Exploiting a priori time constant ratio information in difference equation two-thermocouple sensor characterisation

The characterization of thermocouple sensors for temperature measurement in varying-flow environments is a challenging problem. Recently, the authors introduced novel difference-equation-based algorithms that allow in situ characterization of temperature measurement probes consisting of two-thermocouple sensors with differing time constants. In particular, a linear least squares (LS) lambda formulation of the characterization problem, which yields unbiased estimates when identified using generalized total LS, was introduced. These algorithms assume that time constants do not change during operation and are, therefore, appropriate for temperature measurement in homogenous constant-velocity liquid or gas flows. This paper develops an alternative ß-formulation of the characterization problem that has the major advantage of allowing exploitation of a priori knowledge of the ratio of the sensor time constants, thereby facilitating the implementation of computationally efficient algorithms that are less sensitive to measurement noise. A number of variants of the ß-formulation are developed, and appropriate unbiased estimators are identified. Monte Carlo simulation results are used to support the analysis.

Acoustic, volumetric, compressibility and refractivity properties and reduction parameters for the ERAS and Flory models of some homologous series of amines from 298.15 to 328.15 K

The speeds of sound u, densities ? and refractive indices nD of homologous series of mono-, di-, and tri-alkylamines were measured in the temperature range from 298.15 to 328.15 K. Isentropic and isothermal compressibilities ?S and ?T, molar refraction Rm, Eykman’s constant Cm, Rao’s molar sound function R, thermal expansion coefficient a, thermal pressure coefficient ?, and reduction parameters P*, V*, and T* in frameworks of the ERAS model for associated amines and Flory model for tertiary amines have been calculated from the measured experimental data. Applicability of the Rao theory and the ERAS and Flory models have been examined and discussed for the alkyl amines.

Physicochemical characterization of bioactive polyacrylic acid organogels as potential antimicrobial implants for the buccal cavity

This study describes the formulation and physicochemical characterization of poly(acrylic acid) (PAA) organogels, designed as bioactive implants for improved treatment of infectious diseases of the oral cavity. Organogels were formulated containing a range of concentrations of PAA (3-10% w/w) and metronidazole (2 or 5% w/w, representing a model antimicrobial agent) in different nonaqueous solvents, namely, glycerol (Gly), polyethylene glycol (PEG 400), or propylene glycol (PG). Characterization of the organogels was performed using flow rheometry, compressional analysis, oscillatory rheometry, in vitro mucoadhesion, moisture uptake, and drug release, methods that provide information pertaining to the nonclinical and clinical use of these systems. Increasing the concentration of PAA significantly increased the consistency, compressibility, storage modulus, loss modulus, dynamic viscosity, mucoadhesion, and the rate of drug release. These observations may be accredited to enhanced molecular polymer entanglement. In addition, the choice of solvent directly affected the physicochemical parameters of the organogels, with noticeable differences observed between the three solvents examined. These differences were accredited to the nature of the interaction of PAA with each solvent and, importantly, the density of the resultant physical cross-links. Good correlation was observed between the viscoelastic properties and drug release, with the exception of glycerol-based formulations containing 5 and 10% w/w PAA. This disparity was due to excessive swelling during the dissolution analysis. Ideally, formulations should exhibit controlled drug release, high viscoelasticity, and mucoadhesion, but should flow under minimal stresses. Based on these criteria, PEG 400-based organogels composed of 5% or 10% w/w PAA exhibited suitable physicochemical properties and are suggested to be a potentially interesting strategy for use as bioactive implants designed for use in the oral cavity. © 2008 American Chemical Society.

