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Cern.ch/knowledgetransfer. Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas KT in CERN Two software cases N.Ziogas, KT.

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Presentation on theme: "Cern.ch/knowledgetransfer. Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas KT in CERN Two software cases N.Ziogas, KT."— Presentation transcript:

1 cern.ch/knowledgetransfer

2 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas KT in practice @ CERN Two software cases N.Ziogas, KT group

3 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas FLUKA A fully integrated particle physics MonteCarlo simulation package FLUKA - FLUktuierende KAskade A fully integrated particle physics MonteCarlo simulation package 40 years history & evolution  First generation (the CERN SPS Project, 1962-1978) J.Ranft – Shielding applications  Second generation (development of new hadron generators, 1978-1988) SPS. Rewrite – multi material calculations in different geometries  Third generation (the modern multiparticle/multipurpose code, 1989 to present)  IP jointly owned by CERN and INFN (50-50)  Strong development team at CERN ions Fluka is a general purpose tool for calculations of particle transport and interactions with matter.

4 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas FLUKA- high dissemination potential Strong points  High accuracy simulation of the interaction and propagation in matter of about 60 different particles, in wide energy ranges, including neutrons down to thermal energies and heavy ions.  High level of reliability. Provides predictability where no experimental data are directly available.  Friendly user interface- no programming  Incorporates a 3D visualisation tool  Very active community/site/mailing list. Applications: From proton and electron accelerator shielding to target design, calorimetry, activation, dosimetry, detector design, Accelerator Driven Systems, cosmic rays, neutrino physics and medical applications like radiotherapy, medical hw design etc.

5 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas Uses of FLUKA- Current licences  A very large number of academic licences  Non academic licences. Companies using FLUKA in:  Nuclear waste management, in Italy  Medical hardware design, in China  Commercial fusion research (UK)  Hadron therapy centre design studies (shielding, etc) - China  Hadron therapy treatment planning systems  Requests from start-ups  The calculation of a human body energy deposition map  Unique fingerprinting diamonds  Consultancy services

6 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas The FLUKA commercial licence  Agreed on a ‘standard clause licence’ – CERN & INFN (FCC).  Principle of reciprocity with INFN.  Proprietary CERN-INFN licence – KT.  Object code  Cannot create derivative works  Control over the Physics models- no benchmark comparisons of the models outside the purpose  Tight control over scientific publications  Different conditions if FLUKA output is directly used  FLAIR-FLUKA UI distributed under the same conditions –CERN developed  One site, specific purpose

7 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas Commercial licence for hadron therapy  One of the few 12 C TPS providers. Also provide proton TPS  Company uses FLUKA Output in its flagship TPS product  What they want?  Maximum freedom  Minimum price  No strings attached  Research use  Stability  What we want?  Dissemination  Part of the success  Acknowledgement  See main licence points  Compliance  No warranties

8 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas The negotiation – The agreement  Non exclusive. Object code  Wide but limited use  For commercial purposes – 12 C ion TPS  For research purposes –  Lump sum & royalties  Progressive royalties starting low  Maintenance fee – yearly  Yearly reports  CERN/INFN acknowledgement  PR and use of CERN Tech logo  FLUKA must be sited where it matters  Strict scientific publication control  No benchmarking  3 years, automatically renewable annually

9 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas The agreement – Questions raised  IP valuation  The cost ?  The market ?  How important is it for their business ?  How you place/manage your ‘product’ ?  How far can / should one go given CERN status and MS ?  Compliance  Our part – Tools to enforce it  Legal tools – In practice  Community & Reputation  Dissemination vs reputation and upholding the value – solutions ?

10 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas C 2 MON C 2 MON Framework for building highly available, large industrial monitoring and control systems  3 tier architecture, Data acquisition, server & web interface  Designed for high availability  Allows for short development cycles  Scalable system at all layers  Easy to customise  Modular Java based framework  Able to handle high throughput and millions of different sensors  Powerful rule based filtering resulting to meaningful alerts  IP owned by CERN ions It is based on 10 years of CERN’s experience with the Technical Infrastructure Monitoring systems.

11 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas C 2 MON Applications Applications outside CERN  Any large scale industrial installations with complex multi vendor monitoring hardware  Any industrial SCADA (Supervisory Control And Data Acquisition) system application. Ex. Infrastructure or Facility management  As SCADA middleware with dedicated/bespoke clients Applications at CERN  TIM Service: 24/7 supervision and control of CERN infrastructure spread around the site. ~93'000 data tags, ~40'000 alarms, ~ 1'000 rules. 400 m raw data tags  DIAMON. Monitors the BE controls infrastructure. First line diagnostics and aid to plan first line interventions. Used by the CCC Operators.

12 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas C 2 MON Licensing – KT Support  Components (25-33-58) and OS licences (13)  Contributors  Do we really have to do this?  Due diligence report – Recommendation LGPL v.3  First step – Due Diligence Yes No Potential licence incompatibility Uncertainly in licencing model Uncertainty in the dissemination path EASY All licensing options open All dissemination paths available DIFFICULT Potential licence incompatibility Uncertainly in licencing model Uncertainty in the dissemination path Potential diverging opinions Potential All licensing options open All dissemination paths available Potential diverging opinions Yes No External non CERN contributors involved in the development External code components used

13 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas Licensing considerations – KT Support  Due Diligence  Dissemination path  Use as middleware  Spin-off product development  Consultancy services  Developer team aspirations  ‘Customer’ interest

14 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas Licensing considerations – KT Support Open Source Licence  Not a ‘religious’ issue  Platform technology – Advantage form external contributions  Investment in building and managing an OS community around a project  Relinquish control  Specific rules to follow, © notices etc  Where do I publish?  Who are my users ? – tracking  Acknowledgement - CERN’s return to society in the form of free software

15 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas Good practice from the start  Early decision concerning dissemination outside CERN  Know my team  Know & track my components  Talk to us!

16 Knowledge Transfer | Accelerating Innovation CERN KT Training N.ZiogasPromotion  The KT Fund  Market research  Events, KT network, forums &technology presentations  The BICs and potential start ups  Requests from companies & collaborative development

17 Knowledge Transfer | Accelerating Innovation CERN KT Training N.Ziogas To conclude  Addressed some questions related to software dissemination and specifically with licensing  Overview KT implication and how it can relate your work  Clarified the KT process, highlighted common steps even though each case is unique


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