Fusion Applications Research Articles

Simulation of temperature field and residual stress in high-power laser self-melting welding process of CLF-1 steel medium-thick plate

To mitigate the adverse effects of residual stress and deformation during high-power laser welding, this study established a finite element model based on thermodynamic conditions for high-power laser welding of CLF-1 steel for nuclear fusion applications. The temperature field and residual stress of the weld were simulated by using the composite heat source model together with Gaussian model and conical model. The results showed that the temperature field simulation was in good agreement with the real temperature field. The simulation results of the weld metal (WM) and the heat affected zone (HAZ) in the cross sections were basically consistent with those of the real cross sections. Moreover, the margin of error between the simulation results and the real data was ≤ 1.3% (the largest error ≤0.04 mm). The Von Mises equivalent stress in WM was distributed irregularly, and its largest value was ≤ 220 MPa; the equivalent stress declined with an increase in distance from the center of WM. The transverse stress distribution in the center of WM was in accordance with the vertical stress distribution, which was essentially the same as the experimental data of the vertical stress. The simulation results of deformation in the Z direction of the weld showed that the maximum deformation was about -0.2 mm at the center of the weld corresponding to the length of 300 mm. In summary, the thermal source model, combined with laser welding process parameters, can provide high-precision prediction of stress variations and deformation control during the actual welding manufacturing process of the test blanket module (TBM) structure.

Conference Report on the 7th International Symposium on Liquid metals Applications for fusion (ISLA-7)

Supported by the world magnetic fusion research community, a series of International Symposia on Liquid metals Applications for fusion (ISLA) have been held biannually since 2010. The 7th edition (ISLA-7) was held for the period from 12 December through 16 December 2022, at Chubu University located in Kasugai, Aichi, Japan. For the first time in the history of this series of symposia, ISLA-7 was held in a hybrid fashion, due to the COVID-19 situation. The total number of the participants was 60, 34 out of whom attended the symposium in person, and the rest participated online. As to the presentation statistics, 29 papers were presented in person, whereas 21 presentations were delivered online but real-time by the presenters in China, Spain, the UK, and the USA. Both of the presentations delivered in person and online were recorded, and the video has been shared by all participants. These participants represent 11 countries: China, Czech, Italy, Japan, Latvia, Netherlands, Russia, Thailand, the UK, and the USA. All these numbers are among the largest in this series of symposia. Covered by these presentations are; in session-2, program overviews and liquid metal research review; in session-3, liquid metal flows, and MHD issues; in session-4, liquid metal facilities; in sessions-5 and 6, liquid metal experiments and modeling; in session-7, divertor physics and heat flux mitigation; in session-8, plasma and liquid metals interactions; in session-9 liquid metal plasma-facing components, erosion, and wettability. In addition, there were an opening session whereby several opening addresses were delivered and also a closing session where all technical session summaries were presented by the respective session chairs.

Preliminary engineering design of vacuum thermal shielded Pb-Li loop section for potential nuclear fusion application

Nuclear fusion reactor design and engineering has reached into an advanced phase where the issues pertaining to radioactive tritium handling & accountability, divertor heat load mitigation, reactor size reduction & cost minimization are some of the core problems being addressed globally. Tritium breeding blanket is an important sub system of the reactor, which demands the most efficient design from many perspectives including that of tritium handling and accountability. Especially, Liquid Metal Breeder Blanket (LMBB) design consists of a complex network of heated pipes carrying Lead-Lithium (Pb-Li) Eutectic Alloy liquid metal. There are a few major issues with such pipes, namely (1) Large Space required due to substantial increase in diametric size of such pipes covered with heating elements and silica fibre based thermal insulation, (2) Loss of the bred tritium from liquid metal through permeation across the pipe wall and associated radioactive safety issues, and (3) Tritium retention in silica fibre based insulation resulting in tritium accountability problem and health hazard during maintenance duration. One possible solution to these problems could be putting a vacuum envelope over the loop pipe. The vacuum isolation will take care of thermal insulation for convection loss and at the same time, the pumping port of the envelope will collect all the lost tritium. In order to demonstrate the feasibility of the concept from thermal shielding point of view, we have prepared a conceptual and preliminary engineering design of such a vacuum envelope on a segment of the Pb-Li loop of 1 inch diameter. The loop segment includes a straight part as well as one 180° U bend too. The design is to maintain the envelop temperature less than 50 °C while the loop pipe is maintained at 350 °C. Basic calculation of thermal conductivity of low pressure air (vacuum) is done and compared with that of conventional insulation material silica based fibre felt. The fabrication, integration and maintenance schemes are also discussed in this report.

