Types of Heat Exchangers: Design & Applications

Efficient heat exchangers are essential in various industrial processes, as they effortlessly transfer heat energy while minimizing energy consumption. These incredibly versatile and reliable components can recover and recycle thermal energy, making them a crucial part of modern engineering.

Heat exchangers are a great piece of mechanical engineering! They significantly enhance energy efficiency, promote sustainability, and create a greener world by ensuring an optimal heat transfer mechanism.

This article will review the basic mechanisms and the revolutionary new application of AI to heat exchangers.

Prediction VS Simulation: AI models are able to accurately capture complex flow patterns.

What Is a Heat Exchanger?

Heat exchangers facilitate heat transfer, which can occur between multiple fluids or between a fluid and a solid surface without direct fluid contact.

Notably, "fluid" encompasses fluids in liquid, gas, or vapor form. This results in many possible combinations of how heat-exchanging devices operate based on the flow configuration.

A heat exchanger transfers thermal energy between fluids without them directly contacting each other, whether it involves heating or cooling.

Heat exchangers are crucial in various industries and applications where efficient transfer of heat is necessary, including power plants, refrigeration and air conditioning systems, chemical processing plants, automobiles, and everyday household appliances like water heaters.

Heat exchangers come in various designs and configurations, but their basic principle remains: transferring heat from a hot fluid or surface to a cooler one.

Typically, a heat exchanger consists of tubes or plates. The function of tubes and plates is to create a large surface area for heat transfer. One fluid flows through these tubes or passages while the other passes across or around them.

Depending on the specific design and requirements, fluids can flow in parallel or counterflow patterns. The heat exchanger maximizes the thermal contact between the fluids, promoting efficient heat transfer.

A parallel flow heat exchanger is a type of heat exchanger in which both the hot and cold fluid streams flow in the same direction, parallel to each other. In this configuration, the two fluid streams enter the heat exchanger at the same end and flow side by side through separate channels or passages.

In parallel flow heat exchangers, the flow configuration is characterized by the hot fluid and cold fluid approaching each other and exchanging heat as they move along the length of the heat exchanger. The temperature difference between the two fluids in this flow configuration gradually decreases as heat transfers from the hotter fluid to the cooler fluid.

The effectiveness of a heat exchanger depends on several factors, including the design, surface area, flow rates, temperature differences, and thermal properties of the fluids involved, as well as the chosen flow configurations.

The figure illustrates three types of heat exchangers based on the flow configuration: parallel flow heat exchanger types with fluid flow in the same direction, counter flow heat exchangers, and cross flow heat exchangers. Each flow configuration has a different way of exchanging heat between the working fluids. The most efficient way to exchange heat is the counter-current configuration.

Classification of heat exchangers according to flow configuration, left to right: parallel flow, countercurrent , and crossflow
Classification of heat exchangers according to flow configuration, left to right: parallel flow, countercurrent , and crossflow.

Heat Exchangers in Industry and Nature

Heat exchangers in the industry and heat exchangers in nature (organisms) can be analogous in their function and purpose, despite the differences in scale and specific mechanisms.

While there are obvious differences between industrial and natural heat exchangers, such as the scale, materials used, and complexity of designs, the fundamental principles and objectives of transferring heat efficiently remain consistent. Understanding the analogies between the two can provide insights and inspiration for improving heat transfer technologies in industrial and biological contexts.

The figure shows the three main ways to exchange heat.

A practical review of the three types of heat exchange (Image source: https://physics.stackexchange.com)
A practical review of the three types of heat exchange (Image source: https://physics.stackexchange.com)

Let's explore the analogy between the two macro classes of heat exchangers, industrial and biological.

Heat Exchanger Function

Both industrial and natural heat exchangers transfer heat from one medium to another. The primary objective is facilitating efficient heat transfer to maintain desired temperatures for various processes or biological functions.

