Mohammad H. Hosni

Comparison of Large Eddy Simulation Predictions with Particle Image Velocimetry Data for the Airflow in a Generic Cabin Model

A comparison of computational fluid dynamics (CFD) predictions and experimental data for the airflow in a generic cabin model is presented in this paper. The CFD predictions were generated using the large eddy simulation (LES) model, while the particle image velocimetry (PIV) technique was used to obtain the experimental data. A brief summary of the test setup and the experimental data are described herein. The main focus of this study is to analyze the temporal variation of the experimental data. The time series of the PIV measured velocity components with sampling frequencies of 0.1 and 5 Hz were compared with the CFD predictions, sampling at 20 Hz. Energy spectral analysis, through fast Fourier transformation (FFT) on the PIV data and their CFD counterparts, was performed and is presented in this study. By using direct comparisons of the velocity data, good agreement on the range of the velocity components was obtained at all monitoring locations, hence validating the LES predictions. A similar conclusion can be reached from the results of the energy spectral analysis. The energy-spectrum function calculated from the LES predicted velocity magnitudes has excellent correlation with the Kolmogorov spectrum law in the universal equilibrium range. For the smaller wave numbers, the PIV data taken at 0.1 Hz clearly reveal the characteristic motion of the largest eddy in the flow domain, and it correlates very well with the CFD predictions.

Characterization of the frequency and nature of bleed air contamination events in commercial aircraft

Contamination of the bleed air used to pressurize and ventilate aircraft cabins is of concern due to the potential health and safety hazards for passengers and crew. Databases from the Federal Aviation Administration, NASA, and other sources were examined in detail to determine the frequency of bleed air contamination incidents. The frequency was examined on an aircraft model basis with the intent of identifying aircraft make and models with elevated frequencies of contamination events. The reported results herein may help investigators to focus future studies of bleed air contamination incidents on smaller number of aircrafts. Incident frequency was normalized by the number of aircraft, number of flights, and flight hours for each model to account for the large variations in the number of aircraft of different models. The focus of the study was on aircraft models that are currently in service and are used by major airlines in the United States. Incidents examined in this study include those related to smoke, oil odors, fumes, and any symptom that might be related to exposure to such contamination, reported by crew members, between 2007 and 2012, for US-based carriers for domestic flights and all international flights that either originated or terminated in the US. In addition to the reported frequency of incidents for different aircraft models, the analysis attempted to identify propulsion engines and auxiliary power units associated with aircrafts that had higher frequencies of incidents. While substantial variations were found in frequency of incidents, it was found that the contamination events were widely distributed across nearly all common models of aircraft.

Relaxation of the Turbulent Boundary Layer After an Abrupt Change From Rough to Smooth Wall (Data Bank Contribution)

Measurements of velocity and turbulence intensity profiles and skin friction coefficient are presented for turbulent flat-plate boundary layer flow over a test surface with a rough-to-smooth step change in surface roughness. The first 0.9 m length of the test surface is roughened with 1.27 mm diameter hemispheres spaced 2 base diameters apart in a uniform staggered array, and the remaining 1.5 m length is smooth. The profiles are compared with previous data for all-rough cases under closely matched conditions in the same facility. The skin friction data are compared with previous data for both all-rough and all-smooth cases.

Fine particle dispersion in a commercial aircraft cabin

The spread of particles or contaminants in aircraft cabins is of interest due to the large number of passengers and their close proximity to each other. This close proximity causes concern about the spread of disease and contaminants among passengers. To understand the aircraft cabin environment and the dispersion of fine particles, an experimental study was conducted in an 11-row wide-body aircraft cabin mockup. The experiment focused on the longitudinal dispersion of particles throughout the cabin. The data show the regions close to the source experience higher levels of exposure and higher levels of variation, while locations farther from the source show lower exposure levels and less variation. The variations close to the source likely stem from the interaction of the quick injection burst of particles with chaotic airflow. Particles release in the second row were detected at all locations in the cabin mockup, but there was roughly a 37% decrease in concentration with each successive row in the longitudinal direction from the release location.

