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

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

Background: Displaced intracapsular fracture of the femoral neck remain a challenging issue despite the advancement in the ways of treatment .The purpose of this study is to assess the results of different methods of treatment in different age groups. Methods: This study was conducted over a period from (1998-2004) on 26 patients, with ages of 5 – 85 years with intracapsular fracture of the femoral neck due to different insults in Tikrit teaching hospital. Open reduction and internal fixation was done to those patients of<60 years of age, while uncemented Austin-Moore hemiarthroplasty was conducted in patients of >60 years old. Patients were followed for 6-12 months for any complication. Results: The main age group among the pati

In this research study Hardness (shore D), Water absorption,
Flexural, Impact Test, and Fracture Toughness of polymer nano
composites. The polymer nano composites based on unsaturated
polyester resin reinforced with Kevlar fibers (K.F). The samples are
attended by hand lay – up method according to (Rule mixture) for
various volume fractions of unsaturated polyester resin, fiber and
carbon nanotube. The polyester resin was matrix strengthened with
3% volume fraction from Kevlar fiber and (0.5%, 1%, 1.5%, 2%)
volume fractions of carbon nanotube. The water absorption, hardness
(shore D), flexural test, impact test and toughness fracture properties
were studied. Results showed that the water absorption increas

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, Robust-Proportional-Integral-Derivative (RPID) and structured singular value (M@#@) controllers have been d

Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

PID (proportional-integral-derivative) and Mu controllers are widely used in electro-hydraulic servo systems due to their effectiveness and ease of implementation. This paper explores using particle swarm optimization (PSO) for tuning traditional and robust PID controllers, along with D-K iteration for Mu controller tuning. Three controller types: conventional PID (CPID), robust PID (RPID), and structured singular value controllers are developed, while analyzing multiplicative uncertainty with six uncertain coefficients. Their findings indicated that both PID (CPID and RPID) and Mu controllers maintained system stability. Notably, the Mu controller can handle coefficient uncertainty without a pure integral term, while the RPID controller de

This article investigates the relationship between foot angle and jump stability, focusing on minimizing injury risk. Here are the key points: Importance: Understanding foot angle is crucial for improving jump stability, athletic performance, and reducing jump-related injuries like ankle sprains. Ideal Foot Angle: Research suggests a forward foot angle of around 15 degrees might be ideal for many people during jumps. This angle distributes forces evenly across the foot, lowers the center of gravity, and provides more surface area for pushing off the ground. Factors Affecting Ideal Angle: The optimal angle can vary depending on the type of jump (vertical vs. long jump), fitness level, and personal preference. Incorrect Foot Angles: Landing w

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm