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Dernière mise à jour : Mai 2018

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BIOMP

Multi-scale modelling | Flowsheeting packages | LCA | Process intensification | Metabolic engineering | Property databases | Thermodynamic models

BIOMP

DBTLP

About the Platform 

BIOMP (BIO Modeling Platform) is operated by NTUA/IPSEN and supports access to engineering assets (models, tools and data), expert groups (to tune and develop models) and training material. The platform is intended to build high-throughput capabilities, to face biorefining challenges and to achieve real-life and practical objectives. The platform has invested on the use of semantics to share heterogeneous resources providing access to users, modellers and practitioners. The services combine process systems engineering technologies and ICT methods and cover process synthesis and optimization, multi-scale process flowsheeting and simulation, LCA, value chain analysis, as well as property databases, thermodynamic and costing models.

The BIOMP offers multiple-purpose services and tools that contribute over the steps of DBTL-P cycle by means of: metabolic pathways reduction and the use of KPIs in DESIGN; pathways synthesis and optimization in BUILD; translating and upgrading experimental results into kinetics, integrated process flowsheets and techno-economic results in TEST; ex-ante LCA/costing and pathways clusterization in LEARN; process simulation, synthesis and integration to upscale pilot/lab-work and finalize designs towards sustainable industrial biotechnological applications in PROCESS.

Offer

  • LCA technologies (TEST, LEARN)

‒      Evaluate environmental performance

‒      Chemicals descriptors database and group-contribution techniques to estimate LCA metrics

‒      LCA indicators and inventories for a wide variety of biorenewables, bioproducts and processes:

§  Midpoint indicators: climate change, fossil depletion, ozone depletion, etc

§  Endpoint indicators: Resources depletion, Ecosystem quality, Human health

  • Process cost estimator (TEST, LEARN)

‒      Cost models that cover a wide range of process equipment and operating conditions

  • Algae biorefineries (BUILD, TEST)

‒      Build algae-based value chains (3 alternative species)

‒      Test algal-biorefining technologies

‒      Technological and economic performance of top-rated solutions

  • Biorefinery models and databases (BUILD, TEST, PROCESS)

‒      Property databases and thermodynamic models

‒      Commercial modeling platforms and unit operation libraries to build, test and analyze user-defined chemistries, products and processes

‒      Ready-made and customizable process models of lignocellulosic biorefinery chemistries (equipment, efficiencies, energy consumption, CAPEX and OPEX).

‒      Compare experimental rigs and experiments and explain differences/deviations attributed to physical/chemical phenomena.

  • Downstream process design (TEST, PROCESS)

‒      Assess and optimize downstream separation efficiencies

‒      Fully integrated separations designs to minimize downstream processing cost

  • Scale-up and techno-economic analysis (TEST, PROCESS, LEARN)

Translate experimental data into kinetics and scale-up experiments into industrial scale processes.

‒      Multiple-purpose service: multi-scale process flowsheeting; sizing process equipment; CFD modeling for detailed systems design and optimization; process and energy integration to build efficiencies; techno-economic analysis; LCA

‒      Complete and integrated flowsheets: operation efficiencies and economic performance

‒      Reversely, large-scale process performance will be used to guide, support and improve lab-scale work and experiments

‒      Extrapolate chemistries and lab-scale results (appropriate for low TRL) in industrial scale, ahead of detailed design

‒      Techno-economic analysis and detailed design (appropriate for high TRL)

  • Design of integrated biorefineries (TEST, PROCESS)

This service examines options, benefits and savings of resources by connecting and integrating different (bio)technological applications together and (optionally) with existing industry.

‒      Connect experimental rigs and bridge the gaps between labs

‒      Highlight cost-effective technologies to integrate based at different locations, processing capacities and stages

‒      Detect and design complementary patterns to share and save energy, water and materials

‒      Adapting user-defined processing conditions and constraints (type of biorenewables, chemistries and seasonal data)

‒      Test and improve sustainability of multiple-product and multiple-feedstock biorefineries; build circular economy paradigms and industrial symbiosis networks

‒      Build fully integrated, high performance and eco-friendly biorefinery portfolios: products and processes; feedstocks and operations planning; electric power cogeneration potentials

‒      Trade-off economic benefits with environmental performance; evaluate plant flexibility and resilience against regional constraints and market uncertainties.

  • Metabolic engineering (LEARN, DESIGN, BUILD)

This service combines metabolic engineering with process design technologies to assess and test the effects of metabolic expression on large-scale chemical plant performance.

‒      Analyze and optimize metabolic behavior (fluxes of intra/extracellular metabolites) to extrapolate and optimize cells performance in industrial scale

‒      Reversely: use of engineering criteria to re-engineer metabolic reactions

‒      Support lab-scale work and improve experimental procedure: detect favorable operating conditions and design parameters to prevent blind experimentation and save valuable resources and time

  • Machine Learning (LEARN, BUILD)

Machine learning technologies – also combined with thermodynamic models and kinetics – are implemented to assist in the design of metabolics and targeting cells performance.

‒      Highlight metabolic reactions with significant effects on the production of desired extracellular chemicals (intensification of key metabolic reactions)

‒      Detect and clusterize common genes or genes groups – along with corresponding expressed metabolic reactions – over alternative propositions of genes sequences to systematize knowledge, generalize heuristics for comparison and extract feedback to re-engineer metabolics

‒      Reduction of pathways with minor impacts on cells performance

More info

Member of: BBI, EERA Bioenergy, SusChem, CAPE WP (EFCE), IEA.

Units of access: 1 User-Week

  • Quantity offered: 5 units (on average) of access for a modelling project
  • Total offered: 2 weeks-6 months
  • Type of access: Virtual, On-site

SERVICE INSTALLATION CODE: GR_NTUA_IPSEN-BIOMP

ntua

NTUA is the largest and oldest engineering university in Greece, also a first choice for undergraduate scientists and engineers. The Chemical Engineering School at NTUA is the largest in the country and holds 4 departments and 70 academics. NTUA participates with the research group of Industrial Process Systems ENgineering (IPSEN), a Certified Unit by IChemE, to undertake design and engineering work for chemical plants. IPSEN offers 25-year expertise in: bio-renewables valorization; multi-scale modelling; process design, integration and optimization; techno-economic analysis; state-of-the-art systems engineering. IPSEN collaborates with institutes, universities and the industry through (over 60) research and technology projects, notably in applications for biorefineries, circular economy, and renewable energy networks.

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