یک الگوریتم محاسباتی پیشرفته برای تجزیه و تحلیل سیستم های نیروگاه توکامک

A new computational algorithm for tokamak power plant system analysis is being developed for the ARIES project. The objective of this algorithm is to explore the most influential parameters in the physical, technological and economic trade space related to the developmental transition from experimental facilities to viable commercial power plants. This endeavor is being pursued as a new approach to tokamak systems studies, which examines an expansive, multi-dimensional trade space as opposed to traditional sensitivity analyses about a baseline design point. The new ARIES systems code consists of adaptable modules which are built from a custom-made software toolbox using object-oriented programming. The physics module captures the current tokamak physics knowledge database including modeling of the most-current proposed burning plasma experiment design (FIRE). The engineering model accurately reflects the intent and design detail of the power core elements including accurate and adjustable 3D tokamak geometry and complete modeling of all the power core and ancillary systems. Existing physics and engineering models reflect both near-term as well as advanced technology solutions that have higher performance potential. To fully assess the impact of the range of physics and engineering implementations, the plant cost accounts have been revised to reflect a more functional cost structure, supported by an updated set of costing algorithms for the direct, indirect, and financial cost accounts. All of these features have been validated against the existing ARIES-AT baseline case. The present results demonstrate visualization techniques that provide an insight into trade space assessment of attractive steady-state tokamaks for commercial use.

The Advanced Reactor Innovation and Evaluation Study (ARIES) [1] is a national, multi-institutional research program, which performs progressive, integrated design studies of the long-term fusion energy devices for general consumer utilities. The goal of this activity is to identify key research and development (R&D) directions and to provide visions for the US fusion program. An important route towards this goal is through systems studies of advanced fusion power plant concepts. A traditional approach to fusion power plant systems analysis is to design the optimal power plant and explore the sensitivity of this design to local perturbations in the most critical parameters [2]. This approach was exercised through all the past ARIES design studies, including the most recent steady state tokamak reactor ARIES-AT [3]. Traditionally, the ARIES systems code was utilized [4], [5], [6] and [7] within the ARIES project as a tool for parametric search of a design point [8] that yields the lowest cost of electricity for the prescribed constraints and operational parameters. However, the search for a single optimal point is not sufficient to provide an insight into a vast multi-dimensional space of possibly attractive “near-optimal” designs and may have a difficulty justifying the selection of that particular point. Recently, the ARIES team has focused on identifying the R&D needs in transition from experimental tokamak facilities, such as ITER, to fully operational power plants (i.e., Demo and beyond). In this case, tradeoffs over wide regions of physics and engineering design parameters are sought. In order to fulfill this objective, a new systems code is being developed as a computational tool that integrates the state-of-the-art physics, engineering, and costing algorithms. The new structure of the systems code is modular and composed from a custom-made toolbox of generic, easy-to-assemble building blocks. The steady state plasma physics for advanced tokamaks is modeled by an algorithm that was already developed in order to examine the high field compact tokamak burning plasmas for the fusion ignition research experiment (FIRE) [9]. The reactor model includes the radial build, nuclear parameters, power core and energy conversion systems that are compatible to the ARIES-AT [10] but can easily be altered from this design. For example, the current tokamak model has an option of implementing different blanket concepts, such as the advanced Pb−17Li+SiCf/SiCPb−17Li+SiCf/SiC concept and the dual coolant Pb−17Li+FS+HePb−17Li+FS+He concept, in order to assess the impact of blanket design on the technological and economic attractiveness of the power plant. The former blanket option was used with the ARIES-AT with liquid Pb–17Li as breeder and coolant. The latter option, also known as dual coolant lithium lead (DCLL) blanket, was developed using helium in the first wall in order to mitigate the MHD-induced pressure drop due to the circulation of high velocity liquid metal to cool the first wall (FW) in the presence of a magnetic field. The proposed solution was to use helium as a coolant for the FW and structural box and a lower velocity self-cooled Pb–17Li as a breeder. Both blanket concepts were analytically evaluated on a compact stellarator ARIES-CS [11] and their comparison revealed some economic penalties associated with the DCLL concept [11] and [12]. Those penalties include a thicker blanket and higher pumping costs due to the introduction of helium, as well as decreased passive safety rating, resulting in higher level of safety assurance. As a consequence, the total cost of the DCLL blanket was higher [12] for the compact stellarator, but no similar comparison exists for tokamaks at present. The new tokamak model has a magnetic confinement system that resembles the one used for the ARIES-AT in geometry, while updated algorithms were used for the material composition, size and cost of two magnet options: low temperature superconducting magnet (∼∼4.2 K) and high temperature superconducting magnet (∼∼75 K). The structural support of the toroidal field (TF) magnet is estimated by scaling from the finite element analysis reported in Ref. [13]. The breakdown of all the fusion power plant costing accounts was originally suggested by Schulte et al. [14], who introduced the direct and indirect cost accounts and defined some of the algorithms that are presently used. A complete and well-documented cost assessment was given by Waganer et al. [15] in the STARFIRE conceptual power plant study. The GENEROMAK report [16] developed a basis for a parametric reactor design with modeling algorithms based largely on STARFIRE [15]. The ESECOM study [17] was the first to employ safety assurance credit factors for use with design concepts employing advanced fuels or low activation materials to reduce capital costs on specific systems and subsytems. This credit concept evolved into the Level of Safety Assurance as first employed in ARIES-II, IV final report [18]. The costing accounts and the associated algorithms have been further updated through the 1990s–2000s ARIES design concepts, such as ARIES-I, II, IV, RS, SPPS, ST, and AT. A thorough revision of this costing breakdown is currently in progress in order to reflect a more functional cost structure. The ARIES systems algorithm is outlined and compared to its predecessor code in Section 2. The plasma physics module of the code is described in Section 3. A detailed overview of the power core is given in Section 4, where special attention is paid to the radial build, magnetic confinement system and blanket options. The power flow is described in Section 5, with a detailed description of two power cycles associated with different blanket options. Filtering of tokamak power plants through different engineering criteria is outlined in Section 6. Costing algorithms are overviewed in Section 7, with a detailed account of all the components that comprise the cost of electricity. Example results that highlight the utility of the systems code are demonstrated in Section 8, followed by a discussion and guidelines for future development, given in Section .

