## 7 Conclusions  
This paper highlights the potential of an automated parameter determination (APD) framework that employs a graph-based methodology to derive parameters from in situ tests. This approach is particularly beneficial in the early stages of a project when soil data may be limited. During this phase, cost-effective field tests such as CPT and DMT are typically conducted before more extensive laboratory investigations are performed. By integrating APD into the preliminary design phase, users can gain more detailed insights efficiently. The goal is not to replace laboratory testing, but to complement it, as laboratory analyses remain essential for refining soil properties and constitutive model parameters during the final design stages. APD is characterised by transparency and adaptability, allowing users to contribute their expertise and expand the system's database by incorporating additional methods and parameter correlations.  
Section 3 demonstrated the process of determining soil parameters for a soft, sensitive clay site using the CPT, DMT, and \(V_{s}\)-based workflows. The results from various methods within these three workflows were compared with reference values derived from laboratory tests conducted at the Leda clay test site. This comparison helps to validate the  
Figure 10: (**a**) Failure mechanism, (**b**) load-displacement curve at point 1.  
Figure 9: FE model.  
individual methods and to refine the compiled database of correlations. The results were presented as lower and upper bounds, as well as averages. However, using the average as a representative value for different parameters poses challenges, as it may incorporate less accurate methods. The main issue stems from the large number of methods available within APD and the significant variability in estimated values for the same parameter. To address this, a statistical module is being developed to assist in selecting a more reliable representative value.  
To further demonstrate the broader applicability of the framework, Section 4 presented the application of APD at three additional sites with varying soil types. These case studies illustrate the flexibility of the tool across different geological conditions and reinforce its potential as a valuable aid in preliminary geotechnical assessments. Section 5 presented the stratification of the CPT and the determination of both HS and HSS model parameters. Section 6 illustrated a simple synthetic case study where the stratification and constitutive model parameters, obtained from the previous section, were automatically connected to a finite element (FE) software for the modelling of a shallow foundation. This case study showcases the potential of APD and demonstrates the full workflow implemented in PLAXIS 2D, from importing the in situ results to the numerical modelling of geotechnical problems.  
Conceptualisation, I.M. and F.T.; methodology, I.M. and F.T.; software, I.M.; validation, I.M. and F.T.; formal analysis, I.M. and F.T.; investigation, I.M.; resources, I.M. and F.T.; data curation, I.M.; writing--original draft preparation, I.M.; writing--review and editing, I.M. and F.T.; visualisation, I.M.; supervision, F.T.; project administration, F.T. All authors have read and agreed to the published version of the manuscript  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors extend their gratitude to the members of the APD group, [PERSON], and [PERSON], for their valuable contributions. Special thanks go to [PERSON] for providing the CPT sounding used in this study. We gratefully acknowledge the Open Access Funding by the Graz University of Technology.  
The authors declare no conflicts of interest.