Open Access

Blast and the resultant overpressure (Blast Overpressure – BOP) exposure can cause negative effects to Force Health and Readiness. Such exposures can pose a significant occupational risk among military members both from enemy action and during training from the operation of artillery, shoulder-launched munitions, mortars, high-calibre weapons, and explosives. Most blast exposures over a career are usually experienced in training. Repeated exposure to Low-Level Blast (LLB) can be detrimental to brain health. The cumulative effects of LLB exposure on brain health is of concern. This is distinct from the acute brain effects observed with exposure to a single, high-level blast. Monitoring and documenting Blast Overpressure (BOP) exposure is critical to better understanding the effect on brain health, and to best protect troops throughout and beyond their military careers. Concerned NATO allies formed a multidisciplinary team of military and civilian specialists within the biomechanical and biomedical fields, as well as from the fields of military occupational exposure and implementation domains to develop ‘Guidelines to Mitigate Military Occupational Brain Health Risks from Repetitive Blast Exposure’ as part of NATO STO-TR-HFM-338 Human Factors and Medicine (HFM). The objective of this team was to identify the best practices as well as produce knowledge to control, minimise, and mitigate the risk of developing brain-related health problems due to blast exposure. The HFM-338 aims to achieve this through the development of three products: 1) Blast Interim Exposure Guidelines that may be used today to mitigate the risk of adverse brain health effects; 2) Operational Guidelines that detail the development of four capabilities including: 1) blast exposure monitoring; 2) capture of health; 3) performance information; and 4) data; analysis of blast exposure, health and performance effects, mitigations and health management strategies; 3) Research and Development Guidelines that identify critical research focus areas which, once addressed, will help us better monitor and understand warfighter brain health.

A reliable stress analysis of a cask for radioactive materials under dynamic load conditions requires a qualified numerical model. For this purpose, the cask is typically discretized using a mesh of finite elements. Certain parts of the mesh usually require a refinement to accurately determine the stresses and strains. Other parts of the mesh may not be of interest with respect to stresses and strains. In such parts, a coarse mesh is sufficient. The mesh density can vary considerably within a cask model. Transitions between regions with different mesh densities can be achieved either by gradually changing the element size or by using tie contact conditions. Such mesh transitions can sometimes lead to complications. In general, a finer mesh can transmit higher-frequency signals than a coarser mesh. The propagation of stress waves through the model may be influenced by the transition zone or by any artificially introduced interface. Stress waves arising within the fine mesh can be partially confined by the surrounding coarse mesh. Poor mesh transitions can therefore cause stress waves to be partially reflected or to change their shape. A thin rod is examined to demonstrate the effects. It is modeled with a varying number of elements or varying size of elements respectively. A stress pulse is applied to one end of the rod, while the opposite end remains free. The generated stress wave is observed at various locations along the rod, and its shape and amplitude are analyzed in relation to the mesh density. Inappropriate meshing can lead to incorrect simulation results without the finite element code issuing warnings or error messages. Such problems are often not obvious. As a result, when using finite element meshing, the maximum size of the finite elements required to model the expected stress wave propagation should not be exceeded. In other words, the correct modeling of stress wave propagation determines the minimum number of finite elements required to mesh a cask component. This study illustrates the ASME Guidance Document “Use of Explicit Finite Element Analysis for the Evaluation of Radioactive Material Transport Packages and Storage Casks in Energy-Limited Impact Events”.

This study develops a Bayesian, uncertainty-aware framework for tendon breakage localization in pre-stressed concrete members using high-resolution data from distributed fber-optic sensors (DFOS). DFOS enable full-feldmonitoring of strain changes on the surface of pre-stressed concrete members due to such failure. A fnite elementmodel (FEM) of an experimental tendon-breakage test is constructed, and model parameters are calibrated proba-bilistically against DFOS measurements. To capture model-form uncertainty (MFU), stochastic perturbations areembedded directly into material parameters, enabling the joint inference of physical properties and MFU withina unifed probabilistic framework. Gaussian Process surrogates are employed to effciently emulate the nonlinearFEM response, supporting computationally tractable Bayesian inference. A divergence-based infuence analy-sis identifes the DFOS measurements that most strongly shape the posterior distributions, providing interpretablediagnostics of sensor informativeness and model adequacy. The calibrated parameters and embedded uncertain-ties are then transferred to a FEM of a full-scale structural confguration, enabling prediction of tendon breakagelocalization under realistic conditions. A separability analysis of the predictive strain distributions quantifes theidentifability of tendon breakage at varying depths, assessing the confdence with which different damage sce-narios can be distinguished given the propagated uncertainties. Results demonstrate that the framework achievesrobust parameter calibration, interpretable diagnostics, and uncertainty-informed damage detection, integratingexperimental data, embedded MFU, and probabilistic modeling. By systematically propagating both experimentaland model uncertainties, the approach supports reliable tendon breakage localization, informed decision-making,and optimal DFOS placement.

Die Nutzung komplexer, nichtlinearer Simulationsverfah-ren in sicherheitsrelevanten Bemessungsaufgaben erfordert eine fundierte Validierung der Modelle sowie die Verifikatio der Implementierung. Vorgestelltwird ein im Rahmen von NFDI4Ing entwickeltes Konzept für eine Benchmarking-Plattform, die softwareunabhängige, maschinenlesbare Modellbeschreibungenmit reproduzierbaren Workflws, dezentraler Veröffentlichung via ROHub und Auswertung über JupyterHub zusammenführt.

The reliable validation and verification of simulation models is a key challenge in computational engineering, especially for complex materials and multi-physics problems. Existing approaches are often computationally intensive and tailored to specific setups, making generalization and objective comparison across models and codes difficult. This paper presents a concept for a reproducible and extensible benchmarking platform designed for any FEM or CFD-based simulation setup, with concrete modeling as a motivating example. The platform aims to facilitate data exchange between experimentalists and simulation researchers, enable transparent comparison of models and implementations, and support referencing models with quality criteria in engineering standards. Key components include a machine-readable database structure for experimental metadata, standardized calibration procedures, and quality metrics that account for uncertainties. The platform supports integration of open-source constitutive model libraries into commercial codes, promoting interoperability and community-driven benchmarking. A federated database infrastructure enables sharing and publication of experimental and simulation results, with full provenance tracking to ensure reproducibility. Interactive visualization tools allow users to query, explore, and compare models and results. While the conceptual framework is well developed, a complete implementation is still in progress. Community contributions are needed to realize a broad set of benchmarks and develop tool-agnostic, machine-readable model definitions. The proposed platform aims to advance reproducibility, transparency, and robustness in computational modeling and simulation practice across engineering domains.