Research Project Proposals
Risk & Resilience Engineering for the Natural, Industrialized and Built Environments
Four grants are available:
(*) 2 grants funded by Università degli Studi di Genova
(*)1 grant cofunded by MUR/Department (DICCA)
(*) 1 grant funded within D.M. 630 dated 24.4.2024 (co-funded by ETT S.p.a)
For the two grants funded by Università degli Studi di Genova, possible research topics are described in the following. Interested Candidates are invited to contact the proposers listed below or other members of the Internal Curriculum Committee for agreeing on other possible topics (the complete list of members is available here).
For the grant cofunded by MUR/Department DICCA please refer to the Research topic BF1. For the grant co-funded by ETT S.p.a. within D.M. 630 please refer to the Research topic BF2. For these two grants, the research project of the candidate must agree with the goals identified for this research themes BF1 and BF2, respectively.
Possible research topics for the two grants funded by the University of Genova
Research topic A
Title: Data Assimilation from drones for hyper local weather assessment and prediction in urban environments using CFD
Proposers: Dario Milani (WRBAN S.r.l, DM-AirTech GmbH), Maria Pia Repetto, Massimiliano Burlando
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description: This research aims to integrate high-resolution data collected by drones into Computational Fluid Dynamics (CFD) models of the urban microclimate. The study will focus on developing advanced algorithms for the assimilation of real-time meteorological and environmental data, enhancing the accuracy of urban microclimate simulations. By leveraging drone technology, the project seeks to capture fine-scale variations in wind properties and thermal conditions, which are critical for urban air and ground mobility applications. In this regard, the project will contribute to create tools for reducing the vulnerability of modern cities to extreme weather events like windstorms and heat waves. The research will involve field data collection, CFD model development, machine learning techniques, and validation against empirical observations, ultimately contributing to safer and more cost-effective urban mobility solutions.
For more information please contact: Prof. Massimiliano Burlando, massimiliano.burlando@unige.it
Link to the group or personal webpage: For DM-AirTech: https://www.dm-airtech.com/ , for UniGe: https://www.gs-windyn.it/
References:
o Nithya, D. S., et al. "Review of Wind Flow Modelling in Urban Environments to Support the Development of Urban Air Mobility." Drones 8.4 (2024): 147.
o Subramanian, Balaji, Ndaona Chokani, and Reza S. Abhari. "Drone-based experimental investigation of three-dimensional flow structure of a multi-megawatt wind turbine in complex terrain." Journal of Solar Energy Engineering 137.5 (2015): 051007.
o Pirk, Norbert, et al. "Inferring surface energy fluxes using drone data assimilation in large eddy simulations." Atmospheric Measurement Techniques Discussions 2022 (2022): 1-32.
Research topic B
Title: Seismic assessment of historic reinforced concrete frames with thick masonry infills
Proposers: Chiara Calderini, Stefano Podestà
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description: Reinforced concrete (RC) frames constructed in the early 20th century often feature thick stone or brick masonry infills. However, the interaction between these RC frames and such thick masonry infills poses significant challenges in structural modeling, particularly under seismic loading conditions. This research aims to develop a comprehensive structural model that accurately represents the complex interaction between early 20th century RC frames and thick masonry infills.
The study will focus on the following objectives: (1) investigating the mechanical behavior of thick masonry infills and their impact on the overall structural performance of RC frames, (2) developing analytical models that incorporate the nonlinear behavior of both the RC frame and the infill, and (3) validating these models through experimental testing and finite element analysis (FEA).
Methodologically, the research will encompass a thorough literature review, material characterization tests, analytical modeling, FEA simulations and, if possible, experimental validation. Expected outcomes include a validated analytical model capable of predicting the behavior of RC frames with thick masonry infills under various loading scenarios and improved guidelines for assessing and retrofitting historical RC structures.
This research will significantly contribute to structural engineering by enhancing the understanding of RC frame and masonry infill interactions, thus aiding in the preservation and safety improvement of historically significant buildings.
