Design of a high power production target for the Beam Dump Facility at CERN

The Beam Dump Facility (BDF) project is a proposed general-purpose facility at CERN, dedicated to beam dump and fixed target experiments. In its initial phase, the facility is foreseen to be exploited by the Search for Hidden Particles (SHiP) experiment. Physics requirements call for a pulsed 400 GeV/c proton beam as well as the highest possible number of protons on target (POT) each year of operation, in order to search for feebly interacting particles. The target/dump assembly lies at the heart of the facility, with the aim of safely absorbing the full high intensity Super Proton Synchrotron (SPS) beam, while maximizing the production of charmed and beauty mesons. High-Z materials are required for the target/dump, in order to have the shortest possible absorber and reduce muon background for the downstream experiment. The high average power deposited on target (305 kW) creates a challenge for heat removal. During the BDF facility Comprehensive Design Study (CDS), launched by CERN in 2016, extensive studies have been carried out in order to define and assess the target assembly design. These studies are described in the present contribution, which details the proposed design of the BDF production target, as well as the material selection process and the optimization of the target configuration and beam dilution. One of the specific challenges and novelty of this work is the need to consider new target materials, such as a molybdenum alloy (TZM) as core absorbing material and Ta2.5W as cladding. Thermo-structural and fluid dynamics calculations have been performed to evaluate the reliability of the target and its cooling system under beam operation. In the framework of the target comprehensive design, a preliminary mechanical design of the full target assembly has also been carried out, assessing the feasibility of the whole target system.Comment: 17 pages, 18 figure

Size-advantage of monovalent nanobodies against the macrophage mannose receptor for deep tumor penetration and tumor-associated macrophage targeting

Rationale: Nanobodies (Nbs) have emerged as an elegant alternative to the use of conventional monoclonal antibodies in cancer therapy, but a detailed microscopic insight into the in vivo pharmacokinetics of different Nb formats in tumor-bearers is lacking. This is especially relevant for the recognition and targeting of pro-tumoral tumor-associated macrophages (TAMs), which may be located in less penetrable tumor regions.Methods: We employed anti-Macrophage Mannose Receptor (MMR) Nbs, in a monovalent (m) or bivalent (biv) format, to assess in vivo TAM targeting. Intravital and confocal microscopy were used to analyse the blood clearance rate and targeting kinetics of anti-MMR Nbs in tumor tissue, healthy muscle tissue and liver. Fluorescence Molecular Tomography was applied to confirm anti-MMR Nb accumulation in the primary tumor and in metastatic lesions.Results: Intravital microscopy demonstrated significant differences in the blood clearance rate and macrophage targeting kinetics of (m) and (biv)anti-MMR Nbs, both in tumoral and extra-tumoral tissue. Importantly, (m)anti-MMR Nbs are superior in reaching tissue macrophages, an advantage that is especially prominent in tumor tissue. The administration of a molar excess of unlabelled (biv)anti-MMR Nbs increased the (m)anti-MMR Nb bioavailability and impacted on its macrophage targeting kinetics, preventing their accumulation in extra-tumoral tissue (especially in the liver) but only partially influencing their interaction with TAMs. Finally, anti-MMR Nb administration not only allowed the visualization of TAMs in primary tumors, but also at a distant metastatic site.Conclusions: These data describe, for the first time, a microscopic analysis of (m) and (biv)anti-MMR Nb pharmacokinetics in tumor and healthy tissues. The concepts proposed in this study provide important knowledge for the future use of Nbs as diagnostic and therapeutic agents, especially for the targeting of tumor-infiltrating immune cells.Radiolog