Sugeno Integral Based on Overlap Function and Its Application to Fuzzy Quantifiers and Multi-Attribute Decision-Making

The overlap function is an important class of aggregation function that is closely related to the continuous triangular norm. It has important applications in information fusion, image processing, information classification, intelligent decision-making, etc. The usual multi-attribute decision-making (MADM) is to select the decision object that performs well on all attributes (indicators), which is quite demanding. The MADM based on fuzzy quantifiers is to select the decision object that performs well on a certain proportion or quantification (such as most, many, more than half, etc.) of attributes. Therefore, it is necessary to study how to express and calculate fuzzy quantifiers such as most, many, etc. In this paper, the Sugeno integral based on the overlap function (called the O-Sugeno integral) is used as a new information fusion tool, and some related properties are studied. Then, the truth value of a linguistic quantified proposition can be estimated by using the O-Sugeno integral, and the O-Sugeno integral semantics of fuzzy quantifiers is proposed. Finally, the MADM method based on the O-Sugeno integral semantics of fuzzy quantifiers is proposed and the feasibility of our method is verified by several illustrative examples such as the logistics park location problem.

The response of silicon carbide composites to He ion implantation and ramifications for use as a fusion reactor structural material

Silicon carbide fibre–reinforced silicon carbide matrix (SiCf/SiC) composites are desirable in structural nuclear applications due to their low density, high temperature strength and tolerance to energetic radiation. We have subjected two industrial grades of SiCf/SiC to high energy He²⁺ ion irradiation, up to 10,000 appm implanted He at 700 °C, to determine their suitability for blanket structural applications in nuclear fusion. Minor crystallographic evolution is observed following irradiation, with evidence of phase localised stress, intragranular strain, and lattice swelling. This is attributed to vacancy production and subsequent He bubble formation, both intragranular and at grain boundaries.During post-irradiation annealing up to 1300 °C, varying degrees of He bubble evolution are observed, with the Si phase showing the highest level of instability. The fibres appear stable, with no detectable radiation-induced defects. Meanwhile, bubbles in the fibre coating and matrix grains grow and agglomerate. Despite this, no delamination or microcracking is observed.

Modelling LOFA scenario for WCLL BB concept using MELCOR1.8.5 code

In the framework of the EUROfusion activities for the DEMO project, the evaluation of the Breeding Blanket (BB) performance and its ancillary systems is a compulsory activity. The European liquid BB concept, named Water Cooled Lithium Lead (WCLL), makes use of the liquid metal alloy PbLi as a tritium breeder/neutron multiplier and water as a coolant. A dedicated ancillary system guarantees the recirculation of the PbLi between the BBs and the tritium extraction/purification system. The BBs and the ancillary system must operate safely and reliably under the designed conditions, while accidental scenarios have to be identified for risk assessment and to define safety plans.In the present work an analysis of the In-Board Loss Of Flow Accident (IB LOFA) in the PbLi ancillary loop of the WCLL BB is conducted. This numerical analysis is performed by employing the fully integrated code MELCOR1.8.5, the release for fusion application. A LOFA scenario is considered by assuming the electromagnetic pump in the IB BB loop, which provides forced circulation to the PbLi, stops working. The nodalisation and numerical models are performed by applying geometries and design parameters using the 2020 WCLL PbLi design. The analysis is performed to develop a suitable numerical model, which simulates transients by studying several factors such as: tritium mobilization and transport inside the loop, fast plasma shutdown leading to pressure and temperature transients, and maximum temperatures inside the First Wall (FW).The preliminarily results demonstrate the maximum temperature inside the FW does not exceed the defined temperature thresholds for Tungsten and EUROFER (1000 °C and 500 °C, respectively). Furthermore, the pressure transient is appropriately accommodated within the ancillary loop. The initial tritium inventory in breeding modules is relocated and accrued in the tritium extraction system's free volume. This work is the first step in the safety analyses of the PbLi ancillary system aiming to support the R&D works carried out in the framework of the DEMO project.

