Computer-aided design (CAD) & Computer-aided Engineering (CAE) have transformed engineering analysis to virtual simulation

Rajesh Uppal September 13, 2022 AI & IT, Industry, Manufacturing Comments Off on Computer-aided design (CAD) & Computer-aided Engineering (CAE) have transformed engineering analysis to virtual simulation 338 Views

In today’s world, engineering plays a part in almost everything that surrounds us, and with innovations continuously being brought to market, engineering is experiencing a steady growth extending to all of its wide-ranging facets.

Computer-aided engineering (CAE) is the broad usage of computer software to aid in engineering analysis tasks. Computer-aided engineering (CAE) is the use of computer software to simulate performance in order to improve product designs or assist in the resolution of engineering problems for a wide range of industries. This includes simulation, validation and optimization of products, processes, and manufacturing tools.

Computer-aided design (CAD)

Computer-aided design (CAD) is a category of CAE related to the physical layout and drawing development of a system design. CAD programs specific to the electronics industry are known as electronic CAD (ECAD) or electronic design automation (EDA). With 3D CAD, you can share, review, simulate, and modify designs easily, opening doors to innovative and differentiated products that get to market fast. Metal fabrication, carpentry, and 3D printing are some common applications for CAD that are valuable in manufacturing.

CAD designers are vital to the aerospace industry because three-dimensional models help engineers, designers, and clients determine flaws and benefits of airplanes in the project stage. An extensive three-dimensional model, taking into account all of the engineering aspects of individual projects, can help expose a dangerous or inefficient flight process.

CAD platforms ensure that multiple prototypes need not be produced for testing, thus saving an immense amount of resources. These platforms also help in speeding up the product design cycle and increases operational efficiency, reducing production cost in the process.

The most important capability of a CAD platform is its capability to create 2D/ 3D objects with the help of tools such as extrude, cut, and revolve. CAD applications used in the Aerospace and Defence industry are parametric, which means that designers can change the calibration of the objects according to the specifications.

When an iteration can cost millions of dollars, a minute miscalculation of less than one-tenth of a millimeter can cause a catastrophic accident, it is indeed prudent to have a perfect design ready in the first place.

Computer-Aided Engineering (CAE)

Computer-Aided Engineering (CAE) is a fast emerging field that takes CAD to another level. While CAD is useful in creating 2D and 3D models of a product, CAE software allows a deeper engineering analysis of objects. CAE thus finds applications in engineering fields like fluid dynamics, kinematics, stress analysis, finite element analysis, etc., typically where product development is concerned.

Software used to analyse CAD geometry tools that have been developed to support these activities are considered CAE tools. CAE encompasses not only CAD but also Computer-Aided Manufacturing (CAM), Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD) multibody dynamics (MBD), durability and optimization. Simply put, you can create 2D and 3D objects using CAD, while you can analyze how that object will behave using CAE tools. The automated design tools provided by CAE have transformed engineering analysis from a ‘hands-on’ experience to virtual simulation.

Finite Element Analysis (FEA)

The Finite Element Analysis (FEA) is the simulation of any given physical phenomenon using the numerical technique called Finite Element Method (FEM). Engineers use FEA software to reduce the number of physical prototypes and experiments and optimize components in their design phase to develop better products, faster while saving on expenses.

It is necessary to use mathematics to comprehensively understand and quantify any physical phenomena such as structural or fluid behavior, thermal transport, wave propagation, the growth of biological cells, etc. Differential equations not only describe natural phenomena but also physical phenomena encountered in engineering mechanics. These partial differential equations (PDEs) are complicated equations that need to be solved in order to compute relevant quantities of a structure (like stresses (ϵ), strains (ϵ), etc.) in order to estimate the structural behavior under a given load.

Most of these processes are described using Partial Differential Equations (PDEs). However, for a computer to solve these PDEs, numerical techniques have been developed over the last few decades and one of the prominent ones, today, is the Finite Element Analysis.

It is important to know that FEA only gives an approximate solution to the problem and is a numerical approach to get the real result of these partial differential equations. To be able to make simulations, a mesh, consisting of up to millions of small elements that together form the shape of the structure, needs to be created. Calculations are made for every single element. Combining the individual results gives us the final result of the structure. The results of a simulation based on the FEA method are usually depicted via a color scale that shows, for example, the pressure distribution over the object.

Computational Fluid Dynamics

Computational Fluid Dynamics (CFD) is the process of mathematically modeling a physical phenomenon involving fluid flow and solving it numerically using the computational prowess. In a CFD software analysis, the examination of fluid flow in accordance with its physical properties such as velocity, pressure, temperature, density and viscosity is conducted. To virtually generate an accurate solution for a physical phenomenon associated with fluid flow, those properties have to be considered simultaneously.

