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13 Projects

  • Canada
  • 2018-2022
  • 2014
  • 2018

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  • Funder: EC Project Code: 603288
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  • Funder: NIH Project Code: 5R21NS088166-02
    Funder Contribution: 75,649 USD
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  • Funder: EC Project Code: 612347
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  • Funder: EC Project Code: 613678
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  • Funder: EC Project Code: 603993
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  • Funder: UKRI Project Code: EP/M001067/1
    Funder Contribution: 501,473 GBP

    CRUST takes advantage of the UK's leadership in uncertainty evaluation of earthquake source and ground motion (Goda [PI] and University of Bristol/Cabot Research Institute) and on-shore tsunami impact research (Rossetto [Co-I] and University College of London/EPICentre [Earthquake and People Interaction Centre]) to develop an innovative cross-hazard risk assessment methodology for cascading disasters that promotes dynamic decision-making processes for catastrophe risk management. It cuts across multiple academic fields, i.e. geophysics, engineering seismology, earthquake engineering, and coastal engineering. The timeliness and critical needs for cascading multi-hazards impact assessments have been exemplified by recent catastrophes. CRUST fills the current gap between quasi-static, fragmented approaches for multi-hazards and envisaged, dynamic, coherent frameworks for cascading hazards. CRUST combines a wide range of state-of-the-art hazard and risk models into a comprehensive methodology by taking into account uncertainty associated with predictions of hazards and risks. The work will provide multi-hazards risk assessment guidelines and tools for policy-makers and engineering/reinsurance industries. The proposal capitalises on a breakthrough technology for generating long-waves achieved by Rossetto. CRUST is composed of four work packages (WPs): WP1-'Ground shaking risk modelling due to mega-thrust subduction earthquakes'; WP2-'Tsunami wave and fragility modelling due to mega-thrust subduction earthquakes'; WP3-'Integrated multi-hazards modelling for earthquake shaking and tsunami'; and WP4-'Case studies for the Hikurangi and Cascadia subduction zones'. In WP1-WP3, the research adopts the 2011 Tohoku earthquake as a case study site, since this event offers extensive datasets for strong motion data, tsunami inundation, and building damage survey results, together with other geographical and demographical information (e.g. high-resolution bathymetry data and digital elevation model). The aims of WP1 are: to generate strong motion time-histories based on uncertain earthquake slips, reflecting multiple asperities (large slip patches) over a fault plane (WP1-1); to characterise spatiotemporal occurrence of aftershocks using global catalogues of subduction earthquakes (WP1-2); and to conduct probabilistic seismic performance assessment of structures subjected to mainshock-aftershock sequences (WP1-3). WP2 comprises tsunami wave profile and inundation simulation using uncertain earthquake slips (WP2-1); characterisation of tsunami loads to structures in coastal areas through large-scale physical experiments using an innovative long wave generation system at HR Wallingford (WP2-2); and development of analytical tsunami fragility models in comparison with field observations and experiments (WP2-3). The WP2 will be conducted in collaboration with academic collaborators from Kyoto University and Tohoku University (Japan). WP3 integrates the model components developed from WP1 and WP2 into a comprehensive framework for multi-hazards risk assessment for the 2011 Tohoku earthquake and tsunami (WP3-1). Then, practical engineering tools for the multi-hazards method will be developed in WP3-2. Finally, in WP4, the developed multi-hazards methodology will be applied to the Hikurangi and Cascadia subduction zones. The assessments are done in a predictive mode, and these case studies will be conducted in close collaboration with academic partners, GNS Science (New Zealand) for the Hikurangi zone, and researchers at Western University and University of British Columbia (Canada) for the Cascadia zone.

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  • Funder: EC Project Code: 610510
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  • Funder: UKRI Project Code: NE/L006561/1
    Funder Contribution: 398,042 GBP

