•A neural network is developed as a surrogate tool fed by a numerical dataset.•PSO utilizes monitoring data to estimate most probable rheological parameters.•The methodology is validated on two ...adjacent tunnels in karstic rock mass.•Numerical results agreed well with the long-term monitored settlements.
The continuous monitoring of long-term performance of tunnels constructed in soft rock masses shows that the rock mass deformations continue after construction, albeit at a rate that reduces with time. This is in contrast with NATM postulates which assume deformation stabilizes shortly after tunnel construction. This paper proposes the prediction of long-term vertical settlement performance of a tunnel in soft rock mass, through the inclusion of a Burger’s creep viscous-plastic constitutive law to model post-construction deformations. To overcome issues related to the complex characterization of this constitutive model, a neural network NetRHEO is developed and trained on a numerically obtained dataset. A particle swarm algorithm is then employed to estimate the most probable rheological parameter set, by utilizing the long-term in-situ monitoring data from several observation points on a real tunnel. The paper demonstrates the potential of the proposed methodology, using displacement measurements of two adjacent tunnels in karstic rock mass in Croatia. The complex interaction of a railway tunnel Brajdica and a road tunnel Pećine, conditioned by the character of the surrounding rock mass as well by the chronology of their construction, was evaluated to predict the future behavior of these tunnels.
Levees are linear structures that are continuously reconstructed throughout the years and whose construction and behavior depends on local soil conditions, as well as requirements regarding ...impermeability and mechanical resistance. This results in various levee cross sections, even within the same levee. In situations of extreme water events, when timely actions are required, this variability poses a problem for decision-making based on observed behavior, which is highly dependent on the specific section parameters. Creating models for each problematic section becomes impractical, and because of that, in this study, 91 different cross sections from 16 levees are considered to identify the key levee parameters with the largest effects on three observed mechanisms: deformations, exit hydraulic gradients, and factors of safety. The implemented factor screening methodology is based on the sequential bifurcation method (SB) and numerical analyses. The SB method successively investigates groups of factors and uses their cumulative effects to identify the important groups and to discard the unimportant based on a previously selected parameter Δ, until the groups are reduced to single factors that may be deemed important. It is found that approximately 30% of all the factors used to describe the most complex sections are considered important by at least one of the investigated mechanisms.
To identify the unknown values of the parameters of Burger's constitutive law, commonly used for the evaluation of the creep behavior of the soft soils, this paper demonstrates a procedure relying on ...the data obtained from multiple sensors, where each sensor is used to its best advantage. The geophysical, geotechnical, and unmanned aerial vehicle data are used for the development of a numerical model whose results feed into the custom-architecture neural network, which then provides information about on the complex relationships between the creep characteristics and soil displacements. By utilizing InSAR and GPS monitoring data, particle swarm algorithm identifies the most probable set of Burger's creep parameters, eventually providing a reliable estimation of the long-term behavior of soft soils. The validation of methodology is conducted for the Oostmolendijk embankment in the Netherlands, constructed on the soft clay and peat layers. The validation results show that the application of the proposed methodology, which relies on multisensor data, can overcome the high cost and long duration issues of laboratory tests for the determination of the creep parameters and can provide reliable estimates of the long-term behavior of geotechnical structures constructed on soft soils.
In this paper a modification of the reliability-based robust geotechnical design (RGD) method is proposed. The intention of the proposed modifications is to simplify the method, make it less ...computationally expensive, and harmonise of the results with Eurocode 7. The complexity of the RGD method mainly stems from the calculation of the design’s robustness measure, which is the feasibility robustness index (ββ). Due to this fact, the replacing of the existing robustness measure with a generalised reliability index (β) is considered. It was demonstrated that β fits into the robustness concept, and is traditionally used as a construction reliability measure, making it intuitive and “user friendly”. It is proposed to conduct a sensitivity analysis using Soboli indices, with the aim of freezing the variables whose contribution to the system response variance is negligible, which will further simplify the method. By changing the robustness measure, the number of the required reliability analyses is significantly decreased. Further reduction is achieved by conducting analyses only for the designs chosen in the scope of the genetic algorithm. The original RGD method is used as an extension of traditional reliability-based design. By applying the proposed modifications, the RGD method can be used as an alternative to the classic and reliability-based design method.
This paper offers a solution to overcome time-consuming numerical analysis for the evaluation of the impact of tunnel construction in a complex karst environment by implementing Monte Carlo ...Simulation (MCS) using a neural network (NN) tool. The rock mass is described using three parameters: Geological Strength Index, the uniaxial compression strength of the intact rock, and the Hoek–Brown parameter for the intact rock m
i
. By using their probabilistic distribution as an input, a developed neural network NetTUNN produces probabilistic distributions of tunnel crown displacement, rock bolt axial load, and shotcrete uniaxial compression stress. A full MCS is then applied on these NetTUNN outputs to determine the reliability index and probability of failure for the relevant limit states. To demonstrate the potential of NN in tunnel design, a case study of Tunnel Pećine in Croatia is used, where the NetTUNN-assisted MCS assessment served as a benchmark to evaluate approximate reliability assessment techniques. It was shown that the developed NN can be used as an accurate surrogate model for determination of probabilistic distributions of tunnel design parameters. Further, it was shown that approximate reliability assessment techniques generally overestimate the reliability index and underestimate the probability of failure when compared to the NetTUNN-assisted MCS.
