69 resultados para Sustainable Harvesting


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Prolific algal growth in sewage ponds with high organic loads in the tropical regions can provide cost-effective and efficient wastewater treatment and biofuel production. This work examines the ability of Euglena sp. growing in wastewater ponds for biofuel production and treatment of wastewater. The algae were isolated from the sewage treatment plants and were tested for their nutrient removal capability. Compared to other algae, Euglena sp. showed faster growth rates with high biomass density at elevated concentrations of ammonium nitrogen (NH4-N) and organic carbon (C). Profuse growth of these species was observed in untreated wastewaters with a mean specific growth rate (mu) of 0.28 day(-1) and biomass productivities of 132 mg L-1 day(-1). The algae cultured within a short period of 8 days resulted in the 98 % removal of NH4-N, 93 % of total nitrogen 85 % of ortho-phosphate, 66 % of total phosphate and 92 % total organic carbon. Euglenoids achieved a maximum lipid content of 24.6 % (w/w) with a biomass density of 1.24 g L-1 (dry wt.). Fourier transform infrared spectra showed clear transitions in biochemical compositions with increased lipid/protein ratio at the end of the culture. Gas chromatography and mass spectrometry indicated the presence of high contents of palmitic, linolenic and linoleic acids (46, 23 and 22 %, respectively), adding to the biodiesel quality. Good lipid content (comprised quality fatty acids), efficient nutrient uptake and profuse biomass productivity make the Euglena sp. as a viable source for biofuel production in wastewaters.

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We investigate the thermoelectric (TE) figure-of-merit of a single-layer graphene (SLG) sheet by a physics-based analytical technique. We first develop analytical models of electrical and thermal resistances and the Seebeck coefficient of SLG by considering electron interactions with the in-plane and flexural phonons. Using those models, we show that both the figure-of-merit and the TE efficiency can be substantially increased with the addition of isotope doping as it significantly reduces the phonon-dominated thermal conductivity. In addition, we report that the TE open circuit output voltage and output power depends weakly on the SLG sheet dimensions and sheet concentration in the strongly diffusive regime. Proposed models agree well with the available experimental data and demonstrate the immense potential of graphene for waste-heat recovery application.

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We propose energy harvesting technologies and cooperative relaying techniques to power the devices and improve reliability. We propose schemes to (a) maximize the packet reception ratio (PRR) by cooperation and (b) minimize the average packet delay (APD) by cooperation amongst nodes. Our key result and insight from the testbed implementation is about total data transmitted by each relay. A greedy policy that relays more data under a good harvesting condition turns out to be a sub optimal policy. This is because, energy replenishment is a slow process. The optimal scheme offers a low APD and also improves PRR.

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A circuit topology based on accumulate-and-use philosophy has been developed to harvest RF energy from ambient radiations such as those from cellular towers. Main functional units of this system are antenna, tuned rectifier, supercapacitor, a gated boost converter and the necessary power management circuits. Various RF aspects of the design philosophy for maximizing the conversion efficiency at an input power level of 15 mu W are presented here. The system is characterized in an anechoic chamber and it has been established that this topology can harvest RF power densities as low as 180 mu W/m(2) and can adaptively operate the load depending on the incident radiation levels. The output of this system can be easily configured at a desired voltage in the range 2.2-4.5 V. A practical CMOS load - a low power wireless radio module has been demonstrated to operate intermittently by this approach. This topology can be easily modified for driving other practical loads, from harvested RF energy at different frequencies and power levels.

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Ionic Polymer Metal Composites (IPMCs) are a class of Electro-Active Polymers (EAPs) consisting of a base polymer (usually Nafion), sandwiched between thin films of electrodes and an electrolyte. Apart from fuel cell like proton exchange process in Nafion, these IPMCs can act both as an actuator and a sensor. Typically, IPMCs have been known for their applications in fuel cell technology and in artificial muscles for robots. However, more recently, sensing properties of IPMC have opened up possibilities of mechanical energy harvesting. In this paper, we consider a bi-layer stack of IPMC membranes where fluid flow induced cyclic oscillation allows collection of electronic charge across a pair of functionalized electrode on the surface of IPMC layers/stacks. IPMCs work well in hydrated environment; more specifically, in presence of an electrolyte, and therefore, have great potential in underwater applications like hydrodynamic energy harvesting. Hydrodynamic forces produce bending deformation, which can induce transport of cations via polymer chains of the base polymer of Nafion or PTFE. In our experimental set-up, the deformation is induced into the array of IPMC membranes immersed in electrolyte by water waves caused by a plunger connected to a stepper motor. The frequency and amplitude of the water waves is controlled by the stepper motor through a micro-controller. The generated electric power is measured across a resistive load. Few orders of magnitude increase in the harvested power density is observed. Analytical modeling approach used for power and efficiency calculations are discussed. The observed electro-mechanical performance promises a host of underwater energy harvesting applications.

