All Digital Energy Sensing for Minimum Energy Tracking

Minimizing energy consumption is of utmost importance in an energy starved system with relaxed performance requirements. This brief presents a digital energy sensing method that requires neither a constant voltage reference nor a time reference. An energy minimizing loop uses this to find the minimum energy point and sets the supply voltage between 0.2 and 0.5 V. Energy savings up to 1275% over existing minimum energy tracking techniques in the literature is achieved.

Modelling ternary effects on antiphase boundary energy of Ni3Al

The shearing of ordered gamma' precipitates by matrix dislocations results in the formation of antiphase boundaries (APB) in Ni-base superalloys. The APB energy is an important source of order-strengthening in disk and blade alloys where Ti and Ta substitute for Al in gamma'. While the importance of APB energy is well-acknowledged, the effect of alloying on APB energy is not fully understood. In the present study, the effect of Ti and Ta additions on the {111} and {010} APB energies was probed via electronic structure calculations. Results suggest that at low levels of Ti/Ta, APB energies on either plane increases with alloying. However, at higher Ti/Ta levels, the APB energies decrease with alloying. These trends understood by accounting for nearest neighbour violations about the APB and additionally, invoking the effect of precipitate composition on the energy penalty of the violations. We propose an Environment Dependent Nearest Neighbour Bond (EDNNB) model that predicts APB energies that are in close agreement to calculated values.

Performance Enhancement of Piezoelectric Energy Harvesters Using Multilayer and Multistep Beam Configurations

Low-power requirements of contemporary sensing technology attract research on alternate power sources that can replace batteries. Energy harvesters absorb ambient energy and function as power sources for sensors and other low-power devices. Piezoelectric bimorphs have been demonstrating the preeminence in converting the mechanical energy in ambient vibrations into electrical energy. Improving the performance of these harvesters is pivotal as the energy in ambient vibrations is innately low. In this paper, we focus on enhancing the performance of piezoelectric harvesters through a multilayer and, in particular, a multistep configuration. Partial coverage of piezoelectric material in steps along the length of a cantilever beam results in a multistep piezoelectric energy harvester. We also discuss obtaining an approximate deformation curve for the beam with multiple steps in a computationally efficient manner. We find that the power generated by a multistep beam is almost 90% more than that by a multilayer harvester made out of the same volume of polyvinylidinefluoride ( PVDF), further corroborated experimentally. Improvements observed in the power generated prove to be a boon for weakly coupled low profile piezoelectric materials. Thus, in spite of the weak piezoelectric coupling observed in PVDF, its energy harvesting capability can be improved significantly using it in a multistep piezoelectric beam configuration.

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

Role of stacking fault energy on texture evolution revisited

Three materials, pure aluminium, Al-4 wt.% Mg, alpha-brass have been chosen to understand the evolution of texture and microstructure during rolling. Pure Al develops a strong copper-type rolling texture and the deformation is entirely slip dominated. In Al-4Mg alloy, texture is copper-type throughout the deformation. The advent of Cu-type shear bands in the later stages of deformation has a negligible effect on the final texture. alpha-brass shows a characteristic brass-type texture from the early stages of rolling. Extensive twinning in the intermediate stages of deformation (epsilon(t) similar to 0.5) causes significant texture reorientation towards alpha-fiber. Beyond 40% reduction, deformation is dominated by Bs-type shear bands, and the banding coincides with the evolution of <111>parallel to ND components. The crystallites within the bands preferentially show <110>parallel to ND components. The absence of the Cu component throughout the deformation process indicates that, for the evolution of brass-type texture, the presence of Cu component is not a necessary condition. The final rolling texture is a synergistic effect of deformation twinning and shear banding.

Robust Whisper Activity Detection Using Long-Term Log Energy Variation of Sub-Band Signal

The goal in the whisper activity detection (WAD) is to find the whispered speech segments in a given noisy recording of whispered speech. Since whispering lacks the periodic glottal excitation, it resembles an unvoiced speech. This noise-like nature of the whispered speech makes WAD a more challenging task compared to a typical voice activity detection (VAD) problem. In this paper, we propose a feature based on the long term variation of the logarithm of the short-time sub-band signal energy for WAD. We also propose an automatic sub-band selection algorithm to maximally discriminate noisy whisper from noise. Experiments with eight noise types in four different signal-to-noise ratio (SNR) conditions show that, for most of the noises, the performance of the proposed WAD scheme is significantly better than that of the existing VAD schemes and whisper detection schemes when used for WAD.

Optical and dielectric study of strontium modified barium zirconium titanate ceramic prepared by high energy ball milling

Strontium modified barium zirconium titanate with general formula Ba1-xSrxZr0.05Ti0.95O3 ceramics have been prepared by solid state and high energy ball milling technique. The X-ray diffraction and Rietveld refinement studies show that all the compositions have single phase symmetry. The composition BaZr0.05Ti0.95O3 shows orthorhombic symmetric with space group Amm2. The structure changes from orthorhombic to tetragonal with strontium doping up to x = 0.3 and with further addition, changes to cubic. The scanning electron micrographs show that the grain size decreases with increase in strontium content. The temperature dependent dielectric behavior shows three phase transition in the parent material which merges with an increase in Sr content The transition temperature and dielectric constant decreases with an increase in Sr concentration. The phase transition becomes more diffused with increment in doping concentration. The ferroelectric behavior of the ceramics is studied by the hysteresis loop. The optical behavior is studied by the UV-visible spectroscopy and found that the optical band gap increases with Sr concentration. (C) 2015 Elsevier B.V. All rights reserved.