When constructing flood protection structures such as river levees, oftentimes due to various factors engineers must design composite structures, i.e., reinforced earthen structures which comply with ...all the stability criteria. The most common way of reinforcing such structures is the usage of geosynthetics, or mostly geogrids when talking about stability. Since geosynthetics are man-made materials produced in a controlled environment and go through quality control measures, their characteristics contain a negligible amount of uncertainty compared to natural soils. However, geosynthetic handling, their installation in the levee, and their long-term degradation can all have significant effects of variable magnitude on geosynthetic characteristics. These effects and their variability can be considered as random variables, which can then be used in probabilistic analyses together with soil properties. To investigate the effects of the geogrid’s resistance variability on slope stability compared to soil properties variability, probabilistic analyses are conducted on a river levee in northern Croatia. It is found that the geogrid’s variability generally has very little effect on the total uncertainty compared to the friction angle’s variability, but out of the three geogrid layers used the top grid has the most influence.
This paper proposes the framework for automatic calculation of secondary lining cracks remediation costs. A study focuses on the structural cracks resulting from the tunnel secondary lining ...overloading due to rock mass creep. It is based on the multi-phase workflow combining the on-site measurements of behavior of the rock mass surrounding the tunnel and advanced numerical modelling tools assisted by the custom custom-made neural network, as well as the cost calculations. The workflow is established through the developed TunnCrack LCC platform where the data communication protocols between phases provided the straightforward and automatic data flow. Based on the evaluated long-term behavior of a tunnel, the secondary lining crack repair cost could be calculated for the different crack widths. The established platform presents a step forward in proactive estimation of the secondary lining remediation costs, where the monitoring data is continuously used to enhance the estimates of the crack repair costs, providing the tunnel managers with information on lining remediation life cycle costs, thus easing the overall decision-making process.
•A framework for automatic calculation of secondary lining cracks remediation costs is presented•TunnCrack LCC platform backbone is in on-site monitoring data which feeds into advanced numerical models•Neural network is used to estimate the most probable rheological set so that long-term behavior of rock mass is identified•Long-term rock mass behavior is utilized to calculate the long-term costs of secondary lining remediation•Proactive assessment of lining cracking assists in maintenance of a secondary lining throughout the tunnel's service life
Levees are embankments designed for passive flood protection. In order to reduce the potential of climate-induced flooding risks, it is necessary to reconstruct or upgrade the existing levees. Flood ...risk management aims to reduce the probability of floods and their potential adverse effects on the population, economy, and environment. This paper presents the novel application of reliability analysis for risk ranking in the Otok Virje-Brezje levee reconstruction project in the Republic of Croatia. To identify, verify and analyse key risks, a group of 35 experts, who were directly involved in the levee reconstruction project or have extensive experience in similar projects, was selected. An Analytic network process (ANP) was used for group multi criteria decision-making. Quantitative and qualitative approaches to risk analysis were combined. Different experts from the various organisations may have diverse interests and goals. The geometric mean method was chosen to reach group consensus. The resources that will be allocated to the risk responses are proportional to the risk exposures. To analyse the reliability of the group consensus-reaching method a determination of the risk ranking probability matrix is proposed by using the Monte Carlo simulation method. Different decision-making approaches are proposed for cases in which consensus is not reached with satisfactory reliability.
The most recent major earthquake series struck near Petrinja (December 29th 2020 M 6.2), and triggered extensive ground failures in the wider area of Petrinja, Sisak and Glina. Coseismic ground ...failures including subsidence dolines, liquefaction and landslides have been documented over a large area by various experts and teams. These data are stored in the newly created inventory, which is openly presented in this paper. This inventory is administered and updated by the Croatian Geological Survey, and will be available online via a Web Map Service (WMS) (www.hgi-cgs.hr). The aim of the inventory is to not only provide data for the development of susceptibility maps and more detailed exploration for possible remediation measures, but also to define the priorities for immediate action. The earthquake triggered the rapid development of dropout dolines which endanger the local populations of the villages of Mečenčani and Borojevići. This is still an ongoing process in the vicinity of the houses and therefore in-situ exploration started immediately. Liquefaction related to alluvial sediments of the Sava, Kupa and Glina rivers occurred almost exclusively in loose and pure sands, and was accompanied by sand boils, subsidence and lateral spreading. Liquefaction also presents a greater hazard because settlement of houses and river embankments occurred. Lateral spreading caused failures of river flood embankments and natural river banks. According to the data known to date, the majority of the coseismic landslides were reactivated with minor displacements. Despite that, it has been recognised that houses at the edge, or in landslide colluvium suffered greater damage than other houses located outside the landslide impact zone.
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