This paper presents a practical and cost-effective method for in-motion estimation of a vehicle’s CoG position in all three directions by measuring accelerations during two types of maneuvers: braking (longitudinal and vertical CoG estimation) and cornering (lateral and vertical CoG estimation). The proposed method’s main advantage is that it does not require knowledge of vehicle characteristics, such as mass distribution, suspension geometry, or inertia parameters. It relies solely on the known distances between the sensors and their positions relative to a defined reference point on the vehicle. To validate the developed method, experimental tests were conducted on a prototype vehicle, varying the load conditions for the proposed driving scenarios. The CoG position obtained from dynamic maneuvers was compared with reference values derived from static measurements. The results showed that the proposed method could estimate the CoG position with an average error of 3% in the longitudinal direction, a maximum error of 12% in the lateral direction, and a maximum error of 14% in the vertical direction.

Monitoring large critical infrastructures is a highly complex and costly task. The use of a network of sensors to aid in the detection and identification of potential anomalies is therefore an important step towards easing maintenance effort while maintaining operational soundness. To address this challenge, a monitoring system was developed and installed in a seaport drawbridge. The structural parameters monitored during operation can be used to assess the bridge’s structural behavior. This provides the ability to identify potential anomalies that could lead to its failure at an early stage, allowing for the better planning of maintenance interventions, saving time and money. In this paper, the monitoring system will be presented and the employed signal identification and analysis methods will be described.

The development of wave energy converters (WECs) requires experimental tests at increasing scales. During the process, wave tanks eventually become inadequate due to size limitations. This study proposes a structured methodology to assess the feasibility of using seaports as testbeds for emerging WEC models, supporting innovation to accelerate sustainable energy transition. The method includes evaluating model requirements, ocean wave conditions at the port entrance, local wind-generated waves, tides, bathymetry, seabed composition, wave propagation within the port, and operational constraints, to identify viable test zones. The methodology was applied to the Port of Sines, Portugal, considering a 1:10 REEFS WEC model. Three potential sites were identified. Shelter is adequate but wave conditions matching the model’s requirements only occur approximately 100 hours per summer, due to the rarity of short-period ocean waves. Wind-generated waves contribute marginally, limited by the short fetch. Upscaling the model may allow testing under longer-period waves, which occur more frequently. A key limitation of port-based testing is the lack of environmental control. Despite statistical planning, suitable conditions during test campaigns cannot be guaranteed. This trade-off offsets the benefits of unrestricted space and no need for a wave-maker. The methodology proved effective, simplifying site assessment and saving resources.

This article proposes a methodology to assess the feasibility of using seaports as testbeds for emerging WEC models, supporting innovation to accelerate sustainable energy transition. The development of wave energy converters (WECs) requires experimental tests at increasing scales, with wave tanks eventually becoming inadequate due to size limitations. The method includes evaluating model requirements, ocean wave conditions at the port entrance, local wind-generated waves, tides, bathymetry, seabed composition, wave propagation within the port, and operational constraints to identify viable test zones. The methodology was applied to the Port of Sines, Portugal, considering a 1:10 REEFS WEC model. Three potential sites were identified. Shelter is adequate but wave conditions matching the model’s requirements (periods from 1.9 to 3.8 s) only occur approximately 100 h per summer. Local wind-generated waves contribute marginally, limited by the short fetch. Upscaling the model (larger than 1:10) may allow testing under longer-period waves, which occur more frequently. A key limitation of port-based testing is the lack of environmental control. Despite statistical planning, suitable conditions during test campaigns cannot be guaranteed. This trade-off offsets the benefits of unrestricted space and no need for a wave-maker. The methodology proved effective, simplifying site assessment and saving resources.