CFD Workflow Guide: How to Set Up a Fluid Dynamics Analysis

February 23, 2021

Computational Fluid Dynamics (CFD) is a way of rearranging such processes and systems in a series of differentiating statistics using digital computers. It provides appropriate consultation with the amount of fluid flow through mathematical modeling, optional, and other pre-and post-processing tools. It has greatly helped scientists to improve the strength of the liquid. It has replaced traditional liquid energy methods with more powerful computational tools. The potential effects of computational fluid are comparable to actual laboratory results. Computational Fluid Dynamics is based on the basic physiological mechanisms of the following fluid forces:

  • Energy Conservation
  • Newton’s second law
  • Mass Conservation

CFD Workflow Guide: How to Set Up a Fluid Dynamics Analysis

The result of CFD is usually a set of numbers for the purpose of engineering analysis. Most of the powerful Computational fluid dynamics numerical algorithms we use today are deeply embedded in the mathematical structures of flow equations. It empowers designers and designers to design safe and comfortable environments. It enhances the aerodynamic features of the aircraft by influencing small details. It is also used to reduce health risks from radiation and other hazards. This technology is increasingly being used to simulate walking on a car. Estimates of the pressure field influenced by the rotor by helicopter fuselage can be estimated with the help of this technology. Biomedical engineering has been widely used in circulatory and respiratory systems. The impact of this technology is growing rapidly as it is less expensive. But modern flow measurement is complex and flawed and therefore requires a lot of engineering expertise to approach the desired solutions.

CFD Services uses well-designed geometry and has an understanding of the expected imitation effects that aids the process of obtaining a successful analysis. With special care in modeling and setting your imitation at the beginning of the analysis process, you are likely to save a lot of time over time. Before you can use simulation, and trust the results of the simulation, you must have an accurate measurement and description of the results. These estimates may be based on previous experience or based on previous models or industry performance. Having an idea of what the results should allow you to “mentally test” the effects of simulation. This is important because the performance of CFD results depends on the user’s valid input into the software. If you see unexpected results, you can easily spot potential errors in the simulation settings.

To create a CAD model that is very useful in your CFD analysis, it is important that you first know that you are interested in modeling internal or external flow. In the internal flow bound to solid objects such as pipes, you can simply model a standard object in 3D CAD software. If the flow is around a non-physical object, you can re-enter the model in simulation CFD. In the meantime, you will build a bounding box around the object that describes the size of the liquid flowing around the object. Alternatively, you can create a space around the object firmly inside your CAD software; usually by making a large box around the real thing like a new body. You can then import these bodies into Simulation CFD and set the external ones as any solvent fluid and solids in any structures it needs. This may be necessary if you are not able to adjust the size of the bounding box using the methods designed for Simulation CFD.

For a good CFD analysis, the model needs to be given enough details to show the truth, but not so much detail that it takes less time to do. Water flow can be very sensitive to small details and in addition to simplifying the model, one can miss some of that detail. However, simplification will result in the meshes taking too long to work without increasing the accuracy of the results. Therefore, it is important to leave those details that will not affect the flow, while including that information that will affect the flow. As with FEA, the first step in CFD meshing is usually with software to create automated machine distribution. This mesh is usually a course in places and maybe good for others as well. Mesh refining in CFD is exactly the same as FEA and can be treated in the same way by using built-in filter tools.

A very rough mesh will not be accurate enough to produce the right imitation results. Such a machine often creates dramatic results or displays some of the clearest artistic indications that something is wrong. A very good mesh requires a lot of computing power that can prevent it from performing analysis, or rediscovering the right design solution. One solution is known as adapting meshing, which filters the mesh according to the repetitive effects of the simulation. By using simulation many times, this tool only filters certain areas of the match to meet the correct solution. Here, we should note the differences between the mesh junction and the solution junction, which are discussed further in the resolution phase. For the flexible meshing to be more efficient, care must be taken to create a good first mesh.

During the geometry phase, the CFD engineer prepares the CAD Geometry for the CFD solution, which requires a solid 3D volume of its geometry. CFD requires very high standards in geometric quality than the average person. First, an engineer refines CAD geometry. They redefine areas with simple geometry, removing unnecessary elements such as ties and small details. They search for spaces and holes and often clean up a host of problems that cause problems in a CFD solution. The quality of the CFD machine is built from the quality of the original CAD geometry. Limitations on negative geometry restrict the predictive quality of low CFD. After introducing geometry into CFD software, the engineer created a CFD model. This incorporates physics into geometry. CFD simulations do not automatically load all the physics in the world; computer load can exceed most computers. Instead, the engineer selects the appropriate physics models, the parameters of the input model, and usually incorporates the required physics into your CFD simulation.

The mesh divides the geometry into millions of tiny cells. The combination of these cells and structured physics allows the software to solve the CFD problem. But not all meshes are made equal. Hinges of imitation quality in finding the right size of these cells in the right place. Mesh measurement is a key way to control a CFD engineer; they focus most of their time on this step. Requires a repetitive process: try certain match settings; check imitation; check results; improve match settings. There is no effective simulation for the first time. The engineer is looking at a number of potential problems:

  • Incorrect physics settings
  • Problem areas that require additional match fixes
  • Imitating instability
  • Bad results
  • Some unknown problems.

