Multidisciplinary Design Optimization

Technical Platform

An engineering optimization environment for automating CAD, CAE, FEA, CFD and multiphysics design loops. SmartDO connects simulation parameters, executes iterative analyses, evaluates objectives and constraints, and searches for improved feasible designs.

View Optimization Workflow Explore Solver Technology

SmartDO Optimization Core

CAD Parameters

FEA / Structure

CFD / Thermal

Objectives

Constraints

Core Capabilities

Automated optimization for complex engineering systems

SmartDO is structured around solver orchestration, parameter exchange, design-space exploration and automatic handling of failed or infeasible analyses.

Direct Global Search

Searches beyond a nearby local optimum using adaptive search direction, step control, tunneling and hill-climbing strategies.

Gradient-Based NLP

Efficient constrained nonlinear optimization for continuous and differentiable engineering responses.

Robust Genetic Algorithms

Population-based search for discrete, mixed-variable, discontinuous or highly nonlinear design spaces.

Multi-Objective Optimization

Evaluates competing objectives through Pareto-based methods to identify balanced engineering trade-offs.

Failure-Aware Automation

Detects failed CAD or CAE evaluations, non-convergence and invalid output, then adapts the optimization process.

Open Programmable Architecture

Supports scripted workflow customization using Tcl/Tk and Python for internal tools, custom solvers and automated engineering processes.

Technical Workflow

Closed-loop engineering optimization

The optimization loop connects model parameters, simulation execution, result extraction and solver decisions into one repeatable process.

Define Parameters

Assign geometry, material, process and operating parameters as design variables.

Set Objectives

Define targets such as minimum mass, pressure loss, stress, temperature or cost.

Set Constraints

Specify allowable limits for strength, displacement, temperature, flow and geometry.

Execute CAE

Automatically update the model, run the connected solver and extract response data.

Update Design

Use the optimization algorithm to create the next candidate until convergence.

Solver Technology

Deterministic and stochastic search strategies

Different engineering problems require different optimization methods. SmartDO can apply gradient-driven search, robust genetic search or hybrid workflows.

Search mechanisms

The optimization engine is designed to operate in noisy, constrained and high-dimensional CAE environments.

Active constraint recognition Prioritizes constraints that control the current feasible search boundary.

Response smoothing Reduces the influence of mesh discretization and numerical noise.

Adaptive step control Adjusts search direction and step size according to response behaviour.

Infeasible-start handling Moves an initial invalid design toward the feasible domain before refinement.

Pareto exploration Generates alternatives when objectives conflict with one another

Engineering Domains

Multidisciplinary and multiphysics applications

The platform can coordinate parameters and responses across individual physics solvers or tightly coupled simulation workflows.

Structural MechanicsStress, displacement, fatigue, buckling and lightweight design.

Computational Fluid DynamicsPressure drop, flow uniformity, drag and aerodynamic performance.

Thermal EngineeringPeak temperature, heat transfer, thermal resistance and cooling design.

Fluid–Structure InteractionCoupled pressure, deformation, vibration and performance responses.

ElectromagneticsField distribution, signal behaviour, antenna and electronic design.

CrashworthinessEnergy absorption, intrusion, structural integrity and mass reduction.

Material CalibrationInverse identification and fitting of constitutive model parameters.

Automatic ControlController parameter tuning and dynamic system response optimization.

Integration Architecture

Connect external engineering tools and in-house codes

Integration can be configured through graphical links or programmable interfaces, depending on the solver and automation requirement.

Layer	Technical Function	Typical Data Exchange	Implementation Method
CAD / Geometry	Modify dimensions, shapes and topology controls	Dimensions, feature values, geometry parameters	SmartLink, scripting, file or API-based exchange
CAE Pre-processing	Update materials, mesh, loads and boundary conditions	Mesh controls, load cases, material properties	Solver commands, templates or automation scripts
Solver Execution	Launch structural, CFD, thermal or coupled simulations	Input decks, command parameters, job status	Batch execution, external process control
Post-processing	Extract objective and constraint responses	Stress, displacement, temperature, flow and frequency	Result readers, reports, text or database parsing
Optimization Core	Evaluate feasibility and generate the next design	Design vectors, objective values, constraints	Gradient, genetic, hybrid and multi-objective methods

Problem Definition

Suitable optimization model structure

A reliable workflow requires stable CAD regeneration, repeatable meshing, validated boundary conditions, clearly defined objectives and measurable engineering constraints. Computational demand increaseswith the number of variables, physics domains and solver evaluations.

VariablesGeometry, material, process, operating conditions

ObjectivesMinimize, maximize or target engineering responses

ConstraintsStrength, thermal, flow, frequency and geometric limits

OutputsOptimum design, convergence history and trade-off data

SmartDO