Gentamicin Eluting 3D-Printed Implants for Preventing Post-Surgical Infections in Bone Fractures.

A surgically implantable device is an inevitable treatment option for millions of people worldwide suffering from diseases arising from orthopedic injuries. A global paradigm shift is currently underway to tailor and personalize replacement or reconstructive joints. Additive manufacturing (AM) has provided dynamic outflow to the customized fabrication of orthopedic implants by enabling need-based design and surface modification possibilities. Surgical grade 316L Stainless Steel (316L SS) is promising with its cost, strength, composition, and corrosion resistance to fabricate 3D implants. This work investigates the possibilities of application of the laser powder bed fusion (L-PBF) technique to fabricate 3D-printed (3DP) implants, which are functionalized with a multilayered antimicrobial coating to treat potential complications arising due to postsurgical infections (PSIs). Postsurgical implant-associated infection is a primary reason for implantation failure and is complicated mainly by bacterial colonization and biofilm formation at the installation site. PLGA (poly-d,l-lactide-co-glycolide), a biodegradable polymer, was utilized to impart multiple layers of coating using the airbrush spray technique on 3DP implant surfaces loaded with gentamicin (GEN). Various PLGA-based polymers were tested to optimize the ideal lactic acid: glycolic acid ratio and molecular weight suited for our investigation. 3D-Printed PLGA-GEN substrates sustained the release of gentamicin from the surface for approximately 6 weeks. The 3DP surface modification with PLGA-GEN facilitated cell adhesion and proliferation compared to control surfaces. The cell viability studies showed that the implants were safe for application. The 3DP PLGA-GEN substrates showed good concentration-dependent antibacterial efficacy against the common PSI pathogen Staphylococcus aureus (S. aureus) and Staphylococcus epidermidis (S. epidermidis). The GEN-loaded substrates demonstrated antimicrobial longevity and showed significant biofilm growth inhibition compared to control. The substrates offered great versatility regarding the in vitro release rates, antimicrobial properties, and biocompatibility studies. These results radiate great potential in future human and veterinary clinical applications pertinent to complications arising from PSIs, focusing on personalized sustained antibiotic delivery.

A generalized closed-form solution for 3D registration of two-point sets under isotropic and anisotropic scaling

Fitting of two-point sets under non-uniform scaling involves several applications, including ultrasound-guided surgery, where ultrasound images generally show anisotropy between its lateral and depth resolution. However, the current state-of-the-art only accomplishes the closed-form solution under the assumption of isotropic scaling, and only the iterative form of the solution is available for registration regardless of scaling type. A generalized closed-form solution, including anisotropic scaling, could robust the computation in the applications of multi-modality image fusion and surgical navigation based on ultrasound images. In this paper, a generalized closed-form solution (GCFS) that accounts for isotropic scaling and anisotropic scaling is proposed. GCFS finds the least-squares solution of rotation, translation, and scaling based on the singular value decomposition (SVD). The method was demonstrated to 1) register two 3D point sets under the effect of anisotropic scaling and 2) register two coplanar 3D point sets under the effect of anisotropic scaling. This study evaluates 3D registration between the preoperative model and intraoperative ultrasonic scanning of a femur and 2D registration of ultrasound images to the phantom for ultrasound calibration. In addition, the conditions that affect the transformation estimations like estimating reflection and noise degeneracy were also considered in the evaluation.

