Influence of iodine value on combustion and NOx emission characteristics of a DI diesel engine

Biodiesel is a renewable fuel that has been shown to reduce many exhaust emissions, except oxides of nitrogen (NOx), in diesel engine cars. This is of special concern in inner urban areas that are subject to strict environmental regulations, such as EURO norms. Also, the use of pure biodiesel (B100) is inhibited because of its higher NOx emissions compared to petroleum diesel fuel. The aim of this present work is to investigate the effect of the iodine value and cetane number of various biodiesel fuels obtained from different feed stocks on the combustion and NOx emission characteristics of a direct injection (DI) diesel engine. The biodiesel fuels were chosen from various feed stocks such as coconut, palm kernel, mahua (Madhuca indica), pongamia pinnata, jatropha curcas, rice bran, and sesame seed oils. The experimental results show an approximately linear relationship between iodine value and NOx emissions. The biodiesels obtained from coconut and palm kernel showed lower NOx levels than diesel, but other biodiesels showed an increase in NOx. It was observed that the nature of the fatty acids of the biodiesel fuels had a significant influence on the NOx emissions. Also, the cetane numbers of the biodiesel fuels are affected both premixed combustion and the combustion rate, which further affected the amount of NOx formation. It was concluded that NOx emissions are influenced by many parameters of biodiesel fuels, particularly the iodine value and cetane number.

Le infrastrutture viarie dismesse o declassate ed il progetto di paesaggio

Paesaggio ed infrastrutture viarie sono un binomio molto forte: il primo ha insito il concetto di accessibilità, in quanto non può esistere senza la presenza di un osservatore; la strada, invece, trova i fattori che la connotano nel suo rapporto con la morfologia su cui insiste. Le infrastrutture viarie sono elemento strutturale e strutturante non solo di un territorio, ma anche di un paesaggio. Le attuali esigenze di mobilità portano oggi a ripensare ed adeguare molte infrastrutture viarie: laddove è possibile si potenziano le strutture esistenti, in diversi casi si ricorre a nuovi tracciati o a varianti di percorso. Porsi il problema di conservare itinerari testimoni della cultura materiale ed economica di una società implica considerazioni articolate, che travalicano i limiti del sedime: una via è un organismo più complesso della semplice linea di trasporto in quanto implica tutta una serie di manufatti a supporto della mobilità e soprattutto il corridoio infrastrutturale che genera e caratterizza, ovvero una porzione variabile di territorio definita sia dal tracciato che dalla morfologia del contesto. L’evoluzione dei modelli produttivi ed economici, che oggi porta quote sempre maggiori di popolazione a passare un tempo sempre minore all’interno del proprio alloggio, rende la riflessione sulle infrastrutture viarie dismesse o declassate occasione per la progettazione di spazi per l’abitare collettivo inseriti in contesti paesaggistici, tanto urbani che rurali, tramite reti di percorsi pensate per assorbire tagli di mobilità specifici e peculiari. Partendo da queste riflessioni la Tesi si articola in: Individuazioni del contesto teorico e pratico: Lo studio mette in evidenza come la questione delle infrastrutture viarie e del loro rapporto con il paesaggio implichi riflessioni incrociate a diversi livelli e tramite diverse discipline. La definizione dello spazio fisico della strada passa infatti per la costruzione di un itinerario, un viaggio che si appoggia tanto ad elementi fisici quanto simbolici. La via è un organismo complesso che travalica il proprio sedime per coinvolgere una porzione ampia di territorio, un corridoio variabile ed articolato in funzione del paesaggio attraversato. Lo studio propone diverse chiavi di lettura, mettendo in luce le possibili declinazioni del tema, in funzione del taglio modale, del rapporto con il contesto, del regime giuridico, delle implicazioni urbanistiche e sociali. La mobilità dolce viene individuata quale possibile modalità di riuso, tutela e recupero, del patrimonio diffuso costituito dalle diversi reti di viabilità. Antologia di casi studio: Il corpo principale dello studio si basa sulla raccolta, analisi e studio dello stato dell’arte nel settore; gli esempi raccolti sono presentati in due sezioni: la prima dedicata alle esperienze più significative ed articolate, che affrontano il recupero delle infrastrutture viarie a più livelli ed in modo avanzato non concentrandosi solo sulla conversione del sedime, ma proponendo un progetto che coinvolga tutto il corridoio attraversato dall’infrastruttura; la seconda parte illustra la pratica corrente nelle diverse realtà nazionali, ponendo in evidenza similitudini e differenze tra i vari approcci.

