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The purpose of this paper is to focus on the analysis of the dynamic and periodic interaction between both fixed and rotating blade rows in a single‐stage turbomachine.

A numerical three‐dimensional (3D) simulation of the complete stage is carried out, using a commercial code, FLUENT, that resolves the 3D, unsteady turbulent flow inside the passages of a low‐speed axial flow fan. For the closure of turbulence, both Reynolds‐averaged Navier‐Stokes modeling and large eddy simulation (LES) techniques are used and compared. LES schemes are shown to be more accurate due to their good description of the largest eddy structures of the flow, but require careful near‐wall treatment.

The main goal is placed on the characterization of the unsteady flow structures involved in an axial flow blower of high reaction degree, relating them to working point variations and axial gap modifications.

Complementarily, an experimental facility was developed to obtain a physical description of the flow inside the machine. Both static and dynamic measurements were used in order to describe the interaction phenomena. A five‐hole probe was employed for the static characterization, and hot wire anemometry techniques were used for the instantaneous response of the interaction.

The paper describes development of a methodology to understand the flow mechanisms related to the blade‐passing frequency in a single rotor‐stator interaction.

The purpose of this paper is the development of a CFD methodology based on LES computations to analyze the rotor–stator interaction in an axial fan stage.

A wall-modeled large eddy simulation (WMLES) has been performed for a spanwise 3D extrusion of the central section of the fan stage. Computations were performed for three different operating conditions, from nominal (Q_N) to off-design (85 per cent Q_N and 70 per cent Q_N) working points. Circumferential periodic conditions were introduced to reduce the extent of the computational domain. The post-processing procedure enabled the segregation of unsteady deterministic features and turbulent scales. The simulations were experimentally validated using wake profiles and turbulent scales obtained from hot-wire measurements.

The transport of rotor wakes and both wake–vane and wake–wake interactions in the stator flow field have been analyzed. The description of flow separation, particularly at off-design conditions, is fully benefited from the LES performance. Rotor wakes impinging on the stator vanes generate a coherent large-scale vortex shedding at reduced frequencies. Large pressure fluctuations in the stagnation region on the leading edge of the vanes have been found.

LES simulations have shown to be appropriate for the assessment of the design of an axial fan, especially for specific operating conditions for which a URANS model presents a lower performance for turbulence description.

This paper describes the development of an LES-based simulation to understand the flow mechanisms related to the rotor–stator interaction in axial fan stages.

The purpose of the paper is to quantify the impact of the non-uniform flow generated by the upstream stator on the generation and convection of the tip leakage flow (TLF) structures in the passages of the rotor blades in a low-speed axial fan.

A full three dimensional (3D)-viscous unsteady Reynolds-averaged Navier-stokes (RANS) (URANS) simulation of the flow within a periodic domain of the axial stage has been performed at three different flow rate coefficients (φ = 0.38, 0.32, 0.27) using ReNormalization Group k-ε turbulence modelling. A typical tip clearance of 2.3 per cent of the blade span has been modelled on a reduced domain comprising a three-vaned stator and a two-bladed rotor with circumferential periodicity. A non-conformal grid with hybrid meshing, locally refined O-meshes on both blades and vanes walls with (100 × 25 × 80) elements, a 15-node meshed tip gap and circumferential interfaces for sliding mesh computations were also implemented. The unsteady motion of the rotor has been covered with 60 time steps per blade event. The simulations were validated with experimental measurements of the static pressure in the shroud of the blade tip region.

It has been observed that both TLF and intensities of the tip leakage vortex (TLV) are significantly influenced by upstream stator wakes, especially at nominal and partial load conditions. In particular, the leakage flow, which represents 12.4 per cent and 11.3 per cent of the working flow rate, respectively, has shown a clear periodic fluctuation clocked with the vane passing period in the relative domain. The periodic fluctuation of the TLF is in the range of 2.8-3.4 per cent of the mean value. In addition, the trajectory of the tip vortex is also notably perturbed, with root-mean squared fluctuations reaching up to 18 per cent and 6 per cent in the regions of maximum interaction at 50 per cent and 25 per cent of the blade chord for nominal and partial load conditions, respectively. On the contrary, the massive flow separation observed in the tip region of the blades for near-stall conditions prevents the formation of TLV structures and neglects any further interaction with the upstream vanes.