For more information please contact: Chiara Calderini, chiara.calderini@unige.it
Link to the group or personal webpage: https://rubrica.unige.it/personale/UkNHX1Nr
References:
Morandi, P., Hak, S., Milanesi, R., Magenes, G. (2022). In-plane/out-of-plane interaction of strong masonry infills: From cyclic tests to out-of-plane verifications, Earthquake Engineering and Structural Dynamics, Volume 51 (3), 648 – 672.
Rostamkalaee, S., Peloso, S., Brunesi, E. (2023). Macro-Modelling of IP-OoP Interaction in Unreinforced Solid Masonry Infills under Earthquake-Induced Actions: A Review. Buildings, 13(9),2326.
Baek, E.R., Pohoryles, D.A., Bournas, D. (2024). Seismic assessment of the in-plane/out-of-plane interaction of masonry infills in a two-storey RC building subjected to bi-directional shaking table tests, Earthquake Engineering and Structural Dynamics, 53(6), pp. 2230-2251
Research topic C
Title: The accuracy of precipitation measurement in windy conditions and its role in the assessment of flood risk in urban areas
Proposers: Arianna Cauteruccio , Luca G. Lanza.
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description: Flood risk assessment and mitigation in urban areas relies on the accurate quantification of the flood hazard, deriving from the knowledge and understanding of the space-time evolution of intense precipitation events. This is obtained from measurements based on in-situ instruments and remote sensors. While traditional catching-type instruments measure the integral properties of rainfall (i.e., rainfall intensity and cumulative rainfall), more recently developed non-catching instruments (including disdrometers) can also measure the microphysical properties of rainfall including the drop size distribution (DSD). The research aims to fill knowledge gaps in precipitation measurements and their use in flood risk assessment. It focuses on assessing the accuracy of disdrometer measurements with respect to wind effects and instrumental biases and developing a suitable disdrometer correction method (DCM). Results will assess the impact of using corrected rainfall intensity and DSD data on estimating measurement biases due to environmental conditions, evaluating weather radar estimates, improving statistical analysis of rainfall time series at climatological scales, investigating joint rain/wind climatology features at selected test sites, deriving extreme rainfall event statistics and trends aimed at enhancing the resilience of the urban environment to the risk of flooding.
For more information please contact: Arianna Cauteruccio, arianna.cauteruccio@edu.unige.it Luca G. Lanzaluca.lanza@unige.it
Link to the group or personal webpage: https://rubrica.unige.it/personale/VUZDXV9u
https://rubrica.unige.it/personale/VkZGW15q
References:
o Cauteruccio, A., Chinchella, E., and Lanza, L. G. (2024). The overall collection efficiency of catching type precipitation gauges in windy conditions. Water Resour. Res., 60, e2023WR035098. https://doi.org/10.1029/2023WR035098
o Chinchella E., Cauteruccio A. and L.G. Lanza (2024). The impact of wind on precipitation measurements from a compact piezoelectric sensor, J. of Hydromet., 25 (2), 339 – 352, https://doi.org/10.1175/JHM-D-23-0180.1
o Cauteruccio, A., Stagnaro, M., Lanza, L. G., and Chan, P.W. (2023). Adjustment of 1 min rain gauge time series using co-located drop size distribution and wind speed measurements, Atmos. Meas. Tech., 16, 4155–4163. https://doi.org/10.5194/amt-16-4155-2023
o Cauteruccio, A., Brambilla, E., Stagnaro, M., Lanza, L.G. and D. Rocchi (2021). Wind tunnel validation of a particle tracking model to evaluate the wind-induced bias of precipitation measurements. Water Resour. Res., 57(7), e2020WR028766. https://doi.org/10.1029/2020WR028766
o Cauteruccio, A., Brambilla, E., Stagnaro, M., Lanza, L.G. and D. Rocchi (2021). Experimental evidence of the wind-induced bias of precipitation gauges using Particle Image Velocimetry and particle tracking in the wind tunnel. J. of Hydrol., 600, 126690. https://doi.org/10.1016/j.jhydrol.2021.126690
o Chinchella, E., Cauteruccio, A., Stagnaro, M. and L.G. Lanza (2021). Investigation of the Wind-Induced Airflow Pattern Near the Thies LPM Precipitation Gauge. Sensors, 21(14), 4880. https://doi.org/10.3390/s21144880
Research topic D
Title: Fragility analysis of roof structures in low-rise buildings subjected to non-synoptic outflows
Proposers: Luisa Pagnini, Giuseppe Piccardo and Maria Pia Repetto
