Background This rapid evidence review identifies and integrates evidence from epidemiology, microbiology and fluid dynamics on the transmission of SARS-CoV-2 in indoor environments. Methods Searches were conducted in May 2020 in PubMed, medRxiv, arXiv, Scopus, WHO COVID-19 database, Compendex & Inspec. We included studies reporting data on any indoor setting except schools, any indoor activities and any potential means of transmission. Articles were screened by a single reviewer, with rejections assessed by a second reviewer. We used Joanna Briggs Institute and Critical Appraisal Skills Programme tools for evaluating epidemiological studies and developed bespoke tools for the evaluation of study types not covered by these instruments. Data extraction and quality assessment were conducted by a single reviewer. We conducted a meta-analysis of secondary attack rates in household transmission. Otherwise, data were synthesised narratively. Results We identified 1573 unique articles. After screening and quality assessment, fifty-eight articles were retained for analysis. Experimental evidence from fluid mechanics and microbiological studies demonstrates that aerosolised transmission is theoretically possible; however, we found no conclusive epidemiological evidence of this occurring. The evidence suggests that ventilation systems have the potential to decrease virus transmission near the source through dilution but to increase transmission further away from the source through dispersal. We found no evidence for faecal-oral transmission. Laboratory studies suggest that the virus survives for longer on smooth surfaces and at lower temperatures. Environmental sampling studies have recovered small amounts of viral RNA from a wide range of frequently touched objects and surfaces; however, epidemiological studies are inconclusive on the extent of fomite transmission. We found many examples of transmission in settings characterised by close and prolonged indoor contact. We estimate a pooled secondary attack rate within households of 11% (95% confidence interval (CI) = 9, 13). There were insufficient data to evaluate the transmission risks associated with specific activities. Workplace challenges related to poverty warrant further investigation as potential risk factors for workplace transmission. Fluid mechanics evidence on the physical properties of droplets generated by coughing, speaking and breathing reinforce the importance of maintaining 2 m social distance to reduce droplet transmission. Conclusions This review provides a snap-shot of evidence on the transmission of SARS-CoV-2 in indoor environments from the early months of the pandemic. The overall quality of the evidence was low. As the quality and quantity of available evidence grows, it will be possible to reach firmer conclusions on the risk factors for and mechanisms of indoor transmission.

The aim of this article is to present the application of empirical mode decomposition (EMD) for centrifugal blower flow instabilities detection. The analysis of pressure signal features extracted by EMD technique provides indicators of flow phenomena, which could be used for creating an efficient data-based controller. Quasi-dynamic pressure signals from industrial-size blower are used as an input data for EMD algorithms. An energy-based approach to intrinsic mode functions (IMF) is applied, showing the possibility of condition monitoring and instabilities detection, distinctly displaying surge conditions and inlet recirculation. Different intrinsic mode functions (IMFs) are used to detect different instabilities. EMD also presents some potential in detection of optimal operation conditions for impeller, providing additional benefit for a control system. The possibilities of EMD analysis applied to centrifugal blowers and compressors will be further investigated.

The emergence of large, propeller-based aircraft has revived interest in propeller design and optimization with the use of numerical methods. The flow complexity and computational time necessary to solve complicated flow patterns trailing behind rotating blades, created a need for faster than fully resolved 3D CFD, yet comparably accurate methods for validating multiple design points in shorter time. Improved Virtual Blade Method (VBM) for 2-bladed propeller, including method implementation, analysis and validation against 3D numerical and experimental data is presented. The study introduces adjustments to the original method, accounting for differences between VBM and fully resolved numerical models. These modifications prove to increase the model accuracy for the propeller under consideration and could potentially be applied for different blade configurations as well. The modified Virtual Blade Method allows one to compute the propeller performance with comparable accuracy to 3D CFD computation using only 10% of time needed for one computational point.

