Algorithm for Estimation of Electricity Consumption Reduction by Using Variable Frequency Drive of Main Line Pumps

The article is about using of variable frequency drives for reduction oil pumping main line pumps energy consumption. Block diagram of developed computer program is shown in the article. The computer program allows to determine the reduction of energy consumption and to estimate payback period of variable frequency drives.

Significance of size reduction in solid waste management /

Mode of access: Internet.

Preparation of high purity ZnO nanobelts by thermal evaporation of ZnS

High purity one-dimensional ZnO nanobelts were synthesized by thermally evaporating commercial ZnS powders in a hydrogen-oxygen mixture gas at 1050 degrees C. It was found that these ZnO nanobelts had a single crystal hexagonal wurtzite structure growing along the [0001] direction. They had a rectangle-shaped cross-section with typical widths of 20 to 100 nanometers and lengths of up to hundreds of micrometers with lattice constants of a = 0.325 nm and c = 0.520 nm. The self-catalytic hydrogen-oxygen assisted growth of ZnO nanobelt is discussed. The photoluminescence (PL) characterization of the ZnO nanobelts shows strong near-band UV emission (about 383 nm) and one broad peak at 501 nm, which indicates that the ZnO nanobelts have good potential application in optoelectronic devices.

Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

Understanding changes in mobility & subsistence from terminal Pleistocene to Late Holocene in the highlands of New Guinea through intensity of lithic reduction, changing site types, and paleoclimate

Thesis (Ph.D.)--University of Washington, 2016-08

Phase noise and spur reduction in an array of direct digital synthesizers

Many applications, including communications, test and measurement, and radar, require the generation of signals with a high degree of spectral purity. One method for producing tunable, low-noise source signals is to combine the outputs of multiple direct digital synthesizers (DDSs) arranged in a parallel configuration. In such an approach, if all noise is uncorrelated across channels, the noise will decrease relative to the combined signal power, resulting in a reduction of sideband noise and an increase in SNR. However, in any real array, the broadband noise and spurious components will be correlated to some degree, limiting the gains achieved by parallelization. This thesis examines the potential performance benefits that may arise from using an array of DDSs, with a focus on several types of common DDS errors, including phase noise, phase truncation spurs, quantization noise spurs, and quantizer nonlinearity spurs. Measurements to determine the level of correlation among DDS channels were made on a custom 14-channel DDS testbed. The investigation of the phase noise of a DDS array indicates that the contribution to the phase noise from the DACs can be decreased to a desired level by using a large enough number of channels. In such a system, the phase noise qualities of the source clock and the system cost and complexity will be the main limitations on the phase noise of the DDS array. The study of phase truncation spurs suggests that, at least in our system, the phase truncation spurs are uncorrelated, contrary to the theoretical prediction. We believe this decorrelation is due to the existence of an unidentified mechanism in our DDS array that is unaccounted for in our current operational DDS model. This mechanism, likely due to some timing element in the FPGA, causes some randomness in the relative phases of the truncation spurs from channel to channel each time the DDS array is powered up. This randomness decorrelates the phase truncation spurs, opening the potential for SFDR gain from using a DDS array. The analysis of the correlation of quantization noise spurs in an array of DDSs shows that the total quantization noise power of each DDS channel is uncorrelated for nearly all values of DAC output bits. This suggests that a near N gain in SQNR is possible for an N-channel array of DDSs. This gain will be most apparent for low-bit DACs in which quantization noise is notably higher than the thermal noise contribution. Lastly, the measurements of the correlation of quantizer nonlinearity spurs demonstrate that the second and third harmonics are highly correlated across channels for all frequencies tested. This means that there is no benefit to using an array of DDSs for the problems of in-band quantizer nonlinearities. As a result, alternate methods of harmonic spur management must be employed.

