NRP: Nitikorn Research Partner

02/03/2026

Why You Should Separate Cortical and Cancellous Bone in FEA

Introduction

When performing Finite Element Analysis (FEA) of bone structures, one common shortcut is modeling the entire bone as a single material.

It seems efficient.

But bone is not a solid block.

It is layered — and each layer behaves differently under load.

Understanding this difference is essential for accurate biomechanical simulation.

⸻

Bone Is Like a Coconut

Think of bone like a coconut:
• The hard outer shell = cortical bone
• The softer inner structure = cancellous bone

They are part of the same object, but they serve different mechanical roles.

Cortical bone
• Dense
• Stiff
• Main load-bearing layer

Cancellous bone
• Porous
• Less stiff
• Distributes load internally

If we ignore this structure in FEA, we change how force flows through the model.

⸻

Why Material Stiffness Matters

In linear elastic analysis, stress depends on stiffness:

σ = Eε

Where:
• σ = stress
• E = Young’s modulus
• ε = strain

Cortical bone typically has a Young’s modulus several times higher than cancellous bone.

This means:
• Cortical bone carries higher stress under the same deformation.
• Cancellous bone deforms more under load.

If we assign one averaged modulus to the entire bone:
• The model may become too stiff or too soft.
• Stress distribution may shift artificially.
• Local stress peaks may disappear or move.

This directly affects engineering decisions.

⸻

Example 1: Implant Screw Design

When an orthopedic screw is inserted into bone:
• The threads engage strongly with the cortical layer.
• The cancellous bone provides secondary support.

If both layers are merged into one material:
• Peak stress in the thin cortical rim may be underestimated.
• Fracture risk may not be visible.
• Pull-out strength predictions may be inaccurate.

By separating the layers:
• Load transfer becomes more realistic.
• Stress concentration can be properly evaluated.
• Design improvements can be targeted more effectively.

⸻

Example 2: Stress Shielding in Implants

Stress shielding occurs when an implant carries too much load, reducing mechanical stimulation in the surrounding bone.

The inner cancellous bone plays a key role in internal load sharing.

If not modeled separately:
• Internal strain levels may be miscalculated.
• Bone remodeling predictions may be unreliable.
• Long-term stability assessment may be incomplete.

Separating cortical and cancellous regions allows better understanding of internal load distribution.

⸻

When Is Simplification Acceptable?

Using a single material model may be acceptable for:
• Early concept screening
• Quick comparative studies
• Cases focusing only on implant stress

However, for:
• Design validation
• Research publications
• Regulatory documentation
• Patient-specific simulation

Separating cortical and cancellous bone should be considered best practice.

⸻

Final Thought

Biomechanical simulation is not just about generating colorful stress plots.

It is about representing biological structure in a mechanically meaningful way.

Bone is layered.
Load transfer is layered.
Your model should reflect that reality.

Separating cortical and cancellous bone is not unnecessary complexity.

It is responsible engineering.

Work With Us

If you are developing orthopedic implants or conducting biomechanical FEA and want your model to better reflect real bone structure, we can help.

At NRP Engineering Simulation, we specialize in biomechanical finite element analysis with a focus on realistic material modeling and engineering-driven decision support.

Learn more about our biomechanical simulation services at:

👉 www.nrp.co.th

Let’s build simulations that reflect reality — not assumptions.

27/02/2026

🔬 Need advanced FEA support?

NRP Engineering specializes in:

✔ Biomechanical FEA (bone–implant interaction, medical devices)
✔ Structural & Fatigue Analysis
✔ Advanced simulation for complex engineering problems

We provide engineering-grade simulation — with clear interpretation and professional reporting.

If your project involves medical devices, biomechanics, or structural integrity evaluation, we’re ready to support.

Explore our services:
👉 https://www.nrp.co.th/services

Biomechanics Is Not Just Another FEA Problem.

28/01/2026

Precision Beyond Experience: Elevating Surgical Planning with Digital Twins 🦴💻

Choosing the right bone plate and screw configuration for a complex fracture shouldn’t rely on intuition alone. In the era of personalized medicine, Engineering Data is becoming the surgeon’s most reliable ally.

