Cambridge Scientific Abstracts - Conference Papers Index

This research investigates if bottom ash produced by incinerating municipal solid waste after recovery of metals and aging (weathering) can be used as a substitute for natural aggregates in the manufacture of concrete without additional treatment, rather than being disposed of in landfill. In this research, the performance of eight concrete mixtures that contained different amounts (0–100%) of MSWI bottom ash was analysed. Mixtures were produced by fully replacing coarse aggregate, fine aggregate, and then both of them with MSWI bottom ash and mixing with two amounts (340 and 300 kg/m3) of cement (CEM I 42.5 R). Reference mixtures were produced as well. The influence of MSWI bottom ash as aggregate on concrete performance was evaluated in terms of density, compressive strength and flexural strength. The effect of cement content was investigated as well. In addition, the changes in density and compressive strength after 2 days, 7 days and 28 days were analysed. The research showed that concrete with a compressive strength class of C20/25 and bending strength of 3.4– 4.3 MPa can be produced by fully replacing coarse or fine aggregate. To achieve this, at least 340 kg/ m3 of cement is required.

Diesel vehicles are one of many sources of black carbon (BC) emissions in Europe; nevertheless, due to recent changes in fuel composition towards renewable fuel such as biodiesel, advances in engine design and pollution control technology, BC and organic carbon (OC) emissions may worsen air quality and encourage global warming. As there are no regulatory terms on BC mass concentration levels, assessment of pollution sources is crucial for air quality improvement policies and mitigation of climate change. BC mass concentration and aerosol optical absorption were derived using 7-wavelenght Aethalometer during 3 measurement campaigns in 2014, 2017, and 2020. BC source apportionment analysis was performed using 18 combinations of absorption Ångström exponent (AAE) values for assessing BC to fossil fuel combustion and biomass burning. The choice of the most suitable AAE combination (0.9 and 2.2, respectively) was supported by organic aerosol (OA) source apportionment results. AAE value for transport exhaust emission (0.95) from locally available diesel fuel was established using (CI) 1.9 TDI engine with different engine torque regimes and 7-wavelenght Aethalometer. Statistically and experimentally obtained values were compared and showed great agreement. Subsequently, a statistically obtained AAEtr value was used for BC source apportionment and long-term analysis. A significant increase in the contribution of transport-related BC contribution was observed between years 2014 and 2020 (from 51% to 65%) which was associated with a boost in the use of diesel vehicles (by 83.9% of diesel passenger cars comparing 2014 and 2020) and growing diesel fuel consumption. These findings underline the diesel transport-induced problem for local air quality together with its impact on atmospheric radiative balance and raise concerns for public health.

Modern science offers various probabilistic and mathematical models for students’ learning style modelling. Many of them use expert knowledge and apply key learning style theories from psycho-cognitive field (for example, David Kolb's model, Honey and Mumford's Learning Styles, Anthony Gregorc's Mind Styles, Visual, Auditory and Kinesthetic (VAK) learners’ model, Felder-Silverman Learning Style Model, etc.). Typically, student’s learning style automatic modelling uses reactive approach, i. e. learning style is modelled using massive amount of historical data about learners’ behavioral activities in the virtual learning environment (VLE). A learning-style model classifies students according to where they fit on a number of scales belonging to the ways they receive and process information [Patricio Garcia, 05]. These scales may represent the divisions of learning styles being used in Cognitive Science, Cognitive Psychology and related fields. But in case an example-based approach is used for learning style modelling, no learning style classification is known in advance. Using example-based approach, the real data about students’ behavioral activities in virtual learning environment are studied for capturing stereotypical learning style patterns, and data labeling is made during machine learning process. When example-based approach for students’ learning style modelling is applied, issues related to explanation of model results and integration of example-based model with the adaptation components that implement adaptation rules based on the well-known learning style classifications from psycho-cognitive theories must be solved. The following questions should be considered: what learning style (in terms and concepts generally accepted in psycho-cognitive theories) is represented by the cluster defined by important behavioral activities and prototype (i. e. in case the model classifies behavioral activities)? How student’s behavioral activities map to the particular learning style? How a teacher should apply learning style suitability index in case of example-based modelling which classifies behavioral activities, but not representative characteristics of learning styles presented by model from psycho-cognitive field? How should we deal with feature interaction when the prediction of learning style cannot be expressed as the sum of the feature effects as the effect of one feature depends on the value of the other feature (i. e. features are correlated)? May we reuse adaptation rules defined for particular learning style model for adaptation according to example-based learning styles? After investigating transfer learning which uses previously acquired knowledge in new learning or problem-solving situations, authors try to find answers to these questions. In the paper, an approach based on transfer learning techniques is proposed for application of example-based students’ learning style model in virtual learning environments where concepts from the well-known psycho-cognitive models have been used historically.