In both cases, the heat transfer process mechanism occurs through the same physical mechanisms of conduction, convection, and radiation.

Industrial Heat Exchangers

In industry, heat exchangers are devices designed to efficiently transfer heat between two or more fluids, such as water, air, or process fluids. They often consist of a network of pipes or channels through which the fluids flow. The heat exchange can be achieved through contact between the fluids (in the case of liquid-liquid or gas-gas exchangers) or through walls that separate the fluids (in the case of liquid-gas or gas-liquid exchangers). Examples include shell-and-tube exchangers, plate heat exchangers, and finned-tube cross-flow heat exchangers.

Natural Heat Exchangers

In nature, organisms have evolved various heat exchange mechanisms to regulate their body temperature and optimize metabolic processes in warm-blooded animals, such as mammals and birds, blood vessels near the surface of the skin act as heat exchangers. Blood vessels widen near the skin surface to dissipate heat and narrow to retain heat, helping regulate internal body temperature.

Countercurrent Flow in Natural and Industrial Heat Exchangers

Both industrial and natural heat exchangers often utilize countercurrent flow to enhance efficiency. Countercurrent flow refers to the arrangement where the hot and cold fluids flow in opposite directions. This arrangement maximizes the temperature difference between the two fluids along the heat exchanger, leading to efficient heat transfer.

Optimization in Natural and Industrial Heat Exchangers

In both cases, heat exchangers are designed or evolved to optimize heat transfer efficiency and minimize energy consumption. Industrial heat exchangers are optimized to achieve high heat transfer rates while minimizing pressure drops, fouling, and other inefficiencies. Similarly, natural heat exchangers in organisms are optimized through evolutionary processes to ensure effective temperature regulation and metabolic performance.

Design Characteristics for Heat Exchangers

Designing efficient and high-performance heat exchangers requires careful consideration of several key characteristics. By incorporating these design considerations, engineers can optimize heat exchanger performance, enhance energy efficiency, and ensure reliable operation in a wide range of industrial applications:

  1. Surface Area: One of the fundamental design considerations for heat exchangers is maximizing the heat transfer surface area. The greater the surface area, the more efficient the heat exchange process becomes. This can be accomplished by incorporating extended surfaces (fins) or using a compact design with multiple small tubes or plates.
  2. Fluid Flow Arrangement: Fluid flow arrangement within a heat exchanger significantly affects its performance. Countercurrent flow, where the hot and cold fluids flow in opposite directions, offers the highest temperature difference along the heat exchanger length and maximizes heat transfer efficiency. Cross-flow and parallel-flow configurations are commonly employed, depending on the specific application and desired performance requirements.
  3. Heat Transfer Surface Enhancement: Heat exchangers often incorporate surface enhancements to enhance heat transfer. These enhancements can include fins, turbulators, corrugations, or extended surfaces. Heat exchangers can achieve improved heat transfer rates by increasing the surface turbulence or extending the surface area.
  4. Materials Selection: Selecting appropriate materials is crucial for heat exchanger design, considering factors such as thermal conductivity, corrosion resistance, and cost. The choice of materials depends on the nature of the fluids being processed, operating temperatures, and environmental considerations.
  5. Flow Distribution: Efficient flow distribution is essential to ensure uniform heat transfer across the heat exchanger surface. Uneven flow distribution can lead to hotspots, reduced heat transfer rates, or increased pressure drops. Designing appropriate flow distribution devices, such as baffles, flow distributors, or flow straighteners, helps promote even fluid distribution and optimal heat transfer.
  6. Fluid Velocity and Pressure Drop: Determining the appropriate fluid velocities and pressure drops within a heat exchanger is crucial. Higher fluid velocities generally enhance heat transfer, but excessively high velocities can increase pressure drop and energy consumption. A balance must be struck to achieve optimal heat transfer while considering the system's energy requirements and limitations.
  7. Fouling: The accumulation of unwanted deposits on heat transfer surfaces can significantly degrade heat exchanger performance. Designing heat exchangers with appropriate features, such as easily accessible surfaces for cleaning, fouling-resistant materials, or flow-enhancing techniques, can help mitigate fouling effects and maintain long-term efficiency.
  8. Thermal Expansion and Stress: Heat exchangers are subjected to thermal expansion and contraction during operation, leading to thermal stresses. Proper design accounting for thermal expansion, stress analysis, and material compatibility is essential to ensure structural integrity and avoid leakage or premature failure.