Single-Phase Flow in Meso-Channel Compact Heat Exchangers for Air Conditioning Applications

Experimental study of the single-phase heat transfer and fluid flow in meso-channels, i.e., between micro-channels and mini-channels, has received continued interest in recent years. The studies have resulted in empirical correlations for various geometries ranging from simple circular pipes to complicated enhanced noncircular channels. However, it is still unclear whether the correlations developed for conventional macro-channels are directly applicable for use in micro-/mini-channels, i.e., hydraulic diameter less than 3 mm, with heat exchanger applications. A few researchers have agreed that similar results may be obtained for the laminar flow regime regardless of the channel size, but no general agreement has been reached for the transitional and turbulent flow regimes yet. In this study, different meso-channel air–liquid compact heat exchangers were evaluated and the experimental results were compared with published empirical correlations. A modified Wilson plot technique was applied to obtain the heat transfer coefficients, and the Fanning equation was used to calculate the pressure drop friction factors. The uncertainty estimates for the measured and calculated parameters were also calculated. The results of this study showed that the well-established heat transfer and pressure drop correlations for the macro-channels are not directly applicable for use in the compact heat exchangers with meso-channels.

Comparison of Emission Models With Computational Fluid Dynamic Simulation and a Proposed Improved Model

Understanding source behavior is important in controlling exposure to airborne contaminants. Industrial hygienists are often asked to infer emission information from room concentration data. This is not easily done, but models that make simplifying assumptions regarding contaminant transport are frequently used. The errors resulting from these assumptions are not yet well understood. This study compares emission estimates from the single-zone completely mixed (CM-1), two-zone completely mixed (CM-2), and uniform diffusivity (UD) models with the emissions set as boundary conditions in computational fluid dynamic (CFD) simulations of a workplace. The room airflow and concentration fields were computed using Fluent 4. These numerical experiments were factorial combinations of three source locations, five receptor locations, three dilution airflow rates, and two generation rate profiles, constant and time-varying. The aim was to compute plausible concentration fields, not to simulate exactly the processes in a real workroom. Thus, error is defined here as the difference between model and CFD predictions. For the steady-state case the UD model had the lowest error. When the source near-field contained the breathing zone receptor, the CM-2 model was applied. Then, in decreasing agreement with CFD were UD, CM-2, and CM-1. Averaging over all source and receptor locations (CM-2 applied for only one), in decreasing order of agreement with CFD were UD, CM-1, and CM-2. Source and receptor location had large effects on emission estimates using the CM-1 model and some effect using the UD model. A location-specific mixing factor (location factor) derived from steady-state concentration gradients was used to build a more accurate time-dependent emission model, CM-L. Total mass emitted from a time-varying source was modeled most accurately by CM-L, followed by CM-1 and CM-2.

A Computational Study of Turbulent Airflow and Tracer Gas Diffusion in a Generic Aircraft Cabin Model

In order to study the capability of computational methods in investigating the mechanisms associated with disease and contaminants transmission in aircraft cabins, the computational fluid dynamics (CFD) models are used for the simulation of turbulent airflow and tracer gas diffusion in a generic aircraft cabin mockup. The CFD models are validated through the comparisons of the CFD predictions with corresponding experimental measurements. It is found that using large eddy simulation (LES) with the WernerWengle wall function, one can predict unsteady airflow velocity field with relatively high accuracy. However in the middle region of the cabin mockup, where the recirculation of airflow takes place, the accuracy is not as good as that in other locations. By examining different k-e models, the current study recommends the use of the RNG k-e model with the nonequilibrium wall function as an Reynolds averaged Navier-Stokes model for predicting the steady-state airflow velocity. It is also found that changing the nozzle height has a significant effect on the flow behavior in the middle and upper part of the cabin, while the flow pattern in the lower part is not affected as much. Through the use of LES and species transport model in simulating tracer gas diffusion, a very good agreement between predicted and measured tracer gas concentration is achieved for some monitoring locations, but the agreement level is not uniform for all the locations. The reasons for the deviations between prediction and measurement for those locations are discussed. [DOI: 10.1115/1.4025096]

Experimental Investigation of Optimal Particulate Sensor Location in an Aircraft Cabin

