Marcias Martinez

Firefighting tasks are strenuous and injury-prone. This study developed a biomechanical dataset from 20 professional firefighters performing equipment carry, hose drag, body drag and stair climb, with and without gear, using motion capture and musculoskeletal simulations. Biomechanical loading and activity asymmetry were analysed. Gear effects were found to be task-dependent: trunk muscle activity increased across activities, hip joint reaction forces consistently rose and ankle torque increased only during body drag. In stair climb, ankle torque decreased with gear, while knee and hip torques increased, indicating greater reliance on proximal joints. Leg muscle activity rose bilaterally in all tasks except hose drag. Side-specific patterns also emerged: across all activities, the left knee consistently exhibited higher torques, while ankle and knee reaction forces were greater on the right. During dragging tasks, more power was generated from the left upper body. This dataset and analysis provide insights for ergonomics, training and injury prevention.

Aerial manipulation is an important field of robotics with wide-ranging applications in maintenance, construction, and inspection. However, complex aerial manipulation tasks are often limited to large drones due to the high mass of existing robotic arms, a large potion of which is contained within its actuators. Shape memory alloy (SMA) actuators provide a lightweight alternative to actuate a robotic arm, but have seen little use due to the lack of a robotic arm with suitable strength and range. The strength of existing SMA-actuated arms cannot easily be increased, as increasing the number or size of the actuators drastically increases complexity. This paper addresses these limitations by developing a lightweight, 3-DOF robotic arm actuated by shape memory alloy wires capable of achieving aerial manipulation tasks. Topology optimization was applied to arm links to reduce mass. The resulting arm is capable of exerting over 25 times the torque of existing SMA-actuated arms. Control is achieved using an adaptive proportional-integral (PI) controller, the performance of which was experimentally measured through a series of step responses and path following tasks. The controller was found to be effective in manipulating masses of up to 300 g, roughly three quarters the mass of the arm itself.

Two shape-sensing algorithms, the calibration matrix (CM) method and the inverse Finite Element Method (iFEM), were compared on their ability to accurately reconstruct displacements, strains, and loads and on their computational efficiency. CM reconstructs deformation through a linear combination of known load cases using the sensor data measured for each of these known load cases and the sensor data measured for the actual load case. iFEM reconstructs deformation by minimizing a least-squares error functional based on the difference between the measured and numerical values for displacement and/or strain. In this study, CM is covered in detail to determine the applicability and practicality of the method. The CM results for several benchmark problems from the literature were compared to the iFEM results. In addition, a representative aerospace structure consisting of a twisted and tapered blade with a NACA 6412 cross-sectional profile was evaluated using quadratic hexahedral solid elements with reduced integration. Both methods assumed linear elastic material conditions and used discrete displacement sensors, strain sensors, or a combination of both to reconstruct the full displacement and strain fields. In our study, surface-mounted and distributed sensors throughout the volume of the structure were considered. This comparative study was performed to support the growing demand for load monitoring, specifically for applications where the sensor data is obtained from discrete and irregularly distributed points on the structure. In this study, the CM method was shown to achieve greater accuracy than iFEM. Averaged over all the load cases examined, the CM algorithm achieved average displacement and strain errors of less than 0.01%, whereas the iFEM algorithm had an average displacement error of 21% and an average strain error of 99%. In addition, CM also achieved equal or better computational efficiency than iFEM after initial set-up, with similar first solution times and faster repeat solution times by a factor of approximately 100, for hundreds to thousands of sensors.

