OIM analysis of microstructure and texture of a TRIP assisted steel after static and dynamic deformation

TRIP-assisted steel with a composition of 0.2%C, 1.6%Mn, 1.5%Al was studied in the undeformed state, after the application of 10 and 30 % static tensile strain parallel to rolling the direction of the sheet and after dynamic (Hopkinson) fracture test. Detailed examination of the microstructure and microtexture by means of electron backscattered diffraction (EBSD) was carried out in order to quantify the microstructural constituents and to study the strain distribution. The microtexture evolution and the distribution of the specific texture components between the BCC and FCC phases were studied as a function of the external strain and the strain mode-static or dynamic. The strain localization and strain distribution between the structural constituents were quantified based on local misorientation maps. The full constraint Taylor model was used to predict the texture changes in the material and the results were compared to the experimental findings. Comparing the local misorientation data it was found that at low strains the ferrite accommodates approximately 10 times more deformation than the retained austenite. The strain localizes initially on the BCC-FCC phase boundaries and is then spread in the BCC constituents (ferrite and bainite) creating a deformation skeleton in the BCC phase. It was found that the observed texture changes in the measured retained austenite texture after deformation do not correspond exactly to the model prediction. The austenite texture components which were predicted by the Taylor model were not found in the measured austenite texture after deformation which means that they are first transformed to martensite, which is considered as an indication for the selective transformation of austenite under strain

Проектирование системы электроснабжения домостроительной компании

Объектом исследования является ремонтно-механический цех домостроительной компании. Целью работы является развитие промышленной энергосистемы. Основные конструктивные, технические, технологические и эксплуатационные характеристики: исследуемый завод состоит из пятнадцати цехов, восемь из которых относятся к II категории надежности электроснабжения; Напряжение питающей сети 35 кВ; Рабочее напряжение на предприятии: 10, 0,4 кВ; Питание электроприемников ремонтно-механического цеха осуществляется смешанной сетью электроснабжения.The object of the research is an maintenance shop of a house building factory. The objective of the work is development of an industrial power system. Main constructive, technical, technological and operational characteristic: the studied plant consists of fifteen workshops, eight of them refer to the II power supply reliability category; the feedline voltage is 35 kV; operation voltage in the plant: 10, 0,4 kV; power supply of electrical receivers of the maintenance shop is realized by mixed power supply network

Determination of the high strain rate forming properties of steel sheet

The strain rate dependence of the plastic yield and failure properties displayed by most metals affects energies, forces and forming limits involved in high speed forming processes. In this contribution a technique is presented to assess the influence of the strain rate on the forming properties of steel sheets. In a first step, static and high strain rate tensile experiments are carried out in order to characterize the materials strain rate dependent behaviour. In a second step, the phenomenological Johnson-Cook model and physically-based Voce model are used to describe the constitutive material behaviour. The test results are subsequently used to calculate the forming limit diagrams by a technique based on the Marciniak-Kuczynski model. With the developed technique, static and dynamic forming limit diagrams are obtained for a commercial DC04 steel and a laboratory made CMnAl TRIP steel. The results clearly indicate that increasing the strain rate during a forming process can have a positive or negative effect

Analog VLSI implementation of kernel-based classifiers

Kernel-based classifiers are neural networks (radial basis functions) where the probability densities of each class of data are first estimated, to be used thereafter to approximate Bayes boundaries between classes. Such an algorithm however involves a large number of operations, and its parallelism makes it an ideal candidate for a dedicated VLSI implementation. The authors present in this paper the architecture for a dedicated processor for kernel-based classifiers, and the implementation of the original cells.Peer ReviewedPostprint (published version

Machine Learning and Data Analysis in Astroinformatics

Astroinformatics is a new discipline at the cross-road of astronomy, advanced statistics and computer science. With next generation sky surveys, space missions and modern instrumentation astronomy will enter the Petascale regime raising the demand for advanced computer science techniques with hard- and software solutions for data management, analysis, efficient automation and knowledge discovery. This tutorial reviews important developments in astroinformatics over the past years and discusses some relevant research questions and concrete problems. The contribution ends with a short review of the special session papers in these proceedings, as well as perspectives and challenges for the near future

