Propellant Mass Fraction Calculation Methodology for Launch Vehicles and Application to Ares Vehicles

Propellant Mass Fraction (pmf) calculation methods vary throughout the aerospace industry. While typically used as a means of comparison between candidate launch vehicle designs, the actual pmf calculation method varies slightly from one entity to another. It is the purpose of this paper to present various methods used to calculate the pmf of launch vehicles. This includes fundamental methods of pmf calculation that consider only the total propellant mass and the dry mass of the vehicle; more involved methods that consider the residuals, reserves and any other unusable propellant remaining in the vehicle; and calculations excluding large mass quantities such as the installed engine mass. Finally, a historical comparison is made between launch vehicles on the basis of the differing calculation methodologies, while the unique mission and design requirements of the Ares V Earth Departure Stage (EDS) are examined in terms of impact to pmf

Modeling spatial accessibility to parks: a national study

<p>Abstract</p> <p>Background</p> <p>Parks provide ideal open spaces for leisure-time physical activity and important venues to promote physical activity. The spatial configuration of parks, the number of parks and their spatial distribution across neighborhood areas or local regions, represents the basic park access potential for their residential populations. A new measure of spatial access to parks, population-weighted distance (PWD) to parks, combines the advantages of current park access approaches and incorporates the information processing theory and probability access surface model to more accurately quantify residential population's potential spatial access to parks.</p> <p>Results</p> <p>The PWD was constructed at the basic level of US census geography - blocks - using US park and population data. This new measure of population park accessibility was aggregated to census tract, county, state and national levels. On average, US residential populations are expected to travel 6.7 miles to access their local neighborhood parks. There are significant differences in the PWD to local parks among states. The District of Columbia and Connecticut have the best access to local neighborhood parks with PWD of 0.6 miles and 1.8 miles, respectively. Alaska, Montana, and Wyoming have the largest PWDs of 62.0, 37.4, and 32.8 miles, respectively. Rural states in the western and Midwestern US have lower neighborhood park access, while urban states have relatively higher park access.</p> <p>Conclusions</p> <p>The PWD to parks provides a consistent platform for evaluating spatial equity of park access and linking with population health outcomes. It could be an informative evaluation tool for health professionals and policy makers. This new method could be applied to quantify geographic accessibility of other types of services or destinations, such as food, alcohol, and tobacco outlets.</p

The Effects of Fish Trap Mesh Size on Reef Fish Catch off Southeastern Florida

Catch and mesh selectivity of wire-meshed fish traps were tested for eleven different mesh sizes ranging from 13 X 13 mm (0.5 x 0.5") to 76 x 152 mm (3 X 6"). A total of 1,810 fish (757 kg) representing 85 species and 28 families were captured during 330 trap hauls off southeastern Florida from December 1986 to July 1988. Mesh size significantly affected catches. The 1.5" hexagonal mesh caught the most fish by number, weight, and value. Catches tended to decline as meshes got smaller or larger. Individual fish size increased with larger meshes. Laboratory mesh retention experiments showed relationships between mesh shape and size and individual retention for snapper (Lutjanidae), grouper (Serranidae), jack (Carangidae), porgy (Sparidae), and surgeonfish (Acanthuridae). These relationships may be used to predict the effect of mesh sizes on catch rates. Because mesh size and shape greatly influenced catchability, regulating mesh size may provide a useful basis for managing the commercial trap fishery

Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult -- in both cost and schedule -- to enact. Indeed, the current capability-based paradigm that has emerged because of the constrained economic environment calls for the infusion of knowledge acquired during later design phases into earlier design phases, i.e. bring knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture as the need for more economically viable access to space solutions are needed in today's constrained economic environment. The problem of ascent trajectory optimization is not a new one. There are several programs that are widely used in industry that allows trajectory analysts to, based on detailed vehicle and insertion orbit parameters, determine the optimal ascent trajectory. Yet, little information is known about the launch vehicle early in the design phase - information that is required of many different disciplines in order to successfully optimize the ascent trajectory. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. Additionally, when these obstacles are coupled with The Program to Optimize Simulated Trajectories [1] (POST), an industry standard program to optimize ascent trajectories that is difficult to use, it requires expert trajectory analysts to effectively optimize a vehicle's ascent trajectory. As it has been pointed out, the paradigm of trajectory optimization is still a very manual one because using modern computational resources on POST is still a challenging problem. The nuances and difficulties involved in correctly utilizing, and therefore automating, the program presents a large problem. In order to address these issues, the authors will discuss a methodology that has been developed. The methodology is two-fold: first, a set of heuristics will be introduced and discussed that were captured while working with expert analysts to replicate the current state-of-the-art; secondly, leveraging the power of modern computing to evaluate multiple trajectories simultaneously, and therefore, enable the exploration of the trajectory's design space early during the pre-conceptual and conceptual phases of design. When this methodology is coupled with design of experiments in order to train surrogate models, the authors were able to visualize the trajectory design space, enabling parametric optimal ascent trajectory information to be introduced with other pre-conceptual and conceptual design tools. The potential impact of this methodology's success would be a fully automated POST evaluation suite for the purpose of conceptual and preliminary design trade studies. This will enable engineers to characterize the ascent trajectory's sensitivity to design changes in an arbitrary number of dimensions and for finding settings for trajectory specific variables, which result in optimal performance for a "dialed-in" launch vehicle design. The effort described in this paper was developed for the Advanced Concepts Office [2] at NASA Marshall Space Flight Cente

Estimating Population Exposure to Fine Particulate Matter in the Conterminous U.S. Using Shape Function-Based Spatiotemporal Interpolation Method: A County Level Analysis

This paper investigates spatiotemporal interpolation methods for the application of air pollution assessment. The air pollutant of interest in this paper is fine particulate matter PM2.5. The choice of the time scale is investigated when applying the shape function-based method. It is found that the measurement scale of the time dimension has an impact on the quality of interpolation results. Based upon the result of 10-fold cross validation, the most effective time scale out of four experimental ones was selected for the PM2.5 interpolation. The paper also estimates the population exposure to the ambient air pollution of PM2.5 at the county-level in the contiguous U.S. in 2009. The interpolated county-level PM2.5 has been linked to 2009 population data and the population with a risky PM2.5 exposure has been estimated. The risky PM2.5 exposure means the PM2.5 concentration exceeding the National Ambient Air Quality Standards. The geographic distribution of the counties with a risky PM2.5 exposure is visualized. This work is essential to understanding the associations between ambient air pollution exposure and population health outcomes

Estimating Population Exposure to Fine Particulate Matter in the Conterminous U.S. using Shape Function-based Spatiotemporal Interpolation Method

This paper investigates spatiotemporal interpolation methods for the application of air pollution assessment. The air pollutant of interest in this paper is fine particulate matter PM2.5. The choice of the time scale is investigated when applying the shape function-based method. It is found that the measurement scale of the time dimension has an impact on the quality of interpolation results. Based upon the result of 10-fold cross validation, the most effective time scale out of four experimental ones was selected for the PM2.5 interpolation. The paper also estimates the population exposure to the ambient air pollution of PM2.5 at the county-level in the contiguous U.S. in 2009. The interpolated county-level PM2.5 has been linked to 2009 population data and the population with a risky PM2.5 exposure has been estimated. The risky PM2.5 exposure means the PM2.5 concentration exceeding the National Ambient Air Quality Standards. The geographic distribution of the counties with a risky PM2.5 exposure is visualized. This work is essential to understanding the associations between ambient air pollution exposure and population health outcomes

Heavy Lift Launch Capability with a New Hydrocarbon Engine

The Advanced Concepts Office at NASA's George C. Marshall Space Flight Center was tasked to define the thrust requirement of a new liquid oxygen rich staged combustion cycle hydrocarbon engine that could be utilized in a launch vehicle to meet NASA s future heavy lift needs. Launch vehicle concepts were sized using this engine for different heavy lift payload classes. Engine out capabilities for one of the heavy lift configurations were also analyzed for increased reliability that may be desired for high value payloads or crewed missions. The applicability for this engine in vehicle concepts to meet military and commercial class payloads comparable to current ELV capability was also evaluated