Study of a Multistage Canned Motor Pump: Simulation, Optimization and Validation

2019 ◽  
Author(s):  
Helmut Benigni ◽  
Markus Mosshammer ◽  
Helmut Jaberg
Keyword(s):  
Early Stage ◽  
Turbulence Models ◽  
Relative Increase ◽  
Cfd Simulations ◽  
Loss Analysis ◽  
Wide Range ◽  
Structured Meshes ◽  
Optimized Model ◽  
Main Components ◽  
Canned Motor

Abstract This paper describes the detailed analysis of a multistage canned motor pump with an additional radial suction impeller by means of CFD simulations to determine the main losses and to establish optimization potential of the hydraulic parts. In addition to the main flow channels of the impeller, the degree of detail of the analysis also includes the front and rear impeller side spaces, relief holes, gaps, return sections and all hydraulically wetted surfaces of the canned motor. The model presented was successively generated and already at a very early stage it was obvious that the model has to contain all details mentioned in order to provide valuable simulation results. For the impeller, the gaps and the pressure relief holes primarily structured meshes were used with a final model of the existing pump consisting of more than 35 million nodes. The behavior of the main components was analyzed in detail and additionally the CFD simulations — stationary and transient — with scale resolving turbulence models were validated by means of model tests. Furthermore, a comprehensive loss analysis of the existing pump was performed to verify the optimization potential. The subsequent optimization was realized semi-automated. A tight corset of requirements, e.g. identical head curve, suction behavior and dimensions, has been defined to guarantee retrofit capability of the pump analyzed in order to fully satisfy the demand for a constant delivery head curve and at the same time to provide for a relative increase of the optimum efficiency by 25% and in a wide range of applications by at least 20%. The optimized model was manufactured based on rapid prototyping and tested in the laboratory. The results show a satisfying correlation between the numerically predicted and the measured results on the test rig and prove the high quality of the numerical simulations run.

Simulation of Buoyancy-Driven Flow for Various Power Levels at the NSTF

2016 ◽  
Author(s):  
Adam R. Kraus ◽  
Rui Hu ◽  
Darius D. Lisowski ◽  
Matthew Bucknor
Keyword(s):  
Natural Convection ◽  
Cooling System ◽  
Heated Surface ◽  
Turbulence Models ◽  
Operating Conditions ◽  
Heated Wall ◽  
Test Facility ◽  
Cfd Simulations ◽  
Wide Range ◽  
Convection Model

The Reactor Cavity Cooling System (RCCS) is an important passive safety system that is being incorporated in a number of high temperature reactor design concepts. The Natural convection Shutdown heat removal Test Facility (NSTF), located at Argonne National Laboratory, is an experiment with the objective of investigating the flow and thermal behavior of a particular air-cooled RCCS design. It consists of 12 ducts surrounded by a cavity with a heated wall, through which air flows via natural convection before exiting through two chimneys. The NSTF is a ½-scale facility, and is well instrumented in order to provide data for code validation, including Computational Fluid Dynamics (CFD)-grade data in a number of locations. Instrumentation includes fiber-optic Distributed Temperature Sensors (DTS) throughout one of the riser ducts and in the upper plenum. In conjunction with the experimental tests, CFD simulations were performed to support the design and optimization of these natural convection systems. The CFD simulations were performed using the “as-tested” geometry of the NSTF. All CFD simulations were steady-state. Both a full natural convection model and a smaller forced primary flow model were tested. The influence of boundary conditions, notably at the cavity walls, was tested. Initial simulations assumed adiabatic walls but these were later adapted to simulate heat losses, aided by thermal images taken of the exterior NSTF surfaces during testing. Simulations were run for tests at two different power levels. A number of turbulence models were compared to test their influence. Simulation results were compared with experimental data. Convergence was generally good for both models. It was found that the natural convection model was indeed beneficial for correctly estimating local temperatures in a number of areas, particularly near the top of the riser ducts and from DTS measurements along the flow path. Flow in the heated cavity was complex. In general, the experimental trends were predicted well by CFD, although magnitudes could be improved in some areas. The turbulence models tested had a relatively small effect on the shape of the temperature profile in the ducts and on heated surface temperatures. Results from the simulations have been of direct use in improving test procedures and choosing locations for more accurate instrumentation. In future work, full natural convection simulations of more tests will be performed. After this has been completed, best practices can be established for accurately simulating these general types of natural convection systems across a wide range of operating conditions.

scholarly journals Photonic Crystal Nanobeam Cavities for Nanoscale Optical Sensing: A Review

