Conference Agenda

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Session Overview
Session
1.5 Recent advances in engineering geology and geohazards modelling
Time:
Wednesday, 26/Aug/2020:
10:20am - 12:20pm

Location: Room 2.01

Session extended with 15 min.


Session Abstract

by Anika Braun & Tomas Fernandez-Steeger

Technische Universität Berlin, Germany

The session addresses recent research and studies in the field of engineering geology and geohazards modelling. We welcome in particular the applied research of students, young professionals and early career scientists. First results and findings from recent projects as well as challenges and solutions from industry or consulting projects showing the relevance of geoscience for engineering solutions are welcomed.


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Presentations
10:20am - 10:35am
ID: 184
Invited Virtual Presentation | Keynote

Landslide models and Dam sites visualised in VR

Hans-Balder Havenith

Liège Université, Belgium

For multiple landslide and two dam sites in Central Asia and SE Europe we have completed geophysical surveys (partly) complemented by borehole drilling. These data were first processed and then compiled within a 3D geomodel. Here, we present the geophysical results and the 3D geomodels adapted for visualisation in an immersive virtual environment. The geophysical surveys included electrical and seismic profiles and ambient vibration measurements as well as earthquake recordings. The electrical and seismic data were processed as tomographic sections and analysed with the MASW method (analysis of surface waves), the ambient vibrations as horizontal-to-vertical spectral H/V ratios, and the earthquake data mainly in terms of standard spectral
ratios. For most sites, we computed the local soft layer thickness from the resonance frequencies revealed by the H/V ratios. Earthquake data allowed us to compute site amplification factors for the more or less thick soft material layer on the slope, or for the dam structure. The 3Dgeomodel was first built on the basis of topographic data, satellite imagery, as well as various electrical resistivity and seismic refraction tomographies.
The soft layer thickness information and borehole data were represented in terms of logs in the model (later interpolated to form volumes).

The large Rogun dam site studied in Tajikistan is crossed by the Ionakhsh Fault that could be modeled on the basis of the geological inputs and of a lateral resistivity gradient found on one electrical profile along the steep lower slope.

Numerical models were computed for the largest landslide sites and for a blast-fill dam in Kygyzstan (for which also piezometric data were available). Earthquake shaking was simulated as most sites are located in seismically active regions.

Havenith-Landslide models and Dam sites visualised in VR_Info.pdf


10:35am - 10:50am
ID: 141
Virtual Presentation

ARTIFICIAL INTELLIGENCE AS TOOL TO PREDICT GEOHAZARDS: READINESS TO ACCEPT AND IMPLEMENT

Shrawani Shagun Jha

Mody University of Science and Technology, India

Geological hazards or Geohazards, natural or human-induced disruptions of the earth surface that may trigger landslides, sinkholes, or earthquakes, present serious threats to communities, cost extensive damage to infrastructure and can bring traffic and services to a standstill. Recent climatic changes have increased the intensity of rainfall and raised mean temperature, increasing hydrological hazards, such as debris or earth flows, erosion, and floods. India has 2% of the total land area of the world but supports more than 17% of global population. Due to diverse geological environment and geodynamic processes, the country faces several types of Geohazards including earthquakes, landslides, tsunami, glacial lake outburst floods, and environment adversely. Due to changing climatic conditions, the incidences and impacts of these Geohazards are increasing. Keeping the above context in mind, the national disaster management authority in India has made attempts to assess the types and levels of these disasters that affected the country in the past . Speculations and predictions with regard to Geohazards are not easy due to their complex behavior in the real human world. In recent time, several aspects of these environmental applications are considered in computer-based modeling to accurately estimating real-world phenomena. However, none of the proposed methods have reached to zero uncertainties or errors to recognize the entire disaster’s events but their importance cannot be denied. It is important to detect, monitor and predict them to protect the inhabitants against the potential natural hazards that threaten human lives and properties. Artificial Intelligence as a tool is proposed that can see different aspects of a complex problem with sufficient iteration and details. In recent years, implementation of AI models coupled with geospatial information systems (GIS) are the most efficient and accurate approach to model natural disasters i.e. flooding, earthquake, landslides, forest fire and drought rather than other existing methods. This gives an insight into the ability of applied AI models in some natural hazards applications.

