚❚

ground and road surfaces. Our model can simulate the effectof these actions on the temperature, especially during heat

waves. This is an increasingly important territorial issue inthefight against globalwarming. Some of ourresearchers are working on air quality. Others are simulating land surfaces

since transfers, humidity, vegetation, andsoil sealing allneedto be modeled.We’re also simulating theupper ocean(waves

and swell), running back-trajectories to calculate flotsam and jetsam and pollutant (hydrocarbon) drift. These are all jointresearch units attached to both Météo France andtheFrenchNational Center for Scientific Research (CNRS), which also

ensures we have close ties with academia.

Whattechnicalreourcedo youue?

The supercomputer we’ve been renting from Bull since2014 is in Toulouse; its peak power is one petaflop. One

of our tasks is to purchase computing power suited to ourrequirements, the models we use and their frequency at thebest possible price. This power allows us to produce imme-

diate predictive models covering a few hours and focusedon France. We also provide overall fine mesh forecasting.

L’UsINENOUVELLE i n°3464 suPPLEmEnt i aPriL14 2016


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simulation

ThAicitypojct –dvlopd yAiaTchnologi – ta thinflunc of uilding intoaccountwhn aing

howcity aipollutioni dipd ywind.

A r i A

T e c h n o l o g i e s

mArkeTs

smes, natuRalelement eXPeRts

Climate change and the deployment of new energsources have given simulation a real boost. Offshoand even nuclear entrepreneurs and engineers havseized on environmental modelling. Some of the start-uand SMEs launched by these experts have made a re

name for themselves on this new market. Here are eleve

of these outstanding companies, which are highly rated bthe sector’s experts.

ArIATeCHNOLOGIes Is ANALYZINGPOLLUTANTDIsPersION

Aria Technologies was set u

in 1990. The company prduces a numericalsimulatisoftware suite andcarries o

studies on air pollutant dipersion, climate analysis, anrenewable energy source

Tools intended for industri

lists – in cities suchasRomRio de Janeiro, Peking – and researchers. Some 65%

studies carried out by Aria Technologies are exports. Thcompany’s climate change business is currently expandinrapidly. This work covers storm frequency calculations, thimpact of rising temperatures on urban pollution, and cidwellers’ energy consumption in fifty years’ time.KeYClients t, Cea,R, sz

NUmTeCH Is PreDICTINGAIrPOLLUTIONNumtech is located on LPardieu Technology Pa(in Aubières, near ClermonFerrand) and specializes

weat her fo re ca st ing ansimulating pollutant dispesion into the atmosphere.T

company’soperational systems feed data 24/7 into airmontoring stations run by associations such as AirPARIF an

AirPACA. Numtech opened its first subsidiary in Moroca year ago. Pierre Béal – the company’s founder – is allooking into providing pollution forecasts in very fine scalThis service, called NOA, is at the preparation stage ancould give two-hourly city pollution forecasts, accurate

within a few meters. Ideal for planning your run!KeY Clients eDF, sz evr, t, arv, Cfr,arprf

spcialization Atmosphericsimulation

Dattup 1990

Location Boulogne-Billancourt(Hauts-de-Seine), RiodeJaneiro(Brazil),Milan(Italy)

Wofoc 45 people

T/O (2014) 4million Euros

Several outstanding French companies are atthe cutting edge of environmental simulation, whether of air and land phenomena, pollution,or renewable energy sources.bYALAINCLAPAUD

20

spcialization Atmospheric eventmodellingand simulation

Dattup April2000

Location Aubière(Puy-de-Dôme)

Wofoc 20 people

T/O (2014) 1.3millionEuros


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22

meTeODYN Is CALCULATINGreNeWAbLeeNerGY sOUrCes

Meteodyn was set up by Didier Delaunay – a CSTB(French Scientific and Tech-nical Center forBuildings) re-

searcher – andhaspositioneditself on the market for windand climatology numerical

simulationusingitsown sol- vers.The company produces andmarkets a rangeof calcula-

tion softwareandcarries outstudies forwind-farmoperatorsinEurope, China,andIndia.Meteodynnowemploys aroundfifteen people abroad. It also carries out calculations for theconstruction business, simulating building ventilation andhelping architects constructpassive buildings. Thecompany has diversified into solar energy and has carried out severalsolar-farm feasibility studies, especially for China.KeY Clients eDF, ibrdr, e, Gr ecrc,Jyf mdyWd ergyCpy (Ch)

