Amalija Horvatić

Development of Models for Prediction of Corrosion and Pitting Potential on AISI 304 Stainless Steel in Different Environmental Conditions

Stainless steels are found in various aerated aqueous electrolytes in a passive state which protects them from corrosion. In many aggressive solutions, stainless steels are easily depassivated, which can lead to different types of corrosion. This paper tested the impact of chloride ions at different concentration, temperatures and pH values on the corrosion and pitting potential of AISI 304 stainless steel. In order to predict the behaviour of AISI 304 stainless steel design of experiment and artificial neural network methods were applied. Results of the developed models showed good agreement with the experimental results and no significant differences between models.

Simulation modelling of a company providing two qualitatively different services to market

Simulation modelling is applied onto a market dynamics of a company conducting two qualitatively different services and has a bounded total daily volume. The model contains qualitatively and in a simplified form the characteristics of the dynamics of a general service providing company. The company applies a single strategy how to influence, thus minimise, the number of agents who wait for a given service. The strategy is realised by changing the relative proportion of the daily conducted services. Rather small modification of priority level between the two services influences considerably both the number and the type of end users who wait for a particular service. The model enables the researchers to test different strategies how to control the number of end users who wait for services, by proper changes in priority level of services conducted. The fact important for practitioners is that partial optimisation is achieved through slight difference in priorities between the services. (Received in October 2015, accepted in January 2016. This paper was with the authors 1 week for 1 revision.)