20 research outputs found
Studies on transport mechanism of Cr(VI) extraction from an acidic solution using liquid surfactant membranes
No full textBioremediation of Copper-Contaminated Soil by Co-Application of Bioaugmentation and Biostimulation with Organic Nutrient
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Modelling of air-lift reactors based on bubble dynamics
No full text187-191<span style="font-size:11.0pt;line-height:115%;
font-family:" calibri","sans-serif";mso-ascii-theme-font:minor-latin;mso-fareast-font-family:="" "times="" new="" roman";mso-fareast-theme-font:minor-fareast;mso-hansi-theme-font:="" minor-latin;mso-bidi-font-family:"times="" roman";mso-ansi-language:en-us;="" mso-fareast-language:en-us;mso-bidi-language:ar-sa"="">Predictions of hydrodynamic
performance of an air-lift reactor (ALR) have traditionally considered bulk gas
and liquid phase characteristics. This study aims to present an alternative
approach of modelling an ALR by estimating the energy input to the reactor and
gas hold-up in the riser based on dynamics of individual bubbles. The bubbles
have been assumed to rise in discrete layers in the riser having a diameter in
equilibrium with the surrounding pressure. The model predictions of gas hold-up
and liquid velocity in the downcomer for ALRs have been compared with the
reported experimental data.</span
Studies on surface morphology and electrical conductivity of PEDOT:PSS thin films in presence of gold nanoparticles
No full textPotential Field Methods for Safe Reinforcement Learning: Exploring Q-Learning and Potential Fields
No full textA Reinforcement Learning (RL) agent learns about its environment through exploration. For most physical applications such as search and rescue UAVs, this exploration must take place with safety in mind. Unregulated exploration, especially at the beginning of a run, will lead to fatal situations such as crashes. One approach to mitigating these risks is by using Artificial Potential Fields (APFs). Various approaches to effectively use the potential information gathered by the agent are proposed, tested and discussed. The agent is placed in an environment-model-free setting, where it is still provided with knowledge of its own dynamics. A gridworld simulation is developed using MATLAB to test the interoperability of APFs with Q-learning. It is shown that safety of exploration benefits from adding this layer of information to the agents’ decision making process. In effect, the Q-table gets updated more efficiently due to the agent explicitly knowing of high potential ‘dangerous’ states.Aerospace Engineering | Control & Simulatio
Integral approach of sorption coupled with biodegradation for treatment of azo dye using Pseudomonas sp.: batch, toxicity, and artificial neural network
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