A new method of digital simulation for an aircraft gas turbine engine control system

An LD-9 aircraft gas turbine engine with its control system is simulated digitally by a new method, called the ‘method of spare parts’. The computer program of simulation possesses the main capabilities of a real engine altitude test facility and is called a ‘digital engine altitude simulator’. The results of simulation show that the capabilities of this new method are much better than that of the ordinary ‘method of block diagram’. The method can be used for modelling and simulating any type of gas turbine engines or industrial process control systems.     

The nozzle guide vane problem: Partitioning a heterogeneous inventory

In this paper we describe a problem which is encountered in the maintenance of gas turbine engines used in commercial and military aircraft. In particular, we address the problem of selecting a set of nozzle guide vanes, from a heterogeneous inventory of vanes, for the nozzle assembly of an engine. We formulate this problem as a partitioning problem for a heterogeneous population. Given the combinatorial complexity of the problem we develop a heuristic algorithm which is shown to be very effective in obtaining the maximum number of partitions.     

Optimal self-diagnosis policy for FADEC of gas turbine engines

FADEC (full authority digital engine control) is widely adopted for gas turbine engine controllers. The advancement of microelectronics produces high speed general purpose programmable logic controllers (PLC) with low price. When they are adopted for FADEC, we can expect high cost performance engine controllers. However, these PLCs were originally developed for ordinary industrial machinery controllers and PLC makers prohibited their use as gas turbine controllers because of their low reliability. Engine makers should give some measures to hold enough reliability when they apply PLCs for FADEC. In this paper, a FADEC is self-diagnosed at the n^th control calculations. Introducing an expected cost until self-diagnosis and an expected cost per unit time, optimal policies which minimize them are discussed. Numerical examples are finally given.     

Map-Route: a GIS-based decision support system for intra-city vehicle routing with time windows

This paper presents a Decision Support System (DSS) that enables dispatchers–schedulers to approach intra-city vehicle routing problems with time windows interactively, using appropriate computational methods and exploiting a custom knowledge base that contains information about traffic and spatial data. The DSS, named Map-Route, generates routes that satisfy time and vehicle capacity constraints. Its computational engine is based on an effective heuristic method for solving the underlying optimization problem, while its implementation is developed using MapInfo, a popular Geographical Information System (GIS) platform. Map-Route provides very efficient solutions, is particularly user-friendly, and can reach answers for a wide variety of ‘what if’ scenarios with potentially significant cost implications. We have implemented Map-Route in an actual industrial environment and we report on the experience gained from this real-life application.     

Simulation of Premixed Turbulent Combustion in a Gas Engine using the Immersed Boundary Method and a Level Set Flame Model

An efficient simulation approach for turbulent flame brush propagation is a level set formulation closed by the turbulent flame speed. A formulation of the level set equation with the corresponding treatment of the turbulent mass burning rate that is compatible with standard Finite Volume discretization schemes available in computational fluid dynamics codes is employed. In order to simplify and to speed up the meshing process in complicated geometries (here in gas engines) the immersed boundary method in a continuous formulation, where the forces replacing the boundaries are introduced in the momentum conservation equations before discretization, is employed. In our contribution, aspects of the numerical implementation of the level set flame model combined with the immersed boundary formulation in OpenFOAM are presented. First representative simulation results of a homogeneous methane/air mixture combustion in a simplified engine geometry are shown. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Classification analysis for simulation of the duration of machine breakdowns

Machine failure can have a significant impact on the throughput of manufacturing systems, therefore accurate modelling of breakdowns in manufacturing simulation models is essential. Finite mixture distributions have been successfully used by Ford Motor Company to model machine breakdown durations in simulation models of engine assembly lines. These models can be very complex, with a large number of machines. To simplify the modelling we propose a method of grouping machines with similar distributions of breakdown durations, which we call the Arrows Classification Method, where the Two-Sample Cramér-von-Mises statistic is used to measure the similarity of two sets of the data. We evaluate the classification procedure by comparing the throughput of a simulation model when run with mixture models fitted to individual machine breakdown durations; mixture models fitted to group breakdown durations; and raw data. Details of the methods and results of the classification will be presented, and demonstrated using an example.     