    Boreal regions hold upwards of 60% of the planet's freshwater, an essential ingredient for all life. But human activities, such as climate and land use change, are dramatically altering these landscapes and threatening the delivery of key services provided by aquatic ecosystems, such as clean drinking water and healthy fish populations. Contemporary paradigms of aquatic conservation have emphasized inputs of pollutants and water resource development as causes of declining water security and biodiversity, but restoration attempts are failing when these two factors alone are improved. Increasingly, local watersheds are seen as critical controls of aquatic ecosystems. This is spurred by the recent discovery that pathways of energy mobilization upwards through aquatic food webs - from microbes to fish - rely on organic matter originating from terrestrial vegetation, proving the adage that "clean water is a forest product". Any factor that changes the quality and quantity of organic matter input into freshwater from their surrounding catchments will clearly influence the delivery of aquatic ecosystem services. Fire, forest pests, and resource development, such as mining and logging, are emerging disturbances that are transforming boreal regions, but little is known as to how they will change long-term cycling of nutrients from terrestrial vegetation into aquatic ecosystems. A new watershed-level science that integrates the management of forestry and water resources is clearly needed to inform decision makers of the actions needed to conserve freshwater supplies by linking actions on land to processes in water. Our research will test whether the productivity of aquatic food webs increases with the quantity and quality of terrestrial organic matter under different climate scenarios. We will also answer whether disturbances on land that remove plant biomass and change the quality of plant litter will dampen the productivity of freshwater plants and animals. Our approach will be to create 96 artificial ecosystems in a common lake environment and expose sites to different quantities and qualities of organic matter. We will measure the responses of microbial, algal, and grazer communities using cutting-edge technologies such as next-generation DNA sequencing. We will also plant tagged individuals of a sedentary mussel species closely-related to economically important taxa within each site and monitor their long-term growth and survival. The ultimate goal of this work is to develop a spatially-explicit, dynamical watershed-level simulation model. We want to answer the question if X% of habitat is consumed by fire or insect outbreaks, then food stocks for fish will change by Y%. Outcomes of this research will be highly relevant to the UK and international policy around managing freshwater supplies by demonstrating strong linkages between terrestrial and aquatic ecosystems. For example, the EU has developed legislation to protect freshwater but this ignores the effects of land use practices on lake water quality and biota. The future of extensive forestry plantations and pastures surrounding many socio-economically important watersheds in Britain are also being debated as the EU begins reforming the Common Agricultural Policy. We aim to show that any changes in land use must consider how energy in the form of organic matter is dispersed to aquatic ecosystems and supports their productivity. Finally, this project will have many applications for improving regional land use planning and management, as well as restoring environmentally damaged landscapes. We will work closely with partners in the mining industry and government to inform them of the best practices for re-vegetating degraded watersheds.

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  • Funder: NIH Project Code: 5R01AI111805-03
    Funder Contribution: 758,828 USD
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  • Funder: UKRI Project Code: EP/K040251/2
    Funder Contribution: 1,146,390 GBP

    Mathematics is a profound intellectual achievement with impact on all aspects of business and society. For centuries, the highest level of mathematics has been seen as an isolated creative activity, to produce a proof for review and acceptance by research peers. Mathematics is now at a remarkable inflexion point, with new technology radically extending the power and limits of individuals. "Crowdsourcing" pulls together diverse experts to solve problems; symbolic computation tackles huge routine calculations; and computers check proofs that are just too long and complicated for any human to comprehend, using programs designed to verify hardware. Yet these techniques are currently used in stand-alone fashion, lacking integration with each other or with human creativity or fallibility. Social machines are new paradigm, identified by Berners-Lee, for viewing a combination of people and computers as a single problem-solving entity. Our long-term vision is to change mathematics, transforming the reach, pace, and impact of mathematics research, through creating a mathematics social machine: a combination of people, computers, and archives to create and apply mathematics. Thus, for example, an industry researcher wanting to design a network with specific properties could quickly access diverse research skills and research; explore hypotheses; discuss possible solutions; obtain surety of correctness to a desired level; and create new mathematics that individual effort might never imagine or verify. Seamlessly integrated "under the hood" might be a mixture of diverse people and machines, formal and informal approaches, old and new mathematics, experiment and proof. The obstacles to realising the vision are that (i) We do not have a high level understanding of the production of mathematics by people and machines, integrating the current diverse research approaches (ii) There is no shared view among the diverse re- search and user communities of what is and might be possible or desirable The outcome of the fellowship will be a new vision of a mathematics social machine, transforming the reach, pace and impact of mathematics. It will deliver: analysis and experiment to understand current and future production of mathematics as a social machine; designs and prototypes; ownership among academic and industry stakeholders; a roadmap for delivery of the next generation of social machines; and an international team ready to make it a reality.

