This paper contributes to the AC small signal modeling and analysis of Z source converter (ZSC) in continuous conduction mode. The AC small signal model considers the dynamics introduced by Z network uniquely contained in ZSC. AC small signal model of ZSC is derived and computer simulation results are used to validate the small signal modeling method. Various applications of the AC small signal models to ZSC design and experimental verifications are presented.
Low carbon dioxide (CO ) emissions are the foundation on which to realize the sustainable development of a green China. Recently in Beijing, the capital of China, serious environmental pollution-climate anomaly, severe haze and human sub-health have been accorded more importance. This study examines the energy-related CO emissions generated by Beijing industries from 2000 to 2010 by using an input–output analysis method. The direct, indirect and total CO emissions of sectors in Beijing were calculated. In addition, structural decomposition analysis (SDA) was conducted to evaluate the driving factors from the perspective of technology, sectoral connection, economic structure and economic scale. The results show that the growth rate of sectoral CO emissions in Beijing has drastically increased during this time with a moderate decline during 2007–2010. The metal and non-metal mining industries, the electric power, gas and water supply sector and the construction industry caused the most CO emissions. The economic structure change and the rapid economic growth led to the significant increase in CO emissions growth in Beijing. Thus, optimizing the economic structure and improving the technology are important to alleviate CO emissions. Although we can currently appropriately utilize fossil fuels, further research on new energy and clean development, as well as enhanced government management strength is required to reduce CO emissions.
Abstract A non-linear poroelastic finite element model of the lumbar spine was developed to investigate spinal response during daily dynamic physiological activities. Swelling was simulated by imposing a boundary pore pressure of 0.25 MPa at all external surfaces. Partial saturation of the disc was introduced to circumvent the negative pressures otherwise computed upon unloading. The loading conditions represented a pre-conditioning full day followed by another day of loading: 8 h rest under a constant compressive load of 350 N, followed by 16 h loading phase under constant or cyclic compressive load varying in between 1000 and 1600 N. In addition, the effect of one or two short resting periods in the latter loading phase was studied. The model yielded fairly good agreement with in-vivo and in-vitro measurements. Taking the partial saturation of the disc into account, no negative pore pressures were generated during unloading and recovery phase. Recovery phase was faster than the loading period with equilibrium reached in only ∼3 h. With time and during the day, the axial displacement, fluid loss, axial stress and disc radial strain increased whereas the pore pressure and disc collagen fiber strains decreased. The fluid pressurization and collagen fiber stiffening were noticeable early in the morning, which gave way to greater compression stresses and radial strains in the annulus bulk as time went by. The rest periods dampened foregoing differences between the early morning and late in the afternoon periods. The forgoing diurnal variations have profound effects on lumbar spine biomechanics and risk of injury.
Energy consumption has always been a central issue for sustainable urban assessment and planning. Different forms of energy analysis can provide various insights for energy policy making. This paper brought together three approaches for energy consumption accounting, i.e., energy flow analysis (EFA), input–output analysis (IOA) and ecological network analysis (ENA), and compared their different perspectives and the policy implications for urban energy use. Beijing was used to exemplify the different energy analysis processes, and the 42 economic sectors of the city were aggregated into seven components. It was determined that EFA quantifies both the primary and final energy consumption of the urban components by tracking the different types of fuel used by the urban economy. IOA accounts for the embodied energy consumption (direct and indirect) used to produce goods and services in the city, whereas the control analysis of ENA quantifies the specific embodied energy that is regulated by the activities within the city’s boundary. The network control analysis can also be applied to determining which economic sectors drive the energy consumption and to what extent these sectors are dependent on each other for energy. So-called “controlled energy” is a new concept that adds to the analysis of urban energy consumption, indicating the adjustable energy consumed by sectors. The integration of insights from all three accounting perspectives further our understanding of sustainable energy use in cities.
