We investigate the influence of natural head movement on the infection risk posed by airborne pathogens using a CFD-based forward risk prediction model. Quasi-Monte-Carlo simulations are used to obtain the resulting infection risk distributions by representing head movement via probability distributions of parameters describing the position and orientation of each passenger's breathing zone. A significant impact of fore/aft and lateral head position on infection risk was found and should be accounted for to increase robustness when predictions of local, seat-specific infection risks are used to guide design and policy decisions. Unlike the sampling-based Monte Carlo approach, estimates of the statistical moments of the risk distributions and sensitivities, calculated using first-order second-moment and higher-order methods, were found to inadequately capture the dependencies between head movement components and infection risk.

The SARS-CoV-2 pandemic highlighted the need to understand aerosol transport and associated disease transmission, and motivated many numerical flow studies using different numerical approaches to predict Lagrangian particle transport for infection risk modelling, with varying degrees of accuracy and computational cost. To evaluate the trade-off between these different flow simulation approaches, we compare particle concentration predictions based on solutions of the steady and unsteady Reynolds-averaged Navier-Stokes (RANS) equations with experimental data. A ventilated generic train entry segment is chosen because it is easy to set up for experiments and numerical flow simulations. Two heated dummies are placed in this ventilated space, one of which continuously exhales aerosol. The RANS approach predicts significant particle accumulations that are not observed in either the experiments or the URANS simulations. However, the averaged absolute deviation from the experimental data is reduced by a factor of 2.4 when URANS simulations are performed, albeit at an eightfold increase in computational cost.

We report on an experimental study regarding the performance of state-of-the-art ventilation systems with different inlet positions with respect to the aerosol spread. For that, the spatial distribution of aerosol exposure was determined for six different source locations in a generic passenger compartment. This allowed us to evaluate the different concepts in terms of parameters such as contaminant removal efficiency, the number of seats above a certain threshold or the mean particle concentration in the breathing zone of the passengers. The results revealed strong differences in the local particle concentrations depending on the source position. Further, it was found that two ceiling-based concepts, microjet ceiling and ceiling mounted slot diffusers aimed at the passengers, have significant advantages over the other concepts, especially when it comes to the number of seats with aerosol exposures above certain thresholds. Yet, which concept is optimal still depends on the chosen threshold. The contaminant removal efficiency fluctuates only weakly around 0.5 for the different concepts, revealing mixing-ventilation principles for all concepts.

Understanding the (particle) transport processes through the planar turbulent air curtain jet – a ventilation concept designed to reduce the spread of airborne particles and thus possible airborne infections – is important prior to its implementation in a future passenger cabin. In the present study, two-dimensional Particle Image Velocimetry is used to investigate the deflection of an exhalation jet by an air curtain as well as the deflection of the air curtain itself as an indicator of a possible breakthrough of the exhalation jet. The strength of the two opposing jets is varied by changing the air curtain momentum flux to achieve four different momentum flux ratios γ between 0.17 ≤γ≤ 6.88. Strong deflections of the exhalation jet were observed for γ = 3.47 and γ = 6.88, while less deflection and a (temporal) breakthrough of the air curtain were obtained for γ = 0.65 and γ = 0.17.

The corona pandemic has proved beyond doubt the impact infectious agents can have on our daily life. Infection prevention is a central pillar for a better preparedness against future pandemics. Travel, more precisely passenger cabins, such as aeroplanes, trains and buses, that are frequented by large and varying groups of people, present a substantial challenge in this regard. The aim of the graduate school of the DLR, that comprised of 6 contributing institutes, was to develop and contribute to interdisciplinary solutions and concepts in this field. In this overview, we give a short summary of the conducted studies and how they may support an effective infection prevention.

