Ventilation Configurations Research Articles

INFLUENCE OF VENTILATION PLACEMENT ON THE COOLING EFFICIENCY OF LITHIUM-ION BATTERIES UNDER FORCED AIRFLOW CONDITIONS

In line with a rise in demand for lithium-ion batteries (LIBs) around the globe, LIB thermal management optimization is desirable. Moreover, the temperature rise of LIBs while discharging and charging affects their degradation and thermal runaway. The objective of this study is to investigate cooling performance in LIBs due to battery pack ventilation configuration. In this study, twenty 18650 lithium-ion cells (in 10S2P configuration) were simulated in Altair HyperWorks CFD - AcuSolve. The analysis provides a significant finding for the best thermal management approach by Design 2 with the position of an inlet at the top and outlet at the bottom of the battery pack, indirectly promoting uniform temperature distribution across the pack and avoiding local hot spots. These findings contribute significant insights into the effect of battery ventilation configuration for enhancing lithium-ion cooling performance

Aeration Optimization for the Biodrying of Market Waste Using Negative Ventilation: A Lysimeter Study

This study investigates the optimization of aeration rates for the biodrying of market waste using negative-pressure ventilation. Market waste, characterized by a high moisture content (MC) and rapid decomposition, presents challenges in waste management. Over 12 days, three aeration rates (ARs) of 0.2, 0.4, and 0.6 m3/kg/day were examined, and the most effective continuous ventilation configuration was identified in terms of heat generation, moisture reduction, and biodrying efficiency. The results indicate that the most effective AR for heat retention and moisture removal was 0.2 m3/kg/day, achieving a 6.63% MC reduction and a 9.12% low heating value (LHV) increase. Gas analysis showed that, while AR 0.2 supported high microbial activity during the initial 7 days, AR 0.6 sustained higher overall CO2 production due to its greater aeration rate. The findings also suggest that the biodrying of market waste with a high initial MC can achieve significant weight loss and leachate generation when paired with a high aeration rate of 0.6 m3/kg/day, with a 69.8% weight loss and increased waste compaction being recorded. The study suggests that variable ARs can optimize biodrying, making market waste more suitable for conversion to refuse-derived fuel or landfill pre-treatment and improving waste-to-energy processes and sustainability.

Optimizing greenhouse design for enhanced microalgae production: A CFD Analysis of microclimate and water thermal dynamics in raceway ponds

The increasing demand for sustainable biomass has made microalgae farming into the spotlight as a viable source of biofuels, nutraceuticals, and other valuable products. Raceway ponds are one of the most common systems in algaculture due to their simplicity and cost-effectiveness. However, their efficiency is significantly influenced by surrounding microclimate conditions. In this study, we present a Computational Fluid Dynamics (CFD) analysis aimed at optimizing greenhouse design to enhance microalgae production in a raceway pond housed within a controlled greenhouse environment. The research focuses on evaluating the influence of greenhouse microclimate parameters on water's thermal dynamics in the pond. Simulations were conducted to assess how different greenhouse geometries and ventilation configurations affect the heat exchange between the water surface and air within the greenhouse, as well as the internal flow dynamics, both of which are critical for optimal algae growth.The results provide insights into the optimal greenhouse design parameters that maintain the optimal water temperatures in the pond while minimizing thermal fluctuations to enhance microalgae productivity. Specifically, a significant 5 °C temperature difference was observed between the pond's surface and bottom, mainly due to convective heat transfer. Key design factors, such as greenhouse height and ventilation rates, were shown to have a substantial impact on water temperature.The insights gained are essential for optimizing greenhouse design and ventilation strategies to maximize algae growth and production efficiency. This preliminary modeling lays the foundation for future sensitivity analyses aimed at refining the system, ultimately improving algae cultivation in controlled environment agricultural systems.

