Detailed studies on the effects of pulsed laser interference heating on surface characteristics and subsurface microstructure of amorphous Fe80Si11B9 alloy are reported. Laser interference heating, with relatively low pulsed laser energy (90 and 120 mJ), but with a variable number (from 50-500) of consecutive laser pulses permitted to get energy accumulation in heated areas. Such treatment allowed to form two- Dimensional micro-islands of laser-affected material periodically distributed in amorphous matrix. The crystallization process of amorphous FeSiB ribbons was studied by means of scanning and transmission electron microscopy. Detailed microstructural examination showed that the use of laser beam, resulted in development of nanostructure in the heated areas of the amorphous ribbon. The generation of nanocrystalline seed islands created by pulsed laser interference was observed. This key result may evidently give new knowledge concerning the differences in microstructure formed during the conventional and lased induced crystallization the amorphous alloys. Further experiments are needed to clarify the effect of pulsed laser interference crystallization on magnetic properties of these alloys.
Paper describes the results of Fe80Si11B9 amorphous ribbon investigation after pulsed laser interference heating and conventional annealing. As a result of interference heating periodically placed laser heated microareas were obtained. Structure characterisation by scanning and transmission electron microscopy showed in case of laser heated samples presence of crystalline nanostructure in amorphous matrix. Microscopy observations showed significant difference in material structure after laser heating – nanograin structure, and material after annealing – dendritic structure. Magnetic force microscopy investigation showed expanded magnetic structure in laser heated microareas, while amorphous matrix did not give magnetic signal. Change of magnetic properties was examined by magnetic hysteresis loop measurement, which showed that the laser heating did not have a significant influence on soft magnetic properties.
The influence that general contractors and subcontractors have on the operation of a company is immense. Keeping this in mind, the authors have decided to develop and algorithm based on the analysis of partnering relations between construction companies that would select the best possible construction company for the purposes of cooperation. This algorithm, developed for a given construction company, is meant to support its decision-making system in the field of the selection of another construction company to cooperate with. The author has made references to earlier research, in which she had used the ELECTRE III method, and in which she bad analysed the possibility of applying the BIPOLAR method in order to solve the problem of the selection of a construction company to develop partnering relations with. The author provided an example of the calculations performed for a selection of construction companies.
The paper shows methods of analysis and assessment of partnering relations of construction enterprises with the use of questionnaires, statistics, and fuzzy logic. The results were obtained from Polish, Slovak and Ukrainian enterprises. The definition of partnering in the construction industry indicates that it is a qualitative concept. By applying a scale in the questionnaire, and due to mathematical analysis of the data, the final research result, showing the level of partnering relations of construction enterprises, is rendered quantitatively.
The article presents the use of the Mamdani fuzzy reasoning model to develop a proposal of a system controlling partnering relations in construction projects. The system input variables include: current assessments of particular partnering relation parameters, the weights of these parameters’ impact on time, cost, quality and safety of implementation of construction projects, as well as the importance of these project assessment criteria for its manager. For each of the partnering relation parameters, the project’s manager will receive controlrecommendations. Moreover, the parameter to be improved first will be indicated. The article contains a calculation example of the system’s operations.