A mathematical model of the physical case and a numerical method are used in a CFD software tool to analyze the fluid flow. For instance, the Navier-Stokes (N-S) equations are specified as the mathematical model of the physical case. This describes changes in all those physical properties for both fluid flow and heat transfer. The verification of the mathematical model is extremely important to create an accurate case for solving the problem.

Multibody Dynamics

A multibody dynamic (MBD) system is one that consists of solid bodies, or links, that are connected to each other by joints that restrict their relative motion. The study of MBD is the analysis of how mechanism systems move under the influence of forces, also known as forward dynamics. A study of the inverse problem, i.e. what forces are necessary to make the mechanical system move in a specific manner is known as inverse dynamics.

Motion analysis is important because product design frequently requires an understanding of how multiple moving parts interact with each other and their environment. From automobiles and aircraft to washing machines and assembly lines – moving parts generate loads that are often difficult to predict. Complex mechanical assemblies present design challenges that require a dynamic system-level analysis to be met.

Accurate modeling can require representations of various types of components, like electronic controls systems and compliant parts and connections, as well as complicated physical phenomena like vibration, friction and noise. Motion analysis enables one to meet these challenges by quickly evaluating and improving designs for important characteristics like performance, safety and comfort.

CAE tools benefits

CAE tools are being used, for example, to analyze the robustness and performance of components and assemblies. The term encompasses simulation, validation, and optimization of products and manufacturing tools. In the future, CAE systems will be major providers of information to help support design teams in decision-making. Computer-aided engineering is used in many fields such as automotive, aviation, space, and shipbuilding industries.

CAE provides many benefits. Manufacturers prefer CAE for lowering simulation costs and time during the design process while minimizing errors and improving the performance of components. Since simulating reality is less time-consuming, CAE processes save on time and money. CAE reduces the errors in the design and drawing process. The impacts of changing parameters on a system can be studied with more accuracy. The robustness and performance of components and assemblies can be analyzed. CAE allows for easy visualization and improves designs. CAE aids ease of manufacturing

CAE process

A typical CAE process comprises of preprocessing, solving, and postprocessing steps. In the preprocessing phase, engineers model the geometry (or a system representation) and the physical properties of the design, as well as the environment in the form of applied loads or constraints. Next, the model is solved using an appropriate mathematical formulation of the underlying physics. In the post-processing phase, the results are presented to the engineer for review.

DOD is giving thrust to Digital Engineering (DE) (also known as model-based engineering or model-based systems engineering) is an initiative developed and championed by ODASD(SE) to help streamline the way defense programs collect, retain, and share data. ODASD(SE) asserts that digital engineering has the potential to promote greater efficiency and coherence in defense programs by ensuring stakeholders have access to accurate, relevant, and consistent information throughout the life of a program.

It comprises of incorporating the use of digital computing, analytical capabilities, and new technologies to conduct engineering in more integrated virtual environments to increase customer and vendor engagement, improve threat response timelines, foster infusion of technology, reduce cost of documentation, and impact sustainment affordability. This goal promotes the establishment of robust infrastructure and environments to support the digital engineering goals. It incorporates an information technology (IT) infrastructure and advanced methods, processes, and tools, as well as collaborative trusted systems that enforce protection of intellectual property, cybersecurity, and security classification. These comprehensive engineering environments will allow DoD and its industry partners to evolve designs at the conceptual phase, reducing the need for expensive mock-ups, premature design lock, and physical testing. This approach can enable DoD programs to prototype, experiment, and test decisions and solutions in a virtual environment before they are delivered to the warfighter.

Cloud-based CAE Has the Collaboration Door Wide Open

Most of the CAD and CAE software on the market is still traditional and on-premises. Developed over several decades, the most popular tools include a whole host of complex features and are uncontestedly state of the art. They are not known for their accessibility, cost-effectiveness or ease of use, however. And these challenges can limit the technology’s adoption altogether.

In a globalized world, teams are often international and dispersed around the globe across different time zones. Remote work has also become popular and the trend seems to continue to grow. Technology has opened up these possibilities, which bring significant benefits allowing companies to hire the best talent and have access to multicultural, multi-skilled staff. The advantages don’t come without challenges, however, as teams need to find tools, solutions, and processes that keep feedback rounds and teamwork running. To address the challenges large companies face in having teams collaborate on design or engineering projects companies propose cloud-based software with dedicated team plans to increase productivity and foster cooperation.

