Eduardo Cuesta, Braulio J. Alvarez, Pablo Zapico and Sara Giganto
This study aims to analyze the effect of the different common post-processes on the geometrical and dimensional accuracy of selective laser melting (SLM) parts.
Abstract
Purpose
This study aims to analyze the effect of the different common post-processes on the geometrical and dimensional accuracy of selective laser melting (SLM) parts.
Design/methodology/approach
An artefact has been designed including cubic features formed by planar surfaces orientated according to the machine axes, covering all the X-Y area of the working space. The artefact has been analyzed both geometrically (flatness, parallelism) and dimensionally (sizes, distances) from coordinate measuring machine measurement results at three stages, namely, as-built, after sand-blasting and after stress-relieving heat treatment.
Findings
Results from the SLM machine used in this study lead to smaller parts than the nominal ones. This effect depends on the direction of the evaluated dimension of the parts, i.e. X, Y or Z direction and is differently affected by the sandblasting post-process (average erosion ratio of 68, 54 and 9 µm, respectively), being practically unaltered by the HT applied after.
Originality/value
This paper shows the influence, from a geometric and dimensional point of view, of two of the most common post-processes used after producing SLM parts, such as sand-blasting and stress-relieving heat treatment, that have not been considered in previous research.
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Keywords
Age-difference in couple relationships in Mexico and Latin America has been a field of study predominantly approached by demographers and sociodemographers. In Western Europe and…
Abstract
Age-difference in couple relationships in Mexico and Latin America has been a field of study predominantly approached by demographers and sociodemographers. In Western Europe and North America, the tendency is similar yet sociologists and anthropologists have contributed important knowledge to this discussion. The results of both groups of studies show that in most societies men marry and cohabitate with women younger than them and that in a rather small percentage women are older than men. The discussion on the reasons for which men prefer younger women or women prefer older men when marrying and cohabitating go from psychological to economic grounds. This study aims to contribute to the discussion on the reasons for which this pattern persists by study examining the narratives of 81 Mexican heterosexual men and women from three generations. This is done from a qualitative and sociological standpoint that approaches the age differences from the subjectivity and intimacy of the interviewees aiming to understand (i) the meanings of the age-gap and age discrepancy, (ii) the role of schooling and social class in the significance of the age-gap and age-discrepancy relationships, and (iii) the gender inequality in age-gap relationships. The data show that amid a vigorous and strong trend of unions between older men and younger women where great gender inequalities may persist, there are signs of cultural change that show the discomfort and stigma of such differences. This, rather than being a contradiction, reveals how schooling and social origin affect the resignification of the difference, and moreover, suggests that the power relations in the couple are more equitable.
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Wenzhong Gao, Xingzong Huang, Mengya Lin, Jing Jia and Zhen Tian
The purpose of this paper is to target on designing a short-term load prediction framework that can accurately predict the cooling load of office buildings.
Abstract
Purpose
The purpose of this paper is to target on designing a short-term load prediction framework that can accurately predict the cooling load of office buildings.
Design/methodology/approach
A feature selection scheme and stacking ensemble model to fulfill cooling load prediction task was proposed. Firstly, the abnormal data were identified by the data density estimation algorithm. Secondly, the crucial input features were clarified from three aspects (i.e. historical load information, time information and meteorological information). Thirdly, the stacking ensemble model combined long short-term memory network and light gradient boosting machine was utilized to predict the cooling load. Finally, the proposed framework performances by predicting cooling load of office buildings were verified with indicators.
Findings
The identified input features can improve the prediction performance. The prediction accuracy of the proposed model is preferable to the existing ones. The stacking ensemble model is robust to weather forecasting errors.
Originality/value
The stacking ensemble model was used to fulfill cooling load prediction task which can overcome the shortcomings of deep learning models. The input features of the model, which are less focused on in most studies, are taken as an important step in this paper.