scholarly journals Reducing indoor particle exposure using mobile air purifiers – experimental and numerical analysis

2021 ◽  
Author(s):  
Adrian Tobisch ◽  
Lukas Springsklee ◽  
Lisa-Franziska Schaefer ◽  
Nico Sussmann ◽  
Martin J. Lehmann ◽  
...  
Keyword(s):  
Particle Concentration ◽  
Aerosol Particles ◽  
Air Flow ◽  
Measurement Data ◽  
Operating Conditions ◽  
Comfort Level ◽  
Lecture Hall ◽  
Risk Of Infection ◽  
Particle Exposure ◽  
Air Purifier

Aerosol particles are one of the main routes of transmission of COVID–19. Mobile air purifiers are used to reduce the risk of infection indoors. We focus on an air purifier which generates a defined volumetric air flow through a highly efficient filter material. We investigate the transport of aerosol particles from an infected dummy equipped with an aerosol generator to receiving thermal dummies. For analysis, we use up to 12 optical particle counters to monitor the particle concentration with high spatial resolution. Based on the measurement data, a computational fluid dynamics (CFD) model is set up and validated. The experimental and numerical methods are used to investigate how the risk of infection suggested by the particle exposure in an exemplary lecture hall can be reduced by a clever choice of orientation of the air purifier. The particle concentration at head height deviates by 13 % for variations of location and orientation. Finally, CFD simulation was used to monitor the particle fates. The steady simulation results fit quite well to the experimental findings and provide additional information about particle path and for assessing comfort level due to air flow. Practical implications: Different installation locations and operating conditions of the air purifier are evaluated and the use of thermal dummies mimics the conditions of practical use cases. The measurement results show the integral particle mass over time in the ″faces of the dummies″, representing the potentially inhaled particle load of persons present in the room. At an air change per hour of 5, the cumulated PM1 mass at head level was reduced by 75 %, independently of the location of the infected dummy, compared to the ″natural decay″ case showing that filtration is an effective means of reducing aerosol particle concentrations. It turns out that obstructing the outlet stream of the air purifier may be particularly advantageous.

Nitrogen Removal from Anaerobically-Treated Leachate

1984 ◽  
Vol 19 (1) ◽  
pp. 87-100
Author(s):  
D. Prasad ◽  
J.G. Henry ◽  
P. Elefsiniotis
Keyword(s):  
Nitrogen Removal ◽  
Air Flow ◽  
Operating Conditions ◽  
Air Flow Rate ◽  
Flow Rates ◽  
Anaerobic Filter ◽  
Ph Values ◽  
Wide Range ◽  
Ammonia Desorption ◽  
Effects Of Ph

Abstract Laboratory studies were conducted to demonstrate the effectiveness of diffused aeration for the removal of ammonia from the effluent of an anaerobic filter treating leachate. The effects of pH, temperature and air flow on the process were studied. The coefficient of desorption of ammonia, KD for the anaerobic filter effluent (TKN 75 mg/L with NH3-N 88%) was determined at pH values of 9, 10 and 11, temperatures of 10, 15, 20, 30 and 35°C, and air flow rates of 50, 120, and 190 cm3/sec/L. Results indicated that nitrogen removal from the effluent of anaerobic filters by ammonia desorption was feasible. Removals exceeding 90% were obtained with 8 hours aeration at pH of 10, a temperature of 20°C, and an air flow rate of 190 cm3/sec/L. Ammonia desorption coefficients, KD, determined at other temperatures and air flow rates can be used to predict ammonia removals under a wide range of operating conditions.

Experimental investigation of the air flow in a simplified underhood environment

2021 ◽  
pp. 095440702110597
Author(s):  
Randi Franzke ◽  
Simone Sebben ◽  
Emil Willeson
Keyword(s):  
Flow Field ◽  
Laser Doppler Anemometry ◽  
Fluid Dynamic ◽  
Air Flow ◽  
Measurement Data ◽  
Quality Measurement ◽  
Flow Distribution ◽  
Lateral Position ◽  
Reference Case ◽  
Lateral Direction

In this paper, a simplified underhood environment is proposed to investigate the air flow distribution in a vehicle-like set-up and provide high quality measurement data that can be used for the validation of Computational Fluid Dynamic methods. The rig can be equipped with two types of front openings representative for electrified vehicles. Furthermore, it is possible to install differently shaped blockages downstream of the fan to imitate large underhood components. The distance between the blockages and the fan can be varied in longitudinal and lateral direction. The measurements are performed with Laser Doppler Anemometry at a fixed distance downstream of the fan. The results show that the lack of an upper grille opening in the configuration for a battery electric vehicle has a notable impact on the flow field in the reference case without any downstream blockage. However, the differences in the flow field between the two front designs become less when a downstream obstruction is present. The longitudinal and lateral position of the blockages have a minor impact on the flow field compared to the shape of the obstacle itself.

