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Use the Quanscient API to build and automate efficient design workflows

Learn how the Quanscient API works and how it can be used.

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Quanscient Allsolve

What is the Quanscient API?

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Cloud-based multiphysics simulation

Quanscient Allsolve, a cloud-based multiphysics simulation software, enables confident design decisions and faster design cycles with the ability to explore more design options taking into account real-world conditions and manufacturing constraints.
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Automation & integration

The Quanscient API enables automation and integration of simulations within design workflows, reducing manual effort, accelerating design cycles, and allowing for more thorough exploration of design options.
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Diverse functionalities

The API supports a wide range of functionalities, from simple parameter sweeps to complex optimization algorithms and inverse problem solving.
Challenges with existing design workflows

Local hardware dependencies, inflexible licensing, and limited interfacing hinder the efficiency of multiphysics simulation workflows

Local hardware
Traditional simulation software relies on local hardware, creating scalability and cost limitations.  Expanding computational resources is expensive and challenging to manage, while reducing resources can lead to underutilization and wasted investment.
Licensing inflexibility
Traditional simulation software often employs rigid licensing models. This can restrict usage, limit scalability, and increase costs, especially when adapting to fluctuating project demands.
Limited interfacing
Traditional simulation software often suffers from inconsistent and limited interfacing options.  Java-based interfaces may pose compatibility issues, while even prevalent Python interfaces can lack quality and usability. Furthermore, separate interface licensing and reliance on text-based communication can introduce inefficiencies and errors.
Manual steps
Running simulations often includes a lot of repetitive tasks in order to improve the models and get to the results. However, for large parametric sweeps, optimization, and large design-of-experiments studies, this turns unfeasible and limits the power of innovation that would otherwise be possible with simulation.
Lack of integration in the existing simulation pipelines
Many companies have already built their extensive integrated simulation pipelines with multiple software focusing on different use cases, from CAD geometry building all the way to postprocessing and results of analysis. To include a new software into that pipeline often means a lot of customizing and writing specialized scripts, which creates an additional load on resources needed in order to achieve optimal results.
Key features of the Quanscient API

The Quanscient API offers a modern, scalable, and cost-effective approach to multiphysics simulation

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Single modern API and SDK

The Quanscient API utilizes the same underlying structure as the graphical user interface, facilitating a seamless transition between interactive and programmatic simulation control.

This HTTP-based API provides comprehensive control over projects and simulations, and its OpenAPI definition enables client generation in various programming languages.

For enhanced usability and convenience, a Python SDK package offers a collection of classes and methods tailored to the public API.
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Automatic high-performance computing

Using the Quanscient API, you can run hundreds of simulations easily and concurrently, without preparing any hardware or worrying about handling any infrastructure setup.

Users can readily specify the desired computational resources within their scripts, enabling efficient parallel execution of hundreds of simulations.
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Easy integration into existing workflows

The Quanscient API integrates with existing simulation workflows, reducing the need for extensive customization or specialized scripting.

Its structure and functionality allow incorporation into established processes, enabling the use of cloud-based multiphysics with minimal disruption.
Use cases for the Quanscient API

The Quanscient API enables various simulation workflows, including AI training and automation

FEA plugin development

The Quanscient API allows engineers to develop custom Finite Element Analysis (FEA) plugins, integrating simulation directly into existing CAD or PCB design software for streamlined design and rapid iteration.
Scripting and advanced control

The Quanscient API enables advanced users with programmatic control over simulations, enabling complex parameter sweeps, custom optimization algorithms, and user-defined formulations.
Automated simulation pipelines

The Quanscient API allows for the creation of automated simulation pipelines, enabling efficient testing and validation of design iterations without manual intervention.
AI model training

The Quanscient API enables the generation of comprehensive datasets for training AI models, such as Neural Operators, facilitating rapid and accurate predictions.
SDM system integration

The Quanscient API facilitates integration with Simulation Data Management (SDM) systems, automating the storage and management of simulation results and design versions for enhanced traceability and collaboration.

Customer use case
Automated simulation workflow in fusion stellarator design

Proxima Fusion, a company developing stellarator-based fusion reactors, uses the Quanscient API to streamline the design and analysis of their superconducting coils.

Two critical challenges in their work are:

  • Quench events: Preparing for quench events, where the superconductor loses its superconductivity, is crucial. Uncontrolled quenches can lead to burned coils or even explosions.
  • Mechanical stress: Analyzing the mechanical stress the strong magnetic fields exert on the coil structure is equally important.

Because numerous coil design variations must be considered, Proxima Fusion needed an automated pipeline to perform basic checks after any design changes.

 

Automated simulation workflow with the Quanscient API

Working with Atled Engineering, Proxima Fusion implemented an automated simulation workflow using the Quanscient API. This workflow consists of several steps:

  1. Mesh preparation: The process starts with preparing a mesh, including appropriate tagging information. This mesh is then passed to the Quanscient API.
  2. Resource allocation and preliminary simulation: The API estimates the required degrees of freedom, configures the necessary computational resources (node count and type), and executes a preliminary simulation to determine the background field.
  3. Full-fidelity analysis: A full-fidelity coil analysis is then performed using a refined mesh and the previously calculated background field.
  4. Results export: Finally, the API facilitates the export of relevant results, including field maps and mechanical data.

In the end, Proxima Fusion achieved a fully automated coil design and analysis pipeline, enabling them to efficiently explore a wider range of designs, improve coil safety and reliability, and accelerate the development of their fusion reactor.

Learn more about this case study →

The current roadmap of API development

  • The Quanscient API is currently in a pilot phase with ongoing development based on user feedback.
  • The API roadmap is adaptable, allowing us to incorporate user needs and prioritize features accordingly.
  • We actively encourage users to provide input and help shape the future of the Quanscient API.
2024 Q3 Released alpha version, with the basic functionality of running simulations.  
2024 Q4

Working on beta version.

More functionality for managing projects, simulations and checking quota.

Better API key management with organization level keys.

  
2025 Q1-Q2

Planned first stable public release.

Public repository with the OpenAPI definition and Python SDK.

Meshing capability via the API with coordinate-based picking.

Improved capacity to run large amount of simulations in parallel.

  
2025 Q3 →

Improved integration to different data stores to reduce moving data around.

Webhooks for receiving simulation status, quota and other events.

  
Resources

Learn more about the API and its applications

API Webinar pdf
Webinar PDF summary

Automated workflows in multiphysics simulations with the Quanscient API

Download the 11-page PDF summary detailing our API webinar with our Chief Product Officer, Asser Lähdemäki.
Blog

The future of product design is simulation-driven and automated

Automation and integration are the pillars of future design and validation. Read how the Quanscient API enables these.
 

Read the full article →

Webinar recording

Automated workflows in multiphysics simulations with the Quanscient API

Replay the full 60-minute timestamped webinar with Proxima Fusion.
 

Watch the recording →

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Quanscient Allsolve

Try it out yourself

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  • Validate your use case using Allsolve's full simulation capabilities
  • Explore what's possible with scalable, cloud-native multiphysics simulation
  • Get tailored support and insights from our team

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