Experimental Investigation and RSM Modeling of the Effects of Injection Timing on the Performance and NOx Emissions of a Micro-Cogeneration Unit Fueled with Biodiesel Blends

The (partial or total) substitution of petro-diesel with biodiesel in internal combustion engines (ICEs) could represent a crucial path towards the decarbonization of the energy sector. However, critical aspects are related to the controversial issue of the possible increase in Nitrogen Oxides (NOx) emissions. In such a framework, the proposed study aims at investigating the effects of biodiesel share and injection timing on the performance and NOx emissions of a diesel micro combined heat and power (CHP) system. An experimental campaign has been conducted considering the following operating conditions: (i) a reference standard injection timing (17.2° BTDC), an early injection timing (20.8° BTDC), and a late injection timing (12.2° BTDC); (ii) low (0.90 kW), partial (2.45 kW), and full (3.90 kW) output power load; and (iii) four fuel blends with different biodiesel (B) shares (B0, B15, B30, and B100). Experimental data were also elaborated on thanks to the response surface modelling (RSM) technique, aiming at (i) quantifying the influences of the above-listed variables and their trends on the responses, and (ii) obtaining a set of predictive numerical models that represent the basis for model-based design and optimization procedures. The results show: (i) an overall improvement of the engine performance due to the biodiesel presence in the fuel blend —in particular, B30 and B100 blends have shown peak values in both electrical (29%) and thermal efficiency (42%); (ii) the effective benefits of late SOI strategies on NOx emissions, quantified in an overall average NOx reduction of 27% for the early-to-late injection, and of 16% for the standard-to-late injection strategy. Moreover, it has emerged that the NOx-reduction capabilities of the late injection strategy decrease with higher biodiesel substitution rates; through the discussion of high-prediction-capable, parametric, data-driven models, an extensive RSM analysis has shown how the biodiesel share promotes an increase of NOx whenever it overcomes a calculated threshold that is proportional to the engine load (from about 66.5% to 85.7% of the biodiesel share)

Proposal of a predictive mixed experimental-numerical approach for assessing the performance of farm tractor engines fuelled with diesel-biodiesel-bioethanol blends

The effect of biofuel blends on the engine performance and emissions of agricultural machines can be extremely complex to predict even if the properties and the effects of the pure substances in the blends can be sourced from the literature. Indeed, on the one hand, internal combustion engines (ICEs) have a high intrinsic operational complexity; on the other hand, biofuels show antithetic effects on engine performance and present positive or negative interactions that are difficult to determine a priori. This study applies the Response Surface Methodology (RSM), a numerical method typically applied in other disciplines (e.g., industrial engineering) and for other purposes (e.g., set-up of production machines), to analyse a large set of experimental data regarding the mechanical and environmental performances of an ICE used to power a farm tractor. The aim is twofold: i) to demonstrate the effectiveness of RSM in quantitatively assessing the effects of biofuels on a complex system like an ICE; ii) to supply easy-to-use correlations for the users to predict the effect of biofuel blends on performance and emissions of tractor engines. The methodology showed good prediction capabilities and yielded interesting outcomes. The effects of biofuel blends and physical fuel parameters were adopted to study the engine performance. Among all possible parameters depending on the fuel mixture, the viscosity of a fuel blend demonstrated a high statistical significance on some system responses directly related to the engine mechanical performances. This parameter can constitute an interesting indirect estimator of the mechanical performances of an engine fuelled with such blend, while it showed poor accuracy in predicting the emissions of the ICE (NOx, CO concentration and opacity of the exhaust gases) due to a higher influence of the chemical composition of the fuel blend on these parameters; rather, the blend composition showed a much higher accuracy in the assessment of the mechanical performance of the ICE

Position and Stiffness Control of One DoF Revolute Joint Using a Biphasic Media Variable Stiffness Actuator

