Electrostatic Gas-Liquid Separation from High Speed Streams--Application to Advanced On-Line/On- Demand Separation Techniques

The separation of suspended droplets from gases has been one of the basic scientific and technical problems of the industrial era and this interest continues. Various industrial applications, such as refrigeration and HVAC systems, require control of fine droplets concentrations in moving gaseous mediums to maintain system functionality and efficiency. Separating of such fine droplets can be achieved using electrostatic charging as implemented in electrostatic precipitators (ESPs). They use electrostatic force to charge and collect solid particles. The objective of the present work was to study the feasibility of using wiretube electrostatic separator on the removal of fine water and oil droplets from air stream based on corona discharge ionization process. A parametric study was conducted to find key parameters affecting the separation process. This goal was approached by simulating the charging and separation phenomena numerically, and then verifying the modeling findings through experiments. The numerical methodology simulated the highly complex interaction between droplets suspended in the flow and electrical field. Two test rigs were constructed, one for air-water separation and the other for air-oil separation. A wiretube electrostatic separator was used as the test section for both test rigs. The separation performance was evaluated under different electric field and flow conditions. Finally, based on the results, a novel air-water separator prototype was designed, fabricated and tested. The numerical modeling results qualitatively showed acceptable agreement with the experimental data in terms of the trend of grade efficiency based on droplets size. Both numerical modeling results and experimental data showed that with a proper separator design, high separation efficiency is achievable for water and oil droplets. Based on the experimental data, at flow velocity of 5 m/s and applied voltage of 7.0 kV, the maximum separation efficiency for water and oil was 99.999 % and 96.267 %, respectively. The pressure drop was as low as 100 Pa and maximum power consumption was 12.0 W

THE INTERACTIVE SIMULATION OF MARS DUST STORMS WITH THE MARS GENERAL CIRCULATION MODEL MARSWRF AT THE RESOLUTION OF 7.5°×9° (LATITUDE BY LONGITUDE)

The Mars dust cycle, including dust storms, has a great impact on the temperature, and the climate in general, on Mars. Dust particles in the atmosphere have a great capacity for absorbing/emitting infrared radiation resulting in large changes in the Martian climate. Local and regional dust storms occur in any Martian Year (MY), but global dust storm events (GDEs), which can cover the whole planet, occur, on average, once every 3-4 MYs. MarsWRF is a Mars version of the terrestrial numerical weather and climate model WRF (Weather Research and Forecasting Model) and part of the Planet WRF models for planetary atmosphere research. This requires model calibration by trial and error. The main focus is the formation of global dust storm events. The technique is to run MarsWRF in interactive dust mode. This requires the model user to self-specify the model parameters of the surface dust lifting by dust storms and dust devils. In this thesis, the MarsWRF model is run in interactive dust mode at the classical resolution of 7.5°×9° (latitude by longitude). The resulting dust storms will be compared against higher resolution simulations in Gebhardt et al. (2020)

THE IMPACT OF AN ENRICHMENT PROGRAM ON UAE HIGH SCHOOL STUDENTS’ CREATIVE PROBLEM SOLVING SKILLS

Training human resources to be creative and innovate in the UAE had become a significant matter recently to stay within the stage of progressing towards a more dependable economy rather than oil. Gifted and talented individuals are the country\u27s main resources, and way to progress. This study, therefore, aims to explore the impact of an enrichment program on improving UAE high school gifted students’ creative problem-solving skills. The sample included 78 gifted students from Abu Dhabi government schools. The students were grouped randomly into a control group (27 students), and an experimental group (30 students) who were exposed to a five-week enrichment program through which they practiced various strategies including SCAMPER strategy. To answer the research questions, two instruments were used including Problem-Solving Questionnaire (PSQ) and SCAMPER test. Pre and posttests were analyzed using independent samples T-test to examine the effect of the enrichment program on the participants’ level of awareness of problem solving skills and on their creative problem-solving skills. Findings of this study indicated that the enrichment program produced significant improvements in high school gifted students’ creative problem-solving skills. Additionally, the awareness level of the experimental group in the problem-solving steps is significantly higher after the program. School administrators and teachers should consider using the direct instruction and SCAMPER strategies to enhance their students ‘creative problem-solving skills

Detection of exomoons in simulated light curves with a regularized convolutional neural network

Many moons have been detected around planets in our Solar System, but none has been detected unambiguously around any of the confirmed extrasolar planets. We test the feasibility of a supervised convolutional neural network to classify photometric transit light curves of planet-host stars and identify exomoon transits, while avoiding false positives caused by stellar variability or instrumental noise. Convolutional neural networks are known to have contributed to improving the accuracy of classification tasks. The network optimization is typically performed without studying the effect of noise on the training process. Here we design and optimize a 1D convolutional neural network to classify photometric transit light curves. We regularize the network by the total variation loss in order to remove unwanted variations in the data features. Using numerical experiments, we demonstrate the benefits of our network, which produces results comparable to or better than the standard network solutions. Most importantly, our network clearly outperforms a classical method used in exoplanet science to identify moon-like signals. Thus the proposed network is a promising approach for analyzing real transit light curves in the future

THE IMPACT OF RISK MANAGEMENT ON THE PERFORMANCE OF CONSTRUCTION PROJECTS

This research navigates the intricate landscape of the risk management in the construction industry. This paper also illuminates its profound influence on the success of the project. Diverse risk mitigation strategies have been investigated based on the impact of the same in the critical project metrics, such as adherence schedule, quality benchmark, and control of the cist; all this combined forms the foundation of this research. The objective of this research revolves around evaluating the correlation of the project's outcomes with the identification of risk. This quantifies the mitigation strategies' measurable impacts and compares their effectiveness in the stakeholders' satisfaction and the budget's control. With the empirical insights, this study aims to address the critical gap in understanding the direct link of risk management with the project's success. It equips the industry professional with evidence-based approaches to optimize risk practices, fostering resource allocation and resilience. The comparative analysis of risk management approaches empowers informed and appropriate decision-making. This reduces the disruption of and enhances financial outcomes. These findings signify a paradigm shift in project management in construction, advocating for a culture of effective and proactive risk management. It can revolutionize industry practices, increase predictability, and elevate the project's success. Implementing recommended strategies, inculcating adaptability cultivation, clear communication, and theoretical framework, and embracing complexity promises to enhance risk management effectively, guiding the instruction industry toward continuous improvement and innovatio

Organizational Knowledge Systems Design & Implementation

This research paper aims to explain relationships of   organization learning (OL), knowledge management (KM), talent management (TM) practices and organizational performance (OP) in order to have excellent understanding of the subject by using in-depth analysis of the extant literature. This research offers mechanisms for Organizational Knowledge Systems (OKS) that will help the entity to apply OKS. The research paper has created a complete mechanism of the OKS then tests the proposed model. Keywords: Organization Learning, Knowledge Management, Talent Management and Organization Knowledge Systems