Browse Topic: Quality, Reliability, and Durability

Items (10,183)
Vehicle vibrations during precision instrument transport can cause damage and failure. Existing vibration isolators often lack reliability, mass production feasibility, and easy maintenance. In this paper, we design and analyze a quasi-zero-stiffness vehicle-mounted isolator with an inerter, decreasing dynamic stiffness while raising the effective mass. Theoretical, simulation, and experimental results show improved isolation performance, lower isolation frequency, and a broader isolation bandwidth.
Li, KaiLv, SiboSun, NingDai, Shijie
The magnetic field modeling methodology for ships based on magnetic dipole arrays demonstrates heightened sensitivity to input data. When addressing overdetermined systems characterized by numerous variables and constrained measurement points, the coefficient matrix frequently develops pathological ill-conditioning, leading to solution divergence and compromised result accuracy. This research reformulates the ship magnetic field inversion challenge as a non-convex quadratic programming problem, employing the Successive Convex Approximation (SCA) algorithm as the computational solver. Rigorous comparative validation was performed against conventional stepwise regression algorithms and experimental datasets acquired from scaled ship model measurements. Results substantiate that while the modeling precision of the SCA algorithm remains comparable to that achieved by stepwise regression methods, SCA exhibits demonstrably superior solution stability. This enhanced robustness positions SCA
Chen, HaoPan, Xun
The reliability of aviation maintenance personnel directly impacts flight safety, yet systematic methodologies for the quantitative prediction of human error probability (HEP) in this domain remain lacking. To address this gap, a novel human factors reliability analysis method for aviation maintenance is proposed, extending the SPAR-H model through Evidential Reasoning (ER). This method is implemented as follows: Maintenance tasks are decomposed into subtasks. Subsequently, the eight types of Performance Shaping Factors (PSFs) for each subtask are evaluated by domain experts according to defined PSF levels. Expert judgments are then aggregated using Evidential Reasoning theory, enabling the calculation of aggregated PSF levels. These aggregated levels are interpolated to determine the corresponding impact multipliers. Finally, the HEP for aviation maintenance operations is calculated by integrating the SPAR-H basic error probability model with task series/parallel logic rules. The
Meng, MengMa, NingGuan, ZhongqingHan, ZuyangNan, WenxueCai, Hongbin
Aiming at the problem of insufficient modeling of spatio-temporal heterogeneity in road traffic accident prediction, a dual task machine learning framework integrating geographical environment, location attributes and time periodicity is proposed. The dataset used in this study was derived from traffic accident records of Nanchang during 2019–2023. Firstly, geographical identifiers are generated by rounding and aggregating latitude and longitude coordinates. At the same time, the location type is processed by a one-hot encoding, so as to carry out spatial clustering analysis of accident hotspots. Compared with the North-South pattern, the contribution of geographical features shows a strong East-West trend. The kernel density heatmap identified Zone A and zone B as dual core high-risk areas. Secondly, the sinusoidal/cosine function is used to encode the time feature circularly, which effectively captures the daily change of the accident. The quantitative analysis of random forest
Luo, JiangZhang, YuxinLi, XinWu, Ronghai
The gearbox is a key component of the mechanical transmission system, and its fault diagnosis is essential to the reliability of the equipment. However, obtaining fault samples under actual working conditions for gearbox fault diagnosis is challenging. In this paper, the rigid-flexible coupling dynamic simulation model of the gearbox is established, and the co-simulation of gear normal, crack, and breakage is carried out in the ADAMS and MATLAB environments. The comparison between the simulated and measured signals shows that the simulation method can accurately reflect the key characteristics, such as rotation frequency and meshing frequency, and verify its reliability and accuracy. The research results can provide effective data support for gearbox fault diagnosis and improve the operational safety of mechanical systems.
