The development of a CFD based simulator for water mist suppression systems: the development of the fire submodel

The FIRE Detection and Suppression Simulation (FIREDASS) project was concerned with the development of water misting systems as a possible replacement for halon based fire suppression systems currently used in aircraft cargo holds and ship engine rooms. As part of this program of work, a computational model was developed to assist engineers optimize the design of water mist suppression systems. The model is based on Computational Fluid Dynamics (CFD) and comprised of the following components: fire model; mist model; two-phase radiation model; suppression model; detector/activation model. In this paper the FIREDASS software package is described and the theory behind the fire and radiation sub-models is detailed. The fire model uses prescribed release rates for heat and gaseous combustion products to represent the fire load. Typical release rates have been determined through experimentation. The radiation model is a six-flux model coupled to the gas (and mist) phase. As part of the FIREDASS project, a detailed series of fire experiments were conducted in order to validate the fire model. Model predictions are compared with data from these experiments and good agreement is found.

Application of regularization methods to damage detection in large scale plane frame structures using incomplete noisy modal data

This paper presents an approach for detecting local damage in large scale frame structures by utilizing regularization methods for ill-posed problems. A direct relationship between the change in stiffness caused by local damage and the measured modal data for the damaged structure is developed, based on the perturbation method for structural dynamic systems. Thus, the measured incomplete modal data can be directly adopted in damage identification without requiring model reduction techniques, and common regularization methods could be effectively employed to solve the developed equations. Damage indicators are appropriately chosen to reflect both the location and severity of local damage in individual components of frame structures such as in brace members and at beam-column joints. The Truncated Singular Value Decomposition solution incorporating the Generalized Cross Validation method is introduced to evaluate the damage indicators for the cases when realistic errors exist in modal data measurements. Results for a 16-story building model structure show that structural damage can be correctly identified at detailed level using only limited information on the measured noisy modal data for the damaged structure.

Adaptive ordering for imperfect successive decision feedback multiuser detection

A method for selecting the order in which the users are detected in communication systems employing adaptive successive decision feedback multiuser detection is proposed. Systems employing channel coding without the assumption of perfect decision feedback are analyzed. The method is based on the mean squared error (MSE) measurements during a training period for each user. The analysis' shows that the method delivers BER performance improvement relative to other previously proposed ordering methods

Mixed-Function Oxygenases And Xenobiotic Detoxication-Toxication Systems In Bivalve Mollusks

Components of a xenobiotic detoxication/toxication system involving mixed function oxygenases are present inMytilus edulis. Our paper critically reviews the recent literature on this topic which reported the apparent absence of such a system in bivalve molluscs and attempts to reconcile this viewpoint with our own findings on NADPH neotetrazolium reductase, glucose-6-phosphate dehydrogenase, aldrin epoxidation and other reports of the presence of mixed function oxygenases. New experimental data are presented which indicate that some elements of the detoxication/toxication system inM. edulis can be induced by aromatic hydrocarbons derived from crude oil. This includes a brief review of the results of long-term experiments in which mussels were exposed to low concentrations of the water accommodated fraction of North Sea crude oil (7.7–68 µg 1−1) in which general stress responses such as reduced physiological scope for growth, cytotoxic damage to lysosomal integrity and cellular damage are considered as characteristics of the general stress syndrome induced by the toxic action of the xenobiotics. In addition, induction in the blood cells of microsomal NADPH neotetrazolium reductase (associated with mixed function oxygenases) and the NADPH generating enzyme glucose-6-phosphate dehydrogenase are considered to be specific biological responses to the presence of aromatic hydrocarbons. The consequences of this detoxication/toxication system forMytilus edulis are discussed in terms of the formation of toxic electrophilic intermediate metabolites which are highly reactive and can combine with DNA, RNA and proteins with subsequent damage to these cellular constituents. Implications for neoplasms associated with the blood cells are also discussed. Finally, in view of the increased use of mussel species in pollutant monitoring programmes, the induction phenomenon which is associated with microsomal enzymes in the blood cells is considered as a possible tool for the detection of the biological effects of environmental contamination by low concentrations of certain groups of organic xenobiotics.

Detection of Emerging and Re-Emerging Pathogens in Surface Waters Close to an Urban Area

Current knowledge about the spread of pathogens in aquatic environments is scarce probably because bacteria, viruses, algae and their toxins tend to occur at low concentrations in water, making them very difficult to measure directly. The purpose of this study was the development and validation of tools to detect pathogens in freshwater systems close to an urban area. In order to evaluate anthropogenic impacts on water microbiological quality, a phylogenetic microarray was developed in the context of the EU project µAQUA to detect simultaneously numerous pathogens and applied to samples from two different locations close to an urban area located upstream and downstream of Rome in the Tiber River. Furthermore, human enteric viruses were also detected. Fifty liters of water were collected and concentrated using a hollow-fiber ultrafiltration approach. The resultant concentrate was further size-fractionated through a series of decreasing pore size filters. RNA was extracted from pooled filters and hybridized to the newly designed microarray to detect pathogenic bacteria, protozoa and toxic cyanobacteria. Diatoms as indicators of the water quality status, were also included in the microarray to evaluate water quality. The microarray results gave positive signals for bacteria, diatoms, cyanobacteria and protozoa. Cross validation of the microarray was performed using standard microbiological methods for the bacteria. The presence of oral-fecal transmitted human enteric-viruses were detected using q-PCR. Significant concentrations of Salmonella, Clostridium, Campylobacter and Staphylococcus as well as Hepatitis E Virus (HEV), noroviruses GI (NoGGI) and GII (NoGII) and human adenovirus 41 (ADV 41) were found in the Mezzocammino site, whereas lower concentrations of other bacteria and only the ADV41 virus was recovered at the Castel Giubileo site. This study revealed that the pollution level in the Tiber River was considerably higher downstream rather than upstream of Rome and the downstream location was contaminated by emerging and re-emerging pathogens.