Down scaling to regional assessment of greenhouse gas emissions to enable consistency in accounting for emissions reduction projects and national inventory accounts for northern beef production in Australia

This paper explores the effect of using regional data for livestock attributes on estimation of greenhouse gas (GHG) emissions for the northern beef industry in Australia, compared with using state/territory-wide values, as currently used in Australia’s national GHG inventory report. Regional GHG emissions associated with beef production are reported for 21 defined agricultural statistical regions within state/territory jurisdictions. A management scenario for reduced emissions that could qualify as an Emissions Reduction Fund (ERF) project was used to illustrate the effect of regional level model parameters on estimated abatement levels. Using regional parameters, instead of state level parameters, for liveweight (LW), LW gain and proportion of cows lactating and an expanded number of livestock classes, gives a 5.2% reduction in estimated emissions (range +12% to –34% across regions). Estimated GHG emissions intensity (emissions per kilogram of LW sold) varied across the regions by up to 2.5-fold, ranging from 10.5 kg CO2-e kg–1 LW sold for Darling Downs, Queensland, through to 25.8 kg CO2-e kg–1 LW sold for the Pindan and North Kimberley, Western Australia. This range was driven by differences in production efficiency, reproduction rate, growth rate and survival. This suggests that some regions in northern Australia are likely to have substantial opportunities for GHG abatement and higher livestock income. However, this must be coupled with the availability of management activities that can be implemented to improve production efficiency; wet season phosphorus (P) supplementation being one such practice. An ERF case study comparison showed that P supplementation of a typical-sized herd produced an estimated reduction of 622 t CO2-e year–1, or 7%, compared with a non-P supplemented herd. However, the different model parameters used by the National Inventory Report and ERF project means that there was an anomaly between the herd emissions for project cattle excised from the national accounts (13 479 t CO2-e year–1) and the baseline herd emissions estimated for the ERF project (8 896 t CO2-e year–1) before P supplementation was implemented. Regionalising livestock model parameters in both ERF projects and the national accounts offers the attraction of being able to more easily and accurately reflect emissions savings from this type of emissions reduction project in Australia’s national GHG accounts.

Reduction capability of soil humic substances from the Rio Negro basin, Brazil, towards Hg(II) studied by a multimethod approach and principal component analysis (PCA)

This paper characterizes humic substances (HS) extracted from soil samples collected in the Rio Negro basin in the state of Amazonas, Brazil, particularly investigating their reduction capabilities towards Hg(II) in order to elucidate potential mercury cycling/volatilization in this environment. For this reason, a multimethod approach was used, consisting of both instrumental methods (elemental analysis, EPR, solid-state NMR, FIA combined with cold-vapor AAS of Hg(0)) and statistical methods such as principal component analysis (PCA) and a central composite factorial planning method. The HS under study were divided into groups, complexing and reducing ones, owing to different distribution of their functionalities. The main functionalities (cor)related with reduction of Hg(II) were phenolic, carboxylic and amide groups, while the groups related with complexation of Hg(II) were ethers, hydroxyls, aldehydes and ketones. The HS extracted from floodable regions of the Rio Negro basin presented a greater capacity to retain (to complex, to adsorb physically and/or chemically) Hg(II), while nonfloodable regions showed a greater capacity to reduce Hg(II), indicating that HS extracted from different types of regions contribute in different ways to the biogeochemical mercury cycle in the basin of the mid-Rio Negro, AM, Brazil. (c) 2007 Published by Elsevier B.V.

Microstructure, vibrational and visible emission properties of low frequency ultrasound (42 kHz) assisted ZnO nanostructures

Size and shape tuneable ZnO nanostructures were prepared by a low frequency ultrasound (42 kHz) route using various organic solvents as the reaction media. The crystalline nature, lattice parameters and microstructural parameters such as microstrain, stress and energy density of the prepared ZnO nanostructures were revealed through X-ray diffraction (XRD) analysis. The organic solvents influenced the size and morphology of the ZnO nanostructures, and interesting morphological changes involving a spherical to triangular shaped transition were observed. The visible emission properties and lattice vibrational characteristics of the nanostructures were drastically modified by the changes in size and shape. Raman spectral measurements revealed the presence of multiphonon processes in the ZnO nanostructures. The intensity of the visible emission band was found to vary with the size and morphology of the structures. The strongest visible emission band corresponded to the structure with the largest surface/volume ratio and could be attributed to surface oxygen vacancies. The control over the size and morphology of ZnO nanostructures has been presented as a means of determining the intensity of the visible emission band

