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Description of the research themes for the 37th cycle (2021-2024)

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Seven scholarships (three years) are offered in the 37th cycle, here is a short description of the research themes. Applicants will be asked to select one or more themes during the oral colloquium

Theme 1: Landslides monitoring

The importance of monitoring hydrogeological instability has grown over the years since landscape anthropization has significantly increased the risk of landslides. It is nevertheless a very complex activity which requires the knowledge and analysis of many features, such as soil moisture, soil composition, weather conditions and site history. The acquisition of these data can prove quite challenging due for example to significant differences from point to point, high frequency of temporal variations and technical difficulties of certain the measurements.
In recent years, the development of highly sophisticated sensors and infrastructures has dramatically increased the amount of collected data, also contributing to differentiate its nature. This, in turn, has brought forth the need for the automation of data processing. This project is aimed at dealing with such challenges with the help of machine learning techniques, because they provide reliable predictions and allow the identification of emerging trends in big data analysis, even in the presence of complex environments and non-linear dependencies between said data. The successful candidate will be expected to search the reference literature to identify an existing ML application or come up with one of his/her own to improve one or more steps of prediction and prevention chain for hydrogeological events. In particular, in the geotechnical field the employment of artificial neural networks is still a little-explored subject, even though it has brought about great advancements in lots of other areas of study. The candidate could therefore consider such option and identify elements of the Early Warning System that could benefit from the application of neural networks. The PhD student, possibly in co-tutelle with the University of Zilina (SK), will be supervised by Andrea Segalini.

Theme 2: On climate change resilience and design of Nature Base Solutions (NBS)

Climate Change will significantly impact people's well-being, expenditure of energy, and degradation of the ecosystem. Nature-Based Solutions (NBS) are actions inspired by, supported by, or copied from nature that deploy various natural features and processes. By fostering climate change mitigation, NBS should affect well-being, energy, and biodiversity. The Focus area of the PhD thesis is the study of a holistic approach to design NBS involving thermal comfort, energy patterns of buildings and ecology of places via multi-domain computational methods. The PhD candidate will focus on two main objectives: developing a co-benefits holistic computation tool to be applied at the district and buildings scale, design and an NBS prototype through digital twin (mainly via Rhino - Ladybug tools and ENVI-met software and onsite measurements). Applying candidates should possess knowledge of microclimatic patterns, ecology and be computationally skilled with Grassopher and Envimet. Along with the path, collaborations with universities abroad will be defined. Professor Emanuele Naboni and Barbara Gherri will supervise the PhD candidate.

Theme 3: Durability of corroded reinforced concrete and prestressed concrete structures

This research topic of durability is here afforded towards a structural engineering perspective. The last report “Human Cost of Disasters 2000-2019” (www.undrr.org) illustrates that the number of natural disasters has almost doubled in the last twenty years if compared to the previous twenty years. Indeed, global warming triggers climate change which is recognised as the major driver of disaster losses. It results that the intensity and the frequency of natural hazards, such as tsunami, heatwaves, flooding, storms, hurricanes, are increasing and consequently the exposure of structures to aggressive environmental actions is increasing.

If we consider that the exposure of critical infrastructures is increasing due to urbanisation and industrial development and that the ageing of structures and infrastructures - coupled with insufficient maintenance - amplifies the vulnerability of existing structures; we can conclude that the risks associated to durability issues are increasing over the time. The main causes of vulnerability of existing reinforced concrete structures and prestressed concrete members, are related to corrosion of reinforcement induced by durability issues not considered in the initial design, structures built under negligent inspections, poor quality of concrete, low reinforcement percentage ratios, poor distribution of bars, thin concrete cover, material deterioration, etc. The field of application of the proposed study is related to typical structures affected by corrosion such as parking, thermal power plants, industrial and commercial buildings, schools, public buildings, structures located close to the coast, retaining walls, bridges, tunnels, concrete chimneys, swimming pools, piers, dams, etc. Different levels of complexity in the modelling and in the assessment of corroded RC and PC structures will be considered. The assessment will be carried out by adopting different approaches, such as full probabilistic approach and partial factor design approach. The modelling will be carried out by adopting simplified methods, based on sectional analysis and truss analogy or refined non-linear finite element analyses. An experimental activity will be also carried out to the aim of formulating or validating analytical or numerical methods. The corrosion rate and the rheological effects will be implemented in the time domain by analysing the evolutionary behaviour of the RC and PC members in order to provide engineering tools for the prediction of the residual life of existing structures. The assessment of the residual life of existing RC and PC structures is not a consolidated science and the society needs further improvements to obtain reliable analytical methods that can be used by engineers in the daily practice. Finally, the “Making Critical Infrastructure Resilient” (https://www.undrr.org) report indicates that a huge amount of money will be invested in infrastructures in the future. Several structures and infrastructures have been recently repaired, and a huge amount of structures will be repaired in the coming years. In order to respond to these urgent needs, the research activity will deal with minimize the impact of reactive and proactive interventions considering durability, costs, timing, sustainability, and Life Cycle Assessment. The PhD student will be integrated in the research team of Structural Engineering working at the Department of Engineering and Architecture of the University of Parma. For further information, please contact Beatrice Belletti (beatrice.belletti@unipr.it).

