Modelling of Intensively Blasted Electric Arc

The paper deals with a simplified model of an intensively blasted electric arc burning in the anode chan-nel of an arc heater. The model is based on the energy conservation law, continuity equation and Ohm’s law. For computation, transport and thermodynamic properties of working medium and real experimental results describing the external manifestation of the arc are necessary. Many experimental data have been collected during numerous experiments made out with a modular arc heater operated under various ex-perimental conditions, each experiment being characterized by the arc current, voltage, the sort and flow rate of working gas, and the flow rates and temperatures of cooling water in individual segments of the device. In the presented model a rectangular temperature profile of the arc is used. A dependency of the arc column radius rA on the distance from the cathode is prescribed and parameters of the function rA(z) are estimated using the total power balance at the output cross-section of the anode channel. Special at-tention is paid to the region near the beginning. The dependencies of the arc temperature and electric field intensity on the distance from the cathode are calculated and iterations are stopped if the sums of computed increments agree with the measured values. Computed dependencies are given in diagrams and discussed

Calculation of Arc Power Losses in the Simplified Model of Intensively Blasted Electric Arc

In previous versions of the simplified model of intensively blasted electric arc burning in argon in the arc heater's anode channel, the authors used the constant total power loss coefficient for estimation of arc power losses in all anode channel individual parts. Using this approach, the model with relatively low computational complexity has led to very good agreement between the total computed and experimentally obtained values, but when the computed and measured power losses of individual anode channel segments have been compared, considerable differences have been revealed. In the modified model, theoretically computed net emission coefficient of argon is used in the energy equation to express the arc power losses. This way, satisfactory accordance is achieved between not only the total, but also partial measured and computed values. Exemplary results are given in figures and tables and discussed

Estimation of the Intensively Blasted Electric Arc Model Sensitivity to Selected Variables

Results of measurements carried out on the fabricated experimental modular-type arc heater serve as input data for the designed simplified model of the intensively blasted electric arc burning in argon inside the cylindrical arc heater's anode channel. The axial dependence of the arc temperature and radius is expressed using the exponent, the current density on the cathode tip and the arc temperature at the end of the near-cathode boundary layer. These quantities form the vector of state variables that is sought to minimize the value of the objective function expressing the deviations between measured and computed values. On a typical example, the paper demonstrates the sensitivity of the modelling to individual state variables

Grey wolf genomic history reveals a dual ancestry of dogs

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1–8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located. © 2022, The Author(s).8028-00005B; IP DKRVO 2019-2023, MK000094862; 220457/Z/20/Z, ERC-2013-StG-337574-UNDEAD, ERC-2019-StG-853272-PALAEOFARM; 075-15-2021-1069; European Molecular Biology Organization, EMBO: 217223/Z/19/Z; Vallee Foundation; Velux Fonden; Wellcome Trust, WT; Francis Crick Institute, FCI: FC001595; Horizon 2020 Framework Programme, H2020: 796877; Medical Research Council, MRC; Natural Environment Research Council, NERC: 210119/Z/18/Z, NE/K003259/1, NE/K005243/1, NE/S00078X/1, NE/S007067/1; Cancer Research UK, CRUK; European Research Council, ERC: 852558; Grantová Agentura České Republiky, GA ČR: 15-06446S; Svenska Forskningsrådet Formas: 2018-01640; Knut och Alice Wallenbergs Stiftelse; Vetenskapsrådet, VR: 681396, BELSPO B2/191/P2/ICHIE; Russian Science Foundation, RSF: 16-18-10265-RNF, 20-17-00033, 21-18-00457-RNF, 310763; Science for Life Laboratory, SciLifeLab; Narodowa Agencja Wymiany Akademickiej, NAWA: PPN/PPO/2018/1/00037This work was supported by grants to P. Skoglund from the European Research Council (grant no. 852558), the Erik Philip Sörensen Foundation and the Science for Life Laboratory, Swedish Biodiversity Program, made available by support from the Knut and Alice Wallenberg Foundation. A.B., L.S., P. Swali and P. Skoglund were supported by Francis Crick Institute core funding (FC001595) from Cancer Research UK, the UK Medical Research Council and the Wellcome Trust. P. Skoglund was also supported by the Vallee Foundation, the European Molecular Biology Organisation and the Wellcome Trust (217223/Z/19/Z). Computations were supported by SNIC-UPPMAX. We also acknowledge support from Science for Life Laboratory, the Knut and Alice Wallenberg Foundation, the National Genomics Infrastructure funded by the Swedish Research Council and the Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We thank the Yukon gold mining community and First Nations, including the Tr’ondëk Hwëch’in, for continued support of our palaeontology research in the Yukon Territories, Canada. We thank the Danish National High-Throughput Sequencing Centre and BGI-Europe for assistance in sequencing data generation and the Danish National Supercomputer for Life Sciences–Computerome ( https://computerome.dtu.dk ) for computational resources. We thank National Museum Wales for continued sampling support. M. Germonpré acknowledges support from the Brain.be 2.0 ICHIE project (BELSPO B2/191/P2/ICHIE). M.T.P.G. was supported by the European Research Council (grant no. 681396). M.-H.S.S. was supported by the Velux Foundations through the Qimmeq Project, the Aage og Johanne Louis-Hansens Fond and the Independent Research Fund Denmark (8028-00005B). L.D. acknowledges support from FORMAS (2018-01640). D.W.G.S. received funding for this project from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement no. 796877. M.P. was supported by the Polish National Agency for Academic Exchange–NAWA (grant no. PPN/PPO/2018/1/00037). V.J.S. was supported by the University of Zurich’s University Research Priority Program ‘Evolution in Action: From Genomes to Ecosystems’. This research was done with the participation of ZIN RAS (grant no. 075-15-2021-1069). We are grateful to the museum of the Institute of Plant and Animal Ecology UB RAS (Ekaterinburg, Russia) for provision of samples. R.P.J. and C.O’D. were supported by the Standing Committee for Archaeology of the Royal Irish Academy through the Archaeological Excavation Research Grant Scheme. E.Y.P., P.N. and V.V.P. are supported by the Russian Science Foundation (grant no. 16-18-10265-RNF and 21-18-00457-RNF). Y.V.K. was supported by the Russian Science Foundation (grant no. 20-17-00033). M.H. was supported by the European Research Council (consolidator grant GeneFlow no. 310763). M.L.-G. was supported by the Czech Science Foundation GAČR (grant no. 15-06446S) and institutional financing of the Moravian Museum from the Czech Ministry of Culture (IP DKRVO 2019-2023, MK000094862). L.S. is supported by the Sir Henry Wellcome fellowship (220457/Z/20/Z). We thank Staatliches Museum für Naturkunde Stuttgart for sample access. L.F. and G.L. were supported by European Research Council grants (ERC-2013-StG-337574-UNDEAD and ERC-2019-StG-853272-PALAEOFARM) and Natural Environmental Research Council grants (NE/K005243/1, NE/K003259/1, NE/S007067/1 and NE/S00078X/1). L.F. was also supported by the Wellcome Trust (210119/Z/18/Z). This research was funded in whole, or in part, by the Wellcome Trust (FC001595). For the purpose of open access, the author has applied a CC-BY public copyright licence to any author accepted manuscript version arising from this submission