The paper is proposed to discuss the national initiatives with particular reference to earthquakes and landslides with a view to share and exchange the experiences in disaster risk reduction. How it had helped in learning good and bad practices for promoting disaster resistant / resilient development and nurturing a culture of risk avoidance, prevention, mitigation and preparedness at global level? Recently, Artificial Intelligence (AI) methods have received a great deal of attraction due to their precision to model the complex problems such as natural hazards. How helpful has been professional geologists and engineers and how much have been contributed greatly towards better scientific understanding of the Geohazards and formulating effective plans for safer sustainable development, is proposed to be analysed further in detail in paper.

Jha-ARTIFICIAL INTELLIGENCE AS TOOL TO PREDICT GEOHAZARDS_Info.pdf


10:50am - 11:05am
ID: 122
Virtual Presentation

Using Artificial Intelligence for Disaster Management & Providing Relief

Niteesh Kumar Upadhyay1, Mahak Rathee2

1Assistant Professor of Law, Galgotias University, India; 2Advocate, Supreme Court of India

We have seen drastic growth of Artificial Intelligence in the past few years and what seemed to be a distant dream earlier is now becoming a reality. Though there are a lot of debates on Artificial Intelligence and its use, its legality and much more but Artificial Intelligence can prove to be an asset in the field of Disaster Management and providing relief. There have been many instances wherein a lot of loss in terms of human lives, property and economy of the nation is being caused because of a disaster and it takes time to analyse the situation and provide relief. This problem can be solved if we are able to successfully create an Artificial Intelligence program or machine which can provide quick analysis of the situation, rescue human beings who are stuck and also the reconstruction of the infrastructure which has been damaged can be done more quickly as compared to human labour. One important factor is that use of Artificial Intelligence will save a lot of time in providing relief and hence will mitigate the loss suffered to some extent. The authors will be dealing with the growth of Artificial Intelligence in the past few years, role that AI can play in disaster management and various tasks which can be done by Artificial Intelligence in Disaster management and providing relief.



11:05am - 11:20am
Cancelled
ID: 285
Virtual Presentation | ECS

CANCELLED | Investigation of approaches for rockfall susceptibility mapping in the Elbtalgraben using methods of machine learning

Felix Schumann

Technical University of Berlin, Germany

Mass movements are among the most widespread natural hazards in Central Europe. Due to their mostly regionally limited occurrence, they are rarely noticed by the public. Susceptibility maps are produced to detect and counteract mass movements and to determine their spatial distribution. In this study, approaches for the analysis of rockfall susceptibility in the sub-area of the Elbtalgraben in Saxony were developed.
Rockfalls represent the dominating process of mass movements in the study area. The aim of this study was to develop approaches of spatial representation of rockfalls for susceptibility analysis using Artificial Neural Networks (ANN). Furthermore[HS1] [HS2] [HS3] , the parameters that form the basis for a robust and meaningful susceptibility analysis were determined.
For the spatial discretization of the rockfalls, a circle with a 25m radius was drawn around each rockfall and furthermore, two variants of slope units were created. For each spatial discretization three different susceptibility models were created using ANN and compared with each other. Afterwards, a parameter analysis was performed. All models identified the known rockfall prone areas, like the Elbsandsteingebirge. In addition, further areas with a high probability of rockfall occurrence were identified. The different spatial discretization had only little influence on the result of the analysis. The most accurate susceptibility maps were obtained using the circular spatial discretization. The most important parameters turned out to be slope, landform, profile curvature, lithology, 1st aquifer, hydraulic conductivity and precipitation.



11:20am - 11:35am
ID: 339
Virtual Presentation

Landslide susceptibility mapping on the country scale with data mining techniques in Armenia

Agnieszka Ledworowska1, Anika Braun1, Hans-Balder Havenith2, Tomás Manuel Fernández-Steeger1

1Engineering Geology, Technische Universität Berlin, Germany; 2Department of Geology, University of Liège, Belgium

