Application of a hybrid Entropy–McKinsey Matrix method in evaluating sustainable urbanization : a China case study

Although urbanization can promote social and economic development, it can also cause various problems. As the key decision makers of urbanization, local governments should be able to evaluate urbanization performance, summarize experiences, and find problems caused by urbanization. This paper introduces a hybrid Entropy–McKinsey Matrix method for evaluating sustainable urbanization. The McKinsey Matrix is commonly referred to as the GE Matrix. The values of a development index (DI) and coordination index (CI) are calculated by employing the Entropy method and are used as a basis for constructing a GE Matrix. The matrix can assist in assessing sustainable urbanization performance by locating the urbanization state point. A case study of the city of Jinan in China demonstrates the process of using the evaluation method. The case study reveals that the method is an effective tool in helping policy makers understand the performance of urban sustainability and therefore formulate suitable strategies for guiding urbanization toward better sustainability.

A unique battery/supercapacitor direct integration scheme for hybrid electric vehicles

Battery/supercapacitor hybrid energy storage systems have been gaining popularity in electric vehicles due to their excellent power and energy performances. Conventional designs of such systems require interfacing dc-dc converters. These additional dc-dc converters increase power loss, complexity, weight and cost. Therefore, this paper proposes a new direct integration scheme for battery/supercapacitor hybrid energy storage systems using a double ended inverter system. This unique approach eliminates the need for interfacing converters and thus it is free from aforementioned drawbacks. Furthermore, the proposed system offers seven operating modes to improve the effective use of available energy in a typical drive cycle of a hybrid electric vehicle. Simulation results are presented to verify the efficacy of the proposed system and control techniques.

A direct integration scheme for battery-supercapacitor hybrid energy storage systems with the use of grid side inverter

Battery-supercapacitor hybrid energy storage systems are becoming popular in the renewable energy sector due to their improved power and energy performances. These hybrid systems require separate dc-dc converters, or at least one dc-dc converter for the supercapacitor bank, to connect them to the dc-link of the grid interfacing inverter. These additional dc-dc converters increase power losses, complexity and cost. Therefore, possibility of their direct connection is investigated in this paper. The inverter system used in this study is formed by cascading two 3-level inverters, named as the “main inverter” and the “auxiliary inverter”, through a coupling transformer. In the test system the main inverter is connected with the rectified output of a wind generator while the auxiliary inverter is directly attached to a battery and a supercapacitor bank. The major issues with this approach are the dynamic changes in dc-link voltages and inevitable imbalances in the auxiliary inverter voltages, which results in unevenly distributed space vectors. A modified SVM technique is proposed to solve this issue. A PWM based time sharing method is proposed for power sharing between the battery and the supercapacitor. Simulation results are presented to verify the efficacy of the proposed modulation and control techniques.

Hybrid polymer/metal nanoparticles with surface enhanced raman tracking for potential use in nanomedicine

This project was a preliminary step towards the development of novel methods for early stage cancer diagnosis and treatment. Diagnostic imaging agents with high Raman signal enhancement were developed based on tailored assemblies of gold nanoparticles, which demonstrated potential for non-invasive detection from deep under the skin surface. Specifically designed polymers were employed to assemble gold nanoparticles into controlled morphologies including dimers, nanochains, nanoplates, globular and core-satellite nanostructures. Our findings suggest that the Raman enhancement is strongly dependent on assembly morphology and can be tuned to adapt to the requirements of the diagnostic agent.

A hybrid cascaded multilevel inverter with supercapacitor direct integration for wind power systems

This paper presents a grid-side inverter based supercapacitor direct integration scheme for wind power systems. The inverter used in this study consists of a conventional two-level inverter and three H-bridge modules. Three supercapacitor banks are directly connected to the dc-links of H-bridge modules. This approach eliminates the need for interfacing dc-dc converters and thus considerably improves the overall efficiency. However, for the maximum utilization of super capacitors their voltages should be allowed to vary. As a result of this variable voltage space vectors of the hybrid inverter get distributed unevenly. To handle this issue, a modified PWM method and a space vector modulation method are proposed and they can generate undistorted current even in the presence of unevenly distributed space vectors. A supercapacitor voltage balancing method is also presented in this paper. Simulation results are presented to validate the efficacy of the proposed scheme, modulation methods and control techniques.

Design of a renewable - hybrid energy storage power scheme for short-term power dispatch

A hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC) is proposed for use in a wind farm in order to achieve power dispatchability. In the designed scheme, the rate of charging/discharging powers of the battery is controlled while the faster wind power transients are diverted to the SC. This enhances the lifetime of the battery. Furthermore, by taking into consideration the random nature of the wind power, a statistical design method is developed to determine the capacities of the HESS needed to achieve specified confidence level in the power dispatch. The proposed approach is useful in the planning of the wind farm-HESS scheme and the coordination of the power flows between the battery and SC.

