Browse Topic: Tests and Testing
Modern defense manufacturing and sustainment require timely engineering decisions (e.g., inspection triage, rework/accept decisions, and process adjustment) based on the as-built geometric quality. Advanced machining systems generate rich multichannel controller and sensor streams, yet accurate geometric deviation labels remain costly and delayed because they depend on downstream metrology. This paper introduces ChronosGD, a retrieval-based virtual metrology framework. ChronosGD predicts pointwise geometric deviation from multichannel time series data by: (1) retrieving the most similar historical process windows in a frozen Chronos-2 embedding space, and (2) transferring deviation information through similarity-weighted aggregation. ChronosGD avoids plant-specific gradient retraining during deployment; adaptation is achieved by refreshing a labeled historical memory as new inspected parts become available, while preserving traceability through explicit neighbor provenance.
Modern mission-critical ground vehicle systems must adapt to rapidly evolving threats, deploying changes in months or days while maintaining reliable and safe operation. Historic manual development and testing methods cannot keep pace without compromising safety assurances. Continuous Integration and Continuous Deployment (CI/CD) pipelines offer proven approaches to accelerating development, but implementing them for mission-critical systems requires careful attention to verification rigor. This paper presents a practical framework for implementing CI/CD pipelines across any level of rigor, from rapid prototyping to DO-178C and ISO 26262 certified systems. Drawing on experience from aviation, medical device, and ground vehicle development, the framework provides guidance for each pipeline stage based on the system’s desired level of rigor. This framework includes an examination of the value of Software-in-the-Loop vs Hardware-in-the-Loop testing to optimize development timelines while maintaining software quality.
This SAE Recommended Practice is intended to establish a procedure to certify the low mu/winter driving skill levels of professional drivers. This certification can be used by the individual driver to qualify their skills when seeking employment or other professional activity. These certification levels may also be used by test facilities or other organizations when seeking test or professional drivers of various skills. This document provides directions for obtaining certification through Probitas Authentication®1 and the low mu/winter driving skill examination requirements. This document is a supplement to SAE J3300, providing information specific to the low mu/winter driving skill certification and clarifying the application of the rules set forth in SAE J3300 to the low mu/winter driving certification. While the references, definitions, rules, and guidelines presented in SAE J3300, Sections 1 through 5 apply to the low mu/winter driving certification, they are not repeated in this document.
A numerical study on the influence of annular gap variation in correctly expanded sonic coaxial jets, focusing on its effect on mixing characteristics and jet symmetry, is presented in this paper. The computational simulations were conducted using a three-dimensional steady-state compressible Reynolds-Averaged Navier–Stokes (RANS) framework with the Spalart–Allmaras (SA) turbulence model. Both symmetric (uniform gap) and asymmetric (nonuniform gap) configurations were simulated. Eccentricity was introduced by offsetting the secondary nozzle by 2 mm downward from the center of the primary nozzle. In symmetric configurations with uniform annular gaps, the jet exhibited balanced shear-layer development, uniform entrainment, and symmetric Mach decay characteristics. However, the asymmetric annular gap configuration exhibited approximately 25–30% earlier potential core breakdown, 30–35% greater radial jet spreading, and nearly 6–10% faster centerline velocity decay compared with the symmetric configuration. The streamline analysis revealed enhanced entrainment, localized recirculation regions, asymmetric vortex generation, and accelerated momentum diffusion caused by unequal shear-layer interaction. These results demonstrate that annular gap asymmetry can serve as an effective passive flow control strategy for enhancing jet mixing and directional momentum redistribution. Such configurations may be useful in practical applications including exhaust gas dilution, fuel–air mixing enhancement in combustors, thrust vectoring, and jet-noise suppression systems.
This study compares two international loudness standards—International Organization for Standardization (ISO) 532-1:2017 (Zwicker) and ISO 532-3:2023 (Moore–Glasberg–Schlittenlacher)—for assessing vehicle wind noise using wind tunnel measurement data. The two methods demonstrate good agreement in ranking wind noise quietness at typical highway speeds (120–140 km/h). However, discrepancies arise under specific conditions due to ISO 532-3’s binaural processing, which accounts for interaural inhibition effects. These differences are particularly pronounced in vehicles with asymmetric wind noise levels between the driver and passenger sides. Power-law regression analysis reveals that binaural loudness at the driver side (ISO 532-3) increases at a slower rate with wind speed compared to the monaural measurements [driver outboard ear (DOE)] of ISO 532-1. Under yaw angle conditions, the perceptual contribution of the driver inboard ear (DIE) introduces subtle metric-dependent variations. Contribution analyses further highlight method-specific sensitivities to noise source location and direction. Overall, this study provides a valuable reference for implementing loudness metrics in automotive wind noise engineering.