Li, DongxiaoZhang, QianqiZhang, ZhongzhengLi, Yongbo
In vehicle production, commissioning and testing processes of electric and electronic components are essential for value creation and quality assurance. The emergence of software-defined vehicles, however, leads to an increased scope and complexity of these processes as software functions depend on electric and electronic components for perception, execution, and processing tasks. In this context, this paper tackles a common challenge: Software that is deployed in vehicle production to implement commissioning and testing processes is developed upon specifications that define prerequisites, procedures, and target results in natural language. Therefore, extensive human interpretation and manual translation into executable code are needed being susceptible to errors as well as time-consuming. The large number of vehicle configurations and rapid changes in vehicle software further complicate the development of commissioning and testing software, particularly as verbose textual dependency
Köhler, KatjaEl Asad, AimanHahn, MichaelReuss, Hans-Christian
Stochastic preignition (SPI) or low-speed preignition (LSPI) is an abnormal combustion phenomenon observed in downsized turbocharged direct-injection spark-ignition engines at highly boosted conditions. SPI results from the ignition of the air-fuel mixture from a fuel or oil droplet or a detached deposit before the spark discharge, and its occurrence can lead to extremely high peak pressures and severe knock, which can cause physical damage to the engine. This phenomenon limits the downsizing and boosting potential of direct-injection spark-ignition engines, thereby constraining the efficiency benefits that can be achieved. The propensity for SPI to occur is impacted by engine operating conditions as well as the properties of the fuel, fuel additives, lubricant, and lubricant additives. To mitigate its occurrence, it is important to understand the factors that impact the frequency of SPI events. As this abnormal combustion phenomenon is relatively recent, there was a lack of a standard
Gopujkar, SiddharthDavis, RichardWorm, JeremyTuma, NicShukla, PrajwalReilly, VeronicaChapman, ElanaCiaravino, JosephSeyfried, Philipp
In recent years, the automotive industry has actively explored the application of various AI-based models such as Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, Autoencoders, and Transformers to improve defect detection rates at the End-of-Line (EOL) stage. However, implementing these approaches in the Noise, Vibration, and Harshness (NVH) area face several practical challenges: ① extended evaluation times compared to other data types, which limit the quantity of training data and lead to overfitting; ② label imbalance caused by the relatively small amount of defect data; ③ reduced labeling accuracy due to human error; ④ decreased robustness under domain shifts such as changes in jig fixtures, test environments, and signal-to-noise ratio (SNR); ⑤ diminished model reliability when new defect arise during development; and ⑥ constraints imposed by compatibility requirements with existing test equipment. This study proposes a Convolutional Autoencoder (CAE
Park, Jun-SeoJo, Hyeon-ChoelCho, In-JeSeo, Jae-YongYoo, Seong-Sik
Achieving best-in-class Noise, Vibration, and Harshness (NVH) in electric powertrains demands a paradigm shift in development methodology. This paper presents a practice-oriented overview of simulation methods in NVH development methodology for electric drive units. This includes target cascading and multi-objective optimisation, and by attacking NVH at the source using KPIs early in the design cycle, significant reductions in development time and reliance on traditional testbed loops are realised. Machine learning (Neural Network) algorithms are utilized to find the best-in-class design, using multi-objective optimisation as well as refining simulation accuracy by adding tolerance effects while target cascading ensures alignment of system-level performance objectives down to subsystem contributions. Combined, these strategies enable rapid and robust NVH optimisation, using simulation for next-generation electric powertrain development. Several applications and real-life examples
Mehrgou, MehdiGarcia de Madinabeitia, InigoGraf, BernhardGojo, Josef
This work presents a modular engineering methodology (DiPhyBa - Digital Physical Balance) for the virtual validation of Noise, Vibration, and Harshness (NVH) performance in automotive development. The approach addresses the inefficiency of repeated physical testing across vehicle variants by introducing a structured two-phase process—Launcher and Reskin—centered on quantitative performance indicators with formal acceptance thresholds. In the Launcher phase, a digital replica of the base vehicle is built and iteratively correlated with physical test data. Validation is governed by objective indicators of confidence, conformity, and correlation, each evaluated against predefined thresholds. Once validated, the model becomes a certified reference, enabling its reuse across derivative configurations in the Reskin phase. Physical testing is only required if indicators fall below threshold, with a final gate test on pre-series vehicles ensuring industrial robustness. DiPhyBa formalizes the
