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MARVEL plans to be the first new operational reactor at INL in many years. These documents are being made publicly available to disseminate key information on the MARVEL reactor for private sector use towards reactor development.
MARVEL plans to be the first new operational reactor at INL in many years. These documents are being made publicly available to disseminate key information on the MARVEL reactor for private sector use towards reactor development.
The BR2 nuclear reactor is a material testing reactor (MTR) located in Mol, Belgium, and operated by the Belgian Nuclear Research Centre (SCK CEN) since 1963. The reactor is highly versatile as the number and location of fuel elements and control rods can change significantly from cycle to cycle to accommodate different needs. Argonne National Laboratory (ANL or Argonne) Reactor Conversion (RC) team has collaborated with SCK CEN for over a decade on the conversion of domestic and international research reactors from highly enriched uranium (HEU, ≥20 wt.% of 235 U) to low enriched uranium (LEU, <20 wt.% of 235 U) fuel. The U.S. High-Performance Research Reactor (USHPRR) project within the M3 Reactor Conversion Program aims at converting five U.S. high performance research reactors (MITR, MURR, NBSR, HFIR, and ATR) and one critical facility (ATR-C) to LEU fuel. These USHPRRs still use and regularly refuel with HEU fuel. Each facility has a unique reactor design, operating conditions, and fuel element design to accomplish its mission. The goal of the USHPRR project is to convert the USHPRRs and the critical facility to LEU fuel while maintaining experimental performance and ensuring safe facility operation. The current technical report focuses on two reactors requiring very high-density LEU fuel: the Massachusetts Institute of Technology Reactor (MITR) and the National Bureau of Standards Reactor (NBSR). To support the conversion of these reactors, so-called design demonstration elements (DDE) are planned to be irradiated in the BR2 reactor under conditions similar to the targeted reactors and using a prototypic geometry. In support of this experiment, SCK CEN studied and modeled the DDE irradiations using MCNP6.2 to investigate the feasibility of irradiating the MITR DDE and NBSR DDE in BR2. Argonne reviewed and confirmed the conclusions of this study. Structural analysis is another step toward converting USHPRR to LEU fuel. The objective of the current report is to provide information useful to the structural analysis of the NBSR & MITR DDEs to support its irradiation in BR2. Specifically, the goal is to provide the fast neutron (E>0.1MeV) fluence in the cladding of the fuel plates in BR2 for the whole period of irradiation (8 cycles for MITR DDE and 10 cycles for NBSR DDE). Additionally, fast neutron fluences in the side plates and in the NBSR DDE’s outside plates were calculated and reported. Neutronic calculations were performed using MCNP6.2 on the RTRHPC cluster.
This report documents the activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective and secure DI&C technologies for digital upgrades/designs. A framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the risk impact of plant modernization, considering the introduction of high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the framework provides a means to address relevant technical issues by: (1) defining a risk-informed analysis process for DI&C upgrade, that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk-informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies on nuclear power plant (NPPs).
The technology readiness level scale is revised with clear definitions for magnetohydrodynamic stability control technologies for magnetic confinement fusion. The definitions are in the form of a sentence with three dimensions, which are the system complexity, the test environment, and the cost. A clear and simple definition is sought after to make an assessment based on the evidence which is agreeable to the fusion energy development community. A sample technology readiness assessment (TRA) for the electron cyclotron current drive-based control of neoclassical tearing mode for ST Advanced Reactor, using the proposed scale, reveals that the risk of a TRA being misinterpreted is high, which can only be avoided with an understanding of the procedure described in this paper.
For the development of multi-terminal high voltage DC (MTDC) transmission, it is critical to design the protection system that can selectively isolate the faulty area from the healthy part of the dc grid using DC circuit breakers (DCCBs) while ensuring continuous operation of converter stations in the healthy part. However, because of the lack of fault current blocking capability in half-bridge (HB) modular multilevel converters (MMCs), when a dc fault occurs, the rising fault currents can quickly reach the blocking threshold within a few milliseconds and disrupt the operation of MMCs in the healthy part. Large DC reactors are often considered in series with DCCBs to reduce the rate of rise of fault currents and prevent blocking of MMCs in the healthy part of the grid. However, large DC reactors can prohibitively increase the cost of the system, particularly when they are considered in an offshore environment, for instance in offshore wind projects. Large dc reactors can also introduce stability issues and create post-fault oscillations. This paper presents an adaptive fault current limiting control method for MMCs to avoid their blocking and enable continuous operation of MTDC systems. It contains two parts: The first part is based on circulating current feedforward control that emulates virtual reactors in each arm of an MMC, which is immediately activated when the fault current starts to increase, to reduce the rate of rise of the fault current; the second part is triggered when the fault current exceeds a preset threshold by temporarily bypassing the SMs, serving as a complement to the fault current limiting effect of the first part. Both parts do not require fault detection signal and they are activated automatically during faults. Simulation case studies of a four-terminal bipolar MMC-HVDC system are presented to demonstrate the effectiveness of the proposed control methods.
