A comparative study of the tensile properties of compression molded and 3D printed PLA specimens in dry and water saturated conditions

Journal of Mechanical Science and Technology - This research work presents a comparative study of the tensile properties of polylactic acid (PLA) specimens per ASTM D638-14 fabricated by...     

Mathematical and neural network models for predicting the electrical performance of a PV/T system

There are many photovoltaic/thermal (PV/T) systems' designs that are used mainly to reduce the temperature of the PV cell by using a thermal medium to cool the photovoltaic module. In this study, a PV/T system uses nano‐phase change material (PCM) and nanofluid cooling system was adopted. Three cooling models were compared using nanofluid (SiC‐water) and nano‐PCM to improve the performance and productivity of the PV/T system. Three mathematical models were developed for linear prediction, and their results were compared with the predicted artificial neural network results, results were verified, and experimental results were appropriate. Three common evaluation criteria were adopted to compare that the results of proposed forecasting models with other models developed in many research studies are done, including the R², mean square error (MSE), and root‐mean‐square error (RMSE). Besides, different experiments were implemented using varying number of hidden layers to ensure that the proposed neural network models achieved the best results. The best neural prediction models deployed in this study resulted in good R² score of 0.81 and MSE of 0.0361 and RMSE and RMSE rate is 0.371. Mathematical models have proven their high potential to easily determine the future outcomes with the preferable circumstances for any PV/T system in a precise way to reduce the error rate to the lowest level.     

Biochemical and molecular characterization of novel PAH-degrading bacteria isolated from polluted soil and sludge

Polycyclic aromatic hydrocarbons (PAHs) containing more than three rings are mainly less biodegradable. Therefore, the isolation of PAHs-degrading bacteria is of great importance to be augmented for bioremediation of polluted sites with PAHs. PAHs-degrading bacteria were isolated from contaminated sites of an oil refinery. The strains were confirmed by biochemical tests and 16S rRNA, which were Stenotrophomonas maltophilia (two strains), Thermomonas koreensis (three strains), Achromobacter (two strains), Pseudomonas stutzeri (one strain), Azospirillum brasilense (one strain) and Brevibacillus brevis (one strain). The isolate strains can be applied as a bacterial consortium for purification of polluted soil with high levels of PAHs.     

Solving non-convex economic dispatch problem with valve point effects using modified group search optimizer method

This paper presents a novel solution based on the group search optimizer (GSO) methodology in order to determine the feasible optimal solution of the economic dispatch (ED) problem considering valve loading effects. The basic disadvantage of the original GSO algorithm is the fact that it gives a near-optimal solution rather than an optimal one in a limited runtime period. In this paper, a new modified group search optimizer (MGSO) is presented for improving the scrounger and ranger operators of GSO. The proposed MGSO is applied on different test systems and compared with most of the recent methodologies. The results show the effectiveness of the proposed method and prove that MGSO can be applicable for solving the power system economic load dispatch problem, especially in large scale power systems.     

Flow transients performance in an MTR-type research reactor

During a flow coastdown event leading to slowing down coolant flow, the rate of heat removal from the fuel element must be sufficiently high to prevent meltdown. It is essential to estimate the flow rate change and the decay heat removal capability. In many studies complete pump operating characteristics are used in analytical solutions of the problem. Under the coastdown phenomenon, retarding torque replaces motor torque. In order to determine this torque, all the induction motor losses during the event are identified and where possible these loss parameters are measured. Stator and rotor core losses, stator and rotor stray load losses and magnetizing saturation and rotor conductor skin effects are taken into account. The basics equations for coolant flow and for the rotating parts of the centrifugal pump are subsequently derived for an MTR-type research reactor such Tehran Research Reactor (TRR). Then the equation of flow motion is solved with another one which predicts the pump speed during the coastdown transient. The results of the present work are validated by comparison with experimental and analytical studies of the similar work. The model shows good agreement with the present literature.