scholarly journals Adjoint-Based Multi-Point and Multi-Objective Optimization of a Turbocharger Radial Turbine

2019 ◽  
Vol 4 (2) ◽  
pp. 10 ◽  
Author(s):  
Lasse Mueller ◽  
Tom Verstraete
Keyword(s):  
Computational Cost ◽  
Meridional Flow ◽  
Optimal Designs ◽  
Programming Algorithm ◽  
Turbine Wheel ◽  
Radial Turbine ◽  
Trade Offs ◽  
Order Of Magnitude ◽  
Gradient Based ◽  
The Moment

This paper presents a gradient-based design optimization of a turbocharger radial turbine for automotive applications. The aim is to improve both the total-to-static efficiency and the moment of inertia of the turbine wheel. The search for the optimal designs is accomplished by a high-fidelity adjoint-based optimization framework using a fast sequential quadratic programming algorithm. The proposed method is able to produce improved Pareto-optimal designs, which are trade-offs between the two competing objectives, in only a few iterations. This is realized by redesigning the blade shape and the meridional flow channel for the respective target while satisfying imposed aerodynamic constraints. Furthermore, a comparative study with an evolutionary algorithm suggests that the gradient-based method has found the global Pareto front at a computational cost which is about one order of magnitude lower.

Adjoint-Based Multidisciplinary, Multipoint Optimization of a Radial Turbine Considering Aerodynamic and Structural Performances

2019 ◽  
Author(s):  
Lasse Mueller ◽  
Tom Verstraete ◽  
Marc Schwalbach
Keyword(s):  
Mechanical Stresses ◽  
Programming Algorithm ◽  
Navier Stokes ◽  
Analysis Tool ◽  
Element Analysis ◽  
Turbine Efficiency ◽  
Radial Turbine ◽  
Design Variables ◽  
Gradient Based ◽  
Adjoint Approach

Abstract This paper presents a multidisciplinary adjoint-based design optimization of a turbocharger radial turbine for automotive applications. The aim is to improve the total-to-static efficiency of the turbine while keeping mechanical stresses below a predefined limit. The search for the optimal design is accomplished using an efficient Sequential Quadratic Programming algorithm considering additional aerodynamic and manufacturing constraints. The aerodynamic performance of the wheel is evaluated by a Reynolds-Averaged Navier-Stokes solver, whereas the maximum stresses in the material are predicted by a Finite Element Analysis tool. The design gradients required by the optimizer are computed with the adjoint approach which provides sensitivity information largely independent of the number of design variables. The results presented in this paper show the clear need to take into account mechanical stresses during optimization, as they are the most restrictive design limitation. However, the gradient-based optimization algorithm is able to effectively keep the stress levels below the critical value while significantly improving the turbine efficiency in a few design cycles.

CAD-Based Adjoint Optimization of the Stresses in a Radial Turbine

2017 ◽  
Author(s):  
Tom Verstraete ◽  
Lasse Müller ◽  
Jens-Dominik Müller
Keyword(s):  
Structural Model ◽  
Computational Cost ◽  
Test Case ◽  
Analysis Tool ◽  
Full Potential ◽  
Cad Model ◽  
Stress Concentrations ◽  
Radial Turbine ◽  
Gradient Based ◽  
Von Mises

The design optimization of turbomachinery components has witnessed an increased attention in last decade, and is currently used in many companies in the daily design cycle. The adjoint method proves to have the highest potential in this field, however, has still two major shortcomings before its full potential can be used: 1) the shape is mainly parameterized by its grid and the connection to the CAD model is lost, and 2) the optimization process includes only aerodynamic performance and neglects stress and vibration requirements. Within this paper a methodology is developed to include stress calculations into a gradient-based framework, which requires the differentiation of a stress analysis tool. To allow combining the sensitivities from the structural model with those from the aero performance, the CAD model is used for parameterizing the shape, effectively defining a parametrization that controls both the fluid and solid domain that remain linked to each other without creating voids between both models. The method is tested on a radial turbine test case in which the meridional layout is optimized to reduce the maximum von Mises stresses in the material. The results demonstrate a significant reduction in stress concentrations with a limited computational cost.