Non-nuclear testing can be a valuable tool in development of a space nuclear power or propulsion system. In a non-nuclear test bed, electric heaters are used to simulate the heat from nuclear fuel. Standard testing allows one to fully assess thermal, heat transfer, and stress related attributes of a given system, but fails to demonstrate the dynamic response that would be present in an integrated, fueled reactor system. The integration of thermal hydraulic hardware tests with simulated neutronic response provides a bridge between electrically heated testing and full nuclear testing. By implementing a neutronic response model to simulate the dynamic response that would be expected in a fueled reactor system, one can better understand system integration issues, characterize integrated system response times and response characteristics, and assess potential design improvements at a relatively small fiscal investment. Initial system dynamic response testing was demonstrated on the integrated SAFE-100a heat pipe cooled, electrically heated reactor and heat exchanger hardware, utilizing a one-group solution to the point kinetics equations to simulate the expected neutronic response of the system (Bragg-Sitton, 2005). The current paper applies the same testing methodology to a direct drive gas cooled reactor system, demonstrating the applicability of the testing methodology to any reactor type and demonstrating the variation in system response characteristics in different reactor concepts. In each testing application, core power transients were controlled by a point kinetics model with reactivity feedback based on core average temperature; the neutron generation time and the temperature feedback coefficient are provided as model inputs. Although both system designs utilize a fast spectrum reactor, the method of cooling the reactor differs significantly, leading to a variable system response that can be demonstrated and assessed in a non-nuclear test facility.
To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.
To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.
This report documents the activities performed by Idaho National Laboratory (INL) during fiscal year (FY) 2021 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) Risk Assessment project. In FY-2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades/designs. An integrated risk assessment technology for the DI&C systems (IRADIC technology) was proposed for this strategy, which aims to (1) provide a best-estimate risk-informed capability to quantitatively and accurately estimate the safety margin obtained from plant modernization, especially for the High Safety Significant Safety-related (HSSSR) DI&C systems, (2) develop an advanced risk assessment technology to support transition from analog to DI&C technologies for nuclear industry, (3) assure the long-term safety and reliability of vital HSSSR DI&C systems, (4) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals and deal with the expensive licensing justifications from regulatory insights, the IRADIC technology is instructive for nuclear vendors and utilities to effectively lower the costs associated with digital compliance and speed industry advances by: (1) defining an integrated risk-informed analysis process for DI&C upgrade, including hazard analysis, reliability analysis, and consequence analysis, (2) applying systematic and risk-informed tools to address common cause failures (CCFs) and quantify responding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the individual level, system level, and plant level, (4) providing insights and suggestions on designs to manage the risks; thus, to support the development, licensing, and deployment of advanced DI&C technologies on nuclear power plant (NPPs). In this report, an approach for performing software CCF analysis, given limited data, is developed and demonstrated using a case study of a highly redundant digital reactor trip system. Consequence analysis is also performed based on different accident scenarios. Results indicate that plant modernization including the improvement of HSSSR DI&C systems will make great benefits to plant safety by providing more safety margins to accident management. In addition, a novel approach is proposed in this report for the quantification of software hazards when sufficient operational and testing data available. The method incorporates software development quality as well as strong analysis techniques to identify and link software defects to potential failure modes. The approach includes both semantic and test-based analysis to detect failures that can exist in different stages of the software development life cycle. This method is applied to an advanced human system interface relevant to reactor trip safety developed from the APR 1400 design.