The effects of ventilation layout on cough droplet dynamics relating to seasonal influenza

The primary aim of this paper is to investigate airborne virus transmission in a typical meeting room relating to the heating, ventilation, and air conditioning (A.C.) systems. While the installation of 4-way cassette A.C. systems in offices and meeting rooms has become increasingly common, their efficiency in mitigating short-range airborne virus spread remains poorly understood. Addressing this gap is critical in the post-pandemic era, where understanding the limitations of various ventilation systems is paramount for public health. We systematically compare the performance of the 4-way cassette A.C., various configurations of mixing and displacement ventilation systems, and natural ventilation in controlling the spread of respiratory viruses. Our research uniquely integrates evaporation models to accurately simulate cough clouds' multiphase behavior under both quiescent and thermally influenced conditions. The study benchmarks these systems against two widely recognized ventilation standards (i.e., 5 air changes per hour and 10 l/s per person), offering evidence-based insights applicable across diverse indoor settings. Our findings reveal significant thermal effects in the quiescent case, resulting in 32.3%, 54.3%, and 8.0% changes in the axial, vertical, and lateral spread of the virus-laden droplets, respectively. Notably, the 0.5 m/s 4-way cassette A.C. system demonstrated superior performance, reducing the axial spread by 29.6% compared to other mechanical ventilation configurations. Furthermore, the role of exhaust outlets or doors was found to be critical in shaping the spread pattern in natural ventilation scenarios. This work can offer practical guidance to office workers, engineers, and public health officials on enhancing indoor airborne infection control.

CFD Evaluation of Respiratory Particle Dispersion and Associated Infection Risk in a Coach Bus with Different Ventilation Configurations

The COVID-19 pandemic has underscored the urgency of understanding virus transmission dynamics, particularly in indoor environments characterized by high occupancy and suboptimal ventilation systems. Airborne transmission, recognized by the World Health Organization (WHO), poses a significant risk, influenced by various factors, including contact duration, individual susceptibility, and environmental conditions. Respiratory particles play a pivotal role in viral spread, remaining suspended in the air for varying durations and distances. Experimental studies provide insights into particle dispersion characteristics, especially in indoor environments where ventilation systems may be inadequate. However, experimental challenges necessitate complementary numerical modeling approaches. Zero-dimensional models offer simplified estimations but lack spatial and temporal resolution, whereas Computational Fluid Dynamics, particularly with the Discrete Phase Model, overcomes these limitations by simulating airflow and particle dispersion comprehensively. This paper employs CFD-DPM to simulate airflow and particle dispersion in a coach bus, offering insights into virus transmission dynamics. This study evaluates the COVID-19 risk of infection for vulnerable individuals sharing space with an infected passenger and investigates the efficacy of personal ventilation in reducing infection risk. Indeed, the CFD simulations revealed the crucial role of ventilation systems in reducing COVID-19 transmission risk within coach buses: increasing clean airflow rate and implementing personal ventilation significantly decreased particle concentration. Overall, infection risk was negligible for scenarios involving only breathing but significant for prolonged exposure to a speaking infected individual. The findings contribute to understanding infection risk in public transportation, emphasizing the need for optimal ventilation strategies to ensure passenger safety and mitigate virus transmission.

Mesh Refinement for Dynamics Airflow in Health Care

This studyexplores using computational fluid dynamics(CFD) tooptimize ventilation in healthcare, with a focus on mesh refinement for accurate airflow analysis. The goal is to reduce airborne contaminant spread, which is crucial during COVID-19. Ventilation in healthcare ensures air quality and minimizes pathogen transmission. The research analyzer analyzes mesh element size's impact on airflow accuracy in simulated hospital wards with two coughing patients. The optimal mesh size is determined for reliable predictions. Mesh refinement enhances accuracy in critical zones. The k-epsilon turbulence model is chosen for low error. Experimental validation shows temperature discrepancies, likely due to simulated manikins lacking clothing insulation. Air velocity measurements show minor variations within an acceptable range. Further research on various ventilation configurations and airflow rates in real hospital conditions is crucial. Addressing these limitations optimizer optimizeshealthcare ventilation, enhancing safety and infection control.

Uncertainties in exposure predictions arising from point measurements of carbon dioxide in classroom environments.

