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KM is the process through which organizations generate value from their intellectual and knowledge-based assets 1. Implementation of Knowledge Management (KM) is an important issue for all types of nuclear organizations and in particular for Radioactive Waste Management (RWM) organizations. Thus, the fundamental objective of RWM is to manage the radioactive waste without adverse impact for human health and the environment during its radioactive waste lifetime. Considering the life cycle of the radioactive waste it is obvious that KM accompanies Safety Management (SM). The management of radioactive waste affects future generations and covers pretreatment, treatment, conditioning, storage and disposal. At all mentioned stages operators are dealing with information such as take the records, use the standards & templates, prepare the reports. Without adequate knowledge it would be impossible to carry out this work and conclusively safety will be under risk. It is clear, that managing the knowledge must be implemented at all stages of RWM with the integration of knowledge processes concentrating on the following four core activities: • To generate the knowledge • To store the knowledge • To share the knowledge • To distribute the knowledge and will be focused on • Information and Document Management • Human Resource Management • Knowledge Organizational Structure However, depending on the organization (Regulatory, Operations, R&D organizations) involved in RWM the used KM methods & tools will be different. Nuclear R&D organizations can be categorized into seven types oriented on types of functions undertaken by the respective organization. In 2012 IAEA2 has classified them as follows: (1.) Basic research functions, (2.) Applied research functions, (3.) Design R&D functions, (4.) Functions utilizing nuclear R&D facilities, (5.) Functions utilizing non-nuclear R&D facilities, (6.) Educational R&D functions and (7.) Technical support & service functions. Referring to R&D fu

KM is the process through which organizations generate value from their intellectual and knowledge-based assets 1. Implementation of Knowledge Management (KM) is an important issue for all types of nuclear organizations and in particular for Radioactive Waste Management (RWM) organizations. Thus, the fundamental objective of RWM is to manage the radioactive waste without adverse impact for human health and the environment during its radioactive waste lifetime. Considering the life cycle of the radioactive waste it is obvious that KM accompanies Safety Management (SM). The management of radioactive waste affects future generations and covers pretreatment, treatment, conditioning, storage and disposal. At all mentioned stages operators are dealing with information such as take the records, use the standards & templates, prepare the reports. Without adequate knowledge it would be impossible to carry out this work and conclusively safety will be under risk. It is clear, that managing the knowledge must be implemented at all stages of RWM with the integration of knowledge processes concentrating on the following four core activities: • To generate the knowledge • To store the knowledge • To share the knowledge • To distribute the knowledge and will be focused on • Information and Document Management • Human Resource Management • Knowledge Organizational Structure However, depending on the organization (Regulatory, Operations, R&D organizations) involved in RWM the used KM methods & tools will be different. Nuclear R&D organizations can be categorized into seven types oriented on types of functions undertaken by the respective organization. In 2012 IAEA2 has classified them as follows: (1.) Basic research functions, (2.) Applied research functions, (3.) Design R&D functions, (4.) Functions utilizing nuclear R&D facilities, (5.) Functions utilizing non-nuclear R&D facilities, (6.) Educational R&D functions and (7.) Technical support & service functions. Referring to R&D fu