Celiberti, LuciaCamia, Andrea
The virtual development of Electric Drive Modules (EDMs) for Battery Electric Vehicles (BEVs) requires proven and predictive methodologies. One part of the development investigates the vibro-acoustic assessment for the low- and high-frequency ranges within the targeted operating range. The efficient use of such a methodology requires an understanding of the accuracy and validity of the achievable results, as well as the derivation of suitable improvement measures for goals that have not been achieved. The use of reference data from experimental investigations and a detailed root cause analysis (RCA), to directly link a specific response and behavior to the excitations, modal content, and transfer functions, is an essential and non-trivial part of the methodology development. This paper describes the development of such a methodology using the example of a new EDM virtual model for Noise, Vibration and Harshness (NVH) analysis, including the simulation approach, validation, and
Klarin, BorislavPevec, DenisResch, ThomasEsposito, SaraD'Alessandro, VincenzoSpanu, Giorgio
To minimize noise caused by interior components rubbing against each other, automotive materials are usually tested in advance with the established stick-slip method according to VDA standard 230-206. This procedure is widely used for soft materials, upholstery and plastics. However, it is limited to constant climatic and selected loading conditions. Contrary, in real application, changing climates and dynamic excitations can nevertheless trigger noise issues even in materials rated as suitable in the prior tests. To address this gap, a new test method has been developed that evaluates the stick-slip behavior of material combinations for a wide range of loading and climatic conditions. Conducted in a climate chamber with a standard stick-slip test bench, the procedure applies sinusoidal excitations, dynamic climatic shifts and advanced data analysis. In addition to the usual results the new method also evaluates realistic scenarios such as starting a vehicle in different seasons or
Fritz, SusanneStrangfeld, Martin
Noise, Vibration, and Harshness (NVH) performance is critical in the automotive development process, yet identifying the true root causes of unwanted dynamic behavior remains a challenge in full vehicle or system-level finite element (FEM) models. This work demonstrates how Frequency Based Substructuring (FBS) provides an efficient framework for understanding NVH phenomena and facilitates new root cause analysis (RCA) types and processes. To begin, we prove the numerical accuracy of the FBS algorithm deployed in the presented investigation by comparing its results with those obtained with superelements and without substructuring. We point out that because the used FBS process starts with a modal representation of the components rather than their frequency response functions (FRF) a different class of RCA type becomes available. Then we introduce new RCA types starting with an analysis named Modal Influence (MI) that reveals the effect of the modes of any component on a certain response
Herbst, Markus
Agricultural vehicles operating in rough environments experience increased fatigue damage accumulation, which may decrease machine safety and reliability. Autonomous agricultural machines offer an opportunity to incorporate fatigue damage considerations into path planning. This work investigates whether machine learning can predict fatigue damage to a tractor chassis using light detection and ranging (LiDAR)-based terrain features, vehicle speed, and rotational vehicle state data (e.g., triaxial angle, angular velocity, and angular acceleration). Fatigue damage was estimated using the Rupp filter and the Durability Transfer Concept. Following poor predictive performance of the machine learning models, an exploratory analysis of damage histograms, dominant frequency, and acceleration magnitude was performed. Results indicated that most estimated fatigue damage occurred in the 0–2 Hz band, which coincides with the frequency range of terrain-induced acceleration. On-road driving led to
Govers, Megan EmilyHamilton-Wright, AndrewHassan, MarwanOliver, Michele L.
This digital standard is a digital model of AS9100D Quality Management Systems - Requirements for Aviation, Space, and Defense Organization. This file contains an MBSE model in a mdzip file for use in modeling applications.
This digital standard is a requirements extract of AS4159 Specification For An Automated Interchange Of Standards Data. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
This digital standard is a requirements extract of AS13001A Delegated Product Release Verification Training Requirements. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
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.