The independent mesh study systematically evaluates imitations of various sizes and compares simulation results with each mesh size. The engineer searches for an independent mesh state where the results do not change with the size of the match. Once achieved, the engineer can predict the accuracy of the simulation. The next step specifies numerical parameters, e.g. to set solver parameters, discretization schemes, etc. Depending on the type of simulation, each problem has its own unique structure. Usually, one problem can be solved with repetitive solutions and different solver parameters; however, to solve the problem successfully, it is very important to provide appropriate solver parameters and number systems.

The green output from the CFD simulation is a database of numerical data, which can be easily interpreted by humans. In post-processing, an engineer converts that database into a variety of presentations, highlighting key points. These are usually visual images. But they can also be tables, prices somewhere, or just about any other type of data requested. Discuss the results with your engineer before starting production. Developer programs for most of these output files in one template before making multiple copies in each simulation situation. Generally, engineers are happy to add additional posts to the template. More work comes from adding post usage after the fact because they need to manually edit the processing of each post in each simulation file.

Finally, the engineer writes everything in the report. In addition to the results, the report should provide sufficient detail for the third party to produce a CFD simulation. This serves as an alternative to quality control. Many companies strike a balance between reporting excessive information and protecting their technology. Usually, they will happily explain the simulation settings, but capture details about the exact size of the match. This is because most of the imitation quality is based on mesh size.

Also Read: Role Of Computational Fluid Dynamics In Product Manufacturing

Tips for Meshing Your CAD Model for Structural Analysis

February 9, 2021

CAD modeling is used by many designers to create computer-generated material models before they are physically produced. CAD stands for computer-assisted formulation. Engineers, architects, and even artists use computers to assist with their construction projects. Computers allow them to visualize their make-up and face problems before using any of the tools needed to put them in a physical position. In many cases, it may be helpful to identify other possible measurements in geometry. Using an equation is one of the most common and powerful ways to reduce the size of a problem. By definition, equilibrium exists when there is an asymmetry of geometry, loads, and obstacles with a line or plane of measurement. Structures can have interlocking boundaries, such as intersections between multiple objects, connections, cracks, etc. Statistically, FEM is based on the assumption that migration continues within an object. Joints are regions where it is possible to stop working, such as cracks. This means that migration does not need to continue. In addition to the migration jump, there is a clear escape from the stress on the visual connector.

Tips for Meshing Your CAD Model for Structural Analysis

Meshing Technique

  • Start with meshing problem areas. Meshing is generally repetitive. The mesh is designed for quick removal and retrieval.
  • Set a time limit. Time can run out when meshing. Setting a time limit for certain match regions. For example, give 20 minutes to achieve the best distribution of matches.
  • Focus on the larger picture. Maintain general strategies and inventory as you progress through construction.
  • Perform an extreme run to feel the pressure areas, and then improve accordingly. Avoid overloading the machine, which puts you at risk of tripping over a cliff.

Each asset has a different modulus. In the absence of cracks, the problems in common areas are the same. Now, knowing that stress = modulus x strain leads to different pressures on each side of the interface. In other words, we have pressures. Such an omission cannot be taken with an object passing through the interface. Similarly, other situations where there may be no object across the border include:

  • When geometry changes, elements cannot cross these boundaries, and you need to have nodes in the interface
  • When loads suddenly change, nodes need to be present in the interface when the load suddenly changes
  • Nodes need to be present in areas where fixed loads are used

Automatic algorithms detect communication connectors as long as the CAD model is separated between the interfaces. Normally, the default tetrahedral mesra works well, but if the object is separated from the visible connector, separation is required. Automatic spaces generators usually start by creating a triangular space. They proceeded to extrapolate using these triangles to form tetrahedrons in volume. In many cases, the formation of tetrahedrons built into the volume can be severely disrupted, leading to the failure of the mesh generation. This often meets in two cases:

  • CAD geometries are complex
  • Geometry with high proportions

Depending on the geometry of the structure, the CAD model may contain geometry of high factor ratios, fillets, etc. In such a case, it is possible that the automatic meshing may not produce the best meshes. In most cases, these small structures are bound when large materials are used, and the machine often does not correspond directly to the geometry. In such cases, it is best to resort to mesor refinement. Problems involving direct stiffness are one of the well-researched problems in mechanical engineering. For all solid-line problems, regardless of machine sizes, the Newton-Raphson iteration will switch to a single iteration. However, it is always recommended to do mechanical refinement research and integration to ensure the accuracy of the solution. However, the same cannot be said when a material incompatibility is involved. The problem can be solved and there can be a unique solution. However, the problem may fail to meet if the mesh is not good enough in regions where strong inconsistencies are observed. Here we have provided tips on environmentally friendly communication problems.

Communication is not very linear in nature and to this day it remains a computer challenge for modeling major communication problems. Thinking about it in simple terms, sometimes there is no communication and suddenly there can be communication. Many problems involving excessive submission are out of line but persist. However, it should be remembered that the contact is either a switch or does not stop. Some of the original planes had rectangular windows, but it was soon discovered that sharp corners led to increased pressure and cracking. Identifying such points of unity and refining the mesh in these areas can lead to accurate results of Structural Analysis.

The magnitude of the pressure is that point in the mesh where the pressures do not change. Theoretically, the pressure at this point is constant, and as the match is cut, the pressure at this point continues to increase. However, it is important to know that the migration of people included in these pressures remains accurate even though the actual pressure is currently questionable. That aside, at a very short distance from the point, the calculated pressures are accurate. However, such incidents are actually very common in fact, and the user needs to identify these locations. They are often encountered in point-of-point locations, where sharp corners are located, and at points that are restricted to more than one point.

