Turbulent transport in tokamak plasmas: linear-, quasi- and non-linear simulations

An attractive energy source is nuclear fusion with its abundance of fuel, intrinsic safety and limited environmental impact. Although the concept of fusion energy was established in the 1920s, to develop fusion as an energy source has been challenging. The most developed concept for fusion is the tokamak, a torodial shaped chamber where a plasma, a hot ionized gas, is confined with a strong magnetic field. The feasibility and efficiency of the future fusion power plants depend critically on the energy confinement properties of the tokamaks which are mainly determined by micro turbulence.The turbulent transport is driven by different instabilities in the plasma, especially the Ion Temperature Gradient (ITG) mode, Trapped Electron Mode (TEM) and Electron Temperature Gradient (ETG) mode. The work presented in this thesis focuses on a number of key aspects of turbulent transport using advanced numerical modelling tools. In today\u27s experiments, measurements have shown the plasma\u27s densities to be peaked towards the centre of the plasma. Research into this peaking has uncovered two key mechanisms, a strong particle pinch from the turbulent transport and a particle source from Neutral Beam Injection which is used to heat plasma. In future tokamaks the source will be comparatively smaller, hence it is important to distinguish which of the two provides the dominant contribution. Which is one of the aspects analysed in the thesis. From basic considerations, the turbulent transport should exhibit so called gyro-Bohm scaling, i.e. the transport should increase with the ionic mass. However, this is not observed experimentally and the discrepancy is called the isotope effect. Several mechanism has been suggested as the cause, such as collisions, ExB shear, beta-effects, edge effects and contribution of the ETG mode. A number of JET discharges design to study this isotope effect have been analysed to asses the relative importance of these effects, Calculation of the turbulent transport can be computationally expensive, therefore reduced quasi-linear models that are computationally less intensive have been developed. These models use linear relations between perturbed quantities combined with a saturation rule for the electrostatic potential to determine the turbulent fluxes. A saturation rule adapted to a quasi-linear model has been developed and validated against non-linear gyro-kinetic simulations which are characterized by a high degree of physics fidelity

Upgrade and benchmark of quasi-linear transport model EDWM

The verification of a new saturation rule applied to the quasi-linear fluid model EDWM (extended drift wave model) and the calibration of several other features are presented. As one of the computationally fastest first-principle-based core transport models, EDWM can include an arbitrary number of ions and charge states. This feature is especially important for experimental devices with plasma-facing components made of heavy elements, such as the upcoming ITER device. As a quasi-linear model, EDWM solves a linear dispersion relation to obtain the instabilities driving the turbulence and combines the linear description with an estimation of the saturation level of the electrostatic potential to determine the fluxes. A new saturation rule at the characteristic length combined with a spectral filter for the poloidal wavenumber dependency is developed. The shape of the filter has been fitted against the poloidal wavenumber dependency of the electrostatic potential from non-linear gyrokinetic simulations. Additionally, EDWM\u27s collision frequency and safety factor dependencies, as well as the electron heat flux level, have been calibrated against gyrokinetic and gyrofluid results. Finally, the saturation level has been normalized against non-linear gyrokinetic simulations and later validated against experimental measured fluxes from 12 discharges at JET

Enabling adaptive pedestals in predictive transport simulations using neural networks

We present PEdestal Neural Network (PENN) as a machine learning model for tokamak pedestal predictions. Here, the model is trained using the EUROfusion JET pedestal database to predict the electron pedestal temperature and density from a set of global engineering and plasma parameters. Results show that PENN makes accurate predictions on the test set of the database, with R (2) = 0.93 for the temperature, and R (2) = 0.91 for the density. To demonstrate the applicability of the model, PENN is employed in the European transport simulator (ETS) to provide boundary conditions for the core of the plasma. In a case example in the ETS with varied neutral beam injection (NBI) power, results show that the model is consistent with previous studies regarding NBI power dependency on the pedestal. Additionally, we show how an uncertainty estimation method can be used to interpret the reliability of the predictions. Future work includes further analysis of how pedestal models, such as PENN, or other advanced deep learning models, can be more efficiently implemented in integrating modeling frameworks, and also how similar models may be generalized with respect to other tokamaks and future device scenarios

11q deletion or ALK activity curbs DLG2 expression to maintain an undifferentiated state in neuroblastoma

High-risk neuroblastomas typically display an undifferentiated or poorly differentiated morphology. It is therefore vital to understand molecular mechanisms that block the differentiation process. We identify an important role for oncogenic ALK-ERK1/2-SP1 signaling in the maintenance of undifferentiated neural crest-derived progenitors through the repression of DLG2, a candidate tumor suppressor gene in neuroblastoma. DLG2 is expressed in the murine "bridge signature'' that represents the transcriptional transition state when neural crest cells or Schwann cell precursors differentiate to chromaffin cells of the adrenal gland. We show that the restoration of DLG2 expression spontaneously drives neuroblastoma cell differentiation, high-lighting the importance of DLG2 in this process. These findings are supported by genetic analyses of high-risk 11q deletion neuroblastomas, which identified genetic lesions in the DLG2 gene. Our data also suggest that further exploration of other bridge genes may help elucidate the mechanisms underlying the differentiation of NC-derived progenitors and their contribution to neuroblastomas

Ventilation of the Arctic Ocean: Mean ages and inventories of anthropogenic CO2 and CFC-11