Theme 4: The use of vegetation for the prevention of shallow landslides

The main resource for the emergence and development of crops and shrubs is the soil; how it affects the plant life is widely studied in the natural sciences and agronomy. However, there is also the inverse contribution, i.e. the role of plants in prevention of soil erosion and landslides; this derives from the plant roots, which provide the soil reinforcement, as well as an improvement of the soil hydraulic characteristics. In this direction, the study and research are "recent" and there are no indications of established practice in considering the root reinforcement. The successful candidate will focus on the study, modelling and development of natural interventions, based on the use of vegetation in the prevention of slope movements, with a specific attention to the rainfall-induced shallow landslides. The PhD student will be supervised by Lorella Montrasio

Theme 5: Polyurethane as geotechnical seismic isolation method

Reductions in seismic risk make up one of the most important research topics of earthquake engineering researchers. Alongside structural methods for seismic risk mitigation are the Geotechnical Seismic Isolation (GSI) methods, of geotechnical interest, which provide protection to structures through interventions in the soil. Intervening on the soil represents a technique that has origins in antiquity: for example, gravel was used under the foundation of Temple of Hera at Samos or compact “cushions of earth” under Trojan Walls, to separate the foundations from the rock. The research on GSI methods is often based on the use of synthetic materials; among them, our Geotechnical Laboratory has studied the polyurethane for years to be used through injections.

The successful candidate will focus on the study, modelling and development of GSI interventions, based on the use of polyurethane for the seismic risk mitigation. In particular, experimental tests will be performed on pure polyurethane and composite soil-polyurethane material. A Finite-Element numerical model will be developed to interpretate the experimental test, before being extended to large-scale cases to provide the fundamental for the design of real applications. The PhD student will be supervised by Lorella Montrasio

Theme 6: Non-Newtonian fluids flows in fractures and porous media

Non-Newtonian fluids with complex rheological behavior are often encountered in industrial and environmental flows, often in porous matrix and fractures. Progress in the in-depth knowledge of the process requires experimental work with advanced devices, with physical models that reproduce the complexities of real conditions.
The successful candidate is motivated to investigate these complexities with the use of the most advanced technology in rheometry, available in the Rheology and Rheometry Laboratory of the Department of Civil Engineering and Architecture, like MCR 702 MultiDrive from Anton Paar, with Rheo-microscopy setup.

The PhD student will be supervised by Sandro Longo and Luca Chiapponi. Some relevant publications of the group on this topic are available. See also a gallery of lab videos and activities.

Theme 7: Flood Resilience

Maximising the resilience (Defined as the capability to prepare, adapt, and anticipate) of communities to floods events is nowadays recognized as the most effective way of reducing the damages generated by such natural disasters.

Jongman et al. (2014) estimated that flood events in Europe caused damage of about 4.9 billion euros per year in the period from 2000 to 2012. Due to climate change, moreover, the frequency of flood events in Europe is expected to double. by 2050. However, to increase the resilience advanced knowledge and analysis, based on the use of fast and accurate numerical models, (which aim to predict the evolution and consequences of floods) is required. The objective of the present project is to develop a novel way of generating highly accurate hydraulic risk maps on domains at a regional scale (in the order of 103-104 km2) with the use of highly parallel two-dimensional computational codes, together with artificial neural networks. The successful candidate will exploit the highly parallel PARFLOOD computational code, developed to solve two-dimensional Shallow Waters (Vacondio et al. 2017, Turchetto et al 2020), together with artificial neural networks with the aim of predicting the evolution of flooding on real bathymetry, including urban areas). He/she will work in a large team (7 academics and several PhD students and Post-docs) with well-established international network. During the project, collaborations with university/research centers abroad will be defined (if appropriate). Professor Paolo Mignosa (paolo.mignosa@unipr.it) and Dr. Renato Vacondio (renato.vacondio@unipr.it) will supervise the PhD candidate.

