The effect of using diesel-biodiesel-bioethanol blends on the fuel feed pump of a small-scale internal combustion engine

Biofuels represent an environmental-friendly and feasible alternative to fossil fuels for internal combustion engines. The use of diesel-biodiesel-bioethanol fuel blends (ternary blends) is one of the most interesting solutions in terms of fossil fuels substitution. They provide an improvement of exhausts gas emissions without any significant sacrifices in terms of energy-conversion efficiency. However, engine operation may be affected by the fuel substitution especially in the auxiliary mechanical fuel-feed systems, traditionally designed for low-density and high-viscosity fossil fuels. In the proposed work, two easy-to-use experimental-based mathematical models have been obtained by using the response surface method to assess the behaviour of fuel feed-pumps when biofuels blends are used. Density and mass flow-rates have been measured for several fuel mixtures and at different temperatures. The proposed equations are intended to be used as a practical tool, based on the optimal behaviour of the fuel feed-pump, in order to choose the best ternary fuel-mixture composition and/or predict/infer the engine performances under non-tested conditions (i.e., other mixtures' compositions and temperatures, however within the inquired domain)

Use of diesel-biodiesel-bioethanol blends in farm tractors: first results obtained with a mixed experimental-numerical approach

The fuelling of internal combustion engines with biofuels has certainly many environmental and energetic advantages. These advantages are particularly effective in the agricultural sector, where an integrated biofuel supply-chain would further benefit the overall carbon balance. Unfortunately, there are also some drawbacks, mainly concerning the engine performances (lowering of the torque curve), but also environmental (possible raising of the NOx emissions). However, by appropriately mixing two biofuels with known opposite effects on the combustion process, it is theoretically possible to compensate the aforementioned disadvantages. In this work, some experiments were carried out in this direction by fuelling a farm tractor with four different fuel mixes; the collected data were processed through the Response Surface Methodology to obtain multi-parameter regression equations useful to identify the optimal fuel mixtures composition. Thanks to this approach, it was found that biodiesel has a positive effect on the torque, while the addition of bioethanol has a much bigger detrimental effect; on the contrary, bioethanol should be added to a mixture with a minimum of 8-12 % of biodiesel to get advantages in terms of NOx concentration reduction

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

Immune system activation follows inflammation in unstable angina: pathogenetic implications

AbstractObjectives. The aim of this study was to assess the relations between inflammation, specific immune response and clinical course in unstable angina (UA).Background. Several studies suggest that either inflammation and/or T-cell activation might have a pathogenetic role in UA, but neither their potential reciprocal connection nor their relation to the clinical course is known.Methods. Serum levels of C-reactive protein (CRP) (inflammation), IgG, IgA, IgM, C3, C4 (humoral immunity), IL-2 and the percentage of CD4+, CD8+ and CD3+/DR+ T-cells (cell-mediated immunity) were measured in 35 patients with UA and 35 patients with chronic stable angina (CSA) during a period of 6 months.Results. The CRP levels and the main specific immune markers (CD4+ and CD3+/DR+ cells, IL-2 and IgM) were higher in unstable than in stable angina. In UA, the serum levels of IgM and IL-2 and the percentage of double positive CD3+/DR+ significantly increased at 7 to 15 days, and returned to baseline at 6 months. The increment of circulating activated T cells (CD3+/DR+) in UA was inversely related to the admission levels of CRP (r = −0.63, p = 0.003) and associated with a better outcome.Conclusions. Our data suggest that the inflammatory component systemically detectable in UA may be antigen-related and that the magnitude of the immune response correlates with the clinical outcome of instability

Recent advances of electrochemical and optical enzyme-free glucose sensors operating at physiological conditions

Diabetes is a pathological condition that requires the continuous monitoring of glucose level in the blood. Its control has been tremendously improved by the application of point-of-care devices. Conventional enzyme-based sensors with electrochemical and optical transduction systems can successfully measure the glucose concentration in human blood, but they suffer from the low stability of the enzyme. Non-enzymatic wearable electrochemical and optical sensors, with low-cost, high stability, point-of-care testing and online monitoring of glucose levels in biological fluids, have recently been developed and can help to manage and control diabetes worldwide. Advances in nanoscience and nanotechnology have enabled the development of novel nanomaterials that can be implemented for the use in enzyme-free systems to detect glucose. This review summarizes recent developments of enzyme-free electrochemical and optical glucose sensors, as well as their respective wearable and commercially available devices, capable of detecting glucose at physiological pH conditions without the need to pretreat the biological fluids. Additionally, the evolution of electrochemical glucose sensor technology and a couple of widely used optical detection systems along with the glucose detection mechanism is also discussed. Finally, this review addresses limitations and challenges of current non-enzymatic electrochemical, optical, and wearable glucose sensor technologies and highlights opportunities for future research directions

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