Predictions of airborne infection risk can be made based on the fraction of rebreathed air inferred from point measurements of carbon dioxide (CO[Formula: see text]). We investigate the extent to which environmental factors, particularly spatial variations due to the ventilation provision, affect the uncertainty in these predictions. Spatial variations are expected to be especially problematic in naturally ventilated spaces, which include the majority of classrooms in the UK. An idealized classroom, broadly representative of the physics of (buoyancy-driven) displacement ventilation, is examined using computational fluid dynamics, with different ventilation configurations. Passive tracers are used to model both the CO[Formula: see text] generated by all 32 occupants and the breath of a single infectious individual (located in nine different regions). The distribution of infected breath is shown to depend strongly on the distance from the release location but is also affected by the pattern of the ventilating flow, including the presence of stagnating regions. However, far-field exposure predictions based on single point measurements of CO[Formula: see text] within the breathing zone are shown to rarely differ from the actual exposure to infected breath by more than a factor of two-we argue this uncertainty is small compared with other uncertainties inherent in modelling airborne infection risk.

Human exposure to respiratory aerosols: Impact of ventilation rates, mixing ventilation configuration, and breathing patterns

This study investigates airborne transmission dynamics between occupants in office rooms equipped with mixing ventilation (MV). The primary aim was to assess how different ventilation configurations, air change rates (ACH), breathing patterns, and supply air temperatures influence cross-exposure and infection risks. The experimental setup involved two thermal manikins simulating an infected and an exposed occupant within a climate chamber. The investigated parameters included four ACH levels (1.2, 2, 4 and 6.6 h⁻1, representing four EN 16798–1 ventilation categories), two MV configurations (near-ceiling and near-floor inlets), two breathing patterns (nose and mouth breathing), and two supply air temperatures (19 °C and 21 °C). Carbon dioxide (CO₂) was used as a tracer gas to simulate exhaled aerosols, enabling precise measurements of effectiveness (εv), intake fraction (IF), and infection probability (P). The findings indicate that higher ACH do not uniformly improve εv but are linked to reduced cross-exposure risk. The near-floor inlet MV configuration significantly outperformed the near-ceiling configuration in reducing IF and P by 15–41 % under most investigated scenarios. Additionally, mouth breathing increased IF and P compared to nose breathing, especially at higher ACH (2, 4, and 6.6 h⁻1). The results also showed that lower supply temperatures do not always correlate with higher IF and P, as MV configuration and breathing patterns significantly influence outcomes. This research provides insights into optimizing ventilation strategies for safer indoor environments, emphasizing the importance of airflow dynamics, breathing patterns, and supply temperature in ventilation design.

Performance assessment of the curved-type multi-channel PV roof for space-heating and electricity generation in winter

The curved-type PV roof integrated with flexible PV tiles is a novel attempt to implement the building-integrated photovoltaic/thermal technology into diverse genres of architectural design. To explore its performance in the function of electricity generation and space-heating, different ventilation configurations of the air channels are adopted in the design of the multi-air-channels of the system; two working modes (fresh-air-heating - FAH and recirculated-air-heating - RAH) are applied in the system's operation. The case study is based on a residential building linked with the system in Hefei, China. The performance assessment is conducted on a typical sunny winter day and through the winter of the Typical Meteorological Year. The investigation results indicate that RAH mode has the potential to raise the indoor air temperature to a greater extent. However, the electrical power output shows a disadvantage due to the relatively poor PV cooling effect; increasing the connection air channels could enhance the indoor air heating but add the fan power consumption. The prediction throughout winter manifests that the all-in-parallel connection produces 1827.63 kWh (FAH) and 1574.55 kWh (RAH) of total energy, whereas the 6-in-series connection produces 2085.91 kWh (FAH) and 1618.99 kWh (RAH).