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Multiobjective fuzzy methodology is applied to a case study of Khadakwasla complex irrigation project located near Pune city of Maharashtra State, India. Three objectives, namely, maximization of net benefits, crop production and labour employment are considered. Effect of reuse of wastewater on the planning scenario is also studied. Three membership functions, namely, nonlinear, hyperbolic and exponential are analyzed for multiobjective fuzzy optimization. In the present study, objective functions are considered as fuzzy in nature whereas inflows are considered as dependable. It is concluded that exponential and hyperbolic membership functions provided similar cropping pattern for most of the situations whereas nonlinear membership functions provided different cropping pattern. However, in all the three cases, irrigation intensities are more than the existing irrigation intensity.

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This paper addresses the problem of finding outage-optimal power control policies for wireless energy harvesting sensor (EHS) nodes with automatic repeat request (ARQ)-based packet transmissions. The power control policy of the EHS specifies the transmission power for each packet transmission attempt, based on all the information available at the EHS. In particular, the acknowledgement (ACK) or negative acknowledgement (NACK) messages received provide the EHS with partial information about the channel state. We solve the problem of finding an optimal power control policy by casting it as a partially observable Markov decision process (POMDP). We study the structure of the optimal power policy in two ways. First, for the special case of binary power levels at the EHS, we show that the optimal policy for the underlying Markov decision process (MDP) when the channel state is observable is a threshold policy in the battery state. Second, we benchmark the performance of the EHS by rigorously analyzing the outage probability of a general fixed-power transmission scheme, where the EHS uses a predetermined power level at each slot within the frame. Monte Carlo simulation results illustrate the performance of the POMDP approach and verify the accuracy of the analysis. They also show that the POMDP solutions can significantly outperform conventional ad hoc approaches.

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This paper addresses the problem of finding optimal power control policies for wireless energy harvesting sensor (EHS) nodes with automatic repeat request (ARQ)-based packet transmissions. The EHS harvests energy from the environment according to a Bernoulli process; and it is required to operate within the constraint of energy neutrality. The EHS obtains partial channel state information (CSI) at the transmitter through the link-layer ARQ protocol, via the ACK/NACK feedback messages, and uses it to adapt the transmission power for the packet (re)transmission attempts. The underlying wireless fading channel is modeled as a finite state Markov chain with known transition probabilities. Thus, the goal of the power management policy is to determine the best power setting for the current packet transmission attempt, so as to maximize a long-run expected reward such as the expected outage probability. The problem is addressed in a decision-theoretic framework by casting it as a partially observable Markov decision process (POMDP). Due to the large size of the state-space, the exact solution to the POMDP is computationally expensive. Hence, two popular approximate solutions are considered, which yield good power management policies for the transmission attempts. Monte Carlo simulation results illustrate the efficacy of the approach and show that the approximate solutions significantly outperform conventional approaches.

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Energy harvesting sensor (EHS) nodes provide an attractive and green solution to the problem of limited lifetime of wireless sensor networks (WSNs). Unlike a conventional node that uses a non-rechargeable battery and dies once it runs out of energy, an EHS node can harvest energy from the environment and replenish its rechargeable battery. We consider hybrid WSNs that comprise of both EHS and conventional nodes; these arise when legacy WSNs are upgraded or due to EHS deployment cost issues. We compare conventional and hybrid WSNs on the basis of a new and insightful performance metric called k-outage duration, which captures the inability of the nodes to transmit data either due to lack of sufficient battery energy or wireless fading. The metric overcomes the problem of defining lifetime in networks with EHS nodes, which never die but are occasionally unable to transmit due to lack of sufficient battery energy. It also accounts for the effect of wireless channel fading on the ability of the WSN to transmit data. We develop two novel, tight, and computationally simple bounds for evaluating the k-outage duration. Our results show that increasing the number of EHS nodes has a markedly different effect on the k-outage duration than increasing the number of conventional nodes.

