Inadvertent release of petroleum products such as gasoline into the subsurface can initiate ground water contamination, particularly by the toxic, water‐soluble and mobile gasoline components: benzene, toluene and xylenes (BTX). This study was undertaken to examine the processes controlling the rate of movement and the persistence of dissolved BTX in ground water in a shallow, unconfined sand aquifer. Water containing about 7.6 mg/ L total BTX was introduced below the water table and the migration of contaminants through a sandy aquifer was monitored using a dense sampling network. BTX components migrated slightly slower than the ground water due to sorptive retardation. Essentially all the injected mass of BTX was lost within 434 days due to biodegradation. Rates of mass loss were similar for all monoaromatics; benzene was the only component to persist beyond 270 days. Laboratory biodegradation experiments produced similar rates, even when the initial BTX concentration varied. A dominant control over BTX biodegradation was the availability of dissolved oxygen. BTX persisted at the field site in layers low in dissolved oxygen. Decreasing mass loss rates over time observed in the field experiment are not likely due to first‐order deeradation rates, but rather to the persistence of small fractions of BTX mass in anoxic layers.
Computational models of the human neck have been developed to human response in impact scenarios; however, the assessment and validation of such models is often limited to a small number of experimental data sets despite being used to evaluate the efficacy of safety systems and potential for injury risk in motor vehicle collisions. In the present study, a full neck model with active musculature was developed from previously validated motion segment models of the cervical spine. Tissue mechanical properties were implemented from experimental studies, and were not calibrated in any way. The neck model was assessed with experimental studies at three levels of increasing complexity: ligamentous cervical spine in axial rotation, axial tension, frontal impact, and rear impact; post mortem human subject rear sled impact; and human volunteer frontal and lateral sled tests using an open-loop muscle control strategy. The neck model demonstrated good correlation with the experiments ranging from quasi-static to dynamic, assessed using kinematics, kinetics and tissue level response. The contributions of soft tissues, neck curvature and muscle activation were associated with higher stiffness neck response, particularly for low severity frontal impact. Experiments presenting single-value data limited assessment of the model, while complete load history data and cross correlation enabled improved evaluation of the model over the full loading history. Tissue-level metrics exhibited higher variability and therefore lower correlation, also demonstrating a high dependence on the local tissue geometry. Thus, it is critical to assess models at the gross kinematic and the tissue levels.
Advanced computational human body models (HBM) enabling enhanced safety require verification and validation at different levels or scales. Specifically, the motion segments, which are the building blocks of a detailed neck model, must be validated with representative experimental data to have confidence in segment and, ultimately, full neck model response. In this study, we introduce detailed finite element motion segment models and assess the models for quasi-static and dynamic loading scenarios. Finite element segment models at all levels in the lower human cervical spine were developed from scans of a 26-yr old male subject. Material properties were derived from the in vitro experimental data. The segment models were simulated in quasi-static loading in flexion, extension, lateral bending and axial rotation, and at dynamic rates in flexion and extension in comparison to previous experimental studies and new dynamic experimental data introduced in this study. Single-valued experimental data did not provide adequate information to assess the model biofidelity, while application of traditional corridor methods highlighted that data sets with higher variability could lead to an incorrect conclusion of improved model biofidelity. Data sets with continuous or multiple moment-rotation measurements enabled the use of cross-correlation for an objective assessment of the model and highlighted the importance of assessing all motion segments of the lower cervical spine to evaluate the model biofidelity. The presented new segment models of the lower cervical spine, assessed for range of motion and dynamic/traumatic loading scenarios, provide a foundation to construct a biofidelic model of the spine and neck, which can be used to understand and mitigate injury for improved human safety in the future.
Numerical finite element (FE) models of the neck have been developed to simulate occupant response and predict injury during motor vehicle collisions. However, there is a paucity of data on the response of young cervical spine segments under dynamic loading in flexion and extension, which is essential for the development or validation of tissue-level FE models. This limitation was identified during the development and validation of the FE model used in this study. The purpose of this study was to measure the high rotation rate loading response of human cervical spine segments in flexion and extension, and to investigate a new tissue-level FE model of the cervical spine with the experimental data to address a limitation in available data. Four test samples at each segment level from C2-C3 to C7-T1 were dissected from eight donors and were tested to 10 deg of rotation at 1 and 500 deg/s in flexion and extension using a custom built test apparatus. There was strong evidence (p < 0.05) of increased stiffness at the higher rotation rate above 4 deg of rotation in flexion and at 8 deg and 10 deg of rotation in extension. Cross-correlation software, Cora, was used to evaluate the fit between the experimental data and model predictions. The average rating was 0.771, which is considered to demonstrate a good correlation to the experimental data.
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