An Energy Efficient Mac Layer Design for Wireless Sensor Network

Recent technological advances in sensors, low power integrated circuits, and wireless communications have enabled the design of low-cost, lightweight, and intelligent wireless sensor nodes. The IEEE 802.15.4 standard is a specific Wireless Personal Area Network (WPAN) standard designed for various wireless sensor applications. Idle listening, packet collision, control packet overhead and overhearing are considered as energy consuming resources in WSNs. As the idle listening and packet collision are two major power consuming parts, we considered two solutions for reducing both of them to achieve an energy efficient protocol. We concentrate on the MAC layer design to overcome the energy consumption by radio management procedure and the backoff exponent mechanism. In the radio management, we analyze the contention part of the active duration of the MAC IEEE 802.15.4 standard superframe and allow nodes to enter the sleep state regarding to their available data for transmission instead of staying awake for the entire active period. This method will be useful especially when sensors do not have any data to send. The proposed non-persistent Carrier Sense Multiple Access (np-CSMA) protocol employs backoff exponent management mechanism. This algorithm helps the network to be reliable under traffic changes and saves more energy by avoiding collision. It assigns different range of BE (backoff exponent) to each node with respect to node’s contribution in network traffic. In our scheme a coordinator can observe the network traffic due to the data information associated with devices. It can manage the Personal Area Networks (PANs) devices by the beacon packet to go to sleep mode when they do not have any packet to send. In this thesis, by using the sleep period together with backoff exponent management in our protocol design, the amount of energy consumption will be reduced. The proposed model has been compared to original 802.15.4 standard and the existing Adaptive Backoff Exponent (ABE) MAC protocol to illustrate the improvement. Moreover, the BE management algorithm derives better system performance such as end-to-end delay, throughput, packet delivery ratio and Link Quality Indicator (LQI). The proposed model has been designed in such a way that the introduction of extra sleep period inserted in superframe improves the energy efficiency while maintaining other system performance parameters. The proposed MAC protocol has improved the energy consumption around 60% as compared to ABE-MAC. The proposed MAC protocol with an extra radio management technique together with backoff management procedure can achieve 70% more energy saving than MAC IEEE 802.15.4 standard

Rapid and efficient determination of zinc in water samples by graphite furnace atomic absorption spectrometry after homogeneous liquid-liquid microextraction via flotation assistance

ABSTRACT. A new application of homogeneous liquid–liquid microextraction via flotation assistance (HLLME-FA) has been developed for the determination of Zn(II) in the water samples by using graphite furnace atomic absorption spectrometry (GFAAS). 1-(2-Pyridylazo)-2-naphthol (PAN) was used as a chelating reagent. In this work, low density organic solvent was used as an extraction solvent and no centrifugation was required in this method. A special extraction cell was designed to facilitate collection of the low density extraction solvent. The predominant parameters influencing the HLLME-FA procedure, such as solution pH, concentration of PAN, extraction and homogeneous solvent types and volumes, ionic strength, and extraction time have been optimized. Applying all the optimum conditions in the process, the detection limit of 0.1 μg/L, linear range of 0.5–200 μg/L, and the precision (RSD%, n = 10) of 5.7% were obtained for zinc. The proposed procedure showed satisfactory results for the analysis of tap water, well water and sea water.                 KEY WORDS: Homogeneous liquid-liquid microextraction, Flotation assistance, Zinc, Graphite furnace atomic absorption spectrometry, Water samples Bull. Chem. Soc. Ethiop. 2022, 36(1), 1-11.                                                                     DOI:  https://dx.doi.org/10.4314/bcse.v36i1.