Analyzing subcomponents of affective dysregulation in borderline personality disorder in comparison to other clinical groups using multiple e-diary datasets

Background: Affective dysregulation is widely regarded as being the core problem in patients with borderline personality disorder (BPD). Moreover, BPD is the disorder mainly associated with affective dysregulation. However, the empirical confirmation of the specificity of affective dysregulation for BPD is still pending. We used a validated approach from basic affective science that allows for simultaneously analyzing three interdependent components of affective dysregulation that are disturbed in patients with BPD: homebase, variability, and attractor strength (return to baseline). Methods: We applied two types of multilevel models on two e-diary datasets to investigate group differences regarding three subcomponents between BPD patients (n =43; n =51) and patients with posttraumatic stress disorder (PTSD; n= 28) and those with bulimia nervosa (BN; n= 20) as clinical control groups in dataset 1, and patients with panic disorder (PD; n= 26) and those with major depression (MD; n =25) as clinical control groups in dataset 2. In addition, healthy controls (n= 28; n= 40) were included in the analyses. In both studies, e-diaries were used to repeatedly collect data about affective experiences during participants’ daily lives. In study 1 a high-frequency sampling strategy with assessments in 15 min-intervals over 24 h was applied, whereas the assessments occurred every waking hour over 48 h in study 2. The local ethics committees approved both studies, and all participants provided written informed consent. Results: In contradiction to our hypotheses, BPD patients did not consistently show altered affective dysregulation compared to the clinical patient groups. The only differences in affective dynamics in BPD patients emerged with regard to one of three subcomponents, affective homebase. However, these results were not even consistent. Conversely, comparing the patients to healthy controls revealed a pattern of more negative affective homebases, higher levels of affective variability, and (partially) reduced returns to baseline in the patient groups. Conclusions: Our results indicate that affective dysregulation constitutes a transdiagnostic mechanism that manifests in similar ways in several different mental disorders. We point out promising prospects that might help to elucidate the common and distinctive mechanisms that underlie several different disorders and that should be addressed in future studies

Reviewing, indicating, and counting books for modern research evaluation systems

In this chapter, we focus on the specialists who have helped to improve the conditions for book assessments in research evaluation exercises, with empirically based data and insights supporting their greater integration. Our review highlights the research carried out by four types of expert communities, referred to as the monitors, the subject classifiers, the indexers and the indicator constructionists. Many challenges lie ahead for scholars affiliated with these communities, particularly the latter three. By acknowledging their unique, yet interrelated roles, we show where the greatest potential is for both quantitative and qualitative indicator advancements in book-inclusive evaluation systems.Comment: Forthcoming in Glanzel, W., Moed, H.F., Schmoch U., Thelwall, M. (2018). Springer Handbook of Science and Technology Indicators. Springer Some corrections made in subsection 'Publisher prestige or quality

All downhill from the PhD? The typical impact trajectory of US academic careers

© 2020 The Authors. Published by MIT Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1162/qss_a_00072.Within academia, mature researchers tend to be more senior, but do they also tend to write higher impact articles? This article assesses long-term publishing (16+ years) United States (US) researchers, contrasting them with shorter-term publishing researchers (1, 6 or 10 years). A long-term US researcher is operationalised as having a first Scopus-indexed journal article in exactly 2001 and one in 2016-2019, with US main affiliations in their first and last articles. Researchers publishing in large teams (11+ authors) were excluded. The average field and year normalised citation impact of long- and shorter-term US researchers’ journal articles decreases over time relative to the national average, with especially large falls to the last articles published that may be at least partly due to a decline in self-citations. In many cases researchers start by publishing above US average citation impact research and end by publishing below US average citation impact research. Thus, research managers should not assume that senior researchers will usually write the highest impact papers