Objectives: Aim of the work is to present the feasibility of using an Instrumented Human Head Surrogate (IHHS-1) during multidirectional impacts while wearing a modern ski helmet. The IHHS-1 is intended to provide reliable and repeatable data for the experimental validation of FE models and for the experimental evaluation of modern helmets designed to enhance the degree of protection against multidirectional impacts. Design: The new IHHS-1 includes 9 triaxial MEMS accelerometers embedded in a silicone rubber brain, independently molded and presenting lobes separation and cerebellum, placed into an ABS skull filled with surrogate cerebrospinal fluid. A triaxial MEMS gyroscope is placed at the brain center of mass. Intracranial pressure can be detected by eight pressure sensors applied to the skull internal surface along a transversal plane located at the brain center of mass and two at the apex. Additional MEMS sensors positioned over the skull and the helmet allow comparison between outer and inner structure kinematics and surrogate CSF pressure behavior. Methods: The IHHS-1 was mounted through a Hybrid III neck on a force platform and impacted with a striker connected to a pendulum tower, with the impact energies reaching 24J. Impact locations were aligned with the brain center of mass and located in the back (sagittal axis), right (90 • from sagittal axis), back/right (45 •), and front right (135 •) locations. Following dynamic data were collected: values of the linear accelerations and angular velocities of the brain, skull and helmet; intracranial pressures inside the skull. Results: Despite the relatively low intensity of impacts (HIC at skull max value 46), the skull rotational actions reached BrIC values of 0.33 and angular accelerations of 5216 rad/s 2 , whereas brain angular acceleration resulted between 1,44 and 2,1 times lower with similar values of BrIC. Conclusions: The IHHS-1 is a physical head surrogate that can produce repeatable data for the interpretation of inner structures behavior during multidirectional impacts with or without helmets of different characteristics.

Additive Manufacturing (AM) brought a revolution in parts design and production. It enables the possibility to obtain objects with complex geometries and to exploit structural optimization algorithms. Nevertheless, AM is far from being a mature technology and advances are still needed from different perspectives. Among these, the literature highlights the need of improving the frameworks that describe the design process and taking full advantage of the possibilities offered by AM. This work aims to propose a workflow for AM guiding the designer during the embodiment design phase, from the engineering requirements to the production of the final part. The main aspects are the optimization of the dimensions and the topology of the parts, to take into consideration functional and manufacturing requirements, and to validate the geometric model by computer-aided engineering software. Moreover, a case study dealing with the redesign of a piston rod is presented, in which the proposed workflow is adopted. Results show the effectiveness of the workflow when applied to cases in which structural optimization could bring an advantage in the design of a part and the pros and cons of the choices made during the design phases were highlighted.

Nowadays, topology optimization and lattice structures are being re-discovered thanks to Additive Manufacturing technologies, that allow to easily produce parts with complex geometries.The primary aim of this work is to provide an original contribution for geometric modeling of conformal lattice structures for both wireframe and mesh models, improving previously presented methods. The secondary aim is to compare the proposed approaches with commercial software solutions on a piston rod as a case study.The central part of the rod undergoes size optimization of conformal lattice structure beams diameters using the proposed methods, and topology optimization using commercial software tool. The optimized lattice is modeled with a NURBS approach and with the novel mesh approach, while the topologically optimized part is manually remodeled to obtain a proper geometry. Results show that the lattice mesh modelling approach has the best performance, resulting in a lightweight structure with smooth surfaces and without sharp edges at nodes, enhancing mechanical properties and fatigue life.

It has been recognized that parts produced by additive manufacturing with surfaces in the “as‐built” state exhibit reduced fatigue properties. On the other hand, post‐process surface finishing is expensive and often unfeasible due to the complexity of parts. Therefore, surface quality parameters must be considered when designing as‐built parts for structural applications. This work investigates the as‐built surface topography of Inconel 718 samples manufactured via laser powder bed fusion (L‐PBF) with three different production systems (SLM 280HL, EOS M290, and RENISHAW AM250) and discusses their respective experimental fatigue behavior. The aim of the investigation is to identify a link between the fatigue response of L‐PBF IN718 alloy without post fabrication finishing and the surface morphology; a preliminary comparison among the main surface roughness parameters and the fatigue strength is reported and further investigations are planned to find a univocal correlation. Samples with a mean height (Sa) of approximately 20 μm exhibit lower fatigue strength than those with Sa of approximately 5 μm. Skewness (Ssk) and kurtosis (Sku) are instead found to be discriminating parameters when comparing surfaces with relatively low surface roughness (Sa 5 μm), with higher values of Ssk and Sku associated with inferior fatigue performance.