Nonlinearities of Geometry and the effects of locks are often seen when using solid materials to build small structures. This is especially true if they carry heavy loads. This type of lock is known as “shear locking”. The shear lock should not be confused with membranes or volume lock effects. The shear key is detected from the first-order elements that use the linear functionality of motion translation. In other words, deletion must be by active line and the performance of the line function remains the same. Therefore, challenges are always present in everything. In fact, it is not. Such a wrong measurement of gravity inevitably leads to an inaccurate estimation of the strength of the type, and the overall structure shows very high durability. The displacement of the building net will be much lower than what was seen in the actual building.

The low-quality mesh will not only lead to negative imitation effects but can also cause the solver to produce an error due to instability. Such instability is often caused by poor or illegal quality cells. This is something you want to avoid as much as possible. Similarly, while a mesh can contain millions of nodes, that fact alone does not equal quality. Ensuring a well- defined, simple, clean, and waterproof geometry will often be the difference between an effective high-quality cells. Geometry should be firm and should not have unusual features such as intersections or sharp exits. Clean geometry means it is closed and has no geometric problems. The construction of waterproof geometry will allow the solver to distinguish between different flows domains, which is very important, especially in the simulation of external flow. Maintaining a skewness ratio is key to accuracy and quality. In complex geometries, maintaining the skewness ratio of an entire cell can be difficult, if not impossible, a good practice to ensure that it adheres closely. Different conditions require and control different skewness measurements, but in normal use, solid cell distortion is an indication that the skewness rate of the cell is very large and further refining is required.

Boundary refinement is a very critical parameter that is sometimes overlooked by newcomers to CFD simulations online. While increasing precision near the inner or outer geometric area, the refinement of the boundary layer also, more deeply maintains the distance of the unmeasured wall or Y + of the selected disturbance model to increase accuracy. Accurate measurement of stress levels in areas of concern is required, such as close holes, ties, metal toes, and other similar pressure devices. FEA loads and limits can be applied to points or line features, rather than over-distribution. In practice, any responsibility or support is distributed to the region. Using a point or line means a moderate force applied to a relatively small area, which gives constant pressure – which is the only pressure. Stupid senseless ties and irons also cause this.

Also Read: CAD Designing Services For Mechanical Engineering

CAD Designing Services for Mechanical Engineering

December 8, 2020

Manufacturing industries are striving to reduce product costs to be competitive in the face of global competition. In addition, there is a need to improve quality and performance levels on an ongoing basis. Another important requirement is timely delivery. Given the nature of global exports and long cutting chains across several international borders, the task of continuing to reduce delivery times is a daunting task. The computer has the ability to perform various functions along with the production software. Computer skills are thus exploited not only during production work but also by the entire product development. Computers are needed to integrate the entire production system and thus transform the computer-generated designs into products.

CAD Designing Services for Mechanical Engineering

Computer Aided Design (CAD) is the use of computer programs to assist in the design, modification, analysis or optimization of a design. CAD software is used to enhance designer productivity, improve design quality, improve textual communication, and create a production database. CAD data are usually in the form of electronic files for printing, machinery, or other computer-aided design work used in many fields. Its use in designing electrical systems is known as Electronic Design Automation or EDA. With mechanical design, it is known as Mechanical Design Automation (MDA) or computer-assisted writing (CAD), which involves the process of building a technical drawing using computer software. CAD software for mechanical construction uses vector-based drawings to illustrate traditional writing materials, or it may also produce raster drawings depicting the appearance of architectural elements. However, it involves more than just suspension. As with the actual writing of technical and engineering drawings, the CAD issue should convey information, such as equipment, procedures, size, and tolerance, depending on the specific program meetings. Computer aided engineering can be

used to design curves and figures in a 2D space; or curves, solid surface, and stiffness in a three-dimensional (3D) shape.

Geometric modeling involves the use of a CAD system to improve the mathematical meaning of object geometry. Generally, a geometric model is fitted in the program. These include creating new geometric models from the basic building blocks found in the system. Geometric modeling is a branch of applied mathematics and a computer geometry that learns the methods and algorithms of mathematical interpretation of the shape. The shape studied in Geometric modeling is usually two or three, although most of its tools and principles can be used in sets of limited size.

Today most geometric modeling is done on computers and computer-based applications. Two-dimensional models are essential for computer typing and digital drawing. The three- dimensional models are central to computer-aided design and manufacturing (CAD / CAM), and are widely used in many applied technologies such as field engineering and engineering, crafts, landscape design and medical imaging. Geometric models are often divided into process and process models, which define the complete structure by the opaque algorithm that produces its appearance. They are compared to digital photographs and other models that represent the shape as a clip of a good common local divorce; and fractal models that provide a repetitive description of the shape.

Solid Modeling

This process is used to create the solid parts of the shape you want by joining and cutting different solid rolls. The solid end model is similar to the actual product but is more visible and rotated like a real product. There are two main types; direct where the model can be edited by reversing or converting the model directly to 3D; second one is a parametric in which a model is built using parameters.

Surface Modeling

This process is used to create an environment that is desirable by cutting, sewing and joining various areas to create the final model of shape.

Assembly

This process is used to assemble models made of a stronger or more durable model to form the final assembly. This is used to see the actual balance of all models and to see the actual performance of the assembly.

Drafting Detailing

This process is used to create 2D drawings of elements or assemblies; frequency directly from the 3D modeling, although 2D CAD can create direct 2D drawings.

