Role of large scale flow features on cycle-to-cycle variations of spark-ignited flame-initiation and its transition to turbulent combustion

This study investigates the influence of large-scale flow features, including flow structure and velocity magnitude, on the early-burn period variability in a homogenous-charge spark-ignited engine fueled with premixed propane-air mixture. Particle image velocimetry and in-cylinder pressure measurement data from a previous study - were processed to enable simultaneous flow characterization and flame-front tracking as well as apparent heat-release analysis. By combining probability analysis of flame development with conditional sampling of fast and slow early-burn cycles using 10% fuel mass fraction burned, it is shown that an undesirable flow structure produces an asymmetric flame development at the initial flame growth period. This asymmetric flame structure persists through the whole initial-to-turbulent transition period until the flame becomes fully turbulent. The undesirable flow condition is characterized by large-scale convective flows near spark plug rather than flows that lead to increased flame spread in multiple directions. The simultaneous flow and flame characterization enables the quantifications of flame-front propagation speed, unburned fuel-air mixture velocity ahead of flame front and local burning velocity at flame surface. Here the local burning velocity is referred to as laminar or turbulent flame speed. A simplified approach is introduced to derive integrated values for these quantities per crank-angle-degree, enabling the quantitative comparison of the trend-wise difference in these integrated metrics between fast and slow early-burn cycles. It is revealed that for the transition period, the CCV in the velocity magnitude of unburned fuel-air mixture ahead of the flame front accounts for nearly 50% to the variability of flame propagation speed. The burning velocity provides the remaining source of the flame propagation variability in this period. The flame propagation variations in the initial flame growth and fully turbulent periods are smaller than those in the transition period and are primarily dependent on the variability of large-scale flow features.     

Influence of the in-cylinder flow on cycle-to-cycle variations in lean combustion DISI engines measured by high-speed scanning-PIV

In this study, the influence of the three-dimensional (3D) in-cylinder flow on engine's cycle-to-cycle variations (CCV) in a spray-guided direct-injection spark-ignition engine is investigated. The engine is operated at homogeneous lean air–fuel mixture which enhances the sensitivity to CCV due to reduced laminar flame speed. To compensate this, intake velocity is increased by a tumble-flap (TF) in the intake-port. To address the 3D-nature of the temporal evolution of the instantaneous in-cylinder flow for different TF-positions, time-resolved scanning particle image velocimetry (Scanning-PIV) is applied to the engine. The required scan-frequency is provided by an acousto-optical-deflector (AOD) to measure the flow field quasi-simultaneously in the central tumble-plane and both mid-valve-planes. The three planes are 18?mm displaced from each other to capture the variability of the large-scale tumble vortex. The in-cylinder flow measurements are combined with combustion analyses by the in-cylinder pressure-trace and the detection of the location of ignition through the evaluation of the luminous spark-plasma. A correlation-map analysis is conducted to identify coherent flow features responsible for CCV of the combustion parameters. This reveals a strong dependency of the spark position to variations of an upward directed flow pointing onto the spark plug. The variations of the upward flow are due to strong CCV of the bended tumble-axis position. An increased tumble motion caused by the TF results in favorable flow conditions by stabilizing the tumble-axis in the middle of the cylinder which decreases the CCV of the spark position significantly. Further correlation analysis including the combustion process exhibits that flow-structures moving the spark and early flame kernel towards the cylinder center reduces the crank angle of 5% heat release and the combustion duration considerably.     

Neural network modeling of emotion

This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models.Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.     

Velocity measurement inside a motored internal combustion engine using three-component laser Doppler anemometry

A three-component laser Doppler anemometry (LDA) system has been employed to investigate the structure of the flow inside the cylinder of a motored internal combustion engine. This model engine was reasonably representative of a typical, single cylinder, spark ignition engine although it did not permit firing. It was equipped with overhead valve gear and optical access was provided in the top and side walls of the cylinder. A principal objective was to study the influence of the inlet port design on the flow within the cylinder during the induction and compression strokes of the engine. Here, it can be noted that results obtained in an unfired engine are believed to be representative of the flow behaviour before combustion occurs in a fired engine (see P.O. Witze, Measurements of the spatial distribution and engine speed dependence of turbulent air motion in an i.c. engine, SAE Paper No. 770220, 1977; Witze, Sandia Laboratory Energy Report, SAND 79-8685, Sandia Laboratories, USA, 1979). Experimental data presented for an inclined inlet port configuration reveal the complex three-dimensional nature of the flow inside the model engine cylinder. Not surprisingly, the results also show that the inclined inlet port created flow conditions more favourable to mixing in the cylinder. Specifically, the inclined inlet flow was found to generate a region with a relatively high shear and strong recirculation zones in the cylinder. Inclining the inlet port also produced a more nearly homogeneous flow structure at top dead centre during the compression stroke. The paper identifies the special difficulties encountered in making the LDA measurements. The experimental findings are examined and the problems that arise in presenting time-varying three-dimensional data of this type are discussed. Finally, the future potential of this experimental approach is explored.     

