Browse Topic: Quality, Reliability, and Durability
This digital standard is a requirements extract of AS13100A Quality Management System Requirements for Aero Engine Design and Production Organizations. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
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Gearbox casing cracks in helicopters would be critical impacting the aircraft's reliability and operation safety directly. The Defense Science and Technology Group (DSTG) HUMS2025 gearbox casing failure data set was the unexpected result of a test stand operation. The gearbox undergoes high cycle (> 400 acquisitions) under high torque (100% and 125% nominal torque) conditions. We hypothesized that the any cracking would be due to the planet/ring gear interaction. A condition indicator (CI) would be sensitive to a crack feature and this would be sensitive to change in gearbox torque. This paper explores the development of both a cyclo-stationary based CI (frequency-domain) and a time synchronous average CI (time-domain). The trend shows that proposed methods can help to detect localized defects in gearbox casing at an early stage and trend as the crack propagates before catastrophic failure occurs.
The work performed for the Adaptive Resilient Engineered Structures (ARES) program sponsored by the U.S. Army constitutes a trade study and resulting proposal for a structural demonstrator platform. The trade study was conducted using the Quality Function Deployment (QFD) process and a subsequent Artificial Intelligence (AI) exercise to find clusters of technologies for structural efficiency and resilience from Boeing's internal research activities. From a selection of approximately 150 technologies at different TRLs, Boeing subject matter experts (SMEs) for structural technologies identified several characteristics that could potentially determine the development of ARES structural demonstrator. Through the QFD process, the list of technologies was down selected about 50 unique technologies for consideration. The next stage of the QFD process entailed in identifying 37 different attributes or criteria long which each of these technologies would be assessed. They were grouped under two different categories: vehicle performance criteria and program performance criteria. Importance scores were provided by the SMEs independently and then a statistical approach for AI was used to distill them to 9 significant ones (labeled as 'Pillars') and a further distillation to 3 significant features (labeled as 'Super Metrics'). Clustering algorithms were then employed to group the set of technologies that could provide the resiliency targets sought for the demonstrator platform. The clusters were compared a hypothetical ideal platform to determine suitability and finally, 12 technologies merited attention toward the stated goals of the demonstrator platform.
In this work, a vision-based solution is developed to address the challenge of landing on a ship deck with precision and accuracy. For an autonomous landing, it is important to have a fast and accurate pose estimation system along with a reliable control strategy. This research uses fractal ArUCo markers instead of multiple separate markers to allow smooth pose estimation at different heights. Pose estimates are further improved using an Extended Kalman Filter, and a tracking algorithm then uses these estimates to guide the landing. A four degree-of-freedom (roll, pitch, heave and sway) simulator platform was built and used to validate the algorithm. The accuracy of the vision system is compared against that of a motion capture system. Real-world experiments were performed on different quadrotors to demonstrate tracking and landing on the platform with sway, roll, and pitch motions. The results show that the system is efficient and reliable in achieving safe and successful landings. The proposed landing system is concluded to be applicable for landings on the deck of the ship under sea-state 4.
Low-level flight, defined by high-speed operations near terrain, represents a significant challenge in military rotorcraft missions while providing strategic advantages, such as radar evasion and heightened surprise. Recent conflicts highlight the urgent need for advanced low-level flight capabilities in the design of new rotorcraft. The close proximity to ground obstacles, combined with the complexities of piloting, necessitates precise control and robust handling qualities to prevent accidents. However, existing handling quality standards, such as MIL-DTL-32742, reveal limitations in assessing low-level maneuvers. Given the diverse array of new rotorcraft designs, driven by initiatives like the U.S. Army's Future Vertical Lift and NATO's Next Generation Rotorcraft Capabilities, a customized handling qualities evaluation for each design is impractical. In response, a performance-driven strategy has been implemented, scaling Mission Task Elements to align with aircraft performance capabilities. This approach identifies handling quality gaps across the Operational Flight Envelope, concentrating on the aircraft’s effectiveness in achieving task success under varied conditions. Prior simulator studies validate the effectiveness of this method for assessing different configurations. This paper presents flight test results using DLR's ACT/FHS research helicopter, confirming a set of scalable Mission Task Elements developed at DLR's AVES and NASA's VMS simulators. Pilots utilized a Head-Mounted Display for task cueing, eliminating the need for physical infrastructure. The Mission Task Elements proved suitable for evaluating the low-level handling qualities of the ACT/FHS. Although the provided Head-Mounted Display facilitated Handling Qualities evaluations, it encountered some hardware limitations. The scaling for different airspeeds met pilot expectations, and wind compensation functioned as anticipated, enhancing the independence of flight tests from environmental conditions. These findings lead to recommended updates for task descriptions and course cueing requirements, confirming desired performance tolerances.
