Data for paper: DECAF Cross-device characterization of tokamak disruptions indicated by abnormalities in plasma vertical position and current
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Publications and source records attributed to Erickson, K..
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An overview of advances and progress on the KSTAR plasma control improvement is given. The enhancement of the KSTAR plasma control system (PCS) continues in order to enable implementations of more sophisticated control algorithms and capabilities of integrated controls on magnets, gas, heating and off-normal event handling. Features and functionalities on the generic magnetic controls, kinetic controls and new fault scheme design are added for the operation space expansion, mainly regarding recent achievements of higher plasma current up to 1.0–1.2MA, high-performance long pulse up to 90s, and discharges relevant to ITER. Technical challenges and prospective upgrades in the near future are described.
In this paper, we report on disruption prediction using a shallow machinelearning method known as Random Forests, trained on large databases containingonly plasma parameters that are available in real-time on Alcator C-Mod, DIII-D, and EAST. The database for each tokamak contains parameters sampled ~10 6 times throughout ~10 4 discharges (disruptive and non-disruptive) over the last 4years of operation. It is found that a number of parameters (e.g.P rad /P input ,l i ,n/n G ,B n=1 /B 0 ) exhibit changes in aggregate as a disruption is approached on one ormore of these tokamaks. However, for each machine, the most useful parameters,as well as the details of their precursor behaviors, are markedly different. When the prediction problem is framed using a binary classification scheme to discriminate between time slices "close to disruption" and "far from disruption," it is found that the prediction algorithms differ substantially in performance among the three machines ona time slice-by-time slice basis, but have similar disruption detection rates (~80-90%) on a shot-by-shot basis after appropriate optimisation. This could have important implications for disruption prediction and avoidance on ITER, for which developmentof a training database of disruptions may be infeasible. The algorithm's output is interpretable using a method that identifies the most strongly contributing inputsignals, which may have implications for avoiding disruptive scenarios. Lastly, to further support its real-time capability, successful applications in inter-shot and real-time environments on EAST and DIII-D are also discussed.
A new model of heating, current drive, torque and other effects of neutral beam injection on NSTX-U that uses neural networks has been developed. The model has been trained and tested on the results of the Monte Carlo code NUBEAM for the database of experimental discharges taken during the first operational campaign of NSTX-U. By projecting flux surface quantities onto empirically derived basis functions, the model is able to efficiently and accurately reproduce the behavior of both scalars, like the total neutron rate and shine through, and profiles, like beam current drive and heating. With this being said, the model has been tested on the NSTX-U real-time computer, demonstrating a rapid execution time orders of magnitude faster than the Monte Carlo code that is well suited for the iterative calculations needed to interpret experimental results, optimization during scenario development activities, and real-time plasma control applications. Simulation results of a proposed design for a nonlinear observer that embeds the neural network calculations to estimate the poloidal flux profile evolution, as well as Z eff and fast ion diffusivity, are presented.
MDSplus is a data acquisition and analysis system used worldwide predominantly in the fusion research community. Development began 31 years ago by a collaboration of software developers who were charged with providing a data acquisition system for three new fusion experiments under construction: CMOD at MIT, ZTH at LANL and RFX at Padova, Italy. The design of MDSplus combined the functionality of MDS (MIT/Model Data System developed at MIT for the Alcator and Tara fusion experiments) with new features suggested by the developers from the other laboratories. The development of MDSplus used a RAD (rapid application development) approach before RAD became a mainstream methodology. MDSplus was implemented and ready for the initial operation of CMOD in 1991. Since that time, many other fusion facilities started using MDSplus for data acquisition and/or for exporting their data to other sites. Today MDSplus is still used around the world for fusion energy research, space exploration and other fields of science and technology. Work on MDSplus continues to enhance its capabilities, support more platforms, and improve its reliability. It is anticipated that MDSplus will continue to provide valuable tools for the fusion energy research community. This paper describes some of the history of the MDSplus software, the work that is currently underway, and the plans to enable MDSplus to continue to be available and supported long into the future.
Here, the upgrade to the National Spherical Torus eXperiment (NSTX-U) included two main improvements: a larger center-stack, enabling higher toroidal field and longer pulse duration, and the addition of three new tangentially aimed neutral beam sources, which increase available heating and current drive, and allow for flexibility in shaping power, torque, current, and particle deposition profiles. To best use these new capabilities and meet the high-performance operational goals of NSTX-U, major upgrades to the NSTX-U control system (NCS) hardware and software have been made. Several control algorithms, including those used for real-time equilibrium reconstruction and shape control, have been upgraded to improve and extend plasma control capabilities. As part of the commissioning phase of first plasma operations, the shape control system was tuned to control the boundary in both inner-wall limited and diverted discharges. It has been used to accurately track the requested evolution of the boundary (including the size of the inner gap between the plasma and central solenoid, which is a challenge for the ST configuration), X-point locations, and strike point locations, enabling repeatable discharge evolutions for scenario development and diagnostic commissioning.
