Enthalpies of formation of some solid hafnium nickel compounds and of the Ni-Rich HfNi liquid by direct reaction calorimetry

In the course of a systematic study of binary transition metal alloys, the enthalpies of formation of five Hf-Ni compounds were measured by direct reaction calorimetry: Hf_0.17Ni_0.83(l/6HfNi₅): Δ_fH(1323 K) = − 37,000 J/mole of atoms (±3200) Hf_0.22Ni_0.781/9Hf₂Ni₇): Δ_f(1623 K) = −50,700 J/mole of atoms (±2000) Hf_0.45Ni_0.55(l/2OHf₉Ni₁₁): Δ_fH(1473 K) = −54,500 J/mole of atoms (±2200) Hf_0.50Ni_0.50(l/2HfNi): Δ_fH(1573 K) = −47,900 J/mole of atoms (±1800) Hf_0.67Ni_0.33(l/3Hf₂Ni): ΔH(1423 K) = −36,700 J/mole of atoms (±1300) with reference to pure metals in their equilibrium states at the reaction temperatures. The Ni-rich Hf-Ni liquid was also studied by the dissolution of Hf in the liquid alloy of variable composition at 1743 and 1633 K. Results show that the enthalpy of formation of the liquid at a given composition depends strongly on temperature, and this point suggests the existence of associations in the liquid. The melting temperature of Hf_0.22Ni_0.78(Hf₂Ni₇) which was found (1705 K) is slightly lower than the one (1743 K) given in the literature. Formerly Senior Research Student with the Laboratoire de Thermodynamique Métallurgique, Université de Nancy Un, France     

CONTROL OF A PULSED LIQUID-LIQUID EXTRACTION COLUMN BASED ON A MULTILEVEL SYSTEM OF AUTOMATA

This paper presents the real-time application of the learning control theory to the control of a chemical pilot plant: a pulsed liquid-liquid extraction column.

The behaviour of an agitated liquid-liquid extraction column can be related to random mechanisms such as the phenomena of droplets breakage and coalescence. Previous studies on hydrodynamic and mass transfer aspects showed that a pulsed liquid-liquid extraction column had an optimal behaviour for operating conditions close to flooding. These results led to choose the following strategy to control the column in its optimal behaviour zone:

- the measure of the conductivity of the liquid medium below the distributor which gives a good information about flooding, is the controlled variable

-the pulse frequency is the control action.

The learning control algorithm is based on a multilevel system of automata which operates in a random environment. By means of an evaluation unit of the performances of the column which generates either penalty (inaction) or reward on the basis of heuristic rules, the automaton chooses a value of the pulse frequency. This approach is essentially connected to artificial intelligence in so far as human knowledge on the plant is included in these rules.

This algorithm has been implemented on a microcomputer for control purposes. The experimental results presented show the good performances of the approach.     

Assessment of Agricultural NonPoint Source Model for a Watershed in Tropical Environment

Very little work on the application of watershed modeling has been done in the tropical climatic conditions of Thailand to explore the nature of environmental problems arising from nonpoint source pollution due to agricultural activities, and to evaluate possible remedial measures and strategies. The present study attempts to verify the suitability of a nonpoint source pollution model, the Agricultural NonPoint Source model, for the Huai Nong Prong watershed in Southeastern Thailand. Extensive fieldwork was carried out to collect data and information needed for the model preparation and application. The study has revealed that simulated runoff volume, sediment, and nutrient yield from the watershed with mixed land use and relatively high slopes match favorably with observed data. For the ten rainfall events simulated, the coefficient of performance, a measure of model efficiency (equal to zero for a perfect match), was 0.09, 0.47, 0.09, and 0.03 for runoff volume, sediment yield, total nitrogen, and total phosphorus, respectively. The model, however, could not accurately simulate peak flow rates, suggesting the need for changes in the modeling approach or governing equations and relationships to calculate peak discharges in a tropical environment.     

Bush‐Mosteller learning for a zero-sum repeated game with random pay-offs

This paper deals with the design and analysis of a modified version of the Bush-Mosteller reinforcement scheme applied by partners in a zero-sum repeated game with random pay-offs. The suggested study is based on the learning automata paradigm and a limiting average reward criterion is tackled to analyse the arising Nash equilibrium. No information concerning the distribution of the pay-off is a priori available. The novelty of the suggested adaptive strategy is related to the incorporation of a 'normalization procedure' into the standard Bush-Mosteller scheme to provide a possibility to operate not only with binary but also with any bounded rewards of a stochastic nature. The analysis of the convergence (adaptation) as well as the convergence rate (rate of adaptation) are presented and the optimal design parameters of this adaptive procedure are derived. The obtained adaptation rate turns out to be of o(n 1/3 ).     