With the increase of urbanization and human consumption, the extraction of potentially toxic elements (PTEs) causes higher risk of them to enter sources of human food and potable water. Adsorption has been studied extensively as phenomena to reduce element mobility in both natural and engineered systems. The need to adapt the adsorption models to simulate the adsorption increases as the variety of adsorbents of natural origin is getting bigger and bigger due to their sustainability, availability and low costs. Adsorption of PTEs was analysed in the case of biochar which is a widely studied adsorbent, however, the studies are often limited to standard adsorption equilibrium and kinetic procedures without further analyses into the adsorbate and adsorbent contact zone. Zn(II), Cu(II) and Mn(II) were chosen study due to their nutritional and toxicological features. Diagnostic methods were used to differentiate the metal behaviour during adsorption and dynamic intraparticle model was further employed to simulate the kinetic conditions. Harkins-Jura isotherm model and pseudo-second kinetic model were determined to fit the adsorption of PTEs on biochar. According to the adsorption efficiency and capacity, PTEs fell into the following sequence: Cu(II) > Mn(II)>Zn(II). It was observed that the kinetics of Cu(II) decreased in the solution by about 1.7 times more than of Zn(II) and about 2.3 times more than of Mn(II). Cu(II) decreased faster and more suddenly than Mn(II) and Zn(II) in the solution on the particle surface and in the solution inside the particle.

A finite element model simulates concrete cracking using a smeared crack approach. The uncertainty of the crack width model is verified by the experimental data from tests of reinforced concrete beams. The parametric analysis of the numerical model includes the effects of the bond, fracture energy, and finite element mesh size. The model uncertainty analysis confirmed that the smeared crack model based on fracture mechanics could adequately predict the maximum crack width.

Nowadays worldwide directives have focused the attention on improving energy efficiency in the building sector. The research of models able to predict the energy consumption from the first design and energy planning phase is conducted to improve building sustainability. Use of traditional forecasting tools for building thermal energy demand tends to encounter difficulties relevant to the amount of data required, implementation of the models, computational costs and inability to generalize the output. Therefore, many studies focused on the research and development of alternative resolution methods, but the choice of the most convenient is not clear and simple. Single comparison of statistical quality indexes does not allow an adequate identification of the most efficient method, as the necessary efforts for implementation of the methods from the initial data collection to the use phase are not considered. In this work, the authors propose to apply, for the first time, the multicriteria assessment to determine the most efficient alternative method, used for forecasting of building thermal energy demand. Three alternative “black-box” methods, previously investigated by the authors, were compared by the multiple criteria Complex Proportional Assessment Method. Such a procedure revealed ranking of the methods in four phases, namely Pre-processing, Implementation, Post-processing and Use, as well as overall assessment and selection of the most efficient method in terms of evaluated criteria. This first application could represent an incentive for future multi-criteria analyses involving a growing number of alternative forecasting methods.

Non-contact surface measurement methods as well as roughness parameter determination methods are analyzed in the paper. While most of the modern non-contact surface inspection methods require advanced instrumentation and a big budget, this study looks into a novel approach to non-contact encoder disc roughness measurements by using the proposed system attached to the rotary table with an implemented optical disc pick up head and the reference angle encoder. Application of a conventional optical disc laser reading system resulted in a cost effective and compact solution for a nondestructive angle encoder disc surface inspection. Assets and shortcomings as well as detailed analysis of the measurement procedure are explained in the paper. The experimental setup and the measurement results are presented within this article.

Research background: The value of clusters in developing advanced technology products and services as well as promoting regional growth is acknowledged by many policymakers and researchers (Lee et al., 2012). Hence, clusters are identified as enablers of the circular economy and resource efficiency in this study. Companies aim to enhance competencies and create competitive advantages in global competition and this can be achieved through pulling from a common and accessible pool of resources, information and demand for innovation which means that companies can profit from belonging to a cluster. Purpose of the article: The main aim of the article is to overview the scientific literature that addresses the circular economy, identify clusters and their role in the circular economy and suggest how small and medium enterprises could engage in a circular economy through clusters' performance development. Methods: Bibliometric literature analysis enables identifying the latest trends in scientific articles regarding a circular economy and clusters. The analytical hierarchy process (AHP) allows for composing the scheme of the cluster’s competitive advantage within circular economy. Findings & Value added: The findings suggest that resource efficiency is considered to be one of the most important ambitions and clusters can work as enablers of a circular economy for small and medium enterprises (SMEs), gaining a competitive advantage at the same time. Clusters can encourage and provide conditions in which SMEs would turn to a circular economy. The scheme of Cluster's competitive advantage proposed by the author can help cluster's coordinators, policymakers and all the concerned parties to verify the importance of clusters' involvement in the circular economy.