4,938 research outputs found

    NGC 1058: Gas motions in an extended, quiescent spiral disk

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    Researchers investigate in detail the motion of gas in the galaxy NGC 1058 using the very large array (VLA) to map the emission in the 21-cm line. This galaxy is so nearly face-on that the contribution to the line width due to the variation of the rotational velocity across the D-array beam is small compared with the random z-motion of the gas. Researchers confirm results of earlier studies (Lewis 1987, A. and A. Suppl., 63, 515; van der Kruit and Shostak 1984, A. and A., 134, 258) of the galaxy's total neutral hydrogen (HI) and kinematics, including the fact that the rotation curve drops faster than Keplerian at the outer edge of the disk, which is interpreted as a fortuitous twist of the plane of rotation in the outer disk. However, their very high velocity resolution (2.58 km s(exp -1) after Hanning smoothing) coupled with good spatial resolution, allows researchers to measure more accurately the line width, and even to some extent its shape, throughout the disk. One of the most interesting results of this study is the remarkable constancy of the line width in the outer disk. From radius 90 to 210 seconds the Gaussian velocity dispersion (sigma sub nu) of the 21-cm line has a mean value of 5.7 km s(exp -1) (after correcting for the spectral resolution) with a dispersion of less than 0.9 km s(exp -1) (after correcting for the spectral resolution) with a dispersion of less than 0.9 km s(exp -1). Translating this directly into a kinetic temperature (Doppler temperature): T sub Dopp equals 121K (sigma sub mu exp 2/(km s(exp -1) (exp 2) gives 4000 K, with a dispersion of less than 1500 K over the outer disk. This constancy is observed even when comparing the spiral arms versus inter-arm regions, which in the radius range from 100 to 150 seconds the surface density modulates (defined as the ratio N sub peak -N sub trough/N sub peak + N sub trough) from 0.5 to 0.25 in the range 150 to 200 seconds

    Learning About Ares I from Monte Carlo Simulation

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    This paper addresses Monte Carlo simulation analyses that are being conducted to understand the behavior of the Ares I launch vehicle, and to assist with its design. After describing the simulation and modeling of Ares I, the paper addresses the process used to determine what simulations are necessary, and the parameters that are varied in order to understand how the Ares I vehicle will behave in flight. Outputs of these simulations furnish a significant group of design customers with data needed for the development of Ares I and of the Orion spacecraft that will ride atop Ares I. After listing the customers, examples of many of the outputs are described. Products discussed in this paper include those that support structural loads analysis, aerothermal analysis, flight control design, failure/abort analysis, determination of flight performance reserve, examination of orbit insertion accuracy, determination of the Upper Stage impact footprint, analysis of stage separation, analysis of launch probability, analysis of first stage recovery, thrust vector control and reaction control system design, liftoff drift analysis, communications analysis, umbilical release, acoustics, and design of jettison systems

    Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Verification

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    This paper is focused on applying Monte Carlo simulation to probabilistic launch vehicle design and requirements verification. The approaches developed in this paper can be applied to other complex design efforts as well. Typically the verification must show that requirement "x" is met for at least "y" % of cases, with, say, 10% consumer risk or 90% confidence. Two particular aspects of making these runs for requirements verification will be explored in this paper. First, there are several types of uncertainties that should be handled in different ways, depending on when they become known (or not). The paper describes how to handle different types of uncertainties and how to develop vehicle models that can be used to examine their characteristics. This includes items that are not known exactly during the design phase but that will be known for each assembled vehicle (can be used to determine the payload capability and overall behavior of that vehicle), other items that become known before or on flight day (can be used for flight day trajectory design and go/no go decision), and items that remain unknown on flight day. Second, this paper explains a method (order statistics) for determining whether certain probabilistic requirements are met or not and enables the user to determine how many Monte Carlo samples are required. Order statistics is not new, but may not be known in general to the GN&C community. The methods also apply to determining the design values of parameters of interest in driving the vehicle design. The paper briefly discusses when it is desirable to fit a distribution to the experimental Monte Carlo results rather than using order statistics