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description: Recent catastrophic events in Italy and Europe have highlighted the vulnerability of roof structures to extreme wind induced uplift, often resulting in large economic losses and disruption for those assets. The most destructive events are frequently associated to non-synoptic winds, such as tornadoes and downbursts. The present proposal is addressed to investigate the vulnerability of roof structures to extreme wind actions by means of fragility curves. Fragility curves are extensively adopted in seismic field (e.g. [1]). The same procedure can be reformulated to consider wind loadings and its inherent random nature in speed and direction (e.g. [2]). Specifically, the transient aerodynamic effects caused by downburst accelerated flows will be analyzed through experimental tests in the Giovanni Solari Wind Tunnel, using an innovative active grid capable of replicating the main characteristics of non-synoptic outflows. The results of the proposed project, combined with hazard characterization, will facilitate the study of risk analysis of existing buildings and historical heritage sites against downburst extreme events. Moreover, it will be helpful for determining retrofit options to strengthen existing buildings against this type of extreme meteorological phenomena.
For more information please contact: Luisa Pagnini (pagnini@dicca.unige.it ), Giuseppe Piccardo (giuseppe.piccardo@unige.it) Maria Pia Repetto (repetto@dicca.unige.it)
Link to the group or personal webpage: www.gs-windyn.it
References:
[1] Tomassetti, U, Correia, A.A., Graziotti, F., Penna, A. (2019). Seismic vulnerability of roof systems combining URM gable walls and timber diaphragms. Earthquake Engineering & Structural Dynamics, 48, 1297-1318. DOI: 10.1002/eqe.3187
[2] Gavanski, E., Kopp, G.A. (2017). Fragility Assessment of Roof-to-Wall Connection Failures for Wood-Frame Houses in High Winds. ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng., 2017, 3(4): 04017013
Research topic E
Title: Developing Decision Support Systems to plan, design and install nature-based solutions in urban areas for the mitigation of the pluvial flooding
Proposers: Anna Palla, Ilaria Gnecco
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description: Pluvial flooding has become one of the most frequent natural disasters in recent years, and the pairing of nature-based solutions with the traditional grey infrastructure is recognized as the solution to mitigate the negative impact of urbanization on the hydrological response.
The main objective of the present research was to develop a Decision Support Systems (DSS) for planning the interventions (nature-based solutions and traditional grey infrastructure) at the catchment scale to enhance urban resilience to cope with intense rain events with an insight into both current and future climate. It will be based on the implementation of a multi-objective optimization algorithm. Compared to other existing methodologies in the scientific literature, the methodology will be structured according to the phasing-of-construction/rehabilitation approach, aiming to design interventions in phases rather than all at once at the beginning of the construction, with emphasis to budget limits and availability in time.
The research associated with the multi-phase optimization DSS is essential to enable practitioners and policy-makers to design short-term upgrades of the urban drainage network, aimed at reaching pre-fixed levels of reliability while fitting the expected growth and development of the system in the long term.
For more information please contact: Anna Palla, anna.palla@unige.it; Ilaria Gnecco, ilaria.gnecco@unige.it
Link to the group or personal webpage: -
References:
o Mei, C., Liu, J., Wang, H., (...), Ding, X., Shao, W. Integrated assessments of green infrastructure for flood mitigation to support robust decision-making for sponge city construction in an urbanized watershed. Sci. Total Environ., 2018, 639, 1394-1407.
o Palla, A., Gnecco. I. On the Effectiveness of Domestic Rainwater Harvesting Systems to Support Urban Flood Resilience. Water Resource Management, 2022, 36(15), 5897–5914.
o Palla, A., Gnecco, I. The web-gis TRIG eau platform to assess urban flood mitigation by domestic rainwater harvesting systems in two residential settlements in Italy. Sustainability, 2021, 13(13), 7241.