The Carbothermal Reduction Demonstration (CaRD) project was an effort to develop a prototype system to demonstrate the extraction of oxygen from simulated lunar regolith using concentrated solar energy and a carbothermal reaction. The prototype consisted of a deployable solar concentrator capable of tracking the sun, carbothermal reactor, fluid system, gas analysis, and a solar concentrator control system consisting of avionics and software. These subsystems were developed by multiple NASA centers and a private industry partner, Sierra Space. The various teams worked together to define requirements and interfaces to successfully assemble the complex system and demonstrate an integrated solar carbothermal process. The solar concentrator developed at Glenn Research Center (GRC) was designed to be stowed for a launch environment then deployed on the lunar surface. It utilized a crossed dragone configuration of composite mirrors to direct horizontal sunlight onto a target 90° from the incoming sunlight. The key performance parameters for the solar concentrator were efficiency and power density. The carbothermal reactor was developed by Sierra Space through a separate project called the Carbothermal Oxygen Production Reactor (COPR) where it successfully demonstrated a fully automated process in a thermal vacuum environment. The fluid system needed for the carbothermal reaction was also developed by Sierra Space and successfully demonstrated in the same thermal vacuum test. The gas analysis system was developed at Kennedy Space Center (KSC) and was required to determine the amount of oxygen extracted during each test. The gas analysis system was based on the Mass Spectrometer Observing Lunar Operations (MSOLO) instrument. Avionics and software for the CaRD prototype were also developed at KSC and based on experience with MSOLO avionics and software. The control system was designed to stow, deploy, track the sun, and perform beam alignment of the concentrated light. The prototype subsystems were integrated and tested at Johnson Space Center’s (JSC) Energy Systems Test Area. A heliostat was used to direct sunlight toward the prototype in a way that is representative of the sunlight conditions at the south pole of the Moon. When concentrated sunlight was focused on simulated lunar regolith within the reactor, the gas analysis team confirmed the presence of carbon monoxide gas, which confirmed that a solar carbothermal reaction took place. The key performance parameter for the integrated prototype was grams of oxygen extracted per kilowatt hour of energy arriving at the concentrator primary mirror. The prototype design successfully demonstrated end-to-end capability and further steps to achieve a flight capable system have been defined. With lunar data, engineers would be able to design a scaled-up system capable of extracting oxygen from regolith at useful quantities for crew life support and rocket propellant. On the long term, this method of In-Situ Resource Utilization could be used to drastically reduce the cost and risk of a sustained human presence on the Moon by reducing the amount of oxygen that would have to be delivered.
The Carbothermal Reduction Demonstration (CaRD) project was an effort to develop a prototype system to demonstrate the extraction of oxygen from simulated lunar regolith using concentrated solar energy and a carbothermal reaction. The prototype consisted of a deployable solar concentrator capable of tracking the sun, carbothermal reactor, fluid system, gas analysis, and a solar concentrator control system consisting of avionics and software. These subsystems were developed by multiple NASA centers and a private industry partner, Sierra Space. The various teams worked together to define requirements and interfaces to successfully assemble the complex system and demonstrate an integrated solar carbothermal process. The solar concentrator developed at Glenn Research Center (GRC) was designed to be stowed for a launch environment then deployed on the lunar surface. It utilized a crossed dragone configuration of composite mirrors to direct horizontal sunlight onto a target 90° from the incoming sunlight. The key performance parameters for the solar concentrator were efficiency and power density. The carbothermal reactor was developed by Sierra Space through a separate project called the Carbothermal Oxygen Production Reactor (COPR) where it successfully demonstrated a fully automated process in a thermal vacuum environment. The fluid system needed for the carbothermal reaction was also developed by Sierra Space and successfully demonstrated in the same thermal vacuum test. The gas analysis system was developed at Kennedy Space Center (KSC) and was required to determine the amount of oxygen extracted during each test. The gas analysis system was based on the Mass Spectrometer Observing Lunar Operations (MSOLO) instrument. Avionics and software for the CaRD prototype were also developed at KSC and based on experience with MSOLO avionics and software. The control system was designed to stow, deploy, track the sun, and perform beam alignment of the concentrated light. The prototype subsystems were integrated and tested at Johnson Space Center’s (JSC) Energy Systems Test Area. A heliostat was used to direct sunlight toward the prototype in a way that is representative of the sunlight conditions at the south pole of the Moon. When concentrated sunlight was focused on simulated lunar regolith within the reactor, the gas analysis team confirmed the presence of carbon monoxide gas, which confirmed that a solar carbothermal reaction took place. The key performance parameter for the integrated prototype was grams of oxygen extracted per kilowatt hour of energy arriving at the concentrator primary mirror. The prototype design successfully demonstrated end-to-end capability and further steps to achieve a flight capable system have been defined. With lunar data, engineers would be able to design a scaled-up system capable of extracting oxygen from regolith at useful quantities for crew life support and rocket propellant. On the long term, this method of In-Situ Resource Utilization could be used to drastically reduce the cost and risk of a sustained human presence on the Moon by reducing the amount of oxygen that would have to be delivered.
