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At least 55 records · Page 3

Towards an MHD Theory for the Standoff Distance of Earth's Bow Shock

A magnetohydrodynamic (MHD) theory is developed for the standoff distance a(s) of the bow shock and the thickness Delta(ms) of the magnetosheath, using the empirical Spreiter et al. relation Delta(ms) = kX and the MHD density ratio X across the shock. The theory includes as special cases the well-known gasdynamic theory and associated phenomenological MHD-like models for Delta(ms) and As. In general, however, MHD effects produce major differences from previous models, especially at low Alfev (Ma) and Sonic (Ms) Mach numbers. The magnetic field orientation Ma, Ms and the ratio of specific heats gamma are all important variables of the theory. In contrast, the fast mode Mach number need play no direct role. Three principle conclusions are reached. First the gasdynamic and phenomenological models miss important dependences of field orientation and Ms generally provide poor approximations to the MHD results. Second, changes in field orientation and Ms are predicted to cause factor of approximately 4 changes in Delta(ms) at low Ma. These effects should be important when predicting the shock's location or calculating gramma from observations. Third, using Spreiter et al.'s value for k in the MHD theory leads to maxima a(s) values at low Ma and nominal Ms that are much smaller than observations and MHD simulations require. Resolving this problem requires either the modified Spreiter-like relation and larger k found in recent MHD simulations and/or a breakdown in the Spreiter-like relation at very low Ma.

Carins, Iver H.↗

Relationships between pediatric asthma and socioeconomic/urban variables in Baltimore, Maryland

Spatial relationships between clinical data for pediatric asthmatics (hospital and emergency department utilization rates), and socioeconomic and urban characteristics in Baltimore City were analyzed with the aim of identifying factors that contribute to increased asthma rates. Socioeconomic variables and urban characteristics derived from satellite data explained 95% of the spatial variation in hospital rates. The proportion of families headed by a single female was the most important variable accounting for 89% of the spatial variation. Evidence suggests that the high rates of hospital admissions and emergency department (ED) visits may partially be due to the difficulty of single parents with limited resources managing their child's asthma condition properly. This knowledge can be used for education towards mitigating ED and hospital events in Baltimore City.

Emergency Service, Hospital/utilization↗

Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destination Data

Truck transportation remains the dominant mode of US freight transportation because of its advantages, such as the flexibility of accessing pickup and drop-off points and faster delivery. Because of the massive freight volume transported by trucks, understanding the effects of population and employment characteristics on truck flows is critical for better transportation planning and investment decisions. The US Federal Highway Administration published a truck travel origin-destination data set as part of the Next Generation National Household Travel Survey program. This data set contains the total number of truck trips in 2020 within and between 583 predefined zones encompassing metropolitan and nonmetropolitan statistical areas within each state and Washington, DC. In this study, origin-destination-level truck trip flow data was augmented to include zone-level population and employment characteristics from the US Census Bureau. Census population and County Business Patterns data were included. The final data set was used to train a machine learning algorithm-based model, Extreme Gradient Boosting (XGBoost), where the target variable is the number of total truck trips. Shapley Additive ExPlanation (SHAP) was adopted to explain the model results. Results showed that the distance between the zones was the most important variable and had a nonlinear relationship with truck flows.

Uddin, Majbah↗

Estimation of Surface Air Temperature from MODIS 1km Resolution Land Surface Temperature Over Northern China

Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).

Shen, Suhung↗

Wind tunnel investigation of nacelle-airframe interference at Mach numbers of 0.9 to 1.4 - pressure data, volume 1

Detailed interference force and pressure data were obtained on a representative wing-body nacelle combination at Mach numbers of 0.9 to 1.4. The model consisted of a delta wing-body aerodynamic force model with four independently supported nacelles located beneath the wing-body combination. The model was mounted on a six component force balance, and the left hand wing was pressure instrumented. Each of the two right hand nacelles was mounted on a six component force balance housed in the thickness of the nacelle, while each of the left hand nacelles was pressure instrumented. The primary variables examined included Mach number, angle of attack, nacelle position, and nacelle mass flow ratio. Nacelle axial location, relative to both the wing-body combination and to each other, was the most important variable in determining the net interference among the components.

