Machining Stresses and Initial Geometry on Bulk Residual Stresses Characterization by On-Machine Layer Removal

Prediction and control of machining distortion is a primary concern when manufacturing monolithic components due to the high scrap and rework costs involved. Bulk residual stresses, which vary from blank to blank, are a major factor of machining distortion. Thus, a bulk stress characterization is essential to reduce manufacturing costs linked to machining distortion. This paper proposes a method for bulk stress characterization on aluminium machining blanks, suitable for industrial application given its low requirements on equipment, labour expertise, and computation time. The method couples the effects of bulk residual stresses, machining stresses resulting from cutting loads on the surface and raw geometry of the blanks, and presents no size limitations. Experimental results confirm the capability of the proposed method to measure bulk residual stresses effectively and its practicality for industrial implementation

Error Detection and Correction Methodology for Laser Milling Processes on Biocompatible Ceramic Materials

Abstract This paper shows the work done on the correction of laser milled geometries on biocompatible ceramic material for medical prostheses. After the exposition of the error detection and correction methodology to be followed after the machining of a geometrical feature, the experimental procedure for the application of the methodology is detailed. Finally, the obtained results are exposed and discussed. The results show that the error detection methodology is able to properly identify the defective zones and define a laser milling process for their correction, in order to obtain a geometry within the defined tolerances in comparison to the theoretical one

In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal

Manufacturing structural monolithic components for the aerospace market often involves machining distortion, which entails high costs and material and energy waste in industry. Despite the development of distortion calculation and avoidance tools, this issue remains unsolved due to the difficulties in accurately and economically measuring the residual stresses of the machining blanks. In the last years, the on-machine layer removal method has shown its potential for industrial implementation, offering the possibility to obtain final components from blanks with measured residual stresses. However, this measuring method requires too long an implementation time to be used in-process as part of the manufacturing chains. In this sense, the objective of this paper is to provide a machining distortion prediction method based on bulk residual stress estimation and hybrid modelling. The bulk residual stresses estimation is performed using reduced layer removal measurements. Considering bulk residual stress data and machining-induced residual stress data, as well as geometry and material data, real-part distortion calculations can be performed. For this, a hybrid model based on the combination of an analytical formulation and finite element modelling is employed, which enables us to perform fast and accurate calculations. With the developments here presented, the machining distortion can be predicted, and its uncertainty range can be calculated, in a simple and fast way. The accuracy and practicality of these developments are evaluated by comparison with the experimental results, showing the capability of the proposed solution in providing distortion predictions with errors lower than 10% in comparison with the experimental results

