Artificial neural network application to power system voltage stability improvement

As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Chemically enhanced thermal stability of anodized nanostructured zirconia membranes

Anodized nanotubular and nanoporous zirconia membranes are of interest for applications involving elevated temperatures in excess of 400 degrees C, such as templates for the synthesis of nanostructures, catalyst supports, fuel cells and sensors. Thermal stability is thus an important attribute. The study described in this paper shows that the as-anodized nanoporous membranes can withstand more adverse temperature-time combinations than nanotubular membranes. Chemical treatment of the nanoporous membranes was found to further enhance their thermal stability. The net result is an enhancement in the limiting temperature from 500 degrees C for nanotubular membranes to 1000 degrees C for the chemically treated nanoporous membranes. The reasons for membrane degradation on thermal exposure and the mechanism responsible for retarding the same are discussed within the framework of the theory of thermal grooving.

Ag-Ni Nanoparticles: Synthesis and Phase Stability

The present study provides an electrodeposition based synthesis method for producing solid solution structured Ag-Ni nanoparticles. It was also observed that the room temperature stable solid solution configuration for the electrodeposited Ag-Ni nanoparticle was a kinetically frozen atomic arrangement and not a thermodynamically stable structure as upon annealing of the Ag-Ni nanoparticles in the ambient atmosphere the solid solution structure decomposed producing phases that were oxides of Ag and Ni. (C) 2012 The Electrochemical Society. [DOI: 10.1149/2.esl120008] All rights reserved.

Relevance of local parallel theory to the linear stability of laminar separation bubbles

Laminar separation bubbles are thought to be highly non-parallel, and hence global stability studies start from this premise. However, experimentalists have always realized that the flow is more parallel than is commonly believed, for pressure-gradient-induced bubbles, and this is why linear parallel stability theory has been successful in describing their early stages of transition. The present experimental/numerical study re-examines this important issue and finds that the base flow in such a separation bubble becomes nearly parallel due to a strong-interaction process between the separated boundary layer and the outer potential flow. The so-called dead-air region or the region of constant pressure is a simple consequence of this strong interaction. We use triple-deck theory to qualitatively explain these features. Next, the implications of global analysis for the linear stability of separation bubbles are considered. In particular we show that in the initial portion of the bubble, where the flow is nearly parallel, local stability analysis is sufficient to capture the essential physics. It appears that the real utility of the global analysis is perhaps in the rear portion of the bubble, where the flow is highly non-parallel, and where the secondary/nonlinear instability stages are likely to dominate the dynamics.

Monodispersity and stability: case of ultrafine aluminium nanoparticles (< 5 nm) synthesized by the solvated metal atom dispersion approach

The synthesis of THF coordinated aluminium nanoparticles by the solvated metal atom dispersion (SMAD) method is described. These colloids are not stable with respect to precipitation of aluminium nanoparticles. The precipitated aluminium nanopowder is highly pyrophoric. Highly monodisperse colloidal aluminium nanoparticles (3.1 +/- 0.6 nm) stabilized by a capping agent, hexadecyl amine (HDA), have also been prepared by the SMAD method. They are stable towards precipitation of particles for more than a week. The Al-HDA nanoparticles are not as pyrophoric as the Al-THF samples. Particles synthesized in this manner were characterized by high-resolution electron microscopy and powder X-ray diffraction. Annealing of the Al-HDA nanoparticles resulted in carbonization of the capping agent on the surface of the particles which imparts air stability to them. Carbonization of the capping agent was established using Raman spectroscopy and TEM. The annealed aluminium nanoparticles were found to be stable even upon their exposure to air for over a month which was evident from the powder XRD, TGA/DSC, and TEM studies. The successful passivation was further confirmed with the determination of high active aluminium content (95 wt%) upon exposure and storage under air.

An operator-splitting Galerkin/SUPG finite element method for population balance equations : stability and convergence

We present a heterogeneous finite element method for the solution of a high-dimensional population balance equation, which depends both the physical and the internal property coordinates. The proposed scheme tackles the two main difficulties in the finite element solution of population balance equation: (i) spatial discretization with the standard finite elements, when the dimension of the equation is more than three, (ii) spurious oscillations in the solution induced by standard Galerkin approximation due to pure advection in the internal property coordinates. The key idea is to split the high-dimensional population balance equation into two low-dimensional equations, and discretize the low-dimensional equations separately. In the proposed splitting scheme, the shape of the physical domain can be arbitrary, and different discretizations can be applied to the low-dimensional equations. In particular, we discretize the physical and internal spaces with the standard Galerkin and Streamline Upwind Petrov Galerkin (SUPG) finite elements, respectively. The stability and error estimates of the Galerkin/SUPG finite element discretization of the population balance equation are derived. It is shown that a slightly more regularity, i.e. the mixed partial derivatives of the solution has to be bounded, is necessary for the optimal order of convergence. Numerical results are presented to support the analysis.

Inter-domain interactions influence the stability and catalytic activity of the bi-domain protein tyrosine phosphatase PTP99A

The two protein tyrosine phosphatase (PTP) domains in bi-domain PTPs share high sequence and structural similarity. However, only one of the two PIP domains is catalytically active. Here we describe biochemical studies on the two tandem PTP domains of the bi-domain PTP, PTP99A. Phosphatase activity, monitored using small molecule as well as peptide substrates, revealed that the inactive (D2) domain activates the catalytic (D1) domain. Thermodynamic measurements suggest that the inactive D2 domain stabilizes the bi-domain (D1-D2) protein. The mechanism by which the D2 domain activates and stabilizes the bi-domain protein is governed by few interactions at the inter-domain interface. In particular, mutating Lys990 at the interface attenuates inter-domain communication. This residue is located at a structurally equivalent location to the so-called allosteric site of the canonical single domain PIP, PTP1B. These observations suggest functional optimization in bi-domain PTPs whereby the inactive PTP domain modulates the catalytic activity of the bi-domain enzyme. (C) 2012 Elsevier B.V. All rights reserved.