Reverse engineering

This process is used to convert the actual part into a 3D CAD Model. Different types of instruments such as laser scanner, white scanner, CMM are used to measure or determine it.

Return on investment is one of the most important things to consider when using CAD design automation. Lowering product costs is a common challenge for manufacturers. Design automation solutions help to overcome this challenge as they offer a high cost reduction by reducing manual effort and speeding up construction. Cost reductions are combined with higher production results in a much higher RoI.

Design automation should be seen as a new way of working, not as a single project with a beginning and an end. It helps designers to perform repetitive construction tasks. This leads to a process designed, reduced costs, and increased productivity. In short, automation design empowers engineers to order custom completion days for custom engineering minutes in just minutes.

Manufacturers continually strive to innovate and improve their products in order to meet the high expectations of user experience, quality, and cost reduction. With effective communication across all departments and companies, automation strategies can be integrated with other business plans. In addition, a successful system allows you to climb well without attached strings – which utilizes many aspects of your design and engineering while bringing great benefits to your organization.

Companies are striving for seamless integration between all of their systems. Maintaining consistency between the various details conducted by the various departments can be a daunting task. Fortunately, automated systems are able to interact with broader business systems. Design automation starts in the engineering department. However, all company operations that meet engineering can ultimately benefit from automated design.

The automotive industry uses various event simulations to investigate the skills of several production shops involved in building vehicles such as body shops, paint shops, trim , chassis, assembly stores, and engine machinery stores, machinery stores and stamp shops. The simulation of bodybuilding systems in conceptual time, designing and constructing product life cycle stages allows the automotive company to investigate the impact of the use of tools, delivery and delivery systems There are two distinct approaches to analyzing physical performance. The first is modeling a body shop at station level. The second option is to model the body shop in the line or at the details level below. The channel-level simulation model is used to analyze the solitude of the sub-field.

Channel cycle times and downtime are included in the simulation model and are measured for subassembly power. Subassembly transfer can be directly compared to the acquisition of a physical store. As a general rule, the passage of the subassembly should be greater than the complete overhaul of the body shop or the new construction of the basement will be required. If complex handicrafts occur in a channel, these tasks can be added to a channel- level model. Modeling of travel, van and set times can indicate whether each station can meet the required time cycle of the subway. During the analysis of subway stations, a line level model can be developed. The output limitations for each subassembly model are included in the line level model and the transmission systems are modeled in detail. Interactions between subassemblies and delivery systems can be used to identify sets of subassemblies or individual subassemblies to identify issues in the physical store. Carrier measurement can be achieved by increasing the connection between the bottom of the

bottle and reducing the bath between the non-bottle areas. This process continues in the design phase.

Production managers and engineers remain concerned about quality improvements, reducing both production costs and delivery time. Globalization requires the introduction of new products with improved features at competitive costs. Another challenge is the reduction in product life. This requires a lot of time pressure on the product development cycle. Also notable is the tendency to customize large quantities that require excessive flexibility in production. Large-scale production is another important development in recent years.

Today’s customer expectations include high quality and performance, high technical skills, and timely delivery. All of this will be provided at a reduced cost due to global competition facing the manufacturing industry. Today’s customer expectations include high quality and performance, high technical skills, and timely delivery. All of this will be provided at a reduced cost due to global competition facing the manufacturing industry.

Also Read: Elements Of CAD Design Services

Role of Computational Fluid Dynamics in Product Manufacturing

November 10, 2020

Computational fluid dynamics or CFD involves the analysis of fluid flow, heat transfer, and associated systems with the help of computer-based simulation. It has a wide range of industrial and non-industrial applications and is a very robust tool for product manufacturing. It is excessively used in automobile industries for predicting drag forces and lift of the vehicle. Computational fluid dynamics requires significant knowledge in fluid dynamics, mathematics, and programming. It involves assuming the wide-ranging of variables to generate models that can capture the required needs for the actual real-world system.

Role of Computational Fluid Dynamics in Product Manufacturing

Computational fluid dynamics technique is utilized for the study of aircraft and vehicle. It is helpful in analyzing the lift and drag of the vehicle. The hydrodynamics of ships can be easily examined with this method. The study of combustion in internal combustion engines and gas turbines in industrial power plants and the flow inside rotating passages and diffusers in turbomachinery can be easily done with the use of this technique. In biomedical engineering, it is employed for blood flow analysis through veins and arteries. It is also used for weather prediction by the meteorology department. Modern environmentalists are also using this technique for determining the distribution of effluents and pollutants.

Industrial units are in awe with the computational fluid dynamics as it offers unique advantages over the experiment based techniques to fluid or flow systems design. It allows unlimited levels of details of results and helps to perfect the fluid systems. It reduces the lead times and costs of new designs for a system substantially. CFD facilitates analysis of the system where controlled systems are difficult to perform. It also has the ability to examine systems under disastrous conditions at and beyond their normal performance units. In experimentation studies, the costs of hiring personal and other aspects are variable and hence experimentation is increasingly being ignored by the industries. On the other hand, computational fluid dynamics deliver a huge volume of results without any added cost and is very cheap to perform.

Fluid flow problems can be tackled by computational fluid dynamics codes. These codes are structured around the numerical algorithms and allow smooth access to solve difficult fluid flow problems. A computational fluid dynamic codes consist of a pre-processor, a solver, a post-processor.