Armenia is a country strongly affected by landslides, but still not enough research has been done on landslide susceptibility in this area. Therefore, the main goal of the study was to create one of the first landslide susceptibility zonation maps covering the entire territory of Armenia. Two different data mining techniques for landslide susceptibility analysis were applied: artificial neural networks (ANN) and C5.0 decision trees (C5.0). Created landslide susceptibility maps showed that the C5.0 models are rather not applicable for susceptibility analysis due to strong overfitting and artifacts caused by pruning. The ANN models provided significantly better results than C5.0 models. Though, they still need to be improved. Another goal of the study was to investigate the influence of landslide inventory on susceptibility analysis. For that reason, two different landslide catalogs were used for the analysis: the GEORISK inventory (2004) based on aerial photographs and field surveys provided by GEORISK Scientific Research Company and MATOSSIAN inventory (2017) based on satellite imagery created by Matossian (2017). Susceptibility zonation maps created using ANN models based on MATOSSIAN catalog showed better performance than models based on GEORISK catalog. This observation was rather unexpected, because MATOSSIAN catalog contains only half as much landslides as GEORISK inventory. However, the main difference between these two inventories is the absence of landslides in a large volcanic region (the Aragats region) in MATOSSIAN inventory. In this regard, it was suggested that this area might negatively influence the results and should be excluded for further investigations.

References: Matossian, A. (2017). Identification of giant mass movements in the Lesser Caucasus and assessment of their spatial relationship with major fault zones and volcanoes. Master’s thesis. University of Liège.

Braun-Landslide susceptibility mapping on the country scale with data mining techniques_Info.pdf


11:35am - 11:50am
ID: 220
Virtual Presentation | ECS

THM Experiment for the Investigation of Freeze-Thaw Processes in Unconsolidated Rock and Geotechnical Grouts

Jan Christopher Hesse1,2, Jan-Henrik Kupfernagel3, Markus Schedel1,2, Bastian Welsch1,2, Lutz Müller3, Ingo Sass1,2

1Technical University of Darmstadt, Geothermal Science and Technology, Darmstadt, Germany; 2Darmstadt Graduate School of Excellence Energy Science and Engineering, Darmstadt, Germany; 3Technische Hochschule Ostwestfalen-Lippe, FB 8, Geotechnics and Geothermal Energy, Höxter, Germany

Freezing and thawing in the subsurface is often associated with a complex technical handling of possible influences on the engineered structures (e.g. ground freezing, permafrost, geothermal heat pumps). However, detailed knowledge on freeze-thaw processes in porous media, such as unconsolidated rocks or geotechnical grouts, is still pending.

Freezing in porous media does not occur as a sudden transition from pure liquid water to the ice phase, but rather within a freezing interval strongly depending on various boundary conditions such as soil type or pore water chemistry. As the content of frozen and unfrozen water has a strong impact on material properties, it is essential to have adequate information about the different factors influencing freezing processes as well as the thermo-hydraulic-mechanical (THM) effects on porous media due to phase change.

Therefore, a THM laboratory experiment was designed and built to gain more detailed knowledge on freeze-thaw processes and their effects in porous media. A modified triaxial test, enabling for a confining pressure up to 1.2 MPa, is linked with an ultrasonic measurement device to determine the unfrozen water content at defined boundary conditions. The confining pressure fluid (water-glycol-mixture) can be tempered via a cooling circuit down to -25 °C. Axial and radial deformation of the specimen are measured as well as further mechanical parameters such as the freeze pressure. Furthermore, the hydraulic conductivity of the sample is determined to investigate the influence of water flow on the freezing process.

Hesse-THM Experiment for the Investigation of Freeze-Thaw Processes_Info.pdf


11:50am - 12:05pm
ID: 230
Virtual Presentation | ECS

Impact of Freeze-Thaw Cycles on hydraulic conductivity of Borehole Heat Exchangers

Jan-Henrik Kupfernagel1,2, Jan Christopher Hesse2, Bastian Welsch2, Markus Schedel2, Ingo Sass2, Lutz Müller1

1Technische University of Applied Science Ostwestfalen-Lippe, Germany; 2Technical University of Darmstadt, Germany

For several reasons, the inlet temperature of the heat carrier fluid in borehole heat exchangers (BHE) may temporarily fall below the freezing point of water. Consequently, freezing and thawing processes are induced in the grouting material and the surrounding subsoil. However, these processes also influence the transition zonecontact area between pipes and grout as well as the skin zone between the grout and the undisturbed subsoil. This can lead to significant impairment damage of the grouting material or the subsoil structure and cause detachment phenomena between the pipe and the grout or in the skin zone. As a result, the hydraulic integrity of the system cannot be sustained and possible secondary flow paths may occur.

