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The purpose is to create an algorithm that optimizes the trajectories that an autonomous vehicle must follow to reduce its energy consumption and reduce the emission of greenhouse gases.

An algorithm is presented that respects the dynamic constraints of the robot, including the characteristics of power delivery by the motor, the behaviour of the tires and the basic inertial parameters. Using quadratic sequential programming with distributed and non-monotonous search direction (Quadratic Programming Algorithm with Distributed and Non-Monotone Line Search), an optimization algorithm proposed and developed by Professor K. Schittkowski is implemented.

Relations between important operating variables have been obtained, such as the evolution of the autonomous vehicle’s velocity, the driving torque supplied by the engine and the forces acting on the tires. In a subsequent analysis, the aim is to analyse the relationship between trajectory made and energy consumed and calculate the reduction of greenhouse gas emissions. Also this method has been checked against another different methodology commented on in the references.

The main limitation comes from the modelling that has been done. As greater is the mechanical systems analysed, more simplifying hypotheses should be introduced to solve the corresponding equations with the current computers. However, the solutions are obtained and they can be used qualitatively to draw conclusions.

One main objective is to obtain guidelines to reduce greenhouse gas emissions by reducing energy consumption in the realization of autonomous vehicles’ trajectories. The first step to achieve that is to obtain a good model of the autonomous vehicle that takes into account not only its kinematics but also its dynamic properties, and to propose an optimization process that allows to minimize the energy consumed. In this paper, important relationships between work variables have been obtained.

The idea is to be friendly with nature and the environment. This algorithm can help by reducing an instance of greenhouse gases.

Originality comes from the fact that we not only look for the autonomous vehicle’s modelling, the simulation of its motion and the analysis of its working parameters, but also try to obtain from its working those guidelines that are useful to reduce the energy consumed and the contamination capability of these autonomous vehicles or car-like robots.

The purpose of this paper is to develop a new interdisciplinary methodology to estimate the life cycle cost (LCC) of complex business-to-business products in order to price different types of maintenance contracts and show the applicability of the method in a case study. LCC comprise of initial capital costs as well of operation costs including probabilistic costs (such as the costs of repairs and spare parts), which are directly linked to the maintenance characteristics of the product.

The paper proposes an integrated and practical methodology that applies different approaches from different disciplines. Therefore, exponential distributions for failure rates in subsystems, World Bank logistics factors for logistics costs of spare part handling, as well implied credit default probabilities for the counterpart risk in full service leasing contracts are applied. In order to validate the applicability of the proposed methodology to practical problems, the tool is applied in three case studies.

The results of the case studies show that this methodology can be applied to analyze LCC structures of engines operating in various regions with regard to different types of engine maintenance contracts. The results also highlight the interplay of technical as well as financial risks.

Because the literature in maintenance engineering so far either proposes general frameworks to calculate LCC or concentrates on specific aspects of LCC, the paper contributes to the literature in presenting a new interdisciplinary methodology to estimate the LCC.

The purpose of this paper is to find the configuration of the number (m) and size (n) of the sample in Phase I that would make it possible to detect the out-of-control (OOC) state of the process with the smallest number of samples and ensure a capability index (C_pk) that would meet the customer’s requirements.

The suggested approach addresses this problem using simulation techniques and design of experiments (DOE). The simulation techniques made it possible to reproduce the normal operating conditions of the process. The DOE was used to construct a predictive model for control chart performance and thus to determine combinations of m and n in Phase I that would meet the capability objectives of the process. A numerical example and a simulation study were conducted to illustrate the proposed method.

Using simulation techniques and DOE, the authors can find the number (m) and size (n) of the sample in Phase I that would make it possible to detect the OOC state of the process with the smallest number of samples and ensure a C_pk that would meet the customer’s requirements.

In the real situations of many companies, choosing the numbers and sizes of samples (m and n) in Phases I and II is a crucial decision in relation to implementing a control chart. The paper shows that the simulation method and use of linear regression are effective alternatives because they are better known and more easily applied in industrial settings. Therefore, the need for alternatives to the X control chart comes into play.

This work presents a topology optimization methodology for designing microarchitectures of phononic crystals. The objective is to get microstructures having, as a consequence of wave propagation phenomena in these media, bandgaps between two specified bands. An additional target is to enlarge the range of frequencies of these bandgaps.

The resulting optimization problem is solved employing an augmented Lagrangian technique based on the proximal point methods. The main primal variable of the Lagrangian function is the characteristic function determining the spatial geometrical arrangement of different phases within the unit cell of the phononic crystal. This characteristic function is defined in terms of a level-set function. Descent directions of the Lagrangian function are evaluated by using the topological derivatives of the eigenvalues obtained through the dispersion relation of the phononic crystal.

The description of the optimization algorithm is emphasized, and its intrinsic properties to attain adequate phononic crystal topologies are discussed. Particular attention is addressed to validate the analytical expressions of the topological derivative. Application examples for several cases are presented, and the numerical performance of the optimization algorithm for attaining the corresponding solutions is discussed.

The original contribution results in the description and numerical assessment of a topology optimization algorithm using the joint concepts of the level-set function and topological derivative to design phononic crystals.

This chapter reflects upon the trajectory of research in the geography of tourism in Spain. It begins with a review, including the evolution of the main topics present in the subdiscipline, with a special focus on developments since the 1990s. This is followed by an analysis of the current role and potential impact of academic tourism geography and a discussion on the recent growth in the publication of research results in international journals. Of importance are the institutional factors that explain the increasing recognition of research on the geography of tourism in Spain. Finally, the chapter discusses the hegemony of positivist approaches pivoting on land use, local and regional development, impact analysis, and landscape transformation, as well as the emerging links between Spanish tourism geography and the international mainstream schools of thought.

We suggest that, in some specific settings, individuals may distinguish and be sensitive not only to the distributive, procedural, social, and informational dimensions of justice, but also subdivide the distributive justice dimension into two facets‐reward and task distributive justice. Results of three studies with Portuguese public university teachers reveal that a five‐factor model of justice (distribution of tasks, distribution of rewards, procedural, interpersonal, informational) is adequate, although factor analyses are not categorical in distinguishing interpersonal and informational justice. Results also show that individuals who work with high autonomy and outside close supervisory control in performing their jobs may be very sensitive to the way they feel treated by their superiors, even accepting as normal that the superiors make decisions with no participation, a finding that may be due to the feminine, affiliative, and high power distance cultural context.

The monitoring of respirable particulate matter (PM₁₀) and of total carbon percentage (mass basis) in the atmosphere of São Carlos (SP) was performed in the period between September 1997 and January 2000. São Carlos, located in the central region of the state of São Paulo, has a population of close to 180,000 inhabitants and about 500 industrial establishments of medium to small size, mainly dealing with metallurgy, textiles, food and ceramics. The equipment used for air monitoring was a high volume sampler (GVS‐GRASEBY/GMW) equipped with a one‐stage inertial separator for a 10μm particle cut diameter. The PM₁₀ concentration was determined by gravimetry and the total carbon concentration by the Ströheim method. The results show a well defined seasonal dependence of both the PM₁₀ and of the total carbon concentration. Higher concentrations of PM₁₀ and carbon were observed in autumn and winter, which also coincided with low relative humidity and precipitation. The measured trends were compared with the PM₁₀ data from the city of São Paulo in the same period and showed similar seasonal dependence. However, in relative terms, the PM₁₀ concentration in São Carlos showed stronger seasonal dependence than in São Paulo.