Optimisation of Rigid Inclusion Performance Using Data Integration and Back-Analysis in DAARWIN

Rigid inclusions have become a trusted solution for improving soft or compressible soils, particularly in projects where strict settlement criteria and variable ground conditions demand a reliable form of reinforcement. Whether supporting embankments, industrial slabs, or offshore foundations, their success depends on achieving consistent load transfer between the inclusions, the surrounding soil, and the overlying structure. Yet, one of the greatest challenges in practice remains — connecting design assumptions with actual field performance.

DAARWIN provides a digital framework to bridge that gap. By integrating geotechnical investigation, monitoring, and analysis into one cloud-based environment, it enables engineers to design, validate, and continuously improve rigid inclusion systems through data-driven insight and back-analysis.

From Investigation to Design Inputs

Successful ground improvement begins with a clear understanding of subsurface variability. In rigid inclusion projects, this means identifying compressible strata, quantifying stiffness contrasts, and estimating undrained shear strength (Su), effective friction angle (φ’), and modulus (M).

DAARWIN automates this process by parsing CPT, borehole, and laboratory data from multiple formats (AGS, Excel, PDF) and structuring them according to standardized conventions. Correlations such as Robertson (2010) or Eslami & Fellenius are applied automatically to derive key design parameters. Engineers can then visualize Su and E distributions across depth and compare profiles across the site, identifying zones that require deeper inclusions or denser spacing.

This immediate, consistent structuring of data replaces the traditional reliance on scattered files or manual normalization, ensuring that design inputs are reliable, traceable, and ready for modeling.

Building the Digital Ground Model

CPTs provide the point-based insight; DAARWIN connects those points into a spatially coherent ground model. By integrating CPTs with borehole logs, lab data, and groundwater observations, engineers can generate 2D or 3D interpolated representations of the subsurface. These models depict stratigraphy, stiffness variation, and pore pressure distribution — essential factors for defining the inclusion grid, load transfer platform (LTP) thickness, and improvement depth.

The digital ground model also allows scenario testing. For instance, varying Einc/Esoil ratios or modifying the groundwater profile can show how changes in stiffness contrast or effective stress conditions might influence total and differential settlements. Each version is stored and compared, enabling a data-driven rationale for design choices.

Understanding Load Transfer and Settlement Behavior

Rigid inclusion performance relies on the interaction between inclusions, soil, and the LTP.The load transfer platform redistributes loads from the structure to the inclusions and the surrounding soil. Its efficiency depends on stiffness contrasts, inclusion spacing, and platform thickness — all parameters that can be explored and calibrated within DAARWIN.

Settlement prediction is one of the most critical aspects of design. Using CPT-derived parameters, DAARWIN can generate stiffness maps that feed directly into analytical or numerical models (e.g., Priebe, Ménard, or PLAXIS). After construction, settlement plate data can be uploaded to compare measured versus predicted performance, refining stiffness values and validating the improvement efficiency.

Back-Analysis and Calibration through Monitoring Data

Design is only half the story; performance verification completes it. DAARWIN enables engineers to integrate field monitoring data — settlement, pore pressure, and extensometer readings — directly into the project database. Through back-analysis, engineers can update soil parameters, verify assumptions, and quantify the improvement factor achieved in practice.

This process also allows parametric or probabilistic assessment. Using DAARWIN’s high-performance computing capabilities, multiple stiffness or strength scenarios can be simulated to evaluate sensitivity and define upper and lower performance bounds. The result is a more transparent understanding of how ground improvement behaves under real-world variability.

Construction Data and Continuous Validation

During execution, as-built information (inclusion length, diameter, grout volume, installation resistance) is often collected separately from the design team. By importing this data into DAARWIN, engineers can visually cross-check inclusion depths against the interpreted stratigraphy or CPT profiles — ensuring that each column reaches the intended bearing layer. Deviations can be flagged, and cumulative statistics (e.g., mean depth, refusal ratio) are automatically generated for QA/QC reporting.

As monitoring continues post-installation, DAARWIN maintains the feedback loop: comparing settlement reduction ratios, tracking consolidation trends, and correlating them with inclusion geometry and installation records. This integration transforms traditional data silos into an active performance monitoring system.

Quantifying Uncertainty and Design Robustness

Ground conditions are inherently variable, and rigid inclusion design must reflect that uncertainty.DAARWIN supports probabilistic workflows that assess the influence of input parameter variability (Su, E, OCR) on design outcomes such as total settlement or load transfer efficiency. By running multiple realizations in batch mode, engineers can quantify confidence intervals for predicted performance, providing an evidence-based approach to risk mitigation. This capability helps refine site investigation strategies as well: identifying where additional CPTs or lab tests would most reduce uncertainty and improve model confidence.

Towards Data-Driven Ground Improvement

Rigid inclusions remain one of the most effective solutions for soft ground reinforcement, yet their design often relies on empirical judgment. By integrating investigation, design, construction, and monitoring into a unified digital workflow, DAARWIN transforms this process into data-driven decision-making, enabling engineers to validate assumptions, refine performance, and build a cumulative geotechnical knowledge base that enhances predictability and design efficiency.