Teardown evaluation of chassis system components plays a critical role in benchmarking, failure analysis, and competitive product assessment. These inspections rely heavily on experienced engineers who interpret visual defect patterns, material conditions, wear signatures, and manufacturing variations. However, expert driven evaluation processes are often subjective, difficult to standardize, and challenging to scale across global engineering teams. This paper presents a structured AI-assisted expert evaluation framework developed to enhance consistency, preserve institutional knowledge, and enable continuous improvement in chassis component teardown analysis. The proposed system integrates convolutional neural network architectures, including ResNet18 and its variants, into a human in loop inspection workflow. AI models perform initial classification of component images (e.g., OK/not OK and defect subclasses) and provide associated confidence scores. These predictions are presented as decision support, while final authority remains with the evaluating expert. Experts can confirm or override AI outputs, annotate defect regions using bounding boxes, assign subclass categories, and provide structured technical comments. All expert interactions, including AI disagreements, are systematically recorded. Correction instances are analyzed to identify model limitations, ambiguous defect conditions, and data gaps. Expert validated evaluations are incorporated into the training dataset to enable iterative model refinement. This closed loop process supports progressive improvements in model robustness and classification accuracy across varying teardown conditions and component types. A centralized cloud-based repository maintains full traceability of inspections, including timestamps, AI confidence levels, expert modifications, and annotation metadata. This structured knowledge capture converts tacit engineering judgment into a persistent digital asset, supporting auditability, cross-site alignment, and accelerated onboarding of new engineers. The framework demonstrates how AI can be effectively deployed as an assistive technology in chassis teardown evaluation, improving repeatability, enhancing data driven benchmarking, and enabling scalable knowledge preservation without displacing expert authority.
Drum brake systems are becoming increasingly important in electric vehicles (EV) and purpose-built vehicles due to cost competitiveness and EURO-7 particulate emission regulations. Despite this trend, drum brake friction behavior remains incompletely characterized due to its dependence on multiple coupled variables: temperature history, braking conditions, and component interactions. To address this gap, this study presents a method for developing a time-series friction torque prediction model using the Mixed-effects Random Forest (MERF) machine learning framework. Time-series data collected from sensors during drum brake dynamometer tests were analyzed to identify the key variables that govern the friction torque. Significant inputs were selected through Exploratory Data Analysis (EDA), considering test-to-test variability and potential mixed effects, and were then used to train and tune the MERF model. Model performance was evaluated by comparing predicted friction torque with measured torque, and prediction error was quantified by using Mean Absolute Error (MAE) to check whether predicted model is reliable. The proposed prediction model demonstrates a high level of agreement with experimental measurements, confirming that the MERF approach can effectively capture the non-linear and transient characteristics of drum brake friction torque from time-series sensor signals. These results indicate that friction torque estimation is feasible using only sensor signals already available from conventional test instrumentation, without additional dedicated sensors. This capability is expected to support broader applications, including brake performance prediction for vehicles equipped with drum brakes and enhanced simulation of drum brake thermal performance across operating conditions.
With the large-scale application of intelligent connected vehicles, the verification of their functional safety and reliability has become a core bottleneck in the industrial development. The traditional real- vehicle road test method can no longer meet the current demand for large-scale test verification due to problems such as high cost, low efficiency, and difficulty in reproducing dangerous scenarios. This paper studies the vehicle-in-the-loop simulation test system based on a digital twin. By constructing a virtual scenario highly consistent with the real world, physical-level multi-source perception signals are simulated and mapped to the system under test to enable high- reliability verification of real vehicles. In terms of lateral and longitudinal control functions, multiple sets of test cases are selected respectively for comparison between road tests and virtual simulation tests. The results show that the accuracy of key indicators is above 90%, which provides practical reference for the subsequent test and verification system of high-level autonomous driving.
This test method outlines the recommended procedure for performing the no-load rotational starting torque test on airframe rolling bearings. Bearings covered by this test method shall be antifriction ball bearings and spherical roller bearings.
Ultrasonic TOFD detection is one of the most important non-destructive testing techniques for welds. However, the complex beam deflection, scattering, and attenuation of ultrasonic waves in the heterogeneous weld structure lead to the weak signal of the defect diffraction wave received by the probe and the low signal-to-noise ratio, which has a negative impact on the engineering application of ultrasonic TOFD detection technology in austenitic stainless steel welds. In this study, a numerical model of the ultrasonic TOFD detection process for austenitic stainless steel welds was established based on the finite element method. Combined with the test method, the interaction mechanism between the ultrasonic wave and weld structure is analyzed, and the probe arrangement method to reduce the interference of weld scattering noise is proposed. The results show that the finite element model can simulate the anisotropic characteristics of ultrasonic waves in austenitic stainless steel welds, including sound field distortion, sound energy scattering, and attenuation. Combined with the detection test, it has been proven that the adverse effect of the weld structure on the TOFD detection signal can be reduced by changing the probe detection surface.