Each year millions of people travel by commercial aircrafts. The Bureau of Transportation Statistics indicates that about 600 million passengers fly each year in the United States and, of those, roughly 350,000 are international travelers. This number of travelers leaves commercial airliners potentially vulnerable to biological contamination and makes the transmission of diseases a serious threat. The spread of SARS (Severe Acute Respiratory Syndrome) and H1N1 (swine flu) are examples of documented cases. Consequently, considerable research has been and continues to be conducted to study and understand particulate transport mechanisms and dispersion behavior inside aircraft cabins to develop means for detecting, controlling, and removing contaminants from aircraft cabins and to find methods for preventing the aircraft from being used for intentional contaminant deployment. In order to develop means to monitor and control air quality, infectious disease transmission, and particulate transport inside aircraft cabins, an experimental study was conducted to determine the best sensor placement locations for detection and to identify the number of sensors needed to accurately track air quality incidents within a cabin. An 11-row mockup, intended to be representative of a typical wide-body aircraft, was used for the research. The mockup interior is based on the actual dimensions of the Boeing 767 aircraft cabin. Inside the mockup cabin, actual aircraft equipment including seats and air diffusers were used. Each row has seven passenger seats. Particulates were released from different locations in the second row of the mockup cabin. The transported particles were then collected at six different locations in the lateral direction. The best location to place a sensor was defined as the location having the strongest signal (maximum number of particles collected) or the fastest detection time. After determining the best location in the lateral direction, particles were collected at the same location, but in different rows to estimate the differences between the signal strength and the delay time in detecting the signal from row to row. For the later investigation, the particulates were released in Row 2 and in Row 6 as well. For the six locations examined, it was found that the best location for the placement of a sensor in the 11-row mockup in the lateral direction is on the centerline near the cabin floor. Longitudinally, it was found that a sensor may be used for detecting particulates in the same row as the release and a row in front and in back of the release location. For the mockup cabin, a total of 4 sensors was recommended to monitor particulate releases in the 11 row mockup cabin, each of these sensors separated by two rows.

Tracer Gas Mapping of a Beverage Cart Wake in a Twin Aisle Aircraft Cabin

An experimental study is performed in a mockup Boeing 767 cabin section consisting of eleven rows with seven seats per row. Carbon Dioxide (CO2 ) tracer gas is injected at a constant flow rate at a location of interest until concentrations in the cabin reach steady state. Ventilation equipment and flow rates representative of an actual aircraft are used for all experiments. Seats in the mockup are occupied by thermal manikins to simulate passenger heat load. A motorized beverage cart traverses the length of the cabin aisle passing by the injection location. The concentrations of tracer gas displaced by the cart are measured at locations throughout the cabin. Comparing these measurements to baseline readings taken with no cart movement, a map of the degree to which contaminant transport is affected by the beverage cart is calculated. The cabin mockup is supplied by 100% outdoor air through actual Boeing supply ductwork and linear diffusers along the cabin length above the aisles. The CO2 level is measured in the inlet air, measurement locations in the cabin, and exhaust air using nondispersive infrared (NDIR) sensors. Measured results are reported for all (54) seat locations downstream of the cart traverse/injection location for an injection location near the rear of the cabin. Analogous measurements are also conducted examining the effect of variation in cart speed and modified injection location.Copyright

Design and manufacturing of two thermal observation manikins for automobile applications.

Two state-of-the-art thermal observation manikins were designed and built for use in automobile applications. These manikins not only apply the latest data acquisition and control technology but also incorporate new manufacturing and sensor technology for improved performance. The manikins are equipped with 26 segments that can be easily removed for maintenance and replacement. Furthermore, their unique design offers an important and a major improvement over previous manikin designs by incorporating heat flux transducers (HFTs) to measure heat gain when exposed to external heating conditions. The HFTs provide these manikins the ability to measure heat flux to or from the environment, regardless of segment skin temperature. The end goal for these manikins is to incorporate a subjective model of thermal comfort along with a human thermal physiological model to produce a thermal sensation vote based on a combination of HFTs, temperature sensors, and heater power measurements. This paper discusses the need for two identical research quality thermal manikins and presents the details of the design and construction of two identical thermal manikins and the associated data acquisition and control software.