The influence of flow acceleration on tidal stream turbine wake dynamics: A numerical study using a coupled BEM–CFD model

Studies of tidal stream turbine performance and of wake development are often conducted in tow-tanks or in regulated flumes with uniform flows across the turbine. Whilst such studies can be very useful, it is questionable as to what extent the results would differ if the flows were more complex in nature, for instance if the flows were unsteady or non-uniform or even both. This study aims to explore whether the results would be affected once we move away from the uniform flow scenario. A numerical modelling study is presented in which tidal stream turbine performance and wake development in non-uniform flow conditions are assessed. The model implements the Blade Element Momentum method for characterising turbine rotor source terms which are used within a computational fluid dynamics model for predicting the interaction between the turbines and the surrounding flow. The model is applied to a rectangular domain and a range of slopes are implemented for the water surface to instigate an increase in flow velocity along the domain. Within an accelerated flow domain wake recovery occurred more rapidly although rotor performance was not affected.     

The modeling and numerical simulation of gas flow networks

Summary. A network formulation is introduced for the modeling and numerical simulation of complex gas transmission systems like a multi-cylinder internal combustion engine. Several simulation levels are discussed which result in different network representations of a specific system. Basic elements of a network are chambers of finite volume, straight pipes and connections like valves or nozzles. The pipe flow is modeled by the unsteady, one-dimensional Euler equations of gas dynamics. Semi-empirical approaches for the chambers and the connections yield differential-algebraic equations (DAEs) in time. The numerical solution is based on a TVD scheme for the pipe equations and a predictor-corrector method for the DAE-system. Simulation results for an internal combustion engine demonstrate the practical interest of the new approach. Received May 12, 1994 / Revised version received August 26, 1994     

Two Way Coupled Micro/Meso Scale Method for Wind Farms

Wind turbines extract energy from the approaching flow field resulting in reduced wind speeds, increased turbulence and a wake downstream of the wind turbine. The wake has a multitude of negative effects on downstream wind turbines. This includes reduced efficiency and increased unsteadiness resulting in vibrations and potentially in material fatigue. Moreover, the maintenance can increase compared to non-interfering wind turbines. The simulation of these effects is challenging. Computational fluid dynamics (CFD) simulations of these large and complex geometries requires exceedingly large computational resources. With present Reynolds Averaged Navier-Stokes (RANS) or Large Eddy Simulation (LES) based CFD methods it is virtually impossible to perform such simulations of the interaction between individual wind turbines in a complete wind turbine farm. Coupling to the mesoscale accounting for local weather situations becomes yet more challenging. This is due to the wide range of length and time scales that have to be considered for these simulations and therefore the tremendous computational power needed to perform such simulations. To investigate these effects we propose to combine ideas from existing methods, the Coarse-Grid-CFD (CGCFD) ( [1]) developed at the KIT and the meso-/ micro scale method developed at the University of Thessaloniki ( [2]). Goal of the proposed methodology is to provide a numerical method that allows to implement a wind farm in a meso-scale weather simulation which includes two-way coupling. Thus both the micro and the meso scale wind and energy production of wind farms can be addressed. This proposed multi scale coupling strategy can also be applied in two hierarchies reducing the numerical effort of the global approach yet more. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An impulse control approach for optimal maintenance scheduling of a gas turbine

Today gas turbine outages are determined by one global life counter and deterministic life times. In the future the gas turbine will be equipped with multiple life counters for outage determination. Therefore we present an impulse control approach which takes the probabilistic nature of the damage mechanism into account to calculate an optimized maintenance schedule. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Using the complex polynomial method with Mathematica to model problems involving the Laplace and Poisson equations