The Arctic Ocean constitutes a large body of water that is still relatively poorly surveyed because of logistical difficulties, although the importance of the Arctic Ocean for global circulation and climate is widely recognized. For instance, the concentration and inventory of anthropogenic CO2 (C ant) in the Arctic Ocean are not properly known despite its relatively large volume of well-ventilated waters. In this work, we have synthesized available transient tracer measurements (e.g., CFCs and SF6) made during more than two decades by the authors. The tracer data are used to estimate the ventilation of the Arctic Ocean, to infer deep-water pathways, and to estimate the Arctic Ocean inventory of C ant. For these calculations, we used the transit time distribution (TTD) concept that makes tracer measurements collected over several decades comparable with each other. The bottom water in the Arctic Ocean has CFC values close to the detection limit, with somewhat higher values in the Eurasian Basin. The ventilation time for the intermediate water column is shorter in the Eurasian Basin (∼200 years) than in the Canadian Basin (∼300 years). We calculate the Arctic Ocean C ant inventory range to be 2.5 to 3.3 Pg-C, normalized to 2005, i.e., ∼2% of the global ocean C ant inventory despite being composed of only ∼1% of the global ocean volume. In a similar fashion, we use the TTD field to calculate the Arctic Ocean inventory of CFC-11 to be 26.2 ± 2.6 × 106 moles for year 1994, which is ∼5% of the global ocean CFC-11 inventor

Constraining the Oceanic Uptake and Fluxes of Greenhouse Gases by Building an Ocean Network of Certified Stations: The Ocean Component of the Integrated Carbon Observation System, ICOS-Oceans

The European Research Infrastructure Consortium “Integrated Carbon Observation System” (ICOS) aims at delivering high quality greenhouse gas (GHG) observations and derived data products (e.g., regional GHG-flux maps) for constraining the GHG balance on a European level, on a sustained long-term basis. The marine domain (ICOS-Oceans) currently consists of 11 Ship of Opportunity lines (SOOP – Ship of Opportunity Program) and 10 Fixed Ocean Stations (FOSs) spread across European waters, including the North Atlantic and Arctic Oceans and the Barents, North, Baltic, and Mediterranean Seas. The stations operate in a harmonized and standardized way based on community-proven protocols and methods for ocean GHG observations, improving operational conformity as well as quality control and assurance of the data. This enables the network to focus on long term research into the marine carbon cycle and the anthropogenic carbon sink, while preparing the network to include other GHG fluxes. ICOS data are processed on a near real-time basis and will be published on the ICOS Carbon Portal (CP), allowing monthly estimates of CO2 air-sea exchange to be quantified for European waters. ICOS establishes transparent operational data management routines following the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles allowing amongst others reproducibility, interoperability, and traceability. The ICOS-Oceans network is actively integrating with the atmospheric (e.g., improved atmospheric measurements onboard SOOP lines) and ecosystem (e.g., oceanic direct gas flux measurements) domains of ICOS, and utilizes techniques developed by the ICOS Central Facilities and the CP. There is a strong interaction with the international ocean carbon cycle community to enhance interoperability and harmonize data flow. The future vision of ICOS-Oceans includes ship-based ocean survey sections to obtain a three-dimensional understanding of marine carbon cycle processes and optimize the existing network design

Usefulness of financial reports –A study of the information need in banks’ credit assessment

Background and problem: Financial reports are created for the users as decision support. Stakeholders are often subjects to information asymmetry. Banks represent one of the primary stakeholders and financiers of a company, and place great emphasis on financial reports in their credit assessment process. The question is, however, how useful the financial information actually is. According to previous research, banks consider accounting information as troublesome in some respects, mostly due to accounting choices and judgments. As the newly introduced K-regulations in Sweden are mandatory from 2014, it is not clear how the choice between K2 and K3 will affect a company’s creditworthiness. Purpose: The purpose of this study is to investigate the usefulness of accounting information presented in financial reports, as a part of banks’ information need in the credit assessment process. Methodology: To achieve the purpose, a qualitative research was used. Empirical material was gathered through semi-structured interviews with respondents representing five different banks in Sweden. The respondents were bank officers with great knowledge in the credit assessment process. Secondary data formed the frame of reference, and was collected mainly from scientific articles and doctoral dissertations. Findings and conclusions: This study shows that accounting information is useful and represents one of the main components in the corporate analysis when the bank is performing credit assessment. Since the banks’ rating systems do not alter financial information; two identical companies, apart their choice of K2 and K3, may receive different ratings and consequently different interest rates. However, banks thorough corporate analysis is favorable when changes in accounting regulations are implemented. As they possess great knowledge in the company’s business, accounting choices and regulations becomes almost a non-issue

Simulation and assessment of particle transport in fusion plasmas

A civilized society need energy to function. An attractive new energy source is nuclear fusion with its abundance of fuel, intrinsic safety and limited environmental impact. Although the concept of fusion for energy has been well understood for over a century, to create it here on earth has been more irksome. The most developed concept for fusion is the tokamak, which is a torodial shaped chamber where a hot ionized gas, a plasma, is confined with a strong magnetic field. Early concepts showed promising results, however later machines showed much larger transport than was expected, this was due to turbulent transport.The plasma can be described in a number of different ways, fluid or kinetic descriptions. As the particles are confined to the magnetic field lines due to Lorentz force and this process, called gyromotion, is one of the fastest process in the plasma, it is beneficial to average out this motion. This is the basis of gyrofluid and gyrokinetic descriptions. Several different codes have been devolved such as EDWM, TGLF and GENE etc from the fluid, gyrofluid and gyrokinetic descriptions. All these describes the different instabilities which dominates the plasma: the Ion Temperature Gradient (ITG), Trapped Electron Mode (TEM) and Electron Temperature Gradient (ETG).After introducing the aforementioned descriptions of the plasma we discuss the density peaking of the plasma as it important for the efficiency of a commercial fusion power plan