Research topic F
Title: Participatory Approach to Planning Urban Resilience to Climate Change
Proposers: Francesca Pirlone, Anna Palla, Fabrizio Bracco
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description:
The planning of urban resilience to climate change is addressed with particular attention to the pluvial flooding risk. The adoption of the methodologies typical of participatory processes capable of involving different stakeholders with different techniques (quantitative and qualitative), both in person and online are here foreseen in order to define effective strategies at the levels. The main objective of the present research is to develop a participatory/experiential georeferenced mapping (in GIS) for the planning of urban resilience to climate change. The participatory/experiential georeferenced mapping will be implemented in the city of Genoa for specific case study areas. This research stands out for the important inter-disciplinarity approach of the methodology and subsequent application; the involved interdisciplinary sectors (represented by proposers) are: urban planning, hydrology, and psychology/training science.
For more information please contact: francesca.pirlone@unige.it, anna.palla@unige.it, fabrizio.bracco@unige.it
Link to the group or personal webpage:
https://rubrica.unige.it/personale/UkNGWllr
https://rubrica.unige.it/personale/UkNHWlph
https://rubrica.unige.it/personale/UkNGWVht
References:
o Gnecco, I. Pirlone, F., Spadaro, I.; Bruno, F.; Lobascio, M.C.; Sposito, S.; Pezzagno, M.; Palla, A. Participatory Mapping for Enhancing Flood Risk Resilient and Sustainable Urban Drainage: A Collaborative Approach for the Genoa Case Study. Sustainability, 2024, 16(5), 1936
o Palla, A., Pezzagno, M., Spadaro, I., Ermini, R. Participatory Approach to Planning Urban Resilience to Climate Change: Brescia, Genoa, and Matera—Three Case Studies from Italy Compared. Sustainability (Switzerland), 2024, 16(5), 2170.
o Coppola I., Fiscone C., Bracco F., Rania N. Participative and conscious learning: an active teaching experience with university students. ICERI2023 Proceedings, 2023
Research topic G
Title: Structural Stability, Risks, Consolidation, and Utilization of Archaeological Sites
Proposers: Stefano Podestà and Chiara Calderini
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description: Archaeological sites are invaluable cultural heritage assets that provide insights into past civilizations and human history. However, these sites are often vulnerable to various risks that threaten their structural stability. Factors such as natural decay, environmental conditions, and human activities can cause significant deterioration. This research project aims to investigate the structural stability of archaeological sites, identify the associated risks, develop consolidation methods, and enhance their utilization for educational and tourism purposes.
Objectives:
· Assess the Structural Stability: To evaluate the current structural stability of selected archaeological sites using advanced techniques such as laser scanning, ground-penetrating radar, and photogrammetry.
· Identify Risks: To identify the primary risks affecting these sites, including environmental factors (weathering, erosion, seismic activity), biological factors (vegetation growth, animal activities), and human factors (vandalism, tourism impact).
· Develop Consolidation Methods: To explore and develop effective consolidation and conservation techniques that can enhance the structural integrity of archaeological sites without compromising their historical value.
· Promote Utilization: To propose sustainable strategies for the utilization of these sites, balancing conservation needs with public access and educational opportunities.
Expected Outcomes:
· A set of recommendations for effective consolidation techniques tailored to each site.
· Sustainable utilization plans that can be implemented by site managers and local authorities.
· Increased awareness and engagement from the public regarding the preservation of archaeological heritage.
Conclusion
By focusing on the structural stability, risks, consolidation, and utilization of archaeological sites, this research project aims to contribute to the long-term preservation and appreciation of our shared cultural heritage. The findings and recommendations will provide valuable insights for archaeologists, conservationists, and policymakers, ensuring that these irreplaceable sites can be enjoyed by future generations.
For more information please contact: Stefano Podesta, stefano.podesta@unige.it
Link to the group or personal webpage: https://rubrica.unige.it/personale/UkNHX1Nr
References:
Petrović, I, Ilic I, Sokolovic N., Šekularac N., (2021). Design of Protective Structures for Active Archeological Sites, Conference: 12th International Conference on Structural Analysis of Historical Constructions, DOI:10.23967/sahc.2021.074
C. Modena, F. da Porto, M.R. Valluzzi, M. Munari, Criteria and technologies for the structural repair and strengthening of architectural heritage. Int J 3R (Rep Rest Renew Built Env) (2013) 4 (3): 606-621.