The complex polynomial method variant of the well‐known complex variable boundary element method (CVBEM) is reexamined in its utility in solving Partial Differential Equations (PDE) of the Poisson and Laplace type. Because the CVBEM was recently extended to three and higher dimensions, the use of complex polynomials to solve higher dimension PDE becomes apparent and therefore the advantages afforded by the use of complex polynomials can be brought to focus on higher dimension problems. Because complex polynomials involve use of computational algorithms that require high accuracy in numerical precision, including the solution of fully populated nonsymmetric matrices, the computer program Mathematica is evaluated for use as the underlying computational engine. Furthermore, Mathematica is evaluated for its internal high‐accuracy computational features and algorithms, including ease of program setup. In this research, the new program is found to provide at least a 5‐fold increase in complex polynomial degree utilization (from degree 10 to degree 50), with computational speed less than was involved in the original degree 10 approximation of Hromadka and Guymon [ASCE J Hydraulic Eng 110 (1984), 329–339], and with exceptional computational accuracy and reporting features. The Mathematica program is quite small and is provided to the reader as freeware and can be obtained from the first author. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009     

A neural network approach to efficient valuation of large portfolios of variable annuities

Managing and hedging the risks associated with Variable Annuity (VA) products require intraday valuation of key risk metrics for these products. The complex structure of VA products and computational complexity of their accurate evaluation have compelled insurance companies to adopt Monte Carlo (MC) simulations to value their large portfolios of VA products. Because the MC simulations are computationally demanding, especially for intraday valuations, insurance companies need more efficient valuation techniques. Recently, a framework based on traditional spatial interpolation techniques has been proposed that can significantly decrease the computational complexity of MC simulation (Gan and Lin, 2015). However, traditional interpolation techniques require the definition of a distance function that can significantly impact their accuracy. Moreover, none of the traditional spatial interpolation techniques provide all of the key properties of accuracy, efficiency, and granularity (Hejazi et al., 2015). In this paper, we present a neural network approach for the spatial interpolation framework that affords an efficient way to find an effective distance function. The proposed approach is accurate, efficient, and provides an accurate granular view of the input portfolio. Our numerical experiments illustrate the superiority of the performance of the proposed neural network approach compared to the traditional spatial interpolation schemes.     

Efficient and accurate numerical modeling of a micro–macro nonlinear optics model for intense and short laser pulses

In this work we are interested in the fast simulation of ultrashort and intense laser pulses propagating in macroscopic nonlinear media. In this goal, we consider the numerical micro–macro Maxwell–Schrödinger-Plasma model originally presented by Lorin et al. [9], [10]. Although this model is, in theory, applicable to large domains, due to its computational complexity, only short distances of propagation could be considered (less than 1 mm so far, see [9]). In the present paper, we explore some simple, but fast and accurate techniques allowing to reduce the computational complexity by a large factor (up to 60) and then to consider larger domains. This reduction is naturally essential to make this model relevant to study realistic laser–matter interactions at a macroscopic scale. Numerical simulations are proposed to illustrate the chosen approach.     

A mechanistic model for expansion loss coefficient in upward vertical annular flow

Gas–liquid annular flow draws different responses from its three constituents, namely, the liquid film, the entrained liquid droplets and the gas core, as they flow through a diverging section in a pipe. The resulting change in the pressure profile is a combination of several effects associated with the dynamic interactions among these three fields. Accurate simulation of the response using Eulerian–Eulerian computational fluid dynamics is not feasible because the processes are inherently complex and a framework of relevant and validated constitutive relations describing the physical processes is not yet available. In the present work, a simpler approach is adopted by studying the interactions individually in idealized settings, and bringing together the separate effects into a phenomenological model for pressure loss in upward vertical annular flow. The overall pressure change is expressed as a sum of three contributors: change in area of cross-section available for gas flow, change in the effective interfacial roughness leading to peaking of the velocity profile, and droplet-gas momentum exchange in the immediate downstream of the expansion. Using air–water experimental data from two expansion ratios and three half-angles of the diverging sections, a mechanistic correlation is proposed to evaluate the overall pressure loss coefficient.     