Geometrically qualified ESPI vibration analysis of an engine

This paper presents an application in the automotive industry where a combination of electronic speckle-pattern interferometry and laser doppler velocimetry were used at a critical stage in the design process of an internal combustion engine. Combined deformation and surface relief measurements were used to study the phase and amplitude of deformation of a vibrating engine. The relief data was combined with the interferometer geometry and used to geometrically correct the deformation data, in an effort to improve accuracy. The measurements allowed rapid identification and quantification of design weaknesses, particularly those causing undesirable resonances. This led to a significant reduction in the design time and lowering of costs, when compared with existing design optimisation methods.     

Neural networks for prediction of acoustical properties of polyurethane foams

This paper presents a study of neural networks for prediction of acoustical properties of polyurethane foams. The proposed neural network model of the foam uses easily measured parameters such as frequency, airflow resistivity and density to predict multiple acoustical properties including the sound absorption coefficient and the surface impedance. Such a model is quite robust in the sense that it can be used to develop models for many different classes of materials with different sets of input and output parameters. The current neural network model of the foam is empirical and provides a useful complement to the existing analytical and numerical approaches.     

Differences between PREMIER combustion in a natural gas spark-ignition engine and knocking with pressure oscillations

PREMIER (PREmixed Mixture Ignition in the End-gas Region) combustion occurs with auto-ignition in the end-gas region when the main combustion flame propagation is nearly finished. Auto-ignition is triggered by the increases in pressure and temperature induced by the main combustion flame. Similarly to engine knocking, heat is released in two stages when engines undergo this type of combustion. This pattern of heat release does not occur during normal combustion. However, engine knocking induces pressure oscillations that cause fatal damage to engines, whereas PREMIER combustion does not. The purpose of this study was to elucidate PREMIER combustion in natural gas spark-ignition engines, and differentiate the causes of knocking and PREMIER combustion. We applied combustion visualization and in-cylinder pressure analysis using a compression–expansion machine (CEM) to investigate the auto-ignition characteristics in the end-gas region of a natural gas spark-ignition engine. We occasionally observed knocking accompanied by pressure oscillations under the spark timings and initial gas conditions used to generate PREMIER combustion. No pressure oscillations were observed during normal and PREMIER combustion. Auto-ignition in the end-gas region was found to induce a secondary increase in pressure before the combustion flame reached the cylinder wall, during both knocking and PREMIER combustion. The auto-ignited flame area spread faster during knocking than during PREMIER combustion. This caused a sudden pressure difference and imbalance between the flame propagation region and the end-gas region, followed by a pressure oscillation.     

纹影技术在直喷式柴油机燃烧过程研究中的应用

本文叙述了作者所设计建立的高速纹影摄影光路系统,给出了利用该系统所拍摄的纹影照片,并通过照片简单分析了柴油机缸内的喷雾和燃烧过程。结果表明,纹影技术是研究发动机缸内空气运动和喷雾燃烧过程的有效手段。     

Acoustic time histories from vibrating surfaces of a diesel engine

An experiment on a diesel engine provides for validation of a method that retrieves source strength spectra, source strength time histories and sound pressure time histories of the engine’s complex partial sources. The method is based on empirical transfer function measurements and inverse matrix calculations briefly described in the article. Different simplifying source models were selected by comparison of calculated and measured auto spectra. The results show: (1) indication of time efficient measurements of source strength spectra, (2) the importance of correct source models in the case of separated source strength time histories, and (3) spectra of separated sound pressure time histories. Listening tests reported that it is possible to detect well differentiated sounds of the partial sources as a result of the method.     

LES of supersonic combustion in a scramjet engine model

In this study, Large Eddy Simulation (LES) has been used to examine supersonic flow and combustion in a model scramjet combustor. The LES model is based on an unstructured finite volume discretization, using total variational diminishing flux reconstruction, of the filtered continuity, momentum, enthalpy, and passive/reactive scalar equations, used to describe the combustion process. The configuration used is similar to the laboratory scramjet at the Institute for Chemical Propulsion of the German Aerospace Center (DLR) and consists of a one-sided divergent channel with a wedge-shaped flameholder at the base of which hydrogen is injected. Here, we investigate supersonic flow with hydrogen injection and supersonic flow with hydrogen injection and combustion. For the purpose of validation, the LES results are compared with experimental data for velocity and temperature at different cross-sections. In addition, qualitative comparisons are also made between predicted and measured shadowgraph images. The LES computations are capable of predicting both the non-reacting and reacting flowfields reasonably well—in particular we notice that the LES model identifies and differentiates between peculiarities of the flowfields found in the experiments.     

