A Comparison of Two Skip Entry Guidance Algorithms

The Orion capsule vehicle will have a Lift-to-Drag ratio (L/D) of 0.3-0.35. For an Apollo-like direct entry into the Earth's atmosphere from a lunar return trajectory, this L/D will give the vehicle a maximum range of about 2500 nm and a maximum crossrange of 216 nm. In order to y longer ranges, the vehicle lift must be used to loft the trajectory such that the aerodynamic forces are decreased. A Skip-Trajectory results if the vehicle leaves the sensible atmosphere and a second entry occurs downrange of the atmospheric exit point. The Orion capsule is required to have landing site access (either on land or in water) inside the Continental United States (CONUS) for lunar returns anytime during the lunar month. This requirement means the vehicle must be capable of flying ranges of at least 5500 nm. For the L/D of the vehicle, this is only possible with the use of a guided Skip-Trajectory. A skip entry guidance algorithm is necessary to achieve this requirement. Two skip entry guidance algorithms have been developed: the Numerical Skip Entry Guidance (NSEG) algorithm was developed at NASA/JSC and PredGuid was developed at Draper Laboratory. A comparison of these two algorithms will be presented in this paper. Each algorithm has been implemented in a high-fidelity, 6 degree-of-freedom simulation called the Advanced NASA Technology Architecture for Exploration Studies (ANTARES). NASA and Draper engineers have completed several monte carlo analyses in order to compare the performance of each algorithm in various stress states. Each algorithm has been tested for entry-to-target ranges to include direct entries and skip entries of varying length. Dispersions have been included on the initial entry interface state, vehicle mass properties, vehicle aerodynamics, atmosphere, and Reaction Control System (RCS). Performance criteria include miss distance to the target, RCS fuel usage, maximum g-loads and heat rates for the first and second entry, total heat load, and control system saturation. The comparison of the performance criteria has led to a down select and guidance merger that will take the best ideas from each algorithm to create one skip entry guidance algorithm for the Orion vehicle

A Norm-Minimization Algorithm for Solving the Cold-Start Problem with XNAV

An algorithm is presented for solving the cold-start problem using observations of X-ray pulsars. Using a norm-minimization-based approach, the algorithm extends Lohan's banded-error intersection model to 3-dimensional space while reducing compute time by an order of magnitude. Higher-fidelity X-ray pulsar signal models, including the parallax effect, Shapiro delay, time dilation, and higher-order pulsar timing models, are considered. The feasibility of solving the cold-start problem using X-ray pulsar navigation is revisited with the improved models and prior knowledge requirements are discussed. Monte Carlo simulations are used to establish upper bounds on uncertainty and determine the accuracy of the algorithm. Results indicate that it is necessary to account for the parallax effect, time dilation, and higher-order pulsar timing models in order to successfully determine the position of the spacecraft in a cold-start scenario. The algorithm can uniquely identify a candidate spacecraft position within a 10 AU $\times$ 10 AU $\times$ 0.01 AU spheroid domain by observing eight to nine pulsars. The median position error of the algorithm is on the order of 15 km. Prior knowledge of spacecraft position is technically required, but only to an accuracy of 100 AU, making it practically unnecessary for navigation within the Solar System. Results further indicate that choosing lower-frequency pulsars increases the maximum domain size but also increases position error.Comment: 20 pages, 15 figures. Conference paper at the AAS/AIAA Astrodynamics Specialist Conference, Charlotte, NC, August 2022. AAS 22-56

Enabling and Enhancing Science Exploration Across the Solar System: Aerocapture Technology for SmallSat to Flagship Missions

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Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Entry System Options for Human Return from the Moon and Mars

2005 AIAA Atmospheric Flight Mechanics Conference August 2005, San Francisco, CA.Earth entry system options for human return missions from the Moon and Mars were analyzed and compared to identify trends among the configurations and trajectory options and to facilitate informed decision making at the exploration architecture level. Entry system options included ballistic, lifting capsule, biconic, and lifting body configurations with direct entry and aerocapture trajectories. For each configuration and trajectory option, the thermal environment, deceleration environment, crossrange and downrange performance, and entry corridor were assessed. In addition, the feasibility of a common vehicle for lunar and Mars return was investigated. The results show that a low lift-to-drag ratio (L/D = 0.3) vehicle provides sufficient performance for both lunar and Mars return missions while providing the following benefits: excellent packaging efficiency, low structural and TPS mass fraction, ease of launch vehicle integration, and system elegance and simplicity. Numerous configuration options exist that achieve this L/D

A Conceptual Design Environment for Technology Selection and Performance Optimization for Torpedoes

Presented at the 9th Multi-Disciplinary Analysis and Optimization Symposium in Atlanta, GA, September 4-6, 2002.The Torpedo Optimization, Analysis, and Design (TOAD) program is introduced as a parametric sizing and synthesis tool for torpedoes. Response surface methodology is introduced as a means for efficiently modeling the design space for torpedoes. Response surface equations are produced from the new thermal analysis section to model the design space for a Stored Chemical Energy Propulsion System (SCEPS) powered torpedo. Comparisons are made between SCEPS and electrically powered torpedoes, as well as between different SCEPS engine parameters. The design methods of the Aerospace Systems Design Laboratory (ASDL) are introduced for developing computationally efficient metamodels for the physics-based analysis codes used in design. Response surface methodology is shown to be an effective way to model a SCEPS powered torpedo

BP Neural Network Improved by Sparrow Search Algorithm in Predicting Debonding Strain of FRP-Strengthened RC Beams

To prevent debonding failure of FRP- (fiber reinforced polymer-) strengthened RC (reinforced concrete) beams, most codes proposed models for debonding strain limitation of FRP reinforcements. However, only a few factors that affect debonding failure are considered in the models. The experimental results show that these models cannot accurately evaluate debonding strain and have a large variability. In order to improve the accuracy of predicting the debonding strain of FRP-strengthened RC beams, a BP neural network model was developed based on the sparrow search algorithm (SSA). To predict the debonding strain of FRP reinforcements, the established neural network model was trained and simulated through experimental data. The results show that the coefficient of variation of the present SSA-BP neural network model is 13%. The main factors affecting debonding strain are the longitudinal reinforcement ratio, stirrup reinforcement ratio, and concrete strength, which are not considered in the code models. The present model has better prediction accuracy and more robustness than the traditional BP neural network and the code models

Improving Lunar Return Entry Footprints Using Enhanced Skip Trajectory Guidance

AIAA Space 2006 Conference September 2006, San Jose, CA.The impending development of NASA's Crew Exploration Vehicle (CEV) will require a new entry guidance algorithm that provides sufficient performance to meet all requirements. This study examined the effects on entry footprints of enhancing the skip trajectory entry guidance used in the Apollo program. The skip trajectory entry guidance was modified to include a numerical predictor-corrector phase during atmospheric skip portion of the entry trajectory. Four degree-of-freedom simulation was used to determine the footprint of the entry vehicle for the baseline Apollo entry guidance and predictor-corrector enhanced guidance with both high and low lofting at several lunar return entry conditions. The results show that the predictor-corrector guidance modification significantly improves the entry footprint of the CEV for the lunar return mission. The performance provided by the enhanced algorithm is likely to meet the entry range requirements for the CEV