Thermal Performance of the Supporting System for the Large Hadron Collider (LHC) Superconducting Magnets

The LHC collider will be composed of approximately 1700 main ring superconducting magnets cooled to 1.9 K in pressurised superfluid helium and supported within their cryostats on low heat in-leak column-type supports. The precise positioning of the heavy magnets and the stringent thermal budgets imposed by the machine cryogenic system, require a sound thermo-mechanical design of the support system. Each support is composed of a main tubular thin-walled structure in glass-fibre reinforced epoxy resin, with its top part interfaced to the magnet at 1.9 K and its bottom part mounted onto the cryostat vacuum vessel at 293 K. In order to reduce the conduction heat in-leak at 1.9 K, each support mounts two heat intercepts at intermediate locations on the column, both actively cooled by cryogenic lines carrying helium gas at 4.5-10 K and 50-65 K. The need to assess the thermal performance of the supports has lead to setting up a dedicated test set-up for precision heat load measurements on prototype supports. This paper presents the thermal design of the support system of the LHC arc magnets. The results of the thermal tests of a prototype support made in industry are illustrated and discussed. A mathematical model has been set up and refined by the comparison with test results, with the scope of extrapolating the observed thermal performance to different geometrical and material parameters. Finally, the calculated estimate of the heat load budgets of the support system and their contribution to the total cryogenic budget for an LHC arc are presented

Adverse Childhood Events, Safety, & Comfort: Associations with Adolescent Symptoms

A PowerPoint that accompanied a oral presentation.https://scholarworks.moreheadstate.edu/celebration_posters_2023/1065/thumbnail.jp

deep learning based segmentation of breast masses in dedicated breast ct imaging radiomic feature stability between radiologists and artificial intelligence

Abstract A deep learning (DL) network for 2D-based breast mass segmentation in unenhanced dedicated breast CT images was developed and validated, and its robustness in radiomic feature stability and diagnostic performance compared to manual annotations of multiple radiologists was investigated. 93 mass-like lesions were extensively augmented and used to train the network (n = 58 masses), which was then tested (n = 35 masses) against manual ground truth of a qualified breast radiologist with experience in breast CT imaging using the Conformity coefficient (with a value equal to 1 indicating a perfect performance). Stability and diagnostic power of 672 radiomic descriptors were investigated between the computerized segmentation, and 4 radiologists' annotations for the 35 test set cases. Feature stability and diagnostic performance in the discrimination between benign and malignant cases were quantified using intraclass correlation (ICC) and multivariate analysis of variance (MANOVA), performed for each segmentation case (4 radiologists and DL algorithm). DL-based segmentation resulted in a Conformity of 0.85 ± 0.06 against the annotated ground truth. For the stability analysis, although modest agreement was found among the four annotations performed by radiologists (Conformity 0.78 ± 0.03), over 90% of all radiomic features were found to be stable (ICC>0.75) across multiple segmentations. All MANOVA analyses were statistically significant (p ≤ 0.05), with all dimensions equal to 1, and Wilks' lambda ≤0.35. In conclusion, DL-based mass segmentation in dedicated breast CT images can achieve high segmentation performance, and demonstrated to provide stable radiomic descriptors with comparable discriminative power in the classification of benign and malignant tumors to expert radiologist annotation

Il Picariglio Castigliano, cioè la vita di Lazariglio di Tormes In Venetia. Presso il Barezzi MDCXXII

Il Picariglio Castigliano di Barezzo Barezzi è espressione della ricezione del messaggio picaresco veicolato da una delle più rappresentative opere del genere: la Vida de Lazarillo de Tormes y de sus fortunas y adversidades. Questa edizione propone una trascrizione della prima traduzione italiana del Lazarillo elaborata da Barezzo Barezzi e da lui stesso stampata a Venezia una prima volta nel 1622, in una seconda izione nel 1626, ed in una terza, con notevoli varianti rispetto alle altre due, nel 1635.Il Picariglio Castigliano di Barezzo Barezzi è espressione della ricezione del messaggio picaresco veicolato da una delle più rappresentative opere del genere: la Vida de Lazarillo de Tormes y de sus fortunas y adversidades. Questa edizione propone una trascrizione della prima traduzione italiana del Lazarillo elaborata da Barezzo Barezzi e da lui stesso stampata a Venezia una prima volta nel 1622, in una seconda izione nel 1626, ed in una terza, con notevoli varianti rispetto alle altre due, nel 1635

Heat Flow Measurements on LHC Components

The refrigeration and liquefaction capacity necessary to operate at 1.9 K the 27 km long string of superconducting magnets of the LHC has been determined on the basis of heat load estimates, including static heat inleaks from ambient temperature, resistive heating and dynamic beam-induced heat loads. At all temperature levels, the static heat inleaks determine at least one third of the total heat loads in nominal operating conditions of the machine. Design validation of individual cryocomponents therefore requires a correct estimate of the heat inleaks they induce at all temperature levels, in order not to exceed the allocated heat budget. This paper illustrates the measurements of heat inleaks for several cold components of the future machine, including insulating supports, radiation shields, multi-layer insulation, instrumentation current leads. Distinct methods to determine the heat flow are chosen, depending on the expected heat loads, the temperature range spanned by the heat intercepts, and the working conditions of the component itself

Characterization of the PTW 34031 ionization chamber (PMI) at RCNP with high energy neutrons ranging from 100 – 392 MeV

Radiation monitoring at high energy proton accelerators poses a considerable challenge due to the complexity of the encountered stray radiation fields. These environments comprise a wide variety of different particle types and span from fractions of electron-volts up to several terra electron-volts. As a consequence the use of Monte Carlo simulation programs like FLUKA is indispensable to obtain appropriate field-specific calibration factors. At many locations of the LHC a large contribution to the particle fluence is expected to originate from high-energy neutrons and thus, benchmark experiments with mono-energetic neutron beams are of high importance to verify the aforementioned detector response calculations. This paper summarizes the results of a series of benchmark experiments with quasi mono-energetic neutrons of 100, 140, 200, 250 and 392 MeV that have been carried out at RCNP - Osaka University, during several campaigns between 2006 and 2014