How Do Heat Exchangers Operate?

Heat exchangers are fundamental thermodynamic devices that enable efficient heat transfer between fluids or between a fluid and a solid surface. They operate based on several thermodynamic principles and equations, ensuring the proper energy exchange.

Thermodynamics Principles

Let us delve now into the key concepts governing heat exchanger operation with the aid of some simple maths.

The fundamental equation governing heat transfer (HT) is the heat conduction equation, given by:

Q = h × S × ΔT

where:

  • Q represents the heat transfer (HT)
  • h is the overall HT coefficient
  • S is the surface area available for HT,
  • ΔT is the temperature difference between the fluids or surfaces.

The overall HT coefficient (h) considers various resistances to HT, such as conduction, convection, and radiation. It depends on the materials' thermal conductivities, the walls' thickness, and the fluids' flow rates.

Heat exchangers employ the principle of energy conservation, represented by the first law of thermodynamics. It states that the energy entering a system must equal the energy leaving it. In the case of a heat exchanger, the energy transferred as heat from the hot fluid is equal to the energy gained by the cold fluid.

Different types of heat exchangers utilize specific flow patterns to optimize heat transfer. For example, in a parallel flow heat exchanger, both fluids enter at one end, and hot and cold liquids travel parallel to each other, resulting in a gradual temperature difference reduction along the length of the exchanger. In a counterflow heat exchanger, the hot and cold fluids enter at opposite ends, maximizing the temperature difference and enhancing HT.

Heat Exchanger Effectiveness ε

Efficiency is a crucial consideration in heat exchanger operation.

The effectiveness ε of a heat exchanger is defined as the ratio of actual HT to the maximum possible HT.

It can be calculated using the equation:

ε = Qₐ / Qₘₐₓ

where Qₐ is the actual HT observed, and Qₘₐₓ is the maximum HT possible based on the temperature difference between the fluids.

Engineers consider parameters such as fluid flow rates, properties, and design features to optimize heat exchanger performance. Increasing surface area, using fins or turbulators, and employing materials with high thermal conductivity can enhance HT.

In conclusion, heat exchangers operate based on thermodynamic principles involving energy conservation, heat conduction equations, and fluid flow patterns. By leveraging these principles, heat exchangers efficiently transfer thermal energy between fluids or surfaces, contributing to the overall energy efficiency and sustainability of various industrial processes.

Recuperative Heat Exchangers: Heat Exchanger Heat Recovery

Heat exchanger heat recovery is a process that involves the transfer of heat from a high-temperature fluid or gas stream to a lower-temperature fluid or gas stream. It is a method used to capture and reuse waste heat, which would otherwise be lost to the environment.

A significant amount of waste heat is often generated in various industrial processes and energy systems. Recuperative heat exchangers are designed to recover and transfer this waste heat to another medium, such as water or air, for reuse in other applications. By doing so, the energy efficiency of the overall system can be significantly improved, leading to energy savings and reduced operating costs.

The heat recovery process typically involves using heat exchangers, devices designed to facilitate heat transfer between two fluids without them coming into contact. Depending on the specific application and requirements, these waste heat recovery unit exchangers can take various forms, such as shell-and-tube, plate-and-frame, or finned-tube heat exchangers.

