Celtic Sea Floating Offshore Wind – Shared Anchor Load Resolution & Capacity Verification

Executive Summary

This study establishes the geotechnical verification layer of Morie Analytics by transforming mooring-derived loads into capacity-verified anchor designs.

The workflow identifies the governing event, extracts concomitant loads, transfers them through embedded chain mechanics, resolves shared-anchor demand, and verifies suction pile capacity.

The result is a reproducible framework connecting system response, load transfer, and geotechnical resistance.

This module represents the point where mooring demand and soil resistance are combined into verified design decisions.

Site intelligence → Layout generation → Soil reconstruction → Mooring physics → Anchor verification → Cable optimization

Project Scope

• Governing event identification
• Concomitant load extraction
• Load transfer from mudline to padeye
• Shared-anchor load resolution
• Capacity verification

This study converts mooring loads into geotechnically verified anchor design.

Engineering Context

Shared anchors reduce cost but introduce:

• Multi-directional loading
• Build-up of vertical uplift and torsional effects
• Complex soil–structure interaction

The key principle is:

Design must be based on simultaneous load conditions, not isolated maxima.

This workflow ensures a consistent transition from system mechanics to geotechnical verification.

Inputs and Data Sources

This study builds directly on upstream Morie Analytics outputs:

From morie_site

• Bathymetry context

From morie_layout

• Shared-anchor topology
• Connectivity
• Anchor coordinates

From morie_soil

• Layered soil profile
• Soil parameters

From morie_mooring

• Padeye or mudline loads
• Time series response
• Governing event
• Concomitant load states

Additional Inputs

• Chain properties
• Suction pile geometry
• Coupled capacity model parameters

This provides the load and resistance inputs required for anchor verification.

Technical Architecture

The workflow is implemented in Python using:

• numpy, scipy → numerical operations
• matplotlib → visualization
• famodel → system definition and data handling
• RAFT → dynamic response input
• getTransferLoad → embedded chain load transfer
• getCapacitySuction → suction pile capacity model

Core modules:

• system initialization → project setup and soil loading
• RAFT interface → dynamic response simulation
• event detection → governing load case identification
• time-series reconstruction → PSD-to-time-domain conversion
• concomitant extraction → simultaneous multi-line load definition
• load transfer → mudline-to-padeye force transformation
• vector resolution → shared-anchor load combination
• torsion evaluation → lug-induced torque computation
• capacity verification → suction pile response assessment

System Flow

Mooring Response → Critical Event → Load Transfer → Anchor Resolution → Capacity Check

The architecture ensures traceability from system loads to geotechnical verification.

Processing Workflow

1. Load mooring results
2. Identify governing event
3. Extract concomitant loads
4. Transfer loads to padeye
5. Resolve shared-anchor load state
6. Compute torsional demand
7. Evaluate suction pile capacity
8. Verify load–capacity interaction

This converts mooring loads into capacity-verified anchor design.

Anchor System Topology

Figure 1 – Shared-anchor configurations across the floating wind farm.

Figure 2 – Multiple mooring lines connected to shared anchors.

Engineering Interpretation

Shared anchors form a coupled load network, where:

• Multiple lines contribute simultaneously
• Load directions differ
• Vector combination governs demand

Critical Event & Concomitant Loads

Figure 3 – Mooring tension time series.

The governing event can be represented as:

T_design = T_mean + 3.8·σ

Note, here that the standard deviation was increased to match the maximum load in the context of a limited time series.

Figure 4 – Concomitant loads at peak event.

Engineering Interpretation

The anchor must be checked against simultaneous load conditions, not independent maxima.

Load Extraction

Loads are extracted at the mudline connection point are derived at the padeye connection point:

• Horizontal → Ha
• Vertical → Va
• Direction → θa

Link with Soil Reconstruction

The transformation from mudline loads to padeye loads on sandy soils depends on:

• Soil friction angle (φ)
• Relative density (Dr)
• Embedded line behavior

These parameters are provided by morie_soil, establishing a direct coupling between:

• Mooring response
• Soil-dependent load transfer

Anchor-Level Soil Profile (fowt1b)

The selected anchor fowt1b is exported with its fully reconstructed soil profile in a structured format (profile_map), directly usable in downstream anchor capacity models.

This structure represents the final engineering output of the soil and it was generated in the previous study case morie_soil.