Bencze, D. P.↗

Utilization of the graded universal testing system to increase the efficiency for assessing aerobic and anaerobic capacity

The in-flight exercise test performed by cosmonauts as part of the Russian Exercise Countermeasure Program is limited to 5 minutes due to communication restrictions. During a recent graded exercise test on a U.S. Shuttle flight, the test was terminated early due to an upcoming loss of signal (LOS) with the ground. This exercise test was a traditional test where the subject's exercise capacity dictates the length of the test. For example, one crew member may take 15 minutes to complete the test, while another may take 18 minutes. The traditional exercise test limits the flight schedulers to large blocks of space flight time in order to provide medical and research personnel information on the fitness capacity (maximal oxygen uptake: VO2max) of crew members during flight. A graded exercise test that would take a finite amount of time and a set preparation and recovery time would ease this problem by allowing flight schedulers to plan exercise tests in advance of LOS. The Graded Universal Testing System (GUTS) was designed to meet this goal. Fitness testing of astronauts before and after flight provides pertinent data on many variables. The Detailed Supplemental Objective (DSO608) protocol (6) is one of the graded exercise tests (GXT) currently used in astronaut testing before and after flight. Test times for this protocol have lasted from 11 to 18 minutes. Anaerobic capacity is an important variable that is currently not being evaluated before and after flight. Recent reports (1,2,5) from the literature have suggested that the oxygen deficit at supramaximal exercise is a measure of anaerobic capacity. We postulated that the oxygen deficit at maximal exercise would be an indication of anaerobic capacity. If this postulate can be accepted, then the efficiency of acquiring data from a graded exercise test would increase at least twofold. To examine this hypothesis anaerobic capacity was measured using a modified treadmill test (3,4) designed to exhaust the anaerobic systems in approximately 45 to 75 seconds. Lactate concentration in the blood was analyzed after all tests, since lactate is the end-product of anaerobic energy production. Therefore, the peak lactate response is an additional indication of anaerobic capacity. A preliminary comparison of the GUTS and the DSO608 suggests that the GUTS protocol would increase the efficiency of VO2max testing of astronauts before and after flight. Results for anaerobic capacity have not been tabulated.

Rodgers, Sandra L.↗

Machine-learning-based investigation of the variables affecting summertime lightning occurrence over the Southern Great Plains

Lightning is affected by many factors, many of which are not routinely measured, well understood, or accounted for in physical models. Several commonly used machine learning (ML) models have been applied to analyze the relationship between Atmospheric Radiation Measurement (ARM) data and lightning data from the Earth Networks Total Lightning Network (ENTLN) in order to identify important variables affecting lightning occurrence in the vicinity of the Southern Great Plains (SGP) ARM site during the summer months (June, July, August and September) of 2012 to 2020. Testing various ML models, we found that the random forest model is the best predictor among common classifiers. When convective clouds were detected, it predicts lightning occurrence with an accuracy of 76.9 % and an area under the curve (AUC) of 0.850. Using this model, we further ranked the variables in terms of their effectiveness in nowcasting lightning and identified geometric cloud thickness, rain rate and convective available potential energy (CAPE) as the most effective predictors. The contrast in meteorological variables between no-lightning and frequent-lightning periods was examined for hours with CAPE values conducive to thunderstorm formation. Besides the variables considered for the ML models, surface variables and mid-altitude variables (e.g., equivalent potential temperature and minimum equivalent potential temperature, respectively) have statistically significant contrasts between no-lightning and frequent-lightning hours. For example, the minimum equivalent potential temperature from 700 to 500 hPa is significantly lower during frequent-lightning hours compared with no-lightning hours. Finally, a notable positive relationship between the intracloud (IC) flash fraction and the square root of CAPE ($\sqrt{CAPE}$) was found, suggesting that stronger updrafts increase the height of the electrification zone, resulting in fewer flashes reaching the surface and consequently a greater IC flash fraction.

54 ENVIRONMENTAL SCIENCES↗

A machine learning approach for identifying variables associated with risk of developing neutralizing antidrug antibodies to factor VIII

A key unmet need in the management of hemophilia A (HA) is the lack of clinically validated markers that are associated with the development of neutralizing antibodies to Factor VIII (FVIII) (commonly referred to as inhibitors). This study aimed to identify relevant biomarkers for FVIII inhibition using Machine Learning (ML) and Explainable AI (XAI) using the My Life Our Future (MLOF) research repository. The dataset includes biologically relevant variables such as age, race, sex, ethnicity, and the variants in the F8 gene. In addition, we previously carried out Human Leukocyte Antigen Class II (HLA-II) typing on samples obtained from the MLOF repository. Using this information, we derived other patient-specific biologically and genetically important variables. These included identifying the number of foreign FVIII derived peptides, based on the alignment of the endogenous FVIII and infused drug sequences, and the foreign-peptide HLA-II molecule binding affinity calculated using NetMHCIIpan. The data were processed and trained with multiple ML classification models to identify the top performing models. The top performing model was then chosen to apply XAI via SHAP, (SHapley Additive exPlanations) to identify the variables critical for the prediction of FVIII inhibitor development in a hemophilia A patient. Using XAI we provide a robust and ranked identification of variables that could be predictive for developing inhibitors to FVIII drugs in hemophilia A patients. These variables could be validated as biomarkers and used in making clinical decisions and during drug development. The top five variables for predicting inhibitor development based on SHAP values are: (i) the baseline activity of the FVIII protein, (ii) mean affinity of all foreign peptides for HLA DRB 3, 4, & 5 alleles, (iii) mean affinity of all foreign peptides for HLA DRB1 alleles), (iv) the minimum affinity among all foreign peptides for HLA DRB1 alleles, and (v) F8 mutation type.