Strategic ventilation design for reducing airborne infection transmission in a two-story building: A numerical approach

This study employs Computational Fluid Dynamics (CFD) to assess the impact of various ventilation configurations on respiratory droplet dispersion in a two-story restaurant building, aiming to reduce airborne infection transmission. A total of 24 scenarios, involving three ventilation configurations and eight individuals as potential droplet sources, are studied. The configurations—Case A, Case B, and Case C—are analyzed for their effectiveness in controlling droplet dispersion and improving air exchange effectiveness (AEE). Case B, with an outlet near occupants and an inlet above the zone separation, proved most effective in minimizing the droplet transmission between floors, reducing suspended airborne droplets on each floor, and preventing surface contamination, thereby enhancing indoor air quality. Despite the positioning inlet and outlet vents near crowded areas, Case A falls short in effectively removing droplets due to the intricate airflow patterns caused by air diffusers. Case C showed larger AEE but was less effective in droplet dispersion control, indicating a crucial balance between optimizing air circulation and limiting pathogen dispersion is needed. The findings underscore the importance of strategic ventilation design in mitigating airborne infection transmission in multi-level buildings. An optimal configuration, as demonstrated by Case B, combines efficient air distribution with strategic placement of ventilation components to create barriers against interzonal droplet transmission. This study highlights the potential of targeted ventilation strategies to significantly reduce the risk of airborne infection in enclosed, populated spaces.

Correlation of diaphragm thickening fraction and oesophageal pressure swing in non-invasive ventilation of healthy subjects

IntroductionThe diaphragm thickening fraction (DTF) may be a valuable tool for estimating respiratory effort in non-invasive ventilation. The primary aim of this physiological study is the investigation of the correlation of DTF with oesophageal pressure swings (ΔPoes). A secondary aim is to assess the discriminatory capacity of the index tests for different exercise loads.MethodsHealthy volunteers underwent spontaneous breathing and non-invasive ventilation with a sequence of different respirator settings. The first sequence was carried out at rest. The same sequence was repeated twice, with additional ergometry of 25 and 50 Watts, respectively. DTF and ΔPoes were measured during each ventilation configuration.Results23 individuals agreed to participate. DTF was moderately correlated with ΔPoes (repeated measures correlation ρ = 0.410, p < 0.001). Both ΔPoes and DTF increased consistently with exercise loading in every ventilation configuration, however ΔPoes showed greater discriminatory capacity.ConclusionDTF was moderately correlated with ΔPoes and could discriminate reasonably between exercise loads in a small cohort of non-invasively ventilated healthy subjects. While it may not accurately reflect the absolute respiratory effort, DTF might help titrating individual non-invasive respiratory support. Further investigations are needed to test this hypothesis.Trial RegistrationThis study was not prospectively registered.

Volatile gas scavenging in the paediatric intensive care unit: Occupational health and safety assessment.

The use of volatile anesthetic agents in the paediatric intensive care unit (PICU) is experiencing increased interest since the availability of the miniature vapourizing device. However, the effectiveness of scavenging systems in the presence of humidifiers in the ventilator circuit is unknown. We performed a bench study to evaluate the effectiveness of the Deltasorb® scavenging system in the presence of isoflurane and active humidity by simulating both infant and child ventilator test settings. A total of four ventilators were set to ventilate test lungs, all with active humidity and a Deltasorb scavenging canister collecting exhaled ventilation gas. Two ventilators also had isoflurane delivered using the Anesthesia Conserving Device- small (ACD®-S) on the inspiratory limb (also called alternative ventilator configuration). We performed instantaneous measurements of isoflurane and continuous sampling with passive badges to measure average environmental exposure over a test period of 6.5 hours. Scavenging canisters were returned to the company, where desorption analysis showed the volume of water and isoflurane captured in each canister. Both instantaneous point sampling and diffusive sampling results were below the occupational exposure limit confirming safety. The canisters collected both isoflurane and a portion of the water vapour delivered; the percentage of captured water and isoflurane collected in infants was higher than the child ventilator test settings. The tested scavenging configuration was effective in maintaining a safe working environment with active humidity and inspiratory limb (alternative) ventilator configuration of the the miniature vapourizing device.