Adaptation Application to Engine Modelling

2007 ◽  
Author(s):  
Jude Iyinbor
Keyword(s):  
Measurement Data ◽  
Engine Performance ◽  
Performance Model ◽  
Operating Conditions ◽  
Adaptation Process ◽  
Design Point ◽  
Component Map ◽  
Important Measurement ◽  
Unknown Component ◽  
Selection Of

The optimisation of engine performance by predictive means can help save cost and reduce environmental pollution. This can be achieved by developing a performance model which depicts the operating conditions of a given engine. Such models can also be used for diagnostic and prognostic purposes. Creating such models requires a method that can cope with the lack of component parameters and some important measurement data. This kind of method is said to be adaptive since it predicts unknown component parameters that match available target measurement data. In this paper an industrial aeroderivative gas turbine has been modelled at design and off-design points using an adaptation approach. At design point, a sensitivity analysis has been used to evaluate the relationships between the available target performance parameters and the unknown component parameters. This ensured the proper selection of parameters for the adaptation process which led to a minimisation of the adaptation error and a comprehensive prediction of the unknown component and available target parameters. At off-design point, the adaptation process predicted component map scaling factors necessary to match available off-design point performance data.

Calibration and Uncertainty Quantification of Gas Turbine Performance Models

2015 ◽  
Author(s):  
Manuel Arias Chao ◽  
Darrel S. Lilley ◽  
Peter Mathé ◽  
Volker Schloßhauer
Keyword(s):  
Uncertainty Quantification ◽  
Gas Turbine ◽  
Bayesian Approach ◽  
Least Squares Method ◽  
Measurement Data ◽  
Operating Conditions ◽  
Performance Models ◽  
Regression Problem ◽  
Calibration Problem ◽  
Calibration Parameters

Calibration and uncertainty quantification for gas turbine (GT) performance models is a key activity for GT manufacturers. The adjustment between the numerical model and measured GT data is obtained with a calibration technique. Since both, the calibration parameters and the measurement data are uncertain the calibration process is intrinsically stochastic. Traditional approaches for calibration of a numerical GT model are deterministic. Therefore, quantification of the remaining uncertainty of the calibrated GT model is not clearly derived. However, there is the business need to provide the probability of the GT performance predictions at tested or untested conditions. Furthermore, a GT performance prediction might be required for a new GT model when no test data for this model are available yet. In this case, quantification of the uncertainty of the baseline GT, upon which the new development is based on, and propagation of the design uncertainty for the new GT is required for risk assessment and decision making reasons. By using as a benchmark a GT model, the calibration problem is discussed and several possible model calibration methodologies are presented. Uncertainty quantification based on both a conventional least squares method and a Bayesian approach will be presented and discussed. For the general nonlinear model a fully Bayesian approach is conducted, and the posterior of the calibration problem is computed based on a Markov Chain Monte Carlo simulation using a Metropolis-Hastings sampling scheme. When considering the calibration parameters dependent on operating conditions, a novel formulation of the GT calibration problem is presented in terms of a Gaussian process regression problem.

scholarly journals Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics

2020 ◽  
Author(s):  
Pieter-Jan Daems ◽  
Y. Guo ◽  
S. Sheng ◽  
C. Peeters ◽  
P. Guillaume ◽  
...  
Keyword(s):  
High Frequency ◽  
Failure Modes ◽  
Measurement Data ◽  
Wind Farms ◽  
Frequency Measurement ◽  
Operating Conditions ◽  
Failure Data ◽  
The World ◽  
Operations And Maintenance ◽  
History Of

Abstract Wind energy is one of the largest sources of renewable energy in the world. To further reduce the operations and maintenance (O&M) costs of wind farms, it is essential to be able to accurately pinpoint the root causes of different failure modes of interest. An example of such a failure mode that is not yet fully understood is white etching cracks (WEC). This can cause the bearing lifetime to be reduced to 5–10% of its design value. Multiple hypotheses are available in literature concerning its cause. To be able to validate or disprove these hypotheses, it is essential to have historic high-frequency measurement data (e.g., load and vibration levels) available. In time, this will allow linking to the history of the turbine operating data with failure data. This paper discusses the dynamic loading on the turbine during certain events (e.g., emergency stops, run-ups, and during normal operating conditions). By combining the number of specific events that each turbine has seen with the severity of each event, it becomes possible to assess which turbines are most likely to show signs of damage.

