Opin vísindi
Opin vísindi er varðveislusafn vísindaefnis og doktorsritgerða í opnum aðgangi á vegum íslenskra háskóla og Landsbókasafns Íslands - Háskólabókasafns.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Nýlega bætt við
Electrochemical Production of Silicon Using an Oxygen-Evolving SnO2 Anode in Molten CaCl2-NaCl
(2025-12) Padamata, Sai Krishna; Haarberg, Geir Martin; Saevarsdottir, Gudrun; Department of Engineering
The electrochemical production of silicon from SiO2 in molten salts can reduce energy consumption and mitigate carbon emissions associated with the conventional carbothermic process. In this study, we compare the anodic behaviour of platinum, graphite, and tin oxide electrodes in molten CaCl2-NaCl-CaO-SiO2 at 850 °C using electrochemical methods including cyclic voltammetry, linear sweep voltammetry, and chronoamperometry. Pt exhibited low oxygen evolution overpotentials and no significant currents before OER, compared to SnO2. An eight-hour potentiostatic electrolysis with a SnO2 anode and a graphite cathode yielded a Si-Sn deposit, indicating partial dissolution of the SnO2 anode during the electrolysis process. These results highlight the kinetic trade-off of SnO2 relative to Pt, and the risk of Sn contamination with extended electrolysis times. While SnO2 is unsuitable for production of high-purity Si, it remains a promising anode candidate for Si-Sn alloy formation.
Assessment of defectsin mountain roadway tunnel due to various natural and operational factors – Istiqlol (Republic of Tajikistan)
(2018) Teshaev, Umardzhon R.; Padamata, Sai Krishna; Vokhmin, Sergey A.; Trebush, Yuri P.; Khasanov, Nurali M.; Department of Engineering
The present article analyses the defects in a mountain roadway tunnel (Istiqlol) recorded between 2013 and 2017. The defect analysis of the mountain tunnel is vital as it deals with the safety of the passengers using the tunnel. The factors causing the deterioration of tunnel is discussed in this present work. Deterioration of the tunnel lining is due to continuous maintenance of the tunnel is the biggest threat to the durability of the tunnel. Infiltration of groundwater through seismic (deformation) seams, cracks through the tunnel lining have a special role in deteriorating the state of the tunnel construction, which leads to minor surface corrosion to major ones. The defects in the tunnel were noted personally in a regular basis between the years 2013 and 2017. Defects were categorized into 6 different types with respect to their nature. Probability plots were plotted with help of MINITAB software to analyse the probability at which a particular value of Technical condition severity occurs. The final observations states the main reason for the defects in the tunnel.
A comparative analysis of unsupervised machine-learning methods in PSG-related phenotyping
(2025-06) Ghorvei, Mohammadreza; Karhu, Tuomas; Hietakoste, Salla; Ferreira-Santos, Daniela; Hrubos-Strøm, Harald; Islind, Anna Sigridur; Biedebach, Luka; Nikkonen, Sami; Leppänen, Timo; Rusanen, Matias; Department of Computer Science; Department of Engineering
Obstructive sleep apnea is a heterogeneous sleep disorder with varying phenotypes. Several studies have already performed cluster analyses to discover various obstructive sleep apnea phenotypic clusters. However, the selection of the clustering method might affect the outputs. Consequently, it is unclear whether similar obstructive sleep apnea clusters can be reproduced using different clustering methods. In this study, we applied four well-known clustering methods: Agglomerative Hierarchical Clustering; K-means; Fuzzy C-means; and Gaussian Mixture Model to a population of 865 suspected obstructive sleep apnea patients. By creating five clusters with each method, we examined the effect of clustering methods on forming obstructive sleep apnea clusters and the differences in their physiological characteristics. We utilized a visualization technique to indicate the cluster formations, Cohen's kappa statistics to find the similarity and agreement between clustering methods, and performance evaluation to compare the clustering performance. As a result, two out of five clusters were distinctly different with all four methods, while three other clusters exhibited overlapping features across all methods. In terms of agreement, Fuzzy C-means and K-means had the strongest (κ = 0.87), and Agglomerative hierarchical clustering and Gaussian Mixture Model had the weakest agreement (κ = 0.51) between each other. The K-means showed the best clustering performance, followed by the Fuzzy C-means in most evaluation criteria. Moreover, Fuzzy C-means showed the greatest potential in handling overlapping clusters compared with other methods. In conclusion, we revealed a direct impact of clustering method selection on the formation and physiological characteristics of obstructive sleep apnea clusters. In addition, we highlighted the capability of soft clustering methods, particularly Fuzzy C-means, in the application of obstructive sleep apnea phenotyping.
