Simulation Trends and Technologies

Executive Overview

The overall simulation software market today is comprised of a broad and diverse set of technologies and applications. The traditional core of the simulation software market is computer-aided engineering (CAE), which was developed primarily for product design testing.

Today, the simulation software market has significantly expanded in scope to include simulation software for many industries and areas of science. The all-inclusive industrial market includes everything from communications, automotive, aerospace, consumer electronics, military systems, transportation systems, smart buildings and cities, industrial controls, pharmaceuticals, and drug development, and much more.  Advanced simulation applications enable engineers, scientists, manufacturers, and builders to virtually simulate the physical world to test, validate, optimize, and experience our products, systems, and environment. 

CAE is the use of computer software to simulate the fit, form, function, and ultimately the performance of a product to improve the design or facilitate solving engineering problems for various industries. The application of CAE software may include 3D virtual simulation, validation, and optimization of products, processes, and manufacturing. Typically, a 3D computer-aided design (CAD) product model is developed that is used by CAE software for product testing.

In addition to CAE simulation solutions for product testing, there has been an emergence of 3D virtual simulation software across a wide range of applications for science, industry, infrastructure, and consumers. This advanced level of simulation software allows users to virtually represent the physical world to validate, test, and examine products, systems, and environments before using them in the physical world.

Scientists and researchers are now able to simulate at the molecular level virtually, allowing them to create new compounds for drugs and new materials for various industries. Designers can plan and create 3D virtual cities and infrastructure for the next generation of smart cities. Manufacturing engineers are now able to create and fabricate parts by creating new materials specifically for additive manufacturing and design shapes and functions that could never be made using conventional methods. All of this is enabled by advanced 3D simulation tools that are transforming science, industry, and our physical environment. This strategy report includes applications for traditional CAE simulation and advanced simulation applications for science and industry.

Current Trends and Technologies in Simulation

The solutions that drive today’s comprehensive simulation platforms represent leading-edge technologies across multiple engineering and scientific disciplines. These simulation platforms are typically components of a complete design/test/validate/build product lifecycle solution set provided by PLM suppliers. These PLM providers are leading the way with technologies and solutions that enable their customers to evolve new business models based on the digital twin, generative design for additive manufacturing and material science, and Industrial IoT edge platforms that drive next-generation analytics. Virtual simulation science and technology is involved in all these technologies.

CAE Simulation Tools Test and Validate Engineering Designs

Normally, a CAE process consists of preprocessing, solving, and postprocessing steps. In the preprocessing phase, engineers model the geometry and physical properties of the design, as well as the environmental effects on the design in the form of applied loads or constraints. In the solving phase, the model is solved using an appropriate mathematical formulation of the fundamental physics. In the postprocessing phase, the results are presented to the designer for review and analysis.

Some of the benefits of CAE are:

• Product development cost and time are reduced, with improvement of product quality and life.
• Design of product can be implemented, evaluated, and improved.
• Computer simulation-based design will substitute for the physical prototype testing and results in cost and time savings.
• CAE can give insights about the performance of product prior to development phase when design changes will be less expensive.
• CAE provides information regarding the risk and reliability engineering of the product design.
• Combined CAE data and process management make it possible to effectively strengthen performance insights and improve designs to a broader application.
• Maintenance cost is reduced by identifying and eliminating potential problems. When properly integrated into product design and manufacturing development, CAE can enable earlier problem identification, which can dramatically reduce the costs associated with product wear-out.

In many branches of applied science, engineers and researchers cope with problems exhibiting complex systems of stresses, strains, vibrations, heat transfer, fluid flow, electric fields, and magnetic fields, to name a few. These are commonly modeled using complex systems of differential equations that are difficult to solve.

One approach for practitioners is to break down the complex geometric system under study into small, regularly shaped elements (meshes), each of which is easy to solve. Each element interacts with its neighbors based on physics equations and these in turn are solved. This may have to be done several times until the whole system starts to narrow down (or converge) to a useful set of answers. This method is called finite element analysis (FEA). Engineers make use of this fundamental aspect of CAE to carry out many calculations necessary to solve these physical product test problems with mathematical models and virtual simulation.

Comprehensive Simulation Platforms Drive Concurrent Product Design and Validation

Today’s multi-functional simulation platforms offered by PLM suppliers enable product designers to test their design concepts concurrently. This allows engineers to move through the product development lifecycle process faster and more efficiently, assuring that the product meets all functional requirements prior to the manufacturing process. As the products become increasingly more complex due to multi-engineering discipline integration requirements, engineers can use model-based design (MBD) simulation solutions to assess and optimize the performance of cyber-physical (CPS) and mechatronic systems virtually. This enables CPS engineers to simulate, test, and validate their systems’ design in a concurrent lifecycle process from early development stages until the final performance validation and controls calibration.

This concurrent design/simulate/test/validate process has become an integral part of the MBD approach to systems engineering. Aside from encouraging concurrent design, a system engineering approach to mechatronic development often helps reduce complexity, lower component costs, and increase integration efficiency. With an increasing number of products being designed with built-in intelligence, model-based system design drives engineering organizations toward more efficient engineering practices.

As the automotive industry gears up production for electric vehicles, smart cities and smart infrastructure become more prevalent, and intelligence is embedded in every new product, all these industries will need to deal with complex systems integration challenges. PLM suppliers are meeting this challenge with comprehensive simulation platforms that provide an end-to-end, closed-loop development process.

Table of Contents

• Executive Overview
• Current Trends and Technologies in Simulation
• Simulation Strategies for Users
• Market Strategies for Simulation Suppliers
• Recommendations

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