Micromachines ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 72 ◽  
Author(s):  
Da-Quan Yang ◽  
Bing Duan ◽  
Xiao Liu ◽  
Ai-Qiang Wang ◽  
Xiao-Gang Li ◽  
...  
Keyword(s):  
Photonic Crystal ◽  
Optical Waveguides ◽  
Optical Sensing ◽  
Early Stage ◽  
Disease Diagnosis ◽  
Label Free ◽  
Quality Factors ◽  
Integrated Sensor ◽  
Early Stage Disease ◽  
Wide Range

The ability to detect nanoscale objects is particular crucial for a wide range of applications, such as environmental protection, early-stage disease diagnosis and drug discovery. Photonic crystal nanobeam cavity (PCNC) sensors have attracted great attention due to high-quality factors and small-mode volumes (Q/V) and good on-chip integrability with optical waveguides/circuits. In this review, we focus on nanoscale optical sensing based on PCNC sensors, including ultrahigh figure of merit (FOM) sensing, single nanoparticle trapping, label-free molecule detection and an integrated sensor array for multiplexed sensing. We believe that the PCNC sensors featuring ultracompact footprint, high monolithic integration capability, fast response and ultrahigh sensitivity sensing ability, etc., will provide a promising platform for further developing lab-on-a-chip devices for biosensing and other functionalities.

scholarly journals Non-Albumin Proteinuria (NAP) as a Complementary Marker for Diabetic Kidney Disease (DKD)

Life ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 224
Author(s):  
Jaehyun Bae ◽  
Young Jun Won ◽  
Byung-Wan Lee
Keyword(s):  
Kidney Disease ◽  
Filtration Rate ◽  
Diabetic Kidney Disease ◽  
Estimated Glomerular Filtration Rate ◽  
Early Stage ◽  
Screening Tools ◽  
Tubular Injury ◽  
Current Standard ◽  
Diabetic Kidney ◽  
Wide Range

Diabetic kidney disease (DKD) is one of the most common forms of chronic kidney disease. Its pathogenic mechanism is complex, and it can affect entire structures of the kidney. However, conventional approaches to early stage DKD have focused on changes to the glomerulus. Current standard screening tools for DKD, albuminuria, and estimated glomerular filtration rate are insufficient to reflect early tubular injury. Therefore, many tubular biomarkers have been suggested. Non-albumin proteinuria (NAP) contains a wide range of tubular biomarkers and is convenient to measure. We reviewed the clinical meanings of NAP and its significance as a marker for early stage DKD.

Performance enhancement of Savonius wind turbine by blade shape and twisted angle modifications

2021 ◽  
pp. 095765092098794
Author(s):  
Ahmed M Nagib Elmekawy ◽  
Hassan A Hassan Saeed ◽  
Sadek Z Kassab
Keyword(s):  
Wind Turbine ◽  
Performance Enhancement ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Vertical Axis ◽  
Cfd Simulations ◽  
Sliding Mesh ◽  
Blade Shape ◽  
Rotor Shape ◽  
Twisting Angle

Three-dimensional CFD simulations are carried out to study the increase of power generated from Savonius vertical axis wind turbines by modifying the blade shape and blade angel of twist. Twisting angle of the classical blade are varied and several proposed novel blade shapes are introduced to enhance the performance of the wind turbine. CFD simulations have been performed using sliding mesh technique of ANSYS software. Four turbulence models; realizable k -[Formula: see text], standard k - [Formula: see text], SST transition and SST k -[Formula: see text] are utilized in the simulations. The blade twisting angle has been modified for the proposed dimensions and wind speed. The introduced novel blade increased the power generated compared to the classical shapes. The two proposed novel blades achieved better power coefficients. One of the proposed models achieved an increase of 31% and the other one achieved 32.2% when compared to the classical rotor shape. The optimum twist angel for the two proposed models achieved 5.66% and 5.69% when compared with zero angle of twist.

scholarly journals Contagion Management at the Méditerranée Infection University Hospital Institute

2021 ◽  
Vol 10 (12) ◽  
pp. 2627
Author(s):  
Pierre-Edouard Fournier ◽  
Sophie Edouard ◽  
Nathalie Wurtz ◽  
Justine Raclot ◽  
Marion Bechet ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Early Diagnosis ◽  
Personal Protective Equipment ◽  
Early Stage ◽  
Point Of Care ◽  
University Hospital ◽  
Protective Equipment ◽  
Monitoring Point ◽  
Epidemiological Monitoring ◽  
Wide Range

