Heat Exchange Analysis on Latent Heat Thermal Energy Storage Systems Using Molten Salts and Nanoparticles as Phase Change Materials

The increase of carbon dioxide emissions is the most important contributor to climate change. A better use of produced energy, increasing systems efficiency and using renewable sources, can limit them. A key technological issue is to integrate a thermal energy storage (TES). It consists in stocking thermal energy through the heating/cooling of a storage material for future needs. Among various technologies, latent heat TES (LHTES) provides high energy storage density at constant temperature during melting/solidification of storage media. The bottleneck in the use of typical PCMs is their low thermal conductivity. To improve the heat exchange between heat transfer fluid and PCM, three methods are possible and here experimentally analyzed: conductivity systems enhancements; convective flows promotion in liquid phase; and improvement of PCM thermal properties including small amounts of nanoparticles. CFD models were used to evaluate physical phenomena that are crucial for optimized LHTES systems design. The study of the heat exchange mode allowed some useful indications to achieve an optimized LHTES, taking advantage by convective flows and conductivity promotion systems. The use of NEPCM, to maximize the stored energy density and realize compact systems, makes necessary the improvement of its thermal diffusivity. These will be the future research topics

Shake‑table testing of a stone masonry building aggregate: overview of blind prediction study

City centres of Europe are often composed of unreinforced masonry structural aggregates, whose seismic response is challenging to predict. To advance the state of the art on the seismic response of these aggregates, the Adjacent Interacting Masonry Structures (AIMS) subproject from Horizon 2020 project Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe (SERA) provides shake-table test data of a two-unit, double-leaf stone masonry aggregate subjected to two horizontal components of dynamic excitation. A blind prediction was organized with participants from academia and industry to test modelling approaches and assumptions and to learn about the extent of uncertainty in modelling for such masonry aggregates. The participants were provided with the full set of material and geometrical data, construction details and original seismic input and asked to predict prior to the test the expected seismic response in terms of damage mechanisms, base-shear forces, and roof displacements. The modelling approaches used differ significantly in the level of detail and the modelling assumptions. This paper provides an overview of the adopted modelling approaches and their subsequent predictions. It further discusses the range of assumptions made when modelling masonry walls, floors and connections, and aims at discovering how the common solutions regarding modelling masonry in general, and masonry aggregates in particular, affect the results. The results are evaluated both in terms of damage mechanisms, base shear forces, displacements and interface openings in both directions, and then compared with the experimental results. The modelling approaches featuring Discrete Element Method (DEM) led to the best predictions in terms of displacements, while a submission using rigid block limit analysis led to the best prediction in terms of damage mechanisms. Large coefficients of variation of predicted displacements and general underestimation of displacements in comparison with experimental results, except for DEM models, highlight the need for further consensus building on suitable modelling assumptions for such masonry aggregates

Disease-Modifying Therapies and Coronavirus Disease 2019 Severity in Multiple Sclerosis

Objective: This study was undertaken to assess the impact of immunosuppressive and immunomodulatory therapies on the severity of coronavirus disease 2019 (COVID-19) in people with multiple sclerosis (PwMS). Methods: We retrospectively collected data of PwMS with suspected or confirmed COVID-19. All the patients had complete follow-up to death or recovery. Severe COVID-19 was defined by a 3-level variable: mild disease not requiring hospitalization versus pneumonia or hospitalization versus intensive care unit (ICU) admission or death. We evaluated baseline characteristics and MS therapies associated with severe COVID-19 by multivariate and propensity score (PS)-weighted ordinal logistic models. Sensitivity analyses were run to confirm the results. Results: Of 844 PwMS with suspected (n = 565) or confirmed (n = 279) COVID-19, 13 (1.54%) died; 11 of them were in a progressive MS phase, and 8 were without any therapy. Thirty-eight (4.5%) were admitted to an ICU; 99 (11.7%) had radiologically documented pneumonia; 96 (11.4%) were hospitalized. After adjusting for region, age, sex, progressive MS course, Expanded Disability Status Scale, disease duration, body mass index, comorbidities, and recent methylprednisolone use, therapy with an anti-CD20 agent (ocrelizumab or rituximab) was significantly associated (odds ratio [OR] = 2.37, 95% confidence interval [CI] = 1.18-4.74, p = 0.015) with increased risk of severe COVID-19. Recent use (<1 month) of methylprednisolone was also associated with a worse outcome (OR = 5.24, 95% CI = 2.20-12.53, p = 0.001). Results were confirmed by the PS-weighted analysis and by all the sensitivity analyses. Interpretation: This study showed an acceptable level of safety of therapies with a broad array of mechanisms of action. However, some specific elements of risk emerged. These will need to be considered while the COVID-19 pandemic persists

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score > 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p < 0.001), RR = 2.19 for ICU admission (p < 0.001), and RR = 2.43 for death (p < 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

CFD modelling of an indirect thermocline energy storage prototype for CSP applications

Thermocline thermal energy storage is a (potentially) cost-effective alternative to the more widespread two-tank solution, as both the hot and the cold medium are stored in a single tank. An innovative single-medium indirect thermocline technology was recently developed by ENEA and a prototype was experimentally tested at the Casaccia laboratories. The storage tank is equipped with two flat-coil heat exchangers (HXs) located at the bottom and at the top of the tank, for the charge and discharge phases, respectively. The storage medium is a mixture of molten salt (Hitec XL) and the heat transfer fluid is a mineral oil (Delcoterm Solar E15). An internal vertical channel, which assists the motion of the storage medium during the charge and discharge transients, connects the two HXs. In this paper, a detailed, transient 2D axisymmetric Computational Fluid Dynamics (CFD) model of the prototype has been developed. The model simulates the charge and discharge transients, determining the heat losses and the temperature distribution of the molten salt in the tank. The computational domain includes the storage medium, the tank insulated walls and the main components immersed in the molten salt, i.e., the heat exchangers and the vertical channel. The model has been first calibrated by best-fitting the data measured during a test conducted without any thermal load, then validated against another independent set of experimental data. A first comparison against a charge transient showed some discrepancies between the computed and the measured temperatures of the salt, which could be explained by assuming the presence of a bypass at the location of the HXs. This assumption is discussed and justified in the paper. The CFD domain has then been modified to include the bypass, and this allowed to successfully validate the model against experimental data in both charge and discharge phases. The validated model is finally exploited to assess how a variation in the diameter of the internal vertical channel could affect the thermal performance of the storage system in a charge transient. The results indicate that decreasing the channel diameter leads to an increase of the salt temperature at the very top of the tank at the cost of a longer time to fully charge the storage