To safely, efficiently, and high-quality complete the mechanical testing of batch-produced manned spacecraft during the China Space Station (CSS) phase, a series of optimization measures were proposed based on system engineering principles. These measures cover the entire mechanical testing process from preparation to implementation, including: establishing a standardized mechanical testing documentation system; reducing the number of mechanical sensors that do not affect result evaluation; pre-identifying and measuring background noise; digitizing test notching and evaluation methods; and standardizing and automating testing procedures. Additionally, targeted measures for test safety and quality control were implemented, including regular inspections of reusable spacecraft components, strict control of test hazards and operational risks, and standardized management of ground support equipment (GSE) through regular inspections. The proposed optimization and control measures have been validated through applications in batch-produced manned spacecraft during the CSS phase. The results show that: the generalization rate of mechanical testing documentation exceeds 80%; the number of mechanical sensors has been reduced by more than 10%; the test preparation period has been shortened by over 4 days; test efficiency has been improved by 30%; the single-direction test duration has been reduced by more than 50%; and the total test cycle has been shortened by 25%. These results indicate that the proposed optimization and control measures are reasonable and feasible, which effectively reduces redundant test operations and items, lowers potential test risks, improves test efficiency, shortens the overall test cycle, enhances test safety, and ensures the high-quality completion of mechanical testing for batch-produced manned spacecraft.
With the continuous improvement of performance requirements for aviation equipment, the importance and complexity of hydraulic systems as the core carrier of flight control are becoming increasingly prominent. The cleanliness of aircraft hydraulic pipelines directly affects the reliability and flight safety of hydraulic systems, and it is necessary to use specialized cleaning and testing equipment during design and manufacturing to achieve efficient cleaning. The design of traditional cleaning equipment relies on experience-driven development, with mechanical, hydraulic, and electrical systems developed independently. There are problems such as unclear requirement definitions, low efficiency of interdisciplinary collaboration, and lagging validation, making it difficult to achieve the goal of forward design. Therefore, this study introduces Model-based Systems Engineering (MBSE) method in the development process of pipeline cleaning test equipment, proposes a modeling process based on RFLP (Requirements-Function-Logical-Physical), and uses SysML system modeling language to construct a top down design model system for aircraft hydraulic pipeline cleaning equipment. Through requirement analysis modeling, functional behavior definition, and system architecture design, the significant advantages of MBSE method in the development of complex aviation test equipment have been verified, effectively improving the bold design capability and top down design efficiency. MBSE method can not only improve the design efficiency of equipment, but also promote the intelligent and efficient operation of equipment, which has important significance for the development of intelligent manufacturing and electromechanical integration technology.
Full, industry standard test procedures for measuring the charging performance of a vehicle can be found in ISO/SAE 12906. This document describes the lessons learned during the development of that document, including false assumptions that are common in vehicle charging tests. The purpose of this document to better explain the need for the specific procedures in ISO/SAE 12906. Furthermore, by communicating the false assumptions and complications of historic charging tests, it is also hoped that others wishing to create test procedures different from ISO/SAE 12906 can do so without making the same mistakes of the past.
For decades, hydraulic systems have been relied upon to do all the heavy lifting in aerospace. They are powerful, reliable, and deeply embedded in how aircraft are designed, to the extent that - for many engineers - they are simply part of the landscape. Now, however, things are beginning to change. From advanced air mobility platforms now entering certification to next-generation commercial aircraft on 10-year horizons, electric and electro-hydraulic actuation is steadily replacing the heavy, centralized hydraulic architectures that have defined flight control for decades. Understanding why means stepping back from the actuator itself and looking at the aircraft as a whole system - and, increasingly, as an integrated motion control challenge.
Regarding the external sling load system of heavy-lift helicopters, the influence of the law of lifting point position on flight control stability characteristics has not been distinctly explained. To address this challenge, this paper constructs a sling load flight simulation model based on multi-body dynamics. Overall, the proposed model consists of four parts, including the rotor aeroelastic coupling model, the fuselage rigid body dynamics model, the flexible sling model, and the slung object rigid body model. Furthermore, through the hub six-degree-of-freedom rigid model and the flexible sling model, this paper realizes the dynamic coupling between the components. On this basis, taking the CH-53E heavy-lift helicopter as the research object, this paper utilizes real flight test data to validate the multi-body dynamic model. Subsequently, this paper systematically analyzes the influence of different lifting points’ lateral position, sling load mode, load-mass ratio, and forward flying speed on helicopter control stability characteristics. Simulation results indicate that the lifting point location exerts a significant impact on the helicopter’s trim attitude angles and dynamic stability. Of them, the lifting point location of the front center of gravity is the optimal in terms of trim characteristics and eigenvalue distribution. Furthermore, within a certain flight speed range, the lifting point of the front center of gravity demonstrates superior speed adaptability and system robustness. Apart from providing a solid theoretical basis for the lifting point layout design of the external sling load system of heavy-lift helicopters, the research results have important engineering application value for improving the safety of sling load flight of heavy-lift helicopters.
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