Thermal management in battery-electric Level-4 cabins must balance local thermal comfort against HVAC elec trical power and the resulting range penalty. This study develops and evaluates a data-driven framework for comfort-oriented and energy-aware steady-state setpoint selection for a hybrid convective-radiant HVAC con cept. A vehicle-like mock-up in a climate chamber is instrumented with a 16-zone segmented thermal manikin to measure stationary local equivalent temperatures teq according to DIN EN ISO 14,505-2 under three ambient scenarios (-10 degrees C, +16 degrees C, +28 degrees C), two seating postures, and three air-distribution concepts. Based on the re sulting steady-state dataset, forward multi-output surrogate models are trained to predict the 16 segmental teq values from boundary conditions and actuator settings, using a linear regression baseline and ensemble methods (Random Forest, XGBoost). On the pooled dataset with intra-scenario 5-fold cross-validation, XGBoost achieves a mean R2 = 0.978 and a mean MAE = 0.856 K across the 16 targets, outperforming the linear baseline (R2 = 0.872, MAE = 2.248 K). Scenario-level extrapolation remains limited in a leave-one-scenario-out stress test, indicating that explicit climate coverage is required for deployment beyond the represented operating space. The trained surrogate is embedded in a constrained search over the admissible actuation space to identify comfort-feasible setpoints within the Nilsson neutrality bands with minimum electrical HVAC power, computed from a convec tive energy balance with scenario-dependent COP and measured radiant-panel power. Validation experiments confirm near-neutral comfort in winter and summer. At +16 degrees C, radiant support yields only marginal comfort changes but increases electrical HVAC power from about 0.5 kW in convection-only operation to about 2.1 kW in hybrid operation, causing an estimated WLTP range penalty of roughly 15-17% in the considered reference cycle. The contribution of the present study is therefore limited to steady-state comfort-constrained setpoint selection and actuator prioritization within the measured operating space and does not extend to broadly generalizable real-time HVAC control.

We predict the SARS-CoV-2 infection risk in aircraft cabins by simulating the aerosol transport with computational fluid dynamics and taking medical parameters into account. A recently presented new measurement technique allows us to measure the rapid virus inactivation after exhalation with high temporal resolution. In addition, much higher airborne SARS-CoV-2 inactivation rates than in previous studies were obtained. This raises the question of how the new knowledge of SARS-CoV-2 stability affects the prediction of infection risk. To answer this question, we evaluated 70 Lagrangian particle simulations with an index person sitting in all possible seats in an aircraft cabin. We then estimated the infection risk for the other passengers based on the old and new SARS-CoV-2 stability data. For typical transmission events, we found that the predicted infection risk is reduced by about 50 _2 (500 ppm). However, elevated ambient CO _2 concentrations of 3000 ppm protect the virus from inactivation and increase infection risk by about 50 _2 . In addition, a high relative humidity of the ambient air, e.g., from exhaled breath, delays the rapid inactivation by a few seconds, increasing the risk of infection for immediate neighbors.

PurposeThe purpose of this study is to perform direct numerical simulation (DNS) and unsteady Reynolds-averaged Navier-Stokes simulation (URANS) of cough-induced flow and particles in a large-scale circulation (LSC) to assess the performance and accuracy of the latter.Design/methodology/approachBoth simulations were performed in a 12.5 m(3) room for 30 s, with a background flow defined by a lid-driven LSC. In the URANS, the particles were modelled using a stochastic dispersion model to account for turbulent fluctuations. Initial flow fields were obtained from LSC simulations.FindingsThe URANS predicted a larger cough jet entrainment, resulting in a shorter but wider jet flow, leading to underprediction of the horizontal displacements, especially of the small particles, during the jet and early puff phases. The cough puff in the URANS was overly influenced by the downward background flow, resulting in faster particle descent. The wider jet spread led to an overprediction of particle dispersion during the jet and early puff phases, but subsequently the shorter puff spread led to an underprediction of particle dispersion during the mid and late puff phases.Originality/valueUnlike similar studies, this research includes DNS of a cough-induced flow and particles in a larger domain over a longer period of time within a background flow characterised by an LSC, highlighting the need for a better representation of the flow fields and cough-induced particle dynamics resolved in URANS.