The input of a fluid problem to a CFD program for transformation into an easy part comes into the context of pre-processing. It basically involves defining the geometry of a particular region, ie. a computational domain. It is further divided into a number of smaller, non- overlapping sub-domains in the form of mesh or grid of cells that helps in grid generation. It helps in defining and modeling of fluid properties of a fluid. The solution to such variables such as temperature, pressure, etc. is defined at nodes at each grid. The accuracy of any CFD solution is governed by the number of cells in the grid as the greater the number of cells or grids, the greater the solution accuracy. The fineness of the grid depends on the cost of the system and the accuracy of a solution. Most of the time of any computational fluid dynamics project is utilized at grid generation and domain geometry.

The finite difference, finite element, and spectral methods are three basic numerical solution techniques out of which the finite difference method is mostly used. A numerical algorithm involves integrating the basic equations of fluid flow over all the finite volumes of the region. The resulting integral equations are then transformed into a system of algebraic equations. The algebraic equations are then solved by an iterative method. The basic difference between the finite volume method and other CFD techniques is the integration of the control volume in the finite volume method. The resulting equations have the same properties for each finite-size cell. This simple concept makes it easy for engineers to understand the fluid flow as compared to other methods. The conservation of various flow variables such as enthalpy, velocity within a finite control volume is expressed to estimate whether it increases or decreases. Computational fluid dynamics codes consist of discretization techniques that are helpful for convection, diffusion, and other key transport phenomena.

The ever increasing popularity of CFD software has extended the processing capabilities. It has facilitated great graphic capabilities along with domain geometry, and grid display. The software package of CFD now includes vector plots, line and shaded contour plots, contour postscript output, and particle tracking. These facilities are enhanced by the animated and dynamic result display. This has allowed transmission of ideas to people of non-engineering backgrounds.

The fluid flow problems are built on complex sets of physics, chemistry, mathematics concepts, and mastering them requires skillful professionals. The user must possess significant knowledge in the various subjects prior to the simulation of CFD problems. The user must be able to identify and formulate the chemical and physical aspects of the flow problem. The key decisions that go with the modeling of fluid flow are the effects of ambient temperature, variations in air density, turbulent flow, and air bubbles, etc. The right decisions should be made while modeling the equations as to preserve the necessary characteristics of the problem. The accuracy at the simplification of the equation allows the greater quality of the CFD. The detailed description of the domain geometry and grid design is crucial at the initial stage for obtaining successful simulation results. Successful simulations can be obtained by convergence and grid dependence. A converged solution can be achieved by selecting various acceleration devices and relaxation factors.

The converged solutions are filled with varied issues and require optimization. The optimization of the solution with speed needs extensive experience at the evaluation of the code. The initial grid design depends on the characteristics of the flow. It is filled with numerous errors and requires refinement. Errors can be eliminated by performing a grid dependence study. Each algorithm has a unique error pattern and can be guessed by an experienced professional who has a thorough knowledge of the algorithm.

Computational Fluid Dynamics (CFD) is a way of reorganizing such processes and systems in a series of differential equations by using digital computers. It offers qualitative and quantitative reasoning of fluid flows by the use of mathematical modeling, discretization, and other pre- and post-processing tools. It has helped the scientists enormously in the development of fluid dynamics. It has replaced the traditional approaches to fluid dynamics with more powerful computational tools. The results of the computational fluid dynamics are equivalent to the actual laboratory results.

The ultimate goal of growth in the CFD field is to offer a capability comparable with other CAE applications such as stress analysis codes. The key reason why CFD has remained behind is the significant complexity of the existing behavior, which precludes a description of fluid flows that are simultaneously economical and complete.

The availability of affordable high-performance computing hardware and the introduction of user-friendly interfaces have led to a recent upsurge of interest, and CFD has entered into the wider industrial community. The variable expense of an experiment, in terms of facility hire and/or person-hour costs, is directly proportional to the number of data points and configurations tested. Whereas CFD codes can generate extremely large volumes of solutions at no added expense. It is very cheap and easy to perform parametric studies such as optimizing equipment performance.

The accuracy of a Computational fluid dynamics solution is determined by the number of cells in the grid. Generally, larger the number of cells, the better the solution accuracy. Both the accuracy of a solution and its cost in terms of necessary computer hardware and calculation time is dependent on the fineness of the grid. Optimal meshes are often varied, finer in places where greater variations occur from point to point and coarser in regions with relatively less difference.

Efforts are underway to generate CFD codes with a self-adaptive meshing ability. Ultimately such programs will itself refine the grid in regions of rapid variations. A significant amount of basic development work still needs to be done before these programs are robust enough to be incorporated into industrial CFD codes. The main ingredients for success in CFD are experience and a thorough understanding of the physics of fluid flows and the fundamentals of the numerical algorithms. Without these, it is very unlikely that the user will get the best out of code. It is the intention of this book to provide all the necessary background material for a good understanding of the internal workings of a CFD code and its successful operation.

Also Read: Applications Of Computational Fluid Dynamics

Why Is Finite Element Analysis The Most Trending Thing Now?

October 20, 2020

In today’s world, the development of products is carried out in a systematic manner so as to create high-quality products effectively and efficiently. A product may have various requirements that are evaluated for different solutions to unify the development procedures. Product analysis is carried out at the end for the verification of the product and assists engineering designers to simulate the behavior of the product for further screening. Product analysis has become an important part of the product development process as it helps in the prediction of the final product behavior. One of the most important ways for product analysis is Finite Element Analysis.

