Non-intrusive Uncertainty Propagation in the ARC Fusion Reactor through the nemoFOAM Multi-physics Tool

In the framework of the multiphysics analysis of nuclear reactors, it is important to assess the impact of nuclear data uncertainties on relevant thermal-hydraulic quantities like temperature, pressure and mass flow rate. This is particularly important for the safety assessment and for the design verification of fission and fusion systems, through the so-called Best Estimate Plus Uncertainty approach, which qualifies the outputs providing an estimate of their uncertainties. In this work, the uncertainties are propagated from the nuclear data libraries to the thermal-hydraulic quantities of the Breeding Blanket of the Affordable, Robust, Compact fusion reactor thanks to the multiphysics tool nemoFOAM, and employing different uncertainty propagation techniques, like the Total Monte Carlo and the Unscented Transform

Improvement of Shelf Life for Space Food Through a Hurdle Approach

The processed and prepackaged spaceflight food system is a critical human support system for manned space flights. As missions extend longer and farther from Earth over the next 20 years, strategies to stabilize the nutritional and sensory quality of food must be identified. For a mission to Mars, the space foods themselves must maintain quality for up to 5 years to align with cargo prepositioning scenarios. Optimizing the food system to achieve a 5-year shelf life mitigates the risk of an inadequate food system during extended missions. Because previous attempts to determine a singular pathway to a 5-year shelf life for food were unsuccessful, this investigation combines several approaches, based on science, technological advancement, and past empirical evidence, that will define the prepackaged food system for long duration missions. This study supports the Advanced Food Technology strategic planning process by identifying food processing, packaging, and storage technologies that will be required for exploration missions and the extent that they must be implemented to achieve a 5-year shelf life for the entire food system

Analysis of the Flow Distribution in the Back Supporting Structure Manifolds of the HCPB Breeding Blanket for the EU DEMO Fusion Reactor

The European Union Demonstration Fusion Power Reactor (EU DEMO) is facing its preconceptual design phase. In this phase, the research and development activities make extensive use of computational tools, to, e.g., verify the design calculations or to perform parametric analyses aimed at optimization. The design of the breeding blanket (BB), which will be a first-of-a-kind component in EU DEMO, is supported from the thermal-hydraulic point of view by local three-dimensional (3-D) computational fluid dynamics (CFD) analyses, mainly aimed at verifying the heat removal capabilities of the system, and by analyses at the system level using one-dimensional (1-D) codes. This work presents the development and application of a detailed 1-D model of the coolant manifolds for the helium-cooled pebble bed BB concept for EU DEMO. This model, implemented in the GEneral Tokamak THErmal-hydraulic Model (GETTHEM), allows fast analyses to be performed at the global level but still maintain a good level of detail concerning the coolant distribution. The first results obtained with the model prove that 3-D CFD analyses of the manifolds may provide misleading results due to nonrepresentative boundary conditions (BCs), which must be used to avoid having a domain that is too complex. The application of a global model, which is indeed characterized exploiting local analyses, can in turn provide better BCs to the detailed 3-D CFD analyses

Multiple Monitoring Stations in Big Cities: First Example of Three Spore Traps in Rome

(1) Background: Rome is a municipality with an area of 1287 km(2) and presents floristic-vegetational complexity that is reflected in the composition of aerospora, which are responsible for pollinosis. The presence of airborne pollen can be detected by pollen monitoring. The large extent of the city's territory makes it possible to verify possible changes in pollen composition in different sites of the city. With this in mind, a study was conducted to assess the differences in airborne pollen concentration, considering phenological and production indicators at three different sites in the city. (2) Methods: Pollen data of eight taxa were considered, Alnus spp., Castanea sativa Miller, Cupressaceae-Taxaceae, Olea europaea L., Platanaceae, Poaceae, Quercus spp., and Urticaceae, during 2020 and 2021, using three monitoring samplers. The airborne pollen concentration and the seasons of the three centers were calculated and compared with each other. (3) Results: The diversity between the three samplers shows a phenological succession in accordance with the microclimatic diversity present in the city. The heterogeneity of the airborne pollen concentration reflects the floristic-vegetational diversity, while qualitative and quantitative parameters indicate a homogeneous flowering trend reflecting the seasonality of the various species. (4) Conclusions: The present work and the Italian geographic context suggest the need for a greater number of sampling points to guarantee a true localization of the data. Having several sampling stations also contributes to the protection of health and green areas, which are difficult to manage, conserve, and maintain

Analysis of the effects of primary heat transfer system isolation valves in case of in-vessel loss-of-coolant accidents in the EU DEMO

As DEMO is the first European device planned to produce electricity from fusion, the volume of its Primary Heat Transfer Systems (PHTS) will be consistently larger if compared to present or next-generation tokamaks such as ITER. The consequences of an in-vessel Loss-Of-Coolant Accident (LOCA) would then be more important, and within the EUROfusion Consortium different possible mitigation measures are being investigated. Among these, the introduction of Isolation Valves (IsoVs) on the main cooling loops of the Breeding Blanket is being considered, in view of the many benefits they would introduce, not only in case of accidents, but also e.g. during the maintenance of the in-vessel components. Fast-closing IsoVs on the PHTS would help in relaxing not only the requirements of the VV pressure suppression system (VVPSS) design, but also those related to the expansion volumes that shall accommodate the contaminated coolant discharged from the PHTS after a LOCA. In the present work, the GETTHEM code, the system-level thermal-hydraulic model developed for the EU DEMO at Politecnico di Torino, is used to assess the beneficial effects of the introduction of the IsoVs. The effects of the actuation time of the IsoVs and of their location are parametrically investigated, considering both water and helium as PHTS coolants, with particular reference to the reduction of the in-vessel space-averaged pressure and of the suppression system size

