Mani Sankar Dasgupta

Evaluating Applicability of a Scroll Expander for CO2 Refrigeration System at Warm Climate

Performance of a trans-critical CO2 refrigeration cycle equipped with a scroll work recovery expander is investigated using a semi-empirical model of the scroll, for high ambient temperature application. Maximum isentropic efficiency of 61% is obtained, for a pressure ratio of about 3.7 for the scroll expander. Simulation results obtained are further validated against the reported experimental results. It is also observed that, about 20% of the total energy consumed can be recovered with the help of scroll expander during trans-critical operation. Based on year-round ambient temperature data, at New Delhi (India), an economic analysis is carried out for installation of work recovery scroll system. Total payback period (PBP) for scroll expanders of various capacities are also determined. It is noted that the PBP of scroll expander is about 1 to 2 years or less, which is encouraging. Total Equivalent Warming Impact (TEWI) of the system is compared with that of a conventional trans-critical CO2 refrigeration system and system running on low global warming potential (GWP) hydrofluoroolefin (R1234yf) refrigerant. Trans-critical CO2 system along with work recovery scroll expander appears justified as the same has about 15% lower TEWI compared to conventional trans-critical CO2 system but is 50% more than R1234yf system.

Human detection based on explicit skin colour space thresholding and minor motion detection

In this paper, a novel approach for human presence detection from digital image is presented. This approach is based on combined clue from skin colour and minor motion detection. For skin colour detection, explicit thresholding of CbCr colour channels is used and for minor motion detection morphological differences of multiple consecutive images has been used. MATLAB® is used for processing. Relatively small part of exposed human body in the frame of an image is sufficient for detection. The approach is computationally efficient, potentially real time and robust. The combined technique gives improved performance compared to each individual technique. Location of the object (human) within the frame is also simultaneously identified.

Designing a modular rope climbing bot

This paper discusses design of an autonomous rope climbing robot for identified industrial applications. Modified design goals are drawn up after analyzing the same from prior publications. A modular design with wheel based drive is conceptualized and suitable calculations are done to select drive motor, onboard power source etc. Limited laboratory based test is also carried out to establish suitability of the suggested drive mechanism. An embodiment is drawn out next for light weight modular construction satisfying the design goals. Salient design features are compared with published designs.

Performance evaluation of a CO2 scroll expander for work recovery using ANN

CO2 trans-critical refrigeration systems operate in sub-critical zone for major part of the up-time even for warm climate regions. Recovery of expansion work from CO2 refrigeration systems is viewed as a workable solution to tide over the challenge of typical low coefficient of performance of such systems. Some of the barriers for wide spread implementation of expanders are; relatively low work recovery and high initial investment. In the present study, the functioning of a scroll work recovery expander under sub-critical condition is investigated in an open-loop setup using CO2 as working fluid. The scroll expander itself is obtained through conversion from a scroll compressor with minimal additional investment. Influence of the various operating parameters like mass flow rate, suction pressure, pressure ratio, and rotational speed on the overall performance of the system are examined. An artificial neural network is then trained in Statistical Package for the Social Sciences (SPSS) platform with part of the experimental data and the same is validated with remaining data. It is observed that, the deviation between the shaft speed and shaft work for the model based prediction and experimental results are within ±7.5% and ±11.1%, respectively. The developed artificial neural network will be useful for predicting performance of work recovery scroll expander in closed loop operation with CO2 refrigeration system in sub-critical zone.

Smart control of electric lamp using artificial intelligence based controller

There is need and scope of controlling the power consumed by conventional electric lamps in presence of some natural light. An artificial intelligence based control system has been developed to control a lamp dimmer circuit with bidirectional triode thyristor. The light present in the room is sensed and voltage supplied to the lamp is controlled by varying the time constant of the circuit through change of resistance of a multi-turn potentiometer with a stepper motor. The resistance set in the lamp dimmer circuit is in accordance with signals from an adaptive Neural Network running in MATLAB®. The artificial neural network (ANN) runs in real time in MATLAB® environment to control the time constant of the lamp dimmer circuit for controlling of power consumption. Under test conditions, energy savings up to 35% is achieved.