Among the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For higher concentration, the agglomeration can occur so the scattering of laser light was increased resulting in the decrement of output power. Laser with longer wavelength (650nm) at visible spectral region was more sensing compared with 532 nm laser for low concentration of Ag inside deionized water. The starting sensing powers of 532nm CW diode laser is 0.1W of these concentrations for this type of nanofluid while the ending detection power is 1W.
Nanofluids are proven to be efficient agents for wettability alteration in subsurface applications including enhanced oil recovery (EOR). Nanofluids can also be used for CO2-storage applications where the CO2-wet rocks can be rendered strongly water-wet, however no attention has been given to this aspect in the past. Thus in this work we presents contact angle (θ) measurements for CO2/brine/calcite system as function of pressure (0.1 MPa, 5 MPa, 10 MPa, 15 MPa, and 20 MPa), temperature (23 °C, 50 °C and 70 °C), and salinity (0, 5, 10, 15, and 20% NaCl) before and after nano-treatment to address the wettability alteration efficiency. Moreover, the effect of treatment pressure and temperature, treatment fluid concentration (SiO2 wt%) and
... Show MoreWorldwide attention is being focused on nanocrystalline zeolites and they are replacing conventional ones due to their pronounced potential in many fields. In this study, NaY zeolite has been prepared hydrothermally using sol –gel method and modified to the proton type by ion –exchange process. Characterization is made using X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), Atomic force microscopy (AFM), Brunauer –Emmet- Teller (BET) nitrogen adsorption method, Ammonia Temperature programmed desorption (NH3-TPD) and Scanning electron microscopy( SEM). The effect of aging time, silica to alumina ratio is studied and the results sh
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One of the most important problems in the statistical inference is estimating parameters and Reliability parameter and also interval estimation , and testing hypothesis . estimating two parameters of exponential distribution and also reliability parameter in a stress-strength model.
This parameter deals with estimating the scale parameter and the Location parameter µ , of two exponential distribution ,using moments estimator and maximum likelihood estimator , also we estimate the parameter R=pr(x>y), where x,y are two- parameter independent exponential random variables .
Statistical properties of this distribution and its properti
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Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of
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Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the
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