A TDMA-based Energy Aware MAC (TEA-MAC) Protocol for Reliable Multicast in WSNs

Multicast in wireless sensor networks (WSNs) is an efficient way to spread the same data to multiple sensor nodes. It becomes more effective due to the broadcast nature of wireless link, where a message transmitted from one source is inherently received by all one-hop receivers, and therefore, there is no need to transmit the message one by one. Reliable multicast in WSNs is desirable for critical tasks like code updation and query based data collection. The erroneous nature of wireless medium coupled with limited resource of sensor nodes, makes the design of reliable multicast protocol a challenging task. In this work, we propose a time division multiple access (TDMA) based energy aware media access and control (TEA-MAC) protocol for reliable multicast in WSNs. The TDMA eliminates collisions, overhearing and idle listening, which are the main sources of reliability degradation and energy consumption. Furthermore, the proposed protocol is parametric in the sense that it can be used to trade-off reliability with energy and delay as per the requirement of the underlying applications. The performance of TEA-MAC has been evaluated by simulating it using Castalia network simulator. Simulation results show that TEA-MAC is able to considerably improve the performance of multicast communication in WSNs.

Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-Offs and Optimal Design

Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.

Effects of instabilities and coherent structures on the performance of a thermocline based thermal energy storage

We investigate the transient dynamics of disturbances inside a thermocline based molten salt thermal energy storage (TES). Numerical simulations were conducted with four inlet flow configurations. The disturbances introduced at the inlet grow via Rayleigh Taylor instability. The formed vortical motions inside the tank propagate downstream and destroy the thermocline. The vortex-thermocline interaction upsets the stratification inside the TES. The disturbance growth rate, penetration length and vortex Reynolds number are measured. The growth of penetration length prior to the vortex-thermocline interaction is quadratic. The vortex Reynolds number of the eddy which causes thermocline breakdown increases with increase in Atwood number. The impingement of vortex on thermocline is studied. (C) 2015 Elsevier Ltd. All rights reserved.

Energy-savvy solid-state and sonochemical synthesis of lithium sodium titanate as an anode active material for Li-ion batteries

Lithium sodium titanate insertion-type anode has been synthesized by classical solid-state (dry) and an alternate solution-assisted (wet) sonochemical synthesis routes. Successful synthesis of the target compound has been realized using simple Na- and Li-hydroxide salts along with titania. In contrast to the previous reports, these energy-savvy synthesis routes can yield the final product by calcination at 650 -750 degrees C for limited duration of 1-10 h. Owing to the restricted calcination duration (dry route for 1-2 h and wet route for 1-5 h), they yield homogeneous nanoscale lithium sodium titanate particles. Sono-chemical synthesis reduces the lithium sodium titanate particle size down to 80-100 nm vis-a-vis solid-state method delivering larger (200-500 nm) particles. Independent of the synthetic methods, the end products deliver reversible electrochemical performance with reversible capacity exceeding 80 mAh.g(-1) acting as a 1.3 V anode for Li-ion batteries. (C) 2015 Elsevier B.V. All rights reserved.

Three-Dimensional Nanoarchitecture of BiFeO3 Anchored TiO2 Nanotube Arrays for Electrochemical Energy Storage and Solar Energy Conversion

Here, we report the synthesis of TiO2/BiFeO3 nano-heterostnicture (NH) arrays by anchoring BiFeO3 (BFO) particles on on TiO2 nanotube surface and investigate their pseudocapacitive and photoelectrochemical properties considering their applications in green energy fields. The unique TiO2/BFO NHs have been demonstrated both as energy conversion and storage materials. The capacitive behavior of the NHs has been found to be significantly higher than that of the pristine TiO2 NTs, which is mainly due to the anchoring of redox active BFO nanoparticles. A specific capacitance of about 440 F g(-1) has been achieved for this NHs at a current density of 1.1 A g(-1) with similar to 80% capacity retention at a current density of 2.5 A g(-1). The NHs also exhibit high energy and power performance (energy density of 46.5 Wh kg(-1) and power density of 1.2 kW kg(-1) at a current density of 2.5 A g(-1)) with moderate cycling stability (92% capacity retention after 1200 cycles). Photoelectrochemical investigation reveals that the photocurrent density of the NHs is almost 480% higher than the corresponding dark current and it shows significantly improved photoswitching performance as compared to pure TiO2 nanotubes, which has been demonstrated based the interfacial type-II band alignment between TiO2 and BFO.

Tailoring energy absorption capacity of CNT forests through application of electric field

This study examines the effect of electric field on energy absorption capacity of carbon nanotube forests (CNTFs), comprising of vertically aligned multiwalled carbon nanotubes, under both quasistatic (strain rate, (epsilon) over dot = 10(-3) s(-1)) and dynamic ((epsilon) over dot = similar to 10(3) s(-1)) loading conditions. Under quasistatic condition, the CNTFs were cyclically loaded and unloaded while electric field was applied along the length of carbon nanotube (CNT) either throughout the loading cycle or explicitly during either the loading or the unloading segment. The energy absorbed per cycle by CNTF increased monotonically with electric field when the field was applied only during the loading segment: A 7 fold increase in the energy absorption capacity was registered at an electric field of 1 kV/m whereas no significant change in it was noted for other schemes of electro-mechanical loading. The energy absorption capacity of CNTF under dynamic loading condition also increased monotonically with electric field; however, relative to the quasistatic condition, less pronounced effect was observed. This intriguing strain rate dependent effect of electric field on energy absorption capacity of CNTF is explained in terms of electric field induced strengthening of CNTF, originating from the time dependent electric field induced polarization of CNT. (C) 2015 Elsevier Ltd. All rights reserved.