Design simulation helps manufacturers verify and validate the intended function of a product under development, as well as the manufacturability of the product. The word “simulation” is often used as generic term for computer-aided engineering (CAE). Over the years, several design simulation approaches have become standard components of product development in many industries, and they continue to grow in importance as inexpensive, faster computers and affordable, easy-to-use design simulation software allow users to address new technologies and applications.
Simulation models are sets of mathematical equations representing the behavior of the system in a physical domain of interest. The complexity of the mathematics depends on availability of data and varies in function of the application and the design stage.
In early development, typically more simple system representations use analytical assumptions and verify the interaction between several physical aspects on a concept-level. In late development stages, typically very complex, application-specific models are used for validation and refinement. The applications can cover aspects such as structural behavior, acoustics, system dynamics, crashworthiness, thermal and flow analysis, stress analysis, fuel economy, controls development and much more. Several technologies exist to support these different design stages and applications, such as:
- 1D CAE or systems simulation
- Finite element (FE) modeling
- Boundary element modeling
- Multi-body simulation
- Computational fluid dynamics (CFD)
Operational conditions can be added in the form of boundary conditions, load cases or constraints. Those can result from theoretical assumptions, measured data or the outcome of earlier simulations.
Design Simulation for Virtual Testing and Validation
Design simulation can include a wide range of analyses that virtually test behavior of a product under various operating and environmental conditions. As opposed to trial-and-error, a smart simulation process allows targeted implementation of design choices in various stages of the development cycle. This drastically reduces the need for recurrent, time-consuming testing on expensive physical prototypes, and subsequently shortens the total development time. An effective design simulation process helps companies reduce development costs and bring innovative products to the market faster than the competition.
Design Simulation for Manufacturability
Simulation of manufacturing processes, or the predicting of the manufacturing methods used to make the product, is commonly referred to as “process simulation” or “virtual manufacturing.” It includes the simulation of forming, stamping, machining and other processes to determine the manufacturability of the design, as well as the effect of design changes upon the manufacturing method. It is closer to manufacturing engineering than to the traditional stress engineering described above, though the underlying technology (FE modeling) is the same. Being able to view a simulation of the manufacturing process as you design the product results optimized manufacturing processes, as well as products that are optimized for performance, cost and quality.
Simulation Models versus Physical Prototypes
Simulation models offer more flexibility in the product development process compared to physical prototypes. Creating design alternatives often only requires a few button-clicks, and testing them does not call for a complicated setup. Moreover, design simulation can provide more types of analysis results that might be impossible to obtain through physical testing due to practical reasons. Simulation models can also allow you to virtually test locations in the product which cannot be physically accessed with measurement equipment, can output physical magnitudes for which no sensors exist, and provide a virtual view into the factory floor to understand manufacturing processes.
Because there is no risk of the tested object (product) getting damaged, simulating an extra operational condition is just a matter of applying a different boundary condition. This is especially useful if the product that needs to be tested is something like a satellite – where there is no preliminary physical prototype – because the final product is what would have to be tested, and it would not be desirable to perform extreme tests on it. Design simulation also has a much wider operational range than physical testing; it can virtually model and test conditions which are hard or even impossible to generate in a real-world environment and, because there is no risk of wasting materials, simulating a new manufacturing process is just a matter of working with a product definition to apply a specific manufacturing method.
Whereas physical testing will always remain an essential step in product development, the use of simulation models brings manufacturers closer to their ultimate dream of building one prototype only: the final product.
Benefits of Design Simulation
The benefits of design simulation include reducing product development costs and time by avoiding recurrent physical prototype testing, and improving quality.
- You can make design decisions that take into account their impact on functional performance as well as manufacturing
- Different functional aspects can be balanced during concept development
- Design alternatives can be efficiently evaluated, without trial-and-error testing on expensive physical prototypes, helping to promote design innovation
- Simulation can help optimize the design, removing unneeded material and hence weight, reducing cost and increasing design efficiency
- Design simulation can provide performance and manufacturability insights earlier in the development process, when design changes are less expensive to make
- Detailed, attribute-specific models can be used for validation and product refinement
- Simulation models can provide results which are hard or even impossible to measure on physical prototypes
- Simulation models can be virtually tested under extreme operational conditions
Design Simulation Software
Here are examples of design simulation software applications:
NX CAE is a modern simulation environment that enables engineering teams to reduce modeling time, shorten design-analysis iterations and improve productivity for FEA. NX CAE provides solutions for pre-and postprocessing, structural, thermal, flow, motion and multiphysics analyses, optimization, simulation data management and simulation-driven design.
NX Nastran is a finite element solver that analyzes stress, vibration, structural failure/durability, heat transfer, noise/acoustics and flutter/aeroelasticity.
LMS Virtual.Lab is an integrated suite of finite element, boundary element and multi-body modeling software that simulates real-life performance of mechatronic systems. It allows you to quickly build complex models and accurately study structural integrity, noise, sound, vibration, correlation to test results, system dynamics and durability performance, optimizing designs long before prototyping.
LMS Samtech contains a finite element method (FEM) solver suite to simulate critical performance engineering attributes for mechanical systems. It is designed to fulfill the precise requirements of applications such as wind turbine development, rotor dynamics, structural and thermal analyses, and composites. Its high-end solvers handle both nonlinear FEM and multi-body simulation. The software also features a high-level CAE integration platform for managing the aviation engineering process.
LMS Imagine.Lab helps you drive virtual, intelligent system design all along the design cycle. It offers all the necessary tools to create, manage and use models and data, answering various model-based systems engineering needs. It effectively deals with the specific challenges associated with mechatronic system simulation.
Femap is a CAD-independent, solver-neutral, Windows-native pre- and postprocessor for advanced engineering FEA. It provides engineers and analysts with an FEA modeling solution to handle even the most complex tasks easily, accurately and affordably.
Solid Edge Simulation is a built-in FEA tool for design engineers to validate part and assembly designs digitally within the Solid Edge environment. Based on proven Femap finite element modeling technology, Solid Edge Simulation significantly reduces the need for physical prototypes, thereby reducing material and testing costs, while saving design time.
Fibersim is a suite of software that supports all of the unique and complex design and manufacturing methodologies necessary for you to engineer innovative, durable and lightweight products and parts made of advanced composite materials. It integrates DFM and manufacturing engineering to provide CAD-embedded manufacturing process simulation, and ensures that designs are manufacturable through producibility simulation capabilities. The analysis interface also enables a bi-directional link to other CAE software for import and exporting detailed design data to support product analysis.
Seat Design Environment (SDE) is software that's fully integrated into commercial 3D CAD systems, for designing and manufacturing innovative transportation seat systems and interior components. It captures a complete digital product definition, eliminating extensive physical prototyping, and provides CAD-embedded manufacturing process simulation. Facilitating the early diagnosis of manufacturing issues with producibility simulation capabilities, the software ensures that the product is both efficiently manufactured and meets styling requirements.
The following software components are used by design simulation software developers as the foundation for their applications:
Parasolid is 3D geometric modeling component software, enabling users of Parasolid-based products to model complex parts and assemblies. It is used as the geometry engine in hundreds of different CAD, CAM and CAE applications.
D-Cubed Components are six software libraries that can be licensed by software developers for integration into their products. The capabilities they provide include parametric sketching, part and assembly design, motion simulation, collision detection, clearance measurement and hidden line visualization.