An examination of the rheological and mucoadhesive properties of poly(Acrylic acid) organogels designed as platforms for local drug delivery to the oral cavity

This study examined the rheological/mucoadhesive properties of poly (acrylic acid) PAA organogels as platforms for drug delivery to the oral cavity. Organogels were prepared using PAA (3%, 5%, 10% w/w) dissolved in ethylene glycol (EG), propylene glycol (PG), 1,3-propylene glycol (1,3-PG), 1,5-propanediol (1,5-PD), polyethylene glycol 400 (PEG 400), or glycerol. All organogels exhibited pseudoplastic flow. The increase in storage (G') and loss (G '') moduli of organogels as a function of frequency was minimal, G '' was greater than G '' (at all frequencies), and the loss tangent <1, indicative of gel behavior. Organogels prepared using EG, PG, and 1,3-propanediol (1,3-PD) exhibited similar flow/viscoelastic properties. Enhanced rheological structuring was associated with organogels prepared using glycerol (in particular) and PEG 400 due to their interaction with adjacent carboxylic acid groups on each chain and on adjacent chains. All organogels (with the exception of 1,5-PD) exhibited greater network structure than aqueous PAA gels. Organogel mucoadhesion increased with polymer concentration. Greatest mucoadhesion was associated with glycerol-based formulations, whereas aqueous PAA gels exhibited the lowest mucoadhesion. The enhanced network structure and the excellent mucoadhesive properties of these organogels, both of which may be engineered through choice of polymer concentration/solvent type, may be clinically useful for the delivery of drugs to the oral cavity.

Prediction of Fresh and Hardened Properties of Self-Consolidating Concrete Using Neurofuzzy Approach

Self-consolidating concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work conditions and also reduce the impact on the environment by elimination of the need for compaction. This investigation aimed at exploring the potential use of the neurofuzzy (NF) approach to model the fresh and hardened properties of SCC containing pulverised fuel ash (PFA) as based on experimental data investigated in this paper. Twenty six mixes were made with water-to-binder ratio ranging from 0.38 to 0.72, cement content ranging from 183 to 317 kg/m3 , dosage of PFA ranging from 29 to 261 kg/m3 , and percentage of superplasticizer, by mass of powder, ranging from 0 to 1%. Nine properties of SCC mixes modeled by NF were the slump flow, JRing combined to the Orimet, JRing combined to cone, V-funnel, L-box blocking ratio, segregation ratio, and the compressive strength at 7, 28, and 90 days. These properties characterized the filling ability, the passing ability, the segregation resistance of fresh SCC, and the compressive strength. NF model is constructed by training and testing data using the experimental results obtained in this study. The results of NF models were compared with experimental results and were found to be quite accurate. The proposed NF models offers useful modeling approach of the fresh and hardened properties of SCC containing PFA.

Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183–317 kg/m³ of cement content, 29–261 kg/m³ of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients.

Effect of Mix Proportions on Rheological and Hardened Properties of Composite Cement Pastes

There is an increasing need to identify the effect of mix composition on the rheological properties of composite cement pastes using simple tests to determine the fluidity, the cohesion and other mechanical properties of grouting applications such as compressive strength. This paper reviews statistical models developed using a fractional factorial design which was carried out to model the influence of key parameters on properties affecting the performance of composite cement paste. Such responses of fluidity included mini-slump, flow time using Marsh cone and cohesion measured by Lombardi plate meter and unit weight, and compressive strength at 3 d, 7 d and 28 d. The models are valid for mixes with 0.35 to 0.42 water-to-binder ratio (W/B), 10% to 40% of pulverised fuel ash (PFA) as replacement of cement by mass, 0.02 to 0.06% of viscosity enhancer admixture (VEA), by mass of binder, and 0.3 to 1.2% of superplasticizer (SP), by mass of binder. The derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of composite cement paste are presented. Such parameters can be useful to reduce the test protocol needed for proportioning of composite cement paste. This paper attempts also to demonstrate the usefulness of the models to better understand trade-offs between parameters and compare the responses obtained from the various test methods which are highlighted. The multi parametric optimization is used in order to establish isoresponses for a desirability function of cement composite paste. Results indicate that the replacement of cement by PFA is compromising the early compressive strength and up 26%, the desirability function decreased.