During the heat recovery, the waste heat source, which can be hot exhaust gases, steam, or other high-temperature fluids, passes through one side of the waste heat recovery unit exchanger. Meanwhile, the fluid or gas that requires heating or preheating passes through the other side. As the two streams flow close but remain physically separate, heat is transferred from the high-temperature stream to the lower-temperature stream, raising its temperature without mixing the two fluids.

The recovered air-cooled heat exchangers can be utilized for various purposes, such as space heating, water heating, preheating combustion air, or generating electricity through steam turbines. By implementing heat exchanger heat recovery systems, industries can improve their energy efficiency, reduce their carbon footprint, and achieve cost savings by utilizing waste heat that would otherwise be wasted.

Types of Heat Exchangers

Heat exchangers are vital in various industrial applications, enabling efficient heat transfer between fluids or surfaces. They come in various designs and configurations, each with advantages and limitations. In this section, we will explore some of the most common types of heat exchangers.

Understanding the characteristics and capabilities of each type of heat exchanger is crucial in selecting the appropriate heat exchanger for specific industrial processes, ensuring efficient HT and overall system performance.

plate heat exchanger images - A close-up view of a plate type heat exchanger (Image source: Image Credit: withGod/Shutterstock.com)
Plate heat exchanger images - A close-up view of a plate type heat exchanger.

Double Pipe Heat Exchangers

A double-pipe heat exchanger, or hairpin heat exchanger, consists of two concentric pipes. One fluid flows through the inner pipe, while the other flows through the outer pipe in the opposite direction. A double-pipe heat exchanger is simple, compact, and suitable for low to moderate heat transfer (HT) applications.

Tube Exchangers

Tube heat exchangers are widely used in various industries for efficient heat transfer (HT) between two fluid streams. They consist of a bundle of tubes, typically made of metal, arranged in a cylindrical shell. These tubular heat exchangers are designed to maximize the surface area available for HT, allowing for efficient energy exchange between the fluids.

The basic principle behind this heat exchanger is transferring heat from one fluid to another through the tube walls. The fluids flow in opposite directions, known as counterflow, or in the same direction, known as parallel flow heat exchangers. The temperature difference between the two fluids drives the heat transfer process.

The HT rate in this type of heat exchanger can be quantified using the following equation:

Q = h × S × ΔTₗₘ

Where:

  • Q is the HT rate,
  • h is the overall HT coefficient,
  • S is the total surface area available for HT,
  • ΔTₗₘ is the logarithmic mean temperature difference.

The overall HT coefficient h considers the resistance to HT on both sides of the tube walls and within the fluids themselves.

It can be expressed as:

1/h = (1/hᵢ) + (ϑᵢ/ϰᵢ) + (ϑₒ/ϰₒ) + (1/hₒ)

Where:

  • hᵢ is the convective HT coefficient on the inside of the tubes (in W/(m²·K)),
  • hₒ is the convective HT coefficient on the outside of the tubes (in W/(m²·K)),
  • ϑᵢ is the thickness of the tube wall on the inside (in meters),
  • ϑₒ is the thickness of the tube wall on the outside (in meters),
  • ϰᵢ is the thermal conductivity of the tube wall on the inside (in W/(m·K)),
  • ϰₒ is the thermal conductivity of the tube wall on the outside (in W/(m·K)).

The logarithmic mean temperature difference, ΔTₗₘ, measures the average temperature difference between the two fluids throughout the length of the heat exchanger.

It can be calculated using the equation:

ΔTₗₘ = (ΔT₁ - ΔT₂) / ln T₁ / ΔT₂)

where:

  • ΔT₁ is the temperature difference between the hot fluid entering and leaving the heat exchanger;
  • ΔT₂ is the temperature difference between the cold fluid entering and leaving the heat exchanger.

Tube heat exchangers offer several advantages in terms of their design and operation. Its compact size allows for efficient use of space, making them suitable for various applications.

A tube heat exchanger can handle high pressures and temperatures, making them suitable for demanding industrial processes. Additionally, this type of heat exchanger is relatively easy to maintain and clean, ensuring long-term performance.

