Systems modelling design for waste resource recovery
Lead Research Organisation:
Imperial College London
Department Name: Chemical Engineering
Abstract
Considerable amounts of carbon-containing and nutrient-rich waste resources in solid, liquid and gas phases are generated every year and could be converted to value-added bio-products. By far the most widespread recovery technology in the wastewater treatment and bio- solid sector is anaerobic digestion (AD). By 2016, there were 540 operational AD facilities in the UK with a total capacity of 708 MW (equivalent to powering 850,000 households); over 90 AD plants injected bio-methane into the natural gas grid, accounting for 2.2% UK gas consumption [2]. However, concerns have been raised regarding the energy-focused incentive strategies which could hinder the penetration of other environmentally favourable resource recovery options [1] e.g. phosphorus recovery, the AD biogas reformed to hydrogen for microbial protein production. Moreover, AD digestate could be further processed via thermochemical routes (e.g. hydrothermal liquefaction) to recover value-added products. A shift to technology integration to proactively manage waste and co-recover value-added products is underway. However, the composition variability and traceability of diverse waste streams from various sectors hinder the waste valorisation from current passive response to future proactive management. Another challenge lies in the disconnection between two-level design i.e. conversion process synthesis (single site) and enterprise-wide optimisation (multi-site). Process synthesis determines the flowsheet and equipments for given waste and product stream; whereas multi-site network design involves wider temporal and spatial scales such as the short-term operational decisions and long/mid-term planning. In particular, with the evolving Fourth Industrial Revolution (Industry 4.0) [3], many of the data barriers are being overcome through interconnection of smart machinery, which support collection and analyses of real-time data across multi-sites and supply chain. Despite of the advances in technology and process design and integration, sustainability assessment and mathematical optimisation, research gaps emerge in the modelling approach, that can tackle the challenges above and provide multi-level decision-support.
This PhD programme will build on some preliminary work and focus on modelling approach research, aiming to bridge two-level decision spaces (process synthesis and multi-site network design), tackle the bottleneck (e.g. waste variability) and solve the scheduling and planning problems under uncertainty (e.g. uncertainty in waste supply). This can be achieved by incorporation analytical results and operational data (both from lab and industry) within a modelling framework, that integrates waste-recovery process design and integration, life cycle approach, optimisation approach (e.g. rolling horizon algorithms) and machine learning techniques. Capability of the methodology will be tested in one or two applications in UK/China AD-based bioconversion design for wastewater and bio-solid waste recovery where 'plug-and-play' design solutions for the existing centralised and decentralised AD facilities will be explored. The trade-offs between conflicting economic and environmental criteria will be accounted for in optimisation and smart decision-making under coordinated waste-to-resource systems (waste supply, machines at multi-site are interconnected via internet) will be explored.
1. BIS, Building a high value bioeconomy: opportunities from waste, 2015.
2. Anaerobic Digestion & Bioresources Association, ADBA Market & Policy Reports 2016 & 2017. 2016.
3. Recommendations for implementing the strategic initiative INDUSTRIE 4.0. 2013, National Academy of Science and Engineering.
This PhD programme will build on some preliminary work and focus on modelling approach research, aiming to bridge two-level decision spaces (process synthesis and multi-site network design), tackle the bottleneck (e.g. waste variability) and solve the scheduling and planning problems under uncertainty (e.g. uncertainty in waste supply). This can be achieved by incorporation analytical results and operational data (both from lab and industry) within a modelling framework, that integrates waste-recovery process design and integration, life cycle approach, optimisation approach (e.g. rolling horizon algorithms) and machine learning techniques. Capability of the methodology will be tested in one or two applications in UK/China AD-based bioconversion design for wastewater and bio-solid waste recovery where 'plug-and-play' design solutions for the existing centralised and decentralised AD facilities will be explored. The trade-offs between conflicting economic and environmental criteria will be accounted for in optimisation and smart decision-making under coordinated waste-to-resource systems (waste supply, machines at multi-site are interconnected via internet) will be explored.
1. BIS, Building a high value bioeconomy: opportunities from waste, 2015.
2. Anaerobic Digestion & Bioresources Association, ADBA Market & Policy Reports 2016 & 2017. 2016.
3. Recommendations for implementing the strategic initiative INDUSTRIE 4.0. 2013, National Academy of Science and Engineering.
Publications
Durkin A
(2024)
Surrogate-based optimisation of process systems to recover resources from wastewater
in Computers & Chemical Engineering
Durkin A
(2022)
Can closed-loop microbial protein provide sustainable protein security against the hunger pandemic?
in Current Research in Biotechnology
Durkin A
(2022)
Resource recovery from food-processing wastewaters in a circular economy: a methodology for the future.
in Current opinion in biotechnology
Durkin A
(2022)
14th International Symposium on Process Systems Engineering
Robles I
(2021)
Stochastic optimisation of organic waste-to-resource value chain.
in Environmental pollution (Barking, Essex : 1987)
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/N509486/1 | 30/09/2016 | 30/03/2022 | |||
2194316 | Studentship | EP/N509486/1 | 30/09/2018 | 30/11/2022 | Alexander Durkin |
EP/R513052/1 | 30/09/2018 | 29/09/2023 | |||
2194316 | Studentship | EP/R513052/1 | 30/09/2018 | 30/11/2022 | Alexander Durkin |
EP/T51780X/1 | 30/09/2020 | 29/09/2025 | |||
2194316 | Studentship | EP/T51780X/1 | 30/09/2018 | 30/11/2022 | Alexander Durkin |
Title | Process design and optimisation framework |
Description | A Python-based modelling framework for the design and optimisation of resource recovery processes |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | No |
Impact | Generation of results for journal articles assessing the potential resource recovery from wastewater. |
Description | Quorn Foods |
Organisation | Marlow Foods |
Country | United Kingdom |
Sector | Private |
PI Contribution | Application of the methodology developed to a case study on resource recovery from Quorn fermentation wastewater. |
Collaborator Contribution | Provided data and guidance for case study. Acted as industrial mentor. Provided opportunities to present research findings to industrial audience. |
Impact | Journal article under review. |
Start Year | 2018 |
Description | Great Exhibition Road Festival 2019 |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Public/other audiences |
Results and Impact | Presented collaborative research with Quorn Foods to the general public at a stall at the Great Exhibition Road Festival 2019. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.greatexhibitionroadfestival.co.uk |
Description | Sao Paulo School of Advanced Science on WEF nexus |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Study participants or study members |
Results and Impact | Workshop to learn about, discuss and develop multidisciplinary research on the water, energy, food nexus. |
Year(s) Of Engagement Activity | 2018 |
Description | Tsinghua and Chinese Academy of Sciences academic visit |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Study participants or study members |
Results and Impact | Presentations and research meetings on projects within the research group. Collaborative research with Tsinghua university and Chinese Academy of Sciences. |
Year(s) Of Engagement Activity | 2019 |