MDSplus is a data acquisition and analysis system used worldwide predominantly in the fusion research community. Development began 31 years ago by a collaboration of software developers who were charged with providing a data acquisition system for three new fusion experiments under construction: CMOD at MIT, ZTH at LANL and RFX at Padova, Italy. The design of MDSplus combined the functionality of MDS (MIT/Model Data System developed at MIT for the Alcator and Tara fusion experiments) with new features suggested by the developers from the other laboratories. The development of MDSplus used a RAD (rapid application development) approach before RAD became a mainstream methodology. MDSplus was implemented and ready for the initial operation of CMOD in 1991. Since that time, many other fusion facilities started using MDSplus for data acquisition and/or for exporting their data to other sites. Today MDSplus is still used around the world for fusion energy research, space exploration and other fields of science and technology. Work on MDSplus continues to enhance its capabilities, support more platforms, and improve its reliability. It is anticipated that MDSplus will continue to provide valuable tools for the fusion energy research community. In conclusion, this paper describes some of the history of the MDSplus software, the work that is currently underway, and the plans to enable MDSplus to continue to be available and supported long into the future.
NASA PDS hosts terabytes of valuable data from hundreds of data sources and spans decades of research. Data is stored on flat-file systems regulated through careful meta dictionaries. PDS's data is available to the public through its website which supports data searches through drill-down navigation. While the system returns data quickly, result sets in response to identical input differ depending on the drill-down path a user follows. To correct this Issue, to allow custom searching, and to improve general accessibility, PDS sought to create a new data structure and API, and to use them to build applications that are a joy to use and showcase the value of the data to students, teachers and citizens. PDS engaged TopCoder and Harvard Business School through the NTL to pursue these objectives in a pilot effort. Scope was limited to Small Bodies Node data. NTL analyzed data, proposed a solution, and implemented it through a series of micro-contests. Contest focused on different segments of the problem; conceptualization, architectural design, implementation, testing, etc. To demonstrate the utility of the completed solution, NTL developed web-based and mobile applications that can compare targets, regardless of mission. To further explore the potential of the solution NTL hosted "Mash-up" challenges that integrated the API with other publically available assets, to produce consumer and teaching applications, including an Augmented Reality iPad tool. Two contests were also posted to middle and high school students via the NoNameSite.com platform, and as a result of these contests, PDS/SBN has initiated a Facebook program. These contests defined and implemented a data warehouse with the necessary migration tools to transform legacy data, produced a public web interface for the new search, developed a public API, and produced four mobile applications that we expect to appeal to users both within and, without the academic community.
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This paper reports the investigation findings concerning of the EEPROM single bit failures that were observed on a recent NASA space mission.
Recent events in the International Space Station (ISS) Program have resulted in the necessity to re-examine the research priorities and research plans for future years. Due to both technical and fiscal resource constraints expected on the International Space Station, it is imperative that research priorities be carefully reviewed and clearly articulated. In consultation with OSTP and the Office of Management and budget (OMB), NASA's Office of Biological and Physical Research (OBPR) assembled an ad-hoc external advisory committee, the Biological and Physical Research Maximization and Prioritization (REMAP) Task Force. This paper describes the outcome of the Task Force and how it is being used to define a roadmap for near and long-term Biological and Physical Research objectives that supports NASA's Vision and Mission. Additionally, the paper discusses further prioritizations that were necessitated by budget and ISS resource constraints in order to maximize utilization of the International Space Station. Finally, a process has been developed to integrate the requirements for this prioritized research with other agency requirements to develop an integrated ISS assembly and utilization plan that maximizes scientific output. c2003 American Institute of Aeronautics and Astronautics. Published by Elsevier Science Ltd. All rights reserved.
The worst case timing margin of a synchronous design implemented with a field-programmable gate array (FPGA) is easy to perform using available FPGA design tools. However, it may be difficult to impossible to verify that worst case timing requirements are met for complex asynchronous logic design.
Logic design errors have been observed in space flight missions and the final stages of ground test. The technologies used by designers and their design/analysis methodologies will be analyzed. This will give insight to the root causes of the failures. These technologies include discrete integrated circuit based systems, systems based on field and mask programmable logic, and the use computer aided engineering (CAE) systems. State-of-the-art (SOTA) design tools and methodologies will be analyzed with respect to high-reliability spacecraft design and potential pitfalls are discussed. Case studies of faults from large expensive programs to "smaller, faster, cheaper" missions will be used to explore the fundamental reasons for logic design problems.
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