In conclusion, tube heat exchangers are essential components in many industrial processes, providing an efficient transfer of heat between two fluid streams in the tube heat exchanger. The heat exchanger design, based on the principles of HT, enables effective energy exchange.

By optimizing parameters such as the overall HT coefficient and logarithmic mean temperature difference, they can be tailored to specific applications, ensuring the reliable and efficient operation of heat exchangers.

Shell and Tube Heat Exchanger (Image source: Yousufuddin S (2018) Heat Transfer Enhancement of a Shell and Tube Heat Exchanger with Different Baffle Spacing Arrangements. Sch J Appl Sci Res. Vol: 1, Issu: 6 (50-56))
Shell and Tube Heat Exchanger (Image source: Yousufuddin S (2018) Heat Transfer Enhancement of a Shell and Tube Heat Exchanger with Different Baffle Spacing Arrangements. Sch J Appl Sci Res. Vol: 1, Issu: 6 (50-56))

Tube-in-Tube Heat Exchangers

Tube-in-tube heat exchangers are composed of two concentric tubes, where one fluid flows through the inner tube, and the other flows through the annular space between the two tubes. Tube-in-tube heat exchangers are compact, provide good HT, and are commonly used in limited-space applications.

Plate Heat Exchangers

Plate heat exchangers utilize a series of stacked plates with alternating hot gas and cold fluid passages. The plates provide a large surface area for HT, allowing for efficient heat exchange in a compact design. These heat exchangers are widely used in HVAC, refrigeration, and process industries.

Counterflow sanitary plate heat exchanger for wort cooling (Image source: https://brovarni.com/breweries-units-catalog/brewery-units/plate-wort-chiller/)
Counterflow sanitary plate heat exchanger for wort cooling (Image source: https://brovarni.com/breweries-units-catalog/brewery-units/plate-wort-chiller/)

Finned-Tube Heat Exchangers

A finned-tube heat exchanger consists of tubes with external fins attached. These fins increase the surface area available for heat transfer, improving the finned tube heat exchanger's efficiency compared to its version without fins. A finned-tube heat exchanger can be encountered in many air-cooled applications, such as HVAC systems and radiators.

Other Types of Heat Exchangers

There are several other types of heat exchangers tailored for specific applications. Some examples include:

  • Adiabatic Wheel Heat Exchangers: These are used for heat and humidity transfer in air conditioning systems.
  • Plate-Fin Heat Exchangers: They consist of stacked finned plates and are commonly used in aerospace and cryogenic applications.
  • Regenerative Heat Exchangers: These exchangers use a rotating matrix to alternate the flow direction of the fluids, enabling efficient transfer of heat.

Industries and Applications by Types of Heat Exchangers

Here is a table outlining the industries and applications of different heat exchanger types that may prove useful when you enter this application.

Double Pipe Heat Exchangers

Double-pipe heat exchangers are used in Chemical processing plants, small-scale industrial applications, and laboratory equipment. What are the reasons?

  1. Compact Design: Double-pipe heat exchangers have a compact design, making them suitable for installations where space is limited. They consist of two concentric pipes, one inside the other, allowing for efficient HT (heat transfer) while occupying a smaller footprint than other heat exchangers.
  2. Versatility: Double-pipe heat exchangers can handle various fluids, including liquids, gases, and mixtures. This versatility makes them suitable for different applications where various substances must be cooled or heated.
  3. Flexibility: These heat exchangers offer flexibility in terms of flow configurations. They can be arranged in either a parallel or counterflow arrangement, depending on the specific requirements of the process. This flexibility allows for optimal HT and efficiency.
  4. Easy Maintenance: Double-pipe heat exchangers are relatively easy to maintain. The two pipes can be easily accessed for cleaning, inspection, or repairs. This ease of maintenance reduces downtime and ensures the long-term reliability of the heat exchanger.
  5. Cost-Effectiveness: Double-pipe heat exchangers are often more cost-effective than other heat exchangers, especially for small-scale applications. Their simpler design and construction result in lower manufacturing costs, making them an economical choice for many industries.
  6. Temperature Control: Double-pipe heat exchangers provide effective temperature control. By utilizing a countercurrent flow arrangement, they can achieve a greater temperature differential between the hot and cold fluids, maximizing the efficiency of HT.
  7. Scalability: Double-pipe heat exchangers can be easily scaled up or down to meet the specific requirements of different applications. This scalability makes them suitable for large chemical processing plants and smaller laboratory setups.

