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1.
Food Waste to Energy through Innovative Coupling of CHP and Heat Pump
Jan Drofenik, Danijela Urbancl, Darko Goričanec, Zdravko Kravanja, Zorka Novak-Pintarič, 2023, original scientific article

Abstract: This paper presents the conceptual design of a technological solution for the efficient conversion of food waste into heat and power. The distribution and composition of food loss and waste at different stages of the food supply chain in Slovenia and their potential for biogas production were determined. It was found that more than 50% of food waste comes from households. Therefore, a small plant was designed to convert food waste into biogas, which was innovatively coupled with a combined heat and power (CHP) unit and a heat pump. This doubles the amount of heat generated compared to conventional cogeneration. Based on the capacity of a micro commercial CHP unit, 3330 households (about 8000 residents) would supply food waste. The heat generated could replace 5% of the natural gas used for domestic water heating. The payback period would be 7.2 years at a heat price of about 80 EUR/MWh, however, for municipalities with more than 40,000 inhabitants the payback period would be reduced to less than 3 years. The cost price of the heat generated by this system would be about 25 EUR/MWh, taking into account the government subsidy for the operation of the CHP unit.
Keywords: food waste to energy, biogas, combined heat and power, CHP, heat pump, efficiency, conceptual design, preliminary economic assessment, sensitivity analysis
Published in DKUM: 16.02.2024; Views: 3081; Downloads: 14
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2.
Multi-criteria measurement of ai support to project management
Vesna Čančer, Polona Tominc, Maja Rožman, 2023, original scientific article

Abstract: This paper aims to measure the level of artificial intelligence (AI) support to project management (PM) in selected service sector activities. The exploratory factor analysis was employed based on the extensive survey on AI in Slovenian companies and the multi-criteria measurement with an emphasis on value functions and pairwise comparisons in the analytic hierarchy process. The synthesis and performance sensitivity analysis results show that in the service sector, concerning all criteria, PM is with the level 0.276 best supported with AI in services of professional, scientific, and technical activities, which also stand out concerning the first-level goals in using AI solutions in a project with the value 0.284, and in successful project implementation using AI with the value 0.301. Although the lowest level of AI support to PM, which is 0.220, is in services of wholesale and retail trade and repair of motor vehicles and motorcycles, these services excel in adopting AI technologies in a project with a value of 0.277. Services of financial and insurance activities, with the level 0.257 second-ranked concerning all criteria, have the highest value of 0.269 concerning the first-level goal of improving the work of project leaders using AI. The paper, therefore, contributes to the comparison of AI support to PM in service sector activities. The results can help AI development policymakers determine which activities need to be supported and which should be set as an example. The presented methodological frame can serve to perform measurements and benchmarking in various research fields.
Keywords: artificial intelligence, factor analysis, multiple criteria, performance sensitivity, project management
Published in DKUM: 12.02.2024; Views: 247; Downloads: 15
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3.
A company’s carbon footprint and sustainable development
Jure Gramc, Rok Stropnik, Mitja Mori, 2022, original scientific article

Abstract: Climate changes are already here. And they will get much worse in time. The main reason for global warming is GHG emissions from anthropological sources. That includes transportation, industry, electricity production, agriculture, and others. The European Union has introduced a new Green Deal as an answer to climate change. The European Green Deal puts more pressure on companies to mitigate their carbon footprint and implement sustainable development. One of the basic steps in the analysis of the environmental profile of a company is the identification of hot spots by using the carbon footprint methodology. The workflow of the carbon footprint calculation follows GHG Protocol standardised methodology. The calculation was made for a medium-sized company in the plastics industry. For all GHG emission sources, hot spots were identified and analysed. Based on the hot spots, sensitivity analysis for different pre-defined scenarios has been made, which are aligned with the company’s mid- and long-term sustainability goals. The three main hot spots of the company within scopes 1 and 2 are purchased heat, purchased electricity, and combustion of fuels in company vehicles. GHG emissions of heat and electricity are dependent on their distributor and their electricity and heat sources. The hot spot of scope 3 is purchased goods, especially plastic granulate. In the study, we focus only on scope 1 and scope 2.
Keywords: carbon footprint, sustainable development, environmental impacts, GHG Protocol, greenhouse gas emissions, global warming, sensitivity analysis
Published in DKUM: 30.10.2023; Views: 389; Downloads: 9
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4.
Numerical simulation of intact rock behaviour via the continuum and Voronoi tesselletion models : a sensitivity analysis
Teja Fabjan, Diego Mas Ivars, Vladimir Vukadin, 2015, original scientific article

Abstract: The numerical simulation of intact rock microstructure and its influence on macro-scale behaviour has received a lot of attention in the research community in recent years. Generating a grain-like structure with polygonal area contacts is one of the avenues explored for describing the rock’s microstructure. A Voronoi tessellation implemented in the Universal Distinct-Element Code (UDEC) is used to generate models with a polygonal microstructure that represent intact rock. The mechanical behaviour of the Voronoi polygons is defined by micro-properties, which cannot be measured directly in the laboratory. A numerical calibration procedure is needed to produce the macroscopic response of a model that corresponds to the material behaviour measured during a laboratory experiment. In this research, Brazilian, direct tensile, uniaxial compressive and biaxial test models are constructed to simulate the intact rock behaviour under a standard laboratory stress. An extensive series of parametric sensitivity analyses are executed in order to understand the influence of the input micro-properties on every model test behaviour and predict the relation between the micro-properties and the model’s macro response. The results can be treated as general guidelines for a complete and efficient intact rock calibration procedure. In parallel, a continuum-based model using the Mohr-Coulomb constitutive relationship is running as a benchmark. It has been shown that the Voronoi-based models through their microstructure approach better reproduce the Brazilian to direct tensile strength ratio, and show a better representation of the dilation, crack pattern and post-peak behaviour in comparison to continuum models.
Keywords: distinct-element method, parametric sensitivity analysis, intact rock, Voronoi tessellation, micromechanical properties, standard laboratory test
Published in DKUM: 15.06.2018; Views: 1520; Downloads: 99
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