This image showcases a Finite Element Analysis (FEA) model of a Radius fracture, providing a deep dive into the biomechanical behavior of the fixation system before the first incision is ever made.

✅ Why are Leading Orthopedic Surgeons Integrating FEA?

Patient-Specific Selection: Precisely determine the optimal plate length and screw trajectory based on the unique fracture plane and bone morphology of each patient.

Stress Distribution Mapping: Visualize the load sharing between the Cortical layer (high density) and the Cancellous bone (internal lattice) to prevent complications like stress shielding.

Failure Prediction: Identify potential risks of screw loosening or implant fatigue failure by simulating various physiological loading conditions.

Data-Driven Decisions: Compare different implant designs and materials digitally to find the "Gold Standard" for complex cases.

Transform your surgical planning from "standard procedure" to "optimized precision." Improve patient outcomes and gain absolute confidence in your fixation strategy.

🚀 Empower your clinical practice or research with high-fidelity FEA Simulation. Whether for pre-operative planning or advanced clinical studies, our team is ready to help you visualize the invisible.

📩 Message us today for a consultation or to learn more about our medical simulation services.

10/07/2025

🚨 Why does my simulation stop with ‘Too many attempts made for this increment’? 😩

We've all been there! This error pops up when Abaqus is struggling to solve a non-linear problem and can’t find a stable solution within the allowed attempts. It often means that something in your model’s geometry, loading, or boundary conditions is causing instability.

Here's how to fix it:

1. Reduce the Load Steps: Try lowering the load or displacement increments. This allows the solver to take smaller steps and may help it converge more easily.

2. Check Material Properties: Ensure that your material properties (e.g., elastic modulus, yield stress) are defined correctly. Sometimes incorrect values can lead to unrealistic behavior.

3. Use the Automatic Stabilization: This feature can help control the solution, particularly in cases involving large deformations.

If you’d like to automate the adjustment of the step increments using Python, here’s a simple script to reduce the increment size:

```python
from abaqus import
from abaqusConstants import

# Access the model
model = mdb.models['Model-1']

# Access the step and modify the increment size
step = model.steps['Step-1']
step.setValues(incrementationMethod=SMALL, maxInc=0.01)
```

🔧 Remember to replace 'Model-1' and 'Step-1' with your actual model and step names!

Got a different error? Drop it in the comments — we’ll solve it together! 💬💡

05/07/2025

🔧 Why does my material property result in wildly inaccurate stress values?

We've all been there! You set up your simulation in Abaqus, but unexpected results pop up. Often, this is due to small errors in material property definitions. 😩

Solution

1. Check Units: Make sure all material properties such as density, elastic modulus, and Poisson's ratio are in the correct units. Mixing up units can lead to severe inaccuracies. For example, make sure you don’t input values in grams when your model expects kilograms!

2. Use Consistent Property Values: Sometimes, users overlook the ideal material behavior to model their materials. Ensure that you select the right model (like linear elastic versus plastic) and the corresponding parameters.

Python Tip

If you're constantly checking material properties from a dataset, here's a simple Python script to gather them from a CSV file:

```python
import csv

def read_material_properties(filename):
with open(filename, 'r') as file:
reader = csv.reader(file)
materials = {}
for row in reader:
materials[row[0]] = {'density': row[1], 'elastic_modulus': row[2]}
return materials

filename = 'material_properties.csv'
material_data = read_material_properties(filename)
print(material_data)
```

Call to Action

Have you faced similar issues with material properties turning your simulation into chaos? Share your story or any questions you have in the comments! Let's troubleshoot together. 🛠️

05/07/2025

🌪️ Problem: Why does my simulation stop with ‘Too many attempts made for this increment’?

This frustrating error usually pops up when Abaqus struggles to achieve equilibrium in a nonlinear problem. Think of it like a tightrope walker who keeps losing balance. If the solver can't find a stable way to progress, it will keep making attempts until it hits the limit — hence the error!

✨ Solution: Here’s how to keep that tightrope walker steady.

1. Refine the Mesh: A coarse mesh might be the culprit. Make sure your mesh is fine enough to capture geometric details and stress variations. This will help the solver find a solution without jumping to conclusions.

2. Adjust the Stability Parameters: Lower the maximum increment size in the step settings. You can also switch to a more stable solution method, like increasing the damping coefficient.