Aluminium recycling in single-and multiple-capillary laboratory electrolysis cells
(2021-07) Yasinskiy, Andrey; Padamata, Sai Krishna; Moiseenko, Ilya; Stopic, Srecko; Feldhaus, Dominic; Friedrich, Bernd; Polyakov, Peter; Department of Engineering
This work is a contribution to the approach for Al purification and extraction from scrap using the thin-layer multiple-capillary molten salt electrochemical system. The single-and multiple-capillary cells were designed and used to study the kinetics of aluminium reduction in LiF–AlF3 and equimolar NaCl–KCl with 10 wt.% AlF3 addition at 720–850◦C. The cathodic process on the vertical liquid aluminium electrode in NaCl–KCl (+10 wt.% AlF3) in the 2.5 mm length capillary had mixed kinetics with signs of both diffusion and chemical reaction control. The apparent mass transport coefficient changed from 5.6·10−3 cm.s−1 to 13.1·10−3 cm.s−1 in the mentioned temperature range. The dependence between the mass transport coefficient and temperature follows an Arrhenius-type behaviour with an activation energy equal to 60.5 J.mol−1. In the multiple-capillary laboratory electrolysis cell, galvanostatic electrolysis in a 64LiF–36AlF3 melt showed that the electrochemical refinery can be performed at a current density of 1 A.cm−2 or higher with a total voltage drop of around 2.0 V and specific energy consumption of about 6–7 kW.kg−1 . The resistance fluctuated between 0.9 and 1.4 Ω during the electrolysis depending on the current density. Thin-layer aluminium recycling and refinery seems to be a promising approach capable of producing high-purity aluminium with low specific energy consumption.
Review of Snow Data Assimilation Methods for Hydrological, Land Surface, Meteorological and Climate Models: Results from a COST HarmoSnow Survey
(2018-12-14) Helmert, Jürgen; Şensoy Şorman, Aynur; Alvarado Montero, Rodolfo; De Michele, Carlo; de Rosnay, Patricia; Dumont, Marie; Finger, David C.; Lange, Martin; Picard, Ghislain; Potopová, Vera; Pullen, Samantha; Vikhamar-Schuler, Dagrun; Arslan, Ali; Department of Engineering
The European Cooperation in Science and Technology (COST) Action ES1404 HarmoSnow, entitled, A European network for a harmonized monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction (2014-2018) aims to coordinate efforts in Europe to harmonize approaches to validation, and methodologies of snow measurement practices, instrumentation, algorithms and data assimilation (DA) techniques. One of the key objectives of the action was Advance the application of snow DA in numerical weather prediction (NWP) and hydrological models and show its benefit for weather and hydrological forecasting as well as other applications. This paper reviews approaches used for assimilation of snow measurements such as remotely sensed and in situ observations into hydrological, land surface, meteorological and climate models based on a COST HarmoSnow survey exploring the common practices on the use of snow observation data in different modeling environments. The aim is to assess the current situation and understand the diversity of usage of snow observations in DA, forcing, monitoring, validation, or verification within NWP, hydrology, snow and climate models. Based on the responses from the community to the questionnaire and on literature review the status and requirements for the future evolution of conventional snow observations from national networks and satellite products, for data assimilation and model validation are derived and suggestions are formulated towards standardized and improved usage of snow observation data in snow DA. Results of the conducted survey showed that there is a fit between the snow macro-physical variables required for snow DA and those provided by the measurement networks, instruments, and techniques. Data availability and resources to integrate the data in the model environment are identified as the current barriers and limitations for the use of new or upcoming snow data sources. Broadening resources to integrate enhanced snow data would promote the future plans to make use of them in all model environments.
Flokkar í Opnum vísindum
Veldu flokk til að skoða.
- University of Iceland
- University of Akureyri
- Bifröst University
- Hólar University College
- IRIS
- Agricultural University of Iceland
- National and University Library of Iceland
- Iceland University of the Arts