Nonlinear PCA with Local Approach for Diesel Engine Fault Detection and Diagnosis

This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.

Electrochemical ammonia gas sensing in nonaqueous systems: A comparison of propylene carbonate with room temperature ffonc liquids

First, the direct and indirect electrochemical oxidation of ammonia has been studied by cyclic voltammetry at glassy carbon electrodes in propylene carbonate. In the case of the indirect oxidation of ammonia, its analytical utility of indirect for ammonia sensing was examined in the range from 10 and 100 ppm by measuring the peak current of new wave resulting from reaction between ammonia and hydroquinone, as function of ammonia concentration, giving a sensitivity 1.29 x 10(-7) A ppm(-1) (r(2)=0.999) and limit-of-detection 5 ppm ammonia. Further, the direct oxidation of ammonia has been investigated in several room temperature ionic liquids (RTILs), namely 1-butyl-3-methylimidazolium tetrafluoroborate ([C(4)mim] [BF4]), 1-butyl-3-methylimiclazolium trifluoromethylsulfonate ([C4mim] [OTf]), 1-Ethyl -3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([C(2)mim] [NTf2]), 1-butyl-3-methylimidazolium bis(tritluoromethylsulfonyl)imide ([C4mim] [NTf2]) and 1-butyl-3-methylimidazolium hexafluorophosphate ([C4mim] [PF6]) on a 10 put diameter Pt microdisk electrode. In four of the RTILs studied, the cyclic voltammetric analysis suggests that ammonia is initially oxidized to nitrogen, N-2, and protons, which are transferred to an ammonia molecule, forming NH4+ via the protonation of the anion(s) (A(-)). However, in [C4mim] [PF6], the protonated anion was formed first, followed by NH4+. In all five RTILs, both HA and NH4+ are reduced at the electrode surface, forming hydrogen gas, which is then oxidized. The analytical ability of this work has also been explored further, giving a limit-of-detection close to 50 ppm in [C(2)mim] [NTf2], [C(4)mim] [OTf], [C(4)mim] [BF4], with a sensitivity of ca. 6 x 10(-7) A ppm(-1) (r(2) = 0.999) for all three ionic liquids, showing that the limit of detection was ca. ten times larger than that in propylene carbonate since ammonia in propylene carbonate might be more soluble in comparison with RTILs when considering the higher viscosity of RTILs.

The evolution of solar systems

The recent detection of extra-solar planets and the increasing ability of modern instruments to image discs around young stars has brought a renewed interest in the formation of solar systems. In this article, I shall briefly review what we know about extra-solar planets and the physical structure of protostellar discs. One of the most powerful means of studying these disc systems is to observe the rotational line emission from molecules which can give information on physics and dynamics. At present, the observations are relatively crude but future instruments should be able to resolve molecular structures in the disc around nearby stars. As a prelude to these observations, I discuss some conceptually simple, although numerically challenging, models of the physical and chemical processes involved in determining the molecular distributions.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

PLS modelling and fault detection on the Tennessee Eastman benchmark

This paper describes the application of multivariate regression techniques to the Tennessee Eastman benchmark process for modelling and fault detection. Two methods are applied : linear partial least squares, and a nonlinear variant of this procedure using a radial basis function inner relation. The performance of the RBF networks is enhanced through the use of a recently developed training algorithm which uses quasi-Newton optimization to ensure an efficient and parsimonious network; details of this algorithm can be found in this paper. The PLS and PLS/RBF methods are then used to create on-line inferential models of delayed process measurements. As these measurements relate to the final product composition, these models suggest that on-line statistical quality control analysis should be possible for this plant. The generation of `soft sensors' for these measurements has the further effect of introducing a redundant element into the system, redundancy which can then be used to generate a fault detection and isolation scheme for these sensors. This is achieved by arranging the sensors and models in a manner comparable to the dedicated estimator scheme of Clarke et al. 1975, IEEE Trans. Pero. Elect. Sys., AES-14R, 465-473. The effectiveness of this scheme is demonstrated on a series of simulated sensor and process faults, with full detection and isolation shown to be possible for sensor malfunctions, and detection feasible in the case of process faults. Suggestions for enhancing the diagnostic capacity in the latter case are covered towards the end of the paper.

A SuperWASP search for additional transiting planets in 24 known systems

We present results from a search for additional transiting planets in 24 systems already known to contain a transiting planet. We model the transits due to the known planet in each system and subtract these models from light curves obtained with the SuperWASP (Wide Angle Search for Planets) survey instruments. These residual light curves are then searched for evidence of additional periodic transit events. Although we do not find any evidence for additional planets in any of the planetary systems studied, we are able to characterize our ability to find such planets by means of Monte Carlo simulations. Artificially generated transit signals corresponding to planets with a range of sizes and orbital periods were injected into the SuperWASP photometry and the resulting light curves searched for planets. As a result, the detection efficiency as a function of both the radius and orbital period of any second planet is calculated. We determine that there is a good (>50 per cent) chance of detecting additional, Saturn-sized planets in P ~ 10 d orbits around planet-hosting stars that have several seasons of SuperWASP photometry. Additionally, we confirm previous evidence of the rotational stellar variability of WASP-10, and refine the period of rotation. We find that the period of the rotation is 11.91 +/- 0.05 d, and the false alarm probability for this period is extremely low (~10-13).