RENESENG - kick-off meeting - Athens, Greece November 28/29 th, 2013 Franjo Cecelja.

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Presentation transcript:

RENESENG - kick-off meeting - Athens, Greece November 28/29 th, 2013 Franjo Cecelja

The University of Surrey (UoS)  An international university known for its focus in excellence in both teaching and research: >9000 students, ~4000 staff  Located in Guildford, Surrey, UK  Number 8 in overall UK ranking  The UK, the number one university in the UK for graduate employment.  Strong industrial links  European institution with the highest number (>120) EU projects  Owns and runs the Surrey Research Park, a major centre of research in the UK which provides facilities for 125 companies  According to the Research Assessment Exercise (RAE) carried out in 2008, 88% of the UoS’s research activity was rated as “world- class”.

PRISE Process & Information Systems Engineering Chem. Eng. natural home Ontologies, intelligent systems, semantic web, general IT support Modelling, optimisation, synthesis, integration Staff: 3 academics (+ 1), 3 RAs, 7 PhD students

Work/Projects Biofuel potential in Northern Italy, Thailand, UK Assessment of new technologies; ultrasound supported separation of sugars/lignin from cellulosic biomass Knowledge support to processes (intelligent systems, data integration, model integration) Waste management and processing: eSymbiosis Life+ project General optimisation: stochastic optimisation supported by knowledge models LCA and environmental effects/consequences assessment

IS Domain Ontology (tacit) * Trokanas, N., T. Raafat, F. Cecelja, A. Kokosis, and A. Yang, Semantic Formalism for Waste and Processing Technology Classifications Using Ontology Models. Computer-Aided Chem. Eng., : p

Knowledge-based model s i,k ’ Simplification W1W1 W2W2 W3W3 WcWc Knowledge-based optimization Simplified s i,k ’ ONTOLOGY (simplification and optimization) Optimization Server Production rules … … P1P1 P2P2 PwPw Distribution Centre for Process & Information Systems Engineering

WP Responsibility WP1.2: Physical property modelling for feedstocks, intermediates, bio- derived products WP1.4: Open modelling environment and multi-scale integration WP4.3: LCA for supply chain optimization and network analysis WP6.1: Knowledge engineering models and communication hubs WP8:Creation of a new multicenter PhD and post-doc program Define the curricula Industrial placement Administration Dissemination and integration with existing master programmes ESR: Open-oriented knowledge based platform to integrate conventional and non-conventional models and tools, processing scales and physical properties of bio-renewables ER:Production of prototypes of knowledge models, platform of high- throughput screening of process technologies, biorefineries workbooks and data/information visualization.

WP1.2 Physical (???) property modelling for feedstocks, intermediates, bio-derived products: Biomass, intermediates, product classification and characterisation for: Pre-treatment Process Property identification and variability (compositional, seasonal, geographical) Property modelling – effects on concomitant processes, data integration Effect analysis

Biomass Classification/Characterisation

Focus on process requirements:

WP1.4 Open modelling environment and multi-scale integration: Data integration Model integration: per scales (vertical) and per functionality (horizontal)

WP8 WP8:Creation of a new multicenter PhD and post-doc program To provide a new, multidisciplinary generation of experts in biorefining University/industry partnership To benefit from the project and some existing (EngD) experience EngD programme: 4 year programme Joint academic/industrial supervision Taught/research/practical parts involved 50/50 (government/industry) financial support Identified problems Wide range of expertise and specific needs to be covered No overarching financial support available Differences in (national) expectations and educational procedures (in Europe)

WP8 8.1 Defining the curricula 8.2 Industrial placement 8.3 Administration 8.4 Integration with existing master programmes

Proposal To be formalised in documents and practice

Curricula Taught part: Credit system: EU credit system (60 or 120 credits), compulsory/optional ratio (20/60 – 40/80) Module organisation: per area (process design, process economic, process systems …)/all the same Module list: mainly MSc modules from participating universities, purpose defined modules Timing: 1 year, 2 years, all across the programme, modules offered once/twice a year, thin/thick mode Assessment: by attendance/by formal assessment Industrial training: full/credit system Research part: Length: 3 / 4 years (PhD/EngD) Supervision: selection per quality/incentive/location Supervision responsibility: shared with industry/university Location: university/company/mixed

Curricula Industrial training: Inclusion: compulsory/optional Quality: responsibility/supervision quality assurance, part/full time Length: module system, 1 year, all Location: single/multi -company

Organisation Responsibility: Academic: Centralised (for all students)/individual (supervising) institution Well being: academic/industry Financial: centre/academic/industry Admin support: Mode: centralised (MCPhD)/academic/industrial partner Level: taught/research/industrial//financial/all Financing: Who/how much/self funded Participation/promotion: Voluntary/selected, multi/single company, Initiative: academic/industry/both Promotion: organised (MCPhD)/individual Candidate selection:

Milestones 8.1 Multicentre PhD training curricula completedM6 8.2 Training programme agreement form completedM Review of Ph.D recruitment M3,6,12

Deliverables D8.1 Ph.D training curricula M6 D8.2 Industrial training programme M18 D8.3 Administrative support programme M24 D8.4 Ph.D Training programme participation agreement skeleton M30