How are blow counts predicted in AllWave-PDP?

AllWave-PDP predicts blow counts by simulating the full interaction between hammer, pile, and soil resistance at successive penetration depths using one-dimensional stress-wave analysis. The software runs wave equation calculations for each depth increment, producing a complete blow count profile versus penetration depth rather than a single value. The sections below answer the most common technical questions about how this process works in practice.

What inputs does AllWave-PDP use to calculate blow counts?

AllWave-PDP requires three categories of input to calculate blow counts: a defined hammer model, a pile geometry and material description, and a soil resistance profile derived from ground investigation data. Together, these inputs allow the software to simulate how energy travels through the pile and how the soil responds at each depth increment.

The hammer input draws from a built-in hammer library that stores the mechanical properties of common impact hammers, including ram weight, stroke, efficiency, and cushion characteristics. If a specific hammer is not in the library, you can define its properties manually. Accurate hammer modelling directly affects how much energy enters the pile system, so this input carries significant weight in the final blow count prediction.

For the pile, the software requires cross-sectional geometry, material stiffness, and impedance properties along the full pile length. Changes in cross-section or material affect how stress waves travel and reflect, so the model must reflect the actual pile design.

The soil input is the most variable component. AllWave-PDP accepts ground investigation data in several formats:

CPT data (cone penetration test), which is the most commonly used source for deriving soil resistance profiles
SPT data (standard penetration test) for projects where CPT is unavailable
Laboratory test results to refine soil layer characterisation

From this data, the software builds a soil model that distributes shaft resistance and toe resistance along the pile as a function of depth. The quality of the blow count prediction depends directly on how well this soil model represents actual subsurface conditions.

How does the wave equation method translate hammer energy into blow counts?

The wave equation method translates hammer energy into blow counts by modelling the impact as a stress wave that travels through the pile, interacts with shaft and toe resistance, and produces a measurable permanent set per blow. The blow count is the inverse of that permanent set: more penetration per blow means a lower blow count, and less penetration per blow means a higher blow count.

AllWave-PDP is built on the Method of Characteristics (MoC), a mathematical approach to one-dimensional stress-wave propagation with a long development history in foundation engineering. The method traces back to early Dutch research, including work by De Josselin de Jong in 1956 on toe resistance modelling, followed by theoretical solutions for shaft friction developed in the 1970s. TNO later used this foundation to develop TNOWAVE, from which AllWave-PDP directly descends.

The core principle is that the pile is not treated as a rigid body. When the hammer strikes, a compressive stress wave travels downward through the pile. As it passes each soil layer along the shaft, part of the wave energy is absorbed by shaft resistance. When the wave reaches the toe, it interacts with toe resistance and reflects back upward. The software calculates forces, velocities, displacements, and stresses at every point along the pile and at every moment in time.

The permanent set per blow emerges from this full interaction. If the downward energy exceeds the total soil resistance, the pile advances. The ratio of energy to resistance, mediated by pile impedance and wave reflections, determines how much it advances. This is fundamentally richer than historical dynamic formulas, which estimated capacity directly from hammer energy and set without modelling the wave mechanics explicitly.

You can explore the full capabilities of this approach through the AllWave software package, which covers both impact and vibratory driving simulation.

What soil resistance models are used in AllWave-PDP?

AllWave-PDP uses CPT-based soil resistance models as the primary input for predicting Soil Resistance to Driving (SRD). These models translate cone resistance values into distributed shaft friction and toe resistance along the pile, accounting for factors such as friction fatigue, soil layering, and the difference between static capacity and driving resistance.

Friction fatigue is an important concept in this context. As the pile penetrates deeper, soil that was once near the toe moves up along the shaft. The resistance that this soil exerts on the shaft decreases with increasing distance from the toe, a phenomenon well documented in CPT-based SRD models. Ignoring friction fatigue leads to overestimating shaft resistance and underestimating blow counts at greater depths.

The soil model also distinguishes between the resistance during driving and the long-term static capacity of the pile. These are not the same value. Soil behaviour during dynamic loading differs from its behaviour under static load, and the model applies dynamic soil parameters, including soil damping and quake values, to represent this difference accurately.

