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AETHER OptResearch
AETHER Opt

AETHER Opt

Generative Design Optimization Engine

ResearchRHX.LAB experiment

Find verifiable design candidates from ideas and constraints.

AETHER handles performance goals, weight, and manufacturing constraints in early planning and connects to RHXY Plan as a design exploration layer.

What it enables

Goal-led exploration

Turn goals and constraints into a design search space.

Candidate comparison

Compare directions by strength, weight, and manufacturability.

Verification handoff

Package promising candidates for NEXUS and RHXY Sim validation.

How it works

01

Frame

Structure goals, files, constraints, and evaluation criteria.

02

Explore

Generate parametric or topology candidates and narrow the search.

03

Select

Show trade-offs and validation needs so users can decide.

Example outputs

AETHER Opt
Experiment preview
Candidate design set
Strength-weight trade-offs
Manufacturing constraint checks
Validation request package

Connected to RHXY Plan design exploration.

Currently in research, focused on verifiable candidate generation and RHXY Sim handoff.

Current status

2D topology optimizationComplete
3D SIMP optimizationResearch
Manufacturing constraint integrationResearch

Technical details

Goal definition (NL) → Parametric space generation → Topology optimization (SIMP/Level-set) → Candidate geometry generation → NEXUS solver verification → Pareto front visualization → Final candidate selection Manufacturing constraints (minimum thickness, draft angles, overhang limits) are included in the optimization loop to generate only manufacturable geometries.

Core capabilities

Topology optimization (SIMP, Level-set)
Multi-objective optimization (strength/weight/cost)
Manufacturing constraints (min thickness, draft)
Automated parametric studies
NEXUS solver-integrated verification
Pareto front visualization
AI-driven design suggestions

Roadmap

2D topology optimizationComplete
3D SIMP optimizationResearch
Manufacturing constraint integrationResearch
NEXUS solver integrationPlanned
AI design suggestionsPlanned

Disclosure Scope

Optimization algorithm direction and benchmark results are shared as research notes. Implementation details and trained models are proprietary.

AETHER Opt — RHX.LAB | RHX.LAB