GeOmOD Is PreDICTINGPreCIPITATION ImPACTGeomod’shydrology business

involves assessing the im-pact of precipitation on city wastewater systems. Suez,

Veolia, Lyonnaise des Eaux,and the Greater Paris Sanita-tion Authority (SIAAP) alluse

Geomod’s calculation codes.But this is notthe only string to Philippe Bischoff’s bow. HehasalsopositionedGeomodonmore «land-based» calcula-

tions. For example, noise maps for urban agglomerations of

spcialization Hydrologyandelectromagneticwave pollution

Dattup October1995

Location Lyon (Rhône),Brest(Finistère)

Wofoc 12 people


more than 250,000 inhabitants, and electromagnetic wapropagation maps. Geomod is collaborating with the CSTto develop its Mithra software suite.KeY Clients sz, V, ly d ex,siaaP,

Byg trvx Pbc

INNOseA IsOPTImIZINGmArINeeNerGY sOUrCesInnosea – a spin-off from tÉcole Centrale de Nantes –an engineering company sp

cializing in renewablemarienergy (RME). Its businecoversallaspectsofRMEus

As such, Innosea has carrieout calculations for EDF

offshore wind-farm foundations in Courseulles-sur-M(Calvados) and Saint-Nazaire (Loire-Atlantique). Innoseaengineersareworkingonthenext generation of floatingwin

turbines, and on tidal energy and wave energy convertersKeY Clients eDF, eBW

DATAPOLe Is PreDICTINGWAsTeVOLUmesIf ocean currents and vall

winds can be modelled, wnothumanbehavior too? Thprinciple has inspired Datpole, a start-up establishe

byFrédéricGagnaire in201The company’s initial id was to provide local auth

rities with a tool for forecasting waste volumes generat

by their citizens, thus enabling them to optimize resourcallocated to waste collection. Datapole’s predictive modeare based on collection data, weather forecasts, and shoretail data. Datapole has since developed its initial offer produce an electricity consumptiontool (PrediWatt), andw

shortly be adding a building management tool.KeY Clients eg,PC ggr cy,Chvr Vy pbcwhry

NeXTFLOWsOFTWAre Is DesIGNINGFLOWsANDWAVes

Nextflow Software is a spioff from HydrOcean, a spcialist hydrodynamics fir

boughtoutbyBureauVeritin September2015.Nextflo

has taken over HydrOceansoftware vendor businesA dozen people have join

thisstart-up, including Erwan Jacquin,HydrOcean’s found

Nextflow’s current business should ensure a 1-2 millionEuro turnover, and the company will continue workin

with the École Centrale de Nantes to codevelop simulatiomodels.Nextflow hasparticularexpertise in simulatingwaeffects,which is invaluable fordesigning shiphulls,offshoplatforms, and for building offshore wind farms.KeY Clients R, mch, arbHcpr

spcialization Fluidmechanicssimulationsoftware

Dattup June2015

Location Nantes(Loire-Atlantique)

Wofoc 10people

T/O Not applicable

spcialization Simulation ofrenewablemarine energy sources

Dattup 2012


Wofoc 21people

T/O (2014) 732,000Euros

spcialization Forward-lookingresourcemanagementsoftware

Dattup May2010

Location Paris– LaPlaineSaint-Denis(Seine-Saint-Denis)

Wofoc 11 people

T/O(2015) 410,000Euros

mtodyn’windantonawindfa.