Despite the increasing use of large eddy simulation modelling in turbomachinery environments, which requires extremely high computational costs, URANS modelling is still revealed as a useful technique to describe highly complex viscous mechanisms in 3D swirl flows, such as unsteady tip flow structures, with reasonable accuracy.

The paper presents a validated numerical model that simulates the unsteady response of the TLF to upstream perturbations in an axial fan stage. It also provides levels of instabilities in the TLV derived from the deterministic non-uniformities associated to the vane wakes.

Aging of the oil wells leads to a decrease in reservoir pressure and also to an increase in the water, gas and abrasive particles content. Therefore, there is a need for the oil pumps exploitation characteristics improvements. This paper aims to generate a valuable numerical model which will provide a useful tool to study various cases.

Computational fluid dynamics (CFD) analysis of the generation of so-called coherent structures of eddies and turbulence in the peripheral area of the vortex rotor mounted at the back side of centrifugal rotor was undertaken. After detailed analysis of the influence of the used turbulence models on the results, a hybrid turbulent model Detached Eddies Simulation (DES) was chosen as the most suitable.

Numerical control volume method with unsteady solver and DES turbulence model was proven to be valuable tool for flow analysis in the centrifugal pumps. Having in mind that DES turbulence model consumes much less computational time than large eddies turbulence model, this is a very useful fact that resulted from this research.

The proven numerical model is robust and reliable enough to become a standard method in simulating flow and other physical phenomena occurring in centrifugal pumps and similar turbo machines. This makes it possible to easily research different factors that influence their performances.

Comprehensive experimental and CFD study was performed which made it possible to conduct detailed validation and verification of described CFD model.

Climate change is a problem that concerns all of us. Despite the information produced by organizations such as the Expert Team on Climate Change Detection and Indices and the United Nations, only a few cities have been planned taking into account the climate changes indices. This paper aims to study climatic variations, how climate conditions might change in the future and how these changes will affect the activities and living conditions in cities, specifically focusing on Mexico city.

In this approach, two distinct machine learning regression models, k-Nearest Neighbors and Support Vector Regression, were used to predict variations in climate change indices within select urban areas of Mexico city. The calculated indices are based on maximum, minimum and average temperature data collected from the National Water Commission in Mexico and the Scientific Research Center of Ensenada. The methodology involves pre-processing temperature data to create a training data set for regression algorithms. It then computes predictions for each temperature parameter and ultimately assesses the performance of these algorithms based on precision metrics scores.

This paper combines a geospatial perspective with computational tools and machine learning algorithms. Among the two regression algorithms used, it was observed that k-Nearest Neighbors produced superior results, achieving an R² score of 0.99, in contrast to Support Vector Regression, which yielded an R² score of 0.74.

The full potential of machine learning algorithms has not been fully harnessed for predicting climate indices. This paper also identifies the strengths and weaknesses of each algorithm and how the generated estimations can then be considered in the decision-making process.

This paper aims to present a computational approach which – setting off from measures obtained by using an overdrilling method – determines, automatically and accurately, stress changes undergone in terrain as a consequence of human activity.

The method presented uses the data from three boreholes and the elasticity theory to represent a numerical system whose resolution allows determining the stress state in a particular point. Since the system obtained is over‐dimensioned, the Levenberg‐Marquardt minimization method has been used in order to minimize errors. This paper details the analysis carried out in order to develop the computational method.

This paper provides the algorithm for determining inner stresses in a particular point of a rock mass. Besides, a method to verify obtained results is presented, including its computational encoding in C#. Furthermore, the developed methods have been integrated in a computer tool which presents the results in a graphic environment.