Finite Element Analysis

Finite Element Analysis (FEA) is a numerical method for solving the problem of mathematical and engineering physics. It is used for solving complex geometries, material properties, and loadings where analytical solutions are very difficult to obtain. It is a way to simulate loading conditions to determine the design’s response to those conditions. It is modeled using discrete building blocks called elements. Each of these elements has an exact equation that represents the response to a particular load. FEM has become a powerful tool for solving differential equations and integral differential equations.

The final element method was first used by academic and industrial researchers in the 1950s for evaluating the suspension bridges and steam boilers. Since then it has grown in function and has been used for reducing the amount of prototype testing. It allows multiple simulation scenarios for testing that are used for cost and time savings. It extends reduced testing and redesign costs to shorten the product development cycle. It identifies safety issues or any irregularities in the development of the product. This process is helpful in finding design shortcomings before any future litigations. Designers are increasingly using it with CAD programs to allow solid modeling and mesh generations.

Finite element analysis is applied by businesses in engineering such as aerospace, civil, automotive, and mechanical, etc. It is used to analyze the fluid flow for structural and stress analysis for static and dynamic equations. Modern engineers are also using this process for analyzing the fluid flow and heat transfer in technical and industrial equipment. It is helpful in analyzing electromagnetic fields, soil mechanics, acoustics, and biomechanics.

In the method of finite element analysis, the accuracy of the solution is determined in terms of the refined element mesh. There are generally two methods for mesh refinement. First is h-refinement where an increasing number of elements are used to design a particular structural domain. Second is p-refinement where interpolation functions are increased by using the order of the polynomials. The refinement is done to estimate the sequential solutions that show the exact solution.

In this approach, solutions of the equations are converted into small finite segments. These elements are then further assembled to obtain an overall system of linear algebraic equations. Here is the general process of linear static structural analysis.

The first thing in the finite element method is to divide the solution into small elements so that the structure can be modeled. It is done after deciding the type, number, size, and arrangement of the elements in 1D, 2D, 3D, or axis symmetry. This is followed by the selection of a proper interpolation or displacement model as the structure of the model is very difficult to predict. It is done by assuming a solution from a computational point of view.

Further, strains and stresses are derived from the displacement model within each element by using Hooke’s law and strain-displacement relationship. As the displacements within each element are unknown variables, the compatibility equations within the element are automatically satisfied. The assumed displacement model is also helpful in deriving the load vector and the stiffness matrix by using the various variational principle. The next step in the process is to assemble the elemental equations to derive the overall equilibrium equations. The individual element stiffness matrices and load vectors are assembled in a systematic order for the overall equilibrium equation. The assembly of stiffness is carried out only on elements sharing a particular node. The process of finding the appropriate location for each of the individual element matrix in the global matrix is called the Direct Stiffness Method.

The next step in the finite analysis method is the imposition of boundary conditions in contact problems. After the incorporation of boundary conditions, the equilibrium equations are expressed. The element stresses and strains are further computed by using the equations of solid or structural mechanics.

Finite element analysis can readily handle the complex geometry and types of analysis. It can easily provide the results for vibration analysis, fluid analysis, heat transfer, transients, and no-linear. It can also handle complex loadings such as node-based loading or point loads, time or frequency-dependent loading, and element-based loading for estimating

pressure, thermal or inertial forces. The finite element method can model large displacements and rotations. It can also describe special material effects like swelling, creeping, plasticity, and temperature-dependent properties. It is very useful in handling the complex restraints for analyzing the intermediate structures and non-isotropic materials such as orthotropic and anisotropic materials.

In addition to the above advantages of the finite element method, there are numerous shortcomings as well. The finite analysis method is an approximate mathematical model of a system and a specific numerical result is derived from specific problems. This results in a general closed-form solution to examine the response to changes in various parameters. It requires vast experience and knowledge to construct a genuine finite system model. Further, it accumulates the error and rounds off most of the digits. It is susceptible to modeling errors by choosing a poor type of element. It can distort elements and sometimes geometry is not perfectly modeled. Finite analysis modeling requires a selection of proper mesh size and there is greater unwanted data. Greater memory and high-speed processors are required to carry out the analysis and are incapable of handling incompressible fluids.

There are many commercial finite element modeling packages available in the market. Some of these are ADINA, SOLIDWORKS, ABAQUS, ALGOR, ANSYS, C-MOLD, LS DYNA, etc.
ANSYS is one of the complete software packages used by engineers to analyze structural, thermal, and fluid engineering. It is also used to analyze the low and high-frequency electromagnetics. It is majorly used for electronics analysis in aerospace engineering, heavy equipment analysis in automotive engineering, microelectromechanical systems in biomedical engineering, and in bridges and buildings.

The finite element analysis method is increasingly used to obtain the solution for structural mechanics problems. It offers easy visualization of the machinery and equipment and is applicable to real-life problems of varied physical domains. One of them is the aerospace industry. The finite element analysis is used for the structural analysis in the aerospace industry. It is used for analyzing mode shapes, natural frequencies, and aero-servo-elastic studies. It is also used in aerodynamics and for analyzing natural frequencies.

Finite element analysis can be used to enhance the optimization and dependability of insulated design in high voltage equipment. It is extensively applicable in the complex configuration of dielectric insulating materials and electrodes. Finite element analysis can provide an equipotential field plot for a high voltage transformer and can assure the minimization of stray losses in electrical machines. One of the preferred processes for installing a thermal wire bonding between a lead frame and a semiconductor chip is the thermosonic wire bonding. It is connected by a metal wire. Wirebonding technology is a very complex task and works within certain boundaries and specifications, These designs have to meet the objective of lower mass, inertia, and higher dynamic stiffness. In such technologies, finite element analysis helps in analyzing the dynamic rigidity of the system.