scholarly journals Measurement of Thermal Comfort in Urban Public Spaces Semarang, Indonesia

2021 ◽  
Vol 29 (3) ◽  
Author(s):  
Rina Kurniati ◽  
Wakhidah Kurniawati ◽  
Diah Intan Kusumo Dewi ◽  
Mega Febrina Kusumo Astuti
Keyword(s):  
Thermal Comfort ◽  
Climate Model ◽  
Environmental Changes ◽  
Measurement Data ◽  
Public Spaces ◽  
Comfort Level ◽  
Design Elements ◽  
Central Java ◽  
Outdoor Environments ◽  
Road Geometry

Indonesia reported a maximum annual temperature rise of 0.3°C in urban regions. Semarang, the largest metropolitan city in the province of Central Java, is also experiencing an increase in temperature due to climate change therefore activities in urban public spaces are disrupted due to the absence of a comfortable temperature. Urban design elements, including land cover materials, road geometry, vegetation and traffic frequency expressed significant effects on micro-climate. Measurement of Thermal Comfort in Urban Public Spaces Semarang was carried out s at the micro level as an old historical district The Old Town and Chinatown. This increment indeed influences thermal comfort level in its outdoor environments which are important for comfortability of outdoor activity. This study aims to analyse surface temperature through Thermal Comfort Measurement. Data was obtained by measuring air temperature, wind speed and humidity in the morning, afternoon, and evening. Inverse distance weighted (IDW), thermal comfort calculations and micro-climate model were employed to evaluate existing physical conditions of these settlements. The results showed both Old Town and Chinatown observed thermal comfort value above 27°C and are categorized as uncomfortable for outdoor activities. This research is contributing to the need to further develop public spaces to potentially adapt to environmental changes.

scholarly journals Investigation of the ventilation situation in a lecture room of building 033 at the Universität der Bundeswehr München

2021 ◽  
Author(s):  
Christian J. Kähler ◽  
Thomas Fuchs ◽  
Rainer Hain
Keyword(s):  
Viral Load ◽  
Uv Light ◽  
Aerosol Particles ◽  
Ventilation System ◽  
Armed Forces ◽  
Risk Of Infection ◽  
Free Air ◽  
Lecture Room ◽  
Private And Public ◽  
Public Lives

The SARS-CoV-2 pandemic is limiting both the private and public lives of many people around the world. It is now considered certain that SARS-CoV-2 is transmitted via droplets, smear infection, and aerosol particles. While simple masks, spacing, and hand hygiene significantly reduce the risk of infection via the first two routes mentioned, the risk from aerosol particles remains. These small particles move with the air in the room and spread unhindered throughout it. To reduce the risk of infection from viruses present in aerosol particles, the following options exist. First, good respiratory masks can be worn to reduce the viral load in the inhaled air. Another option is to make the viruses harmless (e.g., by UV light). A third option is to reduce the viral load in the room by bringing in virus-free air and moving contaminated air out or cleaning the air in the room. To investigate how well virus load reduction via ventilation works in a real lecture room, measurements were carried out at the Universität der Bundeswehr München (University of the Federal Armed Forces Munich). The lecture room holds a maximum of approx. 90 people and has a ventilation system as well as 2 windows that can be opened. In the absence of a ventilation system in a comparable room, the effectiveness of a room air cleaner was also investigated.

scholarly journals Optimized Thermal Efficiency of Rotor and Stator Using CFD

2020 ◽  
Vol 6 (6) ◽  
pp. 29-37
Author(s):  
Md. Shahwaz Hussain ◽  
Sujata Pouranik
Keyword(s):  
Temperature Distribution ◽  
Air Flow ◽  
Operating Conditions ◽  
Electrical Machine ◽  
Total Efficiency ◽  
Transfer Pattern ◽  
Turbulence Effect ◽  
Total Temperature ◽  
Simulation Results ◽  
And Performance

