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The purpose of this paper is to propose a new simplified numerical model, based on a very compact semi-empirical formulation, able to simulate the fluid dynamics behaviors of an electrohydraulic servovalve taking into account several effects due to valve geometry (e.g. flow leakage between spool and sleeve) and operating conditions (e.g. variable supply pressure or water hammer).

The proposed model simulates the valve performance through a simplified representation, deriving from the linearized approach based on pressure and flow gains, but able to evaluate the mutual interaction between boundary conditions, pressure saturation and leak assessment. Its performance was evaluated comparing with other fluid dynamics numerical models (a detailed physics-based high-fidelity one and other simplified models available in the literature).

Although still showing some limitations attributable to its simplified formulation, the proposed model overcomes several deficiencies typical of the most common fluid dynamic models available in the literature, describing the water hammer and the nonlinear dependence of the delivery differential pressure with the spool displacement.

Although still based on a simplified formulation with reduced computational costs, the proposed model introduces a new nonlinear approach that, approximating with suitable precision the pressure-flow fluid dynamic characteristic of a servovalve, overcomes the shortcomings typical of such models.

This study aims to investigate the suitability of a multi-step prototyping strategy for producing pneumatic rotary vane actuators (RVAs) for the development of lightweight robots and actuation systems.

RVAs typically have cast aluminum housings and injection-molded seals that consist of hard thermoplastic cores and soft elastomeric overmolds. Using a combination of additive manufacturing (AM), computer numerical control (CNC) machining and elastomer molding, a conventionally manufactured standard RVA was replicated. The standard housing design was modified, and polymeric replicas were obtained by selective laser sintering (SLS) or PolyJet (PJ) printing and subsequent CNC milling. Using laser-sintered molds, actuator seals were replicated by overmolding laser-sintered polyamide cores with silicone (SIL) and polyurethane (PU) elastomers. The replica RVAs were subjected to a series of leakage, friction and durability experiments.

The AM-based prototyping strategy described is suitable for producing functional and reliable RVAs for research and product development. In a representative durability experiment, the RVAs in this study endured between 40,000 and 1,000,000 load cycles. Frictional torques were around 0.5 Nm, which is 10% of the theoretical torque at 6 bar and comparable to that of the standard RVA. Models and parameters are provided for describing the velocity-dependent frictional torque. Leakage experiments at 10,000 load cycles and 6 bar differential pressure showed that PJ housings exhibit lower leakage values (6.8 L/min) than laser-sintered housings (15.2 L/min), and PU seals exhibit lower values (8.0 l/min) than SIL seals (14.0 L/min). Combining PU seals with PJ housings led to an initial leakage of 0.4 L/min, which increased to only 1.2 L/min after 10,000 load cycles. Overall, the PU material used was more difficult to process but also more abrasion- and tear-resistant than the SIL elastomer.

More work is needed to understand individual cause–effect relationships between specific design features and system behavior.

To date, pneumatic RVAs have been manufactured by large-scale production technologies. The absence of suitable prototyping strategies has limited the available range to fixed sizes and has thus complicated the use of RVAs in research and product development. This paper proves that functional pneumatic RVAs can be produced by using more accessible manufacturing technologies and provides the tools for prototyping of application-specific RVAs.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

In fire resistance tests (FRTs) of building materials, a crucial criterion to pass the test procedure is to avoid the leakage of the hot flue gases caused by gaps and cracks occurring due to the thermal exposure. The present study's aim is to calculate the deformation of a steel door, which is embedded within a wall made of bricks, and qualitatively determine the flue gas leakage.

A computational fluid dynamics/finite element method (CFD/FEM) coupling was introduced representing an intermediate approach between a one-way and a full two-way coupling methodology, leading to a simplified two-way coupling (STWC). In contrast to a full two way-coupling, the heat transfer through the steel door was simulated based on a one-way approach. Subsequently, the predicted temperatures at the door from the one-way simulation were used in the following CFD/FEM simulation, where the fluid flow inside and outside the furnace as well as the deformation of the door were calculated simultaneously.

The simulation showed large gaps and flue gas leakage above the door lock and at the upper edge of the door, which was in close accordance to the experiment. Furthermore, it was found that STWC predicted similar deformations compared to the one-way coupling.

Since two-way coupling approaches for fluid/structure interaction in fire research are computationally demanding, the number of studies is low. Only a few are dealing with the flue gas exit from rooms due to destruction of solid components. Thus, the present study is the first two-way approach dealing with flue gas leakage due to gap formation.

This study aims to investigate the potential of using polymer multi-material additive manufacturing (MMAM) to produce miniature hydraulic piston actuators combining rigid structures and flexible seals. Such actuators offer great potential for medical robots in X-ray and magnetic resonance environments, where conventional piston actuators cannot be used because of safety issues caused by metal components.