M e T e o d y n

spcialization Simulation ofrenewableenergy sources

Dattup 2003


Wofoc 50 people



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simulation

OPTIFLUIDes IsmODeLING FLUIDDIsPersIONOptiFluides is located on LaDoua science campus in Vil-leurbanne (Rhône) and has

developedprocess simulationand modelling expertise. Toachieve this, the start-up’s

founderNicolasBoissonusedsimulation codes produced by the software vendor Fluent.OptiFluide’s calculations simulate flows in industrialplants,

thus enabling petrochemical companies to optimize theirprocesses. OptiFluide also models air pollutant dispersionas part of risk assessments for industrial sites.KeY Clients t, eDF, Br sc, svy

OPeNOCeANFOrWeb-bAseDOCeANANALYsIs Jérôme Cuny and RenaudLaborbe set up Open Ocean

in 2011 to put their oceansimulation knowledge online.Although simulation codes

are very complex and gene-rate large volumes of data,Open Ocean gives access to

calculation results viaa simpleweb interface. Thecompany’sMetoceanAnalyticsplatform is the fruit of three years’work.This platform is for industrialists developing projects in thetidal energy, offshore wind turbine, and offshore oil sectors.OpenOcean’s clients include EngieandSabella.OpenOcean

raised 1.6 million Euros in 2015 and intends to increaseits workforce from 11 to 16 people by the end of this year.

KeY Clients eg,sb

AmPLIsIm FOrAIr-QUALITY sImULATION“AsA serVICe”

AmpliSIMwas set up inPar

in 2015 by Sylvie Perdri– a former Aria Technolgies’ employee – and OliviOldrini, the founder of th

consultancy firmMokili. AmpliSIM offers an air-quali

simulation service for desigand engineering offices. This cloud-based service assesstheimpactof industrial-plantandroad-traffic pollutant emsions on surroundingneighborhoods.AmpliSIM’s founde

use open-source simulation codes recommended by the UEnvironmental Protection Agency, and free software (OpeFoam and EDF R&D department’s Code_Saturne softwarAmpliSIM is currently negotiating with Qarnot Computinand Bull to increase its computing power.KeY PaRtneRs B, eDF

eDFsTOre& FOreCAsT Is COUPLINGWeATHerFOreCAsTs ANDreNeWAbLeeNerGY

EDF SFisa spin-offfromEDlaunchedby three researche

at EDF’s R&D departmenTheywantedtoset upa company to market the fruit

their research. Their Pegasoftware (an EMS – energmanagement system) us

energy consumption and meteorological data for precimanagement of battery charging/discharging processcoupled to wind farms and photovoltaic panels. This soltion is suitable for islands since batteries compensate fintermittent energy resources. Following a pilot project La Réunion, EDF Énergies Nouvelles’s photovoltaic powstation inFrenchGuianawas the first facility tobenefit froPegase’s calculations.KeYClients eDF Érg nv, Écrcéd my,erc

spcialization Simulation ofliquid,gas, andmultiphase flows

Dattup June2011

Location Villeurbanne (Rhône)Wofoc 5 people

T/O (2015) 400,000Euros

spcialization Energymanagementsoftware

Dattup March2014

Location IncubateurAgoranov(Paris)

Wofoc 10people

T/O (2014) 474,000Euros

spcialization Online solutionsfor ocean/weather analysis

Dattup 2011

Location Paris andBrest(Finistère)

Wofoc 11 people

T/O (2014) 96,500Euros

24

OpnOcan’onlindciion-aingtoolcanodlocancunt, wind,andwav. o p

e n o c e A n ; A M p l i s i M

AplisIm i aingth ipact of pollutanton aiquality inuanand indutial nvionnt.

spcialization Air-qualitysimulation

Dattup March2015

Location Paris

Wofoc 2people

T/O Not applicable


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© Copyright 2016 COMSOL. COMSOL, COMSOL Multiphysics, Capture the Concept, COMSOL Desktop, COMSOL Server, LiveLink, and Simulation for Everyone are either registered tradema

trademarks of COMSOL AB. All other trademarks are the property of their respective owners, and COMSOL AB and its subsidiaries and products are not aliated with, endorsed by, sponsored bsupported by those trademark owners. For a list of such trademark owners, see www.comsol.com/trademarks

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Agriculture needs to produce bigger, higher quality yields while also reducing its pollution. CybeleTechhas taken up this challenge by incorporatingfarmland data into plant-growth simulation.byJean-FrançoisPrevéraud

a reaL sTar

CYBElEtECH,numERiCalFaRminG

Mllgcpgwthptmzthfftlz,wtttmttmpl.