60 APPLIED LIFE SCIENCES↗

Relative toxicity of products of pyrolysis and combustion of polymeric materials using various test conditions

Relative toxicity data for a large number of natural and synthetic polymeric materials are presented which were obtained by 11 pyrolysis and three flaming-combustion test methods. The materials tested include flexible and rigid polyurethane foams, different kinds of fabrics and woods, and a variety of commodity polymers such as polyethylene. Animal exposure chambers of different volumes containing mice, rats, or rabbits were used in the tests, which were performed over the temperature range from ambient to 800 C with and without air flow or recirculation. The test results are found to be sensitive to such variables as exposure mode, temperature, air flow and dilution, material concentration, and animal species, but relative toxicity rankings appear to be similar for many methods and materials. It is concluded that times to incapacitance and to death provide a more suitable basis for relative toxicity rankings than percent mortality alone, that temperature is the most important variable in the tests reported, and that variables such as chamber volume and animal species may not significantly affect the rankings.

Hilado, C. J.↗

Simple Statistical Models for Predicting Overpressure Due to CO2 and Low-Salinity Waste-Fluid Injection into Deep Saline Formations

Deep saline aquifers have been used for waste-fluid disposal for decades and are the proposed targets for large-scale CO2 storage to mitigate CO2 concentration in the atmosphere. Due to relatively limited experience with CO2 injection in deep saline formations and given that the injection targets for CO2 sometimes are the same as waste-fluid disposal formations, it could be beneficial to model and compare both practices and learn from the waste-fluid disposal industry. In this paper, we model CO2 injection in the Patterson Field, which has been proposed as a site for storage of 50 Mt of industrial CO2 over 25 years. We propose general models that quickly screen the reservoir properties and calculate pressure changes near and far from the injection wellbore, accounting for variable reservoir properties. The reservoir properties we investigated were rock compressibility, injection rate, vertical-to-horizontal permeability ratio, average reservoir permeability and porosity, reservoir temperature and pressure, and the injectant total dissolved solids (TDS) in cases of waste-fluid injection. We used experimental design to select and perform simulation runs, performed a sensitivity analysis to identify the important variables on pressure build-up, and then fit a regression model to the simulation runs to obtain simple proxy models for changes in average reservoir pressure and bottomhole pressure. The CO2 injection created more pressure compared to saline waste-fluids, when similar mass was injected. However, we found a more significant pressure buildup at the caprock-reservoir interface and lower pressure buildup at the bottom of the reservoir when injecting CO2 compared with waste-fluid injection.

