Optiworks: A human-centric framework for high-resolution topology optimization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Advancements in additive manufacturing have significantly broadened the application of topology optimization. However, the mathematical complexity of these formulations often hinders rapid progress in research and usability. This paper introduces Optiworks, an all-in-one human-centric desktop application that simplifies the entire optimization process from domain initialization to the export of the final optimized design. The software incorporates two key algorithms: the Solid Isotropic Material with Penalization (SIMP) and Smooth-Edged Material Distribution for Optimizing Topology (SEMDOT). Users can select the most suitable method based on their specific needs. Additional features of Optiworks include symmetry enforcement to expedite optimization, static analysis to assess the impact of design changes on total displacement, equivalent strain, and von-mises stress, and the generation of smooth boundaries even with relatively coarse meshes. These capabilities eliminate the need for further post-processing, allowing users to directly export the optimized output as an STL file for immediate 3D printing. Several numerical examples demonstrate the software’s effectiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it