This digital standard is a requirements extract of AS9145 Requirements for Advanced Product Quality Planning and Production Part Approval Process. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
German startup Blackwave is building carbon parts for rocket tanks. Technical University of Munich, Munich, Germany Carbon fiber has become indispensable in high-performance industries such as automotive engineering and aerospace. It's lightweight, extremely durable, and can be shaped in almost any way. The start-up Blackwave, founded at the Technical University of Munich (TUM), specializes in this versatile composite material. What began with custom components for sports cars and aircraft has evolved into the development of high-pressure tanks for space applications. As is so often the case in engineering, a small detail determines technological progress. In the case of rockets, it is the high-pressure tanks that are specially designed for the fuel systems. As rockets are designed to be as light as possible, they lose structural stability when the fuel tanks, known as primary tanks, are emptied. A trick is used to counteract this: alongside fuel combustion, noble gases are released
Aerospace manufacturing operates within an intricate ecosystem where quality, compliance and traceability are critical to success. Conventional digital thread frameworks provide connectivity but remain largely passive, lacking the intelligence to autonomously manage complex non-conformities across the product lifecycle. This paper introduces an Agentic Digital Thread powered by Agentic AI, designed to transform non-conformity management into an adaptive, self-orchestrating system that actively drives decision-making and corrective actions [1, 4]. The proposed architecture employs a Master Agent to coordinate workflows and maintain end-to-end data continuity, while specialized Agents autonomously manage domain-specific tasks. In the pre-manufacturing phase, these agents proactively validate requirements, material conformity and process planning through integration with PLM, MES, ERP, QMS and supplier systems. In the post-manufacturing phase, the framework extends to concession
Veluri, SastryGopala Krishnan, Kannan
This paper presents an automated framework for security compliance and quality assurance in DevSecOps CI/CD pipelines, specifically designed for safety-critical avionics software. The framework integrates regulatory compliance checks, security validation, and robust verification directly into the software development lifecycle, supporting continuous integration and delivery for aerospace applications. Automated processes such as code compilation, coding standards compliance, Cyclomatic Complexity Measurement, Sources Line of Code and CRC validation on target hardware are seamlessly orchestrated to maintain consistency and reliability. The system generates comprehensive compliance reports, highlights coding standard violations and security issues, and notifies relevant stakeholders to facilitate timely resolution and corrective actions. As new code is checked in, the framework automatically initiates all verification and compliance tasks, ensuring that every software update is
Bhagwat, Shashank RaviChangappa, Naveen KumarNath, Sunny
Abstract: This research paper investigates the performance of FKM (Fluorocarbon) seal material when exposed to a 50:50 ethylene glycol-water mixture. The study aims to determine the volume change percentage and Hardness change of FKM elastomers under standardized testing conditions. The experimental approach follows ASTM D471 and ASTM 2240 guidelines, focusing on weight and hardness measurements of the test samples to establish a success criterion. The results provide critical insights into the chemical compatibility and durability of FKM elastomers in Aerospace and industrial applications where ethylene glycol-water mixtures are commonly used. The findings contribute to enhanced material selection and design considerations for sealing applications subjected to glycol-based fluids. Samples of FKM material were immersed in the fluid at controlled temperatures and durations, simulating real-world operational conditions. The primary metric of interest, volume change percentage and
Yarolkar, MakrandPatil, SandipSingh, Tanul
The mechanical performance of short fiber-reinforced plastic (SFRP) components is highly sensitive to fiber orientation, which is significantly influenced by the injection gate location during the molding process. Traditionally, gate placement decisions are driven by warpage minimization strategies, often overlooking mechanical performance under diverse load cases. This research introduces an automated workflow within Digimat-MS that integrates injection gate optimization into the early design phase, leveraging Integrated Computational Materials Engineering (ICME) principles. The proposed methodology enables engineers to upload either Marc, Abaqus or Ansys input decks, select a component of interest, assign material cards, and define gate scenarios. A Design of Experiments (DOE) is then executed locally or remotely, allowing Digimat to evaluate multiple gate configurations. The system aggregates results and identifies optimal gate locations based on the initiation of failure under
