Browse Topic: Data exchange
Passive fatigue can cause accidents with automated and regular vehicles. A proof-of-concept prototype [made with light-emitting diode (LED) matrices and white LED (WLED)] and a preliminary comparative usability test (N = 7) are used to study whether the active manipulation of simulated weather cues can be a potential countermeasure to passive fatigue. Participants rated system suitability, system impression, and their fatigue level similarly when they viewed a weather windshield heads-up display (HUD) versus a speedometer windshield HUD [no significant differences found and relatively small 95% confidence interval (CI) ranges around 0]. Qualitative analysis of interviews found that participants saw the potential value of the weather display and that display placement, dynamic graphics, and user activation were commonly mentioned themes. These results suggest the concept is theoretically possible, though further work is needed to prove the concept in practice.
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.
Static electricity is an electrical imbalance on the surface of a material which can interact with other components having same or different materials. Fluid flow within the hose assembly generates static voltage due to friction caused by fluid flow in pipes, that needs to be appropriately quantified and dissipated. Accumulation of such static charge may lead to sudden discharge leading to spark generation. Spark generation around fuel flow might lead to system failure and failure in aircraft engines. Test experiments were conducted to analyze static voltage generated in hose assembly due to fuel flow with the objective that voltage achieved is within the acceptable range to avoid ESD (Electrostatic Discharge) failure. Procedure includes flow rate monitoring and voltage measurement using fuel as test fluid. The testing revealed that the curvature of the hose affects the readings, highlighting the importance of consistent meter alignment. Using a grounding strap is essential to prevent
This Surface Vehicle & Aerospace Recommended Practice offers best practices and a methodology by which IVHM functionality relating to components and subsystems should be integrated into vehicle or platform level applications. The intent of the document is to provide practitioners with a structured methodology for specifying, characterizing and exposing the inherent IVHM functionality of a component or subsystem using a common functional reference model, i.e., through the exchange of design-time data and the application of standard vehicle data communications interfaces. This document includes best practices and guidance related to the specification of the information that must be exchanged between the functional layers in the IVHM system or between lower-level components/subsystems and the higher-level control system to enable health monitoring and tracking of system degradation severity. The intent is to provide an IVHM system that can robustly report the degradation of a given
Hybrid bearings, which pair traditional bearing-steel raceways with ceramic rolling elements, can offer improved performance over full-metal bearings, particularly in aerospace applications. Because rolling-element bearings are critical components, effective condition monitoring is essential to prevent in-flight failures and support proactive maintenance strategies. Wear-debris monitoring is widely used in these applications to detect and diagnose bearing fault modes. To compare degradation behavior and monitoring signatures, bearing life tests were conducted on hybrid and full-metal bearings under matched Hertzian stress conditions. The results showed that differences in degradation curves between the two bearing types were small relative to the overall variability in bearing life. Additionally, hybrid bearings that develop rolling-element pitting were observed to progress toward raceway spall formation. This paper was presented at ERF Forum 51 but has been updated with new findings
Prior work demonstrated that acceleration washout in motion simulators produces decay-rate sensing ambiguity within the vestibular system, forcing pilots to rely on visual cues for control. While Pilot Induced Oscillation Ratings (PIORs) for flight and simulation have been matched using different sensing thresholds, a quantitative basis for the 50% reduction in the visual decay-rate threshold has remained elusive. This paper provides evidence that pilots perceive decay rate proprioceptively through stick force during both flight and simulation, rather than through vestibular or visual channels. The residues of the stick-force sensitivity transfer function reflect the amplification or attenuation of neighboring zeros and poles; when these residues fall outside the human's 30 dB tactile sensory window, the resulting decay rate becomes imperceptible. Modeling reveals that stabilization via the visual channel in simulators produces dominant mode characteristics - decay rates, frequencies
This paper investigates amplitude effects in the aeroelastic damping and frequency characteristics of the Maryland Tiltrotor Rig across four configurations: gimballed or hingeless hubs, each paired with straight or swept-tip blades. The recovery rate method is used to identify the aeroelastic parameters of the primary modes dominated by out-of-plane and in-plane wing bending from experimental free-decay strain time histories, capturing variations in dynamic behavior with the response amplitude. Results from conventional methods that assume linear (amplitude-independent) behavior are also presented for comparison. The local damping ratio of the examined modes generally decreases with increasing strain amplitude across all configurations, a trend missed by conventional linear estimation methods. The strength of amplitude effects varies as the system approaches instability: for gimballed configurations, they weaken near instability; for hingeless configurations, they become more