Multidisciplinary Optimization of a Turbocharger Radial Turbine

2012 ◽  
Author(s):  
Lasse Mueller ◽  
Zuheyr Alsalihi ◽  
Tom Verstraete
Keyword(s):  
Computational Cost ◽  
Differential Evolution Algorithm ◽  
Multidisciplinary Optimization ◽  
Moment Of Inertia ◽  
Navier Stokes ◽  
Radial Turbine ◽  
Performance Predictions ◽  
Mach Number Distribution ◽  
Artificial Neural Network Ann ◽  
The Moment

This paper presents a multidisciplinary design optimization of a turbocharger radial turbine for automotive applications with the aim to improve two major manufacturer requirements: the total-to-static efficiency and the moment of inertia of the radial turbine impeller. The search for the best design is constrained by mechanical stress limitations, by the mass flow and power, and by aerodynamic constraints related to the isentropic Mach number distribution on the rotor blade. The optimization of the radial turbine is performed with a two-level optimization algorithm developed at the von Karman Institute for Fluid Dynamics (VKI). The system makes use of a Differential Evolution algorithm, an Artificial Neural Network (ANN), and a database as a compromise between accuracy and computational cost. The ANN performance predictions are periodically validated by means of accurate steady state 3D Navier-Stokes and centrifugal stress computations. The results show that it is possible to improve the efficiency and the moment of inertia only in a few numbers of iterations while limiting the stresses to a maximum value. Based on the large number of evaluated designs during the optimization, this paper provides design recommendations of a turbocharger radial turbine at least for a good preliminary design.

Gradient-Based Optimization of a Radial Turbine Volute and a Downstream Bend Using Vertex Morphing

2020 ◽  
Author(s):  
Nicolas Lachenmaier ◽  
Daniel Baumgärtner ◽  
Heinz-Peter Schiffer ◽  
Johannes Kech
Keyword(s):  
Shape Optimization ◽  
Combustion Engine ◽  
Pressure Ratio ◽  
Load Condition ◽  
Adjoint Methods ◽  
Turbine Wheel ◽  
Pressure Drops ◽  
Radial Turbine ◽  
Efficiency Increase ◽  
Gradient Based

Abstract The higher the efficiency of a turbocharger’s radial turbine, the lower is the necessary pressure ratio to deliver a specified power to the compressor. This, in turn, reduces the fuel consumption of the internal combustion engine as a lower pressure upstream of the turbine increases the obtained charge-cycle work. In this paper, two components of a nozzled radial turbine system are redesigned: Both the volute upstream and the 90°-bend downstream of the turbine wheel will be improved. To reduce pressure drops, a gradient-based shape optimization workflow based on adjoint methods is applied. The scheme works in an iterative manner, i.e. after running a primal and an adjoint simulation to gather shape sensitivities, the geometry is deformed and the next iteration is started. A steepest descent approach is used to guide the optimization process. As parametrization strategy the Vertex Morphing Method is used to explore design potential, while maintaining smooth surfaces. Both the volute and the bend are optimized successfully leading to an efficiency increase of the turbine system of up to 3%, depending on the load condition.

Multidisciplinary Optimization of a Turbocharger Radial Turbine

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
Lasse Mueller ◽  
Zuheyr Alsalihi ◽  
Tom Verstraete
Keyword(s):  
Computational Cost ◽  
Differential Evolution Algorithm ◽  
Multidisciplinary Optimization ◽  
Moment Of Inertia ◽  
Navier Stokes ◽  
Radial Turbine ◽  
Performance Predictions ◽  
Mach Number Distribution ◽  
Artificial Neural Network Ann ◽  
The Moment

This paper presents a multidisciplinary design optimization of a turbocharger radial turbine for automotive applications with the aim to improve two major manufacturer requirements: the total-to-static efficiency and the moment of inertia of the radial turbine impeller. The search for the best design is constrained by mechanical stress limitations, by the mass flow and power, and by aerodynamic constraints related to the isentropic Mach number distribution on the rotor blade. The optimization of the radial turbine is performed with a two-level optimization algorithm developed at the von Karman Institute for Fluid Dynamics. The system makes use of a differential evolution algorithm, an artificial neural network (ANN), and a database as a compromise between accuracy and computational cost. The ANN performance predictions are periodically validated by means of accurate steady state 3D Navier-Stokes and centrifugal stress computations. The results show that it is possible to improve the efficiency and the moment of inertia only in a few numbers of iterations while limiting the stresses to a maximum value. Based on the large number of evaluated designs during the optimization, this paper provides design recommendations of a turbocharger radial turbine at least for a good preliminary design.

MicroVolt Variations of The Human Brain (Quantitative Electroencephalography) Display Differential Torque Effects During West-East versus North-South Orientation in the Geomagnetic Field

2016 ◽  
Vol 12 (2) ◽  
pp. 4255-4259
Author(s):  
Michael A Persinger ◽  
David A Vares ◽  
Paula L Corradini
Keyword(s):  
Human Brain ◽  
Geomagnetic Field ◽  
Neuronal Cell ◽  
Single Subject ◽  
Additional Energy ◽  
Actual Measurement ◽  
Neuronal Processes ◽  
Basic Physics ◽  
Order Of Magnitude ◽  
The Moment