KM is the process through which organizations generate value from their intellectual and knowledge-based assets 1. Implementation of Knowledge Management (KM) is an important issue for all types of nuclear organizations and in particular for Radioactive Waste Management (RWM) organizations. Thus, the fundamental objective of RWM is to manage the radioactive waste without adverse impact for human health and the environment during its radioactive waste lifetime. Considering the life cycle of the radioactive waste it is obvious that KM accompanies Safety Management (SM). The management of radioactive waste affects future generations and covers pretreatment, treatment, conditioning, storage and disposal. At all mentioned stages operators are dealing with information such as take the records, use the standards & templates, prepare the reports. Without adequate knowledge it would be impossible to carry out this work and conclusively safety will be under risk. It is clear, that managing the knowledge must be implemented at all stages of RWM with the integration of knowledge processes concentrating on the following four core activities: • To generate the knowledge • To store the knowledge • To share the knowledge • To distribute the knowledge and will be focused on • Information and Document Management • Human Resource Management • Knowledge Organizational Structure However, depending on the organization (Regulatory, Operations, R&D organizations) involved in RWM the used KM methods & tools will be different. Nuclear R&D organizations can be categorized into seven types oriented on types of functions undertaken by the respective organization. In 2012 IAEA2 has classified them as follows: (1.) Basic research functions, (2.) Applied research functions, (3.) Design R&D functions, (4.) Functions utilizing nuclear R&D facilities, (5.) Functions utilizing non-nuclear R&D facilities, (6.) Educational R&D functions and (7.) Technical support & service functions. Referring to R&D fu

KM is the process through which organizations generate value from their intellectual and knowledge-based assets 1. Implementation of Knowledge Management (KM) is an important issue for all types of nuclear organizations and in particular for Radioactive Waste Management (RWM) organizations. Thus, the fundamental objective of RWM is to manage the radioactive waste without adverse impact for human health and the environment during its radioactive waste lifetime. Considering the life cycle of the radioactive waste it is obvious that KM accompanies Safety Management (SM). The management of radioactive waste affects future generations and covers pretreatment, treatment, conditioning, storage and disposal. At all mentioned stages operators are dealing with information such as take the records, use the standards & templates, prepare the reports. Without adequate knowledge it would be impossible to carry out this work and conclusively safety will be under risk. It is clear, that managing the knowledge must be implemented at all stages of RWM with the integration of knowledge processes concentrating on the following four core activities: • To generate the knowledge • To store the knowledge • To share the knowledge • To distribute the knowledge and will be focused on • Information and Document Management • Human Resource Management • Knowledge Organizational Structure However, depending on the organization (Regulatory, Operations, R&D organizations) involved in RWM the used KM methods & tools will be different. Nuclear R&D organizations can be categorized into seven types oriented on types of functions undertaken by the respective organization. In 2012 IAEA2 has classified them as follows: (1.) Basic research functions, (2.) Applied research functions, (3.) Design R&D functions, (4.) Functions utilizing nuclear R&D facilities, (5.) Functions utilizing non-nuclear R&D facilities, (6.) Educational R&D functions and (7.) Technical support & service functions. Referring to R&D fu

Control of MHD instabilities using a conducting wall together with external magnetic fields is an important route to improved performance and reliability in fusion devices. Active control of MHD modes is of interest for both the Advanced Tokamak and the Reversed Field Pinch (RFP) configurations. A wide range of unstable, current driven MHD modes is present in the RFP. An ideally conducting wall facing the plasma can in principle provide stabilization to these modes. However, a real, resistive wall characterized by a wall field diffusion time, cannot stabilize the ideal MHD modes unless they rotate with Alfvénic velocity, which is usually not the case. With a resistive wall, the ideal modes are converted into resistive wall modes (RWM) with growth rates comparable to the inverse wall time. Resistive wall modes have been studied in the EXTRAP T2R thin shell RFP device. Growth rates have been measured and found in agreement with linear MHD stability calculations. An advanced system for active control has been developed and installed on the EXTRAP T2R device. The system includes an array of 128 active saddle coils, fully covering the torus surface. Experiments on EXTRAP T2R have for the first time demonstrated simultaneous active suppression of multiple independent RWMs. In experiments with a partial array, coupling of different modes due to the limited number of feedback coils has been observed, in agreement with theory. Different feedback strategies, such as the intelligent shell, the rotating shell, and mode control have been studied. Further, feedback operation with different types of magnetic field sensors, measuring either the radial or the toroidal field components have been compared, QC 20100929