Fasys: Visible-Light-Based Communication and Positioning Services towards Smart Cities.

Visible-light-based transmission application plays an important role in various types of sensor services for the Internet of Things (IoTs). However, in big data scenarios, current visible-light-based systems cannot achieve concurrent high-speed communication, low-speed communication, and positioning. Therefore, in this article, we propose a smart visible-light-based fusion applications system, named Fasys, to solve the above problem for the big data traffic with heterogeneity. Specifically, for low-speed data services, we propose a novel linear block coding and bit interleaving mechanism, which enhances the LED positioning accuracy and recovers the lost data bits in the interframe gap (IFG). For high-speed data services with traffic possessing burstiness, an elegant statistical reliability analysis framework in regard to latency is proposed based on martingale theory. The backlog martingale process is constructed. Leveraging stopping time theory, a tight upper bound of unreliability is obtained. An arrival abstraction and traffic allocation scheme is designed, which contributes to decouple the reliability requirement as the maximum supportable arrival load. Finally, we implement our Fasys system, and extensive experimental results show that our system can achieve consistent high-precision positioning and low-BER data communication for low-speed data services. And the proposed martingale-based traffic allocation scheme can achieve the provisioning of reliability in regard to the latency for high-speed data services.

Surgical Approaches and Short-Term Results of Circumferential Minimally Invasive Correction Surgery for Adult Idiopathic Scoliosis

We present the surgical approaches and short-term (2years postoperative) results pertaining to circumferential minimally invasive spine surgery (CMIS) with lateral lumbar interbody fusion (LLIF) and percutaneous pedicle screw application for adult idiopathic scoliosis (AS). We enrolled eight patients with AS who underwent CMIS (2018-2020) and examined the number of fused levels, upper instrumented vertebra, lower instrumented vertebra, number of LLIF-treated segments, number of preoperative intervertebral fusions, intraoperative blood loss, operative time, various spinopelvic parameters, Oswestry Disability Index, low back pain, visual analog scale (VAS), leg VAS, bone fusion rate, and perioperative complications. The upper instrumented vertebra was T4, T7, T8, and T9 in two cases, whereas lower instrumented vertebra was the pelvis in all the cases. The average numbers of fixed vertebrae and segments that underwent LLIF were 13.3 ± 2.0 and 4.6 ± 0.7, respectively. All spinopelvic parameters improved significantly after surgery (thoracic kyphosis: P < 0.05, lumbar lordosis, cobb angle, pelvic tilt, pelvic incidence-lumbar lordosis, sagittal vertical axis: P < 0.001), and good alignment was achieved. The Oswestry Disability Index and VAS scores improved significantly (P < 0.001). The bone fusion rates achieved in the lumbosacral and thoracic spine were 100% and 88%, respectively. Only 1 patient showed postoperative coronal imbalance. The 2-year postoperative results of CMIS for AS were good, and spontaneous bone fusion was confirmed in the thoracic spine without bone grafting. In this procedure, sufficient intervertebral release with LLIF and a percutaneous pedicle screw device translation technique enabled adequate global alignment correction. Therefore, correcting the global imbalance of the coronal and sagittal planes is more crucial than correcting scoliosis.

Application of Data Sensor Fusion Using Extended Kalman Filter Algorithm for Identification and Tracking of Moving Targets from LiDAR–Radar Data

