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This specification covers an aluminum alloy in the form of sheet and plate from 0.008 to 4.000 inches (0.20 to 101.60 mm) in thickness, inclusive (see 8.5).
AMS D Nonferrous Alloys Committee
This specification covers a corrosion- and heat-resistant steel in the form of forgings, wire, bars, mechanical tubing, flash-welded rings, and stock of any size for forging or flash-welded rings.
AMS F Corrosion and Heat Resistant Alloys Committee
This specification covers a premium aircraft-quality, corrosion- and heat-resistant steel in the form of bars, wire, forgings, mechanical tubing, flash-welded rings, and stock for forging or flash-welded rings.
AMS F Corrosion and Heat Resistant Alloys Committee
This specification covers a corrosion- and heat-resistant cobalt alloy in the form of investment castings.
AMS F Corrosion and Heat Resistant Alloys Committee
This specification covers a premium aircraft-quality, low-alloy steel in the form of bars, forgings, mechanical tubing, and forging stock.
AMS E Carbon and Low Alloy Steels Committee
This specification covers a low-alloy steel in the form of bars, forgings, mechanical tubing, and forging stock.
AMS E Carbon and Low Alloy Steels Committee
This specification covers a corrosion-resistant steel in the form of bars, wire, forgings, and forging stock.
AMS F Corrosion and Heat Resistant Alloys Committee
This specification covers a premium aircraft-quality, low-alloy steel in the form of bars, forgings, mechanical tubing, and forging stock.
AMS E Carbon and Low Alloy Steels Committee
This specification covers a titanium alloy in the form of investment castings (see 8.6).
AMS G Titanium and Refractory Metals Committee
This specification covers corrosion-preventive organic substances dissolved or emulsified in a volatile solvent and supplied in the form of a ready-to-use liquid.
AMS B Finishes Processes and Fluids Committee
This specification covers a copper-nickel-tin alloy in the form of bars and rods up to 3.25 inches (83 mm) in nominal thickness (see 8.7).
AMS D Nonferrous Alloys Committee
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.
ACBG Rolling Element Bearing Committee
ACBG Rolling Element Bearing Committee
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
This test can be used to determine the resistance to scuffing of test specimens such as fiberboards, fabrics, vinyl-coated fabrics, leathers, and similar trim materials.
Textile and Flexible Plastics Committee
J1979 DBCJ1979DBC_2026099/7/2026
The SAE J1979 DBC file contains decoding rules for converting raw J1979 data to 'physical values' (Mph, %, etc.). This file lets you easily decode data from heavy duty vehicles (trucks, buses, tractors, etc.). This DBC file download includes: The SAE J1979 DBC file with Includes 2,400+ Parameter Group Numbers (PGNs) and 16,000+ Suspect Parameter Numbers (SPNs), derived from the J1979-2 released in September 2026. One legal license (1 user, 1 PC) matching the DA license DECODE J1979: Convert J1979 data in wide range of software/API tools REVIEW FIRST: Use our CAN ID converter to check if your PGNs are covered CROWD INPUT: Benefit from free corrections based on large user base SAVE HOURS: Avoid manually constructing the DBC file from scratch Improved Accuracy & Reliability A fully standardized DBC file ensures precise signal decoding, eliminating errors and ensuring reliable data interpretation. Interoperability Seamlessly compatible with many different software stacks, enabling frictionless adoption and significantly expanding market reach. Partnership with Vector Informatik GmbH Works seamlessly with Vector’s free software (CANdb++), used by over 90% of the industry, with free download link provided on SAEI’s J1979DBC file landing page. What is a DBC file? A DBC file is a standardized method for storing the "rules" on how to interpret raw CAN bus data. It contains details on what 'signals' (e.g. RPM, Vehicle Speed, …) are contained within which 'messages' (i.e. CAN IDs). In the J1979 standard, messages are referred to as Parameter Group Numbers (PGN) and signals as Suspect Parameter Numbers (SPN). Further, a DBC file includes names, descriptions, positions, and lengths of the signals - as well as how to offset & scale them.
For the mixing of hydroxy-terminated polybutadiene (HTPB) with silicon dioxide particles, this study adopts the Computational Fluid Dynamics (CFD) method to conduct a visual analysis on the fluid flow field characteristics generated by the umbrella-frame impeller (UF impeller) and umbrella-frame combined impeller (UFC impeller). Comparative studies are carried out from the dimensions of particle concentration distribution, fluid flow trend, vorticity, and path line. The results show that compared with the UF impeller, the UFC impeller, equipped with an upper blade structure, enables its generated flow field to cover the entire stirred tank more effectively, significantly improving the solid-liquid mixing efficiency. In addition, the fluid-structure coupled numerical method is used to analyze the structural deformation characteristics and stress distribution law of the impellers. The research findings can provide a reference for the optimization of dispersion and mixing processes of solid particles in high-viscosity fluids.
Li, RuizhengSun, ZhenxingZhang, YanWu, Qiong
Early diagnosis of osteoporosis is crucial for preventing fractures and improving the quality of life of patients. In clinical practice, the mainstream diagnostic methods, such as dual-energy X-ray absorptiometry (DXA), are limited by high equipment costs and ionizing radiation, resulting in a low coverage rate of large-scale early screening. Only less than one-third of brittle fracture patients have received a DXA assessment. To address this issue, this study proposes an innovative diagnostic method based on ultrasonic guided wave technology. This technology is cost-effective and portable, and it overcomes the limitations of X-ray detection in terms of its unsuitability for large-scale early diagnosis. The Young’s modulus and Poisson’s ratio of water are similar to those of soft tissue, so this method utilizes water coupling to simulate the environment of soft tissue around the bone and combines the transverse isotropy of cortical bone, which is an important characteristic that most existing models ignore, to analyze the propagation of guided waves in anisotropic cortical bone. Through the processing of ultrasonic signals using two-dimensional short-time Fourier transform (2D-STFT), the local thickness of cortical bone can be inverted. By establishing a fluid-coupled orthotropic anisotropic plate model, deriving the dispersion equation, solving the theoretical method for the dispersion curve, using the bovine long plate to construct a water-coupled detection platform, and obtaining experimental data to invert the thickness of the bone plate, the local thickness of the bone plate was obtained, proving that this method can effectively reconstruct the thickness changes of anisotropic and variable cross-section cortical bone under simulated soft tissue conditions, with an average relative error of 13%. This lays the foundation for subsequent in vivo experiments and provides a reliable solution for large-scale early osteoporosis screening.
