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Gauging Issues
Published in Simon Iwnicki, Maksym Spiryagin, Colin Cole, Tim McSweeney, Handbook of Railway Vehicle Dynamics, 2019
In the late 1970s and 1980s, cost engineering became prevalent in Britain, particularly in the area of track maintenance. A given ride quality can be achieved by maintaining high-quality track geometry or by providing softer vehicle suspensions. The former solution is particularly expensive, since, as track quality is raised, the cost of maintaining it increases exponentially. The new generation of rollingstock then being commissioned could readily be given suspension capable of providing adequate ride comfort on poorer track. Air suspension provided this mechanism but at the expense of having greater dynamic movement (movement associated with the speed of the vehicle). The methodologies described would have meant that the infrastructure would have required enlargement to maintain clearance. However, it was recognised that by relating kinematic movement to operating environment, the locations where enlarged infrastructure was required could be minimised. A publication known as ‘Design Guide BASS 501’ [8] provided a methodology whereby the ‘kinematic envelope’ of a vehicle (the space required by a given vehicle, moving at speed) at a specific location could be manually calculated from a number of input parameters. The techniques used are quasi-static, equating dynamic conditions to stationary forces, and are generally conservative. Nevertheless, the techniques were very successful in allowing larger trains to operate on restrictive infrastructure at a minimal cost. In particular, a derivation of the technique has allowed tilting trains to be designed for Britain that would otherwise have been of a non-viable cross-section if traditional gauging rules were applied.
Data collection, processing, and database management
Published in Zongzhi Li, Transportation Asset Management, 2018
Pavement roughness: Pavement roughness measurements indicate whether irregularities in the pavement surface adversely affect the ride quality of a vehicle. Roughness is an important characteristic because it can also affect the vehicle delay costs, fuel consumption, and deterioration rate of vehicles. Roughness currently is quantified in terms of either present serviceability rating (PSR) or international roughness index (IRI).
Assessment of the efficiency of pavement surface rehabilitation techniques
Published in Andreas Loizos, Imad L. Al-Qadi, A. (Tom) Scarpas, Bearing Capacity of Roads, Railways and Airfields, 2017
Surface roughness is related to the irregularities in the road surface that can also adversely affect ride quality. The most common parameter used globally in surface roughness evaluation is the International Roughness Index (IRI), which is obtained from measured longitudinal road profiles (Sayers et al. 1986).
Influence of surface distresses on smartphone-based pavement roughness evaluation
Published in International Journal of Pavement Engineering, 2021
L. Janani, V. Sunitha, Samson Mathew
Road infrastructure can be undoubtedly considered as the most important of all public assets as it plays a crucial role in providing ease of access to education, health, social and employment services. However, with continued usage, the condition of every pavement deteriorates over a period of time. Therefore, the importance of routine pavement maintenance as a measure to increase its service life and minimise further deterioration, is on par with that of the construction of new pavements. Accurate and timely assessment of pavement condition is the sine qua non for an effective pavement maintenance and management system. Routine condition assessment data serves as a valuable source of information in anticipating and prioritising the pavement rehabilitation needs (Janani et al. 2019). Structural adequacy, roughness, distress, drainage adequacy, material durability, the extent of past maintenance activities, etc. are periodically evaluated to determine the overall pavement condition (Shah et al. 2013). The expression of irregularities present on the pavement surface, i.e. the road roughness is considered as the most critical one as it not only affects the pavement’s ride quality but also increases fuel consumption, vehicle delays and maintenance costs.
Pavement serviceability evaluation using whole body vibration techniques: a case study for urban roads
Published in International Journal of Pavement Engineering, 2021
Luis Fuentes, Rafael Camargo, Gilberto Martínez-Arguelles, Julius J. Komba, Bhaven Naik, Lubinda F. Walubita
Ride quality refers to the level of comfort experienced by occupants of vehicles as they travel on a section of roadway. This level of comfort is strongly dependent on the in-vehicle vibrations, especially vertical accelerations, induced by the pavement surface roughness (Ahlin and Granlund 2002). Unevenness of the pavement surface causes vibrations on the users’ whole-body during vehicle motion, adversely affecting the ride quality and comfort. For these reasons, the study of the pavement-vehicle-human interactions and the physical analysis of the vibration phenomena are both critical aspects, particularly for quantitatively relating pavement surface roughness to ride quality (Cantisani and Loprencipe 2010). As discussed subsequently, studies conducted to formulate mathematical representations of pavement surface roughness relative to travel quality, and support the PMS decision-making processes, yielded the well-known and widely used IRI concept (Múčka 2016, 2017a).
Whale-optimized fuzzy-fractional order controller-based automobile suspension model
Published in Engineering Optimization, 2021
P. Swethamarai, P. Lakshmi, S. Gokul Prassad
The ride quality of passengers is a significant aspect that can be improved by an automobile’s suspension system. Owing to the great demand for ride comfort and vehicle handling performance, an active suspension system (ASS) is preferred to the conventional passive suspension system. This is because of various benefits; for example, an ASS uses an actuator to produce a control force against the vehicle vibration and has the potential to minimize the sprung mass acceleration consistently, which results in better wheel traction with the ground surface. To enhance the performance of an ASS, various control techniques have been proposed by researchers for a quarter-car model (QCM), including a proportional–integral-derivative (PID) controller (Senthil Kumar 2008), sky-hook control (Rao and Narayanan 2009), self-organized fuzzy logic controller (FLC) (Lin and Lian 2010), particle swarm optimization (PSO) tuned adaptive neural fuzzy controller (Kothandaraman and Ponnusamy 2012), sliding mode control (Deshpande et al.2014) and parallel adaptive clonal selection algorithm tuned fractional order PID controller (Dong et al.2016). The QCM has been extensively used to study the ride comfort of passengers by contemplating the vertical motion of the vehicle.