OLRIV: a new fast adaptive algorithm for rectangular-block Toeplitzsystems

In this paper, we propose a new algorithm for solving overdetermined systems when they are rectangular-block Toeplitz (the blocks can have more rows than columns). It is based on the expression of the matrix of the system to solve as the intercorrelation between two vectorial processes, namely, the original and the instrumental processes. The instrumental process has generally more components than the original one; therefore, it takes the overdetermined character of the system into consideration. The proposed algorithm known as the overdetermined lattice recursive instrumental variable (OLRIV) belongs to the fast-RLS family and lies on a double lattice structure, where one lattice performs the prediction of the original process and the other one the prediction of the instrumental process. The geometric complete derivation of the proposed algorithm is given in the paper. Afterwards, we show how OLRIV can be applied to perform blind adaptive identification of AR channels using high order statistics, where the systems to solve are often overdetermined to ensure identifiability. Both the scalar and the vectorial cases are investigated. Simulation results are finally given to show the performances of OLRIV     

Adaptive linear quadratic gaussian (LQG) control of a bioreactor

The paper deals with the modelling and adaptive control of a continuous-flow fermentation process for the production of alcohol. The fermenter model has been developed from mass balance and leads to nonlinear differential equations. In practice, control strategies are difficult to derive using this non-linear model. The dilution rate and the substrate concentration have been considered as control and controlled variables, respectively. The adaptive control algorithm implemented is based on the linear quadratic control approach, where the associated Riccati equation is iterated until the system closed-loop poles belong to a restricted stability domain which is included in the unit circle. A single input/output model is used for control purposes. The model parameters are estimated on-line using a robust identification algorithm which includes: data normalization, time-varying forgetting factor, covariance matrix factorization, etc. Experimental results show the performance of this adaptive scheme and its ability to control biotechnological processes.     

Adaptive control: theory and practical aspects

An a overview of discrete adaptive contollers is given. A unified presentation of the underlying control designs is made and the fundamental properties of the parameter estimations to be used are given. Particular emphasis is put on the design assumptions and several adaptive control applications are reported.     

BER and Outage Probability Approximations for LMMSE Detectors on Correlated MIMO Channels

This paper is devoted to the study of the performance of the linear minimum mean-square error (LMMSE) receiver for (receive) correlated multiple-input multiple-output (MIMO) systems. By the random matrix theory, it is well known that the signal-to-noise ratio (SNR) at the output of this receiver behaves asymptotically like a Gaussian random variable as the number of receive and transmit antennas converge to +infin at the same rate. However, this approximation being inaccurate for the estimation of some performance metrics such as the bit error rate (BER) and the outage probability, especially for small system dimensions, Li proposed convincingly to assume that the SNR follows a generalized gamma distribution which parameters are tuned by computing the first three asymptotic moments of the SNR. In this paper, this technique is generalized to (receive) correlated channels, and closed-form expressions for the first three asymptotic moments of the SNR are provided. To obtain these results, a random matrix theory technique adapted to matrices with Gaussian elements is used. This technique is believed to be simple, efficient, and of broad interest in wireless communications. Simulations are provided, and show that the proposed technique yields in general a good accuracy, even for small system dimensions.     

Synthesis,characterization, and gas-sensing performance of macroporous Zn-doped NiO thin films for ammonia gas detection

Journal of Materials Science: Materials in Electronics - Zinc-doped nickel oxide (NiO:Zn) thin films have been synthesized by chemical spray pyrolysis (CSP), then we have studied the structural,...     

The effect of hybridization on the GFRP behavior under high velocity impact

In the present study, experimental and analytical investigations for the behavior of E-glass fiber reinforced composite hybridized with a layer of Kevlar 29 fiber, under high velocity impact, were performed. The experimental work includes the placement of the Kevlar layer at four different locations to verify the effects of the stacking sequence on the impact behavior. Three different projectile geometries, namely, flat-ended, hemispherical and conical were used. The experimental results reveal that hybridization improves the laminates performance under dynamic penetration. The results also indicate that the laminates response was found to be highly sensitive to the projectile geometry. In the case of analytical modeling, two energy models were conducted to calculate the projectile residual velocities. The results obtained from the two models were compared with those obtained experimentally and some conclusions were drawn.