The algorithms presented are applicable when using an overdrilling method to measure stresses.

A reliable determination of global stress state demands the use of any method that is numerically difficult to use. Thus, in practice, it is of great importance to dispose of some reliable automatic tool to calculate stress state.

Accuracy in the results obtained with the tool, together with the simplicity of its interface, involves a certain advantage regarding the use of a general‐scope commercial tool, since it allows – without being necessary to be an expert user – quickly obtaining results within the analysed working area.

Since the early modern age, the debt of the State was a constant source for concern to the Spanish governments. Episodes of defaults caused by enormous expenditure to keep the Empire slowly faded out until a certain reorganization of public finance was attained in the central decades of the nineteenth century. The core idea that finance ministers and economists, in general, had at that time was to balance the public budget controlling expenses, in order to handle the problem of public debt. However, alternative views on government finance existed. Focusing on a crucial period for the consolidation of Spanish liberal regime and its public finance, this chapter shows that, among a predominant concern for reducing public expenditure as the best way to stabilize the economy and promote economic growth, the character of Luis María Pastor emerges to support government expansionary policies financed with credit. Far from fearing deficit, Pastor, one of the leaders of the Spanish liberal school of economic thought, believed that investment in infrastructures financed through debt was the key to economic growth. Through a multiplicative effect, a program of public investment would enhance economic growth, eventually solving the long-term insufficiency of Spanish finance. This gives evidence that ideas on public finance of classical liberal economists were far from uniform, contributing to a more precise view on the body of doctrines of this school.

Massive open online courses (MOOCs), a Taylorist attempt to automate instruction, help make course delivery more efficient, economical and better. As an implementation of Digital Taylorism Implementation (DTI), MOOCs enable individuals to obtain an occupation-oriented education, equipping them with knowledge and skills needed to stay employable. However, learning through online platforms can induce tremendous amounts of technology-related stress in learners such as complexity of platforms and fears of redundancy. Thus, the aim of this paper is to study how student perceptions of DTI and technostress (TS) influence their perceived employability (PE). The role of TS as a mediator between DTI and PE has also been studied.

Stratified sampling technique has been used to obtain data from 305 students from 6 universities. The effect of DTI and TS on PE, and the role of TS as a mediator, has been examined using the partial least squares (PLS) structural equation modelling approach with SMART PLS 4.0. software. Predictive relevance of the model has been studied using PLSPredict.

Results indicate that TS completely mediates the relationship between DTI and PE. The model has medium predictive relevance.

Learning outcomes from Digitally Taylored programs can be improved with certain reforms that bring the human touch to online learning.

This study extends Taylorism literature by linking DTI to PE of students via technostress as a mediator.

Assessing the impacts generated by tourism has become an essential element for the industry’s sustainability. The increasing intensity of the impacts and the need to evaluate them from a resident’s perspective calls for new approaches to assist tourism management. This paper aims to advance from the pressure-state-response framework (PSR) to measure the tourism impacts in urban destinations with a holistic model called PSR-ti.

A multiple linear regression method was adopted to apply the PSR-ti model in the city of Madrid, estimating the relationship between the pressure (objective) and state (subjective) variables. Local statistical yearbook data was used to construct the pressure variables. Regarding the state variables, a survey was designed to assess residents’ perceptions of tourism. A total of 652 responses were obtained.

The results obtained from the study of pressure indicators unveil that these indicators can support decision-making processes as an underused management tool. This work represents a step forward in considering the transversality of tourism concerning urban planning, the development of equipment and infrastructures or activities such as commerce and culture for the analysis of the state indicators; the results obtained determine the need to periodically evaluate the perception of residents on the impacts of tourism, given its crucial role in the sustainability of the destination.

The PSR-ti model offers a holistic vision, including objective and subjective indicators in the model, which enhances the appraisal of the impacts of tourism by identifying pressure and state factors as a starting point for possible responses by the decision makers of the tourist destination.