Nong, KexinLi, Bing
The geometrical and velocity scaling behavior of levitation and dragging forces in Electrodynamic suspension (EDS) systems was studied by both analytical and numerical methods, to provide comparisons between designs for both on-board and ground-mounted magnetic components. Effects of system dimension, levitation gap, magnetic field dependence of critical current density, and vehicle velocity were studied. The lift-to-self-weight ratio of two realistic EDS systems and their geometrical scaling were studied numerically.
Shao, NanZhang, ChangShang, LiangYu, Wenjing
Motivated by the negative Poisson’s ratio tetrahedral-trihedral polyhedron (TMP), this study systematically examines the role of self-locking mechanisms in determining the mechanical response and energy absorption capacity of rigid origami metamaterials. Quasi-static compression tests were conducted on specimens exhibiting three distinct geometries (B19, B22, B23) and four wall thicknesses (0.8–2.0 mm). The results of these tests revealed two unique self-locking behaviors. Type I self-locking originates from inter-wall interlocking, characterized by progressively decreasing inter-wall spacing during compression; Type II self-locking originates from interlocking between creases, characterized by creases contacting each other during compression. The fabrication of the specimens was accomplished through the utilization of FDM-based additive manufacturing, employing PEEK material. The results obtained from this study revealed two distinct locking behaviors: It has been demonstrated that type I locking enables sustained deformation without load reduction. In contrast, type II locking has been shown to result in premature collapse and diminished energy absorption capacity. The B22 configuration has been demonstrated to trigger both locking mechanisms concurrently, thereby significantly enhancing performance metrics. This has been evidenced by improvements in both crush force efficiency (CFE) and specific energy absorption (SEA), whilst also delaying densification. In contrast, structures dominated by a single locking mechanism exhibit premature failure (B19) or inefficient energy absorption (B23). These findings emphasize the pivotal role of synchronized self-locking activation and geometric configuration in enhancing impact resistance and energy dissipation, thereby establishing a foundational theoretical framework for the design of advanced metamaterials in protective engineering.
Wu, BaojiWang, HairuiJiang, Heng
This article studies the fatigue damage problem of vehicles under air drop and off-road conditions. First, a multi-body dynamics model of the entire vehicle is established in ADAMS/View to obtain loads and center-of-gravity acceleration under off-road conditions. Subsequently, a finite element model of the vehicle air drop is created in HyperMesh and LS-DYNA to simulate the landing impact and extract loads on key components. By superimposing and spectrum processing the loads from the two conditions, a vehicle load spectrum is compiled and used as input for fatigue analysis. Based on the Miner linear cumulative damage criterion and the material S–N curve, fatigue life predictions are made for key areas of the frame and suspension. The results indicate that the front cross beam and auxiliary longitudinal beam at the bottom of the frame are the most vulnerable components, with the auxiliary longitudinal beam reaching failure under both conditions, but having a limited impact on the overall vehicle operation. Although the peak acceleration under air drop conditions is higher, the off-road conditions lead to more severe cumulative damage due to higher impact frequency and duration. This study provides references for vehicle structural optimization and service reliability enhancement.
Lin, QingpengZhang, QiangFu, LeiHuang, JianbingQin, WeiweiSun, Xiaowang
This study proposes a physics-informed graph convolutional reduced-order model, namely Phys-GCN, for high-fidelity and computationally efficient prediction of steady incompressible flow fields. In Phys-GCN, the incompressible Navier–Stokes equations are embedded into the loss function via residual constraints, such that the spatial feature extraction of graph convolutional networks is integrated with the physics-constrained learning strategy of physics-informed neural networks. This mixed design enables the model to capture complex nonlinear flow features while maintaining a clear level of physical interpretability. Benefiting from the node-edge encoding inherent to graph neural networks, Phys-GCN operates directly on unstructured CFD meshes to learn flow features from graph representations constructed using node attributes and adjacency relationships. In doing so, Phys-GCN dispenses with voxelization or SDF preprocessing and fully preserves the local geometric and topological characteristics of the flow domain. The proposed model is systematically evaluated on steady flows past circular and elliptical cylinders, where the predicted velocity and pressure fields are compared against reference CFD solutions in both interpolation and extrapolation scenarios. Results show that, for all physical quantities, the reconstructed steady flow fields achieve mean relative errors below 5%, exhibiting excellent agreement with the CFD benchmark solutions. After offline training, Phys-GCN achieves inference times that are several orders of magnitude faster than conventional CFD solvers, while maintaining comparable predictive accuracy. These findings demonstrate that Phys-GCN provides an accurate and efficient graph-based and physics-informed surrogate for steady flow-field reconstruction on non-uniform, unstructured meshes, thereby laying a solid foundation for future extensions to more complex three-dimensional and compressible flow configurations.
Xie, HaoranZhou, HaoYu, ChanghaoLi, QiangLiu, TianyuPeng, Jiangzhou