Charter of Venice, International charter for the conservation and restoration of monuments and sites. Decision and resolutions. ICOMOS, Paris, 1964.
Research topic BF1
Grant cofunded by MUR/ Department DICCA
Title: Enhancing the efficiency of structural monitoring in assessing the seismic damage of strategic buildings
Proposers: Serena Cattari
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description: There is a growing search for cutting-edge technologies to enable effective and large-scale management of structures in urban contexts. Structural monitoring has gained great importance in this field, by allowing real-time assessment of the health conditions of structures and infrastructures based on robust experimental vibration data, giving rise to the established field of Structural Health Monitoring (SHM). The potential of such data is emerging also in the context of Seismic Structural Health Monitoring (S2HM) (Limongelli et al. 2019). In this context, the Italian Seismic Observatory of Structures (OSS), established in the mid-1990s, stands out as a significant achievement in the field of seismic and structural monitoring. The network monitors today more than one hundred and seventy strategic structures across the national territory.
This research project aims to advance S2HM techniques for existing buildings by exploiting also the data available from this network. Available will be used not only to deepen the response of single structures but also to outline a prototypal database to interpret phenomena (such as frequency co-shift, floor amplification seismic actions, …) and corroborate evidences on a large set of buildings.
The research methodology intends adopting multiple tools to interpret the seismic response of monitored structures such as: data driven approaches; machine-learning algorithms; and physic-based surrogate models that make use of numerical models. The final goals is to develop effective tools for assessing the damage and supporting also usability assessment crucial in the aftermath of seismic events.
For more information please contact: Serena Cattari, serena.cattari@unige.it
Additional information: the research presupposes a strict interaction with the Italian Seismic Observatory of Structures and also the collaboration with the LUNITEK company.
Link to the group or personal webpage:
Serena Cattari personal webpage: https://rubrica.unige.it/personale/UkNHUl5s
References:
o Spina D, Lamonaca B, Nicoletti M, et al (2011) Structural monitoring by the Italian Department of Civil Protection and the case of 2009 Abruzzo seismic sequence. Bulletin of Earthquake Engineering 9(1):325 – 346. https://doi.org/10.1007/s10518-010-9232-4
o Dolce M, Nicoletti M, De Sortis A, et al (2017) Osservatorio sismico delle strutture: the Italian structural seismic monitoring network. Bulletin of Earthquake Engineering 15(2):621 – 641. https://doi.org/10.1007/s10518-015-9738-x
o Limongelli MP, Dolce M, Spina D, et al (2019) S2HM in some European countries. Springer Tracts in Civil Engineering p 303 – 343. https://doi.org/10.1007/978-3-030-13976-6 13
o Sivori D, Cattari S, Lepidi M (2022) A methodological framework to relate the earthquake-induced frequency reduction to structural damage in masonry buildings. Bulletin of Earthquake Engineering 20(9):4603 – 4638. https://doi.org/10.1007/s10518-022-01345-8
o Garcıa-Macıas E, Ierimonti L, Venanzi I, et al (2021) An Innovative Methodology for Online Surrogate-Based Model Updating of Historic Buildings Using Monitoring Data. International Journal of Architectural Heritage 15(1):92 – 112. https://doi.org/10.1080/15583058.2019.1668495
o Garcıa-Macıas E, Hernandez-Gonzalez I, Puertas E, et al (2024) Meta-Model Assisted Continuous Vibration-Based Damage Identification of a Historical Rammed Earth Tower in the Alhambra Complex. International Journal of Architectural Heritage 18(3):427 – 453. https://doi.org/10.1080/15583058.2022. 2155883
o Astorga AL, Gueguen P, Rivi`ere J, et al (2019) Recovery of the resonance frequency of buildings following strong seismic deformation as a proxy for structural health. Structural Health Monitoring 18(5-6):1966 – 1981. https://doi.org/10.1177/1475921718820770
o Astorga, A., Guéguen, P., Ghimire, S. et al. NDE1.0: a new database of earthquake data recordings from buildings for engineering applications. Bull Earthquake Eng18, 1321–1344 (2020). https://doi.org/10.1007/s10518-019-00746-6
Research topic BF2
grant funded within D.M. 630 dated 24.4.2024 (co-funded by ETT S.p.a)
Title: Automatic crack detection from images, participatory digital tools and machine learning algorithms to support the seismic damage interpretation of existing buildings
Proposers: Bianca Federici, Serena Cattari, Antonio Novellino and Luca Oneto
Curriculum: Risk and Resilience Engineering for the Natural, Industrialized and Built Environments
Description:
In recent years, several research projects have been launched aimed at automatically processing images for the interpretation of structural damage: so far, the applications are mostly found in tools that can support structural monitoring activities on individual artifacts.