Here's a quick Python tip to automate your increment size adjustment in your input file:

```python
with open('your_model.inp', 'r') as file:
data = file.readlines()

with open('your_model.inp', 'w') as file:
for line in data:
if 'Step' in line:
file.write(line)
file.write('Static
0.1, 1.0, 1.0, 1.0
') # adjust increment size
else:
file.write(line)
```

This script looks for the step definition in your input file and sets a smaller increment size. Just replace `'your_model.inp'` with the name of your input file!

💬 Have you encountered this error before? Share your experience or any other error messages you've battled. Let's troubleshoot together!

03/07/2025

🌟 Problem: “Why does my mesh look distorted in Abaqus?” 🤔

It’s frustrating when your mesh doesn’t show up as expected! This issue often arises because of poor element quality or incompatible geometry. A distorted mesh can lead to inaccurate simulations or even crashes.

🛠️ Solution: Here are two quick fixes you can try:

1. Refine Your Mesh: If you notice irregular shapes or stretched elements, consider refining your mesh. Use the mesh controls to set a finer mesh size in critical areas.

2. Check Geometry: Sometimes the geometry has small gaps or overlaps that cause meshing issues. Visual inspection or tools like “Check Geometry” in Abaqus can help identify these problems.

💻Quick Python Script: You can automate the process of checking element quality in your mesh using the following script. It lists all elements with quality issues:

```python
from odbAccess import
from abaqusConstants import

odb = openOdb(path='your_model.odb')
for element in odb.rootAssembly.instances['PART-1-1'].elements:
if element.quality < 0.5: # Adjust threshold as needed
print('Element ID:', element.label, 'has low quality')
odb.close()
```

With these steps, your mesh will be less likely to lie to you! Got a different mesh issue or error? Drop it in the comments — we’ll solve it together! 💬

01/07/2025

🌌 Ever wondered how engineers visualize the unseen forces at play in structures around us? 🤔

When we talk about stress and strain in materials, it can sound pretty technical. But here's the exciting part: Augmented Reality (AR) and Virtual Reality (VR) are changing the game! These technologies help us visualize complex stress and strain fields in a way that makes them easier to understand. Here's how they work:

🔍 What Are Stress and Strain?
- Stress is the internal force within materials when they are subjected to external loads. Think of it like the pressure you feel on your muscles when lifting weights.
- Strain is the deformation or change in shape that occurs due to stress. When you stretch a rubber band, that’s strain in action!

🕶️ How AR/VR Makes It Easy:
- These technologies create immersive 3D models that display stress and strain as colorful visualizations. You can explore how different materials react under various loads, almost like taking a virtual tour inside a bridge or building!
- This visualization helps students and professionals understand complex concepts without getting lost in numbers and equations.

🌈 Real-World Applications:
- Engineers can test and modify designs before building real structures, saving time and resources!
- Students can engage in interactive learning experiences, making tough concepts feel intuitive and fun!

Have you ever experienced AR or VR in education or engineering? Share your thoughts or experiences below! Let’s discuss how these technologies are reshaping our understanding of the world. 🌍

01/07/2025

🔧 Problem: "Why does my Abaqus simulation crash with 'Too many attempts made for this increment'?" 😩

This frustrating error often arises when the solver struggles to converge on a solution. It can feel like hitting a brick wall, but don't worry—this is a common situation!

🛠️ Solution: There are a couple of typical culprits behind this problem. Congested mesh, unrealistic material properties, or inappropriate boundary conditions can all lead to convergence issues. Here’s how to tackle it:

1. Refine Your Mesh: Ensure that the mesh is not overly coarse, particularly in areas of high-stress concentration.

2. Check Your Boundary Conditions: Make sure they are correctly defined and relevant to the simulation. Over-constraining the model can prevent movement where it’s needed!

💻 Here’s a quick Python script to help review boundary conditions by extracting them from your Abaqus model:

```python
from abaqus import
from abaqusConstants import

model_name = 'YourModelName'
mdb = openMdb('YourModelFile.cae')
model = mdb.models[model_name]

for bc in model.boundaryConditions.keys():
print('Boundary Condition: ', bc)
```

🔍 Run this code in the Abaqus scripting environment to list your boundary conditions. This can help ensure you haven’t overlooked anything critical!

