Improving Predictive Modeling in Geotechnical Projects with DAARWIN: Combining Sensitivity Analysis and Backanalysis

From parameter influence to continuous model calibration, grounded in observation

Understanding What Matters: Sensitivity Analysis First

Every geotechnical model begins with assumptions — elastic moduli, cohesion, friction angle, permeability — all estimated from limited site investigations. While these values are necessary to initiate simulations, they rarely capture the full complexity of real ground behavior. Once construction begins and monitoring data becomes available, the critical question changes:

Which of these parameters actually govern the response we're seeing on site?

Sensitivity analysis provides the answer. It quantifies how variations in each input parameter influence the model's predicted outputs — displacements, pore pressures, settlements, and other field measurements. But its role extends far beyond ranking variables: it fundamentally reshapes how engineers interpret and interact with their models.

By distinguishing which parameters meaningfully affect behavior and which do not, sensitivity analysis simplifies the problem space. It allows engineers to focus their attention, resources, and eventual calibrations only where it truly counts.

DAARWIN's Sensitivity Engine: Technical Precision, Practical Speed

DAARWIN integrates sensitivity analysis as a core function within its numerical modeling ecosystem. Rather than treating it as a separate pre-processing or academic exercise, the platform incorporates sensitivity into the modeling loop — where it can inform live decisions.

Using efficient computational routines, DAARWIN perturbs parameter sets in structured sequences and analyzes the resulting changes in model response. This process provides users with immediate insight into how strongly the model depends on each variable, even in complex conditions involving nonlinearity, time-dependence, or coupled hydro-mechanical effects.

The result is not just diagnostic, but actionable: engineers can identify high-impact parameters with confidence, discard or fix low-impact ones, and prepare their models for calibration in a way that is grounded in physical influence rather than trial and error.

From Influence to Adjustment: Linking Sensitivity to Backanalysis

Understanding which parameters influence the system is only the beginning. The true value emerges when this insight is used to guide how models are corrected in light of real observations.

In geotechnical modeling, discrepancies between predicted and measured behavior are expected.

Deviations in settlements, deformations, or pore pressures can arise from heterogeneities, unexpected ground-structure interactions, or imperfect boundary conditions. The engineering response is to recalibrate — but calibration without a roadmap can quickly become computationally expensive and conceptually ambiguous.

This is where DAARWIN’s approach sets itself apart. By using the output of sensitivity analysis as a filter, the platform narrows the space in which backanalysis is applied. Inverse modeling is no longer a global search — it becomes a targeted optimization, constrained to the parameters that are proven to matter.

Real-Time Backanalysis: Adaptive Modeling, Grounded in Data

DAARWIN’s backanalysis module is designed to work directly with live monitoring data. As measurements arrive from the field — settlements, inclinometer readings, pore pressures — the platform compares them against model predictions. If divergence is detected, DAARWIN can recalibrate the model automatically.

This process ensures that calibration efforts remain efficient, stable, and grounded in the actual behavior of the system, without overfitting or unnecessary parameter manipulation.The result is a model that reflects actual behavior, updated in near real-time.

Why This Approach Matters

• Keeps calibration physically meaningful and technically sound

• Avoids unnecessary parameter adjustments and instability

• Reduces computation time while maintaining model accuracy

• Enables continuous refinement as new data is incorporated

• Supports forward-looking decisions in upcoming construction stages

• Maintains model integrity without needing full reinitialization.

  
  

Whether you're advancing a TBM, excavating a shaft, or constructing a dam embankment, the model remains in sync with reality — not just as a design tool, but as an operational decision-support system.

A Living, Iterative Geotechnical Model

By combining sensitivity analysis and real-time backanalysis, DAARWIN enables a fully integrated feedback loop:

• Parameter influence is assessed systematically and early.

• Model predictions are continuously compared with field behavior.

• Deviations are not just observed, but diagnosed.

• Calibrations are applied precisely where they have impact.

• Models evolve with data — becoming living tools, not static assumptions.

  
  

This approach moves geotechnical modeling beyond static validation and into a domain of adaptive reliability. It empowers engineers to respond to uncertainty, change, and risk not with rework, but with insight — and to maintain trust in their models even as field conditions evolve.

Conclusion: A New Standard in Model Calibration with DAARWIN

In a discipline where uncertainty is the rule and site behavior rarely conforms to predictions, sensitivity analysis and backanalysis should not be treated as optional or separate. They are part of a unified process: one that identifies influence, quantifies confidence, and integrates data into every decision.

DAARWIN embodies this approach — providing engineers with a platform where real-time measurements, model behavior, and calibration strategy converge. You don’t just assume which parameters matter. You measure it. You test it. And you adjust with purpose.

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🔗 Real-Time Backanalysis in DAARWIN🔗 Sensitivity Analysis for Geotechnical Models