Safety and prevention of injuries should always be considered in a firefighting environment due to the hazardous conditions experienced on the fireground. These hazardous environmental conditions lead to an increased risk of contracting job-related injuries and illnesses. This review article focuses on evaluating from a statistical perspective the potential solutions found in the literature and how they decrease the likelihood and impact of occupational firefighting injuries. Investigating, identifying, and prioritizing the most common activities leading to injury, the nature of injury, and the body parts affected is a vital step in the implementation of preventive solutions. The scientific community has conducted various studies to evaluate the main injuries and injury profiles commonly suffered by firefighters. Researchers have conducted many independent studies on firefighter communities in the United States, while others have referenced national databases from sources such as the National Fire Protection Association, the Bureau of Labor Statistics, and the National Electronic Injury Surveillance System. Unfortunately, the results of these independent studies lacked standardization in survey categories and terminology, impairing the ability to obtain a clear consensus among studies on the primary nature of injuries, the body parts injured, and the activities contributing to these injuries. Consequently, this review article performed a comparative statistical analysis of published data between 1992 and 2020 to define and rank the most common work scenarios where firefighters were likely to be injured, the most common types of injuries, the parts of the body affected, and the activities that most contribute to United States firefighter injuries as documented in both national databases and independent research surveys. The statistical analysis consisted of determining the mean, standard deviation, confidence intervals (95%), and coefficients of variation for the reported data. The present study identified that despite the preventative measures taken by many organizations in the firefighting community, strains and sprains were still the leading type of injury reported from all the databases under this analysis.

A smoothed-particle hydrodynamics (SPH) modeling technique was applied in conjunction with the Johnson–Holmquist (JH-2) ceramic material constitutive model to replicate the fracture of soda-lime glass in a milling manufacturing process. Four-point bending tests were conducted to validate the soda-lime glass bulk material properties prior to its implementation in ABAQUS CAE™ Explicit (Version 2017). The JH-2 material constitutive model replicated the fracture load and time to fracture for the four-point bending load cases as per ASTM C158. This study showed how SPH in combination with a validated JH-2 material model in a milling process simulation was able to replicate the output size distribution at 5000 and 6500 revolutions per minute (RPM). For operations at 3000 RPM or lower, it was shown that it is necessary to include additional effects in the model, such as fluid–structure interactions, to improve the correlation with the experimental data. The SPH model was validated through an experimental campaign using high-speed cameras and a particle Camsizer. The experimental results clearly indicate a direct relation between the mill’s RPM and the output particle size distribution.

The primary objective of this study was to evaluate the capability of a distributed fiber optic sensor to capture in situ dynamic transient strain formation during and post-weldment on the surface of a steel plate. The study involved a vertical manual weld of a bead on a plate on a 300 mm × 300 mm × 6.35 mm A36 steel plate (European equivalent S235J2; Chinese equivalent Q235B) clamped at the corners. A fiber optic distributed sensor was used to measure the surface total and thermal strains on the welded side of the plate adjacent to the weld path. Experimental results show a complex behavior of strain changes during the welding process and the residual strain formation post-welding. This study aims to document the use of distributed fiber optic sensing techniques in welding applications. Validations of the experimental data were performed using VrWeld, a commercial software framework for computational weld mechanics, and an iPhone FLIR One Pro. thermographic camera. The experimental results demonstrated that although distributed fiber optic sensing based on Rayleigh backscattering is an appropriate and useful technique for total strain measurements, the manufacturing and the materials used for the thermal sensors are critical in obtaining optimal results. Finally, this study highlights the challenges encountered in synchronizing large experimental data sets captured with different instruments with computational welding mechanic (CWM) models.

Structural Health Monitoring (SHM) aims to shift aircraft maintenance from a time-based to a condition-based approach. Within all the SHM techniques, Acoustic Emission (AE) allows for the monitoring of large areas by analyzing Lamb waves propagating in plate like structures. In this study, the authors proposed a Time Reversal (TR) methodology with the aim of reconstructing an original and unaltered signal from an AE event. Although the TR method has been applied in Narrow-Band (NwB) signal reconstruction, it fails when a Broad-Band (BdB) signal, such as a real AE event, is present. Therefore, a novel methodology based on the use of a Frequencies Compensation Transfer Function (FCTF), which is capable of reconstructing both NwB and real BdB signals, is presented. The study was carried out experimentally using several sensor layouts and materials with two different AE sources: (i) a Numerically Built Broadband (NBB) signal, (ii) a Pencil Lead Break (PLB). The results were validated numerically using Abaqus/CAE^TM with the implementation of absorbing boundaries to minimize edge reflections.