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At least 451 records · Page 25

Data-Driven Anomaly Detection Performance for the Ares I-X Ground Diagnostic Prototype

In this paper, we will assess the performance of a data-driven anomaly detection algorithm, the Inductive Monitoring System (IMS), which can be used to detect simulated Thrust Vector Control (TVC) system failures. However, the ability of IMS to detect these failures in a true operational setting may be related to the realistic nature of how they are simulated. As such, we will investigate both a low fidelity and high fidelity approach to simulating such failures, with the latter based upon the underlying physics. Furthermore, the ability of IMS to detect anomalies that were previously unknown and not previously simulated will be studied in earnest, as well as apparent deficiencies or misapplications that result from using the data-driven paradigm. Our conclusions indicate that robust detection performance of simulated failures using IMS is not appreciably affected by the use of a high fidelity simulation. However, we have found that the inclusion of a data-driven algorithm such as IMS into a suite of deployable health management technologies does add significant value.

Martin, Rodney A.↗

Ares I-X Range Safety Trajectory Analyses Overview and Independent Validation and Verification

All Flight Analysis data products were successfully generated and delivered to the 45SW in time to support the launch. The IV&V effort allowed data generators to work through issues early. Data consistency proved through the IV&V process provided confidence that the delivered data was of high quality. Flight plan approval was granted for the launch. The test flight was successful and had no safety related issues. The flight occurred within the predicted flight envelopes. Post flight reconstruction results verified the simulations accurately predicted the FTV trajectory.

Tarpley, Ashley F.↗

Lift-Off Acoustics Predictions for the Ares I Launch Pad

The vibroacoustic environment associated with large launch vehicles is of concern for the integrity of the launch complex and the vehicle itself. A large body of knowledge of this environment was developed during the early years of the missile and space flight, particularly during the Apollo program. Reference 1, prepared by Sutherland and others during that era, contains much of that knowledge. A specific process for predicting noise on and around the vehicle itself and the launcher is presented in Reference 2, prepared by Eldred, et al. Recent reviews of the process, e.g., Reference 3, have suggested some revised details but generally support the methodology in Reference 2.

Launch Pad↗

Ares Upper Stage Processes to Implement Model Based Design - Going Paperless

Computer-Aided Design (CAD) has all but replaced the drafting board for design work. Increased productivity and accuracy should be natural outcomes of using CAD. Going from paper drawings only to paper drawings based on CAD models to CAD models and no drawings, or Model Based Design (MBD), is a natural progression in today?s world. There are many advantages to MBD over traditional design methods. To make the most of those advantages, standards should be in place and the proper foundation should be laid prior to transitioning to MBD. However, without a full understanding of the implications of MBD and the proper control of the data, the advantages are greatly diminished. Transitioning from a paper design world to an electronic design world means re-thinking how information gets controlled at its origin and distributed from one point to another. It means design methodology is critical, especially for large projects. It means preparation of standardized parts and processes as well as strong communication between all parties in order to maximize the benefits of MBD.

Gregory, Melanie↗

Uncertainty Due to Unsteady Fluid/Structure Interaction for the Ares I Vehicle Traversing the Transonic Regime

Rapid reduced-order numerical models are being investigated as candidates to simulate the dynamics of a flexible launch vehicle during atmospheric ascent. There has also been the extension of these new approaches to include gust response. These methods are used to perform aeroelastic and gust response analyses at isolated Mach numbers. Such models require a method to time march through a succession of ascent Mach numbers. An approach is presented for interpolating reduced-order models of the unsteady aerodynamics at successive Mach numbers. The transonic Mach number range is considered here since launch vehicles can suffer the highest dynamic loads through this range. Realistic simulations of the flexible vehicle behavior as it traverses this Mach number range are presented. The response of the vehicle due to gusts is computed. Uncertainties in root mean square and maximum bending moment and crew module accelerations are presented due to assumed probability distributions in design parameters, ascent flight conditions, gusts. The primary focus is on the uncertainty introduced by modeling fidelity. It is found that an unsteady reduced order model produces larger excursions in the root mean square loading and accelerations than does a quasi-steady reduced order model.

Bartels, Robert E.↗