In surveillance and monitoring systems, the use of mobile vehicles or unmanned aerial vehicles (UAVs), like the drone type, provides advantages in terms of access to the environment with enhanced range, maneuverability, and safety due to the ability to move omnidirectionally to explore, identify, and perform some security tasks. These activities must be performed autonomously by capturing data from the environment; usually, the data present errors and uncertainties that impact the recognition and resolution in the detection and identification of objects. The resolution in the acquisition of data can be improved by integrating data sensor fusion systems to measure the same physical phenomenon from two or more sensors by retrieving information simultaneously. This paper uses the constant turn and rate velocity (CTRV) kinematic model of a drone but includes the angular velocity not considered in previous works as a complementary alternative in Lidar and Radar data sensor fusion retrieved using UAVs and applying the extended Kalman filter (EKF) for the detection of moving targets. The performance of the EKF is evaluated by using a dataset that jointly includes position data captured from a LiDAR and a Radar sensor for an object in movement following a trajectory with sudden changes. Additive white Gaussian noise is then introduced into the data to degrade the data. Then, the root mean square error (RMSE) versus the increase in noise power is evaluated, and the results show an improvement of 0.4 for object detection over other conventional kinematic models that do not consider significant trajectory changes.

WDCIP: spatio-temporal AI-driven disease control intelligent platform for combating COVID-19 pandemic

ABSTRACT The outbreak and subsequent recurring waves of COVID −19 pose threats on the emergency management and people’s daily life, while the large-scale spatio-temporal epidemiological data have sure come in handy in epidemic surveillance. Nonetheless, some challenges remain to be addressed in terms of multi-source heterogeneous data fusion, deep mining, and comprehensive applications. The Spatio-Temporal Artificial Intelligence (STAI) technology, which focuses on integrating spatial related time-series data, artificial intelligence models, and digital tools to provide intelligent computing platforms and applications, opens up new opportunities for scientific epidemic control. To this end, we leverage STAI and long-term experience in location-based intelligent services in the work. Specifically, we devise and develop a STAI-driven digital infrastructure, namely, WAYZ Disease Control Intelligent Platform (WDCIP), which consists of a systematic framework for building pipelines from automatic spatio-temporal data collection, processing to AI-based analysis and inference implementation for providing appropriate applications serving various epidemic scenarios. According to the platform implementation logic, our work can be performed and summarized from three aspects: (1) a STAI-driven integrated system; (2) a hybrid GNN-based approach for hierarchical risk assessment (as the core algorithm of WDCIP); and (3) comprehensive applications for social epidemic containment. This work makes a pivotal contribution to facilitating the aggregation and full utilization of spatio-temporal epidemic data from multiple sources, where the real-time human mobility data generated by high-precision mobile positioning plays a vital role in sensing the spread of the epidemic. So far, WDCIP has accumulated more than 200 million users who have been served in life convenience and decision-making during the pandemic.

Process development for the hybrid additive manufacturing of metallic structures on polymer substrates

3D hybrid additive manufacturing describes the combined application of different additive manufacturing processes in order to manufacture a component with almost unlimited design freedom and free choice of materials. One challenge in the hybrid additive manufacturing lies in the different conditions of individual additive manufacturing processes. For example, in the combined application of the laser powder bed fusion (PBF-LB) of metals with the fused filament fabrication (FFF) of polymers, damage can occur in the plastic due to the higher processing temperatures of PBF-LB. Therefore, in this work a process strategy for the buildup of metallic structures in the PBF-LB process on polymer base structures was developed. By reducing the laser energy density in combination with increasing the height of the first layer, a processing window could be identified. The built hybrid components were investigated with micro-computed tomography and the effects of different processing parameters on the interface between the polymer and metal part are discussed. Finally, a strategy to increase the strength of the interface is presented.

Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade

Mental health is a basic need for a sustainable and developing society. The prevalence and financial burden of mental illness have increased globally, and especially in response to community and worldwide pandemic events. Children suffering from such mental disorders find it difficult to cope with educational, occupational, personal, and societal developments, and treatments are not accessible to all. Advancements in technology have resulted in much research examining the use of artificial intelligence to detect or identify characteristics of mental illness. Therefore, this paper presents a systematic review of nine developmental and mental disorders (Autism spectrum disorder, Attention deficit hyperactivity disorder, Schizophrenia, Anxiety, Depression, Dyslexia, Post-traumatic stress disorder, Tourette syndrome, and Obsessive–compulsive disorder) prominent in children and adolescents. Our paper focuses on the automated detection of these developmental and mental disorders using physiological signals. This paper also presents a detailed discussion on signal analysis, feature engineering, and decision-making with their advantages, future directions and challenges on the papers published on mental disorders of children. We have presented the details of the dataset description, validation techniques, features extracted and decision-making models. The challenges and future directions present open research questions on signal or availability, uncertainty, explainability, and hardware implementation resources for signal analysis and machine or deep learning models. Finally, the main findings of this study are presented in the conclusion section.