Enhanced electrocatalytic activity of Au@Cu core@shell nanoparticles towards CO2 reduction

The development of technologies for the recycling of carbon dioxide into carbon-containing fuels is one of the major challenges in sustainable energy research. Two of the main current limitations are the poor efficiency and fast deactivation of catalysts. Core–shell nanoparticles are promising candidates for enhancing challenging reactions. In this work, Au@Cu core–shell nanoparticles with well-defined surface structures were synthesized and evaluated as catalysts for the electrochemical reduction of carbon dioxide in neutral medium. The activation potential, the product distribution and the long term durability of this catalyst were assessed by electrochemical methods, on-line electrochemical mass spectrometry (OLEMS) and on-line high performance liquid chromatography. Our results show that the catalytic activity and the selectivity can be tweaked as a function of the thickness of Cu shells. We have observed that the Au cubic nanoparticles with 7–8 layers of copper present higher selectivity towards the formation of hydrogen and ethylene; on the other hand, we observed that Au cubic nanoparticles with more than 14 layers of Cu are more selective towards the formation of hydrogen and methane. A trend in the formation of the gaseous products can be also drawn. The H2 and CH4 formation increases with the number of Cu layers, while the formation of ethylene decreases. Formic acid was the only liquid species detected during CO2 reduction. Similar to the gaseous species, the formation of formic acid is strongly dependent on the number of Cu layers on the core@shell nanoparticles. The Au cubic nanoparticles with 7–8 layers of Cu showed the largest conversion of CO2 to formic acid at potentials higher than 0.8 V vs. RHE. The observed trends in reactivity and selectivity are linked to the catalyst composition, surface structure and strain/electronic effects.

Development of antibacterial ZnO-loaded cotton fabric based on in situ fabrication

A method provided for the deposition of nanostructured ZnO on cotton fabric to introduce antibacterial functionality was presented in this article. This strategy enabled fabric to be coated with inorganic-based functional materials through in situ synthesis of nanoparticles using ultrasonic irradiation. The amino-terminated silicon sol (AEAPTS) was employed to generate nanostructured ZnO, and the mechanism of the ultrasound-assisted coating was proposed. Antibacterial activities, UV protection and other properties of ZnO-loaded cotton characterized by SEM, FTIR, XRD and TGA were investigated. The results indicated that ZnO-loaded cotton exhibited excellent UV protective property, efficient antibacterial activities, well water-resistant effect, together with moderate cytotoxicity against L929 and lower tensile strength. The developed method provides not only a facile way for in situ synthesis of ZnO on textile but also the production of antibacterial materials for healthcare applications.

Multi-functional electrocatalysts for CO2 reduction reaction: towards the modulation of selectivity

The electrocatalytic reduction of CO2 (CO2RR) is a captivating strategy for the conversion of CO2 into fuels, to realize a carbon neutral circular economy. In the recent years, research has focused on the development of new materials and technology capable of capturing and converting CO2 into useful products. The main problem of CO2RR is given by its poor selectivity, which can lead to the formation of numerous reaction products, to the detriment of efficiencies. For this reason, the design of new electrocatalysts that selectively and efficiently reduce CO2 is a fundamental step for the future exploitation of this technology. Here we present a new class of electrocatalysts, designed with a modular approach, namely, deriving from the combination of different building blocks in a single nanostructure. With this approach it is possible to obtain materials with an innovative design and new functionalities, where the interconnections between the various components are essential to obtain a highly selective and efficient reduction of CO2, thus opening up new possibilities in the design of optimized electrocatalytic materials. By combining the unique physic-chemical properties of carbon nanostructures (CNS) with nanocrystalline metal oxides (MO), we were able to modulate the selectivity of CO2RR, with the production of formic acid and syngas at low overpotentials. The CNS have not only the task of stabilizing the MO nanoparticles, but the creation of an optimal interface between two nanostructures is able to improve the catalytic activity of the active phase of the material. While the presence of oxygen atoms in the MO creates defects that accelerate the reaction kinetics and stabilize certain reaction intermediates, selecting the reaction pathway. Finally, a part was dedicated to the study of the experimental parameters influencing the CO2RR, with the aim of improving the experimental setup in order to obtain commercial catalytic performances.