Temporal information and children's and adults' causal inferences

Three experiments examined whether children and adults would use temporal information as a cue to the causal structure of a three-variable system, and also whether their judgements about the effects of interventions on the system would be affected by the temporal properties of the event sequence. Participants were shown a system in which two events B and C occurred either simultaneously (synchronous condition) or in a temporal sequence (sequential condition) following an initial event A. The causal judgements of adults and 6-7-year-olds differed between the conditions, but this was not the case for 4-year-olds' judgements. However, unlike those of adults, 6-7-year-olds' intervention judgements were not affected by condition, and causal and intervention judgements were not reliably consistent in this age group. The findings support the claim that temporal information provides an important cue to causal structure, at least in older children. However, they raise important issues about the relationship between causal and intervention judgements.

Hybridization of a class of "second order" models of traffic flow

Despite the simultaneous progress of traffic modelling both on the macroscopic and microscopic front, recent works [E. Bourrel, J.B. Lessort, Mixing micro and macro representation of traffic flow: a hybrid model based on the LWR theory, Transport. Res. Rec. 1852 (2003) 193–200; D. Helbing, M. Treiber, Critical discussion of “synchronized flow”, Coop. Transport. Dyn. 1 (2002) 2.1–2.24; A. Hennecke, M. Treiber, D. Helbing, Macroscopic simulations of open systems and micro–macro link, in: D. Helbing, H.J. Herrmann, M. Schreckenberg, D.E. Wolf (Eds.), Traffic and Granular Flow ’99, Springer, Berlin, 2000, pp. 383–388] highlighted that one of the most promising way to simulate efficiently traffic flow on large road networks is a clever combination of both traffic representations: the hybrid modelling. Our focus in this paper is to propose two hybrid models for which the macroscopic (resp. mesoscopic) part is based on a class of second order model [A. Aw, M. Rascle, Resurection of second order models of traffic flow?, SIAM J. Appl. Math. 60 (2000) 916–938] whereas the microscopic part is a Follow-the Leader type model [D.C. Gazis, R. Herman, R.W. Rothery, Nonlinear follow-the-leader models of traffic flow, Oper. Res. 9 (1961) 545–567; R. Herman, I. Prigogine, Kinetic Theory of Vehicular Traffic, American Elsevier, New York, 1971]. For the first hybrid model, we define precisely the translation of boundary conditions at interfaces and for the second one we explain the synchronization processes. Furthermore, through some numerical simulations we show that the waves propagation is not disturbed and the mass is accurately conserved when passing from one traffic representation to another.

Single-phase fluid flow distribution and heat transfer in microstructured reactors

Single-phase microreactors and micro-heat-exchangers have been widely used in industrial and scientific applications over the last decade. In several cases, operation of microreactors has shown that their expected efficiency cannot be reached either due to non-uniform distribution of reactants between different channels or due to flow maldistribution between individual microreactors working in parallel. The latter problem can result in substantial temperature deviations between different microreactors resulting in thermal run away which could arise from an exothermicreaction. Thus advances in the understanding of heat transfer and fluid flow distribution continue to be crucial in achieving improved performance, efficiency and safety in microstructured reactors used for different applications. This paper presents a review of the experimental and numerical results on fluid flow distribution, heat transfer and combination thereof, available in the open literature. Heat transfer in microchannels can be suitably described by standard theory and correlations, but scaling effects (entrance effects, conjugate heat transfer, viscous heating, and temperature-dependent properties) have often to be accounted for in microsystems. Experiments with single channels are in good agreement with predictions from the published correlations. The accuracy of multichannel experiments is lower due to flow maldistribution. Special attention is devoted to theoretical and experimental studies on the effect of a flow maldistribution on the thermal and conversion response of catalytic microreactors. There view concludes with a set of design recommendations aimed at improving the reactor performance. (C) 2010 Elsevier Ltd. All rights reserved.

On the Sources of Private Information in FX Markets

We investigate the source of information advantage in inter-dealer FX trading using data on trades and counterparty identities. In liquid dollar exchange rates, information is concentrated among dealers that trade most frequently and specialize their activity in a particular rate. In cross-rates, traders that engage in triangular arbitrage are best informed. Better-informed traders are also located on larger trading floors. In cross-rates, the ability to forecast flows explains all of the advantage of the triangular arbitrageurs. In liquid dollar rates, specialist traders can forecast both order flow and the component of exchange rate changes that is uncorrelated with flow.