Kauthale, TanmayMadhavan, VinaySoni, Ganesh
Using vibration data to estimate buckling loads is proven effective for a wide range of structures, including rods, plates, and shells. The Arbelo formulation of the vibration correlation technique improves prediction reliability for cylindrical and spherical shells. In this study, we introduce a simplified variant of the Arbelo approach that provides higher prediction accuracy while requiring significantly lower pre-load levels. We define a new parameter, the Stiffness Decay Index (SDI), to characterize stiffness degradation by normalizing the loaded natural frequency with respect to the unloaded state. This metric enables accurate buckling prediction without causing structural damage or permanent deformation. We evaluate SDI numerically and experimentally for multiple isotropic geometries and demonstrate its advantages over the Arbelo method, particularly for ellipsoidal domes subjected to external pressure. We conduct experiments on rods, plates, oblate shells, and beverage cans to
Rangarajan, GopikrishnaV, VishwajithRaju, GangadharanDinavahi, Ramkrishna
Aircraft lighting systems play a vital role in ensuring operational safety, visibility, and regulatory compliance. Exterior lighting systems are essential for aircraft identification, navigation, collision avoidance, and ground operations under varying environmental conditions. These systems typically include navigation lights, anti-collision lights, landing and taxi lights. An aircraft lighting system comprises light sources, optical elements, electronic control units, power interfaces, wiring harnesses, and mechanical mounting structures. Among these components, optics are critical as they control light distribution, intensity, color accuracy, and efficiency while withstanding harsh aerospace environments such as vibration, thermal cycling, and aerodynamic loads. Aircraft exterior lights are subjected to severe thermo-mechanical stresses due to aerodynamic loading, vibration, and thermal cycling. The use of high-performance optical polymers such as Cyclo Olefin Polymers (COP
Vialta, FredericoS, NikhilKatageri, PraveenSP, PradeepSingh, Abhimanyu Kumar
This SAE standard establishes the requirement for suppliers to plan a reliability program that satisfies the following three requirements: a The supplier shall ascertain customer requirements b The supplier shall meet customer requirements c The supplier shall assure that customer requirements have been met
G-41 Reliability
This document provides methods and techniques for implementing a reliability program throughout the full life cycle of a software product, whether the product is considered as standalone or part of a system. This document is the companion to the Software Reliability Program Standard [JA1002]. The Standard describes the requirements of a software reliability program to define, meet, and demonstrate assurance of software product reliability using a Plan-Case framework and implemented within the context of a system application. This document has general applicability to all sectors of industry and commerce and to all types of equipment whose functionality is to some degree implemented by software components. It is intended to be guidance for business purposes and should be applied when it provides a value-added basis for the business aspects of development, use, and sustainment of software whose reliability is an important performance parameter. Applicability of specific practices will
G-41 Reliability
The sag prediction of overhead ground wire is very important, because excessive sag will reduce the safety margin and endanger the transmission reliability, especially under extreme conditions such as heat wave and icing. To solve this problem, we propose a model that combines Exponential Moving Average (EMA) features and monotonic constraints XGBoost. By fusing multi-source meteorological data and sag monitoring data, sag-related features are extracted after outliers elimination and time alignment. Furthermore, EMA features are introduced to capture short-term fluctuations and time dependence. Monotonic constraints encode the physical prior knowledge of “the higher the temperature, the greater the sag”, which improves the physical interpretability. On the measured data, the model’s coefficient of determination is increased from 0.709 to 0.879, indicating that the short-term prediction accuracy is significantly improved. The combined application of EMA features and monotonic
Li, XingyuLin, ShizhongShao, ZhanCui, ShichengChen, RuiduanLuo, He
