| Just Released! HEEDS NP|
Nonparametric Shape Optimization Software
We are pleased to announce the release of HEEDS® NP, a new software package for nonparametric shape optimization.
HEEDS NP adjusts the surface shape of a 2D or 3D solid to minimize volume while satisfying stress and/or displacement constraints.
HEEDS NP adds mass where needed in regions of high stress and removes mass where possible in regions of low stress. The mass is added by moving the existing nodes, so there are no predefined parametric shapes. No elements are deleted, and no new elements are added to the model.
HEEDS NP modifies the nodal locations directly and is able to generate a wide variety of shapes with very little problem definition up front. The direction and amount of a nodal movement is calculated based on the stress state in the model. HEEDS NP also intelligently maintains smooth surfaces as it morphs a shape.
Learn more about HEEDS NP
|HEEDS NP Reduces Wheel Bracket Mass by 14.2% for Magline|Red Cedar Technology recently used HEEDS NP to reduce the mass of a wheel bracket for Magliner hand trucks.
The final design had a mass that was 14.2% lower than the baseline design, and stress was reduced by up to 20% for several critical load cases to retain superior durability and performance. Read the entire success story
|New! Red Cedar University|
Your Trusted Source for Optimization Education
We've recently launched Red Cedar University, a new online resource for educational and training materials related to optimization.
We are continuously adding content, with the goal of providing the most complete and current educational materials available on the theory and application of optimization, including:
- Detailed optimization theory manuals
- Short courses
- Optimization Viewpoints blog
- Animated tutorials
- White papers
- Application examples
...and much more!
Whether you are an engineer, manager, teacher or student of optimization, you'll find the content at Red Cedar University relevant to you. And, it's free and accessible to anyone.
Visit www.redcedaru.com today, and sign up to receive blog and tips posts by email or RSS!
|When More Is Not Better|
Suppose that your favorite finite element software boasted the following claims:
"Over a dozen equation solvers are available to approximate the solution of your problem, and each solver contains a rich set of parameters that you can define to tune the solver's performance. To maximize the accuracy of your solution and the efficiency of the solution process, simply choose the solver that is intended for your problem type, and then tune it properly. Though it is often not possible to classify your problem type beforehand, usually the right solver can be identified within 3-5 attempts. Then, you can use an iterative tuning process to make the solution even more accurate and efficient."
If the above statements were true, then each finite element solution would require a full-blown research project to find the right equation solver. The added time and cost of numerous solution iterations would offset many of the benefits of the finite element method within the design process.
Users would get frustrated by their inability to systematically determine what solver to use, and many would eventually avoid using the technology altogether. This state of affairs would be completely unacceptable to modern users of the finite element method. Even the idea seems absurd.
But what if we modify the above hypothetical scenario by simply replacing "equation solvers" with "optimization algorithms" and "solution process" with "search process." Then, we would arrive at the actual claims made about most modern optimization software:
"Over a dozen optimization algorithms are available to approximate the solution of your problem, and each algorithm contains a rich set of parameters that you can define to tune the algorithm's performance. To maximize the accuracy of your solution and the efficiency of the search process, simply choose the algorithm that is intended for your problem type, and then tune it properly. Though it is often not possible to classify your problem type beforehand, usually the right algorithm can be identified within 3-5 attempts. Then, you can use an iterative tuning process to make the solution even more accurate and efficient."
Somehow the absurdity of this statement is not quite as obvious. Most optimization software tool developers are still racing to see who can boast the longest list of algorithms on their product data sheets.
The losers in this race are clearly the users of such optimization tools.
Rather than adding value or clarity to the design process, a longer list of optimization algorithms contributes to inefficiency and confusion. The use of optimization technology will not become mainstream until users rely on a single algorithm to solve many broad classes of problems in an efficient and robust manner. This will require a major paradigm shift in the way search algorithms are developed and how they behave.
What is needed is a search process that does more than follow a fixed set of instructions based on a predefined strategy. One that can lead and organize a team of explorers, each with a diverse and complementary set of skills. One that is agile in adapting the search process to the unforeseen local conditions in various parts of the design space, while also carrying out a broad and efficient exploration of the entire domain. A highly skilled and multilingual trekker. A veritable Sherpa.
Visit the Optimization Viewpoints Blog
|Join the North American HEEDS User Group (NAHUG)|NAHUG is a growing community of HEEDS users and others interested in discussing applications of HEEDS to solve unique and challenging optimization problems.
The group gathers quarterly by Webinar, and discussions include HEEDS success stories, development updates, and presentations by featured partners.
The next NAHUG meeting is scheduled for January 26, 2011 at 2 p.m. (Eastern Time). If you would more information about the meeting, please contact us.
As always, we hope you have found this issue informative and interesting. If you have questions or feedback, please don't hesitate to contact us.
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