Aircraft down-range profiles formed from simulated and compact-range radar backscatter

Compact-range radar backscatter measurements are taken of aircraft scale models. In addition, computer software is used to predict the RCS of the aircraft. Synthetic down-range profiles formed from the two sources of backscatter data are compared and visualized in an innovative manner. Similar discrimination rates between the two aircraft are obtained on data from both source

Effect of citrate ions on the electrochemical behaviour of low-carbon steel in borate buffer solutions

The electrochemical behaviour of cold-rolled low carbon steel was studied on both active and passive potential regions in borate buffer solutions with and without the addition of sodium citrate (NaCit). In the active region anodic charges increased significantly and RCT values decreased with citrate, due to the formation of soluble complexes. In the passive potential region the film formed at +0.4 V in borate buffer solution with and without 0.010 M NaCit is probably enriched by Fe3O4 oxide, while films formed at +0.8 V are probably enriched by gamma-Fe2O3. The equivalent circuit [R-s(R(CT)Q)] fitted all experimental impedance data. (C) 2003 Elsevier Ltd. All rights reserved.

A neural network-based preset generation tool for a steel tandem cold mill

This paper traces the development of a software tool, based oil a combination of artificial neural networks (ANN) and a few process equations. aiming to serve as a backup operation instrument in the reference generation for real-time controllers of a steel tandem cold mill By emulating the mathematical model responsible for generating presets under normal operational conditions, the system works as ail option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based oil a lookup table). which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that by this instrument it is possible to achieve nearly the totality of the presets needed by this land of process. The text characterizes the problem, relates the investigated options to solve it. justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results. (C) 2009 Elsevier Ltd. All rights reserved

Nanosized precipitates in H13 tool steel low temperature plasma nitriding

A comprehensive study of pulsed nitriding in AISI H13 tool steel at low temperature (400 degrees C) is reported for several durations. X-ray diffraction results reveal that a nitrogen enriched compound (epsilon-Fe2-3N, iron nitride) builds up on the surface within the first process hour despite the low process temperature. Beneath the surface, X-ray Wavelength Dispersive Spectroscopy (WDS) in a Scanning Electron Microscope (SEM) indicates relatively higher nitrogen concentrations (up to 12 at.%) within the diffusion layer while microscopic nitrides are not formed and existing carbides are not dissolved. Moreover, in the diffusion layer, nitrogen is found to be dispersed in the matrix and forming nanosized precipitates. The small coherent precipitates are observed by High-Resolution Transmission Electron Microscopy (HR-TEM) while the presence of nitrogen is confirmed by electron energy loss spectroscopy (EELS). Hardness tests show that the material hardness increases linearly with the nitrogen concentration, reaching up to 14.5 GPa in the surface while the Young Modulus remains essentially unaffected. Indeed, the original steel microstructure is well preserved even in the nitrogen diffusion layer. Nitrogen profiles show a case depth of about similar to 43 mu m after nine hours of nitriding process. These results indicate that pulsed plasma nitriding is highly efficient even at such low temperatures and that at this process temperature it is possible to form thick and hard nitrided layers with satisfactory mechanical properties. This process can be particularly interesting to enhance the surface hardness of tool steels without exposing the workpiece to high temperatures and altering its bulk microstructure. (c) 2012 Elsevier B.V. All rights reserved.

HANDBOOK CONTAINING INFORMATION, TABLES AND DATA RELATING TO THE MANUFACTURE AND USE OF COLD ROLLED STRIP STEEL

Mode of access: Internet.

The mechanical properties and formability of dual-phase steel

In recent years dual phase steels comprising of 5-20% martensite in a ferrite matrix have come into the limelight of high strength cold formable steels because of their potential for vehicle weight saving. They show the following features: no yield point; relatively low initial flow stress; high initial workhardening rate; well sustained work hardening. As a consequence of these characteristics, dual phase steels exhibit a better combination of strength and elongation than other HSLA steels. In this thesis, a broad view of the factors which influence their properties is presented. Mechanical properties and forming ability of a commercially available dual phase steel and an AL-Si killed steel processed to dual phase form are investigated to ascertain the effect of their microstructure on their properties. It is found that the yield phenomena are masked by the transformation induced stresses present during processing and so yield point could be recovered under suitable ageing treatment; that apart from giving the above properties dual phasing gives rise to very low strain-rate sensitivity and a low R value ~ 1; that the mechanical response under rolling conditions is not different from those under tension; that there is a danger of damage to tooling during forming operations of these steels if fracture should precede instability as a result of grain size dependent strength found for these steels. It is also found that very little deformation of the martensite islands took place during deformation except at high strains. The work-hardening and the strength levels can be controlled by either decreasing the grain size or increasing the martensite volume fraction, but it is found that increasing martensite has a detrimental effect on ductility and the ductility and fracture strength can be controlled better by refining the grain size. A remarkable effect found in the dual phase steel tested is that the compressive strength is higher than the tensile strength. The reason for this observation is not yet clear but it is suggested that it might be due to the introduction of emissary type dislocations into the ferrite lattice as a result of twins formed in the martensite during transformation from austenite. The twins are envisaged to be {111} <112> in character.

