Experimental investigation of stratified combustion: Application of laser diagnostic techniques

In order to better understand the stratified combustion, the propagation of flame through stratified mixture field in laminar and turbulent flow conditions has been studied by using combined PIV/PLIF techniques. A great emphasis was placed on developing methods to improve the accuracy of local measurements of flame propagation. In particular, a new PIV approach has been developed to measure the local fresh gas velocity near preheat zone of flame front. To improve the resolution of measurement, the shape of interrogation window has been continuously modified based on the local flame topology and gas expansion effect. Statistical analysis of conditioned local measurements by the local equivalence ratio of flames allows the characterization of the properties of flame propagation subjected to the mixture stratification in laminar and turbulent flows, especially the highlight of the memory effect.

Primary antibody deficiency and diagnostic delay.

AIMS: To assess the occurrence of diagnostic delay in primary antibody deficiency in the period 1989-2002, since a similar study in 1989, and to assess the impact of UK national guidelines communicated in 1995. METHODS: A retrospective case note review was performed of 89 consecutive patients with antibody deficiency referred to a regional referral centre for clinical immunology in north west England and north Wales. The delay in diagnosis and the estimated resulting morbidity in terms of infections were assessed. RESULTS: Fifty six of the 89 patients experienced delay in diagnosis. The overall median delay was 2 years (mean, 4.4), resulting in substantial morbidity (equivalent to two major infections and one minor infection). This shows a moderate improvement since the previous study in 1989 and since the introduction of UK national guidelines in 1995. Respiratory infections are the most frequent presenting infections, and respiratory physicians the most common source of referral. CONCLUSIONS: There is still considerable delay in the diagnosis of primary antibody deficiency, but the data suggest an improvement in practice since the previous study in 1989 and the distribution of national guidelines in 1995.

Flow field measurements of pulverized coal combustion using optical diagnostic techniques

This paper demonstrates the application of laser Doppler velocimetry (LDV) and particle image velocimetry (PIV) techniques to a particle-laden reacting flow of pulverized coal. A laboratory-scale open-type annular burner is utilized to generate velocity profiles of coal particles and micrometric alumina particles. Pair-wise two-component LDV measurements and high-speed stereo PIV measurements provide three-dimensional velocity components of the flow field. A detailed comparison of velocities for alumina and coal particle seeding revealed differences attributed to the wide size distribution of coal particles. In addition, the non-spherical shape and high flame luminosity associated with coal particle combustion introduces noise to the Mie scatter images. The comparison of mean and RMS velocities measured by LDV and PIV techniques showed that PIV measurements are affected by the wide size distribution of coal particles, whereas LDV measurements become biased toward the velocity of small particles, as signals from large particles are rejected. This small-particle bias is also reflected in the spectral characteristics for both techniques, which are in good agreement within the range of frequencies accessible. PIV measurements showed an expected lack of response of large coal particles to the turbulence fluctuations. The overall good agreement between LDV and PIV measurements demonstrates the applicability of the high-speed PIV technique to a particle-laden, high luminosity coal flame while highlighting some of its limitations. © 2013 Springer-Verlag Berlin Heidelberg.

Development of a time and space resolved sampling probe diagnostic for engine exhaust hydrocarbons

In order to understand how unburned hydrocarbons emerge from SI engines and, in particular, how non-fuel hydrocarbons are formed and oxidized, a new gas sampling technique has been developed. A sampling unit, based on a combination of techniques used in the Fast Flame Ionization Detector (FFID) and wall-mounted sampling valves, was designed and built to capture a sample of exhaust gas during a specific period of the exhaust process and from a specific location within the exhaust port. The sampling unit consists of a transfer tube with one end in the exhaust port and the other connected to a three-way valve that leads, on one side, to a FFID and, on the other, to a vacuum chamber with a high-speed solenoid valve. Exhaust gas, drawn by the pressure drop into the vacuum chamber, impinges on the face of the solenoid valve and flows radially outward. Once per cycle during a specified crank angle interval, the solenoid valve opens and traps exhaust gas in a storage unit, from which gas chromatography (GC) measurements are made. The port end of the transfer tube can be moved to different locations longitudinally or radially, thus allowing spatial resolution and capturing any concentration differences between port walls and the center of the flow stream. Further, the solenoid valve's opening and closing times can be adjusted to allow sampling over a window as small as 0.6 ms during any portion of the cycle, allowing resolution of a crank angle interval as small as 15°CA. Cycle averaged total HC concentration measured by the FFID and that measured by the sampling unit are in good agreement, while the sampling unit goes one step further than the FFID by providing species concentrations. Comparison with previous measurements using wall-mounted sampling valves suggests that this sampling unit is fully capable of providing species concentration information as a function of air/fuel ratio, load, and engine speed at specific crank angles. © Copyright 1996 Society of Automotive Engineers, Inc.

Integrating design attributes, knowledge and uncertainty in aerospace sector

The delivery of integrated product and service solutions is growing in the aerospace industry, driven by the potential of increasing profits. Such solutions require a life cycle view at the design phase in order to support the delivery of the equipment. The influence of uncertainty associated with design for services is increasingly a challenge due to information and knowledge constraints. There is a lack of frameworks that aim to define and quantify relationship between information and knowledge with uncertainty. Driven by this gap, the paper presents a framework to illustrate the link between uncertainty and knowledge within the design context for services in the aerospace industry. The paper combines industrial interaction and literature review to initially define the design attributes, the associated knowledge requirements and the uncertainties experienced. The framework is then applied in three cases through development of causal loop models (CLMs), which are validated by industrial and academic experts. The concepts and inter-linkages are developed with the intention of developing a software prototype. Future recommendations are also included. © 2014 CIRP.

Semantic transform: Weakly supervised semantic inference for relating visual attributes

Relative (comparative) attributes are promising for thematic ranking of visual entities, which also aids in recognition tasks. However, attribute rank learning often requires a substantial amount of relational supervision, which is highly tedious, and apparently impractical for real-world applications. In this paper, we introduce the Semantic Transform, which under minimal supervision, adaptively finds a semantic feature space along with a class ordering that is related in the best possible way. Such a semantic space is found for every attribute category. To relate the classes under weak supervision, the class ordering needs to be refined according to a cost function in an iterative procedure. This problem is ideally NP-hard, and we thus propose a constrained search tree formulation for the same. Driven by the adaptive semantic feature space representation, our model achieves the best results to date for all of the tasks of relative, absolute and zero-shot classification on two popular datasets. © 2013 IEEE.