Cutting Parameter Selection for Efficient and Sustainable Repair of Holes Made in Hybrid Mg–Ti–Mg Component Stacks by Dry Drilling Operations

Drilling is one of the most common machining operations in the aeronautic and aerospace industries. For assembling parts, a large number of holes are usually drilled into the parts so that they can be joined later by rivets. As these holes are subjected to fatigue cycles, they have to be checked regularly for maintenance or repair, since small cracks or damage in its contour can quickly cause breakage of the part, which can have dangerous consequences. This paper focuses on finding the best combinations of cutting parameters to perform repair and maintenance operations of holes in stacked hybrid magnesium–titanium–magnesium components in an efficient, timely, and sustainable (without lubricants or coolants) manner, under dry drilling conditions. For the machining trials, experiments were designed and completed. A product of a full factorial 23 and a block of two factors (3 × 2) was used with surface roughness as the response variable measured as the mean roughness average. Analysis of variance (ANOVA) was used to examine the results. A set of optimized tool and cutting conditions is presented for performing dry drilling repair operations

Spatial Modeling of Rainfall Patterns over the Ebro River Basin Using Multifractality and Non-Parametric Statistical Techniques

Rainfall, one of the most important climate variables, is commonly studied due to its great heterogeneity, which occasionally causes negative economic, social, and environmental consequences. Modeling the spatial distributions of rainfall patterns over watersheds has become a major challenge for water resources management. Multifractal analysis can be used to reproduce the scale invariance and intermittency of rainfall processes. To identify which factors are the most influential on the variability of multifractal parameters and, consequently, on the spatial distribution of rainfall patterns for different time scales in this study, universal multifractal (UM) analysis—C1, α, and γs UM parameters—was combined with non-parametric statistical techniques that allow spatial-temporal comparisons of distributions by gradients. The proposed combined approach was applied to a daily rainfall dataset of 132 time-series from 1931 to 2009, homogeneously spatially-distributed across a 25 km × 25 km grid covering the Ebro River Basin. A homogeneous increase in C1 over the watershed and a decrease in α mainly in the western regions, were detected, suggesting an increase in the frequency of dry periods at different scales and an increase in the occurrence of rainfall process variability over the last decades

Frequency and Intensity of drought events over Ebro River basin.

Lately, several researchers have pointed out that climate change is expected to increase temperatures and lower rainfall in Mediterranean regions, simultaneously increasing the intensity of extreme rainfall events. These changes could have consequences regarding rainfall regime, erosion, sediment transport and water quality, soil management, and new designs in diversion ditches. Climate change is expected to result in increasingly unpredictable and variable rainfall, in amount and timing, changing seasonal patterns and increasing the frequency of extreme weather events. Consequently, the evolution of frequency and intensity of drought periods is of most important as in agro-ecosystems many processes will be affected by them. Realising the complex and important consequences of an increasing frequency of extreme droughts at the Ebro River basin, our aim is to study the evolution of drought events at this site statistically, with emphasis on the occurrence and intensity of them. For this purpose, fourteen meteorological stations were selected based on the length of the rainfall series and the climatic classification to obtain a representative untreated dataset from the river basin. Daily rainfall series from 1957 to 2002 were obtained from each meteorological station and no-rain period frequency as the consecutive numbers of days were extracted. Based on this data, we study changes in the probability distribution in several sub-periods. Moreover we used the Standardized Precipitation Index (SPI) for identification of drought events in a year scale and then we use this index to fit log-linear models to the contingency tables between the SPI index and the sub-periods, this adjusted is carried out with the help of ANOVA inference

Climate Change and Temporal and Spatial Evolution of the Multifractal Universal Parameters in Ebro River Basin