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13 Projects
  • Funder: EC Project Code: 603288
    visibility183
    visibilityviews183
    downloaddownloads1,439
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  • Funder: NIH Project Code: 5R21NS088166-02
    Funder Contribution: 75,649 USD
    more_vert
  • Funder: EC Project Code: 612347
    visibility619
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    downloaddownloads841
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  • Funder: EC Project Code: 613678
    visibility363
    visibilityviews363
    downloaddownloads554
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  • Funder: EC Project Code: 603993
    visibility395
    visibilityviews395
    downloaddownloads437
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  • Funder: UKRI Project Code: EP/M001067/1
    Funder Contribution: 501,473 GBP

    CRUST takes advantage of the UK's leadership in uncertainty evaluation of earthquake source and ground motion (Goda [PI] and University of Bristol/Cabot Research Institute) and on-shore tsunami impact research (Rossetto [Co-I] and University College of London/EPICentre [Earthquake and People Interaction Centre]) to develop an innovative cross-hazard risk assessment methodology for cascading disasters that promotes dynamic decision-making processes for catastrophe risk management. It cuts across multiple academic fields, i.e. geophysics, engineering seismology, earthquake engineering, and coastal engineering. The timeliness and critical needs for cascading multi-hazards impact assessments have been exemplified by recent catastrophes. CRUST fills the current gap between quasi-static, fragmented approaches for multi-hazards and envisaged, dynamic, coherent frameworks for cascading hazards. CRUST combines a wide range of state-of-the-art hazard and risk models into a comprehensive methodology by taking into account uncertainty associated with predictions of hazards and risks. The work will provide multi-hazards risk assessment guidelines and tools for policy-makers and engineering/reinsurance industries. The proposal capitalises on a breakthrough technology for generating long-waves achieved by Rossetto. CRUST is composed of four work packages (WPs): WP1-'Ground shaking risk modelling due to mega-thrust subduction earthquakes'; WP2-'Tsunami wave and fragility modelling due to mega-thrust subduction earthquakes'; WP3-'Integrated multi-hazards modelling for earthquake shaking and tsunami'; and WP4-'Case studies for the Hikurangi and Cascadia subduction zones'. In WP1-WP3, the research adopts the 2011 Tohoku earthquake as a case study site, since this event offers extensive datasets for strong motion data, tsunami inundation, and building damage survey results, together with other geographical and demographical information (e.g. high-resolution bathymetry data and digital elevation model). The aims of WP1 are: to generate strong motion time-histories based on uncertain earthquake slips, reflecting multiple asperities (large slip patches) over a fault plane (WP1-1); to characterise spatiotemporal occurrence of aftershocks using global catalogues of subduction earthquakes (WP1-2); and to conduct probabilistic seismic performance assessment of structures subjected to mainshock-aftershock sequences (WP1-3). WP2 comprises tsunami wave profile and inundation simulation using uncertain earthquake slips (WP2-1); characterisation of tsunami loads to structures in coastal areas through large-scale physical experiments using an innovative long wave generation system at HR Wallingford (WP2-2); and development of analytical tsunami fragility models in comparison with field observations and experiments (WP2-3). The WP2 will be conducted in collaboration with academic collaborators from Kyoto University and Tohoku University (Japan). WP3 integrates the model components developed from WP1 and WP2 into a comprehensive framework for multi-hazards risk assessment for the 2011 Tohoku earthquake and tsunami (WP3-1). Then, practical engineering tools for the multi-hazards method will be developed in WP3-2. Finally, in WP4, the developed multi-hazards methodology will be applied to the Hikurangi and Cascadia subduction zones. The assessments are done in a predictive mode, and these case studies will be conducted in close collaboration with academic partners, GNS Science (New Zealand) for the Hikurangi zone, and researchers at Western University and University of British Columbia (Canada) for the Cascadia zone.