We describe here the implementation of the statistical total correlation spectroscopy (STOCSY) analysis method for aiding the identification of potential biomarker molecules in metabonomic studies based on NMR spectroscopic data. STOCSY takes advantage of the multicollinearity of the intensity variables in a set of spectra (in this case 1H NMR spectra) to generate a pseudo-two-dimensional NMR spectrum that displays the correlation among the intensities of the various peaks across the whole sample. This method is not limited to the usual connectivities that are deducible from more standard two-dimensional NMR spectroscopic methods, such as TOCSY. Moreover, two or more molecules involved in the same pathway can also present high intermolecular correlations because of biological covariance or can even be anticorrelated. This combination of STOCSY with supervised pattern recognition and particularly orthogonal projection on latent structure-discriminant analysis (O-PLS-DA) offers a new powerful framework for analysis of metabonomic data. In a first step O-PLS-DA extracts the part of NMR spectra related to discrimination. This information is then cross-combined with the STOCSY results to help identify the molecules responsible for the metabolic variation. To illustrate the applicability of the method, it has been applied to 1H NMR spectra of urine from a metabonomic study of a model of insulin resistance based on the administration of a carbohydrate diet to three different mice strains (C57BL/6Oxjr, BALB/cOxjr, and 129S6/SvEvOxjr) in which a series of metabolites of biological importance can be conclusively assigned and identified by use of the STOCSY approach.
This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system.
A formal mathematical definition of chattering is proposed. Chattering phenomena are classified into three types. In particular, the first type is harmless and cannot be avoided. Chattering properties of various control approaches are considered. The dangerous second and third types of chattering phenomena are proved to be removable by proper use of high-order sliding-modes (HOSM). Fast stable actuators and sensors only generate the first type of chattering in HOSM systems and practically never affect the sliding motion. Computer simulation confirms the theoretical results.
Solar cells that convert sunlight into electrical power have demonstrated a large and consistent growth through several decades. The growth has spawned research on new technologies that potentially enable much faster, less costly and environmentally friendly manufacture from earth abundant materials. Here we review carbon based solar cells through a complete analysis of all the data that has been reported so far and we highlight what can be expected from carbon based technologies and draw scenarios of how it can be made of immediate use.
This paper presents an overview of the evolution, advancements, and capabilities of the temporal analysis of products (TAP) reactor system as a unique catalyst characterization tool. The origination of the TAP reactor based on molecular beam scattering experiments is briefly mentioned. The advancement in TAP reactor design from the TAP-1 system to the TAP-3 system is introduced to highlight its relevance as a valuable tool for elucidating mechanistic and kinetic aspects of adsorption, diffusion, and reaction in gas–solid systems. Since the invention of the TAP reactor system, a series of TAP microreactor configurations has been introduced with different amounts of catalyst packing starting from the one-zone microreactor to the most recent introduction, the single particle microreactor in which a single Pt particle is packed among 100,000 inert quartz particles. An advantage to decreasing the catalyst zone inside the microreactor is to eliminate non-uniformity in the active zone while still achieving high conversions (95%). Experimental designs and results coupling the TAP reactor to other experimental systems such as a time-of-flight mass spectrometer and atomic beam deposition system is also presented. Key results from recent TAP experiments are presented to show how the TAP reactor is used to answer fundamental questions in catalysis such as bridging the pressure gap between industrial catalysis and surface science, understanding the surface lifetimes of reactive adspecies in TAP pump-probe experiments, finding kinetic rate constants related to changes in catalyst composition and its performance.
This paper presents an effective method to automatically construct trivariate tensor-product spline models of complicated geometry and arbitrary topology. Our method takes as input a solid model defined by its triangulated boundary surface. Using cuboid decomposition, an initial polycube approximating the input boundary mesh is built. This polycube serves as the parametric domain of the tensor-product spline representation required for isogeometric analysis. The polycube’s nodes and arcs decompose the input model’s boundary into quadrilateral patches, and these patches form hexahedral domains. Using aligned global parameterization, the nodes are re-positioned and the arcs are re-routed across the surface in a way to achieve low overall patch distortion, and alignment to principal curvature directions and sharp features. The optimization process is based on one of the main contributions of this paper: a novel way to design cross fields with topological (i.e., imposed singularities) and geometrical (i.e., imposed directions) constraints by solving only sparse linear systems. Based on the optimized polycube and parameterization, compatible B-spline boundary surfaces are reconstructed. Finally, the interior volumetric parameterization is computed using Coon’s interpolation. In the context of parametric studies based on geometrical parameters, this method can be used to compute the morphing required for reduced order modeling. For different parametric instances with the same topology but different geometries, this method allows to have the same representation: i.e., meshes (or parameterizations) with the same topology. The efficiency and the robustness of the proposed approach are illustrated by several examples.