Installing local, individually controllable ventilation - a specific version of a personalized environmental control system - offers great potential in terms of improving the individual thermal comfort and energy savings of the overall train air-conditioning system. In our experimental investigation, we set an increased mean temperature in the train compartment and measured the local equivalent temperature (Teq) and local mean vote (LMV) per body-segment on a selected seat. This seat was equipped with an additional six-air-nozzle device attached to the backrest of the front seat. The objective comfort revealed the achievable ranges for the different settings as well as a strong local effect of the single air jets. The different configurations were afterwards studied in terms of subjective comfort evaluations based on questionnaires and the individual settings of 40 subjects. The results confirmed the positive cooling effect of the air jets as thermal comfort was significantly improved when the subjects used the six-air-nozzle. Air draughts at the subjects' upper legs and the temperature at their chest and face were most relevant for comfort sensations. Furthermore, the findings highlighted the highly subjective demand on the thermal environment as no two subjects chose the same nozzle configuration.

Particle dispersion models (PDMs) are essential to capture the influence of unresolved turbulent eddies on particle transport in computational fluid dynamics (CFD) simulations. However, the validation of these models remains challenging, especially when relying on experimental data or CFD simulations that are based on turbulence models. In this work, we use time-averaged data obtained in a direct numerical simulation (DNS) instead of relying on turbulence models to model particle dispersion. In addition, a new particle dispersion model is presented, referred to as the limited particle–eddy interaction time (LPI) model. For a detailed and systematic evaluation of the new LPI model, we compare its performance with that of other commonly used models, such as the mean particle–eddy interaction time (MPI) model implemented in OpenFOAM® and the randomized particle–eddy interaction time (RPI) model from the literature. The MPI model shows good agreement with the DNS for the largest particles tested (Stokes number, St = 0.2) but exhibits erratic and unphysical trajectories for smaller particles (St ≤ 0.05). To mitigate this erratic behavior, we have adjusted the eddy interaction time in the new LPI model.

We report on the experimental investigation of aerosol particle spreading in an operation room. Different configurations regarding the source position or representative movements of the staff in the room are analyzed. The data acquisition is performed using a sensor grid of more than 50 particulate matter sensors at a measurement frequency of approximately 1 Hz operated with the DLR’s mobile measurement system (MMS): This allows for a reasonable resolution in space and time. The measurement campaign was performed within the framework of the c3vis project in the teaching operational room of the OTH Amberg-Weiden. First results showed that the aerosol particles exhaled by the standing source are down-washed by the airflow and reach, strongly diluted, one of the sensor positions above the operation table next to the standing source. Local concentrations as low as ≈1.5% of the exhalation concentration are found. All other positions above the operation table show a particle concentration close to zero. With a certain time delay the cloud of exhaled aerosol particles reaches single other sensor locations on its way towards the exhaust openings, while being further diluted (≈0.03% of the exhalation concentration). During the dynamic case, we found neglectable effects when the doors were opened or closed, a weak effect caused by the movement of the staff through the room and a strong effect on the aerosol concentration above the operation table when the surgeon was operating on the patient.

An important route of transmission for potentially harmful bacteria is the spread of bioaerosols in indoor environments. In a chamber specially developed for particle dispersion tests, we created a defined bioaerosol to study the performance of two methods commonly used in biology and engineering studies: airborne bacterial detection and particulate matter (PM) analysis. A total of five ventilation cases were investigated in which an air curtain, operated at Reynolds numbers Re < 11, 000, shielded the particles in one half of the test chamber from the other half. In two of these five cases, a HEPA filter was also installed to specifically reduce the particle concentration in the test chamber. In addition to active and passive air sampling measurements of bacteria, we took PM measurements in front of, beneath, and behind the air curtain under constant air temperature and relative humidity conditions. The bioaerosol contained nine bacterial species, evenly distributed in artificial saliva. Two species in the bioaerosol, Staphylococcus capitis DSM 111179 and Burkholderia lata DSM 23089 T , were selected for evaluation due to their antibiotic resistance, which makes them distinguishable from other species. The results show a similar trend in the concentrations of the detected particles and bacteria. The survival rates of the evaluated bacterial species differed; S. capitis exhibited a greater agreement with the PM measurements than B. lata did, which emphasizes the importance of using a various model organism in such experimental setups. We evaluated the effectiveness of the air curtain in reducing particle and bacterial spread, with values reaching up to 66% for both measurement approaches. This study highlights the key differences between the two detection methods and confirms the reproducibility and suitability of the standardized bioaerosol for future research applications. Both methods have demonstrated their potential for use in more realistic scenarios.