The Carbothermal Reduction Demonstration (CaRD) project was an effort to develop a prototype system to demonstrate the extraction of oxygen from simulated lunar regolith using concentrated solar energy and a carbothermal reaction. The prototype consisted of a deployable solar concentrator capable of tracking the sun, carbothermal reactor, fluid system, gas analysis, and a solar concentrator control system consisting of avionics and software. These subsystems were developed by multiple NASA centers and a private industry partner, Sierra Space. The various teams worked together to define requirements and interfaces to successfully assemble the complex system and demonstrate an integrated solar carbothermal process. The solar concentrator developed at Glenn Research Center (GRC) was designed to be stowed for a launch environment then deployed on the lunar surface. It utilized a crossed dragone configuration of composite mirrors to direct horizontal sunlight onto a target 90° from the incoming sunlight. The key performance parameters for the solar concentrator were efficiency and power density. The carbothermal reactor was developed by Sierra Space through a separate project called the Carbothermal Oxygen Production Reactor (COPR) where it successfully demonstrated a fully automated process in a thermal vacuum environment [1]. The fluid system needed for the carbothermal reaction was also developed by Sierra Space and successfully demonstrated in the same thermal vacuum test. The gas analysis system was developed at Kennedy Space Center (KSC) and was required to determine the amount of oxygen extracted during each test. The gas analysis system was based on the Mass Spectrometer Observing Lunar Operations (MSOLO) instrument. Avionics and software for the CaRD prototype were also developed at KSC and based on experience with MSOLO avionics and software. The control system was designed to stow, deploy, track the sun, and perform beam alignment of the concentrated light. The prototype subsystems were integrated and tested at Johnson Space Center’s (JSC) Energy Systems Test Area. A heliostat was used to direct sunlight toward the prototype in a way that is representative of the sunlight conditions at the south pole of the Moon. When concentrated sunlight was focused on simulated lunar regolith within the reactor, the gas analysis team confirmed the presence of carbon monoxide gas, which confirmed that a solar carbothermal reaction took place. The key performance parameter for the integrated prototype was grams of oxygen extracted per kilowatt hour of energy arriving at the concentrator primary mirror. The prototype design successfully demonstrated end-to-end capability and further steps to achieve a flight capable system have been defined. With lunar data, engineers would be able to design a scaled-up system capable of extracting oxygen from regolith at useful quantities for crew life support and rocket propellant. On the long term, this method of In-Situ Resource Utilization could be used to drastically reduce the cost and risk of a sustained human presence on the Moon by reducing the amount of oxygen that would have to be delivered.
A model-guided core–shell catalyst design is presented for methanol synthesis, featuring a phase change material (PCM) core encapsulated by a Cu–Zn–Al 2 O 3 (CZA) catalytic shell. The PCM enables in situ thermal management by absorbing reaction heat at its melting point, mitigates the kinetic decline at high temperatures and therefore avoids low conversion, prevents hot spots, and stabilizes the reaction temperature. A two-dimensional axisymmetric, non-isothermal packed-bed reactor model (COMSOL 6.3) was developed for a 10 g system. Simulations evaluate three PCM candidates, that is, LiNO 3 , 9 wt% LiCl + 91 wt% LiNO 3 , and commercial H250, with melting points near 244–250°C. Results indicate that CO conversion can increase from 34.4% to 52.4%, and methanol production can improve by 69% compared to a conventional packed-bed reactor. Beyond methanol synthesis, the PCM-integrated core–shell concept provides a scalable approach for thermal control in exothermic reactions, improving reactor efficiency and safety.
Molten salt reactors (MSRs) are innovative advanced nuclear reactors that utilize nuclear fuel by dissolving it in a high-temperature liquid salt. This unique feature differentiates MSRs from other types of reactors and allows for enhanced safety and economic performance. The liquid fuel also entails several multiphysics effects that can complicate reactor design and operation. One primary effect termed here as depletion-driven thermochemistry is a driving force in altering the multiphysics behavior of the reactor. Essentially, depletion-driven thermochemistry is the effect that fuel depletion has on changing the chemical redox potential of the fuel salt over time. As the fuel is consumed, the redox potential shifts toward a more oxidizing state. Without active control, the changing chemistry due to depletion increases corrosion thereby limiting reactor component lifetimes. Additionally, the changing redox potential of the fuel salt alters the vapor pressures of chemical species dissolved in the fuel salt. Changing vapor pressures of species in the fuel salt is an important parameter to understand when off-gassing volatile species during normal reactor operation, and for source term characterization during accident scenario transients. The present work represents a fundamental step toward modeling and coupling the driving physics (i.e., neutronics and chemistry) involved in altering the redox potential in an MSR. Here, the neutronic code Griffin models the depletion of the fuel-salt system, while the chemical equilibrium code Thermochimica calculates the thermochemical state of the isotopic inventory, using the Molten Salt Thermodynamic Database - Thermochemical (MSTDB-TC). These two codes are tightly coupled to predict the impact of fuel depletion in altering the chemistry in MSR systems. Redox potential control methods are discussed and can be modeled using this multiphysics approach. The vapor pressures of chemical species that could be extracted to an off-gas system, as determined by the reactor’s thermochemical state, are examined. The neutronics-chemistry coupling developed in this work is expected to have potential application for analyzing corrosion, source term evolution, and material safeguards in MSR systems. Lastly, suggestions for areas of further improvements of the models to expand these capabilities by incorporating other coupled physics effects is provided.
