Journal of Engineering

An experimental and theoretical work was carried out to model the wire condenser in the domestic refrigerator by calculating the heat transfer coefficient and pressure drop and finding the optimum performance. The two methods used for calculation were the zone method and an integral method. The work was conducted using two wire condensers with equal length but different tube diameters, two refrigerants (R-134a and R-600a), and two different compressors matching the refrigerant type. In the experimental work, the optimum charge was found for the refrigerator according to ASHRAE recommendations. The tests were done at 32˚C ambient temperature in a closed room with dimensions (2m2m3m). The results showed that the average heat transfer coefficient for R-600a was higher than for R-134a, so the length of the wire tube was longer with R-134a than R-600a. The pressure drop for the smaller tube diameter was higher than for the other tube. The second law thermodynamic efficiency was higher for R-600a, reaching 41%. The entropy generation minimization analysis showed that the R-600a refrigerant type and smaller tube diameter approached the optimum point.

This study focuses on CFD analysis in the field of the shell and double concentric tube heat exchanger. A commercial CFD package was used to resolve the flow and temperature fields inside the shell and tubes of the heat exchanger used. Simulations by CFD are performed for the single shell and double concentric tube. This heat exchanger included 16 tubes and 20 baffles. The shell had a length of 1.18 m and its diameter was 220 mm. Solid Works 2014, ANSYS 15.0 software was used to analyze the fields of flow and temperature inside the shell and the tubes. The RNG k-ε model was used and it provided good results. Coarse and fine meshes were investigated, showing that aspect ratio has no significant effect. 14 million elements were used in the mesh. A comparison was made between the profiles of temperature and velocity for the experimental and results of the model and it had an acceptable adaptation.

Formation of emulsions during oil production is a costly problem, and decreased water content in emulsions leads to increased productivity and reduces the potential for pipeline corrosion and equipment used. The chemical demulsification process of crude oil emulsions is one of the methods used for reducing water content. The presence of a demulsifier causes the film layer between water droplets and the crude oil emulsion to become unstable, leading to the accelerated coalescence of water. This research was performed to study the performance of a chemical demulsifier Chimec2439 (commercial), a blend of non-ionic oil-soluble surfactants. The crude oils used in these experiments were Basrah and Kirkuk Iraqi crude oil. These experiments were done using different water-to-oil ratios. The study investigated the factors that play a role in demulsification processes, such as the concentration of demulsifier, water content, salinity, pH, and asphaltene content. The results showed that in Basrah crude oil, the average water droplet size was between 5.5–7.5 μm at 25% water content, while it was between 3.3–4 μm at 7% water content. In Kirkuk crude oil, at 7% water content, the droplet size was between 4.5–6 μm, while at 20% it was between 4–8 μm, and at 25% it was between 5–8.8 μm. It was found that the rate of separation increases with increasing concentration of demulsifier. For Basrah crude oil at 400 ppm, the separation was 83%, and for Kirkuk crude oil, it was 88%. The separation efficiency increased with increased water content and salt content. In Basrah crude oil, the separation rate was 84% at a salt dose of 3% (30,000 ppm) and 70.7% at zero salt. In Kirkuk crude oil, the separation rate was 86.2% at a salt dose of 3% (30,000 ppm) and 80% at zero salt.

Membrane distillation (MD) is a hopeful desalination technique for brine (salty) water. In this research, Direct Contact Membrane Distillation (DCMD) and Air Gap Membrane Distillation (AGMD) were used. The sample used is from Shat Al-Arab water (TDS=2430 mg/l). A polyvinylidene fluoride (PVDF) flat sheet membrane was used as a flat sheet form with a plate and frame cell. Several parameters were studied, such as operation time, feed temperature, permeate temperature, and feed flow rate. The results showed that with time, the flux decreases because of the accumulated fouling and scaling on the membrane surface. Feed temperature and feed flow rate had a positive effect on the permeate flux, while permeate temperature had a reverse effect on permeate flux. It is noticeable that the flux in DCMD is greater than AGMD, at the same conditions. The flux in DCMD is 10.95 LMH, and that in AGMD is 7.14 LMH. In AGMD, the air gap layer made a high resistance. Here the temperature transport reduces in the permeate side of AGMD due to the air gap resistance. The heat needed for AGMD is lower than DCMD, leading to low permeate flux because the temperature difference between the two sides is very small, so the driving force (vapor pressure) is low.

Mobile-based human emotion recognition is a challenging subject. Most approaches in this field utilize various contexts derived from external sensors and smartphones, but they face different obstacles and challenges. The proposed system integrates human speech signals and heart rate in one system to enhance the accuracy of human emotion recognition. The system is designed to recognize four human emotions: angry, happy, sad, and normal. The smartphone records user speech and sends it to a server, while a smartwatch measures the user's heart rate during speech and sends it via Bluetooth to the smartphone, which then sends it to the server. At the server side, speech features are extracted and classified by a neural network. To minimize misclassification, the user's heart rate measurement directs the extracted speech features to either an excited (angry and happy) neural network or a calm (sad and normal) neural network. Despite the challenges, the system achieved 96.49% accuracy for known speakers and 79.05% for unknown speakers.

Smear zone is usually formed around the prefabricated vertical drains (PVD’s) due to mandrel driving. The geotechnical properties of the soil in this zone exhibit significant changes that affect the performance of the PVD’s. The most relevant property in this respect is the coefficient of permeability. So far, no serious attention is paid to investigate the effects of shearing under large shear strains on the geotechnical properties of the soft soil in Fao region. In this study, an extensive laboratory testing program was conducted to assess the characteristics of the smear zone with an emphasis on the permeability coefficient of Fao soft soil. The results show that the permeability of the smear zone is about 70% of the horizontal permeability of the intact soil. An attempt was made to estimate the extension of the shearing zone in the direct shear test. The analysis results indicate that thickness of the shearing zone is about (2.4) cm.

This paper discusses the limitation of both Sequence Covering Array (SCA) and Covering Array (CA) for testing reactive systems when the order of parameter-values is sensitive. In doing so, this paper proposes a new model to take the sequence values into consideration. Accordingly, by superimposing the CA onto SCA yields another type of combinatorial test suite termed Multi-Valued Sequence Covering Array (MVSCA) in a more generalized form. This superimposing is a challenging process due to NP-Hardness for both SCA and CA. Motivated by such a challenge, this paper presents the MVSCA with a working illustrative example to show the similarities and differences among combinatorial testing methods. Consequently, the MVSCA is a new trend that can be a research vehicle for researchers to develop new and/or modify existing combinatorial strategies to deal with the combinatorial explosion problem raised by the MVSCA.

The load shedding scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however, its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration of renewable energy resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is able to positively improve the stability of the electric grid. In this paper, a method for shedding the load based on the priority demands with incorporating the wind power generated is proposed. The higher priority demands are fed with a reliable wind energy resource in order to protect them from shedding under contingency conditions such as high overloading by the real-time monitoring of the network. The main objective of this research is to sustain enough power for higher important loads where possible and accurate amount of load shedding while keeping the load under the available power threshold. In such a case, the important loads such as health care are kept intact without any interruption as possible. The simulation results prove the effectiveness and practicality of the applied method paving the way for possible applications in power systems.