Enhanced J-protein interaction and compromised protein stability of mtHsp70 variants lead to mitochondrial dysfunction in Parkinsons disease

Parkinsons disease (PD) is the second most prevalent progressive neurological disorder commonly associated with impaired mitochondrial function in dopaminergic neurons. Although familial PD is multifactorial in nature, a recent genetic screen involving PD patients identified two mitochondrial Hsp70 variants (P509S and R126W) that are suggested in PD pathogenesis. However, molecular mechanisms underlying how mtHsp70 PD variants are centrally involved in PD progression is totally elusive. In this article, we provide mechanistic insights into the mitochondrial dysfunction associated with human mtHsp70 PD variants. Biochemically, the R126W variant showed severely compromised protein stability and was found highly susceptible to aggregation at physiological conditions. Strikingly, on the other hand, the P509S variant exhibits significantly enhanced interaction with J-protein cochaperones involved in folding and import machinery, thus altering the overall regulation of chaperone-mediated folding cycle and protein homeostasis. To assess the impact of mtHsp70 PD mutations at the cellular level, we developed yeast as a model system by making analogous mutations in Ssc1 ortholog. Interestingly, PD mutations in yeast (R103W and P486S) exhibit multiple in vivo phenotypes, which are associated with omitochondrial dysfunction', including compromised growth, impairment in protein translocation, reduced functional mitochondrial mass, mitochondrial DNA loss, respiratory incompetency and increased susceptibility to oxidative stress. In addition to that, R103W protein is prone to aggregate in vivo due to reduced stability, whereas P486S showed enhanced interaction with J-proteins, thus remarkably recapitulating the cellular defects that are observed in human PD variants. Taken together, our findings provide evidence in favor of direct involvement of mtHsp70 as a susceptibility factor in PD.

Evolution of quantum discord and its stability in two-qubit NMR systems

We investigate evolution of quantum correlations in ensembles of two-qubit nuclear spin systems via nuclear magnetic resonance techniques. We use discord as a measure of quantum correlations and the Werner state as an explicit example. We, first, introduce different ways of measuring discord and geometric discord in two-qubit systems and then describe the following experimental studies: (a) We quantitatively measure discord for Werner-like states prepared using an entangling pulse sequence. An initial thermal state with zero discord is gradually and periodically transformed into a mixed state with maximum discord. The experimental and simulated behavior of rise and fall of discord agree fairly well. (b) We examine the efficiency of dynamical decoupling sequences in preserving quantum correlations. In our experimental setup, the dynamical decoupling sequences preserved the traceless parts of the density matrices at high fidelity. But they could not maintain the purity of the quantum states and so were unable to keep the discord from decaying. (c) We observe the evolution of discord for a singlet-triplet mixed state during a radio-frequency spin-lock. A simple relaxation model describes the evolution of discord, and the accompanying evolution of fidelity of the long-lived singlet state, reasonably well.

A Linear S-N Curve with Load Dependent Variance and Explicit Failure Probability

We reconsider standard uniaxial fatigue test data obtained from handbooks. Many S-N curve fits to such data represent the median life and exclude load-dependent variance in life. Presently available approaches for incorporating probabilistic aspects explicitly within the S-N curves have some shortcomings, which we discuss. We propose a new linear S-N fit with a prespecified failure probability, load-dependent variance, and reasonable behavior at extreme loads. We fit our parameters using maximum likelihood, show the reasonableness of the fit using Q-Q plots, and obtain standard error estimates via Monte Carlo simulations. The proposed fitting method may be used for obtaining S-N curves from the same data as already available, with the same mathematical form, but in cases in which the failure probability is smaller, say, 10 % instead of 50 %, and in which the fitted line is not parallel to the 50 % (median) line.

Conservative Failure Criteria for Optimal Design of Composite Structures Including Effect of Shear Loading

A minimum weight design of laminated composite structures is carried out for different loading conditions and failure criteria using genetic algorithm. The phenomenological maximum stress (MS) and Tsai-Wu (TW) criteria and the micro-mechanism-based failure mechanism based (FMB) failure criteria are considered. A new failure envelope called the Most Conservative Failure Envelope (MCFE) is proposed by combining the three failure envelopes based on the lowest absolute values of the strengths predicted. The effect of shear loading on the MCFE is investigated. The interaction between the loading conditions, failure criteria, and strength-based optimal design is brought out.

Thermo-mechanical stability of a cellular assembly of carbon nanotubes in air

Carbon nanotubes (CNT) in bulk form offer outstanding structural and functional properties, and are shown to remain viscoelastic over a wide temperature range (77-1273 K) under inert conditions. We examine the quasi-static and dynamic compressive mechanical response of these cellular CNT materials in ambient air up to a temperature of 773 K. In uniaxial quasi-static compression, several displacement bursts are noted at large strains. These are results of the slippage and zipping of the CNT, and lead to significant mechanical energy absorption. Results of the dynamic mechanical analysis experiments show no degradation in storage modulus and loss coefficient for up to 20 h at 673 K. Hence, these stable cellular CNT structures can be utilized up to a maximum temperature of 673 K in air, which is much higher than the best polymers. (C) 2012 Elsevier Ltd. All rights reserved.