Pilot compensation — the effort required to maintain task performance in the face of deficient vehicle characteristics, as rated on the Cooper–Harper Handling Quality Rating (HQR) scale – is the task-performance-anchored measure of workload. While it has traditionally been inferred from control activity alone, recent work shows that eye-movement activity carries complementary information: as compensation rises, control inputs increase while visual scanning narrows, so neither channel alone captures the full picture. This paper proposes the pilot action metric, which combines control-stick and eye-movement activity rates so that both channel responses reinforce the compensation signal. A shared-slope regression model with per-pilot intercepts is evaluated via leave-one-out cross-validation on 16 simulator runs flown by three military test pilots across four mission task elements. The combined metric succeeds where either channel alone fails, reproducing 94% of ratings to within ±1 HQR
This paper presents a high-fidelity fatigue damage modeling framework for composite structures with ply drops, incorporating several key advancements to capture localized fatigue behavior. The approach includes: (1) computation of local stress ratios at each fatigue cycle; (2) an R-ratio-dependent fatigue damage accumulation model; (3) implementation of a constant load diagram to construct S–N curves at arbitrary R-ratios; and (4) a cycle-jumping technique to account for the evolving rate of fatigue damage accumulation due to progressive stiffness redistribution. A combined experimental and numerical study was conducted on tapered composite beams subjected to mixed axial tension and vertical bending. A custom-designed fatigue test fixture was developed to capture displacement at the loading end, which was then used as a boundary condition in the fatigue life prediction model. To guide the selection of fatigue test peak loads, static failure analyses were first performed on
The Pilot-selected Group Delay Ratio (P-GDR) heuristic is proposed, where the pilot enforces an optimal group delay ratio between the open and closed loop phase slopes at the closed loop dominant frequency. Capturing the slope of the phase at the most critical frequency (the dominant mode frequency), GDR-based control allows the pilot-in-loop system with a damping of 0.2 to mimic the stability and signal latency of an optimally damped second order system. UAS design could also benefit from the simplicity and efficiency of GDR control. A Unified Normative HQR (UN-HQR) methodology is proposed, which computes two components of HQRs: 1) HQRα, reflecting the cost of oscillation through decay rate, and 2) HQRe, reflecting the cost arising from tracking error. This paper demonstrates that ADS-33’s phase delay and bandwidth serve as proxies for the mathematical inverses of closed-loop stability (decay rate) and task performance. While legacy criteria track these symptoms, the pilot’s internal
A common-open data exchange standard for rotorcraft health and usage monitoring systems (CODEX-HUMS), SAE Aerospace Standard AS7140, was issued in September 2025. This standard provides a definition for the CODEX-HUMS open data format produced or used by an on-board or off-board system. The centerpiece of the standard is the data model. This paper describes how the two main data types, stream and batch data, are defined and modeled distinctly by AS7140. The batch data model, targeted at high-frequency, short-duration recorded data, features and delineates a "source", an "indicator", and a "status" element. The streaming data model, intended for lower-frequency, longer-duration HUMS data, covers events and parametric data. The data model is structured by defined data collections to describe the data collected or supporting metadata specifying details about the system or underlying data. In particular, there are definition-type entities and recorded data-type entities. This data model is
Traditional safe-life methodologies for rotorcraft structural components rely on deterministic safety factors to account for uncertainty in loads, material properties, and operational usage. While effective for ensuring safety, these approaches lead to early retirement lives and reduced aircraft availability. This paper presents an updated digital twin-based probabilistic framework for rotorcraft component fatigue life assessment that integrates a probabilistic stress–life (S-N) material model, machine learning-based load estimation from flight data, and Monte Carlo uncertainty propagation. The approach is demonstrated for a critical location on the CH-146 Griffon main rotor yoke. Compared with earlier work, the present study advances the framework through independent validation of the load-estimation model and application to available in-service flight data from multiple mission categories. A probabilistic sensitivity analysis is used to examine the separate and combined effects of
