Is it possible to design you own soil fatigue model in AllWave-PDP?

Yes, you can design your own soil fatigue model in AllWave-PDP. The software provides a flexible framework that lets you define layer-specific soil resistance parameters, fatigue degradation behavior, and loading history effects rather than locking you into a single fixed model. This makes it particularly useful for projects where standard built-in models do not reflect the actual ground conditions you are working with.

The ability to customize fatigue behavior matters most in vibratory driving scenarios, where the ground experiences thousands of loading cycles and a one-size-fits-all approach to residual strength produces physically unrealistic results. The sections below walk through the key parameters, how AllWave-PDP handles cyclic loading internally, what customization options are available, how to implement a custom model in practice, and where the boundaries of user-defined models lie.

What parameters define a soil fatigue model in pile driving analysis?

A soil fatigue model in pile driving analysis is defined by the parameters that describe how soil resistance degrades as the number of loading cycles increases. The core parameters are initial soil resistance, residual soil resistance, the rate of degradation between those two states, and the number of cycles required to reach residual conditions. Together, these four inputs control how the model transitions from peak to degraded strength.

In practice, the initial resistance represents the undisturbed soil strength before any cyclic loading begins. The residual resistance is the stabilized lower strength the soil reaches after sufficient cycling. The degradation rate describes the shape of the transition curve between these two states, and the cycle count threshold defines when the soil is considered fully fatigued at a given depth.

Beyond these core inputs, a physically realistic fatigue model also requires depth-dependent loading history tracking. Soil at the top of the pile shaft experiences far more cycles than soil near the current pile tip, so applying a uniform residual strength across the full shaft is not accurate. A well-constructed model assigns fatigue state as a function of local cycle count at each depth increment, not as a global average. Additional parameters such as soil damping coefficients and quake values further shape how the model behaves during each simulated hammer blow.

How does AllWave-PDP handle soil resistance during cyclic loading?

AllWave-PDP handles soil resistance during cyclic loading through a one-dimensional stress-wave analysis framework based on the Method of Characteristics. For each penetration step, the software calculates the coupled hammer-pile-soil response and tracks how shaft resistance evolves as the pile advances and the loading history accumulates at each depth. This means soil resistance is not treated as a static input but as a depth- and cycle-dependent variable.

The underlying engine traces its development back to TNOWAVE, which was built to model the interaction between hammer, cushion system, pile, and ground during every individual blow. AllWave-PDP extends this by allowing the soil model to update as penetration increases, so the active pile length and the corresponding resistance distribution change with each step in the simulation.

For vibratory driving specifically, the cyclic loading challenge is more pronounced than in impact driving. A vibratory hammer operating at 23 Hz produces roughly 10,000 cycles in approximately seven minutes. Soil near the top of the shaft accumulates that full loading history, while soil near the current pile tip has experienced far fewer cycles. AllWave-PDP accounts for this by treating fatigue as a function of local loading history rather than applying a single global degradation factor to the entire shaft.

The classic simplification for this problem is the Beta Factor, originally proposed by Jonker, which expresses residual soil strength as a ratio of initial strength. While straightforward to apply, a single constant Beta does not capture the depth-dependent variation in cycle count. AllWave-PDP supports more advanced approaches that assign fatigue state layer by layer, which produces a more physically realistic resistance profile during simulation.

What customization options does AllWave-PDP offer for soil models?

AllWave-PDP offers several layers of customization for soil models, ranging from parameter adjustments within built-in model structures to more detailed layer-by-layer input of resistance and fatigue behavior. You can define shaft resistance and tip resistance independently for each soil layer, assign layer-specific dynamic parameters such as damping and quake, and control how resistance degrades with depth and cycle count.

The software supports CPT-based soil modeling, where measured cone resistance values are translated directly into driveability parameters. This approach, developed and refined through work by Alm and Hamre among others, reduces dependence on subjective interpretation of intermediate soil parameters and links the model more directly to field measurements. Where CPT data is available, this pathway tends to produce more consistent results than approaches that rely heavily on derived shear strength profiles.

Beyond CPT input, you can also incorporate SPT data and laboratory test results to build or calibrate the soil model. The key customization levers available to you include:

Layer-specific initial and residual resistance values for both shaft and tip
Degradation rate and cycle threshold per layer to control fatigue progression
Soil damping coefficients (Smith damping or rate-dependent alternatives) per layer
Quake values for shaft and tip, defining the elastic displacement limit before plastic movement begins
Penetration step size, which controls how frequently the active soil profile updates during simulation
Sensitivity analysis inputs, allowing you to test a range of parameter values and assess how uncertainty in soil properties affects predicted blow count, stresses, and refusal risk

This combination of inputs gives you meaningful control over how the model represents real ground behavior, particularly in layered profiles where fatigue characteristics vary significantly between soil types.

How do you implement a custom soil fatigue model in AllWave-PDP?