The reliability of welded joints is a vital factor in modern manufacturing, directly affecting product performance and durability. This study investigates methods to enhance the mechanical and metallurgical quality of butt joints in AISI 304L stainless steel welded by the gas tungsten arc (GTA) process. A systematic experimental design was implemented using the Taguchi method with an L9 orthogonal array, considering welding current, gas flow rate, and travel speed as the main parameters. To determine overall weld performance, the joints were characterized by measuring ultimate tensile strength (UTS), yield strength, percentage elongation, and examining their microstructural morphology. An experimental strategy based on the Taguchi approach has been implemented. The welding performance of the material was investigated, and the process parameters were optimized using multiresponse optimization through principal component analysis (PCA), incorporating an orthogonal array design, signal-to
Ghosh, NabenduRoy, Angshuman
This standard establishes the common requirements for training of DPRV personnel for use at all levels of the aerospace engine supply chain. This standard shall apply when an organization elects to delegate product release verification by contractual flow down to its suppliers (reference 9100 and 9110 standards) and to perform product acceptance on its behalf. It is intended that organizations specify their DPRV requirements through the application of AS9117. While the delegating organization will use the AS13001 standard as the baseline for establishing DPRV process and product training, it may include additional contractual training requirements to meet its specific needs. The DPRV training material was primarily developed for aerospace engine supply chain requirements. However, this standard may also be used in other aerospace industry sectors where a DPRV process requiring specific training can be of benefit.
G-22 Aerospace Engine Supplier Quality (AESQ) Committee
This FMEA standard describes potential failure mode and effects analysis in design (DFMEA), supplemental FMEA-MSR, and potential failure mode and effects analysis in manufacturing and assembly processes (PFMEA). It assists users in the identification and mitigation of risk by providing appropriate terms, requirements, rating charts, and worksheets. As a standard, this document contains requirements—”must”—and recommendations—”should”—to guide the user through the FMEA process. The FMEA process and documentation must comply with this standard as well as any corporate policy concerning this standard. Documented rationale and agreement with the customer are necessary for deviations in order to justify new work or changed methods during customer or third-party audit reviews.
Automotive Quality and Process Improvement Committee
The Army requires rotorcraft drive systems to operate for 30 minutes following a loss of lubrication event to make an emergency landing. Coatings research has shown great promise for loss of lubrication, but coating repeatability and quality control is a primary hurdle. The Army partnered with Acree Technologies via a Small Business Innovation Research (SBIR) effort to develop an optimized gear coating for loss of lubrication. The research culminated in a system level transmission experiment that maintained flight relevant torque and speed through a helicopter gearbox without oil for three hours. The authors decided to shutdown the experiment for inspection after three hours of operation without oil because the temperature and vibration signals maintained steady state conditions without signs of failure. Teardown analysis showed the transmission gear surfaces did not scuff, scanning electron microscope analysis showed coating remained on the gear teeth, and cross-sectional SEM analysis
Riggs, MarkPomplon, WilliamFetty, JasonMilligan, RyanWoods, RonWong, KelvinMatzke, CalebJacques, KellyHood, Adrian
This paper presents the implementation of a fully automated Health and Usage Monitoring System (HUMS) data chain designed to accelerate installed engine performance diagnostics during the pre-delivery phase of new-generation helicopters. Ensuring that engine performance remains consistent with original engine manufacturer (OEM) baseline data is a critical step in the final assembly process, yet traditionally time-consuming. The developed system automates data offloading and integrates three distinct streams: OEM engine performance characteristics, in-flight Engine Power Checks (EPC), and high-frequency continuous recordings. The core innovation lies in a multi-source data fusion methodology combined with a physics-based model to differentiate between genuine installation discrepancies and sensor anomalies through temperature deviation analysis. Results from the production environment demonstrate that this automated approach significantly reduces troubleshooting lead times and ensures
Esterle, FlorentLecauchois, ClaireMaisonneuve, Pierre-LoïcCalvet, Thomas