Markov modelling of the IEEE 802.11 DCF for real-time applications with periodic traffic

Popular wireless network standards, such as IEEE 802.11/15/16, are increasingly adopted in real-time control systems. However, they are not designed for real-time applications. Therefore, the performance of such wireless networks needs to be carefully evaluated before the systems are implemented and deployed. While efforts have been made to model general wireless networks with completely random traffic generation, there is a lack of theoretical investigations into the modelling of wireless networks with periodic real-time traffic. Considering the widely used IEEE 802.11 standard, with the focus on its distributed coordination function (DCF), for soft-real-time control applications, this paper develops an analytical Markov model to quantitatively evaluate the network quality-of-service (QoS) performance in periodic real-time traffic environments. Performance indices to be evaluated include throughput capacity, transmission delay and packet loss ratio, which are crucial for real-time QoS guarantee in real-time control applications. They are derived under the critical real-time traffic condition, which is formally defined in this paper to characterize the marginal satisfaction of real-time performance constraints.

Assetti proprietari e meccanismi di governance nelle imprese familiari [Finacial reporting in small family firms : searching for a new framework]

SOMMARIO: 1. La “governance” nelle aziende familiari: rilevanza, aspetti distintivi e criticità. 2. Il ruolo della compagine proprietaria nella definizione dei meccanismi di governo. 3. Composizione e funzioni del consiglio d’amministrazione. 4. I patti di famiglia come strumento di disciplina dei rapporti impresa-famiglia. 5. Considerazioni conclusive: prospettive di analisi e scenari futuri negli studi sulla governance delle imprese familiari.

L'informativa di bilancio nelle imprese familiari di piccole dimensioni : caratteri distintivi e aspetti evolutivi

SOMMARIO: 1. I fattori che incidono sulla funzione informativa del bilancio nelle imprese familiari. 2. Funzione, obiettivi e attese informative nella comunicazione esterna delle imprese familiari. 3. I caratteri del “familismo” nei prospetti di bilancio. 4. Verso un nuovo modello di bilancio per le imprese familiari: riflessioni critiche e spunti per la ricerca.

Remaining useful life prediction using elliptical basis function network and Markov Chain

This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

Multivariate Markov Process Models for the transmission of methicillin-resistant Staphylococcus Aureus in a hospital ward

Methicillin-resistant Staphylococcus Aureus (MRSA) is a pathogen that continues to be of major concern in hospitals. We develop models and computational schemes based on observed weekly incidence data to estimate MRSA transmission parameters. We extend the deterministic model of McBryde, Pettitt, and McElwain (2007, Journal of Theoretical Biology 245, 470–481) involving an underlying population of MRSA colonized patients and health-care workers that describes, among other processes, transmission between uncolonized patients and colonized health-care workers and vice versa. We develop new bivariate and trivariate Markov models to include incidence so that estimated transmission rates can be based directly on new colonizations rather than indirectly on prevalence. Imperfect sensitivity of pathogen detection is modeled using a hidden Markov process. The advantages of our approach include (i) a discrete valued assumption for the number of colonized health-care workers, (ii) two transmission parameters can be incorporated into the likelihood, (iii) the likelihood depends on the number of new cases to improve precision of inference, (iv) individual patient records are not required, and (v) the possibility of imperfect detection of colonization is incorporated. We compare our approach with that used by McBryde et al. (2007) based on an approximation that eliminates the health-care workers from the model, uses Markov chain Monte Carlo and individual patient data. We apply these models to MRSA colonization data collected in a small intensive care unit at the Princess Alexandra Hospital, Brisbane, Australia.

