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The RAMDO Software

Reliability Analysis & Multidisciplinary Design Optimization

RAMDO increases the reliability and robustness of optimized designs while significantly reducing the time and limited computer resources needed for an accurate solution of multidisciplinary design problems. RAMDO is a game changer; instead of spending money on modifying designs that have failed in the field, companies will spend less money up front to produce a better product, protecting against warranty concerns and strained customer relationships. RAMDO has comprehensive capabilities that will assist users.

PREVIOUSLY APPLIED APPLICATIONS

  • Casting Process Design Optimization

  • Electromagnetic Device Designs

  • Superconducting Magnetic Energy Storage System Design

  • Fluid-Solid Interaction (FSI) Problems

  • Reduce Residual Deformation in Welding

  • Thermo-Elasto-Plastic Residual Deformation

  • Electro-Thermal Polysilicon Microactuator

  • High-Fidelity CFD Outputs

  • Fatigue Analysis and Durability

  • Explosion Analysis and Survivability

  • Vehicle and Machine Dynamics

  • Noise, Vibration, and Harshness (NVH)

  • Crashworthiness

  • Wind Turbine Blades Design

  • Wind Turbine Drivetrain Dynamics under Wind Load and Axial Misalignment Uncertainties

POTENTIAL APPLICATIONS

  • Robotic Systems

  • Advanced and Hybrid Powertrain

  • Human Centered Design

  • MEMS and Nano/Micromechanics Based Materials Design

EXAMPLE SOURCES OF VARIABILITY AND UNCERTAINTY

  • Material Properties

  • Gauge and Geometry

  • Loads

  • Ocean Wave

  • Wind Velocity

  • Ground Surface

  • Electric Current

  • Climate/Sunlight

  • Human Factors

  • Machine Error

  • Explosion

  • Manufacturing Process

  • Earthquake and Tsunami

EXAMPLES OF OUTPUT VARIABILITY AND UNCERTAINTY

  • Cost

  • Noise

  • Vibration

  • Safety

  • Durability

  • Deformation

  • Stress and Strain

  • Temperature

  • Pressure

  • Survivability

  • Porosity

  • Flux Density

  • Magnetic Field

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SAMPLING-BASED RBDO

Perform RBDO using Monte Carlo simulation, surrogate modeling methods, and stochastic design sensitivity.

SENSITIVITY-BASED RBDO

Perform inverse reliability analysis and RBDO using design sensitivity of performance measures provided by the simulation solver (or user).

INPUT MODELING AND VARIABLE SCREENING

Provide best fit distribution types and parameters based on the user provided input data. Reduce dimension of RBDO problems using efficient and effective variable screening method.

OUTPUT DISTRIBUTION

Generate response output distribution using Monte Carlo simulation and surrogate modeling methods.

RELIABILITY-BASED ROBUST DESIGN OPTIMIZATION (RBRDO)

Provide an optimum design which yields maximum robustness while satisfying target reliability of performance measures.

CONFIDENCE-BASED RBDO FOR LIMITED INPUT DATA

Provides user confidence in the RBDO optimum design that meets the target reliability in the presence of insufficient input data.