This standard establishes supplemental requirements for 9100 and 9145 and applies to any organization receiving it as part of a Purchase Order or other contractual document from a customer. AS13100 also provides details of the Reference Materials (RM13xxx) developed by the SAE G-22 AESQ committee and listed in Section 2 - Applicable Documents, that can also be used by organizations in conjunction with this standard.
Rotorcraft dynamic component fatigue lives and corresponding reliability have long been derived from three major contributors: material strength, loads, and usage. This paper provides a historical perspective of the contribution of aircraft usage to overall U.S. Army rotorcraft dynamic component reliability. A quick background of how we got to a six-nines reliability requirement is first provided. Different types of usage spectra and the nuances and trade-offs of two specific usage gathering methods, pilot surveys and usage monitoring, are discussed. Finally, I describe where usage spectrum fits into fatigue life calculations and the existing reliability policy and requirements. Each OEM (e.g., Bell Helicopter, Boeing, Sikorsky) has been free to develop their own fatigue methods over the years. These differences in method can lead to vastly different results, even with the same input parameters as evidenced by a now well-known round robin problem. There is notable variability between OEM methodologies, each with viable solutions to this trivariate problem. In the interest of normalizing independent U.S. Government (USG) assessments across multiple OEM paradigms, the Army is investigating a USG method to assess the reliability contribution from usage. No new methods are presented herein, only findings of previous work. Uncited opinions herein are those of the author based on literature review, peer discussions, and experience with U.S. Army and U.S. Air Force (USAF) airworthiness processes. Reliability values in this paper are approximate, as there are elements of statistical distribution and non-statistical estimation that contribute.
Wear debris monitoring and analysis is a common practice for the condition assessment of engine and transmission health. Oil debris monitoring (ODM) and electronic chip detectors (ECD) are two common methods deployed for continuous monitoring of oil wetted component health in-flight. This study evaluates the diagnostic performance of the two sensing technologies within controlled rolling element bearing (REB) fault experiments. Progressive visual inspection of the REB spall progression through failure provided a ground truth against which both systems could be compared. Quantifiable metrics of reliability, diagnostic accuracy, provided maintenance interval were defined to create a framework for condition-based maintenance (CBM) program decision making. In summary, it was found that the ODM sensor system provided earlier fault notice, but more so, vastly outperformed the ECD in reliability and avoidance of false positives.
A framework for statistical comparison between analytical and experimental structural loads has been developed and applied to approximately 100 counters within the UH-60A Airloads test program. This framework relies on established structural load variability methods with novel applications to analytical structural load development maneuver time transient analysis. The analytical results are from Rotorcraft Comprehensive Analysis System (RCAS) spanwise structural loads developed with hub load and spanwise aerodynamic loads prescribed. RCAS consistently under predicted the Coefficient of Variation (COV) associated with spanwise Normal bending when compared to flight data. This resulted in significant scale factors required to achieve a μ+2σ reliability for structural load development. RCAS results for Edgewise bending scale factors proved slightly better than Normal bending in addition to more even over / under prediction of COV when compared to flight data.
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