In situ sensor for cycle-resolved measurement of temperature and mole fractions in IC engine exhaust gases

We present a multi-species mole fraction and temperature sensor for in situ exhaust gas diagnostic of internal combustion (IC) engines. The sensor is based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) and incorporates four optical channels - two miniature White cells and two double-traversal cells - with base lengths of 6?cm. It has been demonstrated at a hot air test stand and in the exhaust manifold of a single-cylinder research engine, with measured temperatures of up to 1000?K. Stable operation was achieved with absorption lengths of up to 192?cm (test stand) and 97?cm (engine). Employing time-division multiplexed detection, six species were measured simultaneously in the engine exhaust, at wavelengths ranging from 1.4?µm to 5.2 µm: water vapor (H₂O), carbon dioxide (CO₂), carbon monoxide (CO), methane (CH₄), nitrogen dioxide (NO₂) and nitric oxide (NO). The effective measurement rate was as high as 1?kHz, and cycle-to-cycle variations were clearly detected. We show the correlation of the air-fuel equivalence ratio with the spectroscopically measured mole fraction of each species. At a cycle-resolved rate, detection limits for the legally regulated species NO and NO₂ were 1?ppm and 4?ppm, respectively. The sensor is intended to help improve the understanding of IC engine emission behavior during fast transients.     

A feasibility study of dynamic stress analysis inside a running internal combustion engine using synchrotron X‐ray beams

The present investigation establishes the feasibility of using synchrotron‐generated X‐ray beams for time‐resolved in situ imaging and diffraction of the interior components of an internal combustion engine during its operation. The demonstration experiment was carried out on beamline I12 (JEEP) at Diamond Light Source, UK. The external hutch of the JEEP instrument is a large‐scale engineering test bed for complex in situ processing and simulation experiments. The hutch incorporates a large capacity translation and rotation table and a selection of detectors for monochromatic and white‐beam diffraction and imaging. These capabilities were used to record X‐ray movies of a motorcycle internal combustion engine running at 1850 r.p.m. and to measure strain inside the connecting rod via stroboscopic X‐ray diffraction measurement. The high penetrating ability and high flux of the X‐ray beam at JEEP allowed the observation of inlet and outlet valve motion, as well as that of the piston, connecting rod and the timing chain within the engine. Finally, the dynamic internal strain within the moving connecting rod was evaluated with an accuracy of ～50 × 10^?6.     

Combustion parameters identification and correction in diesel engine via vibration acceleration signal

Using closed loop control of the internal combustion engine is beneficial to reducing emission and fuel consumption. Accurate combustion parameters are the foundation of effective closed loop control. Some combustion parameters, including the start of combustion, the location of maximum pressure rise rate and the location of peak pressure can be identified from the vibration signals. Empirical Mode Decomposition (EMD) method is introduced to reconstruct the vibration acceleration signal, from which the combustion parameters are identified. However, there are angle deviations between the combustion parameters extracted from the reconstructed vibration acceleration signal and those from the cylinder pressure. Algorithms to correct the angle deviations are introduced. A system deviation value is used to correct the extracted start of combustion with an error bound being within 0.6 °CA. Two algorithms are proposed to correct the deviation between the predicted location of maximum pressure rise rate and that from the cylinder pressure. Test results show that the two algorithms are able to correct the deviation within 0.3 °CA error bound. The location of peak pressure can be predicted with the knee point following the peak value in the reconstructed vibration acceleration signal. The predicted result is then corrected using a linear regression of the location of peak pressure versus the knee point within 0.5 °CA error bound. A real-time monitoring framework is utilized for calculating the combustion parameter prediction.     

Synchronization regimes in a map-based model neural network

The dynamical activity of a neural network model composed of electrically connected map-based neurons is investigated. After detailing the behavior of the isolated neuron for a wide parameter range, collective network states are depicted using the activity, spatial correlation and time phase distribution as measures. A detailed discussion on the stability of global and partial synchronization states is presented.     

Monofractal and multifractal analysis of simulated heat release fluctuations in a spark ignition heat engine

We study data from cycle-by-cycle variations in heat release for a simulated spark-ignited engine. Our analyses are based on nonlinear scaling properties of heat release fluctuations obtained from a turbulent combustion model. We apply monofractal and multifractal methods to characterize the fluctuations for several fuel-air ratio values, ?, from lean mixtures to stoichiometric situations. The monofractal approach reveals that, for lean and stoichiometric conditions, the fluctuations are characterized by the presence of weak anticorrelations, whereas for intermediate mixtures we observe complex dynamics characterized by a crossover in the scaling exponents: for short scales, the variations display positive correlations while for large scales the fluctuations are close to white noise. Moreover, a broad multifractal spectrum is observed for intermediate fuel ratio values, while for low and high ? the fluctuations lead to a narrow spectrum. Finally, we explore the origin of correlations by using the surrogate data method to compare the findings of multifractality and scaling exponents between original simulated and randomized data.     

