Aerosol tracer testing in Boeing 767 and 777 aircraft to simulate exposure potential of infectious aerosol such as SARS-CoV-2

The COVID-19 pandemic has reintroduced questions regarding the potential risk of SARS-CoV-2 exposure amongst passengers on an aircraft. Quantifying risk with computational fluid dynamics models or contact tracing methods alone is challenging, as experimental results for inflight biological aerosols is lacking. Using fluorescent aerosol tracers and real time optical sensors, coupled with DNA-tagged tracers for aerosol deposition, we executed ground and inflight testing on Boeing 767 and 777 airframes. Analysis here represents tracer particles released from a simulated infected passenger, in multiple rows and seats, to determine the exposure risk via penetration into breathing zones in that row and numerous rows ahead and behind the index case. We present here conclusions from 118 releases of fluorescent tracer particles, with 40+ Instantaneous Biological Analyzer and Collector sensors placed in passenger breathing zones for real-time measurement of simulated virus particle penetration. Results from both airframes showed a minimum reduction of 99.54% of 1 μm aerosols from the index source to the breathing zone of a typical passenger seated directly next to the source. An average 99.97 to 99.98% reduction was measured for the breathing zones tested in the 767 and 777, respectively. Contamination of surfaces from aerosol sources was minimal, and DNA-tagged 3 μm tracer aerosol collection techniques agreed with fluorescent methodologies.

Determination the Levels of Thief Zones Based on Machine Learning

The technique of interwell tracer testing is considered as one of the most effective method to identify the thief zone (TZ) in reservoirs. However, in heavy oil reservoirs, tracer breakthrough curves are mostly parabolic and unimodal, thus resulting in slight differences between curves. It is inefficient and inaccurate to identify different types of curves with traditional methods applied to characterize the levels of TZs. In this paper, convolutional neural network (CNN) is applied to construct a classification model for the automatic identification of the levers of TZs. According to the TZs criteria specified on the field, the analytical tracer transport model was applied to generate 3000 curves as the sample, which can meet the requirements of model training accuracy. In the meantime, One-hot encoding, Xavier initialization, Adam optimizer, and mini-batch normalization were used to construct the model, and the key parameters are optimized to improve the performance of the model. The results show that the appropriate activation function is ReLU and the optimal dropout rate is 0.5. Moreover, the construction of CNN with discrete data points (DDP-CNN) as input contributed to a further improvement of classification accuracy of tracer curves. The accuracy of DDP-CNN in training set is 0.96, which is 14% and 23% higher than random forest (RF) and k-means, respectively. In practical applications, DDP-CNN proves capable to correctly classify 88 of the 100 curves.

Aerosol tracer testing in Boeing 767 and 777 aircraft to simulate exposure potential of infectious aerosol such as SARS-CoV-2

The COVID-19 pandemic has reintroduced questions regarding the potential risk of SARS-CoV-2 exposure amongst passengers on an aircraft. Quantifying risk with computational fluid dynamics models or contact tracing methods alone is challenging, as experimental results for inflight biological aerosols is lacking. Using fluorescent aerosol tracers and real time optical sensors, coupled with DNA-tagged tracers for aerosol deposition, we executed ground and inflight testing on Boeing 767 and 777 airframes.Analysis here represents tracer particles released from a simulated infected passenger, in multiple rows and seats, to determine the exposure risk via penetration into breathing zones in that row and numerous rows ahead and behind the index case. We completed over 65 releases of 180,000,000 fluorescent particles from the source, with 40+ Instantaneous Biological Analyzer and Collector sensors placed in passenger breathing zones for real-time measurement of simulated virus particle penetration.Results from both airframes showed a minimum reduction of 99.54% of 1 µm aerosols from the index source to the breathing zone of a typical passenger seated directly next to the source. An average 99.97 to 99.98% reduction was measured for the breathing zones tested in the 767 and 777, respectively. Contamination of surfaces from aerosol sources was minimal, and DNA-tagged 3 µm tracer aerosol collection techniques agreed with fluorescent methodologies.

MFIT 1.0.0: Multi-Flow Inversion of Tracer breakthrough curves in fractured and karst aquifers

More than half of the Earth's population depends largely or entirely on fractured or karst aquifers for their drinking water supply. Both the characterization and modeling of these groundwater reservoirs are therefore of worldwide concern. Artificial tracer testing is a widely used method for the characterization of solute (including contaminant) transport in groundwater. Tracer experiments consist of a two-step procedure: (1) introducing a conservative tracer-labeled solution into an aquifer, usually through a sinkhole or a well, and (2) measuring the concentration breakthrough curve (BTC) response(s) at one or several downstream monitoring locations, usually spring(s) or pumping well(s). However, the modeling and interpretation of tracer test responses can be a challenging task in some cases, notably when the BTCs exhibit multiple local peaks and/or extensive backward tailing. MFIT (Multi-Flow Inversion of Tracer breakthrough curves) is a new open-source Windows-based computer package for the analytical modeling of tracer BTCs. This software integrates four transport models that are all capable of simulating single- or multiple-peak and/or heavy-tailed BTCs. The four transport models are encapsulated in a general multiflow modeling framework, which assumes that the spatial heterogeneity of an aquifer can be approximated by a combination of independent one-dimensional channels. Two of the MFIT transport models are believed to be new, as they combine the multiflow approach and the double-porosity concept, which is applied at the scale of the individual channels. Another salient feature of MFIT is its compatibility and interface with the advanced optimization tools of the PEST suite of programs. Hence, MFIT is the first BTC fitting tool that allows for regularized inversion and nonlinear analysis of the postcalibration uncertainty of model parameters.