Energy consumption and thermal comfort assessment using CFD in a naturally ventilated indoor environment under different ventilations

The rising energy demands of modern buildings necessitate the proper balance between occupant comfort and energy efficiency. This study numerically evaluates the effect of different inlet and exhaust vent profiles on indoor IEQ and energy consumption in well-validated, occupied office buildings for a cold climate conditions. Using ANSYS products, the research evaluates the impact of different ventilation configurations on occupant comfort using different comfort parameters such as, PMV, PPD, air temperature, temperature gradient, fluid flow velocity. The study also analyze how different ventilation configurations affect the thermal load on the radiator for indoor thermal comfort. The findings reveal a significant effect of ventilation profiles on both IEQ and energy consumption. Inadequate ventilation configuration selection can lead to a significant increase in radiator heat load, potentially increase up to 117.3%. Conversely, the adoption of an optimized ventilation strategy can simultaneously reduce energy consumption and improve indoor occupant thermal comfort. Indoor occupant comfort with minimal radiator heat load can be achieved using vertically oriented, rectangular inlet and exhaust vents with a perimeter ratio of 0.611. This research contributes to the development of sustainable buildings and describes indoor comfort design for cold climate conditions.

A GPU-accelerated computational fluid dynamics solver for assessing shear-driven indoor airflow and virus transmission by scale-resolved simulations

We explore the applicability of MATLAB for 3D computational fluid dynamics (CFD) of shear-driven indoor airflows. A new scale-resolving, large-eddy simulation (LES) solver titled DNSLABIB is proposed for MATLAB utilizing graphics processing units (GPUs). In DNSLABIB, the finite difference method is applied for the convection and diffusion terms while a Poisson equation solver based on the fast Fourier transform (FFT) is employed for the pressure. The immersed boundary method (IBM) for Cartesian grids is proposed to model solid walls and objects, doorways, and air ducts by binary masking of the solid/fluid domains. The solver is validated in two canonical reference cases and against experimental data. Then, we demonstrate the validity of DNSLABIB in a room geometry by comparing the results against another CFD software (OpenFOAM). Next, we demonstrate the solver performance in several isothermal indoor ventilation configurations and the implications of the results are discussed in the context of airborne transmission of COVID-19. The novel numerical findings using the new CFD solver are as follows. First, a linear scaling of DNSLABIB is demonstrated and a speed-up by a factor of 3-4 is also noted in comparison to similar OpenFOAM simulations. Second, ventilation in three different indoor geometries are studied at both low (0.1 m/s) and high (1 m/s) airflow rates corresponding to Re=5000 and Re=50000. An analysis of the indoor CO2 concentration is carried out as the room is emptied from stale, high CO2 content air. We estimate the air changes per hour (ACH) values for three different room geometries and show that the numerical estimates from 3D CFD simulations differ by 80%–150% (Re=50000) and 75%–140% (Re=5000) from the theoretical ACH value based on the perfect mixing assumption. Third, the analysis of the CO2 probability distributions (PDFs) indicates a relatively non-uniform distribution of fresh air indoors. Fourth, utilizing a time-dependent Wells-Riley analysis, an example is provided on the growth of the cumulative infection risk which is shown to reduce rapidly after the ventilation is started. The average infection risk is shown to reduce by a factor of 2 for lower ventilation rates (ACH=3.4-6.3) and 10 for the higher ventilation rates (ACH=37-64). Finally, we utilize the new solver to comment on respiratory particle transport indoors. A key contribution of the paper is to provide an efficient, GPU compatible CFD solver environment enabling scale-resolved simulations (LES/DNS) of airflow in large indoor geometries on a single GPU designed for high-performance computing. The demonstrated efficacy of MATLAB for GPU computing indicates a high potential of DNSLABIB for various future developments on airflow prediction.

Ventilation-Based Strategy to Manage Intraoperative Aerosol Viral Transmission in the Era of SARS-CoV-2.