The space between rotor and stator plays a very important role in the design and performance of rotating machinery. The thickness of the gap can vary considerably depending on the size and operating conditions for the different types of rotating machines. Analysis the air velocity and temperature distribution over the air flow gap in stator and motor. Changing the design of rotor to develop turbulence in air flow gap. Compare the velocity and temperature distribution of proposed design with previous studies. The simulation results pinpoint also the periodic heat transfer pattern from the rotor surface and this provides useful information for the prediction of the temperature distribution inside the rotating electrical machine. The simulation results of case-1 show about 117°C temperature inside the rotor machine. Then increase the number of slot inside the rotor machine the total temperature of the rotor machine decreases up to 76°C. Due to low temperature total efficiency of the system increases. And also reduces the loss due to heat. The turbulence effect inside the rotor increase in third case. Due to turbulence effect the air cover large amount of area inside the rotor. So total temperature of the rotor casing decreases. In a system where volume is held constant, there is a direct relationship between Pressure and Temperature. For this case, when the pressure increases then the temperature also increases. When the pressure decreases, then the temperature decreases. So pressure in third case decrease upto1.26Pa and temperature 76 °C.

Artificial Intelligence and Data Analytics for Virtual Flow Metering

2021 ◽  
Author(s):  
Anton Gryzlov ◽  
Liliya Mironova ◽  
Sergey Safonov ◽  
Muhammad Arsalan
Keyword(s):  
Machine Learning ◽  
Multiphase Flow ◽  
Real Time ◽  
Production Control ◽  
Measurement Data ◽  
Sufficient Accuracy ◽  
Operating Conditions ◽  
Machine Learning Techniques ◽  
Flow Metering ◽  
Oil Gas

Abstract Modern challenges in reservoir management have recently faced new opportunities in production control and optimization strategies. These strategies in turn rely on the availability of monitoring equipment, which is used to obtain production rates in real-time with sufficient accuracy. In particular, a multiphase flow meter is a device for measuring the individual rates of oil, gas and water from a well in real-time without separating fluid phases. Currently, there are several technologies available on the market but multiphase flow meters generally incapable to handle all ranges of operating conditions with satisfactory accuracy in addition to being expensive to maintain. Virtual Flow Metering (VFM) is a mathematical technique for the indirect estimation of oil, gas and water flowrates produced from a well. This method uses more readily available data from conventional sensors, such as downhole pressure and temperature gauges, and calculates the multiphase rates by combining physical multiphase models, various measurement data and an optimization algorithm. In this work, a brief overview of the virtual metering methods is presented, which is followed by the application of several advanced machine-learning techniques for a specific case of multiphase production monitoring in a highly dynamic wellbore. The predictive capabilities of different types of machine learning instruments are explored using a model simulated production data. Also, the effect of measurement noise on the quality of estimates is considered. The presented results demonstrate that the data-driven methods are very capable to predict multiphase flow rates with sufficient accuracy and can be considered as a back-up solution for a conventional multiphase meter.

scholarly journals Rubber Dam Isolation and High-Volume Suction Reduce Ultrafine Dental Aerosol Particles: An Experiment in a Simulated Patient

2020 ◽  
Vol 10 (18) ◽  
pp. 6345
Author(s):  
Julián Balanta-Melo ◽  
Albio Gutiérrez ◽  
Gustavo Sinisterra ◽  
María del Mar Díaz-Posso ◽  
David Gallego ◽  
...  
Keyword(s):  
Volume Fraction ◽  
Aerosol Particles ◽  
High Volume ◽  
Simulated Patient ◽  
Volume Distribution ◽  
Risk Of Infection ◽  
Dental Services ◽  
Total Particulate Matter ◽  
Rubber Dam ◽  
Average Size

The ongoing Coronavirus Disease 2019 (COVID-19) pandemic has triggered the paralysis of dental services ascribed to the potential spread of severe acute respiratory syndrome (SARS)-CoV-2. Aerosol-generating procedures (AGPs) are common in dentistry, which in turn increase the risk of infection of the dental personnel due to the salivary presence of SARS-CoV-2 in COVID-19 patients. The use of rubber dam isolation (RDI) and high-volume evacuators (HVE) during AGPs is recommended to control dental aerosols, but the evidence about their effectiveness is scarce. This first study aimed to compare, in a simulated patient, the effectiveness of the following strategies: standard suction (SS), RDI and RDI + HVE. Using the laser diffraction technique, the effect of each condition on the volume distribution, average size and concentration of coarse (PM10), fine (PM2.5) and ultrafine (PM0.1) particles were evaluated. During the teeth drilling, the highest volume fraction of dental aerosol particles with SS was below 1 μm of aerodynamic diameter. Additionally, the RDI + HVE significantly reduced both the ultrafine dental aerosol particles and the concentration of total particulate matter. AGPs represent a potential risk for airborne infections in dentistry. Taken together, these preliminary results suggest that isolation and high-volume suction are effective to reduce ultrafine dental aerosol particles.

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