Application and theoretical analysis of the flamelet model for supersonic turbulent combustion flows in the scramjet engine

In the framework of Reynolds-averaged Navier–Stokes simulation, supersonic turbulent combustion flows at the German Aerospace Centre (DLR) combustor and Japan Aerospace Exploration Agency (JAXA) integrated scramjet engine are numerically simulated using the flamelet model. Based on the DLR combustor case, theoretical analysis and numerical experiments conclude that: the finite rate model only implicitly considers the large-scale turbulent effect and, due to the lack of the small-scale non-equilibrium effect, it would overshoot the peak temperature compared to the flamelet model in general. Furthermore, high-Mach-number compressibility affects the flamelet model mainly through two ways: the spatial pressure variation and the static enthalpy variation due to the kinetic energy. In the flamelet library, the mass fractions of the intermediate species, e.g. OH, are more sensible to the above two effects than the main species such as H₂O. Additionally, in the combustion flowfield where the pressure is larger than the value adopted in the generation of the flamelet library or the conversion from the static enthalpy to the kinetic energy occurs, the temperature obtained by the flamelet model without taking compressibility effects into account would be undershot, and vice versa. The static enthalpy variation effect has only little influence on the temperature simulation of the flamelet model, while the effect of the spatial pressure variation may cause relatively large errors. From the JAXA case, it is found that the flamelet model cannot in general be used for an integrated scramjet engine. The existence of the inlet together with the transverse injection scheme could cause large spatial variations of pressure, so the pressure value adopted for the generation of a flamelet library should be fine-tuned according to a pre-simulation of pure mixing.     

Ordered bursting synchronization and complex wave propagation in a ring neuronal network

Ordered bursting synchronization and complex propagation are investigated for a ring neuronal network in which each neuron exhibits chaotic bursting behaviour. The neurons become more and more synchronous in chaotic bursting as the synaptic strength is increased. It is shown that excitatory chemical synapses can effectively tame the chaos, and ordered bursting synchronization can be observed as the synaptic strength is further increased. However, synchronization among neurons is weakened as the number of neurons is increased. More importantly, it is shown that ordered bursting synchronization can be turned into spiking synchronization at certain noise intensity. Complex spatio-temporal patterns propagating towards both sides of pacemaker are found in this network before the emergence of spiking synchronization.     

Numerical simulation and validation of SI-CAI hybrid combustion in a CAI/HCCI gasoline engine

SI-CAI hybrid combustion, also known as spark-assisted compression ignition (SACI), is a promising concept to extend the operating range of CAI (Controlled Auto-Ignition) and achieve the smooth transition between spark ignition (SI) and CAI in the gasoline engine. In this study, a SI-CAI hybrid combustion model (HCM) has been constructed on the basis of the 3-Zones Extended Coherent Flame Model (ECFM3Z). An ignition model is included to initiate the ECFM3Z calculation and induce the flame propagation. In order to precisely depict the subsequent auto-ignition process of the unburned fuel and air mixture independently after the initiation of flame propagation, the tabulated chemistry concept is adopted to describe the auto-ignition chemistry. The methodology for extracting tabulated parameters from the chemical kinetics calculations is developed so that both cool flame reactions and main auto-ignition combustion can be well captured under a wider range of thermodynamic conditions. The SI-CAI hybrid combustion model (HCM) is then applied in the three-dimensional computational fluid dynamics (3-D CFD) engine simulation. The simulation results are compared with the experimental data obtained from a single cylinder VVA engine. The detailed analysis of the simulations demonstrates that the SI-CAI hybrid combustion process is characterised with the early flame propagation and subsequent multi-site auto-ignition around the main flame front, which is consistent with the optical results reported by other researchers. Besides, the systematic study of the in-cylinder condition reveals the influence mechanism of the early flame propagation on the subsequent auto-ignition.     

Active noise control in a duct by an analog neural network circuit

Conventional active noise control (ANC) in ducts has been realized with digital signal processing. The physical size of the conventional ANC systems is usually large owing to the signal processing interval, and the cost of the system depends on the price of the digital signal processor (DSP). This paper proposes a new ANC system with an analog neural network circuit, which will process signals in short time periods without DSP. The proposed neural network circuit has a simple structure consisting of analog multipliers and an integrator, and we simulated the performance of the circuit by HSPICE. We also fabricated a circuit connected to a real duct and confirmed operation of the proposed ANC system.