Evolutionary Algorithm for the Determination of Optimal Mode of Bioreactor Operation

Stirred tank bioreactors, employed in the production of a variety of biologically active chemicals, are often operated in batch, fed-batch, and continuous modes of operation. The optimal design of bioreactor is dependent on the kinetics of the biological process, as well as the performance criteria (yield, productivity, etc.) under consideration. In this paper, a general framework is proposed for addressing the two key issues related to the optimal design of a bioreactor, namely, (i) choice of the best operating mode and (ii) the corresponding flow rate trajectories. The optimal bioreactor design problem is formulated with initial conditions and inlet and outlet flow rate trajectories as decision variables to maximize more than one performance criteria (yield, productivity, etc.) as objective functions. A computational methodology based on genetic algorithm approach is developed to solve this challenging multiobjective optimization problem with multiple decision variables. The applicability of the algorithm is illustrated by solving two challenging problems from the bioreactor optimization literature.

Methodology for alleviation of voltage excursions in large power systems

This paper presents a method for minimizing the sum of the square of voltage deviations by a least-square minimization technique, and thus improving the voltage profile in a given system by adjusting control variables, such as tap position of transformers, reactive power injection of VAR sources and generator excitations. The control variables and dependent variables are related by a matrix J whose elements are computed as the sensitivity matrix. Linear programming is used to calculate voltage increments that minimize transmission losses. The active and reactive power optimization sub-problems are solved separately taking advantage of the loose coupling between the two problems. The proposed algorithm is applied to IEEE 14-and 30-bus systems and numerical results are presented. The method is computationally fast and promises to be suitable for implementation in real-time dispatch centres.

Optimal placement of Distributed Generation for a projected load increase using Relative Electrical Distance approach

There is a lot of pressure on all the developed and second world countries to produce low emission power and distributed generation (DG) is found to be one of the most viable ways to achieve this. DG generally makes use of renewable energy sources like wind, micro turbines, photovoltaic, etc., which produce power with minimum green house gas emissions. While installing a DG it is important to define its size and optimal location enabling minimum network expansion and line losses. In this paper, a methodology to locate the optimal site for a DG installation, with the objective to minimize the net transmission losses, is presented. The methodology is based on the concept of relative electrical distance (RED) between the DG and the load points. This approach will help to identify the new DG location(s), without the necessity to conduct repeated power flows. To validate this methodology case studies are carried out on a 20 node, 66kV system, a part of Karnataka Transco and results are presented.

Generalizing the Amplify-and-Forward Relay Gain Model: An Optimal SEP Perspective

Two models for AF relaying, namely, fixed gain and fixed power relaying, have been extensively studied in the literature given their ability to harness spatial diversity. In fixed gain relaying, the relay gain is fixed but its transmit power varies as a function of the source-relay channel gain. In fixed power relaying, the relay transmit power is fixed, but its gain varies. We revisit and generalize the fundamental two-hop AF relaying model. We present an optimal scheme in which an average power constrained AF relay adapts its gain and transmit power to minimize the symbol error probability (SEP) at the destination. Also derived are insightful and practically amenable closed-form bounds for the optimal relay gain. We then analyze the SEP of MPSK, derive tight bounds for it, and characterize the diversity order for Rayleigh fading. Also derived is an SEP approximation that is accurate to within 0.1 dB. Extensive results show that the scheme yields significant energy savings of 2.0-7.7 dB at the source and relay. Optimal relay placement for the proposed scheme is also characterized, and is different from fixed gain or power relaying. Generalizations to MQAM and other fading distributions are also discussed.

A novel gas flow sensing application using piezoelectric ZnO thin films deposited on Phynox alloy

We report on the novel flow sensing application of piezoelectric ZnO thin film deposited on Phynox alloy sensing element. Characterization of piezoelectric ZnO films deposited on Phynox (Elgiloy) substrate at different RF powers is discussed. ZnO films deposited at RF power of 100W were found to have fine c-axis orientation, possesses excellent surface morphology with lower rms surface roughness of 1.87 nm and maximum d(31) coefficient value 4.7 pm V-1. The thin cantilever strip of Phynox alloy with ZnO film as a sensing layer for flow sensing has been tested for flow rates ranging from 2 to 18 L min(-1). A detailed theoretical analysis of the experimental set-up showing the relationship between output voltage and force at a particular flow rate has been discussed. The sensitivity of now sensing element is similar to 18 mV/(L min(-1)) and typical response time is of the order of 20 m s. The sensing element is calibrated using in-house developed testing set-up. (C) 2012 Elsevier B.V. All rights reserved.