🤔 Got a different error? Drop it in the comments — we’ll solve it together! 💬

26/06/2025

🛠️ Problem → Solution: Why Does My Simulation Stop with 'Too Many Attempts Made for This Increment'?

Have you ever faced the dreaded message, "Too many attempts made for this increment"? 🤯 You're not alone! This common issue can be really frustrating and halt your workflow.

What's Causing This?
This error often means that Abaqus is struggling to solve the equations for a certain increment of time. It usually happens when the model is too complex, has nonlinear geometry (NLGEOM) enabled, or if the material properties are not adequately defined.

How to Fix It:
1. Adjust the Time Increment: Try reducing the time increment size in your step settings. Smaller time increments can sometimes lead to more stable solutions.

2. Review Material Properties: Ensure that your material definitions are correct and that no discontinuities exist in the material behavior.

3. Increase the Number of Attempts: You can also increase the maximum number of attempts by modifying the solver settings in your analysis step.

Here's a quick Python snippet that may help with changing the increment size automatically in your input file:

```python
from abaqus import

def adjustIncrementSize(modelName, stepName, newIncrement):
mdb = openMdb('YourDatabase.cae')
step = mdb.models[modelName].steps[stepName]
step.timeIncrement = newIncrement
mdb.save()

# Usage
adjustIncrementSize('Model-1', 'Step-1', 0.1)
```

✨ Your simulation should run smoother now! If you encounter a different error or need more assistance, drop a comment — let's solve it together! 💬

24/06/2025

🛑 Why does my output look scrambled when I try to read my results? 🤔

If you're working with Abaqus, you might have run into issues deciphering the `.msg`, `.dat`, and `.sta` files. You’re not alone! Many users find it tricky to make sense of these files without some guidance.

Solution:

1. Understanding the Files:
- .msg File: Contains messages and warnings during the analysis.
- .dat File: This is the detailed output file that has results for each analysis step.
- .sta File: Provides the status of the analysis, including whether it finished successfully.

2. Reading the Files:
- Use a text editor like Notepad++ or VS Code to open these files. They help highlight errors and make reading easier.
- For quick checks, you can search for keywords like “ERROR” or “WARNING”.

3. Using Python to Automate It:
You can write a simple script to extract relevant lines from these files. Here’s a small Python script that reads a `.msg` file and highlights any issues:

```python
file_path = 'your_file.msg' # Replace with your path
keyword = 'ERROR' # Keyword to search for

try:
with open(file_path, 'r') as file:
for line in file:
if keyword in line:
print(line.strip())
except IOError:
print("Error reading the file. Please check the path.")
```

This will help you quickly locate any errors or important messages in your `.msg` file instead of scrolling through all the text! 👌

Got any other file-reading tips or experiences? Share them in the comments — let's decode these files together! 📊

24/06/2025

🔍 Ever wondered how we can make complex models more manageable?

Welcome to the exciting world of Reduced-Order Modeling (ROM) and Geometric Deep Learning! 🌐 These concepts might sound intricate, but they play crucial roles in simplifying data analysis and enhancing machine learning. Let’s break them down!

🔑 Reduced-Order Modeling (ROM):
- Think of it like editing a movie. You take hours of footage and create a short trailer that captures the essence of the story. Similarly, ROM condenses complex mathematical models to make calculations faster and easier.
- It's especially useful in engineering and physics, where detailed simulations can be time-consuming. By using ROM, you can achieve accurate results with fewer resources!

✨ Geometric Deep Learning:
- This is all about understanding shapes and structures in data! Imagine trying to identify a cat in various poses. Geometric Deep Learning helps AI systems recognize different structures, whether it’s geometry in 3D models or graphs.
- By focusing on the relationships between data points, we can enhance everything from social network analysis to predicting protein structures in biology.

🌟 Why Does This Matter?:
- Both techniques lead to faster computations, improved predictions, and more efficient learning processes. They can revolutionize fields like aerospace, healthcare, and artificial intelligence!

Curious to learn more? What applications of these techniques do you find interesting? Share your thoughts below! Let's dive into the discussion! 🔽