    Distinct Sums Over Subsets

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    Calculating Launch Vehicle Flight Performance Reserve

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    This paper addresses different methods for determining the amount of extra propellant (flight performance reserve or FPR) that is necessary to reach orbit with a high probability of success. One approach involves assuming that the various influential parameters are independent and that the result behaves as a Gaussian. Alternatively, probabilistic models may be used to determine the vehicle and environmental models that will be available (estimated) for a launch day go/no go decision. High-fidelity closed-loop Monte Carlo simulation determines the amount of propellant used with each random combination of parameters that are still unknown at the time of launch. Using the results of the Monte Carlo simulation, several methods were used to calculate the FPR. The final chosen solution involves determining distributions for the pertinent outputs and running a separate Monte Carlo simulation to obtain a best estimate of the required FPR. This result differs from the result obtained using the other methods sufficiently that the higher fidelity is warranted

    Development of a Smooth Trajectory Maneuver Method to Accommodate the Ares I Flight Control Constraints

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    Six degree-of-freedom (DOF) launch vehicle trajectories are designed to follow an optimized 3-DOF reference trajectory. A vehicle has a finite amount of control power that it can allocate to performing maneuvers. Therefore, the 3-DOF trajectory must be designed to refrain from using 100% of the allowable control capability to perform maneuvers, saving control power for handling off-nominal conditions, wind gusts and other perturbations. During the Ares I trajectory analysis, two maneuvers were found to be hard for the control system to implement; a roll maneuver prior to the gravity turn and an angle of attack maneuver immediately after the J-2X engine start-up. It was decided to develop an approach for creating smooth maneuvers in the optimized reference trajectories that accounts for the thrust available from the engines. A feature of this method is that no additional angular velocity in the direction of the maneuver has been added to the vehicle after the maneuver completion. This paper discusses the equations behind these new maneuvers and their implementation into the Ares I trajectory design cycle. Also discussed is a possible extension to adjusting closed-loop guidance

    Exploring Agricultural Production Systems and Their Fundamental Components with System Dynamics Modelling

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    Agricultural production in the United States is undergoing marked changes due to rapid shifts in consumer demands, input costs, and concerns for food safety and environmental impact. Agricultural production systems are comprised of multidimensional components and drivers that interact in complex ways to influence production sustainability. In a mixed-methods approach, we combine qualitative and quantitative data to develop and simulate a system dynamics model that explores the systemic interaction of these drivers on the economic, environmental and social sustainability of agricultural production. We then use this model to evaluate the role of each driver in determining the differences in sustainability between three distinct production systems: crops only, livestock only, and an integrated crops and livestock system. The result from these modelling efforts found that the greatest potential for sustainability existed with the crops only production system. While this study presents a stand-alone contribution to sector knowledge and practice, it encourages future research in this sector that employs similar systems-based methods to enable more sustainable practices and policies within agricultural production

    Launch Vehicle Failure Dynamics and Abort Triggering Analysis

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    Launch vehicle ascent is a time of high risk for an on-board crew. There are many types of failures that can kill the crew if the crew is still on-board when the failure becomes catastrophic. For some failure scenarios, there is plenty of time for the crew to be warned and to depart, whereas in some there is insufficient time for the crew to escape. There is a large fraction of possible failures for which time is of the essence and a successful abort is possible if the detection and action happens quickly enough. This paper focuses on abort determination based primarily on data already available from the GN&C system. This work is the result of failure analysis efforts performed during the Ares I launch vehicle development program. Derivation of attitude and attitude rate abort triggers to ensure that abort occurs as quickly as possible when needed, but that false positives are avoided, forms a major portion of the paper. Some of the potential failure modes requiring use of these triggers are described, along with analysis used to determine the success rate of getting the crew off prior to vehicle demise

    Explicit guidance of drag modulated aeroassisted transfer between elliptical orbits

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77220/1/AIAA-1984-1848-977.pd
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