Hydraulic pistons with two different integrated flexible seal shapes are designed and manufactured using MMAM. Design 1 features a ring-shaped seal made from a flexible material that is printed on the surface of the rigid piston shaft. Design 2 appears identical from the outside, yet an axial opening in the piston shaft is added to enable self-reinforced sealing as fluid pressure increases. For both designs, samples with three different outer diameters are fabricated leading to a total of six different piston versions. The pistons are then evaluated regarding leakage, friction and durability.

Measurement results show that the friction force for Design 2 is lower than that of Design 1, making Design 2 more suitable for the intended application. None of the versions of Design 2 shows leakage for pressures up to 1.5 MPa. For Design 1, leak-tightness varies with the outer diameter, yet none of the versions is consistently leak-tight at 1.5 MPa. Furthermore, the results show that prolonged exposure to water decreases the durability of the flexible material significantly. The durability the authors observe may, however, be sufficient for short-term or single-use devices.

The authors investigate a novel design approach for hydraulic piston actuators based on MMAM. These actuators are of particular interest for patient-specific medical devices used in radiological interventions, where metal-free components are required to safely operate in X-ray and magnetic resonance environments. This study may serve as a basis for the development of new actuators, as it shows a feasible solution, yet pointing out critical aspects such as the influence of small geometry changes or material performance changes caused by water absorption.

The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model parametrization in transformer grey box topology models.

Two transformer topology models with two different hysteresis models are used together with a DC hysteresis measurement via the power transformer terminals to parameterize the hysteresis models by means of an optimization. The calculated current waveform with the derived model in the transformer no-load condition is compared to the measured no-load current waveforms to validate the model.

The proposed DC hysteresis measurement via the power transformer terminals is suitable to parametrize two hysteresis models implemented in transformer topology models to calculate the no-load current waveforms.

Different approaches for the measurement and utilization of transformer terminal measurements for the hysteresis model parametrization are discussed in literature. The transformer topology models, derived with the presented approach, are able to reproduce the transformer no-load current waveform with acceptable accuracy.

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

The European Union's Emissions Trading System (EU ETS), which is already one of the EU's most impactful instruments for reducing greenhouse gases (GHGs), will soon include the maritime transport industry. Although ports are this industry's most environmental-friendly component, there are still some barriers to including ports in the system. Therefore, the purpose of the study is to identify these barriers and to reveal the barriers' interrelationships.

The study was conducted by identifying barriers from a literature review before analyzing the barriers with the Fuzzy DEMATEL method. Finally, based on the Complex Adaptive System Approach, various solutions are proposed to overcome these barriers.

The identified barriers were grouped into cause-and-effect groups. Two barriers, namely long payback period and high investment costs, were evaluated as triggers of the model while the others were more sensitive to the model.

This study only includes the perceptions of green certificated ports in Türkiye. The results revealed an expectation that elimination of financial concerns will alleviate other barriers to including ports in the system. The study's findings can guide port managers on the integration of the managers' processes into the system.

This study provides novel findings regarding the relationships between barriers hindering ports from involvement in the EU ETS.

The purpose of this work is to bridge FL and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. FL is an emerging collaborative machine learning technique that trains a model across multiple devices or servers holding private data samples without exchanging their data. The locally trained results are aggregated by a centralized server in a privacy-preserving way. However, there is an assumption where the centralized server is trustworthy, which is impractical. Fortunately, blockchain technology has opened a new era of data exchange among trustless strangers because of its decentralized architecture and cryptography-supported techniques.

In this study, the author proposes a novel design of a smart agent inspired by the smart contract concept. Specifically, based on the proposed smart agent, a fully decentralized, privacy-preserving and fair deep learning blockchain-FL framework is designed, where the agent network is consistent with the blockchain network and each smart agent is a participant in the FL task. During the whole training process, both the data and the model are not at the risk of leakage.

A demonstration of the proposed architecture is designed to train a neural network. Finally, the implementation of the proposed architecture is conducted in the Ethereum development, showing the effectiveness and applicability of the design.

The author aims to investigate the feasibility and practicality of linking the three areas together, namely, multi-agent system, FL and blockchain. A blockchain-FL framework, which is based on a smart agent system, has been proposed. The author has made several contributions to the state-of-the-art. First of all, a concrete design of a smart agent model is proposed, inspired by the smart contract concept in blockchain. The smart agent is autonomous and is able to disseminate, verify the information and execute the supported protocols. Based on the proposed smart agent model, a new architecture composed by these agents is formed, which is a blockchain network. Then, a fully decentralized, privacy-preserving and smart agent blockchain-FL framework has been proposed, where a smart agent acts as both a peer in a blockchain network and a participant in a FL task at the same time. Finally, a demonstration to train an artificial neural network is implemented to prove the effectiveness of the proposed framework.