Ansari, Esmail↗

A New Approach to Monitoring Coastal Marshes for Persistent Flooding

Many areas in coastal Louisiana are below sea level and protected from flooding by a system of natural and man-made levees. Flooding is common when the levees are overtopped by storm surge or rising rivers. Many levees in this region are further stressed by erosion and subsidence. The floodwaters can become constricted by levees and trapped, causing prolonged inundation. Vegetative communities in coastal regions, from fresh swamp forest to saline marsh, can be negatively affected by inundation and changes in salinity. As saltwater persists, it can have a toxic effect upon marsh vegetation causing die off and conversion to open water types, destroying valuable species habitats. The length of time the water persists and the average annual salinity are important variables in modeling habitat switching (cover type change). Marsh type habitat switching affects fish, shellfish, and wildlife inhabitants, and can affect the regional ecosystem and economy. There are numerous restoration and revitalization projects underway in the coastal region, and their effects on the entire ecosystem need to be understood. For these reasons, monitoring persistent saltwater intrusion and inundation is important. For this study, persistent flooding in Louisiana coastal marshes was mapped using MODIS (Moderate Resolution Imaging Spectroradiometer) time series of a Normalized Difference Water Index (NDWI). The time series data were derived for 2000 through 2009, including flooding due to Hurricane Rita in 2005 and Hurricane Ike in 2008. Using the NDWI, duration and extent of flooding can be inferred. The Time Series Product Tool (TSPT), developed at NASA SSC, is a suite of software developed in MATLAB(R) that enables improved-quality time series images to be computed using advanced temporal processing techniques. This software has been used to compute time series for monitoring temporal changes in environmental phenomena, (e.g. NDVI times series from MODIS), and was modified and used to compute the NDWI indices and also the Normalized Difference Soil Index (NDSI). Coastwide Reference Monitoring System (CRMS) water levels from various hydrologic monitoring stations and aerial photography were used to optimize thresholds for MODIS-derived time series of NDWI and to validate resulting flood maps. In most of the profiles produced for post-hurricane assessment, the increase in the NDWI index (from storm surge) is accompanied by a decrease in the vegetation index (NDVI) and then a period of declining water. The NDSI index represents non-green or dead vegetation and increases after the hurricane s destruction of the marsh vegetation. Behavior of these indices over time is indicative of which areas remain flooded, which areas recover to their former levels of vegetative vigor, and which areas are stressed or in transition. Tracking these indices over time shows the recovery rate of vegetation and the relative behavior to inundation persistence. The results from this study demonstrated that identification of persistent marsh flooding, utilizing the tools developed in this study, provided an approximate 70-80 percent accuracy rate when compared to the actual days flooded at the CRMS stations.

Kalcic, M. T.↗

The effects of forced air flow and oxygen concentration on flammability, smoke density, and pyrolytic toxicity

The question is posed whether forced air flow should be incorporated into flammability tests as a relevant variable. A test apparatus is described which permits tests to be conducted on small test specimens in a forced flow which is (continuously) variable over flow velocities from zero to 300 feet per minute (1.52 m/s). The effects of air-flow rate and oxygen concentration on flame propagation rate, maximum smoke density, and pyrolytic product toxicity were measured for a single material and were statistically evaluated. Regression analysis was used to graph the resulting relationships. It is concluded that air velocity is an important variable for laboratory flammability testing.

Sauers, D. G.↗

Demonstration of the Application of Composite Load Spectra (CLS) and Probabilistic Structural Analysis (PSAM) Codes to SSME Heat Exchanger Turnaround Vane

This report describes a probabilistic structural analysis performed to determine the probabilistic structural response under fluctuating random pressure loads for the Space Shuttle Main Engine (SSME) turnaround vane. It uses a newly developed frequency and distance dependent correlation model that has features to model the decay phenomena along the flow and across the flow with the capability to introduce a phase delay. The analytical results are compared using two computer codes SAFER (Spectral Analysis of Finite Element Responses) and NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) and with experimentally observed strain gage data. The computer code NESSUS with an interface to a sub set of Composite Load Spectra (CLS) code is used for the probabilistic analysis. A Fatigue code was used to calculate fatigue damage due to the random pressure excitation. The random variables modeled include engine system primitive variables that influence the operating conditions, convection velocity coefficient, stress concentration factor, structural damping, and thickness of the inner and outer vanes. The need for an appropriate correlation model in addition to magnitude of the PSD is emphasized. The study demonstrates that correlation characteristics even under random pressure loads are capable of causing resonance like effects for some modes. The study identifies the important variables that contribute to structural alternate stress response and drive the fatigue damage for the new design. Since the alternate stress for the new redesign is less than the endurance limit for the material, the damage due high cycle fatigue is negligible.

Rajagopal, Kadambi R.↗

Applying NIR and MIR spectroscopy for C and soil property prediction in northern cold-region ecosystems. Which approach works better?

Here, developing reliable predictions of soil attributes is necessary to understand northern cold-region climate-soil feedback. Calibration models using near-infrared (NIR) and mid-infrared (MIR) spectroscopy were developed to predict eight commonly measured soil properties for 119 soil samples representing a range of vegetation types, parent materials, and soil types spanning >23° of latitude from southeast Alaska to the Canadian high Arctic. In order to obtain a more accurate prediction, this study compared the performance of linear and non-linear calibration techniques, including lasso regression (Lasso), support vector machine (SVM), random forest (RF) and classic partial least squares (PLS) to predict different soil properties of these soils. Comparing the four models, we noticed that their performance was quite similar for MIR overall, while NIR achieved better results with a PLS model for our dataset. PLS coupled with MIR showed a better performance for soil parameters, such as total organic carbon (TOC), total nitrogen (TN), cation exchange capacity (CEC) and clay (R-squared of 0.9, 0.81, 0.80, and 0.84) when compared with NIR (R-squared of 0.85, 0.72, 0.81 and 0.68). However, using either MIR or NIR spectroscopy, PLS predictions for bulk density (BD) and sand content were not accurate. The variable importance analysis based on the PLS model successfully estimated the relative contribution of wavelengths influencing soil property predictions most. Overall, TOC, TN, CEC and clay mineral predictions are closely related to the occurrence of specific spectral bands in the MIR region. For example, wavelengths at 2978 and 1761 cm -1 for TOC and TN, as well as at 3064 cm -1 for CEC, were selected as the most influential predictor variables. We demonstrated that MIR spectroscopy is a powerful tool for more extensive monitoring in soils of the northern cold climate region; however, NIR could be utilized for rapid estimates when the highest accuracy is not essential.

