The Behavior of a 1.4301 Stainless Steel Subjected to Cryogenic Temperatures

AbstractUsually equipments that work at low and cryogenic temperatures are made of stainless steel due to their good mechanical and anti corrosion properties. The best stainless steels for this kind of applications are the ones that present an austenitic microstructure. The austenitic microstructure is the most plastic phase of the Fe-Fe3C alloys but this gives it a very good resilience at low temperature. This paper analysis the behavior of a 1.4301 stainless steel subjected to prolonged exposure to cryogenic temperatures and thermal cycles of cooling to cryogenic temperatures and heating to room temperature. The cryogenic temperatures were obtained by immersing the samples in liquid air which has a temperature of -196°C. The samples were analyzed using scanning electron microscopy, optical microscopy and x-ray diffraction

Organic Rankine Cycle with Solar Heat Storage in Paraffin Way

The paper presents an electricity generation system based on an Organic Rankine Cycle and proposed storing the amount of the heat produced by the solar panels using large volume of paraffin wax. The proposed working fluid is R-134a refrigerant. The cycle operates at very low temperatures. A efficiency of 6,55% was obtained

Study of the influence of ceramic thermal coating on the aircraft blade vibration

The paper analyzes the influence of the ceramic layer on the vibration of the high pressure stage turbine blades in take-off transient conditions. As reference model, the high pressure stage blades of the Tumanski R13 jet engine were considered. The analyse was done using the Ansys 14.5. The vibration eigenmodes and eigenvalues for the blade with and without a ZrO2/3%Y2O3 deposited coating are compared

Assessing the Capability of KELM Meta-Model Approach in Predicting the Energy Dissipation in Different Shapes Channels

For transition of a supercritical flow into a subcritical flow in an open channel, a hydraulic jump phenomenon is used. Different shaped channels are used as useful tools in the extra energy dissipation of the hydraulic jump. Accurate prediction of relative energy dissipation is important in designing hydraulic structures. The aim of this paper is to assess the capability of a Kernel extreme Learning Machine (KELM) meta-model approach in predicting the energy dissipation in different shaped channels (i.e., rectangular and trapezoidal channels). Different experimental data series were used to develop the models. The obtained results approved the capability of the KELM model in predicting the energy dissipation. Results showed that the rectangular channel led to better outcomes. Based on the results obtained for the rectangular and trapezoidal channels, the combination of Fr1, (y2-y1)/y1, and W/Z parameters performed more successfully. Also, comparison between KELM and the Artificial Neural Networks (ANN) approach showed that KELM is more successful in the predicting process

Optimization of Heat Exchange in a Heat Accumulator with Latent Heat Storage

AbstractThe paper analyzes the possibility to optimize the construction of a heat exchanger, which has the role of thermal accumulator in a solar energy storage system for residential use. The storage of solar energy is made in a phase change material (PCM), namely wax paraffin. Starting from a model of thermal accumulator tested experimentally, aiming at improving the heat transfer between wax paraffin and water takes the heat stored. For the new construction solutions proposed heat transfer modeling was performed, using Fluent module from ANSYS 14.5