The proposed project aims to develop a methodology to support the interpretation of damage of existing buildings in the aftermath of seismic events exploiting the potential of new technologies and tools, such as automatic crack detection from images, participatory digital tools and machine learning algorithms. The research intends supporting the attribution of synthetic damage levels at scale of single assets with the final goal to improve also the assessment of seismic impact at urban scale.
The attention will be focused either on monumental assets, such a churches, and residential buildings.
Advanced survey techniques will be used, including photogrammetry from drone and laser scanner with SLAM (Simultaneous Localization and Mapping) technology. A crack detection model has been recently developed by the UniGE research group using a deep learning model, the Convolution Neural Network, applied to images relative to churches; the same or other models could be applied to other typologies of existing buildings.
Images will be automatically interpreted to identify cracks and their geometric characteristics, i.e. length and width. Then, appropriate tools will be developed to determine the cracks position in the 3D space or on a plan or façade orthophoto, for supporting the interpretation at the scale of single assets. The potential of machine learning algorithms will be adopted to elaborate large dataset of data (either available from real seismic events or numerically generated by other research experiences) and to address the design of dedicated dashboard useful to support engineers in the attribution of synthetic damage levels (Cattari and Angiolilli 2022).
At urban scale, the images, and therefore the identified damages, will then be georeferenced to be automatically managed in a Geographic Information System (GIS) for mapping the consequences of the seismic shaking. Participatory digital tools (like MUST : https://ettsolutions.com/progetti/must/) will be explored and further developed to speed up and integrate the acquisition of damage information with the aim of supporting the rapid collection of data that are also useful to update and validate damage scenario estimated from mechanical/empirical approaches.
For more information please contact: Bianca Federici, bianca.federici@unige.it Serena Cattari, serena.cattari@unige.it
Link to the group or personal webpage:
Bianca Federici personal webpage: https://rubrica.unige.it/personale/UkNHWV5q
Serena Cattari personal webpage: https://rubrica.unige.it/personale/UkNHUl5s
References:
o Cattari, S., Angiolilli, M. Multiscale procedure to assign structural damage levels in masonry buildings from observed or numerically simulated seismic performance. Bull Earthquake Eng 20, 7561–7607 (2022). https://doi.org/10.1007/s10518-022-01504-x
o Golding, V.P.; Gharineiat, Z.; Munawar, H.S.; Ullah, F. Crack Detection in Concrete Structures Using Deep Learning. Sustainability 2022, 14, 8117. https://doi.org/10.3390/su14138117.
o Munawar, H. S., Ullah, F., Heravi, A., Thaheem, M. J., & Maqsoom, A. (2022). Inspecting Buildings Using Drones and Computer Vision: A Machine Learning Approach to Detect Cracks and Damages. Drones, 6(1), 5. https://doi.org/10.3390/drones6010005
o Rezaie, A.; Achanta, R.; Godio, M.; Beyer, K. Comparison of crack segmentation using digital image correlation measurements and deep learning. *Construction and Building Materials*, 261, 120474 (2020). https://doi.org/10.1016/j.conbuildmat.2020.120474
o Giacco, G., Mariniello, G., Marrone, S., Asprone, D., Sansone, C. (2022). Toward a System for Post-Earthquake Safety Evaluation of Masonry Buildings. In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13232. Springer, Cham. https://doi.org/10.1007/978-3-031-06430-2_26