The cloud has made it possible for entire applications, no matter their complexity, to be developed, installed, and accessed in a standard web browser. With such a level of accessibility, sharing and collaboration capabilities are practically native to this new field. AutoDesk®, Dassault Systèmes®, Siemens®, Onshape, and SimScale are only a few of the CAD and CAE companies that have brought cloud-based solutions and collaboration features to the market.

Computer-Aided Engineering (CAE) Market

The global market for Computer-Aided Engineering (CAE) estimated at US$5.8 Billion in the year 2022, is projected to reach a size of US$8.7 Billion by 2026, growing at a CAGR of 9.1% over the analysis period. Finite Element Analysis (FEA), is projected to record a 9.4% CAGR and reach US$5.6 Billion.

Finite Element Analysis (FEA) segment dominates market share due to the numerous benefits offered by the software. Besides enabling easier modeling of complex geometries, FEA also offers benefits such as increased accuracy, adaptability and visualization. FEA also supports simulations that are time-constrained, for example, in aerospace manufacturing (crash simulations).

Computational Fluid Dynamics (CFD) Segment to Reach $2.1 Billion by 2026. Computational Fluid Dynamics (CFD) is one of the major forms of engineering analysis performed by CAE software. The capabilities of CFD enables in resolving issues related to identification of compressible and incompressible fluids, multiphase flow problems, and laminar and turbulent flows. CFD software is a popular tool for analyzing air flow around cars and aircraft. As the cooling infrastructure of server rooms has increased in complexity, CFD has also become a useful tool in the data center for analyzing thermal properties and modeling air flow.

The Computer Aided Engineering (CAE) market in the U.S. is estimated at US$1.8 Billion in the year 2022. Global Computer Aided Engineering (CAE) Market to Reach $8.7 Billion by 2026. Computer-aided engineering (CAE) refers to the use of computer and software solutions to design, analyze and generate processes and products. CAE broadly incorporates computer aided design (CAD) as well as computer aided manufacturing (CAM) capabilities for providing assistance in engineering analysis processes.

Cloud computing is bringing down costs of licensing, deployment as well as maintenance, which is likely to expand the market. Companies are also leveraging advanced technologies like machine learning and artificial intelligence for creating advanced CAE tools. The market for CAE would also be positively influenced by emerging engineering modes like building information modeling, concurrent engineering and 3D printing.

China, the world`s second largest economy, is forecast to reach a projected market size of US$1.1 Billion by the year 2026 trailing a CAGR of 11.5% over the analysis period. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 7.6% and 8.7% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 8.2% CAGR.

Some of the leading players are Altair Engineering, Inc.; SimuTech Group; Dassault Systèmes SE; Dell Inc.; ESI Group; Hexagon AB; Mentor Graphics, Inc.; NEC Display Solutions, Ltd.; Numeca International; Siemens Industry Software Inc.; Simerics Inc.; Symscape; Synopsys, Inc. and Others.

CAE in Space Industry

The application of CAE was spearheaded by MSC. The core of MSC Nastran was the code that NASA used to structurally analyze the Apollo Space Program. In 1971, MSC Software released a commercial version of the same software and since then its value to society (both tangible and intangible) in the creation, extension and spread of FEA simulation technologies was calculated by a NASA valuation of MSC Nastran in 2003 to be $10B in economic value. Moreover, MSC Software’s tools and solutions have been in the vanguard of modern space industry simulations and related equipment design – from multi-body dynamics to acoustics, FEA to CFD (Computational Fluid Dynamics), and, latterly, materials analysis and novel manufacturing techniques (like additive manufacturing).

Many researchers in the last 10 years have used MSC Software to examine the dynamics of lunar landers and ascent vehicles and a typical study was S.P. Korolev Rocket and Space Public Corporation Energia (RSC Energia) in Russia in 2018. Researchers in Harbin University in China successfully coupled MSC’s Adams multi-body dynamics solver to EDEM from DEM Solutions in a cosimulation chain to model a novel new spider-like robotic lander vehicle capable of dealing with rough terrain on other planets. a Masters Thesis from the Massachusetts Institute of Technology in America in 2016 employed SimXpert and MSC Nastran to investigate whether a CubeSat satellite design that uses a combination of propulsion and solar arrays stresses the dynamics of the solar panels and their hinges that hold them in place.

The exploration (and exploitation) of space, our neighboring planets, and moons, for commercial means has never been so topical, or more lucrative. Assorted commercial players in the space industry have started to enter the market in the last 20 years bringing down the cost of participation. Polar moon bases, lunar mining, landing on asteroids, and colonies on planet Mars are all being examined as feasible opportunities. Even in situ 3D printer facilities, lunar factories, chemical processing facilities, and lunar greenhouses are being proposed and designed using CAE before ever being built.