Previous research on this issue focused on the grout only or on the compound simplified system of grout and BHE-pipes, but completely omitted the subsoil as well as the skin zone. For this reason, a large-scale experiment was developed, which allows for a simulation of freeze-thaw cycles, considering a realistic BHE configuration of a double-U-Pipe embedded in a grout cylinder and surrounded by compacted soil material. During the experiment, the hydraulic conductivity and temperature distribution areis measured constantly.

The experimental results illustrate the extent of freeze-thaw damage processes under in situ conditions., Furthermore, the transition zonecontact area between the pipes and the grout material is clearly identified as the major weak point of the system compound. The findings are used to develop improvement measures in order to maintain the integrity of the system even under the impact of numerous freeze-thaw cycles.

Kupfernagel-Impact of Freeze-Thaw Cycles on hydraulic conductivity of Borehole Heat Exchangers_Info.pdf


12:05pm - 12:20pm
ID: 148
Virtual Presentation | ECS

Assessing sediment accumulation at inundated anthropogenic marshland in the southern North Sea: Using turbidity measurements and particle tracking

Ingo Jürgen Hache1, Sebastian Niehüser2, Volker Karius1, Arne Arns3, Hilmar von Eynatten1

1University of Göttingen, Geoscience Center (GZG), Department of Sedimentology and Environmental Geology, Goldschmidtstraße 3, 37077 Göttingen, Germany; 2University of Siegen, Research Institute for Water and Environment, Paul-Bonatz-Straße 9-11, 57076 Siegen, Germany; 3University of Rostock, Faculty of Agricultural and Environmental Sciences, Justus-von-Liebig-Weg 6, 18059, Rostock, Germany

New approaches to coastal protection measures become increasingly important to protect for or to mitigate sea level rise (SLR) worldwide. Measures that involve only the heightening of dykes or revetments are prone to disturb the natural adaptation capacity especially of shallow marine tidal systems and adjacent marshlands. This applies to ten island-like marsh areas called Halligen in the southern North Sea, Germany. Here, the adaptation potential depends on the accumulation of suspended particulate matter (SPM) during annually occurring inundations that generates relevant vertical accretion rates. According to previous studies, todays accretion rates are too low to keep pace with SLR. To invoke appropriate strategies to mitigate the imbalance it is crucial to know whether the particle accumulation is material limited (i.e. there is not sufficient SPM available in the water column around the Halligen) or transport-limited (i.e. SPM is available but not transported efficiently onto the Halligen). In this study we assessed the spatial and temporal distribution of SPM at the largest Hallig Langeness with an autonomous working turbidity measurement system. Recorded inundation events covered a wide range of water levels resulting from moderate wind conditions to storm surges. We were able to quantify the impact of the existing coastal protection measures on present sediment accumulation rates. A detailed numerical sediment transport model of the Hallig and its surrounding tidal flats was used to simulate the effect of various height adjustments of revetments in different hydrodynamic scenarios.

Hache-Assessing sediment accumulation at inundated anthropogenic marshland_Info.pdf


12:20pm - 12:35pm
ID: 239
Virtual Presentation

Parameters for the design of HDD installed power cables in soil and rock

Ingo Sass1,2, Maximilian Eckhardt1, Markus Schedel1,2

1Technical University of Darmstadt, Geothermal Science and Technology, Darmstadt, Germany; 2Darmstadt Graduate School of Excellence Energy Science and Engineering, Darmstadt, Germany

When operating buried power cables, the mechanical and thermal properties of the cable bedding need to meet certain requirements. On the one hand, positioning and protection of the cable and protection pipe from mechanical stress demand mechanical stability. On the other hand, electric losses during transmission result in thermal energy that needs to be dissipated. Since the ampacity of the cable depends on the maximum permissible temperature of the conductor, the potential load of the power line is directly connected to the thermal properties of the bedding. To avoid accelerated aging or even damaging of the cable, an adequate assessment of the cable bedding is essential to ensure a safe long-term operation within the mechanical and thermal limits.

While an underground cable route is typically realized using cable trenches, intersection points with existing infrastructure (e.g. roads, railway network, inland waters) need to be crossed under using engineering methods like horizontal directional drilling (HDD). Since one segment of the cable route with poorer bedding properties would reduce the potential load of the whole power line, the backfill materials used to fill the space between protection pipe and borehole wall also have to be designed to meet the requirements mentioned.

In this contribution, laboratory investigations are discussed, which can be used for the design of adequate backfill materials considering important subsoil properties.

Sass-Parameters for the design of HDD installed power cables_Info.pdf


 
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