Profile Structure

profile_map = {
    'layers': [
        {
            'type': 'sand',
            'z_top': stick-up_length,
            'z_bottom': Z1 + stick-up_length,
            'gamma_top': 9.0,
            'gamma_bot': 10.0,
            'phi_top': 30.0,
            'phi_bot': 32.0,
            'Dr_top': 60.0,
            'Dr_bot': 75.0},
        {
            'type': 'sand',
            'z_top': Z1 + stick-up_length,
            'z_bot': Z2 + stick-up_length,
            'gamma_top': 10.0,
            'gamma_bot': 11.0,
            'phi_top': 32.0,
            'phi_bot': 37.0,
            'Dr_top': 75.0,
            'Dr_bot': 85.0},
        {
            'type': 'sand',
            'z_top': Z2 + stick-up_length,
            'z_bot': Zmax + stick-up_length,
            'gamma_top': 11.0,
            'gamma_bot': 12.0,
            'phi_top': 37.0,
            'phi_bot': 40.0,
            'Dr_top': 85.0,
            'Dr_bot': 95.0}]}

Load Transfer to Padeye

Figure 5 – Inverse catenary load transfer.

Figure 6 – Load transformation from mudline to padeye.

Engineering Interpretation

• Loads evolve along embedded chain, reducing the tension and increasing the angle with the horizontal plane
• Chain and soil properties influence transfer
• Padeye loads govern anchor design

Anchor Load Aggregation

Loads from all connected lines are combined into anchor-level demand. This allows going from a multi-linear action to a single line load that allows for it’s capacity check.

Engineering Interpretation

Shared Anchor Load Resolution

Figure 7 – Load vectors acting on a shared anchor.

Load resolution:

Hx = Ha*cos(ψ)
Hy = Ha*sin(ψ)

H_total = √(Hx² + Hy²)
V_total = ΣVa

Engineering Interpretation

This step converts:

Multiple line forces → Single design load

This is the critical interface between physics and design. Multiple lines are combined into a single 3D load state.

Torsional Load Evaluation

T_i = Ha,i*r_lug*sin(ψ_lug)
T_total = Σ|T_i|

Figure 8 – Shared-anchor interaction.

Engineering Interpretation

Torsion arises from:

• Load misalignment
• Padeye eccentricity
• Multi-line interaction

Suction Pile Capacity Model

Figure 9 – Suction pile geometry.

Vertical capacity:

V_max = min(V1, V2, V3)

Figure 10 – Failure mechanisms.

Engineering Interpretation

Capacity depends on:

• Pile geometry and slenderness ratio (L/D)
• Load combination
• Layered soil profile capacity

Load–Capacity Interaction

Figure 11 – VHM interaction surface.

Figure 12 – VH capacity envelope.

Engineering Interpretation

Defines admissible load combinations and anchor utilization.

Outputs Generated

• Concomitant load states
• Padeye loads
• Shared-anchor load evaluation
• Resultant anchor loads (Ha, Va, Ta) at padeye elevation
• Anchor sizing and verification
• Capacity envelopes
• Utilization factors

Engineering Applications

The outputs support:

• Shared-anchor verification
• Anchor sizing for extreme loading conditions
• Geotechnical design decisions
• Floating wind optimization

This enables:

System Response → Anchor Demand → Geotechnical Verification

Relationship to Other Morie Study Cases

This study is the geotechnical verification layer of the Morie Analytics workflow.

Receives from

• morie_site → bathymetry context
• morie_layout → geometry and topology
• morie_soil → layered soil profile and load-transfer environment
• morie_mooring → design-driving loads

Completes

The anchor branch of the system workflow.

It provides the geotechnical transition from anchor demand to capacity-verified design.

Why It Matters Commercially

Shared-anchor strategies only create value if they remain geotechnically feasible.

• Validates shared-anchor concepts
• Reduces unnecessary overdesign
• Links system loads to foundation cost
• Ensures geotechnical feasibility

This is where:

• Layout efficiency is validated
• Anchor cost is determined
• System design becomes physically viable

Aspects to Improve

• Soil–mooring static vs dynamic decoupling loads
• Probabilistic loads
• Optimization anchor design loops
• Installation aspects of suction piles
• Cyclic loading capacity
• Seismic analysis

Design Philosophy

This study reflects the Morie Analytics approach:

• Physics-informed
• Modular
• Traceable
• Engineering-focused
• Scalable

How to Run

1. Place datasets in celtic_sea_share/

2. Install dependencies:

   • numpy
   • matplotlib
   • FAModel
3. Execute:

python morie_anchor.py