The Méditerranée Infection University Hospital Institute (IHU) is located in a recent building, which includes experts on a wide range of infectious disease. The IHU strategy is to develop innovative tools, including epidemiological monitoring, point-of-care laboratories, and the ability to mass screen the population. In this study, we review the strategy and guidelines proposed by the IHU and its application to the COVID-19 pandemic and summarise the various challenges it raises. Early diagnosis enables contagious patients to be isolated and treatment to be initiated at an early stage to reduce the microbial load and contagiousness. In the context of the COVID-19 pandemic, we had to deal with a shortage of personal protective equipment and reagents and a massive influx of patients. Between 27 January 2020 and 5 January 2021, 434,925 nasopharyngeal samples were tested for the presence of SARS-CoV-2. Of them, 12,055 patients with COVID-19 were followed up in our out-patient clinic, and 1888 patients were hospitalised in the Institute. By constantly adapting our strategy to the ongoing situation, the IHU has succeeded in expanding and upgrading its equipment and improving circuits and flows to better manage infected patients.

scholarly journals Design of Personalized Devices—The Tradeoff between Individual Value and Personalization Workload

2020 ◽  
Vol 11 (1) ◽  
pp. 241
Author(s):  
Juliane Kuhl ◽  
Andreas Ding ◽  
Ngoc Tuan Ngo ◽  
Andres Braschkat ◽  
Jens Fiehler ◽  
...  
Keyword(s):  
Customer Value ◽  
Early Stage ◽  
Treatment Success ◽  
Product Family ◽  
Flow Diverter ◽  
New Method ◽  
Product Families ◽  
Wide Range ◽  
The Individual ◽  
Individual Value

Personalized medical devices adapted to the anatomy of the individual promise greater treatment success for patients, thus increasing the individual value of the product. In order to cater to individual adaptations, however, medical device companies need to be able to handle a wide range of internal processes and components. These are here referred to collectively as the personalization workload. Consequently, support is required in order to evaluate how best to target product personalization. Since the approaches presented in the literature are not able to sufficiently meet this demand, this paper introduces a new method that can be used to define an appropriate variety level for a product family taking into account standardized, variant, and personalized attributes. The new method enables the identification and evaluation of personalizable attributes within an existing product family. The method is based on established steps and tools from the field of variant-oriented product design, and is applied using a flow diverter—an implant for the treatment of aneurysm diseases—as an example product. The personalization relevance and adaptation workload for the product characteristics that constitute the differentiating product properties were analyzed and compared in order to determine a tradeoff between customer value and personalization workload. This will consequently help companies to employ targeted, deliberate personalization when designing their product families by enabling them to factor variety-induced complexity and customer value into their thinking at an early stage, thus allowing them to critically evaluate a personalization project.

scholarly journals Integration of early disease-resistance phenotyping, histological characterization, and transcriptome sequencing reveals insights into downy mildew resistance in impatiens

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ze Peng ◽  
Yanhong He ◽  
Saroj Parajuli ◽  
Qian You ◽  
Weining Wang ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Downy Mildew ◽  
Transcriptome Sequencing ◽  
Early Stage ◽  
Economic Losses ◽  
Potential Candidate ◽  
Early Disease ◽  
True Leaf ◽  
Cotyledon Stage ◽  
Wide Range

AbstractDowny mildew (DM), caused by obligate parasitic oomycetes, is a destructive disease for a wide range of crops worldwide. Recent outbreaks of impatiens downy mildew (IDM) in many countries have caused huge economic losses. A system to reveal plant–pathogen interactions in the early stage of infection and quickly assess resistance/susceptibility of plants to DM is desired. In this study, we established an early and rapid system to achieve these goals using impatiens as a model. Thirty-two cultivars of Impatiens walleriana and I. hawkeri were evaluated for their responses to IDM at cotyledon, first/second pair of true leaf, and mature plant stages. All I. walleriana cultivars were highly susceptible to IDM. While all I. hawkeri cultivars were resistant to IDM starting at the first true leaf stage, many (14/16) were susceptible to IDM at the cotyledon stage. Two cultivars showed resistance even at the cotyledon stage. Histological characterization showed that the resistance mechanism of the I. hawkeri cultivars resembles that in grapevine and type II resistance in sunflower. By integrating full-length transcriptome sequencing (Iso-Seq) and RNA-Seq, we constructed the first reference transcriptome for Impatiens comprised of 48,758 sequences with an N50 length of 2060 bp. Comparative transcriptome and qRT-PCR analyses revealed strong candidate genes for IDM resistance, including three resistance genes orthologous to the sunflower gene RGC203, a potential candidate associated with DM resistance. Our approach of integrating early disease-resistance phenotyping, histological characterization, and transcriptome analysis lay a solid foundation to improve DM resistance in impatiens and may provide a model for other crops.