Learning to detect good image features

State-of-the-art keypoint detection algorithms have been designed to extract specific structures from images and to achieve a high keypoint repeatability, which means that they should find the same points in images undergoing specific transformations. However, this criterion does not guarantee that the selected keypoints will be the optimal ones during the successive matching step. The approach that has been developed in this thesis work is aimed at extracting keypoints that maximize the matching performance according to a pre-selected image descriptor. In order to do that, a classifier has been trained on a set of “good” and “bad” descriptors extracted from training images that are affected by a set of pre-defined nuisances. The set of “good” keypoints used for the training is filled with those vectors that are related to the points that gave correct matches during an initial matching step. On the contrary, randomly chosen points that are far away from the positives are labeled as “bad” keypoints. Finally, the descriptors computed at the “good” and “bad” locations form the set of features used to train the classifier that will judge each pixel of an unseen input image as a good or bad candidate for driving the extraction of a set of keypoints. This approach requires, though, the descriptors to be computed at every pixel of the image and this leads to a high computational effort. Moreover, if a certain descriptor extractor is used during the training step, it must be used also during the testing. In order to overcome these problems, the last part of this thesis has been focused on the creation and training of a convolutional neural network (CNN) that uses as positive samples the patches centered at those locations that give correct correspondences during the matching step. Eventually, the results and the performances of the developed algorithm have compared to the state-of-the-art using a public benchmark

On-line refueling for the advanced high temperature reactor

Several academic and commercial organizations around the world are developing the Fluoride salt-cooled High-temperature Reactor (FHR) technology, due to its safety features and potential to generate high temperature energy for electricity and process heat applications. The Advanced High Temperature Reactor (AHTR) being considered in this study is a FHR design developed at Oak Ridge National Laboratory (ORNL) and based on the use of graphite as moderator, TRISO particles as fuel and FLiBe as coolant. The AHTR reference design is based on a traditional batch refueling approach, which requires to shut down the reactor and replace/reshuffle a certain amount of fuel assemblies in the core at a specific frequency. Several options have been evaluated in the design process, in order to maximize the lifetime of a single batch and optimize the use of fuel. However, the relatively short cycle and poor fuel utilization are intrinsic features of this family of reactors, due to the low heavy metal loading in the core and insufficient moderation, which are competing aspects in terms of core volume fraction. Since the fuel is expected to be more expensive than the fuel of light water reactors (LWR), this issue might challenge the economic viability of the AHTR. In order to eliminate or ameliorate this issue, a novel approach to refueling has been developed, consisting in continuous on-power refueling, or on-line refueling, in which the refueling procedure is performed at full power or partially reduced power (the reactor is not shut down) and a single assembly is removed per each refueling operation. A systematic neutronic and thermal-hydraulic analysis approach has been developed and performed to assess the viability and safety of the refueling operations, followed by the evaluation of the core design requirements and a quantification of the economic advantages deriving from the implementation of this procedure.Ph.D

PRELIMINARY THERMAL-HYDRAULIC ANALYSIS OF THE AHTR FUEL ELEMENT

The Advanced High Temperature Reactor (AHTR) is a molten-salt cooled reactor utilizing TRISO particle based fuel plate with graphite matrix. Its fuel type leads to low heavy metal loading which may challenge the desired cycle length and require increasing the core volume and/or reducing the power density. Therefore, tradeoffs are necessary in the core thermal and neutronic design to provide adequate cooling and moderating capability, while preserving the heavy metal loading. The cooling system must be designed to provide efficient heat removal, reducing the total core volume and the maximum fuel temperature. For preliminary analysis of the thermal performance of the system, a MATLAB model of the single coolant channel and fuel plate was developed. The model provides a steady-state characterization of the coolant temperature, velocity and other physical properties, as well as the temperature distribution within the fuel plate. The power density distribution of the plate, both in the axial and transversal directions, was studied in order to determine realistic operating conditions and to evaluate the effects on the temperature distribution. The MATLAB model was then used to perform sensitivity studies on the main parameters of the assembly design: graphite conductivity change due to irradiation and temperature, sleeve thickness, fuel stripe thickness, TRISO particle packing fraction, coolant channel thickness; also, the combined effect of the coolant gap and fuel stripe thickness variation was considered. A RELAP5-3D model of the coolant channel and fuel plate was developed, in order to validate the MATLAB model and provide the capability for transient simulations. A pipe component was selected for the modeling of the coolant channel and a slab heat structure was selected for the fuel plate. A comparison between the MATLAB and RELAP5 model was performed both with a uniform and cosine axial power density distribution, showing that the difference between the two models is mainly due to the discretization of the power profile in the RELAP5 model. An adapted MATLAB model was developed to evaluate the changes between the continuous and the discretized cosine power profile. A RELAP5 model with increased number of axial intervals was tested and a lower error was obtained. The differences between the two models were considered acceptable and the RELAP5 model will be used for implementation in full core simulations