An infrared study of adsorption of paranitrophenol on mono, di and trialkyl surfactant intercalated organoclays

Infrared spectroscopy has been used to study the adsorption of paranitrophenol on mono, di and tri alkyl surfactant intercalated montmorillonite. Organoclays were obtained by the cationic exchange of mono, di and tri alkyl chain surfactants for sodium ions [hexadecyltrimethylammonium bromide (HDTMAB), dimethyldioctadecylammonium bromide (DDOAB), methyltrioctadecylammonium bromide (MTOAB)] in an aqueous solution with Na-montmorillonite. Upon formation of the organoclay, the properties change from strongly hydrophilic to strongly hydrophobic. This change in surface properties is observed by a decrease in intensity of the OH stretching vibrations assigned to water in the cation hydration sphere of the montmorillonite. As the cation is replaced by the surfactant molecules the paranitrophenol replaces the surfactant molecules in the clay interlayer. Bands attributed to CH stretching and bending vibrations change for the surfactant intercalated montmorillonite. Strong changes occur in the HCH deformation modes of the methyl groups of the surfactant. These changes are attributed to the methyl groups locking into the siloxane surface of the montmorillonite. Such a concept is supported by changes in the SiO stretching bands of the montmorillonite siloxane surface. This study demonstrates that paranitrophenol will penetrate into the untreated clay interlayer and replace the intercalated surfactant in surfactant modified clay, resulting in the change of the arrangement of the intercalated surfactant.

Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.

Poly[di-mu-aqua-bis(mu-2-amino-4-nitrobenzoato)dicaesium]

In the structure of title compound [Cs2(C7H5N2O4)2(H2O)2]n the asymmetric unit comprises two independent and different Cs centres, one nine-coordinate, the other seven coordinate, with both having irregular stereochemistry. The CsO9 coordination comprises oxygen donors from three bridging water molecules, one of which is doubly bridging, three from carboxylate groups, and three from nitro groups, of which two are bidentate chelate bridging. The CsO6N coordination comprises the two bridging water molecules, one amine N donor, one carboxyl O donor and four O donors from nitro groups (two from the chelate bridges). The extension of the dimeric unit gives a two-dimensional polymeric structure which is stabilized by both intra- and intermolecular amine N-H...O and water O-H...O hydrogen bonds to carboxyl O acceptors, as well as inter-ring pi-pi interactions [minimum ring centroid separation, 3.4172(15)A].

A Python package for Bayesian estimation using Markov Chain Monte Carlo

Markov chain Monte Carlo (MCMC) estimation provides a solution to the complex integration problems that are faced in the Bayesian analysis of statistical problems. The implementation of MCMC algorithms is, however, code intensive and time consuming. We have developed a Python package, which is called PyMCMC, that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood of coding error, as well as aid in the minimisation of repetitive code. PyMCMC contains classes for Gibbs, Metropolis Hastings, independent Metropolis Hastings, random walk Metropolis Hastings, orientational bias Monte Carlo and slice samplers as well as specific modules for common models such as a module for Bayesian regression analysis. PyMCMC is straightforward to optimise, taking advantage of the Python libraries Numpy and Scipy, as well as being readily extensible with C or Fortran.

Bounded parameter Markov Decision Processes with average reward criterion

Bounded parameter Markov Decision Processes (BMDPs) address the issue of dealing with uncertainty in the parameters of a Markov Decision Process (MDP). Unlike the case of an MDP, the notion of an optimal policy for a BMDP is not entirely straightforward. We consider two notions of optimality based on optimistic and pessimistic criteria. These have been analyzed for discounted BMDPs. Here we provide results for average reward BMDPs. We establish a fundamental relationship between the discounted and the average reward problems, prove the existence of Blackwell optimal policies and, for both notions of optimality, derive algorithms that converge to the optimal value function.