scholarly journals Early Dropout Prediction in MOOCs through Supervised Learning and Hyperparameter Optimization

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1701
Author(s):  
Theodor Panagiotakopoulos ◽  
Sotiris Kotsiantis ◽  
Georgios Kostopoulos ◽  
Omiros Iatrellis ◽  
Achilles Kameas
Keyword(s):  
Online Education ◽  
Online Courses ◽  
Early Stage ◽  
Activity Patterns ◽  
Daily Basis ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Educational Institutions ◽  
Student Dropout ◽  
Wide Range

Over recent years, massive open online courses (MOOCs) have gained increasing popularity in the field of online education. Students with different needs and learning specificities are able to attend a wide range of specialized online courses offered by universities and educational institutions. As a result, large amounts of data regarding students’ demographic characteristics, activity patterns, and learning performances are generated and stored in institutional repositories on a daily basis. Unfortunately, a key issue in MOOCs is low completion rates, which directly affect student success. Therefore, it is of utmost importance for educational institutions and faculty members to find more effective practices and reduce non-completer ratios. In this context, the main purpose of the present study is to employ a plethora of state-of-the-art supervised machine learning algorithms for predicting student dropout in a MOOC for smart city professionals at an early stage. The experimental results show that accuracy exceeds 96% based on data collected during the first week of the course, thus enabling effective intervention strategies and support actions.

scholarly journals Imaging features and differential diagnoses of non-neoplastic diffuse mediastinal diseases

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Flavian Tabotta ◽  
Gilbert R. Ferretti ◽  
Helmut Prosch ◽  
Samia Boussouar ◽  
Anne-Laure Brun ◽  
...  
Keyword(s):  
Early Stage ◽  
Specific Treatment ◽  
Imaging Features ◽  
Mediastinal Diseases ◽  
Pictorial Review ◽  
Wide Range ◽  
Chest X Ray ◽  
Delayed Recognition ◽  
Patient’S History ◽  
Contiguous Spread

Abstract Acute or chronic non-neoplastic diffuse mediastinal diseases have multiple causes, degrees of severity, and a wide range of management. Some situations require emergency care while others do not need specific treatment. Although the diagnosis may be suspected on chest X-ray, it is mainly based on CT. A delayed recognition is not uncommonly observed. Some findings may prompt the radiologist to look for specific associated injuries or lesions. This pictorial review will successively describe the various non-neoplastic causes of diffuse mediastinal diseases with their typical findings and major differentials. First, pneumomediastinum that can be provoked by extra- or intra-thoracic triggers requires the knowledge of patient’s history or recent occurrences. Absence of any usual etiological factor should raise suspicion of cocaine inhalation in young individuals. Next, acute mediastinitis may be related to post-operative complications, esophageal perforation, or contiguous spread of odontogenic or retropharyngeal infections. The former diagnosis is not an easy task in the early stage, owing to the similarities of imaging findings with those of normal post-operative appearance during the first 2–3 weeks. Finally, fibrosing mediastinitis that is linked to an excessive fibrotic reaction in the mediastinum with variable compromise of mediastinal structures, in particular vascular and airway ones. Differential diagnosis includes tumoral and inflammatory infiltrations of the mediastinum.

scholarly journals Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report)

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Paul Erhardt ◽  
Kenneth Bachmann ◽  
Donald Birkett ◽  
Michael Boberg ◽  
Nicholas Bodor ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecule ◽  
Chemical Structure ◽  
Early Stage ◽  
Xenobiotic Metabolism ◽  
Drug Discovery And Development ◽  
Small Molecule Drug ◽  
Technical Report ◽  
Wide Range ◽  
Draft Version

Abstract This project originated more than 15 years ago with the intent to produce a glossary of drug metabolism terms having definitions especially applicable for use by practicing medicinal chemists. A first-draft version underwent extensive beta-testing that, fortuitously, engaged international audiences in a wide range of disciplines involved in drug discovery and development. It became clear that the inclusion of information to enhance discussions among this mix of participants would be even more valuable. The present version retains a chemical structure theme while expanding tutorial comments that aim to bridge the various perspectives that may arise during interdisciplinary communications about a given term. This glossary is intended to be educational for early stage researchers, as well as useful for investigators at various levels who participate on today’s highly multidisciplinary, collaborative small molecule drug discovery teams.

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