Shell-and-Tube Heat Exchangers

Shell-and-tube heat exchangers are used in power generation, oil refineries, chemical processing, HVAC systems, food and beverage industry.

Air conditioners. Image source: Pixabay
Air conditioners

The reasons are:

  1. High Heat Transfer Efficiency: Shell-and-tube heat exchangers are known for their high heat transfer efficiency. They consist of a shell (a large outer vessel) and multiple tubes (smaller diameter tubes) inside the shell. The large surface area provided by the numerous tubes allows for efficient heat exchange between the two fluids, maximizing the transfer of heat energy. This makes shell-and-tube heat exchangers particularly effective in handling severe temperature and pressure differentials.
  2. Versatility and Durability: Shell-and-tube heat exchangers can handle various fluids, including corrosive or fouling substances. The robust construction, typically using materials such as stainless steel or other corrosion-resistant alloys, ensures their durability and resistance to harsh operating conditions.
  3. Flexibility and Easy Maintenance: Shell-and-tube heat exchangers offer flexibility in design and operation. They can be customized with different tube arrangements (such as straight, U-tube, or multi-pass) and varying shell diameters and lengths to suit specific requirements. Additionally, their modular construction allows for easy maintenance and cleaning.

Tube-in-Tube Heat Exchangers

Tube-in-tube heat exchangers are used in the pharmaceutical and dairy industries and heating and cooling systems in residential and commercial buildings.

Plate Heat Exchangers

Plate heat exchangers are used in HVAC systems, refrigeration, food and beverage industry, chemical processing, and power plants.

What are the main reasons for plate heat exchangers?

Efficiency due to their unique design. They consist of multiple thin plates with corrugated patterns, creating a large surface area for heat exchange. The corrugations enhance turbulence and promote an efficient heat transfer process between the fluids on either side of the plates. This design enables a significant heat transfer coefficient and heat energy in a compact unit, making plate heat exchangers highly efficient for heating or cooling applications.

  1. Compact Size and Space Efficiency: Plate heat exchangers are known for their compact size and space efficiency. The stacked plate configuration allows for a large HT surface area within a relatively small physical footprint. This compactness makes them ideal for installations where space is limited, such as HVAC systems, refrigeration units, and food processing facilities.

Finned-Tube Heat Exchangers

Finned-tube heat exchangers are used in HVAC systems, radiators, aerospace industry.

Other Heat Exchanger Types

  • Adiabatic wheel heat exchangers - for air conditioning systems.
  • Plate-fin heat exchangers - for aerospace and cryogenic applications.
  • Regenerative heat exchangers -for industrial processes, energy recovery.

How to Improve the Lifetime of a Heat Exchanger

Here are some key strategies to consider.

By following these practices and considering the specific requirements of your heat exchanger, you can significantly improve its lifetime and optimize its performance.

Regular Maintenance

It is recommended to establish a routine maintenance schedule for the heat exchanger. This includes periodic inspection, cleaning, and servicing. Regular heat exchanger maintenance helps identify potential issues early on and allows for prompt repairs, preventing further damage.

Proper Fluid Selection

Selecting the appropriate fluid for heat recovery and the right heat exchanger is important. Heat exchanger engineers should ensure the fluid and construction materials are compatible to avoid corrosion, erosion, or fouling and guarantee heat recovery.