What do you get if you take an agronomist, a nume-rical simulation researcher,a student engineermad

about IT developments, an agri-food marketing expert and bring them together under a name evoking thePhrygian goddess of nature and abundance? CybeleTech, of course – a French start-up established at the end of 2011to model plant growth. “As is often the case, CybeleTech’sstory is first and foremost about human encounters rather

than technology,” explains Marie-Joseph Lambert, NovartisAgro’s former director of business forecasting. Together with the mathematician Christian Saguez, his PhD stu-dent Paul-Henry Cournède, and two other members of theDigiplante team (Professor Véronique Letort – Cournède’s

deputy – and Benoit Bayol), Lambert is one of CybeleTech’sfive cofounders.

Ml b rl-Tm MmtSaguez metPhilippedeReffye – the agronomist in this story

(who is not one of CybeleTech’s cofounders) – in the early 2000s. Together they developed a model to simulate plantgrowth and architecture, for use in agronomy and imaging.In 2003, they set up the Digiplante joint research unit at

the École Centrale de Paris. Under Cournède’s leadership,this research team developed a plant-growth model usedin an online tourist application produced by Île-de-Franceregional council: 3D simulation of the gardens at the Palaceof Versailles.

This application appealed to Lambert, who was looking

for a plant-growth model to synthesize and exploit his owndata. “I thought, if these guys can produce this, I need tomeet them,” he recounts. Several projects were launched to validate the feasibilityof this approach and test its relevance.Following successfulresults, Saguez, Cournède andLambertset up CybeleTech at the end of 2011. The company’s firstorders came from a satellite operator that wantedto develop

its image-based service offer, and a seed company that hastarted using modelling for genotype selection.

CybeleTech’s expertise enabled Digiplante’s mechanistplant-growth models to be combined with satellite imagshowing plantbiomasspotentialat anypointona givenpie

of land. According to theweatherconditions forecast, farmecan now calculate the correct fertilizer and phytosanitatreatment needed to achieve set added-value targets whialso causing as little pollution as possible.

Tw Plt PLMThis solution means farmers can base their decisions o

real-time crop measurements rather than on extrapolationfrom previous years’ experience. It is now possible to accurtely predict disease onset according to a plant’s actual stagof development. Consequently, farmers can give plants moprotectionwhilealso intervening less often. In theshort termthis approach will meet the challenges facing agriculture:


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director of industrial relationsandsubsidiaries at the FrenchNational Center for SpaceStudies (CNES).At the sametime,hewasalsoaprofessorat theÉcole Centrale de Paris,wherehesetuptheMathematicsApplied toSystems(MAS) Laboratory. Hewas president of the TER@TECAssociation (EuropeanCompetence Center for High-PerformanceNumericalSimulation) until 2009. He is amemberoftheFrenchAcademy

of Technology’s Communicationand IT TechnologyCommission,aswellaspresidentoftheScilabConsortium.

Paul-HEnRYCouRnèdE,sctfca – Cf

Paul-HenryCournèdegraduatedfromtheÉcoleCentrale deParis(1997)and Cambridge

University,andhasaPhDinapplied mathematics (2001).HeisdirectoroftheCentraleSupélec’s Digiplanteteam, working on mathematicalmodelingofplantgrowthintheMAS laboratory.

27

tHREEKEYPlaYERs

maRiE-JosEPHlamBERt,dct – Cf

Marie-JosephLamberttrainedinsalesand marketingbefore pursuinghis careerin various

industrial groups. He becameNovartis Agro’s directorofcommercial policy anddistribution marketing in 1997,and itsdirector of businessforecasting in 2000. After the

company merged with Zeneca,he was key accountmanagerEuropefrom2001to2005,before joiningCybeleTech asits director.