                The human brain was assumed to be an elliptical electric dipole. Repeated quantitative electroencephalographic measurements over several weeks were completed for a single subject who sat in either a magnetic eastward or magnetic southward direction. The predicted potential difference equivalence for the torque while facing perpendicular (west-to-east) to the northward component of the geomagnetic field (relative to facing south) was 4 μV. The actual measurement was 10 μV. The oscillation frequency around the central equilibrium based upon the summed units of neuronal processes within the cerebral cortices for the moment of inertia was 1 to 2 ms which are the boundaries for the action potential of axons and the latencies for diffusion of neurotransmitters. The calculated additional energy available to each neuron within the human cerebrum during the torque condition was ~10-20 J which is the same order of magnitude as the energy associated with action potentials, resting membrane potentials, and ligand-receptor binding. It is also the basic energy at the level of the neuronal cell membrane that originates from gravitational forces upon a single cell and the local expression of the uniaxial magnetic anisotropic constant for ferritin which occurs in the brain. These results indicate that the more complex electrophysiological functions that are strongly correlated with cognitive and related human properties can be described by basic physics and may respond to specific geomagnetic spatial orientation.

Integrated Optimization Design for a Radial Turbine Wheel of a 100kW-Class Microturbine

2011 ◽  
Author(s):  
Lei Fu ◽  
Yan Shi ◽  
Qinghua Deng ◽  
Huaizhi Li ◽  
Zhenping Feng
Keyword(s):  
Optimization Design ◽  
Design Method ◽  
Aerodynamic Performance ◽  
Original Design ◽  
Element Analysis ◽  
Turbine Wheel ◽  
Strength Performance ◽  
Integrated Optimization ◽  
Radial Turbine ◽  
Integrated Optimization Design

The aerodynamic performance, structural strength and wheel weight are three important factors in the design process of the radial turbine. This paper presents an investigation on these aspects and develops an optimization design approach for radial turbine with consideration of the three factors. The aerodynamic design for the turbine wheel with inlet diameter of 230mm for 100kW-class microturbine unit is carried out firstly as the original design. Then, the cylinder parabolic geometrical design method is applied to the wheel modeling and structural design, but the maximum stress predicted by Finite Element Analysis greatly exceeds the yield limit of material. Furthermore, the wheel weight is above 7.2kg thus bringing some critical difficulties for bearing design and turbine operation. Therefore, an integrated optimization design method for radial turbine is studied and developed in this paper with focus on the wheel design. Meridional profiles and shape lines of turbine wheel are optimized with consideration of the whole wheel weight. Main structural modeling parameters are reselected to reduce the wheel weight. Trade-off between aerodynamic performance and strength performance is highly emphasized during the optimization design. The results show that the optimized turbine wheel gets high aerodynamic performance and acceptable stress distribution with the weight less than 3.8kg.

Gradient-Based Optimization of a Radial Turbine Volute and a Downstream Bend Using Vertex Morphing

2021 ◽  
Author(s):  
Nicolas Lachenmaier ◽  
Daniel Baumg\xe4rtner ◽  
Heinz-Peter Schiffer ◽  
Johannes Kech
Keyword(s):  
Radial Turbine ◽  
Gradient Based

Mistuning and Damping of a Radial Turbine Wheel. Part 1: Fundamental Analyses and Design of Intentional Mistuning Pattern

2021 ◽  
Author(s):  
Alex Nakos ◽  
Bernd Beirow ◽  
Arthur Zobel
Keyword(s):  
High Stress ◽  
Forced Response ◽  
Experimental Investigations ◽  
Detailed Knowledge ◽  
Turbine Wheel ◽  
Operation Conditions ◽  
Radial Turbine ◽  
Influence Coefficients ◽  
Modes Of Vibration ◽  
The Impact

Abstract The radial turbine impeller of an exhaust turbocharger is analyzed in view of both free vibration and forced response. Due to random blade mistuning resulting from unavoidable inaccuracies in manufacture or material inhomogeneities, localized modes of vibration may arise, which involve the risk of severely magnified blade displacements and inadmissibly high stress levels compared to the tuned counterpart. Contrary, the use of intentional mistuning (IM) has proved to be an efficient measure to mitigate the forced response. Independently, the presence of aerodynamic damping is significant with respect to limit the forced response since structural damping ratios of integrally bladed rotors typically take extremely low values. Hence, a detailed knowledge of respective damping ratios would be desirable while developing a robust rotor design. For this, far-reaching experimental investigations are carried out to determine the damping of a comparative wheel within a wide pressure range by simulating operation conditions in a pressure tank. Reduced order models are built up for designing suitable intentional mistuning patterns by using the subset of nominal system modes (SNM) approach introduced by Yang and Griffin [1], which conveniently allows for accounting both differing mistuning patterns and the impact of aeroelastic interaction by means of aerodynamic influence coefficients (AIC). Further, finite element analyses are carried out in order to identify appropriate measures how to implement intentional mistuning patterns, which are featuring only two different blade designs. In detail, the impact of specific geometric modifications on blade natural frequencies is investigated.

Sign in / Sign up

Export Citation Format

Share Document