Comparative analysis of alternative fuels in detonation combustion

Detonation combustion prominently exhibits high thermodynamic efficiency which leads to better performance. As compared to the conventionally used isobaric heat addition in a Brayton cycle combustor, detonation uses a novel isochoric Humphrey cycle which utilises shocks and detonation waves to provide pressure-rise combustion. Such unsteady combustion has already been explored in wave rotor, pulse detonation engine and rotating detonation engine configurations as alternative technologies for the next generation of the aerospace propulsion systems. However, in addition to the better performance that the detonation mode of combustion offers, it is crucial to observe the environmental concerns as well. Therefore, this paper presents a one-dimensional numerical analysis for alternative fuels: Jet-A, Acetylene, Jatropha Bio-synthetic Paraffinic Kerosene, Camelina Bio-synthetic Paraffinic Kerosene, Algae Biofuel, and Microalgae Biofuel under detonation combustion conditions. For simplicity, the analysis is modelled using an open tube geometry. The analysis employs the Rankine-Hugoniot Equation, Rayleigh Line Equation, and Zel’dovich–von Neumann–Doering model and takes into account species mole, mass fraction, and enthalpies-of-formation of the reactants. Initially, minimum conditions for the detonation of each fuel are determined. Pressure, temperature, and density ratios at each stage of the combustion tube for different types of fuel are then explored systematically. Finally, the influence of different initial conditions is numerically examined to make a comparison for these fuels

A multifidelity multiobjective optimization framework for high-lift airfoils

High-lift devices design is a challenging task as it involves highly complex flow features while being critical for the overall performance of the aircraft. When part of an optimization loop, the computational cost of the Computational Fluid Dynamics becomes increasingly problematic. Methods to reduce the optimization time has been of major interest over the last 50 years. This paper presents a multiobjective multifidelity optimization framework that takes advantage of two approximation levels of the flow equations: a rapid method that provides quick estimates but of relatively low accuracy and a reference method that provides accurate estimations at the cost of a longer run-time. The method uses a sub-optimization, under a trust-region scheme, performed on the low-fidelity model corrected by a surrogate model that is fed by the high-fidelity tool. The size of the trust region is changed according to the accuracy of the corrected model. The multiobjective optimizer is used to set the positions of the ap and slat of a two-dimensional geometry with lift and drag as objectives with an empirical-based method and a Reynolds Averaged Navier-Stokes equations solver. The multifidelity method shows potential for discovering the complete Pareto front, yet it remains less optimal than the Pareto front from the high-fidelity-only optimization

Wall-resolved large eddy simulation over NACA0012 airfoil

The work presented here forms part of a project on Large-Eddy Simulation (LES) of aeroengine aeroacoustic interactions. In this paper we concentrate on LES of near-field flow over an isolated NACA0012 airfoil at zero angle of attack with Rec=2e5. The predicted unsteady pressure/velocity field is used in an analytically-based scheme for far-field trailing edge noise prediction. A wall resolved implicit LES or so-callednumerical Large Eddy Simulation (NLES) approach is employed to resolve streak-like structure in the near-wall flow regions. The mean and RMS velocity and pressure profile on airfoil surface and in wake are validated against experimental data and computational results from other researchers. The results of the wall-resolved NLES method are very encouraging. The effects of grid-refinement and higher-order numerical scheme on the wall-resolved NLES approach are also discussed

Effects of biofuels properties on aircraft engine performance

Purpose-The purpose of this paper is to examine the effects of heat capacity and density of biofuels on aircraft engine performance indicated by thrust and fuel consumption. Design/methodology/approach-The influence of heat capacity and density was examined by simulating biofuels in a two-spool high-bypass turbofan engine running at cruise condition using a Cranfield in-house engine performance computer tool (PYTHIA). The effect of heat capacity and density on engine performance was evaluated through a comparison between kerosene and biofuels. Two types of biofuels were considered: Jatropha Bio-synthetic Paraffinic Kerosene (JSPK) and Camelina Bio-synthetic Paraffinic Kerosene (CSPK). Findings-Results show an increase in engine thrust and a reduction in fuel consumption as the percentage of biofuel in the kerosene/biofuel mixture increases. Besides a low heating value, an effect of heat capacity on increasing engine thrust and an effect of density on reducing engine fuel consumption are observed. Practical implications-The utilisation of biofuel in aircraft engines may result in reducing over-dependency on crude oil. Originality/value-This paper observes secondary factors (heat capacity and density) that may influence aircraft engine performance which should be taken into consideration when selecting new fuel for new engine designs

Electrical power grid network optimisation by evolutionary computing

A major factor in the consideration of an electrical power network of the scale of a national grid is the calculation of power flow and in particular, optimal power flow. This paper considers such a network, in which distributed generation is used, and examines how the network can be optimized, in terms of transmission line capacity, in order to obtain optimal or at least high-performing configurations, using multi-objective optimisation by evolutionary computing methods

Integrated system to perform surrogate based aerodynamic optimisation for high-lift airfoil

