Exploring Concepts of Operations for On-Demand Passenger Air Transportation

In recent years, a surge of interest in "flying cars" for city commutes has led to rapid development of new technologies to help make them and similar on-demand mobility platforms a reality. To this end, this paper provides analyses of the stakeholders involved, their proposed operational concepts, and the hazards and regulations that must be addressed. Three system architectures emerged from the analyses, ranging from conventional air taxi to revolutionary fully autonomous aircraft operations, each with vehicle safety functions allocated differently between humans and machines. Advancements for enabling technologies such as distributed electric propulsion and artificial intelligence have had major investments and initial experimental success, but may be some years away from being deployed for on-demand passenger air transportation at scale

Developments in Atmosphere Revitalization Modeling and Simulation

"NASA's Advanced Exploration Systems (AES) program is pioneering new approaches for rapidly developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond Earth orbit" (NASA 2012). These forays beyond the confines of earth's gravity will place unprecedented demands on launch systems. They must not only blast out of earth's gravity well as during the Apollo moon missions, but also launch the supplies needed to sustain a crew over longer periods for exploration missions beyond earth's moon. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. Current efforts are focused on improving the current state-of-the-art systems utilizing fixed beds of sorbent pellets by evaluating structured sorbents, seeking more robust pelletized sorbents, and examining alternate bed configurations to improve system efficiency and reliability. These development efforts combine testing of sub-scale systems and multi-physics computer simulations to evaluate candidate approaches, select the best performing options, and optimize the configuration of the selected approach, which is then implemented in a full-scale integrated atmosphere revitalization test. This paper describes the development of atmosphere revitalization models and simulations. A companion paper discusses the hardware design and sorbent screening and characterization effort in support of the Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project within the AES program

Statistical and Probabilistic Extensions to Ground Operations' Discrete Event Simulation Modeling

NASA's human exploration initiatives will invest in technologies, public/private partnerships, and infrastructure, paving the way for the expansion of human civilization into the solar system and beyond. As it is has been for the past half century, the Kennedy Space Center will be the embarkation point for humankind's journey into the cosmos. Functioning as a next generation space launch complex, Kennedy's launch pads, integration facilities, processing areas, launch and recovery ranges will bustle with the activities of the world's space transportation providers. In developing this complex, KSC teams work through the potential operational scenarios: conducting trade studies, planning and budgeting for expensive and limited resources, and simulating alternative operational schemes. Numerous tools, among them discrete event simulation (DES), were matured during the Constellation Program to conduct such analyses with the purpose of optimizing the launch complex for maximum efficiency, safety, and flexibility while minimizing life cycle costs. Discrete event simulation is a computer-based modeling technique for complex and dynamic systems where the state of the system changes at discrete points in time and whose inputs may include random variables. DES is used to assess timelines and throughput, and to support operability studies and contingency analyses. It is applicable to any space launch campaign and informs decision-makers of the effects of varying numbers of expensive resources and the impact of off nominal scenarios on measures of performance. In order to develop representative DES models, methods were adopted, exploited, or created to extend traditional uses of DES. The Delphi method was adopted and utilized for task duration estimation. DES software was exploited for probabilistic event variation. A roll-up process was used, which was developed to reuse models and model elements in other less - detailed models. The DES team continues to innovate and expand DES capabilities to address KSC's planning needs

Patterns and predictors of smoking by race and medical diagnosis during hospital admission: A latent class analysis

Hospital-based tobacco treatment programs provide tobacco cessation for a diverse array of admitted patients. Person-centered approaches to classifying subgroups of individuals within large datasets are useful for evaluating the characteristics of the sample. This study categorized patients who received tobacco treatment while hospitalized and determined whether demographics and smoking-related health conditions were associated with group membership. Chart review data was obtained from 4854 patients admitted to a large hospital in South Carolina, USA, from July 2014 through December 2019 who completed a tobacco treatment visit. Smoking characteristics obtained from the visit interview were dichotomized, and then latent class analysis (LCA) was conducted to categorize patients based on smoking history and interest in stopping smoking. Finally, logistic regressions were used to evaluate demographics and smoking-related health conditions as predictors of class membership. LCA generated 5 classes of patients, differentiated by heaviness of smoking and motivation to quit. Patients who were black/African American were more likely to be lighter smokers compared to white patients. Hospitalized patients with a history of hypertension, diabetes, and congestive heart failure were more likely to be motivated to quit and also were more likely to be lighter smokers at the time of hospitalization. Hospitalized patients who smoke and receive tobacco treatment are heterogeneous in terms of their smoking histories and motivation to quit. Understanding latent categories of patients provides insight for tailoring interventions and potentially improving tobacco treatment outcomes