Duty cycling and power management with a network of energy harvesting sensors

In this paper, we study duty cycling and power management in a network of energy harvesting sensor (EHS) nodes. We consider a one-hop network, where K EHS nodes send data to a destination over a wireless fading channel. The goal is to find the optimum duty cycling and power scheduling across the nodes that maximizes the average sum data rate, subject to energy neutrality at each node. We adopt a two-stage approach to simplify the problem. In the inner stage, we solve the problem of optimal duty cycling of the nodes, subject to the short-term power constraint set by the outer stage. The outer stage sets the short-term power constraints on the inner stage to maximize the long-term expected sum data rate, subject to long-term energy neutrality at each node. Albeit suboptimal, our solutions turn out to have a surprisingly simple form: the duty cycle allotted to each node by the inner stage is simply the fractional allotted power of that node relative to the total allotted power. The sum power allotted is a clipped version of the sum harvested power across all the nodes. The average sum throughput thus ultimately depends only on the sum harvested power and its statistics. We illustrate the performance improvement offered by the proposed solution compared to other naive schemes via Monte-Carlo simulations.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.

Power-law transformation for enhanced recognition of born-digital word images

In this paper, we discuss the issues related to word recognition in born-digital word images. We introduce a novel method of power-law transformation on the word image for binarization. We show the improvement in image binarization and the consequent increase in the recognition performance of OCR engine on the word image. The optimal value of gamma for a word image is automatically chosen by our algorithm with fixed stroke width threshold. We have exhaustively experimented our algorithm by varying the gamma and stroke width threshold value. By varying the gamma value, we found that our algorithm performed better than the results reported in the literature. On the ICDAR Robust Reading Systems Challenge-1: Word Recognition Task on born digital dataset, as compared to the recognition rate of 61.5% achieved by TH-OCR after suitable pre-processing by Yang et. al. and 63.4% by ABBYY Fine Reader (used as baseline by the competition organizers without any preprocessing), we achieved 82.9% using Omnipage OCR applied on the images after being processed by our algorithm.

Supercritical carbon dioxide Brayton cycle for concentrated solar power

Supercritical carbon dioxide based Brayton cycle for possible concentrated solar power applications is investigated and compared with trans- and sub-critical operations of the same fluid. Thermal efficiency, specific work output and magnitude of irreversibility generation are used as some of the performance indicators. While the thermal efficiency increases almost linearly with low side pressure in the sub- and trans-critical cycles, it attains a maximum in the supercritical regime at 85 bar after which there are diminishing returns on increasing the low side pressure. It is also found that supercritical cycle is capable of producing power with a thermal efficiency of >30% even at a lower source temperature (820K) and accounting for foreseeable non-idealities albeit with a higher turbine inlet pressure (similar to 300 bar) which is not matched by a conventional sub-critical cycle even with a high source temperature of 978K. The reasons for lower efficiency than in an ideal cycle are extracted from an irreversibility analysis of components, namely, compressor, regenerator, turbine and gas cooler. Low sensitivity to the source temperature and extremely small volumetric flow rates in the supercritical cycle could offset the drawback of high pressures through a compact system.

Intracellular reactive oxidative stress, cell proliferation and apoptosis of Schwann cells on carbon nanofibrous substrates

Despite considerable research to develop carbon based materials for biomedical applications, the toxicity of carbon remains a major concern. In order to address this issue as well as to investigate the cell fate processes of neural cells from the perspective of neural tissue engineering applications, the in vitro cytocompatibility of polyacrylonitrile (PAN) derived continuous carbon nanofibers and PAN derived carbon thin films were investigated both quantitatively and qualitatively using in vitro biochemical assays followed by extensive flow cytometry analysis. The experimental results of Schwann cell fate, i.e. cell proliferation, cell metabolic activity and cell apoptosis on amorphous carbon substrates are discussed in reference to the time dependent evolution of intracellular oxidative stress. Apart from providing evidence that an electrospun carbon nanofibrous substrate can physically guide the cultured Schwann cells, this study suggested that continuous carbon nanofibers and amorphous carbon films are not cytotoxic in vitro and do not significantly induce apoptosis of Schwann cells, but in fact even facilitate their proliferation and growth.

