In recent years, there has been a significant increase in research on hydrogen due to the urgent need to move away from carbon-intensive energy sources. This transition highlights the critical role of hydrogen storage technology, where hydrogen tanks are crucial for achieving cleaner energy solutions. This paper aims to provide a general overview of hydrogen treatment from a mechanical viewpoint, and to create a comprehensive review that integrates the concepts of hydrogen safety and storage. This study explores the potential of hydrogen applications as a clean energy alternative and their role in various sectors, including industry, automotive, aerospace, and marine fields. The review also discusses design technologies, safety measures, material improvements, social impacts, and the regulatory landscape of hydrogen storage tanks and safety technology. This work provides a historical literature review up to 2014 and a systematic literature review from 2014 to the present to fill the gap between hydrogen storage and safety. In particular, a fundamental feature of this work is leveraging systematic procedural techniques for performing an unbiased review study to offer a detailed analysis of contemporary advancements. This innovative approach differs significantly from conventional review methods, since it involves a replicable, scientific, and transparent process, which culminates in minimizing bias and allows for highlighting the fundamental issues about the topics of interest and the main conclusions of the experts in the field of reference. The systematic approach employed in the paper was used to analyze 55 scientific articles, resulting in the identification of six primary categories. The key findings of this review work underline the need for improved materials, enhanced safety protocols, and robust infrastructure to support hydrogen adoption. More importantly, one of the fundamental results of the present review analysis is pinpointing the central role that composite materials will play during the transition toward hydrogen applications based on thin-walled industrial vessels. Future research directions are also proposed in the paper, thereby emphasizing the importance of interdisciplinary collaboration to overcome existing challenges and facilitate the safe and efficient use of hydrogen.

In this investigation, the nonlinear swing-up problem associated with the cart-pole system modeled as a multibody dynamical system is solved by developing a deep Reinforcement Learning (RL) controller. Furthermore, the sensitivity analysis of the deep RL controller applied to the cart-pole swing-up problem is carried out. To this end, the influence of modifying the physical properties of the system and the presence of dry friction forces are analyzed employing the cumulative reward during the task. Extreme limits for the modifications of the parameters are determined to prove that the neural network architecture employed in this work features enough learning capability to handle the task under modifications as high as 90% on the pendulum mass, as well as a 100% increment on the cart mass. As expected, the presence of dry friction greatly affects the performance of the controller. However, a post-training of the agent in the modified environment takes only thirty-nine episodes to find the optimal control policy, resulting in a promising path for further developments of robust controllers.

The goal of this investigation is to construct a computational procedure for identifying the modal parameters of linear mechanical systems. The methodology employed in the paper is based on the Eigensystem Realization Algorithm implemented in conjunction with the Observer/Kalman Filter Identification method (ERA/OKID). This method represents an effective and efficient system identification numerical procedure based on the time domain. The algorithm developed in this work is tested by means of numerical experiments on a full-car vehicle model. To this end, the modal parameters necessary for the design of active and semi-active suspension systems are obtained for the vehicle system considered as an illustrative example. In order to analyze the performance of the methodology developed in this investigation, the system identification numerical procedure was tested considering two case studies, namely a full state measurement and an incomplete state measurement. As expected, the numerical results found for the identified dynamical model showed a good agreement with the modal parameters of the mechanical system model. Furthermore, numerical results demonstrated that the proposed method has good performance considering a scenario in which the signal-to-noise ratio of the input and output measurements is relatively high. The method developed in this paper can be effectively used for solving important engineering problems such as the design of control systems for road vehicles.

In this paper, a new computational algorithm for the numerical solution of the adjoint equations for the nonlinear optimal control problem is introduced. To this end, the main features of the optimal control theory are briefly reviewed and effectively employed to derive the adjoint equations for the active control of a mechanical system forced by external excitations. A general nonlinear formulation of the cost functional is assumed, and a feedforward (open-loop) control scheme is considered in the analytical structure of the control architecture. By doing so, the adjoint equations resulting from the optimal control theory enter into the formulation of a nonlinear differential-algebraic two-point boundary value problem, which mathematically describes the solution of the motion control problem under consideration. For the numerical solution of the problem at hand, an adjoint-based control optimization computational procedure is developed in this work to effectively and efficiently compute a nonlinear optimal control policy. A numerical example is provided in the paper to show the principal analytical aspects of the adjoint method. In particular, the feasibility and the effectiveness of the proposed adjoint-based numerical procedure are demonstrated for the reduction of the mechanical vibrations of a nonlinear two degrees-of-freedom dynamical system.