Using Association Rules to Solve the Cold-Start Problem in Recommender Systems

Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus it is difficult for a recommender system to make quality recommendations. This problem is known as the cold-start problem. Here we investigate using association rules as a source of information to expand a user profile and thus avoid this problem. Our experiments show that it is possible to use association rules to noticeably improve the performance of a recommender system under the cold-start situation. Furthermore, we also show that the improvement in performance obtained can be achieved while using non-redundant rule sets. This shows that non-redundant rules do not cause a loss of information and are just as informative as a set of association rules that contain redundancy.

Innovative damage assessment of steel truss bridges using modal strain energy correlation

As a part of vital infrastructure and transportation network, bridge structures must function safely at all times. Bridges are designed to have a long life span. At any point in time, however, some bridges are aged. The ageing of bridge structures, given the rapidly growing demand of heavy and fast inter-city passages and continuous increase of freight transportation, would require diligence on bridge owners to ensure that the infrastructure is healthy at reasonable cost. In recent decades, a new technique, structural health monitoring (SHM), has emerged to meet this challenge. In this new engineering discipline, structural modal identification and damage detection have formed a vital component. Witnessed by an increasing number of publications is that the change in vibration characteristics is widely and deeply investigated to assess structural damage. Although a number of publications have addressed the feasibility of various methods through experimental verifications, few of them have focused on steel truss bridges. Finding a feasible vibration-based damage indicator for steel truss bridges and solving the difficulties in practical modal identification to support damage detection motivated this research project. This research was to derive an innovative method to assess structural damage in steel truss bridges. First, it proposed a new damage indicator that relies on optimising the correlation between theoretical and measured modal strain energy. The optimisation is powered by a newly proposed multilayer genetic algorithm. In addition, a selection criterion for damage-sensitive modes has been studied to achieve more efficient and accurate damage detection results. Second, in order to support the proposed damage indicator, the research studied the applications of two state-of-the-art modal identification techniques by considering some practical difficulties: the limited instrumentation, the influence of environmental noise, the difficulties in finite element model updating, and the data selection problem in the output-only modal identification methods. The numerical (by a planer truss model) and experimental (by a laboratory through truss bridge) verifications have proved the effectiveness and feasibility of the proposed damage detection scheme. The modal strain energy-based indicator was found to be sensitive to the damage in steel truss bridges with incomplete measurement. It has shown the damage indicator's potential in practical applications of steel truss bridges. Lastly, the achievement and limitation of this study, and lessons learnt from the modal analysis have been summarised.

Microalgal species selection for biodiesel production based on fuel properties derived from fatty acid profiles

Physical and chemical properties of biodiesel are influenced by structural features of the fatty acids, such as chain length, degree of unsaturation and branching of the carbon chain. This study investigated if microalgal fatty acid profiles are suitable for biodiesel characterization and species selection through Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis. Fatty acid methyl ester (FAME) profiles were used to calculate the likely key chemical and physical properties of the biodiesel [cetane number (CN), iodine value (IV), cold filter plugging point, density, kinematic viscosity, higher heating value] of nine microalgal species (this study) and twelve species from the literature, selected for their suitability for cultivation in subtropical climates. An equal-parameter weighted (PROMETHEE-GAIA) ranked Nannochloropsis oculata, Extubocellulus sp. and Biddulphia sp. highest; the only species meeting the EN14214 and ASTM D6751-02 biodiesel standards, except for the double bond limit in the EN14214. Chlorella vulgaris outranked N. oculata when the twelve microalgae were included. Culture growth phase (stationary) and, to a lesser extent, nutrient provision affected CN and IV values of N. oculata due to lower eicosapentaenoic acid (EPA) contents. Application of a polyunsaturated fatty acid (PUFA) weighting to saturation led to a lower ranking of species exceeding the double bond EN14214 thresholds. In summary, CN, IV, C18:3 and double bond limits were the strongest drivers in equal biodiesel parameter-weighted PROMETHEE analysis.