Numerical Analysis of Performance Deterioration of a Centrifugal Pump Operating in Two-Phase Flows

Pumps handling two-phase flows are essential parts of industrial process mainly in oil and gas facilities and power plants. It is known that for centrifugal pumps the presence of gas phase in liquid flow causes the performance to deteriorate. Knowledge improvement of the highly complex internal flow is the way to design more efficient and reliable pumps. The paper describes the results of studies conducted in a centrifugal pump operating in two-phase air/water mixture flows, for performance determination and flow field investigation using numerical simulations. The aim is to provide a new highlight on the performance evolution and to identify the physical mechanism responsible for the deterioration. The work is carried out at design flow rate with varying inlet gas volume fraction. The results show significant performance deterioration compared to single-phase situation. The analysis of flow fields in case of two-phase flows reveals an accumulation of the gas in the impeller passages, causing an alteration of the conventional single-phase flow structure. The effect of interaction with volute is also investigated and it is found to play a key role in changing the flow pattern inside the impeller. At the conclusion of the study, special design features are suggested as concepts for enhancing two-phase pumping behavior of centrifugal pumps

A mobile assisted coverage hole patching scheme based on particle swarm optimization for WSNs

Wireless sensor networks (WSNs) have drawn much research attention in recent years due to the superior performance in multiple applications, such as military and industrial monitoring, smart home, disaster restoration etc. In such applications, massive sensor nodes are randomly deployed and they remain static after the deployment, to fully cover the target sensing area. This will usually cause coverage redundancy or coverage hole problem. In order to effectively deploy sensors to cover whole area, we present a novel node deployment algorithm based on mobile sensors. First, sensor nodes are randomly deployed in target area, and they remain static or switch to the sleep mode after deployment. Second, we partition the network into grids and calculate the coverage rate of each grid. We select grids with lower coverage rate as candidate grids. Finally, we awake mobile sensors from sleep mode to fix coverage hole, particle swarm optimization (PSO) algorithm is used to calculate moving position of mobile sensors. Simulation results show that our algorithm can effectively improve the coverage rate of WSNs

Iterative Reconstructions in Reduced-Dose CT: Which Type Ensures Diagnostic Image Quality in Young Oncology Patients?

To compare adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms for reduced-dose computed tomography (CT). Forty-four young oncology patients (mean age 30 ± 9 years) were included. After routine thoraco-abdominal CT (dose 100%, average CTDI javax.xml.bind.JAXBElement@e7f585f 9.1 ± 2.4 mGy, range 4.4-16.9 mGy), follow-up CT was acquired at 50% (average CTDI javax.xml.bind.JAXBElement@2e35610f 4.5 ± 1.2 mGy, range 2.2-8.4 mGy) in 29 patients additionally at 20% dose (average CTDI javax.xml.bind.JAXBElement@37ad3473 1.9 ± 0.5 mGy, range 0.9-3.4 mGy). Each reduced-dose CT was reconstructed using both ASIR and MBIR. Four radiologists (two juniors and two seniors) blinded to dose and technique read each set of CT images regarding objective and subjective image qualities (high- or low-contrast structures), subjective noise or pixilated appearance, diagnostic confidence, and lesion detection. At all dose levels, objective image noise was significantly lower with MBIR than with ASIR (P < 0.001). The subjective image quality for low-contrast structures was significantly higher with MBIR than with ASIR (P < 0.001). Reduced-dose abdominal CT images of patients with higher body mass index (BMI) were read with significantly higher diagnostic confidence than images of slimmer patients (P < 0.001) and had higher subjective image quality, regardless of technique. Although MBIR images appeared significantly more pixilated than ASIR images, they were read with higher diagnostic confidence, especially by juniors (P < 0.001). Reduced-dose CT during the follow-up of young oncology patients should be reconstructed with MBIR to ensure diagnostic quality. Elevated body mass index does not hamper the quality of reduced-dose CT

Use of Mathcad as a teaching and learning tool for reinforced concrete design of footings

Owing to their nature, numerous and complex equations are commonly used in the design of reinforced concrete structures. This is because of the nature of reinforced concrete design. Mathcad, which possesses efficient computation and presentation capabilities, holds strong potential as a teaching tool and learning aid for education and training. This article demonstrates the use of Mathcad to supplement and enhance traditional teaching and learning methods for reinforced concrete design. The article, which focuses on the topic of foundation design, demonstrates a Mathcad program for the design of combined footings and shows its impact as a teaching and learning tool.Wiley Online Librar

Structure Mixture Response Of Buildings Due To Simulated Earthquake Loading

This paper presents two case studies to evaluate the performance of the structure mixture theory in the earthquake response analysis of buildings. In the first case study, the actual earthquake responses of the two-story reinforced concrete building, which was tested at the University of California at Berkeley, were compared to those obtained using the structure mixture theory. In the second case study, the seven-story reinforced concrete building, which was tested as a part of the US-Japan Cooperative Earthquake Program, was considered. Both case studies showed that the structure mixture theory results were very close to experimental results. The mean differences between the maximum roof displacements obtained experimentally in the first and second case studies and those obtained using the structure mixture theory were found to be equal to 3.5% and 3.2%, respectively

Cost optimization of composite beams using genetic algorithms

This paper presents a genetic algorithm model for the cost optimization of composite beams based on the load and resistance factor design (LRFD) specifications of the AISC. The model formulation includes the cost of concrete, steel beam, and shear studs. Two design examples taken from the literature were analyzed in order to validate the proposed model, to illustrate its use, and to demonstrate its capabilities in optimizing composite beam designs. The results obtained show that the model is capable of achieving substantial cost savings. Hence, it can be of practical value to structural designers. A parametric study was also conducted to investigate the effects of beam spans and loadings on the cost optimization of composite beams

An Evidential Approach for Network Interface Selection in Heterogeneous Wireless Networks

International audienceWhen several networks (e.g., Wi-Fi, UMTS, and LTE) cover the same region, the mobile terminals that are equipped with multiple network interfaces provide the possibility for mobile end-users to select their believed best network. This is known as the network selection problem, which is a decision making problem with multiple criteria (network conditions, service requirements, terminal characteristics, and user needs). Many network selection solutions using different mathematical theories have been proposed in the literature to allow the best connectivity for applications, users, and terminals. Unfortunately, most approaches for the network selection do not make effective selection decisions, since they are vulnerable to the uncertainty and imprecision related to network state information. In this paper, we investigate the belief functions theory to devise an efficient lightweight uncertainty- aware network interface selection scheme. We provide analytical studies and simulation experiments to demonstrate the efficiency of the proposed solution