The spread of exhaled particles in a passenger aircraft cabin is an important parameter for evaluating infection risk modelling or the spread of other contaminants and odours. It is well known that the ventilation concept has a significant influence on this process and therefore also on the direct transmission of the contaminants. The present experimental study, conducted in the ground-based Do728 research aircraft cabin of the DLR, compares the aerosol spread under state-of-the-art mixing ventilation (MV) conditions with cabin displacement ventilation (CDV) and a combined CDV-MV ventilation (hybrid ventilation - HV). Various source positions in longitudinal direction and in the cross-section as well as different airflow distributions were investigated. Furthermore, the dynamic influence of people walking in the aisle was analyzed. This study shows that the spread of particles in a short-range aircraft is strongly affected by the installed ventilation system. Compared to the state-of-the-art MV, the mean concentration can be reduced by up to 80% under CDV conditions. Furthermore, the number of seats where certain thresholds are exceeded can be significantly reduced. By combining the systems to HV, the mean concentration can be reduced by 10% compared to MV. However, this results in a 130% increase in the maximum value. The spread of particles in case of MV and HV is strongly influenced by the source position, in both the longitudinal and in cross-sectional directions. Movement in the aisle has only a minor influence on the mean particle load and the number of seats above a certain threshold under MV conditions. However, the direction of spreading within the cabin is changed by the movement, decreasing the particle load in front and increasing it in the rear of the cabin. A considerably stronger effect was measured under CDV conditions, where the induced air flow by the manikin movement leads to increased particle concentrations in large area of the cabin. Here, the otherwise well-defined, upward-directed buoyancy driven flow which transports the exhaled particles directly to the exhaust, is now disturbed by the movement and thus more spreading of particles occurs in the breathing zone of the passengers.

We report on the experimental investigation of the spreading of aerosol particles in a train compartment. For this purpose, a moving thermal manikin is used representing a heat-releasing, standing passenger, which can be moved through the aisle with a peak walking velocity of 1 m/s on a traverse system. The results highlight the impact of the movement by showing high peaks of increased local concentrations on different seats, which are up to nine times higher compared to the average concentration on this seat. Meanwhile the mean concentration in the compartment remains almost constant, whereas on some other seats the average concentration is locally slightly decreased. In general, the movement results in a decrease of the concentration at the highest contaminated seats near the source while increasing the concentration farther away. This effect can be explained by the additional mixing of the air in the cabin. The measurements were performed for different source locations, showing the different spreading behavior originating from aisle and window seats.

This computational fluid dynamics (CFD) study examines the comfort parameters of an innovative air vent concept for car cabin interiors using a reduced order model (ROM) and proper orthogonal decomposition (POD). The focus is on the analysis of the influence of geometric and fluid mechanical parameters on the resulting jet, in particular on the deflection angle of the airflow and the total pressure difference along the outlet geometry. Different parameters of the investigated system, such as the surface orientation, the outlet height, the separator distance, and the separator height, lead to different effects on the airflow structure. The results show that changes in the air vent surface orientation are always accompanied by an increase in the deflection angle and the total pressure difference. In contrast, the variation of the outlet height ratio positively influences the deflection angle and the total pressure difference in terms of the requirements for air vent geometries. The study also examines the interaction of the geometric parameters and reveals complex correlations that influence the resulting air jet. A comprehensive understanding of these influences makes it possible to adapt the design and implementation of new and innovative air vent concepts to meet specific requirements. By balancing design considerations and technical requirements, optimized solutions are characterized by a high deflection angle and a reduced overall pressure difference for improved system performance and efficiency. Therefore, this evaluation provides a final framework for the design and implementation of an innovative air vent concept based on the volume flow vectoring that is tailored to specific application requirements.

Installing local, demand-controlled ventilation offers great potential in terms of improving the individual thermal comfort and the energy savings of the overall train air-conditioning system. In the experimental investigation, we set both reduced and increased mean temperatures in the compartment and measured the local equivalent temperature per body-segment on a selected seat which is equipped with an additional six-air-nozzle device attached to the backrest of the front seat. The single nozzles are oriented towards, e.g., the legs, the upper body and the head. First results revealed that at decreased mean temperatures in the compartment, the warm air jets are not capable to reach all body parts due to entrainment and mixing with the ambient air. Hence, in the current setup, individual heating seems more promising by, e.g., by infrared heating elements. In contrast, at increased mean temperatures the air vents provide a possibility to locally decrease the equivalent temperature.