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We consider a Gaussian multiple access channel (GMAC) where the users are sensor nodes powered by energy harvesters. The energy harvesters may have finite or infinite buffer to store the harvested energy. First, we find the capacity region of a GMAC powered by transmit nodes with an infinite energy buffer. Next, we consider a GMAC with the transmitting nodes equipped with a finite energy buffer. Initially we assume perfect knowledge of the buffer state information at both the encoders and the decoder. We provide an achievable region for this case. We also generalize the achievable region when only partial information about buffer state is available at both the encoders and the decoder.

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Environmental inputs can improve the level of innovation by interconnecting them with traditional inputs regarding the properties of materials and processes as a strategic eco-design procedure. Advanced engineered polymer composites are needed to meet the diverse needs of users for high-performance automotive, construction and commodity products that simultaneously maximize the sustainability of forest resources. In the current work, wood polymer composites (WPC) are studied to promote long-term resource sustainability and to decrease environmental impacts relative to those of existing products. A series of polypropylene wood–fiber composite materials having 20, 30, 40 and 50 wt. % of wood–fibers were prepared using twin-screw extruder and injection molding machine. Tensile and flexural properties of the composites were determined. Polypropylene (PP) as a matrix used in this study is a thermoplastic material, which is recyclable. Suitability of the prepared composites as a sustainable product is discussed.

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The structural, magnetic and dielectric properties of nano zinc ferrite prepared by the propellant chemistry technique are studied. The PXRD measurement at room temperature reveal that the compound is in cubic spinel phase, belong to the space group Fd (3) over barm. The unit cell parameters have been estimated from Rietveld refinement. The calculated force constants from FTIR spectrum corresponding to octahedral and tetrahedral sites at 375 and 542 cm(-1) are 6.61 x 10(2) and 3.77 x 10(2) N m(-1) respectively; these values are slightly higher compared to the other ferrite systems. Magnetic hysteresis and EPR spectra show superparamagnetic property nearly to room temperature due to comparison values between magnetic anisotropy energy and the thermal energy. The calculated values of saturation magnetization, remenant magnetization, coercive field and magnetic moment supports for the existence of multi domain particles in the sample. The temperature dependent magnetic field shows the spin freezing state at 30 K and the blocking temperature at above room temperature. The frequency dependent dielectric interactions show the variation of dielectric constant, dielectric loss and impedance as similar to other ferrite systems. The AC conductivity in the prepared sample is due to the presence of electrons, holes and polarons. The synthesized material is suitable for nano-electronics and biomedical applications. (C) 2014 Elsevier B.V. All rights reserved.

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Energy harvesting sensor nodes are gaining popularity due to their ability to improve the network life time and are becoming a preferred choice supporting green communication. In this paper, we focus on communicating reliably over an additive white Gaussian noise channel using such an energy harvesting sensor node. An important part of this paper involves appropriate modeling of energy harvesting, as done via various practical architectures. Our main result is the characterization of the Shannon capacity of the communication system. The key technical challenge involves dealing with the dynamic (and stochastic) nature of the (quadratic) cost of the input to the channel. As a corollary, we find close connections between the capacity achieving energy management policies and the queueing theoretic throughput optimal policies.

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In the immediate surroundings of our daily life, we can find a lot of places where the energy in the form of vibration is being wasted. Therefore, we have enormous opportunities to utilize the same. Piezoelectric character of matter enables us to convert this mechanical vibration energy into electrical energy which can be stored and used to power other device, instead of being wasted. This work is done to realize both actuator and sensor in a cantilever beam based on piezoelectricity. The sensor part is called vibration energy harvester. The numerical analyses were performed for the cantilever beam using the commercial package ANSYS and MATLAB. The cantilever beam is realized by taking a plate and fixing its one end between two massive plates. Two PZT patches were glued to the beam on its two faces. Experiments were performed using data acquisition system (DAQ) and LABVIEW software for actuating and sensing the vibration of the cantilever beam.