Adequate Fluid Flow and Pressure

Maintain proper fluid flow rates and pressures within the recommended range. Low flow rates can lead to stagnant areas and potential fouling in the heat exchanger, while high flow rates may cause erosion or vibration. Ensure the heat exchanger is operating within the specified design parameters.

Cleanliness and Fouling Prevention

Implement effective cleaning practices to prevent fouling, which can reduce HT efficiency. Regularly clean the heat exchanger surfaces to remove deposits, debris, or biofilms hindering HT. Consider using chemical treatments or mechanical cleaning methods, such as brushing or high-pressure water jets on the heat exchanger.

Temperature Control

The recommendation is to avoid extreme temperature differentials that can cause thermal stress or fatigue on the heat exchanger. Monitor and control the fluid temperatures within the recommended operating range to prevent thermal shocks or material degradation of the heat exchanger.

Corrosion Protection

The recommendation is to implement corrosion protection measures, such as corrosion-resistant materials or coatings, sacrificial anodes, or cathodic protection systems.

Vibration and Mechanical Stress

The recommendation is to address any mechanical issues that can lead to excessive vibration or stress on the heat exchanger. Install proper supports, dampeners, or expansion joints on the frame heat exchanger to accommodate thermal expansion and contraction without causing damage to your heat exchangers.

Monitoring and Alarms

Install temperature, pressure, and flow sensors to monitor the performance of the heat exchanger. Implement alarm systems that notify operators of abnormal operating conditions, allowing immediate action to prevent further damage to heat exchangers.

Heat Exchanger Simulation - How to Solve the Conduction Equation?

The conduction equation is commonly used in heat exchanger simulations to model HT within a solid medium. It describes how heat is conducted through a material based on its temperature distribution. Solving the conduction equation allows us to determine the temperature profile and the HT rates within a heat exchanger. It is desirable to designers access simulations: we will see how AI can provide an answer.

Analytical Solution for Heat Exchangers

To determine the temperature distribution within the heat exchanger, an accurate mathematical expression, called the analytical solution of the conduction equation, must be found. However, these solutions are only applicable to basic geometries and boundary conditions. Unfortunately, in most practical cases, the complexity of the heat exchanger geometry or boundary conditions makes analytical solutions unavailable. For simple geometries (e.g. the 1D heat conduction problem in a rod), analytical solutions can be derived using the Fourier series, Laplace transforms, or the separation of variables method.

Numerical Solution for Heat Exchangers

Numerical methods are commonly employed to solve the conduction equation for more complex geometries and boundary conditions and give 1D, 2D, or 3D (and time-dependence) of the heat transfer process. These methods involve discretizing the heat exchanger into a grid or mesh and approximating the temperature at each point within the grid.

Heat exchanger CFD simulation (Image source: Saffarian, M.R., Fazelpour, F. & Sham, M. Numerical study of shell and tube heat exchanger with different cross-section tubes and combined tubes. Int J Energy Environ Eng 10, 33–46 (2019). https://doi.org/10.1007/s40095-019-0297-9
Heat exchanger CFD simulation (Image source: Saffarian, M.R., Fazelpour, F. & Sham, M. Numerical study of shell and tube heat exchanger with different cross-section tubes and combined tubes. Int J Energy Environ Eng 10, 33–46 (2019). https://doi.org/10.1007/s40095-019-0297-9)

The most widely used numerical methods for solving the conduction equation include the Finite Difference Method (FDM), Finite Element Method (FEM), and Finite Volume Method (FVM).

Numerical methods like FDM, FEM, and FVM are more versatile and commonly employed in practical heat exchanger simulations, allowing for the analysis of complex geometries and boundary conditions.

