Exergy Analysis of a Vapor Absorption Refrigeration System Using Carbon Dioxide as Refrigerant

Vapor absorption refrigeration systems can be an alternative to vapor compression systems in many applications as they can operate on a low-grade heat source and are environment friendly. Widely used refrigerants such as CFCs and HFCs cause significant global warming. Natural refrigerants can be used instead of them, among which carbon dioxide is promising. Its inherent safety, ability to withstand high pressure and high heat transfer coefficient coupled with easy availability make it a likely choice for refrigerant. [Bmim][PF6] is a room temperature ionic liquid (RTIL) composed of a large organic cation and an inorganic anion. Its properties such as non-toxicity, stability over a wide temperature range and ability to dissolve gases like carbon dioxide, make it a suitable absorbent for a vapor absorption refrigeration system. In this paper, an absorption chiller utilising the CO2-[bmim][PF6] working pair and consisting of a generator, condenser, evaporator and absorber has been proposed. A thermodynamic model was set up using the Redlich-Kwong cubic equations of state to predict the behavior of the refrigerant and absorbent pair at different points in the system. A MATLAB code was used to obtain the values of enthalpy and entropy at selected points in the system. The exergy destruction in each component and exergetic coefficient of performance (ECOP) of the system were calculated by performing an exergy analysis based on the second law of thermodynamics. The effect of every component on the ECOP was examined by calculating the amount of exergy destruction in each of them. The exergetic coefficient of performance was calculated for five generator temperatures in the range of 60-100⁰C for an evaporator temperature of 10⁰C and was found to be in the range of 0.02-0.2. Such a chiller can be employed for refrigeration purposes, such as in the storage of food items

Design of optimal band-stop FIR filter using L1-norm based RCGA

AbstractIn this paper, an optimal design of linear phase digital finite impulse response (FIR) band stop (BS) filter using the L1-norm based real-coded genetic algorithm (L1-RCGA) is presented. Although RCGA has proved its ability to overcome the drawbacks associated with conventional gradient-based optimization methods of filter design, it is applied here with a novel fitness function based on the L1-norm. This leads to a global optimal solution along with the improvement in filter design with same specifications. The designed filter pursues a better response in terms of flat passband, high stopband attenuation and fast convergence. The simulation results justify that the proposed FIR BS filter using L1-RCGA outperforms the existing optimization techniques, the L1-method and particle swarm optimization (PSO) and the conventional methods such as least-squares (LS) approach, Kaiser window method and the Parks McClellan (PM) algorithm. A detailed analysis is performed to evaluate the performance of the designed filters

Role of Exosomes in Tumor Induced Neo-Angiogenesis

Exosomes are the nanovesicles, belonging to the type of extracellular vesicles (EVs), produced by normal as well as tumor cells and function as a mode in cell-to-cell communication. Tumor cells utilize various approach to communicate with neighboring cells for facilitating tumor invasion and progression, one of these approaches has been shown through the release of exosomes. Tumor-derived exosomes (TEX) have the ability to reprogram/modulate the activity of target cells due to their genetic and molecular cargo. Such exosomes target endothelial cells (among others) in the tumor microenvironment (TME) to promote angiogenesis which is an important element for solid tumor growth and metastasis. So, exosomes play a vital role in cancer invasiveness and progression by harboring various cargoes that could accelerate angiogenesis. Here first, we will present an overview of exosomes, their biology, and their role in different cancer models. Then, we will emphasis on exosomes derived from tumor cells as tumor angiogenesis mediators with a particular importance on the underlying mechanisms in various cancer origins. In the end, we will unveil the therapeutic potential of tumor derived exosomes as drug delivery vehicles against angiogenesis

Design of optimal band-stop FIR filter using L1-norm based RCGA

In this paper, an optimal design of linear phase digital finite impulse response (FIR) band stop (BS) filter using the L1-norm based real-coded genetic algorithm (L1-RCGA) is presented. Although RCGA has proved its ability to overcome the drawbacks associated with conventional gradient-based optimization methods of filter design, it is applied here with a novel fitness function based on the L1-norm. This leads to a global optimal solution along with the improvement in filter design with same specifications. The designed filter pursues a better response in terms of flat passband, high stopband attenuation and fast convergence. The simulation results justify that the proposed FIR BS filter using L1-RCGA outperforms the existing optimization techniques, the L1-method and particle swarm optimization (PSO) and the conventional methods such as least-squares (LS) approach, Kaiser window method and the Parks McClellan (PM) algorithm. A detailed analysis is performed to evaluate the performance of the designed filters

Optimal design of FIR high pass filter based on L1 error approximation using real coded genetic algorithm

In this paper, an optimal design of linear phase digital finite impulse response (FIR) highpass (HP) filter using the L1-norm based real-coded genetic algorithm (RCGA) is investigated. A novel fitness function based on L1 norm is adopted to enhance the design accuracy. Optimized filter coefficients are obtained by defining the filter objective function in L1 sense using RCGA. Simulation analysis unveils that the performance of the RCGA adopting this fitness function is better in terms of signal attenuation ability of the filter, flatter passband and the convergence rate. Observations are made on the percentage improvement of this algorithm over the gradient-based L1 optimization approach on various factors by a large amount. It is concluded that RCGA leads to the best solution under specified parameters for the FIR filter design on account of slight unnoticeable higher transition width