A SIMPLE FRAMEWORK FOR COMPUTATIONAL ENGINEERING TO LINK THE VIRTUAL WITH
THE NATURAL WORLD.
We build easy-to-use tools for engineers, enabling you to work more
efficiently. As engineering projects grow increasingly complex, the
existing software stack falls short in adapting to a rapidly changing
landscape with numerous diverse domains. Most engineering software is
overly specialized and complicated, making it difficult for non-experts
to use effectively.
We provide software tools that facilitate teamwork and collaboration
across various domains and departments. Our tools enable you to
integrate engineering knowledge directly into the product, creating an
engineering system linked to all relevant data points. This single
source of truth forms the foundation of an effective engineering system,
allowing seamless collaboration with others. Given the sensitivity of
engineering data and intellectual property, our tools are designed with
robust data security and safety measures.
We view the engineering process as an exciting and dynamic journey, free
from tedious and repetitive tasks. Consider the sketch below, which
illustrates this process as a series of cycles where each iteration
brings new insights and data. These new insights and data are then used
to optimize and tweak the model, facilitating further iterations and
ultimately leading to the most fitting solution.
[ Figure 1 ] iterative process in computational engineering
To achieve this ambitious goal, we have decided to
open-source most of our software. By doing
so, we aim to build trust within our community. However, to provide the
most value, some parts will remain
closed-source to allow for custom and
privacy-critical solutions for end-users and other companies. If you
want to see what the future holds for powell-donovan, take a look at our
roadmap.
We believe in the value that open-source software brings to all users.
Our core modules are open-sourced and hosted on
GitHub. Powell-Donovan
is structured as an open-source development environment (dev-environment) that hosts all the core modules in a single workspace. If you want to
contribute to the capabilities of Powell-Donovan, this is the best way
to get involved.
The dev-environment is structured into individual modules, each
representing a different capability. These modules can be compiled into
standalone, hostable solutions. Anyone can build these solutions, which
can either be locally hosted and accessed via the powell-donovan
web-interface (coming soon)
or accessed directly from our provided servers.
If you want to host a solution, the best way to get started is by
following our guide on
How to host a solution.
In addition to our public open-source solutions, we offer private
solutions that are custom-built for end-users or other companies. These
private solutions are not open-source, as they contain customer data and
intellectual property, which is not available to the public.
Except for being closed-source, these private solutions use the same
functionality provided by the core modules. Private solutions can also
be self-hosted or hosted on our servers, depending on where the compute
happens and where the data is stored. Access to any solution is the
same, using our
web-interface (coming soon).
Building private solutions also serves as a means to generate sufficient
revenue to sustain the continued development of powell-donovan.
If you're interested in building a private solution or custom
functionality, feel free to reach out to us at
powell-donovan@outlook.com.
Given our current early stage of development, this roadmap is subject to
regular updates and changes. Nonetheless, here's a rough outline of what
to expect in the near future.
┌─[ 06/2024 ] started
│
├─[ today ]
│
└─[ to be dated ]
Who are the people whom this software is intended for?
This software is intended for working engineers seeking tools to
streamline their workflows and reduce inefficiencies encountered with
existing software solutions.
What are some fields or industries where this software could find
practical applications?
This software could find practical applications in fields such as
mechanical engineering, civil engineering, aerospace engineering,
electrical engineering, environmental engineering, biomedical
engineering, manufacturing engineering, and materials science, among
others. Its versatility enables its use across various industries
where computational engineering plays a crucial role in
problem-solving and optimization.