Multifractal techniques are applied to the study of rainfall daily time series over 14 stations from Ebro river Basin over the second half of XX century. The aim is to determine how climate change affects the evolution of the probability distribution of daily precipitation, through the values of universal multifractal parameters: C1; ; H y s for different periods of time. These will offer direct explanations of the shape of the distribution, especially about the extreme events: C1 is the mean intermittency codimension. When C1 increases the precipitation becoming less continuous and more sporadic in time. Therefore there is an increase of extremes. ; is a mesure of multifratility so an increase of it corresponds to a larger variation of the range of precipitation intensity, and thus also of extremes. H is the degree of non-conservation of the field, which measures the scale dependency of the average field. s; the maximal probable singularity that can be observed on a unique sample. It’s directly related to the ratio of the range and the mean of field. From the data collected, we perceive a decline in average rainfall, from 1980. But how is affected the global parameters in this situation?. Results vary according to different rainfall stations

Experimental Study for Improving the Repair of Magnesium–Aluminium Hybrid Parts by Turning Processes

One of the lightest metallic materials used in the aeronautics, aerospace, and automotive industries, among others, is magnesium, due to its excellent weight/strength ratio. Most parts used in these industries need to be made of materials that are rigid, strong, and lightweight, but sometimes the materials do not simultaneously satisfy all of the properties required. An alternative is to combine two or more materials, giving rise to a hybrid component that can satisfy a wider range of properties. The pieces machined in these industrial fields must satisfy stringent surface roughness requirements that conform to the design specifications. This work shows an experimental study to analyse the surface roughness reached in hybrid components made up of a base of magnesium alloy (UNS M11917) and two inserts of aluminium alloy (UNS A92024) obtained by turning. Its purpose is to determine the influence of the factors and their possible interactions on the response variable, the surface roughness Ra. The study is carried out using a design of experiments (DOE). A product of a full factorial 23 and a block of two factors 3 × 2 was selected. The factors identified as possible sources of variation of the surface roughness are: depth of cut, feed rate, spindle speed, type of tool, location with respect to the specimen (LRS), and location with respect to the insert (LRI). Data were analysed by means of the analysis of variance (ANOVA) method. The main conclusion is the possibility to carry out the repair and maintenance of parts of magnesium–aluminum hybrid components by dry turning; that is, without cutting fluids and, therefore, in the most sustainable way that the process can be carried out. In addition, different combinations of cutting parameters have been identified that allow these operations to be carried out in an efficient manner, reducing mechanization times and, therefore, also the direct and indirect costs associated with them

Robust regression applied to fractal/multifractal analysis.

Fractal and multifractal are concepts that have grown increasingly popular in recent years in the soil analysis, along with the development of fractal models. One of the common steps is to calculate the slope of a linear fit commonly using least squares method. This shouldn?t be a special problem, however, in many situations using experimental data the researcher has to select the range of scales at which is going to work neglecting the rest of points to achieve the best linearity that in this type of analysis is necessary. Robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non-parametric methods. In this method we don?t have to assume that the outlier point is simply an extreme observation drawn from the tail of a normal distribution not compromising the validity of the regression results. In this work we have evaluated the capacity of robust regression to select the points in the experimental data used trying to avoid subjective choices. Based on this analysis we have developed a new work methodology that implies two basic steps: ? Evaluation of the improvement of linear fitting when consecutive points are eliminated based on R pvalue. In this way we consider the implications of reducing the number of points. ? Evaluation of the significance of slope difference between fitting with the two extremes points and fitted with the available points. We compare the results applying this methodology and the common used least squares one. The data selected for these comparisons are coming from experimental soil roughness transect and simulated based on middle point displacement method adding tendencies and noise. The results are discussed indicating the advantages and disadvantages of each methodology

Universal Multifractal description applied to precipitation pattern in the Ebro River Basin