The genomic history of the Iberian Peninsula over the past 8000 years

We assembled genome-wide data from 271 ancient Iberians, of whom 176 are from the largely unsampled period after 2000 BCE, thereby providing a high-resolution time transect of the Iberian Peninsula. We document high genetic substructure between northwestern and southeastern hunter-gatherers before the spread of farming. We reveal sporadic contacts between Iberia and North Africa by ~2500 BCE and, by ~2000 BCE, the replacement of 40% of Iberia’s ancestry and nearly 100% of its Y-chromosomes by people with Steppe ancestry. We show that, in the Iron Age, Steppe ancestry had spread not only into Indo-European–speaking regions but also into non-Indo-European–speaking ones, and we reveal that present-day Basques are best described as a typical Iron Age population without the admixture events that later affected the rest of Iberia. Additionally, we document how, beginning at least in the Roman period, the ancestry of the peninsula was transformed by gene flow from North Africa and the eastern Mediterranean.J.M.F., F.J.L.-C., J.I.M., F.X.O., J.D., and M.S.B. were supported by HAR2017-86509-P, HAR2017-87695-P, and SGR2017-11 from the Generalitat de Catalunya, AGAUR agency. C.L.-F. was supported by Obra Social La Caixa and by FEDER-MINECO (BFU2015- 64699-P). L.B.d.L.E. was supported by REDISCO-HAR2017-88035-P (Plan Nacional I+D+I, MINECO). C.L., P.R., and C.Bl. were supported by MINECO (HAR2016-77600-P). A.Esp., J.V.-V., G.D., and D.C.S.-G. were supported by MINECO (HAR2009-10105 and HAR2013-43851-P). D.J.K. and B.J.C. were supported by NSF BCS-1460367. K.T.L., A.W., and J.M. were supported by NSF BCS-1153568. J.F.-E. and J.A.M.-A. were supported by IT622-13 Gobierno Vasco, Diputación Foral de Álava, and Diputación Foral de Gipuzkoa. We acknowledge support from the Portuguese Foundation for Science and Technology (PTDC/EPH-ARQ/4164/2014) and the FEDER-COMPETE 2020 project 016899. P.S. was supported by the FCT Investigator Program (IF/01641/2013), FCT IP, and ERDF (COMPETE2020 – POCI). M.Si. and K.D. were supported by a Leverhulme Trust Doctoral Scholarship awarded to M.B.R. and M.P. D.R. was supported by an Allen Discovery Center grant from the Paul Allen Foundation, NIH grant GM100233, and the Howard Hughes Medical Institute. V.V.-M. and W.H. were supported by the Max Planck Society

The genomic history of the Iberian Peninsula over the past 8000 years

We assembled genome-wide data from 271 ancient Iberians, of whom 176 are from the largely unsampled period after 2000 BCE, thereby providing a high-resolution time transect of the Iberian Peninsula. We document high genetic substructure between northwestern and southeastern hunter-gatherers before the spread of farming. We reveal sporadic contacts between Iberia and North Africa by ~2500 BCE and, by ~2000 BCE, the replacement of 40% of Iberia's ancestry and nearly 100% of its Y-chromosomes by people with Steppe ancestry. We show that, in the Iron Age, Steppe ancestry had spread not only into Indo-European-speaking regions but also into non-Indo-European-speaking ones, and we reveal that present-day Basques are best described as a typical Iron Age population without the admixture events that later affected the rest of Iberia. Additionally, we document how, beginning at least in the Roman period, the ancestry of the peninsula was transformed by gene flow from North Africa and the eastern Mediterranean.J.M.F., F.J.L.-C., J.I.M., F.X.O., J.D., and M.S.B. were supported by HAR2017-86509-P, HAR2017-87695-P, and SGR2017-11 from the Generalitat de Catalunya, AGAUR agency. C.L.-F. was supported by Obra Social La Caixa and by FEDER-MINECO (BFU2015- 64699-P). L.B.d.L.E. was supported by REDISCO-HAR2017-88035-P (Plan Nacional I+D+I, MINECO). C.L., P.R., and C.Bl. were supported by MINECO (HAR2016-77600-P). A.Esp., J.V.-V., G.D., and D.C.S.-G. were supported by MINECO (HAR2009-10105 and HAR2013-43851-P). D.J.K. and B.J.C. were supported by NSF BCS-1460367. K.T.L., A.W., and J.M. were supported by NSF BCS-1153568. J.F.-E. and J.A.M.-A. were supported by IT622-13 Gobierno Vasco, Diputación Foral de Álava, and Diputación Foral de Gipuzkoa. We acknowledge support from the Portuguese Foundation for Science and Technology (PTDC/EPH-ARQ/4164/2014) and the FEDER-COMPETE 2020 project 016899. P.S. was supported by the FCT Investigator Program (IF/01641/2013), FCT IP, and ERDF (COMPETE2020 – POCI). M.Si. and K.D. were supported by a Leverhulme Trust Doctoral Scholarship awarded to M.B.R. and M.P. D.R. was supported by an Allen Discovery Center grant from the Paul Allen Foundation, NIH grant GM100233, and the Howard Hughes Medical Institute. V.V.-M. and W.H. were supported by the Max Planck Society