Tritium transport in the vacuum vessel pressure suppression system for helium cooled pebble bed

In the frame of the safety studies for the EU-DEMO reactor, attention is paid to the hydrogen concentration in the vacuum vessel and connected volumes since it would lead to a possible hazard of releasing tritium and activated dust. The risk of explosion cannot be excluded a priori if H2 stockpiles. For this reason, in both water (WCLL) and helium (HCPB) cooled breeding blanket concepts of EU-DEMO, the problem is under investigation with a cross-reference between the available technologies in fission (such as the Passive Autocatalytic Recombiners – PAR) and fusion application. In particular, the recent analyses pointed out the implementation of the PARs into the Vacuum Vessel Pressure Suppression System or linked systems.This paper evaluates the Hydrogen behavior (main mobilized tritium source term) for the Helium-Cooled Pebble Bed (HCPB) VVPSS concept. The analyses preliminary investigate the stratification of the hydrogen mass inventory inside the PSS. In particular, a MELCOR 1.8.6 model of the PSS, based on past activities aimed at dust transport and thermohydraulic analyses, is adopted. The paper also introduces the applicability of PAR technology in the operation range of fusion devices, analyzing the problem of the recombination rate due to the dilution of Hydrogen after a Helium blowdown.

Effect of chirp on stimulated-forward Raman scattering in a magnetised plasma with rippled density for fusion applications

Stimulated Raman scattering (SRS) is one of the mechanisms limiting power scaling in inertial confinement fusion (ICF). In this work, we demonstrate the effective suppression of SRS by the combined effects of static density fluctuations and an azimuthal magnetic field with a propagating chirped laser pulse. In the presence of an azimuthal magnetic field, chirped laser pulse propagates through a density-rippled plasma and undergoes stimulated-forward Raman scattering (SFRS), resulting in two radially localized electromagnetic sidebands waves and a lower-hybrid wave. Absolute and growing modes saturate due to ion density fluctuations, which then suppress instability growth through mode coupling. The modes modified by the combined effect of chirp and azimuthal magnetic field are effectively damped after saturation. As a result, the overall growth rate of the instability reduces. The comparison of positive and negative chirp demonstrated that when a positive chirp is being used, instability is more effectively suppressed. Based on non-local theory, we have analyzed the growth of the SFRS for positive and negative chirp and estimated it for ICF-relevant parameters and observed the effect of the growth rate.

Current status of MELCOR 2.2 for fusion safety analyses

MELCOR is an integral code developed by Sandia National Laboratories (SNL) for the US Nuclear Regulatory Commission (USNRC) to perform severe accident analyses of Light Water Reactors (LWR). More recently, MELCOR capabilities are being extended also to analyze non-LWR fission technologies. Within the European MELCOR User Group (EMUG), organized in the framework of USNRC Cooperative Severe Accident Research Program (CSARP), an activity on the evaluation of the applicability of MELCOR 2.2 for fusion safety analyses has been launched and it has been coordinated by ENEA. The aim of the activity was to identify the physical models to be possibly implemented in MELCOR 2.2 necessary for fusion safety analyses, and to check if those models are already available in MELCOR 1.8.6 for fusion version, developed by Idaho National Laboratory (INL). From this activity, a list of modeling needs emerged from the safety analyses of fusion-related installations have been identified and described. Then, the importance of the various needs, intended as the priority for model implementation in the MELCOR 2.2 code, has been evaluated according to the technical expert judgement of the authors. In the present paper, the identified modeling needs are discussed. The ultimate goal would be to propose to have a single integrated MELCOR 2.2 code release capable to cover both fission and fusion applications.