In our recent studies, we have applied a measurement system for aerosol spreading in the generic train laboratory Göttingen (GZG) for different source locations and various ventilation concepts. The latter comprised, among others, different exhaust positions either in the lateral ceiling or in the legroom. The measurements were carried out until a quasi-stationary local aerosol particle concentration was reached. The evaluation was performed in terms of the mean aerosol concentration load in the compartment and with regard to the number of seats revealing aerosol concentrations above certain thresholds. First results highlight the influence of the airflow concept on the aerosol spreading within the passenger compartment. In this context, the exhaust position caused only a minor change in the local aerosol particle concentrations, whereas larger differences were found for alternative, hybrid air-supply positions.

Current models to determine the risk of airborne disease infection are typically based on a backward quantification of observed infections, leading to uncertainties, e.g., due to the lack of knowledge whether the index person was a superspreader. In contrast, the present work presents a forward infection risk model that calculates the inhaled dose of infectious virus based on the virus emission rate of an emitter and a prediction of Lagrangian particle trajectories using CFD, taking both the residence time of individual particles and the biodegradation rate into account. The estimation of the dose-response is then based on data from human challenge studies. Considering the available data for SARS-CoV-2 from the literature, it is shown that the model can be used to estimate the risk of infection with SARS-CoV-2 in the cabin of a Do728 single-aisle aircraft. However, the virus emission rate during normal breathing varies between different studies and also by about two orders of magnitude within one and the same study. A sensitivity analysis shows that the uncertainty in the input parameters leads to uncertainty in the prediction of the infection risk, which is between 0 and 12 infections among 70 passengers. This highlights the importance and challenges in terms of superspreaders for risk prediction, which are difficult to capture using standard backward calculations. Further, biological inactivation was found to have no significant impact on the risk of infection for SARS-CoV-2 in the considered aircraft cabin.

This study investigates the dispersion of a cough-induced particle cloud in the presence of a large-scale circulation (LSC) predicted in an unsteady Reynolds-averaged Navier–Stokes simulation (URANS), and compares the results with those of a direct numerical simulation (DNS). Both simulations share identical initial conditions and domain sizes, but they differ in spatial and temporal resolution and their approach to turbulence. After the jet phase, it is found that the particles in the URANS have not advanced as far in the horizontal direction as those in the DNS. The shape of the URANS particle cloud is symmetric in the horizontal inlet midplane, whereas in the DNS the particles appear to be irregularly distributed. In the well-developed puff phase, the particles of URANS have moved less far in horizontal direction than those of DNS. Although the lateral dispersion of the URANS particles is similar to that of the DNS particles, the top view shows a cone-shaped pattern for the URANS particles, whereas those of the DNS have a uniform distribution. The major difference between the URANS and DNS results in the late puff phase is the thicker and stronger boundary layer near the upper wall of the URANS, which impedes the vertical ascent of the particles, resulting in a stronger overall circulation intensity throughout the domain. In the jet phase, both URANS and DNS predictions exhibit good agreement in the vertical particle probability density distribution (PDF). However, this agreement is not observed in the well-developed and late puff phases.

Aviation is among the social sectors most impacted by the COVID-19 pandemic, and at the same time has contributed to the rapid global spread of the SARS-CoV-2 virus. SARS-CoV-2 is one of the coronaviruses that have led to outbreaks such as MERS-CoV in the past. This group of pathogens, as well as others that may be unknown at this time, will continue to challenge our society in the future. In order to be able to react better, a research training group was established at DLR in cooperation with 6 institutes, which will develop interdisciplinary approaches to researching and combating current and future pandemics. Engineers, physicists, software developers, biologists and physicians are working closely together on new concepts and the development of interdisciplinary knowledge in order to better control and contain future pandemics and to be able to react in a more targeted manner. One focus is the reduction of germ contamination in airplanes but also in other means of public transport such as buses and trains. In this review, we provide an overview of the baseline situation and possible approaches to address future pandemic challenges.