A blog on what's new, notable, and next in turbomachinery

Optimization of Cycle Parameters, Fuel Consumption, and Weight of a Turboshaft Engine Using 1D Design Tools

By Oleg Dubitsky
Jun 1, 2017

  • Facebook
  • Twitter
  • LinkedIn

New engine development is a costly endeavor and making the right decisions early in the engine design is extremely important. It requires multi-disciplinary consideration of the engine thermodynamic cycle coupled with preliminary aerodynamic design of key engine components. This includes evaluation of size, weight and cost parameters, with constraints imposed by aero, structural, geometrical, manufacturing, and material requirements.

Preliminary design tools, like the ones found in Concepts NREC's Agile Engineering Design System®, help solve this difficult challenge.

Let’s consider, as an example, a design task to find specifications for gas-generators for the most efficient turboshaft engine with shaft power output 956kW, similar to the 2-spool MTR390. The gas generator of this engine utilizes a 2-stage radial compressor and a single-stage axial turbine. A schematic view of the engine layout is shown below:

Helicopter Engine Cutaway.jpg

The problem formulation is as follows:

  • Find geometry of a gas generator  ( 2-spool helicopter engine) for an engine with the specified shaft power, optimized for SFC and weight. The requested outcomes are cycle parameters, spool-1 speed and 1D geometry of the compressor and turbine, with spool-2 speed defined.

  • Constraints are set to follow common design practice and material choices. Components of the compressor and turbine are to be optimized in the process, with consideration of all flow path components (impeller, diffusers, nozzles etc.), stage pressure ratio splits (in compressor stages, between HPT and LPT) and reactions. Spool-1 power needs to satisfy shaft power balance between the compressor and HP turbine.

Modeling of the engine is set in a simplified way:

  • Replicate engine cycle balances (flow, energy) with  shaft power balances 

  • Model 2-stage radial compressor with all diffuser and de-swirl components using COMPAL® (Spool 1)

  • Model 1 stage HP Turbine using AXIAL (spool 1)

  • Use simple models for combustor, inter-turbine transitional duct (to account for fuel injection, combustion pressure losses in these components as required). The combustor model calculates amount of required heat (ie fuel) to the cycle, which is used to evaluate SFC

  • Use a simple adiabatic model for LP Power turbine (spool 2) with user specified efficiency

  • Use weight and size estimations (user correlations, driven by  results of  COMPAL and AXIAL)

  • Use constraints, per common design practice (not per specific engine design! – though that is also possible), which are imposed on AN2, Zweifel coefficient, maximum disk rim speed (disk stress), allowed gas temperatures (affected by choice of materials and blade cooling settings), minimally allowed blade heights, flow-path flare angles in turbine, tip speeds, Mach numbers at inlet of impeller and diffuser components and limitations of allowed levels of flow diffusion (to guarantee stall operating margins), etc.

The Process:

2-stage Compressor model is set in COMPAL in preliminary design mode to allow the optimizer to control the pressure ratio in the compressor stages, geometry of impeller and diffuser systems.

HP turbine is set in AXIAL in redesign mode, allowing variations in flowpath contours, radial sizes, various blade parameters, turbine reaction and pressure ratio.

Assumptions on inter-duct and combustor losses, shaft mechanical losses, amount of cooling are adopted at levels typical for turboshaft engines of similar class, or deduced from the published research papers.

The IOSO PM Optimizer® is used to set up interactions between the models and to drive optimization, executing user models and calls to COMPAL and AXIAL, with TurboOpt ll to facilitate data communication and design tools calls  during optimization run.

A schematic view of the modeling flowchart is shown in the picture below:

 Flowchart for Modeling Helicopter Engine.jpg

The optimization problem includes 29 input variables, 4 objectives and 42 constraints.

The objectives are: minimize SFC, minimize weight, minimize spool 1 shaft power imbalance, minimize LP turbine power to specific target value.

Parallel optimization was set and executed on 8 computers with time from start to completion ~ 24 hrs, producing >6000 solutions.

Optimization of Helicopter Engine.jpg

Once optimization is stopped, the obtained results are represented as Pareto line SFC vs Weight, so that the user can pick an optimized solution per desired trade off between weight and SFC.

The table below compares results of an optimized solution, selected from the obtained Pareto front, to be in close proximity to MTR30 by weight, vs reported data for the existing engine, accumulated from various public sources:

 Helicopter Engine Specs gathered from Public resources.jpg

Parameters that are not shown in bold font in the table are result of optimization. Comparison of the optimized results vs data of the existing engine is quite good, considering that the only real specification in the problem is to deliver required shaft power.

The outcome of this problem is not only the cycle and overall engine data, but 1D designs for the compressor and turbine, ready to be moved to 3D geometry design.

A similar approach can be used for engine turbochargers, refrigeration turbo-expanders and rocket turbopump systems.

Tags: CAE Software

Subscribe to SpinOffs