Prediction and sensitivity analysis of CNTs-modified asphalt’s adhesion force using a radial basis neural network model

Abstract

The expected longer service life of modified asphalt can be jeopardized by different environmental factors, such as moisture, oxidation, etc. which affect the desired properties by altering the adhesive property. An insight into knowledge of the adhesive property of the asphalt can help in providing more durable asphalt pavement. The study attempted to develop different models of adhesive properties of polymers and carbon nanotubes (CNTs) modified asphalt binders. The polymer-CNT modified asphalt is processed to prepare different types of samples, by simulating the damage due to moisture and oxidization, following the corresponding standard method. An Atomic Force Microscopy (AFM) was employed to assess the nanoscale adhesion force of the tested samples following the existing functional group in asphalt. Finally, the study has developed Radial Basis Function Neural Network (RBFNN) as a function of different parameters including; asphalt chemistry (i.e. AFM tip type and constant), type and percentages of polymers and CNTs and different environmental exposures (oxidation, moisture, etc.) to predict the nano adhesion force of asphalt. It is observed that the adhesive property of the Styrene–Butadiene modified asphalt is more consistent compared to the Styrene–Butadiene–Styrene modified asphalt, while the presence of Single-Wall Nanotubes (SWNT) is observed to affect the adhesive properties of asphalt significantly as compared to Multi-Wall Nanotubes (MWNT). The higher accuracy level of RBFNN model also indicates that the functional group (tip-type) adding with the percentages and types of polymers and CNTs significantly affect the adhesive properties of asphalt.     

Cost effective second generation AC-modules: Development and testing aspects

In the framework of the European research project PV2GO, a new AC-module inverter was developed, taking into account all relevant aspects from a European market's point of view (standards, market, application, and research and development goals). The project goal was to achieve the overall system costs of 3 Euro per Wp for a modular plug-and-play photovoltaic system. For the photovoltaic-module, a standard 130-Wp Eurosolare module was chosen. The research and development (R&D) goal was to develop an advanced DC-control system consisting of a state-of-the-art programmable digital device and an Application Specific Integrated Circuit (ASIC) for the AC-control of the inverter. According to the topology concept, thermal and magnetic designs were optimized with regard to production technology and packaging for large-scale production. The new AC-modules were tested in a number of field-test sites in various parts of Europe and their reliability was assessed through Highly Accelerated Stress Tests. Efficiency and power quality have been tested in the laboratory. Further in the PV2GO project an optimization study of the manufacturing process of the new generation of AC-modules for high volume output was done. Another task was the pre-certification procedure to assure compliance with the European guidelines and standards.     

A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems

For more than three decades, similarity coefficient measures one of the important tools for solving group technology problems have gained the attention of the research community in cellular manufacturing systems. A new similarity coefficient measure that uses a set of important characteristic properties for grouping is developed here for use as an intermediate tool to form cohesive cells. A mathematical model that uses this similarity coefficient for optimally solving the cell-formation problems in cellular manufacturing is developed. A heuristic procedure that improves the optimal methodology in term of solution capability of the large instances is devised for an efficient solution. Both the optimal methodology and the heuristic are applied to some well-known problems from literature to compare the grouping efficiencies. The similarity coefficient and the solution methodologies developed are able to solve the cell formation problems efficiently.     

XPloreRank: exploring XML data via you may also like queries

World Wide Web - In many cases, users are not familiar with their exact information needs while searching complicated data sources. This lack of understanding may cause the users to feel...     

Optimum structural modelling for tall buildings

It is a common practice to model multi‐storey tall buildings as frame structures where the loads for structural design are supported by beams and columns. Intrinsically, the structural strength provided by the walls and slabs are neglected. As the building height increases, the effect of lateral loads on multi‐storey structures increases considerably. The consideration of walls and slabs in addition to the frame structure modelling shall theoretically lead to improved lateral stiffness. Thus, a more economic structural design of multi‐storey buildings can be achieved. In this research, modelling and structural analysis of a 61‐storey building have been performed to investigate the effect of considering the walls, slabs and wall openings in addition to frame structure modelling. Sophisticated finite element approach has been adopted to configure the models, and various analyses have been performed. Parameters, such as maximum roof displacement and natural frequencies, are chosen to evaluate the structural performance. It has been observed that the consideration of slabs alone with the frame modelling may have negligible improvement on structural performance. However, when the slabs are combined with walls in addition to frame modelling, significant improvement in structural performance can be achieved. Copyright © 2012 John Wiley & Sons, Ltd.     

Polyaniline matrix containing nickel ferromagnet

Metallic nickel (Ni) was successfully dispersed onto a polyaniline (PANI) matrix by a simple one‐step electrochemical method. Ni particles as deposited onto the polymer seemed to be much smaller compared to those deposited onto bare Pt. The size of the Ni deposits was found to be influenced by the electrolytic bath composition and potential sweep rate. The PANI matrix thus dispersed with Ni particles exhibited ferromagnetic behavior and a lower electrical conductance. The decrease in conductivity may be attributed to the partial blockage of the conductive path by the Ni particles thus embedded in the polymer matrix. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 321–327, 2006     

Optimization of a natural gas SI engine employing EGR strategy using a two-zone combustion model

Natural gas has been recently used as an alternative to conventional fuels in order to satisfy some environmental and economical concerns. In this study, a natural gas spark-ignition engine employing cooled exhaust gas recirculation (EGR) strategy in a high pressure inlet condition was optimized. Both engine compression ratio and start of combustion timing were optimized in order to obtain the lowest fuel consumption accompanied with high power and low emissions. That was achieved numerically by developing a computer simulation of the four-stroke spark-ignition natural gas engine. A two-zone combustion model was developed to simulate the in-cylinder conditions during combustion. A kinetic model based on the extended Zeldovich mechanism was also developed in order to predict NO emission. In addition, a knocking model was incorporated with the two-zone combustion model in order to predict any auto-ignition that might occur. It was found that the value of the compression ratio at which the minimum fuel consumption occurs varies with the engine speed. A minimum fuel consumption of about 200 g/kW h was achieved at an engine speed of 1500 rpm, inlet conditions of 200 kPa and 333 K, and a compression ratio of about 12. Also, it was found that cooled EGR can significantly reduce NO emission at high compression ratio conditions. NO emission decreased by about 28% when EGR was increased from 20% at compression ratio of 10 to 27% at compression of 12 at the same engine speed of 3000 rpm.     

The lithium intercalation process in the low-voltage lithium battery anode Li(1+x)V(1-x)O2

Lithium can be reversibly intercalated into layered Li(1+x)V(1-x)O(2) (LiCoO(2) structure) at ~0.1 V, but only if x>0. The low voltage combined with a higher density than graphite results in a higher theoretical volumetric energy density; important for future applications in portable electronics and electric vehicles. Here we investigate the crucial question, why Li cannot intercalate into LiVO(2) but Li-rich compositions switch on intercalation at an unprecedented low voltage for an oxide? We show that Li(+) intercalated into tetrahedral sites are energetically more stable for Li-rich compositions, as they share a face with Li(+) on the V site in the transition metal layers. Li incorporation triggers shearing of the oxide layers from cubic to hexagonal packing because the Li(2)VO(2) structure can accommodate two Li per formula unit in tetrahedral sites without face sharing. Such understanding is important for the future design and optimization of low-voltage intercalation anodes for lithium batteries.