In operating theaters, ventilation systems are designed to protect the patient from airborne contamination for minimizing risks of surgical site infections (SSIs). Ventilation systems often produce an airflow pattern that continuously pushes air out of the area surrounding the operating table, and hence reduces the resident time of airborne pathogen-carrying particles at the patient's location. As a result, patient-released airborne particles due to the use of powered tools, such as surgical smoke and insufflated CO2, typically circulate within the room. This circulation exposes the surgical team to airborne infection-especially when operating on a patient with infectious diseases, including COVID-19. This study examined the flow pattern of functional ventilation configurations in view of developing ventilation-based strategies to protect both the patient and the surgical team from aerosolized infections. A favorable design that minimized particle circulation was deduced using experimentally validated numerical models. The parameters adapted to quantify circulation of airborne particles were particles' half-life and elevation. The results show that the footprint of the outlet ducts and resulting flow pattern are important parameters for minimizing particle circulation. Overall, this study presents a modular framework for optimizing the ventilation systems that permits a switch in operation configuration to suit different operating procedures.

Impact of Diffuser Location on Thermal Comfort Inside a Hospital Isolation Room

Thermal comfort is increasingly recognized as vital in healthcare facilities, where patients spend 80–90% of their time indoors. Sensing, controlling, and predicting indoor air quality should be monitored for thermal comfort. This study examines the effects of ventilation design on thermal comfort in hospital rooms, proposing four distinct ventilation configurations, each with three airflow rates of 9, 12, and 15 Air Changes per Hour (ACH). The study conducted various ventilation simulation scenarios for a hospital room. The objective is to determine the effect of airflow and the diffuser location distribution on thermal comfort. The Reynolds-Averaged Navier–Stokes (RANS) equations, along with the k–ε turbulence model, were used as the underlying mathematical representation for the airflow. The boundary conditions for the simulations were derived from the ventilation standards set by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) and insights from previous studies. Thermal comfort and temperature distribution were assessed using indices like Predicted Percentage Dissatisfaction (PPD), Predicted Mean Vote (PMV), and Air Diffusion Performance Index (ADPI). Although most of the twelve scenarios failed to attain thermal comfort, two of those instances were optimal in this simulation. Those instances involved the return diffuser behind the patient and airflow of 9 ACH, the minimum recommended by previous studies. It should be noted that the ADPI remained unmet in these cases, revealing complexities in achieving ideal thermal conditions in healthcare environments. This study extends the insights from our prior research, advancing our understanding of ventilation impacts on thermal comfort in healthcare facilities. It underscores the need for comprehensive approaches to environmental control, setting the stage for future research to refine these findings further.

A novel transparent cabin used in the classroom during the coronavirus pandemic: a CFD analysis

A coronavirus family is a diverse group of many viruses. Coronavirus disease 19 (COVID-19) spreads when an infected person breathes out droplets and very small particles that contain the virus. These droplets and particles can be breathed in by other people or land on their eyes, noses, or mouths. In this paper, the airflow distribution and the movement of coronavirus particles during normal breathing and sneezing in classrooms have been studied using a CFD model developed in ANSYS® 2022R2. The objective is to find ways to control the spread of the virus that enable us to practice academic activity and deal normally with the pandemic and the spread of the disease. Experiments were done with more than one turbulence model to know which was closest to the experiments as well as to determine the best number of meshes in the classroom. The effect of turbulent dispersion on particles is resolved using a discrete random walk model for the discrete phase and the RANS model for the continuous phase in a coupled Eulerian–Lagrangian method. Furthermore, that is done in two scenarios: the first is to find the best ventilation configuration by investigating the following parameters: the effect of air change per hour, the height of the air inlets and outlets, and the infected student's position. The second is to control the spread of the coronavirus in the classroom in the event of sneezing from an infected student by placing cabins and an air filter with optimal design installed at the top around each student. It was found that optimal ventilation is achieved when fresh air enters from the side walls of the classroom at a distance of 1 m from the floor and the air exits from the ceiling in the form of two rows, and the rate change of air per hour (ACH) is 4, which leads to energy savings. In addition, a novel transparent cabin is designed for the student to sit in while in the classroom, consisting of a high-efficiency particulate air filter (HEPA) that collects any contamination and recirculates it from the top of the cabin back into the classroom with different fan speeds. Through this study, this cabin with a filter was successfully able to prevent any sneeze particles inside from reaching the rest of the students in the classroom.