Compact integrated microchannel combustor, recuperator and heat exchanger For hydrogen storage applications

A novel microscale combustor-heat exchanger (μCHX) for hydrogen storage applications is presented in this dissertation. The design of the μCHX is motivated by its application to two particular systems for automotive use- those that utilize metal hydrides (MH) and cryo-adsorbents (CA) to store hydrogen. Thermal energy needs to be supplied to the MH bed to raise its temperature to 170 °C in order to desorb hydrogen for use in a fuel cell. On the other hand, in a CA system, hydrogen gas that exits the storage tank needs to be heated to a minimum temperature of -40 °C prior to entering the fuel cell. During cold start conditions, heat exchange with ambient air or with the fuel cell coolant is insufficient to provide this minimum temperature, thereby requiring an additional source of thermal energy. For both storage systems, the required thermal energy can be provided by oxidizing a small amount of hydrogen and transferring the heat from combustion to the working fluid, which is an oil in a MH system and hydrogen in a CA system. The μCHX presented herein is a compact and highly efficient way of providing the required thermal energy rate. The µCHX is comprised of repeating unit cells that each perform identical unit operations, namely (a) catalytic combustion of a hydrogen-air mixture, (b) transfer of produced thermal energy rate to a heat transfer fluid, and (c) recuperation between the exhaust gas stream and incoming reactant gases. Heterogeneous catalytic combustion occurs on the walls of microchannels in the presence of a platinum catalyst. A multi-kilowatt µCHX device can be achieved by having multiple unit cells with appropriate fluidic distribution headers. The µCHX design is common for both hydrogen storage systems with minor changes. The design of the µCHX is performed using computational fluid dynamics simulations (CFD) at the unit cell and device level. At the unit cell level, the performance is documented using validated CFD simulations for variations in geometric and fluidic parameters. Varied geometric parameters include the length and location of the catalyst bed, length of the device, and the height of the combustion channel. Varied fluidic parameters include the working fluid inlet temperature, flow rates of the working fluid and reactants, and the equivalence ratio of the reactants. Performance is characterized using a global efficiency, heat transfer effectiveness and hydrogen conversion. The parametric variations are captured non-dimensionally as variations in Damkohler and Peclet numbers, which are in turn used to describe the changes in hydrogen conversion and efficiency. Performance maps for hydrogen conversion and pressure drop in the combustion channel are presented based on values of the Damkohler and Peclet numbers and regions of desired operability of the combustor are identified. For the CA µCHX, it is shown that with the help of a novel distributed catalyst arrangement, extinction of the reaction due to the cold gas stream is prevented and hydrogen conversion in excess of 95 percent is achieved for a range of operating conditions. Comparisons between simulations and experiments are not performed since, in the simulations, (a) ideal catalyst activity and surface distribution are assumed, and (b) the effect of substrate conduction is not considered. At the device level, three dimensional simulations of fluid flow are performed to ensure uniformity in flow distribution while maintaining low pressure drop through the device. Fabrication constraints are also incorporated into the device level design and simulations. A multi-watt CA µCHX consisting of 16 unit cells is experimental characterized using nitrogen as a surrogate heat exchange fluid. In experiments, a total catalyst length of 22.5 mm is used instead of 12.5 mm (which was used for the simulations) to account for reduced catalyst activity from the simulated ideal case. Experimental results show that hydrogen residence time and body temperature have significant effects on the overall efficiency of the device. Conversions as high as 94.1% and efficiencies as high as 88.3% are achieved. Highest hydrogen conversion is recorded at an equivalence ratio of 0.6

Prediction of Thermo-Physical Properties of TiO2-Al2O3/Water Nanoparticles by Using Artificial Neural Network

In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. View Full-Tex

Microplastics in Aquatic Environments: Recent Advances in Separation Techniques

Separation and removal of microplastic pollution from aquatic environments as a global environmental issue is classified as one of the major concerns in both water and wastewater treatment plants. Microplastics as polymeric particles less than 5 mm in at least one dimension are found with different shapes, chemical compositions, and sizes in soil, water, and sediments. Conventional treatment methods for organic separation have shown high removal efficiency for microplastics, while the separation of small microplastic particles, mainly less than 100 µm, in wastewater treatment plants is particularly challenging. This review aims to review the principle and application of different physical and chemical methods for the separation and removal of microplastic particles from aquatic environments, especially in water treatments process, with emphasis on some alternative and emerging separation methods. Advantages and disadvantages of conventional separation techniques such as clarification, sedimentation, floatation, activated sludge, sieving, filtration, and density separation are discussed. The advanced separation methods can be integrated with conventional techniques or utilize as a separate step for separating small microplastic particles. These advanced microplastic separation methods include membrane bioreactor, magnetic separation, micromachines, and degradation-based methods such as electrocatalysis, photocatalysis, biodegradation, and thermal degradation