CHRistiansaGuEz,Ceo–Cf

ChristianSaguezgraduated fromthe ÉcoleCentrale deParisin 1972,andwas

director of international andindustrial relations at the FrenchNational Institute for Researchin ComputerScience andAutomation (INRIA).Hesubsequently founded andwasCEO of Simulog, and was also

increase production 1.5-fold while also reducing inputs by 30-40% and improving the sanitary quality of products.

“The next stage of this technology will enable farmers toselect plant varieties for sowing and draw up a completeprotocol for growing them on a given piece of land, varying this protocol according to the qualities expected in the end

product. It will be a sort of ‘plant PLM’ [ed. note: productlifecycle management], connecting every step of the process

from start to finish,” explains Lambert. CybeleTech currently carries outa dozenadhocstudiesa year forindustrialists,butits short-term plan is to provide online services for farmers.This will provide farmers – via their cooperatives – with

the seed and inputs they need to maximize yield on eachpiece of land. CybeleTech is currently working on arable

crops (cereals, oilseeds), market-garden produce (tomatoes,strawberries), and perennial crops (vines). The company plans to expand into forestry (developing the value of forestresources, adapting to climate change), andtropical products(coffee, cocoa beans, cotton, bananas). For Lambert, thismeans CybeleTech could generate turnover of 5-10 millionEuros over the next five years. ❚❚

L’usine nouveLLe I N°3464SUPPLEMENT I APRIL142016


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Challenges in agricultural modeling – simulating wheat growth, optimizing inputs, predicting milk production, etc. – have spurred on start-ups and yielded a bumper crop of innovations.byADRIENCAHUZAC

DIGITAL TRANSFORMATION

tHE nEW

aGRiCultuRalREVolution

Airinodronescalculatethe nitrogen requirementsof wheat andrapeseed.

Jean-Hilaire Renaudat farms 1,200 hectares north

Châteauroux (Indre) and belongs to a new generatioof farmers at the cutting edge of digital technology.

a few days’ time, he will be applying nitrogen fertilizer

his soft wheat, barley, and rapeseed crops. What’s speciabout this is that the amountof fertilizerRenaudat appliesentirely adjusted todata collectedby sensors onhisfield cr

sprayer.TheN-Sensor software developedby theNorwegigroupYarameasurescrops’ light reflectance to calculate thbiomassandnitrogenrequirements. TheGermanagricultur

giantBayeruses the samemethod to adjust fungicide leve

as does a combine harvester-mounted software prograthat calculates yields in real time while they are harveste

Renaudat sees many advantages in using these new tool

“We made a return on our investment within four yearWe’vecutdown onnitrogen fertilizer,have less crop diseas

andproducehigher,more protein-richyields,” he says, cleadelighted. Renaudat also uses his smartphone to calcula

the nitrogen requirements of his rapeseed.As in industry, digital tools mean farmers can now ke

track of running their business. Above all, these tools hefarmers anticipate, increase yields, and predict the quanti

and quality of harvests even before production is over. Th

radical shake up has been dubbed the “third agriculturrevolution” in some quarters, following the first revolutio

that turned agriculture into a commercial business and thsecond that mechanized it and introduced chemical fertilzers to increase yields. The past few years have witnesse

an abundance of decision-making andsimulationsolutionadjustedirrigation, crop-disease forecasting, yield simulatiomilking robotsondairy farms,calving prediction, automat

cowshed cleaning, etc. “One of the main challenges is improve eco-friendly crop management by limiting the uof agricultural inputs,” says Jacques Mathieu, director Arvalis Plant Institute.

RequirementsCalculated toWithina SquareMeterArvalis and Airbus Defence& Space developedFarmstar

2003; it was one of the first systems to make crop-managment recommendations based on satellite photos. Althou

Farmstar has always been very popular with farmers, oth

systems have gradually caught up. Drones are now usefor precision farming, and France seems far ahead of othEuropean countries on this technology. Airinov is a start-uthat was established in a barn in Poitou-Charentes by tw

engineers and a farmer’s son back in 2010. Within a fe years, the company has become the French number one oagridrone-based recommendations for nitrogen fertilizatio