The ARIES systems code is being developed as a general purpose tool for parametric design space analysis and optimization of advanced tokamak models. As a foundation of the systems code, the custom-made toolbox of C++ classes and generic functions was built for a wide scope of possible applications in systems analysis of power plants. The algorithms presented in this paper, however, were developed for tokamaks that are similar in configuration to the ARIES-AT but allow for a variety of different options, such as plasma shape and size, blanket options, and type and size of the magnets. The parametric space approach assumed in this analysis derives information from a large database of viable tokamak systems instead of using a single optimal solution. This became possible due to ever-increasing ubiquity of inexpensive computing power, which allows for creation and storage of millions of power plant models on a desktop-type computer within days. A similar approach in the eighties would have required a Cray supercomputer and prohibitively expensive data processing/storage arrangements. Test results presented in Section 8. benchmarked the new ARIES systems code against the ARIES-AT as a reference tokamak power plant and demonstrated several possible ways a rich database of models can be exploited. The “cloud” of operating points was visualized in 2D and 3D parametric spaces to reveal the key parameters that impact the cost of electricity and their mutual dependence. The visualization highlighted several well-understood effects, such as the proportionality of the COE to plasma major radius and toroidal field at plasma major radius, tradeoff between the plasma energy density and magnetic energy density (ββ versus BTBT), impact of the argon impurities on the plasma core radiation fraction and peak heat flux on divertor and impact of the electron density on the COE. In addition to plotting multiple parameters across the “universe” of tokamaks, several operating points with the lowest COE were presented with the most relevant physics and engineering parameters. This was done in order to “zoom” into a narrower span of parameters likely to harbor the optimal machines. For these operating points, the magnitudes of the peak heat flux on divertor were close to a limit of 8 MW/m2 which signals possible cost benefits from either shifting this constraint to higher values (by searching for more advanced divertor plate materials) or from alleviating the divertor heat flux through enhancing the radiation from the power core. This introductory study lays out a path for an in-depth analysis of the operating parametric space of advanced tokamaks. A more detailed physics and engineering assessment will be complemented by a full optimization of the tokamak model and described in a subsequent publication. This assessment will also include a comparison of the cost impact of utilizing the two blanket configurations described in Section (the Pb–17Li+SiCf/SiC and DCLL options). A complementary effort is being accomplished to document and update the ARIES cost data base and costing algorithms to be compatible with past study results and reflect the current cost databases and costing trends. There is a rich heritage of economic studies relating to conceptual fusion power plants, upon which the ARIES code is based, as evidenced in this paper. However, the assumptions upon which these estimates are based are now dated and may be obsolete and inconsistent. This costing update effort is meant to document the past efforts and offer new costing models consistent with the evolutionary physics and technology changes evidenced in the new fusion design concepts. These new costing models will be included in the new ARIES systems code to enable more consistent and viable performance and economic comparisons and trade studies.