Implementing a custom soil fatigue model in AllWave-PDP follows a structured workflow that begins with ground investigation data and ends with a validated, layer-specific resistance profile that updates as the pile penetrates. The process requires you to translate geotechnical data into model parameters, define how resistance degrades with cycling, and verify the model against known behavior before using it for prediction.

A practical implementation sequence looks like this:

Gather and interpret ground investigation data. Start with CPT profiles, SPT records, or laboratory test results. Where CPT data is available, use a direct CPT-to-driveability parameter approach to minimize interpretation uncertainty.
Define the soil layering. Divide the profile into layers that reflect meaningful changes in soil type, density, or stiffness. Each layer will carry its own resistance and fatigue parameters.
Assign initial and residual resistance per layer. For each layer, set the undisturbed shaft resistance and the residual value the model should reach after full fatigue. The ratio between these values is effectively your layer-specific Beta.
Set degradation rate and cycle threshold per layer. Define how quickly each layer transitions from initial to residual resistance and at what cycle count that transition is considered complete.
Input dynamic soil parameters. Assign damping coefficients and quake values per layer. These control how the soil responds dynamically during each simulated blow.
Run the simulation and check outputs. Review blow count versus penetration, compression and tension stresses, energy transfer, and refusal risk. Identify depth intervals where the model produces unexpected results.
Run sensitivity analyses. Vary uncertain parameters within plausible ranges to understand how model outputs respond. This step is important for communicating prediction uncertainty to your project team.
Calibrate against monitoring data where available. If installation data from a comparable project exists, use signal matching and back-analysis to refine the model. This closes the prediction-monitoring-postdiction loop and improves future predictions.

The AllWave software package supports this workflow end to end, including the signal matching tools needed for back-analysis after installation.

What are the limitations of user-defined fatigue models in AllWave-PDP?

User-defined fatigue models in AllWave-PDP are limited primarily by the quality of the input data, the assumptions embedded in the chosen model structure, and the inherent uncertainty in predicting how soil behaves under cyclic loading at depth. The software gives you significant flexibility, but that flexibility does not eliminate the need for engineering judgment in interpreting results.

The most important limitations to keep in mind are:

Data dependency. A custom fatigue model is only as reliable as the ground investigation data behind it. Sparse CPT coverage, variable soil conditions between boreholes, or limited laboratory data all introduce uncertainty that no model structure can fully compensate for.
Model structure assumptions. Even a layer-specific model still requires you to choose a degradation curve shape and a cycle threshold. These choices involve judgment, and different reasonable choices can produce meaningfully different predictions, particularly in mixed or layered profiles.
Validation dependency. A custom model that has not been calibrated against actual installation data from comparable conditions carries higher uncertainty. Without back-analysis from monitored installations, you are working with an uncalibrated prediction.
Vibratory driving complexity. Soil fatigue behavior under vibratory loading is more complex than under impact loading, and the available calibration databases for vibratory driving are smaller. Custom models for vibratory scenarios therefore carry more inherent uncertainty than those for impact driving.
Software scope. AllWave-PDP operates within a one-dimensional stress-wave framework. Three-dimensional soil effects, lateral loading interactions, and complex pile-soil interface behavior at large displacements fall outside what the model can represent directly.

The AllWave-PDP manual describes this honestly as The Art of Prediction: driveability engineering combines models, simulations, and data, but always depends on engineering judgment for interpreting soil behavior and assessing hammer performance. A driveability prediction is a well-reasoned forecast with explicit assumptions and acknowledged uncertainties, not a deterministic calculation. The most reliable approach treats the prediction as the starting point of a learning loop that gets refined through installation monitoring and post-analysis.

How We Support Custom Soil Fatigue Modeling and Drivability Predictions

We work with project teams at every stage of the drivability prediction process, from initial soil model development through installation monitoring and post-analysis. Our approach is built on decades of experience with impact and vibratory driving, onshore and offshore, and on the AllWave software tools we have developed and refined over that time.

When you need to develop or validate a custom soil fatigue model, we can support you with:

CPT-based soil model development that links measured field data directly to driveability parameters, reducing interpretation uncertainty
Layer-specific fatigue parameter definition for both impact and vibratory driving scenarios, including sensitivity analysis across uncertain parameter ranges
AllWave-PDP and AllWave-VDP simulations covering blow count, pile stresses, energy transfer, refusal risk, and fatigue cycle generation
Installation monitoring and signal matching to back-analyze actual driving data and calibrate the soil model against real behavior
Post-analysis and updated predictions that feed into your experience database and improve future project forecasts
Independent technical review of existing drivability studies where you need a second opinion or validation of model assumptions

Whether you are working on an offshore wind foundation, a large infrastructure project, or a marine structure, the quality of your soil fatigue model directly affects the reliability of your installation plan. Contact us to discuss your project and find out how we can help you build a more accurate and defensible drivability prediction.