The cascaded H-bridge (CHB)-based medium-high voltage motor drive suffers a severe 2nd-harmonic ripple power problem on the DC side, especially under low output frequency conditions. Currently, strategies to address this problem include increasing the DC capacitors or adopting active power-decoupling methods that require extra switches and passive components. This paper proposes a novel power decoupling control method for the regenerative cascaded multilevel motor drive converter. Considering the inherent balance of the ripple power in the three phases and the special topology of the regenerative CHB-based motor drive, this method induces a negative-sequence current with special frequency into the active front end of each power module to transfer the ripple power of all power modules into the core column of the input transformer, allowing them to counteract each other. In this way, the 2nd-harmonic ripple of the DC voltages are eliminated without the need for additional components or impacts on the input and output power quality, which can greatly decrease the requirement for DC capacitors.
In order to grasp the factors affecting road traffic safety and discharge the potential hazard fundamentally, an AHP (Analytic Hierarchy Process) method, which suits for solving complex decision making was proposed in this paper. Started from the view of system science, this paper calculated the weights of the causes of road traffic accidents by establishing the AHP model of the major factors affecting road traffic safety. The results of the experiment showed that factors of drivers accounted for a large proportion of traffic accidents, in which speeding was the most active factor. The AHP method overcome the drawbacks of the traditional analytical measures which only considered one single factor, the number of traffic accidents, and obtained objectively the major causes of road traffic accidents with a comprehensive consideration of people, vehicles, roads and environmental influence. Finally, several corresponding preventive measures were proposed, which will play a guiding role on the development of road traffic safety.
An efficient visible-light-induced para-selective C(sp2)–H difluoroalkylation of diverse electron-deficient (hetero)aromatic carbonyls (aldehydes and ketones) at ambient temperature has been developed by employing Ir(ppy)3 as the catalyst and 1,10-phenanthroline as the additive. This protocol was highlighted by its wide substrate scope, high regioselectivity, low catalyst usage, and operational simplicity.
Abstract Understanding the site interaction nature of single‐atom catalysts (SACs), especially densely populated SACs, is vital for their application to various catalytic reactions. Herein, we report a site distance effect, which emphasizes how well the distance of the adjacent copper atoms (denoted as d Cu1−Cu1 ) matches with the reactant peroxydisulfate (PDS) molecular size to determine the Fenton‐like reaction reactivity on the carbon‐supported SACs. The optimized d Cu1−Cu1 in the range of 5–6 Å, which matches the molecular size of PDS, endows the catalyst with a nearly two times higher turnover frequency than that of d Cu1−Cu1 beyond this range, accordingly achieving record‐breaking kinetics for the oxidation of emerging organic contaminants. Further studies suggest that this site distance effect originates from the alteration of PDS adsorption to a dual‐site structure on Cu 1 −Cu 1 sites when d Cu1−Cu1 falls within 5–6 Å, significantly enhancing the interfacial charge transfer and consequently resulting in the most efficient catalyst for PDS activation so far.
This research demonstrates the development of temporal GIS and its applicability to support spatio-temporal hazard mitigation modeling. Many GIS data models have been proposed to incorporate temporal information into spatial databases. Thematic characteristics are represented as attributes of spatial objects. Temporal information is either associated with time-s tamped individual layers, such as the Snapshot Model, or individual spatial objects, such as the Space-Time Composite Model. On our earth lots of events occurs everyday continually. If the effect of these events is negative on human life called natural hazards. If these hazards severely destroy human lives and properties called natural disasters. Earthquake, landslides, floods and tornadoes are the example of mostly occurring natural disasters all over the world. We can not eliminate these hazards but we can minimize the risk of these hazards, the minimization of risk is called hazard mitigation. For prevention and mitigation of these hazards a geospatial based system can be realized. The main aim of this paper is to present a geospatial based hazard management system that can predict, asses and mange the hazards in order to help minimizing destruction. In this paper we presented Spatio Temporal Hazard Mitigation Modeling using GIS and Geospatial Data mining Techniques.