  1. Finite Difference Method (FDM): in this approach, the heat exchanger domain is divided into a grid, and the temperature at each grid point is approximated using a finite difference equation derived from the conduction equation. This method is relatively simple to implement but has limitations in handling complex geometries.
  2. Finite Element Method (FEM). FEM involves dividing the heat exchanger domain into smaller elements and approximating the temperature within each element using a set of shape functions. The temperature distribution is then obtained by solving a system of equations derived from the variational form of the conduction equation.
  3. Finite Volume Method (FVM). FVM divides the heat exchanger domain into control volumes and applies the conservation laws of mass, energy, and momentum within each control volume. The conduction equation is discretized in a set of algebraic equations. Solving these equations yields the temperature distribution within the heat exchanger. FVM is particularly useful for solving flow and HT problems in fluid-filled heat exchangers.

AI Solution for Heat Exchangers

Various industries, particularly the automotive sector, have conducted heat exchanger simulations for decades. These simulations have produced numerous files, then stored in the company's PLM (=Product lifecycle management) or SLM (=Simulation lifecycle management) system.

However, can these data be utilized more productively besides just storing and retrieving them? The answer is yes, leveraging AI in Engineering (AI=Artificial Intelligence).

Basic heat exchanger topology before optimization
Basic heat exchanger topology before optimization

AI comes to help with a data-driven approach that can simulate various types of heat exchangers. Also, it is possible for AI to generate data-driven designs. It uses deep learning to understand the connection between shape (CAD) and functionality (CFD, FEA), making custom surrogates for the CFD or FEA solvers. Comparing AI, CFD, or FEA results shows promising outcomes for the tested heat exchangers.

The solution is particularly suitable for design engineers and for anyone wishing to operate on heat exchanger geometries to optimize their performance. The outcome can be a generatively designed heat exchanger, as in the figure.

Heat exchanger topology after optimization
Heat exchanger topology after optimization

Conclusion and Next Steps

Our investigation examined different industrial heat exchangers, drawing comparisons to the heat transfer process in biological systems and exploring techniques to prolong their durability. We have also looked into design resources for these heat transfer process systems.

Finally, we briefly touched upon Deep Learning applications to mechanical engineering, a promising AI technology that has shown promising results in analyzing and enhancing heat exchangers.

Stay tuned for more informative articles in the future!

Bibliography

  1. "Incropera's Principles Of Heat And Mass Transfer", by Frank P. Incropera, P. Dewitt, ISBN 978-8126578245
  2. "Thermodynamics", by Enrico Fermi, ISBN 978-0486603612
  3. "Fundamentals of Heat Exchanger Design", by Dusan P. Sekulic, Ramesh K. Shah, ISBN 978-1119883265

About the author
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Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Thomas von Tschammer
Thomas joined Neural Concept in the company's early days in 2018, following his master’s degree in mechanical engineering with a specialization in Neuroprosthetics. He is now Director of Operations, leading the Application Engineering team, and working closely with large companies to deploy AI-based workflow in their engineering design processes.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Philipp Egolf
Philipp is responsible for the product development around the NCS platform. He has numerous years of experience in the Artificial Intelligence and data analytics environment with a background in Mechanical Engineering, the development of product visions and strategies and Human Centered Design Thinking.
About the author
Thomas von Tschammer
Thomas joined Neural Concept in the company's early days in 2018, following his master’s degree in mechanical engineering with a specialization in Neuroprosthetics. He is now Director of Operations, leading the Application Engineering team, and working closely with large companies to deploy AI-based workflow in their engineering design processes.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Thomas von Tschammer
Thomas joined Neural Concept in the company's early days in 2018, following his master’s degree in mechanical engineering with a specialization in Neuroprosthetics. He is now Director of Operations, leading the Application Engineering team, and working closely with large companies to deploy AI-based workflow in their engineering design processes.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Luca Zampieri
Luca joined the Application team in 2018, aiming to build the next generation Deep-Learning tool dedicated to CAD and CAE.
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Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
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