Artificial Neural Network (ANN) modeling of the pulsed heat load during ITER CS magnet operation

Artificial Neural Networks (ANNs) are applied to the development of a simplified transient model of the ITER Central Solenoid (CS), aiming at predicting the evolution of the pulsed heat load from the CS to the LHe bath during plasma operation. The ANNs are trained using the thermal–hydraulic evolution in the CS, computed with the 4C code, due to AC losses. The capability of the ANN model to predict the heat load to the LHe bath is successfully demonstrated in the case of different transients, among which a nominal plasma operating scenario. The gain in speed of the simplified model with respect to the 4C code results is by order of magnitudes, with a small loss of accuracy

Design and optimization of Artificial Neural Networks for the modelling of superconducting magnets operation in tokamak fusion reactors

In superconducting tokamaks, the cryoplant provides the helium needed to cool different clients, among which by far the most important one is the superconducting magnet system. The evaluation of the transient heat load from the magnets to the cryoplant is fundamental for the design of the latter and the assessment of suitable strategies to smooth the heat load pulses, induced by the intrinsically pulsed plasma scenarios characteristic of today's tokamaks, is crucial for both suitable sizing and stable operation of the cryoplant. For that evaluation, accurate but expensive system-level models, as implemented in e.g. the validated state-of-the-art 4C code, were developed in the past, including both the magnets and the respective external cryogenic cooling circuits. Here we show how these models can be successfully substituted with cheaper ones, where the magnets are described by suitably trained Artificial Neural Networks (ANNs) for the evaluation of the heat load to the cryoplant. First, two simplified thermal-hydraulic models for an ITER Toroidal Field (TF) magnet and for the ITER Central Solenoid (CS) are developed, based on ANNs, and a detailed analysis of the chosen networks' topology and parameters is presented and discussed. The ANNs are then inserted into the 4C model of the ITER TF and CS cooling circuits, which also includes active controls to achieve a smoothing of the variation of the heat load to the cryoplant. The training of the ANNs is achieved using the results of full 4C simulations (including detailed models of the magnets) for conventional sigmoid-like waveforms of the drivers and the predictive capabilities of the ANN-based models in the case of actual ITER operating scenarios are demonstrated by comparison with the results of full 4C runs, both with and without active smoothing, in terms of both accuracy and computational time. Exploiting the low computational effort requested by the ANN-based models, a demonstrative optimization study has been finally carried out, with the aim of choosing among different smoothing strategies for the standard ITER plasma operation

EFFECT OF WIND LOADS ON NON REGULARLY SHAPED HIGH-RISE BUILDINGS

Wind loads have historically been recognized as one of the most important issue in high-rise buildings analysis and design. In particular, in regions of low seismic intensity, a high-rise building lateral design is controlled by wind loads. In wind analysis, Computational Fluid Dynamics (CFD) and/or wind tunnel testing are required to calculate the external pressures acting on a building. In this paper, two case studies are presented to show how the wind loads are calculated and applied in design. The first case study is based on the CFD results for the New Marina Casablanca Tower in Casablanca, Morocco. The second case study considers the results from the wind tunnel test studies conducted for the Al- Hamra tower, in Kuwait City, Kuwait. The New Marina Casablanca tower is a 167m tall concrete building, with a unique twisting shape generated from the relative rotation of two adjacent floors. Sloped columns are introduced in the perimeter to follow the tower outer geometry and to support the concrete slabs spanning between the central core and the perimeter frame. The effects of wind loads on the twisted geometry has been studied in details since the pressure coefficients are not easily identified for such a complex form. In addition, the effect of the wind loads on the structure presented unique challenges that required innovative structural solutions. The Al-Hamra tower is a 412m tall concrete building with a sculpted twisting form which optimizes the views to the Arabian Gulf while minimizing the solar heat gain. The complex form is realized using sloped walls and vertical columns on the perimeter and a central concrete core. The unique shape of the tower presented several design challenges related to the wind loads on the structure. This paper will discuss the unique challenges and solutions associated with wind loads effect on buildings of unique form

Human Papilloma Virus (HPV) status, P16INK4a and p53 overexpression in epithelial malignant and borderline ovarian neoplasms

This investigation is the first to evaluate simultaneously human papilloma virus (HPV) status, p16(INK4a), and p53 immunoreactivity in epithelial ovarian neoplasms. The results were analyzed and correlated with histological type, histological grade, and survival of patients. Subtypes considered are papillary serous and mucinous. Polymerase chain reaction (PCR) analysis, performed in our previous study, had already demonstrated a small number of HPV-positive epithelial ovarian neoplasms. No significant correlation was found between the presence of HPV DNA and subtypes of ovarian neoplasms; thus, HPV cannot be considered responsible for epithelial ovarian neoplasm. Since p16 immunoreactivity was present in many other HPV-negative cases of epithelial ovarian neoplasms, this study suggests that p16 overexpression in some neoplasms of the female genital tract is not related to HPV carcinogenesis. A higher p53 expression rate observed between borderline and malignant serous tumors and between serous and mucinous neoplasms can confirm a recent dualistic model of ovarian carcinogenesis. According to this theory, low-grade serous carcinomas (serous intraepithelial carcinomas, serous borderline neoplasm, and ovarian mucinous neoplasms) (type I tumors) develop from mutations of KAS and BRAF, while high-grade serous carcinomas (type II tumors) develop from mutation of p53. In malignant neoplasms, for univariate analysis, patient survival seems to be related to p53, strong and diffuse p16 overexpression, and the stage of development of neoplasms at the diagnosis. In multinomial logistic regression, used to evaluate the role of staging, grading, p16 and p53 immunopositivity as predictor variables of unfavorable outcome of the disease, only p16 positivity was significantly related to the poor prognosis of the cancer