The Evolution Of Modern Jet Engine Design Methodologies

Turbofan engines are the backbone of modern aviation, powering nearly everything from commercial airliners to military jets. These engines must strike a delicate balance between efficiency, performance, and reliability while also meeting increasingly strict environmental and economic demands. Traditionally, the turbofan and jet engine design process has relied on incremental improvements, component-level optimization, and extensive physical testing. However, these methods often result in suboptimal integration, longer development cycles, and higher costs. To address these challenges, a more advanced and efficient approach has emerged in the form of holistic design methodologies.

An Introduction to Turbofans

A turbofan engine (Figure 1) combines the principles of a turbojet with a fan-driven bypass system, improving efficiency and reducing noise. It consists of several key components:

• Fan – Draws in a large volume of air, with some bypassing the core engine to provide additional thrust.
• Compressor – Increases the pressure of the incoming air before combustion.
• Combustor – Burns fuel to generate high-energy gases.
• Turbine – Extracts energy from the hot gases to drive the fan and compressor.
• Nozzle – Expels the gases to produce thrust.

Turbofans offer several key advantages over other types of jet engines, particularly in terms of fuel efficiency. They are significantly more efficient than pure turbojets, especially at subsonic speeds. Additionally, turbofans produce less noise due to the bypass air, making them especially valuable in commercial aviation, where noise reduction is a priority. The high thrust provided by turbofans improves both takeoff performance and cruise efficiency. These advantages make turbofans the engine of choice for most modern airliners and many military aircraft, offering the optimal balance between speed, efficiency, and noise reduction.

Traditional Turbofan Development Methods and Their Shortcomings

Turbofan engine development has traditionally followed a structured approach aimed at balancing performance, reliability, and manufacturability. While these traditional methods have served as the foundation of the industry, they have limitations as the demand for higher efficiency, performance, and innovation increases.

Traditional turbofan development relies heavily on empirical design, drawing from historical data and prior engine configurations. Engineers typically focus on incremental improvements, guided by established experience rather than disruptive innovation. To support this, they often use rule-based and analytical models rooted in legacy designs. While these tools enable rapid calculations, they can also limit the design space, making it harder to explore unconventional solutions. As a result, progress may be slowed by an overreliance on what’s already proven.

The traditional design process often involves sequential development, where different teams of engineers work on distinct subsystems—such as the fan, compressor, combustor, turbine, and nozzle—before attempting to integrate them into a complete engine. While this method allows engineers to focus on perfecting individual components, it often leads to inefficiencies when it comes to system integration. As a result, development times are extended due to the iterative nature of the process.

Another significant challenge of traditional methods is the heavy reliance on physical prototyping and real-world testing, including wind tunnels, engine test beds, and flight testing. While these methods provide valuable data on actual engine performance, they are costly and time-consuming, often requiring multiple iterations before an optimal design is reached. Despite these drawbacks, physical experiments are irreplaceable in the final stages of the design process, as they offer essential real-world validation of the engine’s performance, ensuring that the design meets all operational requirements and safety standards before production.

As the aerospace industry faces growing demands for higher efficiency, sustainability, and performance, it is clear that modern development methods—such as integrated digital simulations, AI-driven optimization, and especially holistic design frameworks—are essential for the development of next-generation turbofan engines.

What is Holistic Design and How Does it Benefit Turbofan Development?

Holistic design considers the entire system as a unified whole, rather than focusing on individual components separately. The term ‘holistic’ originates from the Greek word “hólos,” meaning “whole,” emphasizing the importance of integration over fragmentation.

In turbofan development, this approach optimizes the engine as a complete system from the outset, considering the interactions between components, gas dynamics, thermodynamics, and operational conditions. Instead of treating the fan, compressor, turbine, and combustor separately, holistic design ensures they function efficiently together, maximizing performance and minimizing inefficiencies.

Holistic design offers several key benefits in turbofan development. By optimizing all components together, holistic design reduces energy losses and improves fuel efficiency, resulting in a more efficient engine. The integration of digital simulations and multidisciplinary collaboration accelerates development, reducing reliance on costly prototyping and testing. Additionally, considering factors such as airflow interactions, thermal stresses, and vibrations ensure greater reliability and robustness. Holistic design also supports the adoption of advanced materials, alternative fuels, and emissions reduction strategies, helping manufacturers meet sustainability goals and regulatory requirements. By minimizing trial and error through simulation-driven design, this holistic process significantly reduces development costs, shortens time to market, and enables the creation of high-performance, sustainable turbofan engines.

How We Approach Holistic Design in the AxSTREAM Platform

The AxSTREAM platform applies a holistic design approach to turbofan development by integrating advanced multidisciplinary optimization, system-level analysis, and digital prototyping into a unified workflow. This ensures that all components work together efficiently rather than being designed in isolation.