The production of Ca(OH) 2 via thermal decomposition of limestone is an energy intensive process resulting in significant CO 2 emissions. However, if produced in a manner that obviates the need for the thermal decomposition of limestone, Ca(OH) 2 could be a “CO 2 -negative” material. Herein, we design and demonstrate the operation of a continuous, low-temperature (< 100 °C), aqueous-phase pilot-process to produce Ca(OH) 2 using calcium extracted from alkaline industrial wastes. The three-step process encompasses unit operations including: (i) calcium leaching from basic oxygen furnace BOF slag, (ii) leachate concentration by reverse osmosis (RO), and (iii) Ca(OH) 2 precipitation by temperature swing. Here this process presents several advantages compared to the traditional route. First, it advances the recycling of waste from the steel industry. Second, it operates significantly below the temperature used in conventional lime production (900 °C) as it bypasses limestone calcination, responsible for ~65% of the CO 2 emissions from the current process. Thus, the new process has a lower CO 2 footprint and enables the use of industrial waste heat. The mass and energy balances were quantified to reveal that increasing the calcium concentration of the feed solution and the precipitation temperature, decrease the energy demands of the RO step, thereby reducing the process’s overall CO 2 footprint. The pilot system operated continuously and achieved a production rate of nearly 1 kg per day of Ca(OH) 2 with a purity greater than 95 wt%. The average particle size of the precipitates depended on the residence time in the precipitation reactor, demonstrating an ability to produce size-controlled particulates. Importantly, the process achieved full water recirculation/reutilization level indicative of a low-consumable water demand. The outcomes offer new insights and understanding relevant to developing and upscaling low-CO 2 processes for cement, lime, and portlandite.
We report the 24th workshop on magnetohydrodynamic (MHD) stability control was held on the Columbia University campus 28–30th October, 2019. The purpose of this annual workshop is to discuss cutting edge results and form future plans for active control of MHD instabilities in magnetic confinement fusion reactor concepts. The program was organized by an international committee of representatives from Auburn University (USA), Columbia University (USA), Massachusetts Institute of Technology (USA), Princeton Plasma Physics Laboratory (USA), Princeton University (USA), Tottori University (Japan), Kyoto Institute of Technology (Japan), National Institute of Radiological Sciences (Japan), National Institute for Fusion Science (Japan), Institutes of Physical Science—Chinese Academy of Sciences (People's Republic of China), and Consiglio Nazionale delle Ricerche (Italian Republic). Dr Gerald Navratil and Columbia University, in particular, were responsible for organizing and hosting the meeting on their beautiful Morningside Heights campus.
We discuss how the combination of experimental observations and rapid modeling has enabled to improve understanding of the tokamak ramp-down phase in ASDEX Upgrade. A series of dedicated experiments has been performed, to disentangle the effect of individual actuators like plasma current, auxiliary heating and plasma shaping. Optimized discharge termination strategies with increased margin with respect to radiative and vertical stability limits are proposed and tested in experiment. Radiative collapse of the edge $T$ $e$ profile after the HL back-transition is avoided by initially maintaining auxiliary heating during L-mode, showing beneficial effects even after the auxiliary heating is turned off. The capability of the RAPTOR code to model the time evolution of the internal inductance $\ell$ $i3$ has been validated, including the effect of a change in the $I$ $p$ ramp-down rate and the HL transition timing. The reduction of $\ell$ $i3$ caused by rapid compression of the plasma cross-section has been quantitatively recovered in simulations. Successful modeling of the $\ell$ $i3$ time evolution is essential to optimize ramp-down scenarios for future fusion reactors, for which vertical stability and power balance control will be more challenging.