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  • Funder: EC Project Code: 610510
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  • Funder: UKRI Project Code: NE/L006561/1
    Funder Contribution: 398,042 GBP

    Boreal regions hold upwards of 60% of the planet's freshwater, an essential ingredient for all life. But human activities, such as climate and land use change, are dramatically altering these landscapes and threatening the delivery of key services provided by aquatic ecosystems, such as clean drinking water and healthy fish populations. Contemporary paradigms of aquatic conservation have emphasized inputs of pollutants and water resource development as causes of declining water security and biodiversity, but restoration attempts are failing when these two factors alone are improved. Increasingly, local watersheds are seen as critical controls of aquatic ecosystems. This is spurred by the recent discovery that pathways of energy mobilization upwards through aquatic food webs - from microbes to fish - rely on organic matter originating from terrestrial vegetation, proving the adage that "clean water is a forest product". Any factor that changes the quality and quantity of organic matter input into freshwater from their surrounding catchments will clearly influence the delivery of aquatic ecosystem services. Fire, forest pests, and resource development, such as mining and logging, are emerging disturbances that are transforming boreal regions, but little is known as to how they will change long-term cycling of nutrients from terrestrial vegetation into aquatic ecosystems. A new watershed-level science that integrates the management of forestry and water resources is clearly needed to inform decision makers of the actions needed to conserve freshwater supplies by linking actions on land to processes in water. Our research will test whether the productivity of aquatic food webs increases with the quantity and quality of terrestrial organic matter under different climate scenarios. We will also answer whether disturbances on land that remove plant biomass and change the quality of plant litter will dampen the productivity of freshwater plants and animals. Our approach will be to create 96 artificial ecosystems in a common lake environment and expose sites to different quantities and qualities of organic matter. We will measure the responses of microbial, algal, and grazer communities using cutting-edge technologies such as next-generation DNA sequencing. We will also plant tagged individuals of a sedentary mussel species closely-related to economically important taxa within each site and monitor their long-term growth and survival. The ultimate goal of this work is to develop a spatially-explicit, dynamical watershed-level simulation model. We want to answer the question if X% of habitat is consumed by fire or insect outbreaks, then food stocks for fish will change by Y%. Outcomes of this research will be highly relevant to the UK and international policy around managing freshwater supplies by demonstrating strong linkages between terrestrial and aquatic ecosystems. For example, the EU has developed legislation to protect freshwater but this ignores the effects of land use practices on lake water quality and biota. The future of extensive forestry plantations and pastures surrounding many socio-economically important watersheds in Britain are also being debated as the EU begins reforming the Common Agricultural Policy. We aim to show that any changes in land use must consider how energy in the form of organic matter is dispersed to aquatic ecosystems and supports their productivity. Finally, this project will have many applications for improving regional land use planning and management, as well as restoring environmentally damaged landscapes. We will work closely with partners in the mining industry and government to inform them of the best practices for re-vegetating degraded watersheds.

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  • Funder: NIH Project Code: 5R01AI111805-03
    Funder Contribution: 758,828 USD
    more_vert
  • Funder: UKRI Project Code: EP/K040251/2
    Funder Contribution: 1,146,390 GBP

    Mathematics is a profound intellectual achievement with impact on all aspects of business and society. For centuries, the highest level of mathematics has been seen as an isolated creative activity, to produce a proof for review and acceptance by research peers. Mathematics is now at a remarkable inflexion point, with new technology radically extending the power and limits of individuals. "Crowdsourcing" pulls together diverse experts to solve problems; symbolic computation tackles huge routine calculations; and computers check proofs that are just too long and complicated for any human to comprehend, using programs designed to verify hardware. Yet these techniques are currently used in stand-alone fashion, lacking integration with each other or with human creativity or fallibility. Social machines are new paradigm, identified by Berners-Lee, for viewing a combination of people and computers as a single problem-solving entity. Our long-term vision is to change mathematics, transforming the reach, pace, and impact of mathematics research, through creating a mathematics social machine: a combination of people, computers, and archives to create and apply mathematics. Thus, for example, an industry researcher wanting to design a network with specific properties could quickly access diverse research skills and research; explore hypotheses; discuss possible solutions; obtain surety of correctness to a desired level; and create new mathematics that individual effort might never imagine or verify. Seamlessly integrated "under the hood" might be a mixture of diverse people and machines, formal and informal approaches, old and new mathematics, experiment and proof. The obstacles to realising the vision are that (i) We do not have a high level understanding of the production of mathematics by people and machines, integrating the current diverse research approaches (ii) There is no shared view among the diverse re- search and user communities of what is and might be possible or desirable The outcome of the fellowship will be a new vision of a mathematics social machine, transforming the reach, pace and impact of mathematics. It will deliver: analysis and experiment to understand current and future production of mathematics as a social machine; designs and prototypes; ownership among academic and industry stakeholders; a roadmap for delivery of the next generation of social machines; and an international team ready to make it a reality.

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