A characteristic average and biofidelity response corridors are commonly used to represent the average behaviour and variability of biomechanical signal data for analysis and comparison to surrogates such as anthropometric test devices and computational models. However, existing methods for computing the characteristic average and corresponding response corridors of experimental data are often customized to specific types or shapes of signal and therefore limited in general applicability. In addition, simple methods such as point-wise averaging can distort or misrepresent important features if signals are not well aligned and highly correlated. In this study, an improved method of computing the characteristic average and response corridors of a set of experimental signals is presented based on arc-length re-parameterization and signal registration. The proposed arc-length corridor method was applied to three literature datasets demonstrating a range of characteristics common to biomechanical data, such as monotonic increasing force-displacement responses with variability, oscillatory acceleration-time signals, and hysteretic load-unload data. The proposed method addresses two challenges in assessing experimental data: arc-length re-parameterization enables the assessment of complex-shaped signals, including hysteretic load-unload data, while signal registration aligned signal features such as peaks and valleys to prevent distortion when determining the characteristic average response. The arc-length corridor method was shown to compute the characteristic average and response corridors for a wide range of biomechanical data, while providing a consistent statistical framework to characterize variability in the data. The arc-length corridor method is provided to the community in the freely available and open-source software package, ARCGen.

This work documents the development of a tool to perform automated parameter fitting of constitutive material models. Specific to this work is the fitting of a Swift hardening rule and isotropic linear plasticity model to aluminum 2024-T351, C36000 brass, and C10100 copper. Material characterization was conducted through the use of compressive, cold upsetting tests. A noncontact, optical displacement measurement system was applied to measure the axial and radial deformation of the test specimens. Nonlinear optimization techniques were then applied to tune a finite element model to match experimental results through the optimization of material model parameters as well as frictional coefficient. The result is a system, which can determine constitutive model parameters rapidly and without user interaction. While this tool provided material parameters for each material and model tested, the quality of the fit varied depending on how appropriate the constitutive model was to the material's actual plastic behavior. Aluminum's behavior proved to be an excellent match to the Swift hardening rule while the behavior of brass and copper was described better by the linear plasticity model.

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BackgroundInterlaminar delamination is a common damage mechanism in composite laminates that can lead to structural failure. Assessment using contemporary numerical modeling techniques requires delamination behavior as a traction-separation response. However, existing experimental characterization approaches are not well suited to support these modeling techniques as specimens were developed to assess single delamination parameters, not a full traction-separation response, or utilize analysis schemes that require knowledge of material properties. ObjectiveTo develop a test specimen and data analysis methodology to directly measure the traction-separation response of Mode I delamination in a laminated fiber-reinforced polymer (FRP) composite, including strength, toughness, and damage response. 2 MethodsThe proposed composite Rigid Double Cantilever Beam (cRDCB) specimen is comprised of a [0]_4 unidirectional E-glass/epoxy laminate co-cured to rigid metallic adherends. Traction-separation response was assessed directly from measured force and displacement behavior using a closed-form analysis scheme that does not require a priori knowledge of composite material properties. Standard double cantilever beam (DCB) tests were performed for comparison. ResultsThe cRDCB specimen captured early damage initiation and progression in greater detail than the DCB, with measured strain energy release rates agreeing well between the two approaches. The cRDCB also captured the effects of large-scale damage mechanisms such as fiber bridging. The measured traction-separation responses are suitable for scenarios where prediction of the initiation and early damage response of delamination is important. ConclusionsCombined with a data processing technique, a single cRDCB test enabled measurement of the full Mode I tractionseparation response. In addition, the cRDCB provided high-resolution and could detect early-stage Mode I delamination damage in FRP laminates. The measured traction-separation responses can be directly inputted into cohesive zone models to predict the initiation and progression of Mode I delamination.