54 ENVIRONMENTAL SCIENCES↗

Wind tunnel investigation of Nacelle-Airframe interference at Mach numbers of 0.9 to 1.4-pressure data, volume 2

Detailed interference force and pressure data were obtained on a representative wing-body nacelle combination at Mach numbers of 0.9 to 1.4. The model consisted of a delta wing-body aerodynamic force model with four independently supported nacelles located beneath the wing-body combination. The primary variables examined included Mach number, angle of attack, nacelle position, and nacelle mass flow ratio. Four different configurations were tested to identify various interference forces and pressures on each component; these included tests of the isolated nacelle, the isolated wing-body combination, the four nacelles as a unit, and the total wing-body-nacelle combination. Nacelle axial location, relative to both the wing-body combination and to each other, was the most important variable in determining the net interference among the components. The overall interference effects were found to be essentially constant over the operating angle-of-attack range of the configuration, and nearly independent of nacelle mass flow ratio.

Bencze, D. P.↗

Wind tunnel investigation of Nacelle-Airframe interference at Mach numbers of 0.9 to 1.4-force data

Detailed interference force and pressure data were obtained on a representative wing-body-nacelle combination at Mach numbers of 0.9 to 1.4. The model consisted of a delta wing-body aerodynamic force model with four independently supported nacelles located beneath the wing-body combination. The model was mounted on a six-component force balance, and the left-hand wing was pressure-instrumented. Each of the two right-hand nacelles was mounted on a six-component force balance housed in the thickness of the nacelle, while each of the left-hand nacelles was pressure-instrumented. The primary variables examined included Mach number, angle of attack, nacelle position, and nacelle mass-flow ratio. Four different configurations were tested to identify various interference forces and pressures on each component; these included tests of the isolated nacelle, the isolated wing-body combination, the four nacelles as a unit, and the total wing-body-nacelle combination. Nacelle axial location, relative to both the wing-body combination and to each other, was the most important variable in determining the net interference among the components.

Bencze, D. P.↗

Formation of Amorphous Carbon Multi‐Walled Nanotubes from Random Initial Configurations

Amorphous carbon nanotubes (a‐CNT) with up to four walls and sizes ranging from 200 to 3200 atoms have been simulated, starting from initial random configurations and using the Gaussian Approximation Potential. The important variables (like density, height, and diameter) required to successfully simulate a‐CNTs were predicted with the machine learning random forest technique. The width of the a‐CNT models ranged between 0.55–2 nm with an average inter‐wall spacing of 0.31 nm. The topological defects in a‐CNTs were analyzed and new defect configurations were observed. The electronic density of states and localization in these phases were discussed and delocalized electrons in the π subspace were identified as an important factor for inter‐layer cohesion. Spatial projection of the electronic conductivity favors axial transport along connecting hexagons, while non‐hexagonal parts of the network either hinder or bifurcate the electronic transport. A vibrational density of states was calculated and is potentially an experimentally comparable fingerprint of the material. The appearance of a low‐frequency radial breathing mode was discussed and the thermal conductivity at 300 K was estimated using the Green‐Kubo formula.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sea Ice Floe Distribution in the Beaufort and Chukchi Seas Measured by ERS-1 SAR

This study examines the spatial and temporal character of sea ice floe size distribution during summer melt, important variables for understanding the summer heat and mass budgets and the distribution of heat between the vertical and horizontal ice melt. Preliminary results are presented that indicate the gradual decrease in medium size floes (1-5 km diameters) and a fairly steady maintenance of floes smaller than 1 km in diameter over the primary summer months within the central pack ice region. The latter result indicates that smaller floes continue to melt or decay rather than accumulate, indicating the importance of dynamics in affecting ice melt.

sea ice floes SAR imagery Beaufort Sea Chukchi Sea↗