References

Jongman B, Hochrainer-Stigler S, Feyen L, Aerts JCJH, Mechler R, Botzen WJW, Bouwer LM, Pflug G, Rojas R, Ward PJ (2014) Increasing stress on disaster-risk finance due to large floods. Nat Clim Change 4:264–268

R. Vacondio, A. Dal Palù, A. Ferrari, P. Mignosa, F. Aureli, S. Dazzi, A non-uniform efficient grid type for GPU-parallel Shallow Water Equations models, Environmental Modelling & Software, Vol 88, 2017, pp. 119-137.

M. Turchetto, A. D. Palù and R. Vacondio, "A General Design for a Scalable MPI-GPU Multi-Resolution 2D Numerical Solver," in IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 5, pp. 1036-1047, 1 May 2020.

Theme 8: Inverse problems in groundwater

Considering that one third of humanity is totally dependent on groundwater for their daily needs, it is clear that groundwater is a resource that must be properly preserved and managed. Above all, the impact of climate change on water resources, both quantitatively and qualitatively, could be severe. Numerical modeling of groundwater has played a key role in aquifer management and in the design and verification of remediation procedures for contaminated sites. Unfortunately, the spatial distribution of the hydraulic properties of the aquifer (such as transmissivity and dispersion parameters) are highly variable and never fully known. Furthermore, another problem is the identification of pollutant sources and their release in time.

The objective of this PhD is the development of new inverse procedures aimed at estimating the hydraulic parameters of the aquifer and identifying the sources of contaminants. The developed procedures will be applied and tested at a site in northern Italy, also considering the effect of climate change. The successful candidate should know groundwater modeling, Matlab and Python and should be motivated in the groundwater field. The PhD student will be supervised by Andrea Zanini (Scopus, ORCid). For further information, please contact andrea.zanini@unipr.it.

Selected references

Butera I., Tanda M.G., Zanini A. (2013), Simultaneous identification of the Pollutant Release History and the Source Location in Groundwater by means of a Geostatistical Approach (2013), Volume 27, Issue 5 , pp 1269-1280, Stochastic Environmental Research and Risk Assessment, , Springer Berlin / Heidelberg, ISSN: 1436-3240 (online). doi: 10.1007/s00477-012-0662-1

Chen Z., Xu T., Gómez-Hernández J.J., Zanini A., (2021), Contaminant Spill in a Sandbox with Non-Gaussian Conductivities: Simultaneous Identification by the Restart Normal-Score Ensemble Kalman Filter. Math Geosci. doi: 10.1007/s11004-021-09928-y

D’Oria M., Zanini A. (2019), Characterization of hydraulic heterogeneity of alluvial aquifer using natural stimuli: A field experience of Northern Italy, Water 11(1) 176. doi: 10.3390/w11010176

Zanini A., Kitanidis P. K. (2009), Geostatistical inversing for large-contrast transmissivity fields, Stochastic Environmental Research and Risk Assessment, 23:565–577, Springer Berlin / Heidelberg, ISSN: 1436-3240 (online) 1436-3259 (cartaceo). doi: 10.1007/s00477-008-0241-7

Zanini A., Woodbury A.D. (2016), Contaminant source reconstruction by empirical Bayes and Akaike's Bayesian Information Criterion, Journal of Contaminant Hydrology, doi: 10.1016/j.jconhyd.2016.01.006

Theme 9: Laboratory characterization and performance-based mechanical modeling of cold recycled asphalt mixtures

Asphalt pavements have a great potential to be fully and repetitively recyclable; two of the most common techniques are cold recycling with foam bitumen and with bituminous emulsion. Despite the common and frequent uses, these techniques still extensively utilize empirical approaches for material characterization as well as for the design of pavements with layers made with cold recycled mixtures (CRM).

This research project will undertake testing of CRM in order to develop a laboratory characterization approach that is able to consider all performance characteristics of the material, without considering it as a granular material or a low-performance asphalt mixture. The second goal of the project is to develop a performance-based mechanical model able to suitably characterize of CRM within pavement structural analysis, and propose an approach that can reliably design rehabilitated flexible pavements with layers consisting of CRM.

This Ph.D. will be in cotutelle with the University of New Hampshire. The two supervisors will be Dr. Gabriele Tebaldi and Dr. Eshan Dave.

Theme_1_Segalini_movimenti_frana
Naboni Gherri 37 Cycle proposal
Belletti_tema_Dottorato_37_Ciclo
Tema_1_Montrasio
Montrasio_theme
T6
Flood Resilience
Zanini inverse problem
Tebaldi project
Pubblicato Wednesday, 5 May, 2021 - 07:17 | ultima modifica Monday, 28 June, 2021 - 06:49