Composition, structure and electrical properties of DC reactive magnetron sputtered Al2O3 thin films

Thin films of alumina (Al2O3) were deposited over Si < 1 0 0 > substrates at room temperature at an oxygen gas pressure of 0.03 Pa and sputtering power of 60 W using DC reactive magnetron sputtering. The composition of the as-deposited film was analyzed by X-ray photoelectron spectroscopy and the O/Al atomic ratio was found to be 1.72. The films were then annealed in vacuum to 350, 550 and 750 degrees C and X-ray diffraction results revealed that both as-deposited and post deposition annealed films were amorphous. The surface morphology and topography of the films was studied using scanning electron microscopy and atomic force microscopy, respectively. A progressive decrease in the root mean square (RMS) roughness of the films from 1.53 nm to 0.7 nm was observed with increase in the annealing temperature. Al-Al2O3-Al thin film capacitors were then fabricated on p-type Si < 1 0 0 > substrate to study the effect of temperature and frequency on the dielectric property of the films and the results are discussed.

Apparatus and method for heat-run test on high-power PWM converters with low energy expenditure

Before installation, a voltage source converter is usually subjected to heat-run test to verify its thermal design and performance under load. For heat-run test, the converter needs to be operated at rated voltage and rated current for a substantial length of time. Hence, such tests consume huge amount of energy in case of high-power converters. Also, the capacities of the source and loads available in the research and development (R&D) centre or the production facility could be inadequate to conduct such tests. This paper proposes a method to conduct heat-run tests on high-power, pulse width modulated (PWM) converters with low energy consumption. The experimental set-up consists of the converter under test and another converter (of similar or higher rating), both connected in parallel on the ac side and open on the dc side. Vector-control or synchronous reference frame control is employed to control the converters such that one draws certain amount of reactive power and the other supplies the same; only the system losses are drawn from the mains. The performance of the controller is validated through simulation and experiments. Experimental results, pertaining to heat-run tests on a high-power PWM converter, are presented at power levels of 25 kVA to 150 kVA.

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

An integrated model for optimal reservoir operation for irrigation of multiple crops

An integratedm odel is developed,b asedo n seasonailn puts of reservoiri nflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocationst o multiple crops.T he model is conceptuallym ade up of two modules. Module 1 is an intraseasonal allocation model to maximize the sum of relative yieldso f all crops,f or a givens tateo f the systemu, singl inear programming(L P). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growthw ith time. Module 2 is a seasonaal llocationm odel to derive the steadys tate reservoiro peratingp olicyu sings tochastidc ynamicp rogramming(S DP). Reservoir storage, seasonal inflow, and seasonal rainfall are the state variables in the SDP. The objective in SDP is to maximize the expected sum of relative yields of all crops in a year.The resultso f module 1 and the transitionp robabilitieso f seasonailn flow and rainfall form the input for module 2. The use of seasonailn puts coupledw ith the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study,w hile affectinga dditionali mprovementsT. he model is applied to an existing reservoir in Karnataka State, India.

A general geomorphological recession flow model for river basins

Recession flows in a basin are controlled by the temporal evolution of its active drainage network (ADN). The geomorphological recession flow model (GRFM) assumes that both the rate of flow generation per unit ADN length (q) and the speed at which ADN heads move downstream (c) remain constant during a recession event. Thereby, it connects the power law exponent of -dQ/dt versus Q (discharge at the outlet at time t) curve, , with the structure of the drainage network, a fixed entity. In this study, we first reformulate the GRFM for Horton-Strahler networks and show that the geomorphic ((g)) is equal to D/(D-1), where D is the fractal dimension of the drainage network. We then propose a more general recession flow model by expressing both q and c as functions of Horton-Strahler stream order. We show that it is possible to have = (g) for a recession event even when q and c do not remain constant. The modified GRFM suggests that is controlled by the spatial distribution of subsurface storage within the basin. By analyzing streamflow data from 39 U.S. Geological Survey basins, we show that is having a power law relationship with recession curve peak, which indicates that the spatial distribution of subsurface storage varies across recession events. Key Points The GRFM is reformulated for Horton-Strahler networks. The GRFM is modified by allowing its parameters to vary along streams. Sub-surface storage distribution controls recession flow characteristics.