Effect of neutron irradiation on tensile properties of advanced Cu-based alloys and composites developed for fusion applications

The effect of neutron irradiation on tensile properties and fracture mode has been investigated for several advanced CuCrZr alloys in the frame of the European fusion material development program. Five material grades utilizing different strengthening principles have been exposed to neutron irradiation up to ∼2.5 dpa (displacement per atom) in the target operational temperature range of 150–450 °C. The strengthening mechanisms are based on the application of: i) tungsten particles; ii) tungsten foils (laminate structure); iii) tungsten fibers; iv) Y2O3 particles; v) vanadium addition (0.22%). Neutron irradiation was performed in the BR2 material test reactor inside the fuel channel in order to maximize the fast neutron flux. The upper irradiation temperature of 450 °C was selected to validate the ability of the pre-selected advanced grades to sustain the high temperature irradiation, since the baseline ITER specification CuCrZr is known not to retain sufficient tensile strength above 400 °C in non-irradiated conditions and shows strong irradiation induced softening above 300 °C. Neutron irradiation at 150 °C caused severe embrittlement of tungsten-copper laminates as well as a considerable reduction of the total elongation of all other grades. The irradiation at 450 °C led to the reduction of the yield strength and ultimate tensile strength (i.e. irradiation softening) in the vanadium-doped alloy similar to CuCrZr, while all other materials preserved or increased their strength (irradiation hardening). The fracture surfaces of the tested samples were analysed to investigate the modification of the deformation mechanisms in each particular case.

Water Chemistry Impact on Activated Corrosion Products: An Assessment on Tokamak Reactors

Activated Corrosion Product (ACP) formation and deposition pose a critical safety issue for nuclear fusion reactors. The working fluid transports the ACPs towards regions accessible by worker personnel, i.e., the steam generator. The code OSCAR-Fusion has been developed by the CEA (France) to evaluate the ACP generation and transport in closed water-cooled loops for fusion application. This work preliminary assesses the impact of water chemistry on the transport, precipitation, and deposition of corrosion products for the EU-DEMO divertor Plasma Facing Unit Primary Heat Transfer System. Sensitivity analyses and uncertainty quantification are needed due to the multi-physics phenomena involved in ACP formation and transport. The OSCAR-Fusion/RAVEN code coupling developed by the Sapienza University of Rome and ENEA are used. This work presents the perturbation results of different parameters chosen for a closed water-cooled loop considering a continuous scenario of 1888 days. The aim of this work is to preliminarily assess the variation of build-up of ACPs, perturbing the alkalizing agent concentration into the coolant, and the corrosion and release rates of different materials. The assessment of ACP formation deposition and transport is fundamental for source term identification, reduction of radiation exposure assessment, maintenance plan definition, design optimization, and waste management.

A New Correlation Measure for Belief Functions and Their Application in Data Fusion.

Measuring the correlation between belief functions is an important issue in Dempster-Shafer theory. From the perspective of uncertainty, analyzing the correlation may provide a more comprehensive reference for uncertain information processing. However, existing studies about correlation have not combined it with uncertainty. In order to address the problem, this paper proposes a new correlation measure based on belief entropy and relative entropy, named a belief correlation measure. This measure takes into account the influence of information uncertainty on their relevance, which can provide a more comprehensive measure for quantifying the correlation between belief functions. Meanwhile, the belief correlation measure has the mathematical properties of probabilistic consistency, non-negativity, non-degeneracy, boundedness, orthogonality, and symmetry. Furthermore, based on the belief correlation measure, an information fusion method is proposed. It introduces the objective weight and subjective weight to assess the credibility and usability of belief functions, thus providing a more comprehensive measurement for each piece of evidence. Numerical examples and application cases in multi-source data fusion demonstrate that the proposed method is effective.