Ethanol production from sugarcane bagasse by means of on-site produced and commercial enzymes; a comparative study

In this study ethanol was produced without using expensive commercial enzymes from sugarcane bagasse. Alkali pretreatment was used to prepare biomass before enzymatic hydrolysis. The comparison between NaOH, KOH and Ca(OH)_2 revealed that NaOH has been more effective on bagasse structure. The required enzymes for biomass hydrolysis were produced by bagasse solid state fermentation using three fungi: Trichoderma longibrachiatum, T. reesei and Aspergillus niger. Results indicated enzyme solution produced by A. niger has functioned better than the other two in cellulose conversion during sole hydrolysis. Ethanol was produced by simultaneous saccharification and fermentation (SSF) with on-site prepared crude enzyme solutions and yeast Saccharomyces cerevisiae. Here, T. longibrachiatum had the best performance in ethanol production. To evaluate this procedure, SSF of pretreated bagasse applying Celluclast 1.5L by Novozymes was also investigated. The yield of ethanol production by commercial enzyme and T. longibrac hiatum enzyme solution were 81% and 52.5% respectively

Effect of Freezing Stress on Lipid Peroxidation and Antioxidant Enzyme Activities of Olive cvs. ‘Fishomi’ and ‘Roughani’

Changes in freezing injury percentage, lipid peroxidation (malonaldehyde formation), antioxidant enzymes activity and proline content were monitored in the leaves of olive cvs. ‘Fishomi’ and ‘Roughani’ under different freezing temperatures (-5, -10, -15 and -20°C for 10 h). The results showed that freezing injury (determined by electrolyte leakage analysis) and malonaldehyde (MDA) content of cv. ‘Fishomi’ were significantly lower than of cv. ‘Roughani’ ones. The activities of peroxidase (POD), catalase (CAT), ascorbate peroxidase (APX) and polyphenol oxidase (PPO) enzymes of cv. ‘Fishomi’ were signifi cantly higher than those of cv. ‘Roughani’. However, superoxide dismutase (SOD) activity of cv. ‘Roughani’ was higher than of cv. ‘Fishomi’. The proline accumulated in leaves of cv. ‘Fishomi’ was significantly higher than of cv. ‘Roughani’ during freezing stress. The results demonstrated that freezing injury percentage was positively correlated with ion leakage percentage and MDA content in both cultivars. In contrast, SOD, APX and CAT activities and also proline content were negatively correlated with freezing injury percentage. There was a significant negative correlation between PPO activity and freezing injury in cv. ‘Fishomi’. It can be concluded that the lower freezing injury percentage, ion leakage, and MDA content followed by the higher antioxidant enzyme activates as well as proline content in cv. ‘Fishomi’ is a consequence of more effective protective mechanisms

Dynamic electricity pricing for electric vehicles using stochastic programming

Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, departure time and location. In smart grids, the electricity demand can be controlled via Demand Response (DR) programs. Smart charging and vehicle-to-grid seem highly promising methods for EVs control. However, high capital costs remain a barrier to implementation. Meanwhile, incentive and price-based schemes that do not require high level of control can be implemented to influence the EVs’ demand. Having effective tools to deal with the increasing level of uncertainty is increasingly important for players, such as energy aggregators. This paper formulates a stochastic model for day-ahead energy resource scheduling, integrated with the dynamic electricity pricing for EVs, to address the challenges brought by the demand and renewable sources uncertainty. The two-stage stochastic programming approach is used to obtain the optimal electricity pricing for EVs. A realistic case study projected for 2030 is presented based on Zaragoza network. The results demonstrate that it is more effective than the deterministic model and that the optimal pricing is preferable. This study indicates that adequate DR schemes like the proposed one are promising to increase the customers’ satisfaction in addition to improve the profitability of the energy aggregation business.info:eu-repo/semantics/acceptedVersio