It is highly crucial to identify the physical behaviors like fluid flow, strength, and transfer capability of complex objects. It is also useful in understanding the optimal design and predicting the behavior and performance of the design. It is considered as an important mathematical method for analyzing problems of mathematical and engineering physics. It is applicable to problems with complex loading, material properties, and geometries. Though stress analysis of trusses and beams can be analyzed by finding an analytical solution while finite element analysis is utilized in the situation where the designs are very complex. It is highly required for the situation where the accuracy is essential and to predict what’s going to happen when the product is used.

Also Read: Finite Element Analysis For Industrial Machinery And Equipment

The Future of CAE in Product Design

August 4, 2020

In the past, computer aided engineering (CAE) had a very limited application, being primarily used for advanced research and development, and for other specialty tasks which required simulation and optimization. In the modern world, CAE now has a much broader usage, and is routinely used to help accelerate the whole process surrounding product development. In the future, CAE will become even more sophisticated and it will help to model ever more sophisticated designs, while also reducing the time needed for getting a product to market.

CAE and simulation

Simulating various scenarios has proven to be of enormous value in validating and perfecting the design of various products. One excellent example is how it is no longer necessary to crash a sport utility vehicle into a barrier several times in order to analyze the results. Instead, engineers can conduct virtual crash tests using highly capable computers, and then tweaking designs so as to make the vehicle safer.

It’s not hard to see how a ton of money can be saved by not having to destroy a vehicle in multiple crash tests, and simply simulating the whole process on a high-performance computer. This has significantly increased the value of simulation and moved it solidly toward the direction of the initial phases of design for a product.

It’s very commonplace for engineers to use CAE software for the purpose of creating initial designs, as well as for optimizing the product itself. Some of this optimizing involves subtracting material from a potential product, so as to reduce its overall footprint while making no sacrifices regarding performance or strength. This has allowed CAE engineers to enhance performance as well as ergonomics, increase value and affordability, and to produce products which are more energy- efficient and which are more sustainable.

It’s not an exaggeration to say that simulations such as these have been at the forefront of advancing product development timelines, and that they have created all kinds of innovative designs for improving reliability and quality.

CAE Simulation

More sophisticated CAE tools

Engineers can also focus on high-value tasks more and more, because software tools have now emerged which automates all the best designs practices, as well as providing sophisticated analysis features. Product engineering has been boosted significantly by using customizable workflow processes that expedite development and testing, as opposed to spending a great deal of time inputting data to a system, and having to validate any particular model. This has freed up time for software engineers, so they can create new designs and develop new capabilities for products which have a ready market.

CAE and Covid-19

With the world currently in the grip of the coronavirus pandemic, CAE has moved to the forefront to provide crucial training for healthcare personnel, so that diagnoses can be quickly formulated, and treatment administered. One of the best examples of how CAE is supporting this effort is with a brand-new Lung Simulator which has been developed to help train clinicians in the techniques which are generally used in lung ultrasounds.

Lung imaging has already been implemented on an international basis to help manage treatment options for those impacted by the Covid-19 virus. Since the CAE lung simulator perfectly replicates many of the properties of actual human tissue, it allows students to practice their ultrasound imaging skills so they can diagnose many of the findings commonly associated with coronavirus.

Using this CAE imaging simulation, students can learn all about ultrasound system controls, applying PPE, recognition and understanding of coronavirus lung anatomy, and the positioning and navigation between intercostal spaces. This is a lifesaving technology which can serve as the best available training tool for identifying coronavirus which has settled into a patient’s lungs. It has been developed so that it perfectly mimics each of the stages of the coronavirus disease as it affects a person’s lungs.

The future of CAE

There are definitely some trends beginning right now in the world of CAE which are expected to intensify in the very near future, and become part of mainstream CAE technology. One of these is the democratization of perpetual licenses which are currently sold by big CAE corporations. There are already a number of CAE applications which are available free of charge or very near free. A whole slew of products is beginning to appear which will allow users to pay as they go, and to use the tools anywhere at all without regard to a specific computing device.

Another trend which is rapidly gaining momentum is that of system modeling with the use of CAE software. Currently, it’s fairly routine for engineers to design and analyze parts or assemblies, but a full system analysis is rarely pursued by designers and developers. Technology which is currently emerging will allow CAE professionals to test entire systems, so that performance of the holistic entity can be analyzed. An example might be the case where several discrete assemblies within an automobile are tested according to current methodologies. In the near future, more testing will focus on analyzing results from a complete automobile, and its behavior under various conditions.

In the past and even in most cases during the present, it has been necessary to perform a new analysis whenever a new design for a product arises. CAE of the future will cut through much of this wasted effort and allow engineers to mine data from other simulations, and couple it with analytics so as to help understand design strengths and weaknesses.

Also see more about: Elements Of CAD Design Services

One really exciting effort which is just beginning to gain traction is known as multi-scale modeling, which offers the opportunity to use the same CAE software to model objects at a molecular level as well as objects the size of a rocket ship. The benefits of having such a capability would be to conduct multi-scale modelling with the same software tool, rather than having to conduct two separate modelling efforts.

