Aerodynamic and Hydrodynamic Performance
design for Powerboats

Advanced analysis of Dynamic Lateral Stability gives effective prediction for vee hulls and tunnel hulls. Predicts onset of chine walk, track rolling, turn hook, bow steer, more.  "THIS IS A FANTASTIC NEW TOOL!"

TBDP/VBDP Lateral Stability Analysis predicts onset of insabilities including chine-walk, track-rolling, hook, roll-over, and more.

Lateral instability in high-speed planing hulls is a dynamic phenomenon that cannot be reliably predicted using static equilibrium methods or isolated numerical simulations. Many hulls that appear 'stable' by traditional criteria actually exhibit growing roll oscillations, chine walk, or loss of control as speed increases. This occurs because real stability depends on how roll energy is stored, dissipated, and restored over time - not simply on whether restoring moments exist at a given condition.

This is better => The presented (AR®) analysis technique introduces a dynamic, energy-based method for evaluating lateral stability across the full operating speed range. Developed through extensive hydrodynamic research, modeling and full-scale testing, it captures the complex interactions of roll forces, damping, geometry, and pressure fields within a single, unified framework. 

By separating Restoring Authority from Damping Effectiveness and identifying which physical mechanism governs stability at each speed, the method accurately predicts instability onset before it manifests on the water. Implemented within TBDP/VBDP software, the approach provides designers with a practical, physics-based tool to assess real-world handling behavior and apply targeted design corrections early in the design process.

"This new dynamic lateral stability analysis by AeroMarine Research delivers a major step forward in predicting a boat’s true stability behavior across all speeds, from the first moments of planing to the highest performance speed ranges.  Despite the depth and sophistication of the method, the resulting 'Dynamic Stability Index' makes it amazingly easy for users to assess stability quickly and confidently." [PBDesign magazine, Dec 2025]

Making it Easy:
While stability analysis is complex, TBDP©/VBDP© presents a reporting format that makes the results and recommendations easy to understand...

TBDP©/VBDP© presents a full range of reporting information that makes the results and recommendations easy to understand.

For each of the Stability measures, the software does ALL the work behind the scenes, and gives both DETAILS and also gives the 'GOOD/NO GOOD' summary of all considerations.  [Check out 'Easy Results View' here]

What Is Lateral Dynamic Stability?
Lateral dynamic stability describes a hull’s ability to resist growing roll motion when subjected to small disturbances such as waves, steering inputs, or asymmetric lift. A hull is laterally stable if these disturbances decay with time, and unstable if they grow from cycle to cycle.

So, lateral stability can not determined solely by static balance (which is what most naval analysis software does). A hull may have positive restoring stiffness and still be dynamically unstable if roll energy persists or amplifies as speed increases. This distinction explains why some boats appear stable at low speed yet develop chine walk or violent roll oscillations at higher speeds.

Dynamic lateral stability is governed by three interacting factors: ·

• how much roll energy is generated by disturbances,

• how effectively that energy is dissipated each cycle,

• how strongly the hull restores itself as heel develops.

Understanding stability therefore requires evaluating motion over time, as well as forces at equilibrium.

Why Traditional Methods Fall Short

• Savitsky-Based Analysis - Savitsky theory evaluates planing hull behavior using static equilibrium of forces and moments. Lateral stability is inferred from restoring stiffness and lift distribution at individual operating points, implicitly assuming that roll disturbances decay naturally. Roll inertia, energy persistence, and speed-dependent amplification mechanisms are not modeled. As a result, Savitsky-based methods cannot predict when or why lateral instability will develop as speed increases.

• CFD Software Analysis - CFD software tools provide detailed pressure and force distributions at specific speeds, but are typically as isolated snapshots. They do not dynamically evaluate whether roll motion grows or decays over successive cycles, nor do they efficiently capture regime transitions across a speed range. Even 'high-end' add-ons for CFD software are computationally expensive and often fail to translate directly into real-world handling predictions.

A Dynamic Energy-Based Stability Framework

This presented (AR®) method treats lateral stability as a dynamic energy balance problem. Instead of simply testing whether restoring forces exist, it evaluates whether roll energy introduced by disturbances is removed faster than it accumulates. Two complementary stability mechanisms are both necessarily evaluated: · 

• A-DSI (Amplitude-Limited Stability Index)  - measures the hull’s inherent geometric and hydrostatic ability to resist and limit roll motion as heel amplitude increases. This is an advanced modeling indicator (developed by AR®) that more accurately represents higher velocity stability behaviors. This indicator represents a hull's dynamic 'Restoring Authority' - the hull’s ability to generate corrective roll moments as heel amplitude develops - or 'how strongly the hull shape itself pushes back against rolling as it leans'.  It reflects hull geometry, lift distribution, and effective roll leverage.

• C-DSI (Cycle-Limited Stability Index). - measures the hull’s ability to dissipate roll energy from cycle to cycle during oscillatory motion. This is a classical Savitsky analysis (implicitly assumes cycle-limited behavior everywhere) that works for low-speed planing hull behaviors. This indicator measures how effectively the hull sheds roll energy over time instead of letting oscillations build. It captures the combined influence of roll inertia, hydrodynamic damping, and flow interaction.

Both mechanisms are evaluated continuously across the operating speed range.

Dynamic Regime Identification (Λ)

The Dynamic Regime Indicator, Lambda (Λ), identifies which physical mechanism governs stability at each operating condition by comparing the time scale of energy dissipation to the time scale of energy storage and release. Λ identifies whether roll motion is controlled principally by how quickly energy is shed each cycle, or by how strongly the hull pushes back as it heels.  LOW Lambda means stability is ‘damping dominated’ (A-DSI); HIGH Lambda means stability is ‘stiffness dominated’ (C-DSI); in between means stability is in ‘transitional regime’ (both A-DSI and C-DSI are influential).

The AR® analysis technique evaluates all of the conditions:

• Λ > 1 — Stiffness-Dominated Regime (C-DSI) - Restoring authority controls stability. Geometry and lateral lift engagement are the primary stabilizing mechanisms.

• Λ < 1 — Damping-Dominated Regime (A-DSI) - Stability depends primarily on energy dissipation. Roll inertia and lift concentration dominate, and instability onset becomes more likely.

• Transitional Regime (A-DSI and C-DSI) Both mechanisms contribute. Stability is highly sensitive to speed, trim, and loading, and small design changes can have large effects.

This regime awareness is extremely helpful to the designer because it explains not just whether a hull is unstable, but why.

Instability Onset and Trend Indicators

Instability is identified through trends across speed, rather than just single-point thresholds. Our research and real-world testing has proven that many conditions must be evaluated simultaneously in order to accurately identify hull stability state.  Key indicators considered include:

• declining governing stability margin with increasing speed;

• peak-and-decline behavior in restoring authority,

• divergence between damping-based and restoring-based stability measures,

• persistent warning conditions across adjacent speeds,

• transitions into damping-dominated regimes,

• normalized values of dynamic energy-based Stability Indicators.

These indicators..allow instability to be detected before loss of control occurs, aligning closely with observed real-world behavior.