Airinov has developed quad-band sensors that can, fexample,work outrapeseedweightandcalculatechlorophlevels in wheat using green and infra-red light wavelength

emitted by the plants. Airnov then calculates how mucnitrogen is required for each square meter of a land parce

“Our technology is the most advanced in Europe. Aftfive years of trial and error, we found our business modthanks to a partnershipwiththeFrench dronemanufactur

Parrot, which invested capital with us,” explains RomaFaroux, Airinov’s cofounder. Airinov’s technology offe


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“Our start-upsmustmoe into the industrial phase”

maRinE PouYat,Director of theRenaissance

Numérique think tank andheadof

thelegal department at theFrench

Federationof E-commerceand

DistanceSelling(FEVAD).

Whdid ousend thegoernment

anofficial report on agriculture and

digital technolog lastNoemer?

Agriculture is facing many challenges. It must feed theplanet, be eco-f riendly , make its

profession more attractive, as well as reconnect withconsumers and win back their

trust. We’ve made sixteenproposals to rethink agricultural

production, distribution and

consumption in the digital era.

Whatare theseproposals?

We want farmers to receivetraining and support topurchase precision digital tools,

especially tools reconciling yieldtargets with sustainabledevelopment. We also suggest

setting up regional open dataexperimental programs in somebranches of agriculture. This

will bring production costs andretail prices back into balance.What’s more, we believe that

cooperatives – which haveaccess to agricultural and

market data – should be at theforefront of agricultural big data

strategies to defend farmers’interests.

HasFranceadequatel got the

measureof thisnewagricultural

reolution?

France has a large pool of start-ups, which must now move their solutions into a

more industrial phase. Frenchpublic and private stakeholders

should seize on this officialreport now or else it will be toolate. We’re facing internationalcompetition from very powerful

groups. ❚❚

We equip,you compute

Genci (Grand équipement national de calcul intensif)makes available powerful HPC resources to French scientific

communities and also to industrials wishing to conduct researchin link with an academic PI, in all fields.

Climate changes

Propagation of major firesReducing pollutant

emissionswww.genci.fr

Prevention of seismic damages

L’USINENOUvELLE i n° 3464supplement i apRil14 2016


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many benefits. “Although satellite images are expensive,they’re worthwhile if you can recover the cost on large landparcels or areas. Drones can be used for more occasional

missions, even though they’re still expensive to access [Ed.note: 25,000 Euros for Airinov’s solution],” says Véronique

Bellon-Maurel, director of the ecotechnology departmentat the French National Research Institute of Science andTechnology for the Environment and Agriculture (IRSTEA).

Since 2014, several chambers of agriculture in the Grand-Ouest region of France have been offering decision-making

services based on drone images. “Drones fly over area very quickly and precisely. Weather conditions sometimmake it harder to use satellites, although drones can’t fly

strongwind,” saysNassimHamiti, anagricultural equipmeproject leader at the Permanent Assembly of Chambers

Agriculture (APCA). Another constraint is that, for the timbeing, drone-based services are limited to nitrogen-inp

recommendations for rapeseed and soft wheat, althoug

Airinov is extending this to other crops.Many other French start-ups like Airinov have appeared

the field of agricultural digital technology. After tough ear years, some of them are consolidating and have moved in

a more industrial phase. One example is Naïo, a Toulousbased start-up established in 2010. Naïo developed the O

robot formechanicalweedingofmarket-garden crops on laparcels covering less than ten hectares. “Oz features eleveinfra-red sensors on its front and sides, together with fo

electric-motor driven wheels. These wheels are powered blead batteries giving Oz four hours of autonomy,” explaiGaëtan Séverac, Naio’s cofounder. Although Naïo has on

soldabout thirty of itsOzrobots–whichsell for 21,000Eur

“or chege pre

h d hrd pre.

se f he, kethe,

cd e e pgrwh.”

