Fluid-Structure Interaction Simulation of Blood Flow and Cerebral Aneurysm: Effect of Partly Blocked Vessel

In this study, using fluid-structure interaction (FSI), 3-dimensional blood flow in an aneurysm in the circle of Willis - which is located in the middle cerebral artery (MCA) - has been simulated. The purpose of this study is to evaluate the effect of a partly blocked vessel on an aneurysm. To achieve this purpose, two cases have been investigated using the FSI method: in the first case, an ideal geometry of aneurysm in the MCA has been simulated; in the second case, modeling is performed for an ideal geometry of the aneurysm in the MCA with a partly blocked vessel. All boundary conditions, properties and modeling methods were considered the same for both cases. The only difference between the two cases was that part of the MCA parent artery was blocked in the second case. In order to consider the hyperelastic property of the wall and the non-Newtonian properties of the blood, the Mooney-Rivlin model and the Carreau model have been used, respectively. In the second case, the Von Mises stress in the peak systole is 26% higher than in the first case. With regard to the high amount of Von Mises stress, the risk of rupture of the aneurysm is higher in this case. In the second case, the maximum wall shear stress (WSS) is 12% higher than in the first case. And maximum displacement in the second case is also higher than in the first. So, the risk of growth of the aneurysm is higher in cases with a partly blocked vessel.

Validation of mobile in situ measurements of dairy husbandry emissions by fusion of airborne/surface remote sensing with seasonal context from the Chino Dairy Complex

Mobile in situ concentration and meteorology data were collected for the Chino Dairy Complex in the Los Angeles Basin by AMOG (AutoMObile trace Gas) Surveyor on 25 June 2015 to characterize husbandry emissions in the near and far field in convoy mode with MISTIR (Mobile Infrared Sensor for Tactical Incident Response), a mobile upwards-looking, column remote sensing spectrometer. MISTIR reference flux validated AMOG plume inversions at different information levels including multiple gases, GoogleEarth imagery, and airborne trace gas remote sensing data. Long-term (9-yr.) Infrared Atmospheric Sounding Interferometer satellite data provided spatial and trace gas temporal context. For the Chino dairies, MISTIR-AMOG ammonia (NH₃) agreement was within 5% (15.7 versus 14.9 Gg yr^-1, respectively) using all information. Methane (CH₄) emissions were 30 Gg yr^-1 for a 45,200 herd size, indicating that Chino emission factors are greater than previously reported. Single dairy inversions were much less successful. AMOG-MISTIR agreement was 57% due to wind heterogeneity from downwind structures in these near-field measurements and emissions unsteadiness. AMOG CH₄, NH₃, and CO₂ emissions were 91, 209, and 8200 Mg yr^-1, implying 2480, 1870, and 1720 head using published emission factors. Plumes fingerprinting identified likely sources including manure storage, cowsheds, and a structure with likely natural gas combustion. NH₃ downwind of Chino showed a seasonal variation of a factor of ten, three times larger than literature suggests. Chino husbandry practices and trends in herd size and production were reviewed and unlikely to add seasonality. Higher emission seasonality was proposed as legacy soil emissions, the results of a century of husbandry, supported by airborne remote sensing data showing widespread emissions from neighborhoods that were dairies 15 years prior, and AMOG and MISTIR observations. Seasonal variations provide insights into the implications of global climate change and must be considered when comparing surveys from different seasons.

METHODS FOR ATTRIBUTING AMBIENT AIR POLLUTANTS TO EMISSION SOURCES

▪ Abstract  Six methods for attributing ambient pollutants to emission sources are reviewed: emissions analysis, trend analysis, tracer studies, trajectory analysis, receptor modeling, and dispersion modeling. The ranges of applicability, types of information provided, limitations, performance capabilities, and areas of active research of the different methods are compared. For primary, nonreactive pollutants whose effects of concern occur on a global scale, an accounting of emissions rates by source type and location largely characterizes source contributions. For other pollutants or smaller spatial scales, accurate estimates of emissions are needed for identifying the emissions reduction potentials of possible control measures and as inputs to dispersion models. Emission levels are frequently known with factor-of-two accuracy or worse, and improved estimates are needed for dispersion modeling. The analysis of regional or urban-scale trends in emissions and ambient pollutant concentrations can provide qualitative information on source contributions, but quantitative results are limited by the confounding influence of variations in meteorology and uncertainties in the areas over which emissions affect concentrations. Tracer studies are useful for quantifying dispersion characteristics of plumes, qualitatively characterizing transport directions, and providing empirical data for evaluating trajectory and dispersion models. Data are usually temporally limited to a short study period, typically do not provide information on vertical pollutant distributions, and are most applicable to the transport of primary, nonreactive pollutants. Trajectory analyses are routinely used to estimate atmospheric transport directions. Trajectory errors of about 20% of travel distance are considered typical of the better models and data sets. Receptor models use measurements of ambient pollutant concentrations to quantify the contributions of different source types to primary particulate matter or volatile organic compounds, or to characterize source-region contributions to a single pollutant. Accuracy rates of ∼30% are often achieved when quantifying the contributions from different types of emission sources. Dispersion models are well-suited for estimating quantitative source-receptor relationships, as the effects of individual emission sources or source regions can be studied. Lagrangian and Gaussian dispersion models are computationally efficient and can simulate the transport of nonreactive primary or linear secondary species. Eulerian models are computationally intensive but lend themselves to the simulation of nonlinear chemistry. Careful evaluation of modeling accuracy is needed for a model application to fulfill its potential for source attribution. Accuracy can be evaluated through a combination of performance evaluation, sensitivity analysis, diagnostic evaluation, and corroborating analyses.