How does nTop work?
The nTop Approach – Building Design Intelligence
When using nTop for conceptual design, you are encoding your design logic into a set of parameters and algorithms that drive the design, rather than defining the geometry of an object.
In CAD, you use drawings to create geometry, whereas in nTop, you’re using functions to construct a design space that enables rapid iteration, analysis, and optimization, ultimately leading to better solutions and faster development cycles.
From Requirements to Computational Logic
Your workflow in nTop follows a different pattern than traditional CAD:
- Start with Requirements: Define what needs to be achieved, not how it looks
- Decompose into Logic: Break the problem into relationships and rules
- Build Parametric Relationships: Connect parameters to create flexible behavior
- Validate and Iterate: Test the design space, not just individual designs
The Notebook as Your Program
Think of your nTop notebook as source code for your design. You use blocks to compose functions, and the structure you create determines how data flows through your model. Also, every piece of data has a type (Curve, Body, Field, Number, etc.), and types guide how blocks can connect. This system helps prevent errors and makes complex logic more manageable. If you’ve written code or built formulas in Excel, the mindset is similar: you’re encoding logic and establishing relationships to make your model flexible and reusable.
Key Principles:
- Every element can be parametric
- Logic flows through connected blocks
- Documentation travels with the model
- Changes propagate automatically and reliably
The Mathematical Foundation – Signed Distance Fields
What Are Signed Distance Fields (SDFs)?
At the heart of everything in nTop are Signed Distance Fields (SDFs). These are the mathematical representations of geometry that store the distance from any point in space to the nearest surface.
Distance values are “signed” to indicate position:
- Negative values: Inside the geometry
- Positive values: Outside the geometry
- Zero: Exactly on the surface boundary
Why SDFs Matter
This mathematical representation gives nTop its unique capabilities:
- Parametric Flexibility: Unlike mesh-based or B-rep modeling, fields are mathematically defined functions. Your models can “flex” and adapt to significant parameter changes without topological errors.
- Complex Geometry Made Simple: Operations that are difficult in traditional CAD, like smooth blending between disparate shapes, geometry-driven texturing, and variable-density lattices, become straightforward with fields.
- Computational Efficiency: Field operations are evaluated on-demand, giving you precise control over computational resources while maintaining model responsiveness.
Everything Has a Field
Different geometric types interact with fields in unique ways:
- Point: Volumeless—only positive distances in all directions
- Curve: One-dimensional path—distance to nearest point on curve
- Plane: Divides space into positive/negative half-spaces
- Profile: Closed 2D shape with interior/exterior regions
- Primitive Bodies: Full volumetric shapes with well-defined interiors
Implicit Modeling
Now let’s see how it comes together in nTop’s implicit modeling approach.
Transcript
In nTop, we generate geometry with implicit modeling, a technique that defines shapes using mathematical functions rather than surface boundaries. Implicit bodies are represented by functions with Signed Distance Fields or SDFs. The function is evaluated at all points in space, and the SDF represents the number that’s returned: negative inside the body, positive outside, and zero at the body’s surface. Later modeling courses will dive deeper into the intricacies of SDFs and how we can manipulate them to adjust our implicit models. Unlike Boundary Represented or b-rep models that represent solids with discrete features like edges and fillets, implicit bodies define entire volumes with a single implicit function. As a result, the geometry is continuous and resolution-independent. So you get robust, watertight shapes with no faces to fail and no edges to break. This makes implicit bodies incredibly fast and stable to iterate upon. You can change inputs, dimensions, logic, relationships, and the implicit bodies intelligently update to match your design intent without fragile dependencies or cascading failures. Whether you’re designing a feature, a full part, or an entire system, the speed of iteration stays the same. In addition to being geometrically adept, implicit bodies also couple seamlessly with simulation results because of their shared, field-based nature. This empowers engineers to achieve more optimal and higher performing designs faster. You may wonder when you should use implicit modeling and how it’s different from other forms of geometry you might be more familiar with. Traditional CAD tools excel at creating precise geometry, but often fall short during the design process when there’s a need to explore multiple design variations quickly, automate repetitive tasks, optimize designs based on performance data, create complex parameter-driven geometry, and document design intent and decision-making.
Implicit modeling allows us to achieve rapid exploration of design alternatives, automation of repetitive design tasks, integration of analysis results into the design process, creation of reusable parametric components, and optimization via rapid iteration through the design space. Implicit modeling fundamentally changes what’s possible in computational design. With nTop, you can focus on design intent over modeling constraints, explore more design iterations, and create geometry that was previously impossible.
0:00 Implicit Modeling in nTop
0:35 Advantages of Implicit Bodies
1:02 Implicit vs. Traditional CAD
1:28 Benefits of Implicit Modeling
The nTop Advantage – Why This Approach Matters
1. True Parametric Freedom
Traditional CAD systems often struggle with significant parameter changes. Change a hole diameter, and features might fail. Modify a fillet, and downstream operations break.
nTop’s field-based approach eliminates these failures. Since geometry is represented mathematically rather than as fixed topology, your models remain robust under dramatic parameter changes.
2. Design Space Exploration
Instead of creating individual design files, you build design spaces—parametric models that can generate many valid variations.
nTop Approach:
- Create one parametric notebook
- Generate unlimited design variants
- Systematic exploration of the design space
- Automated optimization and analysis
3. Engineering Knowledge Preservation
Your nTop notebooks become repositories of engineering knowledge. The logic, constraints, and design rules are captured in executable form, not just as static documentation.
What Gets Preserved:
- Design rules and relationships
- Manufacturing constraints
- Validation logic
- Performance requirements
- Design rationale and decision history