Water supplies in the Ebro River Basin are increasingly stressed, especially during the summer season. The year-to-year fluctuations in rainfall over this area exert vital influence on the regional hydrology, agriculture and several related industries in the region. Repeated anomalous rainfall in recent decades has had a devastating impact on this region, both socially and economically. We characterised the change in the rainfall variability pattern in the Ebro River Basin using universal multifractal (UM) analysis, which estimates the concentration of the data around the precipitation average (C1, codimension average), the degree of multiscaling behaviour in time (α index) and the maximum probable singularity in the rainfall distribution (γs ). Fourteen meteorological stations were selected based on the length of rainfall series and the climatic classification to obtain a representative untreated data set from the river basin. Daily rainfall series from 1957 to 2002 were obtained from each meteorological station and subdivided (1957–1980 and 1981–2002) to analyse the difference between the 2 periods. The general scenario observed in this study, through the UM parameters, can be summarised as follows: the range of variation of precipitation amounts was spatially more homogenous in 1980–2002 than in 1957–1979; at the same time, there is higher frequency of dry periods at different scales in 1980–2002; and in almost all of the stations, the range of precipitation over the years has been decreasing at a lower rate than the rainfall average. We then analysed the evolution of the UM parameters from 1957 to 2002. Continuous variations in C1 and α were found for 2 of the stations, indicating that a precipitation regime change has begun in the last few decades and should be considered in the agricultural development of the region

Change of extreme rainfall indexes at Ebro River Basin

The purpose of this work is to provide a description of the heavy rainfall phenomenon on statistical tools from a Spanish region. We want to quantify the effect of the climate change to verify the rapidity of its evolution across the variation of the probability distributions. Our conclusions have special interest for the agrarian insurances, which may make estimates of costs more realistically. In this work, the analysis mainly focuses on: The distribution of consecutive days without rain for each gauge stations and season. We estimate density Kernel functions and Generalized Pareto Distribution (GPD) for a network of station from the Ebro River basin until a threshold value u. We can establish a relation between distributional parameters and regional characteristics. Moreover we analyze especially the tail of the probability distribution. These tails are governed by law of power means that the number of events n can be expressed as the power of another quantity x : n(x) = x? . ? can be estimated as the slope of log-log plot the number of events and the size. The most convenient way to analyze n(x) is using the empirical probability distribution. Pr(X mayor que x) ? x-?. The distribution of rainfall over percentile of order 0.95 from wet days at the seasonal scale and in a yearly scale with the same treatment of tails than in the previous section

Thresholding Soil Surface Images

Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on several factors being one of them surface micro-topography, usually quanti[U+FB01]ed trough soil surface roughness (SSR). SSR greatly affects surface sealing and runoff generation, yet little information is available about the effect of roughness on the spatial distribution of runoff and on flow concentration. The methods commonly used to measure SSR involve measuring point elevation using a pin roughness meter or laser, both of which are labor intensive and expensive. Lately a simple and inexpensive technique based on percentage of shadow in soil surface image has been developed to determine SSR in the field in order to obtain measurement for wide spread application. One of the first steps in this technique is image de-noising and thresholding to estimate the percentage of black pixels in the studied area. In this work, a series of soil surface images have been analyzed applying several de-noising wavelet analysis and thresholding algorithms to study the variation in percentage of shadows and the shadows size distributio

Spatial and temporal precipitation patterns of the Ebro River Basin, Spain

The Ebro River Basin, with around 85 000 km2 and located in NE Spain, is characterized by the high spatial heterogeneity of its geology, topography, climatology and land use. Rainfall is one of the most important climatic variables studied owing to its non-homogenous behaviour in event and intensity, which creates drought, water runoff and soil erosion with negative environmental and social consequences. In this work we characterized the rainfall variability pattern in the Ebro River Basin using universal multifractal (UM) analysis, which estimates the concentration of the data around the precipitation average (C1, codimension average), the degree of multiscaling behaviour in time (? index) and the maximum probable singularity in the rainfall distribution ( s). A spatial and temporal analysis of the UM parameters is applied to study the possible changes. With this porpoise, 60 daily rainfall series were selected from 132 synthetic series generated by Luna and Balairón (AEMet). These daily rainfall series present a length of 60 years, from 1950 to 2009. Each one of them was subdivided (1950?1970 and 1980?2009) to analyse the difference between the two periods. The range of variation of precipitation amounts and the frequency of dry events between both periods are discussed, as well as the evolution of the UM parameters through the years