This study investigates the use of the Overset mesh method for propeller simulations in OpenFOAM and compares it with the Arbitrary Mesh Interface (AMI) approach. While AMI is well validated for rotor aeroacoustics, it is limited in handling large relative motions and complex component interactions. In contrast, the Overset method enables flexible simulation of transition kinematics using overlapping grids, though its aeroacoustic capability in OpenFOAM has not been well established. A comparative analysis was conducted on a Joby-scale five-bladed propeller at an 80° tilt angle without a fairing, representing a transition-flight condition. Aerodynamic and acoustic predictions were obtained using hybrid DDES coupled with the Ffowcs Williams–Hawkings method. Results show that the Overset method provides improved agreement with experimental thrust and torque and captures stronger leading-edge vortices than AMI. Both methods resolve blade-vortex and blade-wake interactions. However, the
Hua, JieMankbadi, Reda R.Lyrintzis, Anastasios S.Golubev, Vladimir
This study highlights that rotor-rotor interactions can significantly modify both tonal and broadband noise characteristics. Continued investigation into these mechanisms is vital to developing reliable noise prediction methodologies and establishing design strategies that balance propulsion efficiency with acoustic acceptability for AAM vehicles. This work sought to answer what physical mechanisms contribute to the increased dominance of broadband noise in eVTOL-scale rotors. By characterizing the tip vortex of a single rotor, it was found that rotor-rotor interaction is highly dependent on two factors: Blade-vortex phasing and interaction duration. Characteristic vortex time scales can be correlated with increased noise. Interactions that generate increased noise have a non-linear relationship with rotor positioning. The interaction-generated noise is highly directive. This work aims to elucidate the dominant source noise mechanisms of rotor-rotor interaction noise by characterizing
Sorensen, PeterSeth, DhureeCuppoletti, Daniel
This document applies to the development of Plans for integrating and managing COTS assemblies in electronic equipment and Systems for the commercial, military, and space markets, as well as other ADHP markets that wish to use this document. For purposes of this document, COTS assemblies are viewed as electronic assemblies such as printed wiring assemblies, disk drives, servers, printers, laptop computers, etc. There are many ways to categorize COTS assemblies1, including the following spectrum: At one end of the spectrum are COTS assemblies whose design, internal parts2, materials, configuration control, traceability, reliability, and qualification methods are at least partially controlled, or influenced, by ADHP customers (either individually or collectively) or by industry standards. An example at this end of the spectrum is a VME circuit card assembly. At the other end of the spectrum are COTS assemblies whose design, internal parts, materials, configuration control, and
APMC Avionics Process Management
This paper presents a hybrid optimization framework that integrates Multi-Physics Topology Optimization (MPTO) with a Neural Network–surrogated Design of Experiments (NN-DOE) to enable lightweight structural design while satisfying crashworthiness, durability, and noise, vibration, and harshness (NVH) requirements under practical casting and packaging constraints. In the proposed MPTO formulation, crash and durability performances are incorporated through equivalent static compliance measures, while NVH performance is assessed using a frequency-domain dynamic stiffness metric, allowing consistent evaluation of trade-offs among competing design requirements. The framework is first demonstrated using a mass-produced passenger-car lower control arm (LCA) as a benchmark component. In this application, MPTO achieves weight reduction under multi-physics objectives by removing non-load-bearing material. Results show that single-discipline optimization produces unbalanced topologies, while
Kim, HyosigSenkowski, AndresGona, KiranSaroha, LalitBoraiah, Mahesh
Software-defined vehicles offer customers a greater degree of customization of vehicle controls and driving experience. One such feature is user-adjustable tuning of vehicle ride and handling, where customers can vary ride height, damper stiffness, front-rear torque balance, and other aspects of vehicle dynamics. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than those in the nominal design condition, particularly when such tuning is extended to cover spirited “sport” mode driving, off-road driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability. In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving
Demiri, AlbionRamakrishnan, SankaranWhite, DylanKhapane, PrashantBorton, Zackery
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