Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics.

Vehicle handling and stability performance and ride comfort is normally assessed through standard field test procedures, which are time consuming and expensive. However, the rapid development of digital technologies in the automotive industry have enabled to properly model and simulate the full-vehicle dynamics, thus drastically reducing design and manufacturing times and costs while enhancing the performance, safety, and longevity of vehicle systems. This paper focus on a computationally efficient multi-objective optimization framework for developing an optimal design of a vehicle steering system, which is carried out by coupling certain computer-aided design tools (CAD) and computer-aided engineering (CAE) software. The 3D CAD model of the steering system is made using SolidWorks, the Finite Element Analysis (FEA) is modelled using Ansys Workbench, while the multibody kinematic and dynamic is analysed using Adams/Car. They are embedded in a multidisciplinary optimization design framework (modeFrontier) with the aim of determining the optimal hardpoint locations of the suspension and steering systems. This is achieved by minimizing the Ackermann error and toe angle deviations, together with the volume, mass, and maximum stresses of the rack-and-pinion steering mechanism. This enhances the vehicle stability, safety, manoeuvrability, and passengers' comfort, extends the vehicle systems reliability and fatigue life, while reducing the tire wear. The method has been successfully applied to different driving scenarios and vehicle maneuvers to find the optimal Pareto front and analyse the performance and behaviour of the steering system. Results show that the design of the steering system can be significantly improved using this approach.

Impact of digital transformation on the automotive industry.

Digital technologies are transforming the automotive industry and disrupting traditional business models. New business opportunities related to Industry 4.0 are emerging, so companies must adapt to the new environment. The study presents an application of fuzzy-set qualitative comparative analysis (fsQCA) to analyze the future impact of digital transformation on business performance models and the different actors' satisfaction. A wide range of aspects and actors derived from the digital transformation process in the automotive industry are considered. The study covers connected and autonomous driving, mobility as a service, digital information sources in car purchasing, big data, etc. The disruptive effect of the gradual introduction of electric vehicles into the market is also considered, which is boosted by environmental policies on climate change and directives for the potential use of renewable energy sources to power electric vehicles. On the other hand, the study analyses the impacts of digital transformation on the automotive industry from the point of view of different actors, ranging from automobile manufacturers, service providers, public transportation providers, and consumers to governments. The methodology has been successfully applied to a complex case study-based empirical analysis. It presents a novel application of fsQCA to digital transformation in the automotive industry in Spain. The conclusions show that it is necessary to invest in adequate measures for adaptation to digital transformation, and manufacturers will end up having greater profits, productivity, and competitiveness. From the point of view of consumers, there will be access to more and better services and greater satisfaction with the required services.

Application of Fuzzy Set/Qualitative Comparative Analysis to Public Participation Projects in Support of the EU Water Framework Directive.

This study analyzes the level of satisfaction of stakeholders in the public participation process (PPP) of water resources management, which is mandatory according to the EU Water Framework Directive (WFD). The methodology uses a fuzzy set/qualitative comparative analysis (fsQCA), which allows the identification of a combination of factors that lead to the outcome that is stakeholders' satisfaction. It allows dealing with uncertain environments due to the heterogeneous nature of stakeholders and factors. The considered causes range from environmental objectives pursued, actual capacity of efficiently carrying out those objectives, socioeconomic development of the region, level of involvement and means of participation of the stakeholders engaged in the PPP, and alternative policies and measures that should be performed. Results support the argument that different causal paths explain the stakeholders' satisfaction. The methodology may help in the implementation of the WFD and conflict resolution since it leads to greater fairness, social equity, and consensus among stakeholders.

Stochastic hydro-economic model for groundwater quality management using Bayesian networks.

A strong normative development in Europe, including the Nitrate Directive (1991) and the Water Framework Directive (WFD) (2000), has been promulgated. The WFD states that all water bodies have to reach a good quantitative and chemical status by 2015. It is necessary to consider different objectives, often in conflict, for tackling a suitable assessment of the impacts generated by water policies aimed to reduce nitrate pollution in groundwater. For that, an annual lumped probabilistic model based on Bayesian networks (BNs) has been designed for hydro-economic modelling of groundwater quality control under uncertain conditions. The information introduced in the BN model comes from different sources such as previous groundwater flow and mass transport simulations, hydro-economic models, stakeholders and expert opinion, etc. The methodology was applied to the El Salobral-Los Llanos aquifer unit within the 'Easter Mancha' groundwater body, which is one of the largest aquifers in Spain (7,400 km(2)), included in the Júcar River Basin. Over the past 30 years, socioeconomic development within the region has been mainly depending on intensive use of groundwater resources for irrigating crops. This has provoked a continuous groundwater level fall in the last two decades and significant streamflow depletion in the connected Júcar River. This BN model has proved to be a robust Decision Support System for helping water managers in the decision making process.