At this time, several industrial processes and service tasks need safe interactions between humans and robots. This safety can be achieved using compliance design and control of mechanisms. This paper presents a compliant revolute joint mechanism using a variable stiffness actuator. The method for adapting the stiffness in the actuator includes a member onfigured to transmit motion that is connected to a fluidic circuit, into which a biphasic control fluid circulates. Actuator's stiffness is controlled by changing pressure of control fluid into distribution lines. The used control fluid is biphasic, composed of separated gas and liquid fractions with predefined ratio. A mathematical model of the actuator is presented, a modelbased control method is implemented to track the desired position and stiffness, and equations relating to the dynamics of the mechanism are provided. Results from force loaded and unloaded simulations and experiments with a physical prototype are discussed

Evaluation of extraction-free RT-qPCR methods for SARS-CoV-2 diagnostics

Extraction-based real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) is currently the “gold standard” in SARS-CoV-2 diagnostics. However, some extraction-free RT-qPCR techniques have recently been developed. In this study, we compared the sensitivity of traditional extraction-based, heated extraction-free, and unheated extraction-free RT-qPCR methods for SARS-CoV-2 detection in nasopharyngeal swabs from symptomatic individuals. The unheated extraction-free method showed perfect agreement with the standard extraction-based RT-qPCR. By contrast, the heat-treated technique was associated with an 8.2% false negativity rate. Unheated extraction-free RT-qPCR for the molecular diagnosis of SARS-CoV-2 is a valuable alternative to the traditional extraction-based methods and may accelerate turnaround times by about two hours

Identification of hip fracture patients from radiographs using Fourier analysis of the trabecular structure: a cross-sectional study

Peer reviewedPublisher PD

Outbreak of sars-cov-2 lineage 20i/501y.V1 in a nursing home underlines the crucial role of vaccination in both residents and staff

Elderly residents in nursing homes are at very high risk of life-threatening COVID-19-related outcomes. In this report, an epidemiological and serological investigation of a SARS-CoV-2 outbreak in an Italian nursing home is described. Among the residents, all but one (19/20) were regularly vaccinated against SARS-CoV-2. In mid-February 2021, a non-vaccinated staff member of the nursing home was diagnosed with the SARS-CoV-2 infection. Following the outbreak investigation, a total of 70% (14/20) of residents aged 77–100 years were found positive. The phylogenetic analysis showed that the outbreak was caused by the SARS-CoV-2 variant of concern 202012/01 (the so-called “UK variant”). However, all but one positive subjects (13/14) were fully asymptomatic. The only symptomatic patient was a vaccinated 86-year-old female with a highly compromised health background and deceased approximately two weeks later. The subsequent serological investigation showed that the deceased patient was the only vaccinated subject that did not develop the anti-spike protein antibody response, therefore being likely a vaccine non-responder. Although the available mRNA SARS-CoV-2 vaccine was not able to prevent several asymptomatic infections, it was able to avert most symptomatic disease cases caused by the SARS-CoV-2 variant of concern 202012/01 in nursing home residents

Comparative diagnostic performance of rapid antigen detection tests for COVID-19 in a hospital setting

Background: The availability of accurate and rapid diagnostic tools for COVID-19 is essential for tackling the ongoing pandemic. Our study aimed to quantify the performance of available antigen-detecting rapid diagnostic tests (Ag-RDTs) in a real-world hospital setting. Methods: In this retrospective analysis, the diagnostic performance of 7 Ag-RDTs was compared with real-time reverse transcription quantitative polymerase chain reaction assay in terms of sensitivity, specificity and expected predictive values. Results: A total of 321 matched Ag-RDTreal-time reverse transcription quantitative polymerase chain reaction samples were analyzed retrospectively. The overall sensitivity and specificity of the Ag-RDTs was 78.7% and 100%, respectively. However, a wide range of sensitivity estimates by brand (66.0%–93.8%) and cycle threshold (Ct) cut-off values (Ct <25: 96.2%; Ct 30–35: 31.1%) was observed. The optimal Ct cut-off value that maximized sensitivity was 29. Conclusions: The routine use of Ag-RDTs may be convenient in moderate-to-high intensity settings when high volumes of specimens are tested every day. However, the diagnostic performance of the commercially available tests may differ substantially