This work deals with the aerodynamics optimisation of a generic two-dimensional three element high-lift configuration. Although the high-lift system is applied only during take-off and landing in the low speed phase of the flight the cost efficiency of the airplane is strongly influenced by it [1]. The ultimate goal of an aircraft high lift system design team is to define the simplest configuration which, for prescribed constraints, will meet the take-off, climb, and landing requirements usually expressed in terms of maximum L/D and/or maximum CL. The ability of the calculation method to accurately predict changes in objective function value when gaps, overlaps and element deflections are varied is therefore critical. Despite advances in computer capacity, the enormous computational cost of running complex engineering simulations makes it impractical to rely exclusively on simulation for the purpose of design optimisation. To cut down the cost, surrogate models, also known as metamodels, are constructed from and then used in place of the actual simulation models. This work outlines the development of integrated systems to perform aerodynamics multi-objective optimisation for a three-element airfoil test case in high lift configuration, making use of surrogate models available in MACROS Generic Tools, which has been integrated in our design tool. Different metamodeling techniques have been compared based on multiple performance criteria. With MACROS is possible performing either optimisation of the model built with predefined training sample (GSO) or Iterative Surrogate-Based Optimization (SBO). In this first case the model is build independent from the optimisation and then use it as a black box in the optimisation process. In the second case is needed to provide the possibility to call CFD code from the optimisation process, and there is no need to build any model, it is being built internally during the optimisation process. Both approaches have been applied. A detailed analysis of the integrated design system, the methods as well as th

Modelling of spray evaporation and penetration for alternative fuels

The focus of this work is on the modelling of evaporation and spray penetration for alternative fuels. The extension model approach is presented and validated for alternative fuels, namely, Kerosene (KE), Ethanol (ETH), Methanol (MTH), Microalgae biofuel (MA), Jatropha biofuel (JA), and Camelina biofuel (CA). The results for atomization and spray penetration are shown in a time variant condition. Comparisons have been made to visualize the transient behaviour of these fuels. The vapour pressure tendencies are revealed to have significant effects on the transient shape of the evaporation process. In a given time frame, ethanol fuel exhibits the highest evaporation rate and followed by methanol, other biofuels and kerosene. Ethanol also propagates the farthest distance and followed by methanol and kerosene. However, all biofuels have a shorter penetration length in the given time. These give penalty costs to biofuels emissions formation. The influences of initial conditions such as temperature and droplet velocity are also explored numerically. High initial temperature and velocity could accelerate evaporation rate. However, high initial temperature has resulted in low penetration length while high initial velocity produces contrasting results

The impact, assessment, and longitudinal course of negative symptoms of schizophrenia.

PhDThe negative symptoms of schizophrenia include impoverished speech, affective blunting, an inability to anticipate pleasure, asociality, and amotivation. Current effective treatment options are limited, which is a significant issue given their strong association to functional impairment. The primary aims of this thesis are to explore areas which may inform the design of clinical trials addressing these symptoms, build upon recent advances in negative symptom assessment, and further understand the impact of negative symptoms on outcomes. A meta-analysis examining the longitudinal course of negative symptoms demonstrated a consistent reduction in negative symptoms over the study period in all treatment conditions examined, including in studies which adopted different eligibility criteria to minimise the presence of secondary negative symptoms. A comparison of different eligibility criteria revealed that whilst these criteria reduce the association between negative and depressive symptoms, their association to positive symptoms remains largely unaffected, and can substantially reduce the proportion of available participants. Given existing negative symptom assessment tools have been identified as a significant barrier in the development of new treatments, a comparison of assessment methods was performed. Results revealed the Clinical Assessment Interview for Negative Symptoms to be a more sensitive instrument, and a better predictor of functional impairments, relative to the negative subscale of the Positive and Negative Syndrome Scale. Findings described here also demonstrate that the link between negative symptoms and subjective quality of life may be stronger than previously assumed, relating exclusively to experiential deficits. Finally, manic and positive symptoms, rather than negative symptoms, were found to be associated with inpatient treatment appraisal, an important factor in treatment outcomes. Overall, this thesis describes key findings which demonstrate the importance of the appropriate assessment of negative symptoms of schizophrenia, shine new light on symptom progression over time, and highlight a need to further refine clinical trial inclusion criteri

Surrogate modelling for wing planform multidisciplinary optimisation using model-based engineering

Optimisation is aimed at enhancing aircraft design by identifying the most promising wing planforms at the early stage while discarding the least performing ones. Multiple disciplines must be taken into account when assessing new wing planforms, and a model-based framework is proposed as a way to include mass estimation and longitudinal stability alongside aerodynamics. Optimisation is performed with a particle swarm optimiser, statistical methods are exploited for mass estimation, and the vortex lattice method (VLM) with empirical corrections for transonic flow provides aerodynamic performance. Three surrogates of the aerodynamic model are investigated. The first one is based on radial basis function (RBF) interpolation, and it relies on a precomputed database to evaluate the performance of new wing planforms. The second one is based on an artificial neural network, and it needs precomputed data for a training step. The third one is a hybrid model which switches automatically between VLM and RBF, and it does not need any precomputation. Its switching criterion is defined in an objective way to avoid any arbitrariness. The investigation is reported for a test case based on the common research model (CRM). Reference results are produced with the aerodynamic model based on VLM for two- and three-objective optimisations. Results from all surrogate models for the same benchmark optimisation are compared so that their benefits and limitations are both highlighted. A discussion on specific parameters, such as number of samples for example, is given for each surrogate. Overall, a model-based implementation with a hybrid model is proposed as a compromise between versatility and an arbitrary level of accuracy for wing early-stage design