Functional Brain Imaging Predicts Public Health Campaign Success

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a ‘self-localizer’ defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400 000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R2 up to 0.65) and (ii) this relationship depends on message content—self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns

Multidisciplinary Applications of Detached-Eddy Simulation to Separated Flows at High Reynolds Numbers

We focus on multidisciplinary applications of detached-eddy simulation (DES), principally flight mechanics and aeroelasticity. Specifically, the lateral instability (known as abrupt wing stall) of the preproduction F/A-18E is reproduced using DES, including the unsteady shock motion. The presence of low frequency pressure oscillations due to shock motion in the current simulations and the experiments motivated a full aircraft calculation, which showed low frequency high-magnitude rolling moments that could be a significant contributor to the abrupt wing stall phenomenon. DES is also applied to the F-18 high angle of attack research vehicle (HARV) at a moderate angle of attack to reproduce the vortex breakdown leading to vertical stabilizer buffet. Unsteady tail loads are compared to flight test data. This work lays the foundation for future deforming grid calculations to reproduce the aero-elastic tail buffet seen in flight test. Solution based grid adaption is used on unstructured grids in both cases to improve the resolution in the separated region. Previous DoD Challenge work has demonstrated the unique ability of the DES turbulence treatment to accurately and efficiently predict flows with massive separation at flight Reynolds numbers. DES calculations have been performed using the Cobalt code and on unstructured grids, an approach that can deal with complete configurations with very few compromises. A broad range of flows has been examined in previous Challenge work, including aircraft forebodies, airfoil sections, a missile afterbody, vortex breakdown on a delta wing, and the F-16 and F-15E at high angles-of-attack. All DES predictions exhibited a moderate to significant improvement over results obtained using traditional Reynolds-averaged models and often excellent agreement with experimental/flight-test data. DES combines the efficiency of a Reynolds-averaged turbulence model near the wall with the fidelity of Large-Eddy Simulation (LES) in separated regions. Since it uses Large-Eddy Simulation in the separated regions, it is capable of predicting the unsteady motions associated with separated flows. The development and demonstration of improved methods for the prediction of flight mechanics and aeroelasticity in this Challenge is expected to reduce the acquisition cost of future military aircraft

Advancements in Carbon Dioxide and Water Vapor Separations Using COMSOL

No abstract availabl

Wet scavenging of soluble gases in DC3 deep convective storms using WRF-Chem simulations and aircraft observations

We examine wet scavenging of soluble trace gases in storms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. We conduct high-resolution simulations with the Weather Research and Forecasting model with Chemistry (WRF-Chem) of a severe storm in Oklahoma. The model represents well the storm location, size, and structure as compared with Next Generation Weather Radar reflectivity, and simulated CO transport is consistent with aircraft observations. Scavenging efficiencies (SEs) between inflow and outflow of soluble species are calculated from aircraft measurements and model simulations. Using a simple wet scavenging scheme, we simulate the SE of each soluble species within the error bars of the observations. The simulated SEs of all species except nitric acid (HNO_3) are highly sensitive to the values specified for the fractions retained in ice when cloud water freezes. To reproduce the observations, we must assume zero ice retention for formaldehyde (CH_2O) and hydrogen peroxide (H_2O_2) and complete retention for methyl hydrogen peroxide (CH_3OOH) and sulfur dioxide (SO_2), likely to compensate for the lack of aqueous chemistry in the model. We then compare scavenging efficiencies among storms that formed in Alabama and northeast Colorado and the Oklahoma storm. Significant differences in SEs are seen among storms and species. More scavenging of HNO_3 and less removal of CH_3OOH are seen in storms with higher maximum flash rates, an indication of more graupel mass. Graupel is associated with mixed-phase scavenging and lightning production of nitrogen oxides (NO_x), processes that may explain the observed differences in HNO_3 and CH_3OOH scavenging