Taherdangkoo, Reza

[["dc.bibliographiccitation.artnumber","S0169772221000838"],["dc.bibliographiccitation.firstpage","103844"],["dc.bibliographiccitation.journal","Journal of Contaminant Hydrology"],["dc.bibliographiccitation.volume","242"],["dc.contributor.author","Taherdangkoo, Reza"],["dc.contributor.author","Liu, Quan"],["dc.contributor.author","Xing, Yixuan"],["dc.contributor.author","Yang, Huichen"],["dc.contributor.author","Cao, Viet"],["dc.contributor.author","Sauter, Martin"],["dc.contributor.author","Butscher, Christoph"],["dc.date.accessioned","2021-12-01T09:23:36Z"],["dc.date.available","2021-12-01T09:23:36Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1016/j.jconhyd.2021.103844"],["dc.identifier.pii","S0169772221000838"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/94701"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-478"],["dc.relation.issn","0169-7722"],["dc.title","Predicting methane solubility in water and seawater by machine learning algorithms: Application to methane transport modeling"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","S0022169422002530"],["dc.bibliographiccitation.firstpage","127678"],["dc.bibliographiccitation.journal","Journal of Hydrology"],["dc.bibliographiccitation.volume","609"],["dc.contributor.author","Xing, Yixuan"],["dc.contributor.author","Liu, Quan"],["dc.contributor.author","Hu, Rui"],["dc.contributor.author","Gu, Hongbiao"],["dc.contributor.author","Taherdangkoo, Reza"],["dc.contributor.author","Yang, Huichen"],["dc.contributor.author","Ptak, Thomas"],["dc.date.accessioned","2022-06-01T09:40:19Z"],["dc.date.available","2022-06-01T09:40:19Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.1016/j.jhydrol.2022.127678"],["dc.identifier.pii","S0022169422002530"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/108698"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-572"],["dc.relation.issn","0022-1694"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","A general numerical model for water level response to harmonic disturbances in aquifers considering wellbore effects"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","S0169772221001492"],["dc.bibliographiccitation.firstpage","103910"],["dc.bibliographiccitation.journal","Journal of Contaminant Hydrology"],["dc.bibliographiccitation.volume","243"],["dc.contributor.author","Taherdangkoo, Reza"],["dc.contributor.author","Yang, Huichen"],["dc.contributor.author","Akbariforouz, Mohammadreza"],["dc.contributor.author","Sun, Yuantian"],["dc.contributor.author","Liu, Quan"],["dc.contributor.author","Butscher, Christoph"],["dc.date.accessioned","2021-12-01T09:24:13Z"],["dc.date.available","2021-12-01T09:24:13Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1016/j.jconhyd.2021.103910"],["dc.identifier.pii","S0169772221001492"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/94882"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-478"],["dc.relation.issn","0169-7722"],["dc.title","Gaussian process regression to determine water content of methane: Application to methane transport modeling"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","128148"],["dc.bibliographiccitation.journal","Journal of Hydrology"],["dc.bibliographiccitation.volume","612"],["dc.contributor.author","Yang, Huichen"],["dc.contributor.author","Liu, Quan"],["dc.contributor.author","Hu, Rui"],["dc.contributor.author","Ptak, Thomas"],["dc.contributor.author","Taherdangkoo, Reza"],["dc.contributor.author","Liu, Yuxi"],["dc.contributor.author","Noubactep, Chicgoua"],["dc.date.accessioned","2022-12-01T08:30:39Z"],["dc.date.available","2022-12-01T08:30:39Z"],["dc.date.issued","2022"],["dc.description.sponsorship"," http://dx.doi.org/10.13039/501100002855 Ministry of Science and Technology of the People's Republic of China"],["dc.identifier.doi","10.1016/j.jhydrol.2022.128148"],["dc.identifier.pii","S0022169422007223"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/117945"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-621"],["dc.relation.issn","0022-1694"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","Numerical case studies on long-term effectiveness of metallic iron based permeable reactive barriers: Importance of porosity heterogeneity of the barrier"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","10"],["dc.bibliographiccitation.journal","Data"],["dc.bibliographiccitation.volume","7"],["dc.contributor.affiliation","Taherdangkoo, Reza; 1TU Bergakademie Freiberg, Institute of Geotechnics, Gustav-Zeuner-Str. 1, 09599 Freiberg, Germany"],["dc.contributor.affiliation","Tian, Miaomiao; 2School of Mines, China University of Mining and Technology, Xuzhou 221116, China"],["dc.contributor.affiliation","Sadighi, Ali; 1TU Bergakademie Freiberg, Institute of Geotechnics, Gustav-Zeuner-Str. 1, 09599 Freiberg, Germany"],["dc.contributor.affiliation","Meng, Tao; 3Taiyuan University of Science and Technology, Taiyuan 030024, China"],["dc.contributor.affiliation","Yang, Huichen; 4Department of Applied Geology, Geosciences Center, University of Göttingen, Goldschmidtstr. 3, D-37077 Göttingen, Germany"],["dc.contributor.affiliation","Butscher, Christoph; 1TU Bergakademie Freiberg, Institute of Geotechnics, Gustav-Zeuner-Str. 1, 09599 Freiberg, Germany"],["dc.contributor.author","Taherdangkoo, Reza"],["dc.contributor.author","Tian, Miaomiao"],["dc.contributor.author","Sadighi, Ali"],["dc.contributor.author","Meng, Tao"],["dc.contributor.author","Yang, Huichen"],["dc.contributor.author","Butscher, Christoph"],["dc.date.accessioned","2022-11-15T16:00:36Z"],["dc.date.available","2022-11-15T16:00:36Z"],["dc.date.issued","2022-10-16"],["dc.date.updated","2022-11-11T13:12:21Z"],["dc.description.abstract","Calcium sulfate exists in three forms, namely dihydrate or gypsum (CaSO4·2H2O), anhydrite (CaSO4), and hemihydrate or bassanite (CaSO4·0.5H2O) depending on temperature, pressure, pH, and formation conditions. The formation of calcium sulfates occurs widely in nature and in many engineering settings. Herein, a dataset containing the experimental solubility data of calcium sulfate minerals, i.e., gypsum and anhydrite, in aqueous solutions is presented. The compiled dataset contains calcium sulfates solubility values extracted from 42 papers published between 1906 and 2019. The dataset can be used for various scientific and engineering purposes such as environmental applications (e.g., gas treatment, wastewater treatment, and chemical disposal), geotechnical applications (e.g., clay-sulfate rock swelling), separation processes (e.g., crystallization, extractive distillation, and seawater desalination), and electrochemical processes (e.g., corrosion and electrolysis)."],["dc.description.sponsorship","German Research Foundation DFG"],["dc.identifier.doi","10.3390/data7100140"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/117055"],["dc.language.iso","en"],["dc.relation.eissn","2306-5729"],["dc.title","Experimental Data on Solubility of the Two Calcium Sulfates Gypsum and Anhydrite in Aqueous Solutions"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]