It may well be that some of these trends may not receive widespread support in the future, but it does appear that they provide such obvious benefits that it’s very likely most of them will become mainstays of future CAE processes. Look for some or all of these trends to achieve widespread acceptance in the CAE world, and for CAE to become an even more effective tool for designing, developing, and simulating.

Applications of Computational Fluid Dynamics

April 2, 2019

From the external view, we all see industrial equipment as just a sheer assembly of all components. But what goes into manufacturing one is enormous. Assembling components alone are not involved in manufacturing of industrial equipment. Validation is an important part of the process and under validation comes the testing of Computational Fluid Dynamics. Perfect and stunning outer look alone won’t say equipment is fit to be launched in the market. Rather how it reacts to different conditions and is it resistant to untoward incidents. So many tests like finite element method, spectral element method, coherent vortex simulation, direct numerical simulation to name a few are done to ensure each equipment manufactured is in the best of all conditions to make the end user’s ride comfortable. Here are some of the applications of Computational Fluid Dynamics.

CFD Services

Thermal Management

For any product controlling temperature is quite critical. If you’re operating a chemical reactor less than the required temperature the yield turns out to be less. At the same time, too high temperature will make it toxic for the workforce. Hence thermal management test is a must for any industry application. CFD involves a combination of unique simulations and analysis that generates unique results. Several cases are solved based on assumptions and general rules, but for critical cases like thermal management CFD turns out to be more viable.

Cavitation

Pumps, valves, compressors and fuel injectors are often prone to formation of vapour bubbles. It is quite a common challenge and in many cases can pull down the overall performance of the equipment. Excessive noise and vibration is one among the biggest challenges posed by cavitation. Hence to fix this issue, wide of range of CFD analysis and simulations can be utilized. Cavitation is a problem which can be avoided if the design is right. Hence engineers can utilize an array of CFD analysis methods to see the design doesn’t produce a model which is prone to cavitation in any of the relevant components.

Turbomachinery

Improving efficiency of turbochargers and turbopumps is a big challenge for any manufacturer. Experts say improving this performance can actually save billions of money spent on air transport and gas powered electrical industry. Also, performance improvements with regard to safety, operating range, reliability, operating costs and time to market are other set of challenges involved. Accurate simulation is the optimal solution to overcome this issue and CFD applications are the right ones to do so. With CFD, not only your efficiency and reliability increases, but also you can lower your emissions.

Structure Interactions

An important challenge involved in fluid flow management is structural interactions. Interaction of fluid with structures will actually cause damage to some parts and cause deformations. This in turn might change the course of fluid flow. To overcome this, you need to fix this issue in the design stage itself. To predict possible fluid and structural interactions, Computational Fluid Dynamics comes as a problem solver with its optimal simulations and analysis. Hence with CFD, you can better understand the behavior of your product and avoid challenges.

Technosoft Engineering with an experience of two decades in the field of computational fluid dynamics offers impeccable solutions to simplify complex processes. Refer to this page to understand how the offerings of Technosoft are unique and how it keeps your ante up in the market. Also, know the Trends in Electrical Engineering Services.

General Process of Fatigue Analysis

October 3, 2018

Before letting a product in the market, every manufacturer runs a stress test on the product to see if it can withstand in any condition and last for long. So a product should be robust enough and should come through all these tests before entering the market. This is a quality analyzing process. Stress test is still a part of the process; there is a more general term that consumes stress test and i.e. Fatigue Analysis. The name might sound clinical, but its significance is not. Fatigue Analysis is to fundamentally test the capacity of the product and how many life cycles it can take. By doing this, you are releasing a product that is way more viable for your target audience to make you relevant for a prolonged time. Here is the general process involved in Fatigue Analysis.

Fatigue Analysis

Time & the No. of Cycles it Should Last

When you make a product you come up with a plan. For example, when you manufacture a battery, you have a time planned for it to last. Your idea will be to let it last for three months. In the contrary, you might even think your product should last forever. But the tiny component comes with limited capacity and every time the one who uses might have to refill the battery. Hence when you manufacture the product, you need to decide how long the product should last.

Stress Analysis for Each Load

When we say each load, it is the cycle it revamps. Let us say the component you manufacture keeps falling down every one year. Hence you have to do a stress analysis for each load i.e. for the each cycle. So you will know how much refill, where to fix, how to fix etc. By doing so, you limit overall damages.

No. of Cycles Each Loading Event in a Cycle Will See

When you reload or refill to revamp the product, you should exactly know the time when the component will fail. So you can approach your clients, get the component and revamp it completely. If you fail to do so, they end up changing it with some other brand. This activity will amp up your relevance in the market.

Find a Fatigue Curve with Correct Loading Ratio to Find Damage Produced by Each Stress Level for Each Loading Event

Times keep changing. We might have a plan, but whatever happens is not going to be as we planned. Hence you should always come with a Plan B to cover up the extra damage. Fatigue Analysis suggests identifying the Fatigue Curve, testing the damage for each stress level and for each loading event. This activity will help you do the right changes while revamping in each and every cycle.

Combine All Damages & Multiply by Desired Safety Factor

Damages in each revamping cycle will differ. Hence you need to keep a note of damages that occurred in every cycle. This will help you ensure that you employ practices to limit the number of damage while manufacturing the next set of components.

Technosoft Engineering with an experience of two decades in the field of engineering design offers impeccable solutions to simplify complex processes. Refer to this page to understand how the offerings of Technosoft are unique and how it keeps your ante up in the market.