Geometric CAD TRIZ Cases

Multi-material topology optimization finds rotor magnet quantity, size, and placement to raise torque density while cutting permanent magnet use.

Controlled GSE load testing updates eVTOL battery models with voltage, current, and temperature data for more accurate state-of-health prediction.

Pole-based stability diagrams show how inertia and stiffness choices affect abnormal vibration in feedback-controlled motor-driven mechanisms.

A 3D digital twin guides vehicles to available chargers and exit paths, improving charging station control and user interaction.

A virtual vehicle simulation reproduces front lamp control behavior and illuminated driver views, cutting verification effort and correction time.

A shared scene encoder and agent-specific decoder cut trajectory prediction latency while preserving context and accuracy for autonomous driving.

Frequency-domain permeability and Maxwell matrices replace mesh-heavy FEM to verify linear motor force, flux linkage, Back-EMF, and inductance faster.

A shared scene encoder and agent-specific fusion cut trajectory prediction latency and compute while preserving autonomous driving accuracy.

Real-world trace extraction and inferred agent goals enable closed-loop AV simulation that cuts road testing time while preserving realism.

Multi-stage layout generation builds PFS diagrams from 3D process data, cutting manual redraw time when industrial models change.

Balancing top cross beam and pillar inertia helps ROPS structures deform together, absorb rollover impact energy, and avoid excess weight.

Signal-network tracing identifies which control unit inputs can affect OBD-relevant outputs, cutting manual compliance checks in complex vehicle systems.

A shared global environment model generates synchronized sensor data for multiple AGVs, then converts it to local frames for realistic control.

Intentional lattice mismatch and band gap selection shift solar cell design toward higher end-of-life efficiency under space heat and radiation.

Camera image features are mapped into BEV and decoded with transformers to estimate road objects accurately with lower real-time compute and memory demand.

BEV feature transformation and transformer object embeddings improve road geometry estimation accuracy without heavy compute or memory use.

Models realistic nearby vehicle behavior and configurable traffic scenarios to evaluate autonomous vehicle motion planners more thoroughly.

Real logged vehicle data is augmented into varied actor scenarios, boosting training data volume without losing real-world driving realism.

Converts a 3D assembly model into occupied and free space to auto-route wires with collision avoidance and shorter paths.

Measures display lag from driving behavior data to adjust cockpit simulation load and keep travel and component images real-time.

Triangular surface models cut storage and processing load while enabling conflict-free routing of variable-size MEP paths in bounded 3D spaces.

WFSim-based layout and yaw tuning cuts wake losses, lowers downstream turbine loads, and raises wind farm power output.

By adding dummy patterns where local pattern volume is low, this template layout evens residual film thickness in semiconductor imprinting.

Dynamic thermal modeling sizes power plant transformers for variable renewable loads, cutting over-dimensioning while meeting temperature limits.

Machine learning predicts viscoelastic and processability properties of tire tread compounds, cutting lab testing time, cost, and variability.

Dynamic thermal sizing uses load and ambient temperature profiles to cut transformer overdesign while preserving emergency loading reliability.

Shared vehicle dimension and motion data builds digitized body models that cut real-time sensing load while improving control reliability.

Virtual vehicles fill unsensed ramp regions to reproduce and predict traffic status more accurately for physical road traffic control.

Adversarial reinforcement learning generates actor trajectories that expose rare autonomous driving defects faster while reducing real-world test miles.

Realistic simulated vehicle behaviors and perception playback improve autonomous motion planner testing capacity without physical road trials.

Model-based grading of electrode thickness cuts trial-and-error design, lowers overpotential, and improves battery energy, power, and cycle life.

A fifth aligning link keeps scrub radius and track width constant through suspension travel, eliminating bump steer and steering feedback.

Adversarial reinforcement learning generates actor trajectories in simulation to expose rare autonomous vehicle software defects with fewer test miles.

Automated RVE meshing converts fuel cell unit-cell regions into simpler FEM submodels, reducing setup effort and simulation time.