Aerodynamic instabilities in centrifugal compressors are dangerous phenomena affecting machine efficiency and in severe cases leading to failure of the compressing system. Quick and robust instability detection during compressor operation is a challenge of utmost importance from an economical and safety point of view. Rapid indication of instabilities can be obtained using a pressure signal from the compressor. Detection of aerodynamic instabilities using pressure signal results in specific challenges, as the signal is often highly contaminated with noise, which can influence the performance of detection methods. The aim of this study is to investigate and compare the performance of two non-linear signal processing methods—Empirical Mode Decomposition (EMD) and Singular Spectrum Analysis (SSA)—for aerodynamic instability detection. Two instabilities of different character, local—inlet recirculation and global—surge, are considered. The comparison focuses on the robustness, sensitivity and pace of detection—crucial parameters for a successful detection method. It is shown that both EMD and SSA perform similarly for the analysed machine, despite different underlying principles of the methods. Both EMD and SSA have great potential for instabilities detection, but tuning of their parameters is important for robust detection.

Unstable flow structures cause inevitable energy losses in all power energy systems, including turbomachines. In this study, a set of analyses was conducted with the use of spectral maps on the pressure signals obtained from an industrial centrifugal compressor. The spectral maps provide one a detailed visualization of the flow conditions present in the machine along the performance curve and to distinguish the flow phenomena present prior to the surge. The method accuracy is especially useful in detecting the inlet recirculation. The study was conducted at four impeller rotational speeds with varying loads imposed by a valve at the outlet. At each speed, the machine experienced different stages of unstable flow conditions prior to the surge. Five main frequency peaks that appeared in all cases were identified and discussed. The surge was observed at all impeller speeds. At lower ones, however, it appeared at higher valve closures. At higher speeds, the surge was much more intense. The study has also shown that the inlet recirculation appears also for the closed-type industrial impeller. The phenomenon was present in all conditions. The higher impeller speed, the faster onset of the inlet recirculation was. This structure has a strong potential for an early instability warning because it appears in various types of impellers, has a very particular spectral structure and its positioning is very predictable. This study gives another example of the inlet recirculation universality and potential for efficient anti-surge protection.

An efficient approach to the geometry optimization problem of a non-axisymmetric flow channel is discussed. The method combines geometrical transformation with a computational fluid dynamics solver, a multi-objective genetic algorithm, and a response surface. This approach, through geometrical modifications and simplifications allows transforming a non-axisymmetric problem into the axisymmetric one in some specific devices i.e., a scroll distributor or a volute. It results in a significant decrease in the problem size, as only the flow in a quasi-2D section of the channel is solved. A significantly broader design space is covered in a much shorter time than in the standard method, and the optimization of large flow problems is feasible with desktop-class computers. One computational point is obtained approximately eight times faster than in full geometry computations. The method was applied to a scroll distributor. For the case under analysis, it was possible to increase flow uniformity, eradicate separation zones, and increase the overall efficiency, which was followed by energy savings of 16% for the scroll. The results indicate that this method can be successfully applied for the optimization of similar problems.

Aerodynamic instabilities in centrifugal compressors are dangerous phenomena affecting machines efficiency and in severe cases leading to failures of the compressing system due to high amplitude vibrations. Efficient instabilities detection during compressor operation is a challenge of utmost importance from economical and safety point of view. The most sensitive detection is possible with use of a pressure signal from inside of the compressor because specific pressure patterns are the first symptoms of instabilities. Detection of aerodynamic instabilities results in specific challenges, as the pressure signal is often very noisy and contains high amount of randomness. Surge -most severe instability, can develop very quickly. Therefore, the method of detection should be sensitive but also robust and quick. Another common instability, inlet recirculation is less dangerous, but it results in decrease of efficiency, which is to be avoided. Inlet recirculation often happens before surge, thus its presence can be used for surge proximity detection. The aim of this study is to investigate and compare the performance of two non-linear processing methods -Empirical Mode Decomposition (EMD) and Singular Spectrum Analysis (SSA) in the context of aerodynamic instabilities detection -inlet recirculation and surge. The comparison focuses on the robustness, sensitivity and pace of detection -crucial parameters for a successful detection method. It is shown that both methods perform similarly within the analyzed bounds for both instabilities. A slight advantage of SSA may be noticed for surge due to lower dispersion of the indicator value for the same conditions.

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