Data mining for lifetime prediction of metallic components

The ability to accurately predict the lifetime of building components is crucial to optimizing building design, material selection and scheduling of required maintenance. This paper discusses a number of possible data mining methods that can be applied to do the lifetime prediction of metallic components and how different sources of service life information could be integrated to form the basis of the lifetime prediction model

Defining the flammability of cylindrical metal rods through characterization of the thermal effects of the ignition promoter

All relevant international standards for determining if a metallic rod is flammable in oxygen utilize some form of “promoted ignition” test. In this test, for a given pressure, an overwhelming ignition source is coupled to the end of the test sample and the designation flammable or nonflammable is based upon the amount burned, that is, a burn criteria. It is documented that (1) the initial temperature of the test sample affects the burning of the test sample both (a) in regards to the pressure at which the sample will support burning (threshold pressure) and (b) the rate at which the sample is melted (regression rate of the melting interface); and, (2) the igniter used affects the test sample by heating it adjacent to the igniter as ignition occurs. Together, these facts make it necessary to ensure, if a metallic material is to be considered flammable at the conditions tested, that the burn criteria will exclude any region of the test sample that may have undergone preheating during the ignition process. A two-dimensional theoretical model was developed to describe the transient heat transfer occurring and resultant temperatures produced within this system. Several metals (copper, aluminum, iron, and stainless steel) and ignition promoters (magnesium, aluminum, and Pyrofuze®) were evaluated for a range of oxygen pressures between 0.69 MPa (100 psia) and 34.5 MPa (5,000 psia). A MATLAB® program was utilized to solve the developed model that was validated against (1) a published solution for a similar system and (2) against experimental data obtained during actual tests at the National Aeronautics and Space Administration White Sands Test Facility. The validated model successfully predicts temperatures within the test samples with agreement between model and experiment increasing as test pressure increases and/or distance from the promoter increases. Oxygen pressure and test sample thermal diffusivity were shown to have the largest effect on the results. In all cases evaluated, there is no significant preheating (above about 38°C/100°F) occurring at distances greater than 30 mm (1.18 in.) during the time the ignition source is attached to the test sample. This validates a distance of 30 mm (1.18 in.) above the ignition promoter as a burn length upon which a definition of flammable can be based for inclusion in relevant international standards (that is, burning past this length will always be independent of the ignition event for the ignition promoters considered here. KEYWORDS: promoted ignition, metal combustion, heat conduction, thin fin, promoted combustion, burn length, burn criteria, flammability, igniter effects, heat affected zone.

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

Tris[4,4,4-trifluoro-1-(2-thienyl)butane-1,3-dionato]aluminium(III)-tris[4,4,4-trifluoro-1-(2-thienyl)butane-1,3-dionato]iron(III) (3/1)

In the title compound, [Al(C8H4F3O2S)3]3[Fe(C8H4F3O2S)3], the metal centre is statistically occupied by AlIII and FeIII cations in a 3:1 ratio. The metal centre is within an octahedral O6 donor set defined by three chelating substituted acetoacetonate anions. The ligands are arranged around the periphery of the molecule with a mer geometry of the S atoms.

Synthesis, characterization of palygorskite supported zero-valent iron and its application for methylene blue adsorption

In this work, natural palygorskite impregnated with zero-valent iron (ZVI) was prepared and characterised. The combination of ZVI particles on surface of fibrous palygorskite can help to overcome the disadvantage of ultra-fine powders which may have strong tendency to agglomerate into larger particles, resulting in an adverse effect on both effective surface area and catalyst performance. There is a significant increase of methylene blue (MB) decolourized efficiency on acid treated palygorskite with ZVI grafted, within 5 mins, the concentration of MB in the solution was decreased from 94 mg/L to around 20 mg/L and the equilibration was reached at about 30 to 60 mins with only around 10 mg/L MB remained in solution. Changes in the surface and structure of prepared materials were characterized using X-ray diffraction (XRD), infrared (IR) spectroscopy, surface analysing and scanning electron microscopy (SEM) with element analysis and mapping. Comparing with zero-valent iron and palygorskite, the presence of zero-valent iron reactive species on the palygorskite surface strongly increases the decolourization capacity for methylene blue, and it is significant for providing novel modified clay catalyst materials for the removal of organic contaminants from waste water.