Transmission Of Intra-cellular Genetic Information: A System Proposal.

One of the great challenges of the scientific community on theories of genetic information, genetic communication and genetic coding is to determine a mathematical structure related to DNA sequences. In this paper we propose a model of an intra-cellular transmission system of genetic information similar to a model of a power and bandwidth efficient digital communication system in order to identify a mathematical structure in DNA sequences where such sequences are biologically relevant. The model of a transmission system of genetic information is concerned with the identification, reproduction and mathematical classification of the nucleotide sequence of single stranded DNA by the genetic encoder. Hence, a genetic encoder is devised where labelings and cyclic codes are established. The establishment of the algebraic structure of the corresponding codes alphabets, mappings, labelings, primitive polynomials (p(x)) and code generator polynomials (g(x)) are quite important in characterizing error-correcting codes subclasses of G-linear codes. These latter codes are useful for the identification, reproduction and mathematical classification of DNA sequences. The characterization of this model may contribute to the development of a methodology that can be applied in mutational analysis and polymorphisms, production of new drugs and genetic improvement, among other things, resulting in the reduction of time and laboratory costs.

Effects Of High Pressure Homogenization On The Activity, Stability, Kinetics And Three-dimensional Conformation Of A Glucose Oxidase Produced By Aspergillus Niger.

High pressure homogenization (HPH) is a non-thermal method, which has been employed to change the activity and stability of biotechnologically relevant enzymes. This work investigated how HPH affects the structural and functional characteristics of a glucose oxidase (GO) from Aspergillus niger. The enzyme was homogenized at 75 and 150 MPa and the effects were evaluated with respect to the enzyme activity, stability, kinetic parameters and molecular structure. The enzyme showed a pH-dependent response to the HPH treatment, with reduction or maintenance of activity at pH 4.5-6.0 and a remarkable activity increase (30-300%) at pH 6.5 in all tested temperatures (15, 50 and 75°C). The enzyme thermal tolerance was reduced due to HPH treatment and the storage for 24 h at high temperatures (50 and 75°C) also caused a reduction of activity. Interestingly, at lower temperatures (15°C) the activity levels were slightly higher than that observed for native enzyme or at least maintained. These effects of HPH treatment on function and stability of GO were further investigated by spectroscopic methods. Both fluorescence and circular dichroism revealed conformational changes in the molecular structure of the enzyme that might be associated with the distinct functional and stability behavior of GO.

Islet Neogenesis-associated Protein (ingap): The Role Of Its Endogenous Production As A Positive Modulator Of Insulin Secretion.

Islet neogenesis-associated protein (INGAP) is a peptide found in pancreatic exocrine-, duct- and islet- non-β-cells from normal hamsters. Its increase induced by either its exogenous administration or by the overexpression of its gene enhances β-cell secretory function and increases β-cell mass by a combination of stimulation of cell replication and islet neogenesis and reduction of β-cell apoptosis. We studied the potential modulatory role of endogenous INGAP in insulin secretion using two different experimental approaches. Hamster islets transfected with INGAP-small interfering RNA (INGAP-siRNA) were used to study glucose-stimulated insulin secretion (GSIS). In parallel, freshly isolated islets were incubated with high glucose and the same concentration of either a specific anti-INGAP rabbit serum or normal rabbit serum. INGAP-siRNA transfected islets reduced their INGAP mRNA and protein content by 35.1% and 47.2%, respectively whereas GSIS decreased by 25.8%. GSIS by transfected islets attained levels comparable to those recorded in control islets when INGAP pentadecapeptide (INGAP-PP) was added to the culture medium. INGAP antibody in the medium decreased significantly GSIS in a dose-dependent manner. These results indicate that endogenous INGAP plays a physiological positive modulatory role in insulin secretion, supporting its possible use in the treatment of prediabetes and Type 2 diabetes.