Control of MHD instabilities using a conducting wall together with external magnetic fields is an important route to improved performance and reliability in fusion devices. Active control of MHD modes is of interest for both the Advanced Tokamak and the Reversed Field Pinch (RFP) configurations. A wide range of unstable, current driven MHD modes is present in the RFP. An ideally conducting wall facing the plasma can in principle provide stabilization to these modes. However, a real, resistive wall characterized by a wall field diffusion time, cannot stabilize the ideal MHD modes unless they rotate with Alfvénic velocity, which is usually not the case. With a resistive wall, the ideal modes are converted into resistive wall modes (RWM) with growth rates comparable to the inverse wall time. Resistive wall modes have been studied in the EXTRAP T2R thin shell RFP device. Growth rates have been measured and found in agreement with linear MHD stability calculations. An advanced system for active control has been developed and installed on the EXTRAP T2R device. The system includes an array of 128 active saddle coils, fully covering the torus surface. Experiments on EXTRAP T2R have for the first time demonstrated simultaneous active suppression of multiple independent RWMs. In experiments with a partial array, coupling of different modes due to the limited number of feedback coils has been observed, in agreement with theory. Different feedback strategies, such as the intelligent shell, the rotating shell, and mode control have been studied. Further, feedback operation with different types of magnetic field sensors, measuring either the radial or the toroidal field components have been compared, QC 20100929

Control of MHD instabilities using a conducting wall together with external magnetic fields is an important route to improved performance and reliability in fusion devices. Active control of MHD modes is of interest for both the Advanced Tokamak and the Reversed Field Pinch (RFP) configurations. A wide range of unstable, current driven MHD modes is present in the RFP. An ideally conducting wall facing the plasma can in principle provide stabilization to these modes. However, a real, resistive wall characterized by a wall field diffusion time, cannot stabilize the ideal MHD modes unless they rotate with Alfvénic velocity, which is usually not the case. With a resistive wall, the ideal modes are converted into resistive wall modes (RWM) with growth rates comparable to the inverse wall time. Resistive wall modes have been studied in the EXTRAP T2R thin shell RFP device. Growth rates have been measured and found in agreement with linear MHD stability calculations. An advanced system for active control has been developed and installed on the EXTRAP T2R device. The system includes an array of 128 active saddle coils, fully covering the torus surface. Experiments on EXTRAP T2R have for the first time demonstrated simultaneous active suppression of multiple independent RWMs. In experiments with a partial array, coupling of different modes due to the limited number of feedback coils has been observed, in agreement with theory. Different feedback strategies, such as the intelligent shell, the rotating shell, and mode control have been studied. Further, feedback operation with different types of magnetic field sensors, measuring either the radial or the toroidal field components have been compared, QC 20100929

Control of MHD instabilities using a conducting wall together with external magnetic fields is an important route to improved performance and reliability in fusion devices. Active control of MHD modes is of interest for both the Advanced Tokamak and the Reversed Field Pinch (RFP) configurations. A wide range of unstable, current driven MHD modes is present in the RFP. An ideally conducting wall facing the plasma can in principle provide stabilization to these modes. However, a real, resistive wall characterized by a wall field diffusion time, cannot stabilize the ideal MHD modes unless they rotate with Alfvénic velocity, which is usually not the case. With a resistive wall, the ideal modes are converted into resistive wall modes (RWM) with growth rates comparable to the inverse wall time. Resistive wall modes have been studied in the EXTRAP T2R thin shell RFP device. Growth rates have been measured and found in agreement with linear MHD stability calculations. An advanced system for active control has been developed and installed on the EXTRAP T2R device. The system includes an array of 128 active saddle coils, fully covering the torus surface. Experiments on EXTRAP T2R have for the first time demonstrated simultaneous active suppression of multiple independent RWMs. In experiments with a partial array, coupling of different modes due to the limited number of feedback coils has been observed, in agreement with theory. Different feedback strategies, such as the intelligent shell, the rotating shell, and mode control have been studied. Further, feedback operation with different types of magnetic field sensors, measuring either the radial or the toroidal field components have been compared, QC 20100929