Frç Her, rof hFrh noi foragrrRrh (inRa)

Aralismodels theresistanceof plants towater shortageusingsensor dataand cameras(RGb imagesof photosnthesis).

p a s c a l G u i t t e t


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each – the company has just developed Oz’s big brother: ahigh-clearance robot called Anatis. This robot was designedin collaboration with the French manufacturer Carré and is

for weeding land parcels bigger than ten hectares. But that’snot all it does since Anatis features 3D cameras and many sensors to collect data on humidity, soil temperature, weed

infestation, density, and plant development stage.Digital technology is also radically changing agricultural

research, leading technology institutes to adapt their researchprograms. Two of Arvalis Plant Institute’s experimentalfarms are currently specialist “digital farms”. The first – inBoigneville (Essonne) – specializes in arable crops,while the

second – in Saint-Hilaire-en-Woëvre (Meuse) – specializes

in mixed farming and cattle rearing (beef production). By the end of 2016, both farms will have implemented digital

productionmanagement, combining existing techniqueswithtest tools and prototypes from external companies.

A Phenotping Experimental StationFundamental research is also adopting digital tools to

improve its efficiency. Since 2013, the French NationalInstitute forAgricultural Research (INRA) hasbeenworking

to f fro ghoogy, w gor ggo hg. thagro edi erooo– wy yrgo y grrorgzoo rov ry xhg whyoryr r – rzg ro-g. “th w ggho oro yh of h

fr hf of 2016 w y rr o ro oror.coorv hr ofgrr w o hg

rory,” ybro pré, ceO of agroedi ero. th oooworkg whh uoFrç sr(uFs, Frh r oofor o rr)o roo, horyoro rz or og oror. “th wfFrh r,

kg hor rov v,” y pré,who ho h Frh yw ro o ero. ❚❚

StandardizedComputerLanguage

with Arvalis on a national high-throughput cereal phenot

ping program called Phénome. One of the main platformfor this 24-million Euro project jointly funded by the Fren“Investment for the Future” initiative is in the commune

Ouzouer-le-Marché, deep in Le Loir-et-Cher. This site height large, mobile greenhouses in the middle of a fielSensors measure rainfall, soil humidity, wind, etc. At thfar end of the land parcel is an imposing boom on a ramounted gantry. This boom – fitted with many sensors ancameras – takesphotos toanalyze plants’ phenotype(i.e. th

physical characteristics) and chlorophyll content. “The gois to create controlled water stress in plants and stop rafalling on the plot,” explains Yann Flodrops, director of th

experimentalstation.Thispioneering Europeanprogramwhelpscientists select varieties consuming less inputs (watnitrogen, and pesticides) and identify phenotype genes.

Orléans – Plant Digitalvalle

The adventof thousands or evenmillions piecesof agricutural data from fields and research programs presupposhigh-securitydata storage facilities.The INRA hasbuilt twdata centers – oneinToulouse(Haute-Garonne) in2014 an

another in Bruyères-le-Châtel (Essonne) in October 201– which each cost four million Euros. “The challenge is

promote this data to third parties such as Thales, whicuse it to simulate plant growth,” says François Houlliepresident of INRA.

Although entering the digital era is a major change fagriculture, digital projects and initiatives remain scattereFacedwith globalforeign giantsat thecuttingedge of agricutural digital technology – such as John Deere and Monsan

– French projects urgently need to pool their efforts. Som joint initiatives are starting to emerge: for example, ththree-year Smart Agriculture System project launched 2014. This project brings together the Végépolys, CéréalVallée, DREAMEau&Milieux competitivenessclustersanprivate groups suchasLimagrain. Its purpose is todesign

innovative wheat modeling, yield forecasting, and decisiomaking system.

“Seed companies will be able to market their seeds faste

Farmers will be able to discover constraints more quickpredict water requirements, and increase production. Th

will give a real competitive advantage,” says an enthusiastChristian Saguez, CEO of the start-up CybeleTech, one the project’s partners. Alongside this project, a plant digit

valley – Agreen Tech Valley – is to be established in Orléaand its suburbs (Loiret) in 2017. This initiative is expecteto bring together several agricultural companies – such

Axéréal, Kuhn and Sofiprotéol – as well as the University Orléans. “France has all the skills it needs to hold a stronposition in the internati

Special simumlation issue : S.O.S Planet

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