3D-hybrid networks with controllable electrical conductivity from the electrochemical deposition of terthiophene-functionalized polyphenylene dendrimers

(Figure Presented) Unusual conductivity effects: Suitably functionalized dendrimers (see picture) are capable of forming truly covalent three-dimensional networks with remarkably high conductivity on electrochemical doping. Depending on the charging level of the electroactive components used as building blocks for the dendrimer core and the perimeter, two separated regimes of electrical conductivity can be observed.

A novel dc-link voltage regulation method for single source hybrid multilevel inverters

This paper presents a novel dc-link voltage regulation technique for a hybrid inverter system formed by cascading two 3-level inverters. The two inverters are named as “bulk inverter” and “conditioning inverter”. For the hybrid system to act as a nine level inverter, conditioning inverter dc link voltage should be maintained at one third of the bulk inverter dc link voltage. Since the conditioning inverter is energized by two series connected capacitors, dc-link voltage regulation should be carried out by controlling the capacitor charging/discharging times. A detailed analysis of conditioning inverter capacitor charging/discharging process and a simplified general rule, derived from the analysis, are presented in this paper. Time domain simulations were carried out to demonstrate efficacy of the proposed method on regulating the conditioning inverter dc-link voltage under various operating conditions.

Mission path planning of aerial survey tasks using hybrid game evolutionary algorithm

The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

Engineering the mechanical properties of graphene nanotube hybrid structures through structural modulation

The excellent multi-functional properties of carbon nanotube (CNT) and graphene have enabled them as appealing building blocks to construct 3D carbon-based nanomaterials or nanostructures. The recently reported graphene nanotube hybrid structure (GNHS) is one of the representatives of such nanostructures. This work investigated the relationships between the mechanical properties of the GNHS and its structure basing on large-scale molecular dynamics simulations. It is found that increasing the length of the constituent CNTs, the GNHS will have a higher Young’s modulus and yield strength. Whereas, no strong correlation is found between the number of graphene layers and Young’s modulus and yield strength, though more graphene layers intends to lead to a higher yield strain. In the meanwhile, the presences of multi-wall CNTs are found to greatly strengthen the hybrid structure. Generally, the hybrid structures exhibit a brittle behavior and the failure initiates from the connecting regions between CNT and graphene. More interestingly, affluent formations of monoatomic chains and rings are found at the fracture region. This study provides an in-depth understanding of the mechanical performance of the GNHSs while varying their structures, which will shed lights on the design and also the applications of the carbon-based nanostructures.

The affect heuristic and public support for three types of wood smoke mitigation policies

This study applied the affect heuristic model to investigate key psychological factors (affective associations, perceived benefits, and costs of wood heating) contributing to public support for three distinct types of wood smoke mitigation policies: education, incentives, and regulation. The sample comprised 265 residents of Armidale, an Australian regional community adversely affected by winter wood smoke pollution. Our results indicate that residents with stronger positive affective associations with wood heating expressed less support for wood smoke mitigation policies involving regulation. This relationship was fully mediated by expected benefits and costs associated with wood heating. Affective associations were unrelated to public support for policies involving education and incentives, which were broadly endorsed by all segments of the community, and were more strongly associated with rational considerations. Latent profile analysis revealed no evidence to support the proposition that some community members experience internal “heart versus head” conflicts in which their positive affective associations with wood heating would be at odds with their risk judgments about the dangers of wood smoke pollution. Affective associations and cost/benefit judgments were very consistent with each other.

Hybrid chalcogenide nanoparticles : 2D-WS2 nanocrystals inside nested WS2 fullerenes

The MOCVD assisted formation of nested WS2 inorganic fullerenes (IF-WS2) was performed by enhancing surface diffusion with iodine, and fullerene growth was monitored by taking TEM snapshots of intermediate products. The internal structure of the core-shell nanoparticles was studied using scanning electron microscopy (SEM) after cross-cutting with a focused ion beam (FIB). Lamellar reaction intermediates were found occluded in the fullerene particles. In contrast to carbon fullerenes, layered metal chalcogenides prefer the formation of planar, plate-like structures where the dangling bonds at the edges are stabilized by excess S atoms. The effects of the reaction and annealing temperatures on the composition and morphology of the final product were investigated, and the strength of the WS2 shell was measured by intermittent contact-mode AFM. The encapsulated lamellar structures inside the hollow spheres may lead to enhanced tribological activities.