Water and wastewater CFD and validation: are we losing the balance?

A literature screening on computational fluid dynamics (CFD) modelling in water treatment applications showed a vast range of validation ranging from no validation at all, over residence time distribution (RTD) and tracer testing, to velocity field, species concentration and, finally, turbulence properties measurements. The validation level also differs depending on process scale (laboratory, pilot, full) and type of system (rheology, single phase vs. multiphase). Given the fact that CFD is in more widespread use, a discussion on the extent and need of validation needs to be initiated. This paper serves as a discussion starter on the topic.

A novel approach towards the reliable characterization of complex sedimentary aquifers

<p>The reliable characterization of heterogeneous sedimentary aquifers, especially the identification of preferential flow paths and their connectivity remains a challenge in applied hydrogeology research and practice. However, aforementioned information is crucial for predicting subsurface flow and contaminant transport in complex deposits. Well established characterization methods such as outcrop analogue studies, hydraulic tomography, tracer testing, and direct push profiling suffer from uncertainty due to non-uniqueness of underlying inversions or insufficient temporal and/or spatial data resolution. Furthermore, the relation and effects of observed heterogeneity in hydraulic conductivity on transport is not always straight forward.</p><p>A promising novel approach to overcome the limitations of conventional hydraulic site characterization techniques is the joint application of tracer testing and direct push logging. We present a proof-of-concept field study, where conventional salt tracer testing was combined with vertical high resolution direct push electrical conductivity profiling. The method successfully captured tracer distribution in heterogeneous sedimentary deposits in-situ and visualized measured tracer distribution over time. Additional measurements, such as breakthrough-curves and surface geophysics can be easily integrated to set up ex-post simulations to further increase site-specific understanding of groundwater flow and transport processes.</p>

Solute Reactive Tracers for Hydrogeological Applications: A Short Review and Future Prospects

Tracer testing is a mature technology used for characterizing aquatic flow systems. To gain more insights from tracer tests a combination of conservative (non-reactive) tracers together with at least one reactive tracer is commonly applied. The reactive tracers can provide unique information about physical, chemical, and/or biological properties of aquatic systems. Although, previous review papers provide a wide coverage on conservative tracer compounds there is no systematic review on reactive tracers yet, despite their extensive development during the past decades. This review paper summarizes the recent development in compounds and compound classes that are exploitable and/or have been used as reactive tracers, including their systematization based on the underlying process types to be investigated. Reactive tracers can generally be categorized into three groups: (1) partitioning tracers, (2) kinetic tracers, and (3) reactive tracers for partitioning. The work also highlights the potential for future research directions. The recent advances from the development of new tailor-made tracers might overcome existing limitations.

MFIT 1.0.0: Multiflow inversion of tracer breakthrough curves in fractured and karst aquifers

More than half of the Earth’s population depends largely or entirely on fractured or karst aquifers for their drinking water supply. Both the characterization and modeling of these groundwater reservoirs are therefore of worldwide concern. Artificial tracer testing is a widely used method for the characterization of solute (including contaminant) transport in groundwater. Tracer experiments consist of a two-step procedure: 1) introducing a conservative tracer-labeled solution into an aquifer, usually through a sinkhole or a well, and 2) measuring the concentration breakthrough curve (BTC) response(s) at one or several downstream monitoring locations, usually spring(s) or pumping well(s). However, the modeling and interpretation of tracer test responses can be a challenging task in some cases, notably when the BTCs exhibit multiple local peaks and/or extensive backward tailing. MFIT is a new open-source, Windows-based computer package for the analytical modeling of tracer BTCs. This software integrates four transport models that are all capable of simulating single- or multiple-peak and/or heavy-tailed BTCs. The four transport models are encapsulated in a general multiflow modeling framework, which assumes that the spatial heterogeneity of an aquifer can be approximated by a combination of independent one-dimensional channels. Two of the MFIT transport models are believed to be new, as they combine the multiflow approach and the double-porosity concept, which is applied at the scale of the individual channels. Another salient feature of MFIT is its compatibility and interface with the advanced optimization tools of the PEST suite of programs. Hence, MFIT is the first BTC fitting tool that allows regularized inversion and nonlinear analysis of the postcalibration uncertainty of model parameters.