Engine Performance Calculation: Practical Case

For this practical case, the PW1127G engine, which powers the Airbus A320neo and competes with the CFM LEAP-1A, was analyzed. The engine has a mass of 6,300 lb. (2,858 kg) and features a turbofan configuration of 1G-3-8-2-3 (1-stage fan + gearbox + 3-stage LPC + 8-stage HPC + 2-stage HPT + 3-stage LPT) with a fan outer diameter of 81 inches. The aircraft itself has a maximum range of 6,300 km, a maximum takeoff weight (MTOW) of 79 tons, and cruises at Mach 0.78 (833 km/h) while accommodating up to 194 passengers.

From the known data, the engine has a bypass ratio of 12.5 and an overall pressure ratio of 50, though the exact operating conditions these values correspond to remain unclear. The maximum spool RPMs, including the gearbox ratio, are 3,281; 10,047; and 22,300 rpm, with a takeoff thrust of 120.43 kN (27,075 lbf). The maximum TIT is 1,083°C at takeoff and 1,043°C in continuous operation, though the exact location of these values in the cycle needs to be confirmed.

Several critical parameters need to be determined to complete the engine performance calculation, including turbomachinery geometries, pressure ratio distribution between the fan and low-pressure compressor, turbomachinery efficiencies, and the engine mass flow rate. These parameters will be refined through cycle analysis and system-level modeling, ensuring accurate performance predictions for the PW1127G engine. The accuracy and speed of a calculation model depend on the quality of its elements. A reliable model must balance accuracy and computational efficiency to produce meaningful results (Figure 2). However, speed is also a critical factor, as faster simulations enable quicker decision-making and product development. Using a multi-fidelity approach, we can strike a balance between detail and efficiency, ultimately speeding up the design and optimization process.

 

A 0D model (Figure 3) represents components without geometric details, relying on predefined or dynamic characteristics. This approach is fast and ideal for system-level studies but lacks the precision required for detailed design.

A 1D-2D model incorporates basic component geometry, offering a more accurate representation of fluid and heat flow properties. It provides higher fidelity than 0D models but cannot capture complex 3D effects. A 3D model provides the highest accuracy but is computationally intensive and best suited for detailed studies.

There are several approaches that are utilized to determine turbomachinery component performance within system-level modeling, each with their own advantages and limitations.

A simplified approach map provides a quick way to estimate performance but lacks the ability to accurately capture effects like secondary flows, variable guide vane (VGV) restaggering, and component degradation (Figure 4).

Preliminary design methods or 1D/2D analysis offer a more detailed assessment at specific boundary conditions. These approaches strike a balance between accuracy and computational efficiency, making them highly suitable for design studies (Figure 5).

An emerging alternative is AI-based predictions, which leverage machine learning and data-driven models to provide fast and adaptable performance estimates, potentially bridging the gap between speed and accuracy (Figure 6).

 

A holistic modeling approach that integrates 0D, 1D, and 2D methods streamlines turbomachinery design by using a single project, eliminating the need for costly iterations between different software tools. This method accounts for dynamic component performance, considering both real-world (as-is) and ISO conditions, ensuring more accurate system behavior predictions. The integration of AxSTREAM’s flow path modules further enhances this approach by allowing the direct use of turbomachinery geometry, removing the need for predefined performance maps (Figure 7).

By combining 0D, 1D, and 2D layers, this holistic model enables comprehensive system analysis without time-consuming iterations between subsystems, leading to a more efficient and accurate design process.

Summary

The AxSTREAM platform enhances turbofan engine development by integrating a holistic 0D-1D-2D modeling approach, eliminating the inefficiencies of separate software tools. Traditional design methods, which rely on empirical data, physical prototyping, and isolated component optimization, can lead to system integration challenges and extended development cycles. AxSTREAM overcomes these limitations by enabling system-level analysis, digital prototyping, and multidisciplinary optimization, ensuring accurate and efficient engine performance predictions.

By leveraging multi-fidelity modeling, AxSTREAM accelerates decision-making while maintaining high accuracy. The generative design of turbomachinery geometry within the system model removes the need for predefined performance maps, allowing for seamless integration of real-world (as-is) and ISO conditions. Additionally, AI-driven predictions enhance performance estimates, bridging the gap between computational speed and accuracy. This approach significantly reduces development costs, accelerates innovation, and supports the next generation of high-performance, efficient, and sustainable turbofan engines.

References:

1. Hendler, M.; Extra, S.; Lockan, M.; Bestle, D.; Flassig, P. Compressor Design in the Context of Holistic Aero Engine Design; AIAA-2017-3334. In Proceedings of the 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Denver, CO, USA, 5–9 June 2017;
2. Konstantinos G. Kyprianidis, An Approach to Multi-Disciplinary Aero Engine Conceptual Design, ISABE-2017-22661;
3. Marco Hendler, Michael Lockan, Dieter Bestle, and Peter Flassig, Component-Specific Preliminary Engine Design Taking into Account Holistic Design Aspects. Int. J. Turbomach. Propuls. Power 2018, 3, 12; doi:10.3390/ijtpp3020012;
4. Public presentation by Alan Epstein from Pratt & Whitney at Academie de l’Air et de l’Espace (2015)