Optimization of the design of recuperative heat exchangers in the exhaust nozzle of an aero engine

Today the needs for safer, cleaner and more affordable civil aero engines are found to be of great importance. Five years ago, the EU initiated an action for the design and the construction of efficient and environmentally friendly aero engines (EEFAE). One of the major European gas turbine industries, MTU, has presented a new technology for an advanced aero engine design, which uses an alternative thermodynamic cycle. The basis of this cycle is the adoption of a recuperation part with the use of a system of heat exchangers, installed in the exhaust nozzle of the aircraft engine. Thermal energy in the turbine exhaust is used in the recuperator to pre-heat the compressor outlet air before combustion. The benefits of this technique are focused on reduced pollutants and decreased fuel consumption. In this work, the procedure of the optimization of this installation, by means of the imposed pressure drop downstream the aircraft engine and the balanced mass inflow to the heat exchangers is presented. The optimization is based on experimental measurements in laboratory conditions and preliminary 2D CFD modeling for the flow inside the exhaust duct and through the heat exchangers. It is shown that with a careful approach, a better arrangement of the heat exchangers can be achieved in order to have a minimum pressure drop in the exhaust nozzle which can positively affect the engine’s performance.     

Block mesh refinement for incompressible flows in curvilinear domains

A method for the solution of the Navier–Stokes equation for the prediction of flows inside domains of arbitrary shaped bounds by the use of Cartesian grids with block-refinement in space is presented. In order to avoid the complexity of the body fitted numerical grid generation procedure, we use a saw tooth method for the curvilinear geometry approximation. By using block-nested refinement, we achieved the desired geometry Cartesian approximation in order to find an accurate solution of the N–S equations. The method is applied to incompressible laminar flows and is based on a cell-centred approximation. We present the numerical simulation of the flow field for two geometries, driven cavity and stenosed tubes. The utility of the algorithm is tested by comparing the convergence characteristics and accuracy to those of the standard single grid algorithm. The Cartesian block refinement algorithm can be used in any complex curvilinear geometry simulation, to accomplish a reduction in memory requirements and the computational time effort.     

Active Flow Control Implemented in a Multi-Stage High-Speed Axial Compressor

The decrease of fuel consumption is a main objective in the development of modern aircraft engines and heavy-duty gas turbines. Especially at off-design conditions, one promising approach to suppress flow losses and to increase the efficiency of the compressor is Active Flow Control (AFC) by aspiration or injection. Aerodynamically, the compressor flow of a gas turbine responds more sensitively to volatile flow conditions than the turbine flow because of the positive pressure gradient in a compressor achieved by flow deceleration. In a decelerating flow, particularly at off-design operating conditions, the compressor flow tends to separate from the blade surfaces. This flow separation causes unstable operating conditions inside the flow path resulting in low overall engine efficiency. Thus it is obvious that counter-measures against increased flow losses at off-design operation should be concentrated on the compressor. Considering industrial objectives, both the performance increase and the operating range enhancement are subjects of current compressor research, as is a reduction of vanes or even entire stages. While a reduced vane count reduces cost, even greater benefits can be gained if entire stages could be eliminated and thus the number of rotor discs reduced, which further reduces cost along with reducing the length of the rotor which could also improve rotor dynamics. For all of these purposes, different AFC approaches were implemented in a four stage axial compressor (4AV) and were experimentally examined. This paper presents an overview of the past and ongoing AFC research at the Institute of Turbomachinery and Fluid Dynamics (TFD). (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

变循环发动机部件法建模及优化

对2013年全国研究生数学建模竞赛A题"变循环发动机部件法建模及优化"的问题进行建模及求解.通过模型设计出逐维线性插值法对风扇和CDFS的几何特性进行研究.利用阻尼牛顿迭代法对共同工作方程组进行求解.运用非线性规划约束优化算法对发动机的性能进行优化.然后通过数值仿真验证了提出的算法的有效性.     

A more accurate second-order polynomial metamodel using a pseudo-random number assignment strategy

The response surface metamodel is a useful sequential methodology for approximating the relationship between the input variables and the output response in computer simulation. Several strategies have been proposed to increase the accuracy of the estimation of the metamodel. In the current paper, we introduce an effective pseudo-random number (PRN) assignment strategy with Box-Behnken design to construct a more accurate second-order polynomial metamodel to estimate the network reliability of a complex system. The results obtained from the simulation approach show that the reduction in maximum absolute relative error between the response surface approximation and the actual reliability function is 35.63% after the PRN assignment strategy is applied.