Newly designed eVTOL aircraft utilize propellers that operate with a large range of propeller rotation rates. Traditional nomenclature uses nondimensionalization based on the blade tip speed, and input reduction based on a similarity assumption under constant advance ratios. In this study, we explore the validity of this similarity assumption in the context of hover and descent scenarios for a variable pitch eVTOL propeller with rotation rates ranging from 54%-100% of the maximum value. In hover, the relative Reynolds number and Mach number effects are found to be relatively minor. As the axial descent ratio increases, prior to the onset of vortex ring state, the similarity assumption breaks down, and the mean thrust coefficient varies up to ±10% under different rotation rates. A similar breakdown is observed for descent conditions with higher edgewise flow. A detailed exploration shows that the effect is primarily due to relative Mach number effects, which alters the tip vortex wake
Linear time-invariant (LTI) reduced-order models (ROMs) have been widely used in battery thermal management simulations due to their low hardware requirements, high computational efficiency, and good accuracy. However, the inherent assumption of LTI behavior limits their applicability in scenarios with varying coolant flow rates, where this assumption is no longer valid. To address this limitation, a novel ROM is developed by decomposing the entire battery thermal system into two subsystems. All solid components are modeled as a traditional LTI ROM, while the coolant channel is represented using Newton’s cooling law. The two subsystems are then coupled through the exchange of heat transfer rate and temperature at the fluid–solid interface between the coolant and the cold plate. Model fidelity is further enhanced by introducing a spatially distributed heat flux during the generation of the LTI ROM for solid components. Validation is performed against CFD simulations at both module and
As the utilization of lithium-ion batteries in electric vehicles expands, monitoring the usable cell capacity (UCC) is essential for ensuring accurate state-of-health (SOH) estimation. Battery performance degradation is influenced by temperature and constraints. Capacity tests in laboratory settings are typically conducted at low C-rates to approximate equilibrium conditions, whereas in real vehicle applications, charging currents are often much higher. This discrepancy in rates frequently results in deviations between laboratory characterization and on-board Battery Management Systems (BMS) capacity estimation. To investigate how C-rate of diagnostic Reference Performance Test (RPT) modulates aging effects under temperature and mechanical loading, we conducted long-term cycling tests on lithium iron phosphate/graphite pouch cells at 25°C and 45°C under different constrained conditions. The cycling protocol is a tiered multi-rate protocol. Cells were aged at Block1 under 1C, and UCC
Foam material models for automotive structural analysis typically require tensile and compressive data at multiple strain rates. The testing is costly and may require a long time to complete. For many applications, foams of similar chemistry are used and the foam structural responses, such as stiffness and compression force deflection, are controlled by the foam density. In such cases, Machine Learning (ML) lends itself as an ideal tool to detect the trends in material response based on density and strain rate. In this paper, two sets of polyurethane (PU) foams of different densities were tested at four strain rates ranging from 0.01/s to 100/s. ML models capable of predicting compressive stress-strain response for a range of densities were developed. The models demonstrated good prediction capability for intermediate strain rates at all foam densities and in extrapolating stress-strain curves at higher densities at all strain rates. The strain rate trends for density outside of the
Autonomous vehicle navigation requires accurate prediction of driving path curvature to ensure smooth and safe trajectory planning. This paper presents a novel approach to curvature prediction using deep neural networks trained on GPS-derived ground truth data, rather than model predictions, providing a more accurate training signal that reflects actual vehicle motion. We develop a multi-modal neural network architecture with temporal GRU encoders that processes vision features, driver intent signals, historical curvature, and vehicle state parameters to predict curvature. A key innovation is the use of GPS-based actual curvature measurements computed from vehicle motion data (κ = ωz/v) as training supervision, enabling the model to learn from real-world driving patterns. The model is trained on 5,322 samples from real-world driving data collected on The University of Oklahoma’s Norman Campus using a Comma 3X device and a 2025 Nissan Leaf electric vehicle. Experimental results
Ammonia has emerged as a viable hydrogen energy carrier owing to its superior hydrogen density and mature industrial utilization. However, ammonia faces critical challenges including inadequate ignition characteristics and sluggish combustion kinetics, necessitating supplementary high-reactivity fuels for optimizing combustion. Onboard ammonia decomposition technology resolves this problem through on-demand hydrogen real-time production. Among existing ammonia decomposition methods, gliding arc plasma (GAP) demonstrates exceptional promise for onboard hydrogen production given its high processing flow rate，decent hydrogen conversion rate, and transient response capability. Prevailing research predominantly relies on experimental approaches, with insufficient understanding of the effects of specific electrical field parameters and inlet pressure on system performance. This study established a quasi-one-dimensional numerical model for GAP-assisted ammonia decomposition. A comprehensive
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