Comparison of the performance of different mixing ventilation configurations in particle removal from indoor spaces

Re-suspended particles from indoor sufaces present a real threat to occupants. The ventilation system plays a primordial role in enhancing the indoor air quality. A CFD model was developed to compare particle removal effectiveness of variable mixed air distribution configurations. A parametric study was performed to assess the effect of two main factors affecting the airflow pattern: the relative inlet/outlet location and suction velocity. It was found that the mixing ventilation configuration with floor outlets located at middle of the walls presented the best performance due to the creation of a suction effect covering the majority of the floor area leading to high removal effectiveness. Furthermore, increasing the suction velocity strengthened the suction effect resulting in better particle removal by the escape of a larger number of particles generated at floor level.

Esophageal balloon catheter system identification to improve respiratory effort time features and amplitude determination

Objective. Understanding a patient’s respiratory effort and mechanics is essential for the provision of individualized care during mechanical ventilation. However, measurement of transpulmonary pressure (the difference between airway and pleural pressures) is not easily performed in practice. While airway pressures are available on most mechanical ventilators, pleural pressures are measured indirectly by an esophageal balloon catheter. In many cases, esophageal pressure readings take other phenomena into account and are not a reliable measure of pleural pressure. Approach. A system identification approach was applied to provide accurate pleural measures from esophageal pressure readings. First, we used a closed pressurized chamber to stimulate an esophageal balloon and model its dynamics. Second, we created a simplified version of an artificial lung and tried the model with different ventilation configurations. For validation, data from 11 patients (five male and six female) were used to estimate respiratory effort profile and patient mechanics. Main results. After correcting the dynamic response of the balloon catheter, the estimates of resistance and compliance and the corresponding respiratory effort waveform were improved when compared with the adjusted quantities in the test bench. The performance of the estimated model was evaluated using the respiratory pause/occlusion maneuver, demonstrating improved agreement between the airway and esophageal pressure waveforms when using the normalized mean squared error metric. Using the corrected muscle pressure waveform, we detected start and peak times 130 ± 50 ms earlier and a peak amplitude 2.04 ± 1.46 cmH2O higher than the corresponding estimates from esophageal catheter readings. Significance. Compensating the acquired measurements with system identification techniques makes the readings more accurate, possibly better portraying the patient’s situation for individualization of ventilation therapy.

Ventilator hyperinflation associated with flow bias optimization in the bronchial hygiene of mechanically ventilated patients

Background: Ventilation configurations are of great clinical importance for adequate outcomes in mechanically ventilated patients, and they may even be used as specific physical therapy techniques.Objectives: To compare the effectiveness of lung hyperinflation through mechanical ventilation (HMV) with HMV plus flow bias optimization regarding respiratory mechanics, hemodynamics, and volume of secretion.Methods: Patients mechanically ventilated > 24 h were included in this randomized crossover clinical trial. The following techniques were applied: HMV alone (control group) and HMV plus flow bias optimization (intervention group).Results: The 20 included patients underwent both techniques, totaling 40 collections. A total of 52 % were women, the mean age was 60.8 (SD, 15.7) years, and the mean mechanical ventilation time was 4.3 (SD, 3.0) days. The main cause of mechanical ventilation was sepsis (44 %). Expiratory flow bias in optimized HMV was higher. than conventional HMV (p < 0.001). The volume of tracheal secretions collected was higher during optimized than conventional HMV. (p = 0.012). Significant differences in peak flow occurred at the beginning of the technique and a there was a significant decrease in respiratory system resistance immediately and 30 min after applying the technique in the intervention group.Conclusions: The volume of tracheal secretions collected was higher during optimized HMV, and, HMV with flow bias optimization resulted in lower respiratory system resistance and flow peaks and produced expiratory flow bias.