Because soil conditions vary and ground investigation data always carries some uncertainty, the soil model is not a fixed input. Sensitivity analyses using upper and lower bound SRD estimates are standard practice, giving you a range of predicted blow counts rather than a single line. This range is more useful for planning hammer selection and assessing refusal risk than any single deterministic prediction.

How accurate are blow count predictions from AllWave-PDP?

Blow count predictions from AllWave-PDP are as accurate as the soil model and hammer input allow. The wave equation calculation itself is well-established and consistent, but prediction accuracy depends on how well the input data represents actual subsurface conditions and hammer performance. Predictions should always be understood as informed estimates with explicit uncertainty, not exact forecasts.

Several factors influence how closely predictions match measured blow counts during installation:

Ground investigation quality: Sparse or unrepresentative CPT data produces a less reliable soil model, which directly affects blow count accuracy.
Hammer performance assumptions: Actual hammer efficiency in the field often differs from theoretical values. If the assumed efficiency is too high, predicted blow counts will be lower than measured ones.
Soil variability: Lateral variation in soil conditions between the investigation location and the pile installation point introduces uncertainty that no model can fully eliminate.
Dynamic soil parameters: Damping and quake values are estimated from correlations and experience. Different parameter choices produce different blow count profiles.

The AllWave-PDP manual describes this honestly as “The Art of Prediction”: drivability engineering relies on models and data, but engineering judgement remains important for interpreting soil behaviour and assessing whether the inputs are realistic. A prediction is not a guarantee. It is a structured estimate with defined assumptions that must be tested against field measurements.

When should drivability predictions be updated during a project?

Drivability predictions should be updated whenever measured blow counts, hammer performance data, or dynamic monitoring results differ meaningfully from what the model predicted. Treating the initial prediction as final throughout installation ignores valuable information that the installation process itself generates.

The approach behind AllWave-PDP follows an iterative learning loop that the original TNOWAVE philosophy established explicitly. The workflow moves through these stages:

Ground investigation and initial soil model development
Drivability prediction based on that model
Installation monitoring during driving
Signal matching and back-analysis using measured data
Updated soil model that reflects what the installation revealed
Comparison with the original prediction to identify and explain deviations
Experience database update to improve future predictions

A deviation between prediction and measurement is not simply an error to explain away. It is technical information. If measured blow counts are consistently higher than predicted, the soil model likely underestimates resistance, the hammer is performing below assumed efficiency, or both. Back-analysis using dynamic measurements allows you to identify which factor is responsible and update the model accordingly.

This principle applies equally to vibratory driving. When a pile reaches early refusal during vibratory installation, as occurred in the 2022 NAM L13-F1-1 case with a 4.5 m diameter monopile, the vibratory phase itself becomes a calibration experiment. Signal matching from the vibratory phase can refine the soil model before an impact hammer takes over, improving the reliability of subsequent predictions and capacity assessments.

The practical trigger for updating a prediction is straightforward: update the model when the gap between prediction and reality is large enough to affect decisions about hammer selection, installation planning, or pile integrity assessment.

How We Support Drivability Studies and Blow Count Prediction

At Allnamics, we combine the AllWave-PDP software with decades of field experience to deliver drivability studies that go beyond a single calculated blow count. Our approach integrates ground investigation data, hammer modelling, and soil resistance analysis into a complete prediction that covers the full installation process.

Here is what we provide in a typical drivability study:

Blow count profiles versus penetration depth, including upper and lower bound scenarios based on SRD uncertainty
Pile stress analysis covering maximum compression and tension stresses throughout installation
Hammer selection support, assessing whether a proposed hammer can achieve target penetration within acceptable stress limits
Refusal risk assessment, identifying depths where practical refusal may occur
Fatigue analysis input, generating stress cycle data for structural assessment
Installation monitoring and back-analysis, updating the soil model during driving when measurements indicate a deviation from the prediction

We work with offshore wind developers, EPC contractors, foundation contractors, and civil engineering firms on projects where getting the installation right the first time matters. Whether you need an independent review of an existing drivability study or a full prediction from ground investigation through post-installation back-analysis, our team can support your project.

Contact us to discuss your project requirements and find out how we can help you plan a reliable and safe pile installation.