Iskanje po katalogu digitalne knjižnice

Opis: Waste heat recovery technologies play an important role in enhancing energy efficiency and supporting sustainable energy production. This study investigates the utilization of waste heat from aluminium production through an Organic Rankine Cycle (ORC) system to generate electricity and heat simultaneously. Based on operational data from an aluminium plant, the system is firstly optimized from both the thermodynamic and economic perspectives. To maximize performance and to identify optimal configurations, a mathematical model is developed and solved using GAMS, capturing the complex interdependencies between the operational, economic and thermodynamic parameters. The environmental impact of the optimized scenarios is subsequently evaluated using a Life Cycle Assessment (LCA), considering a broad range of impact categories. The results indicate a maximum power output of 830.9 kW and a maximum net present value (NPV) of 51.71 M€, confirming the system’s technical and economic viability. The environmental assessment demonstrates the potential of ORC systems as sustainable energy solutions, with significant environmental unburdening under optimized operating conditions (up to -606.0 kg CO2 eq./h). A sensitivity analysis indicates that the greatest environmental benefits occur under the optimal thermodynamic scenario, achieved through the utilization of higher-energy flue gas streams (up to -515.0 kg CO2 eq./h), and under the optimal economic scenario by balancing the electricity and heat prices optimally for simultaneous heat and power production (up to -696.7 kg CO2 eq./h). These findings highlight the importance of the thermal input quality and availability in maximizing ORC performance. With the ability to prioritize electricity, heat, or both, the optimized ORC systems support flexible energy solutions tailored to specific applications and environmental conditions, offering a promising pathway for unburdening the environment through the efficient utilization of industrial waste heat.
Ključne besede: waste heat recovery, aluminium production, organic rankine cycle, environmental impact, life cycle assessment, sustainable energy solutions
Objavljeno v DKUM: 13.06.2025; Ogledov: 0; Prenosov: 5
Celotno besedilo (1,30 MB)

Opis: Every combination of product mix and production volume requires a suitable layout of workplaces (functional units). An optimised layout is of utmost importance to achieve global competitiveness of companies and to build an efficient, sustainable production. We plan the layout mainly with heuristic methods; constructive, improvement and combined methods are available. In this paper, a modification of the established improvement algorithm CRAFT (exchange method) is presented, which provides much better and more accurate results at a slightly higher computational cost. The most important change is the immediate precise determination of the centroids of the areas of workplaces (or departments) that are exchanged. The distance between any two workplaces is represented by the orthogonal distance between the centroids. In the example given, which is based on a pairwise exchange, the difference is 22 % in favour of the modified algorithm.
Ključne besede: algorithm modification, CRAFT method, layout optimisation, pair-wise exchanges, production layout
Objavljeno v DKUM: 21.05.2025; Ogledov: 0; Prenosov: 5
Celotno besedilo (890,32 KB)
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Opis: This study focuses on the segmentation part in the development of a potato-sorting system that utilizes camera input for the segmentation and classification of potatoes. The key challenge addressed is the need for efficient segmentation to allow the sorter to handle a higher volume of potatoes simultaneously. To achieve this, the study employs a region-based convolutional neural network (R-CNN) approach for the segmentation task, while trying to achieve more precise segmentation than with classic CNN-based object detectors. Specifically, Mask R-CNN is implemented and evaluated based on its performance with different parameters in order to achieve the best segmentation results. The implementation and methodologies used are thoroughly detailed in this work. The findings reveal that Mask R-CNN models can be utilized in the production process of potato sorting and can improve the process.
Ključne besede: image segmentation, potato sorting, neural network, mask RCNN, object detection, production process, machine learning, AI
Objavljeno v DKUM: 27.03.2025; Ogledov: 0; Prenosov: 12
Celotno besedilo (5,97 MB)
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Opis: The environment hosts a diversity of microorganisms whose potential for biotechnological applications has not yet been exhausted. The quest of our study was to find isolates of Pichia kudriavzevii from the environment that could be used as new biotechnological agents. Moreover, we aimed to explore the resource efficiency for microbial cultivation, in particular the efficiency of spent coffee grounds (SCG), an easily accessible waste coffee product with a high unutilized organic content. In this study, Pichia kudriavzevii strain ZMUM_K002, a yeast strain isolated from a grape pomace compost, was investigated. Antifungal susceptibility, particularly fluconazole susceptibility, was assessed, and the strain’s biotechnological potential by comparing its ability to utilize low-cost carbon sources, including SCG, with a natural isolate of Saccharomyces cerevisiae (strain ZMUM_K003) was assessed. The P. kudriavzevii strain ZMUM_K002 exhibited higher fluconazole susceptibility and yielded more than 30% more biomass in optimized media formulations compared to S. cerevisiae ZMUM_K003. These findings demonstrate that P. kudriavzevii ZMUM_K002 has the potential for efficient biomass production in sustainable industrial biotechnology, particularly in processes requiring high biomass yields on alternative substrates.
Ključne besede: Pichia kudriavzevii, Candida krusei, environmental sampling, biomass production, sauerkraut, safety assessment, spent coffee grounds
Objavljeno v DKUM: 21.03.2025; Ogledov: 0; Prenosov: 6
Celotno besedilo (1,93 MB)
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Opis: The significance of the agricultural sector in the economy of Republika Srpska, as well as the importance of dairy cattle farming within agriculture, determined the thematic field of the research, which had several key research objectives. The first objective of the dissertation was to determine the economic efficiency of the investment in milk production and sales on family farms with 8-15 dairy cows in Republika Srpska. The second objective was to assess the risk, or volatility, of such investment projects. The third objective was to calculate the additional value of diversification in transitioning from selling milk to milk processing into cheese on the same farm and determine the additional project's strategic value. The final objective was to compare the case studies of the analyzed farms based on selected indicators. Primary data were collected by interviewing five farmers who produce milk and process it into cheese while secondary data were obtained from various sources. Key data processing methods included Cost-Benefit Analysis, Monte Carlo simulations, and Black-Scholes and Binomial methods for evaluating real options. Based on the results of the analysis of milk production projects on small farms in Republika Srpska, it was concluded that these projects are economically unsustainable due to their negative and insufficiently satisfactory indicators. Through Monte Carlo simulations, it was determined that changes in input and output prices have an impact on such projects. Diversification of milk production into cheese processing on small farms is economically efficient, as the option values of the additional project are satisfactory and the NPVS, representing the total value of the additional project, ranges from €28,000 to €143,000 for all five analyzed farms. Based on the farm analysis, the conclusion is that the farm with the highest number of dairy cows implements an extensive feeding method, and sells its products at a prominent tourist location in rural areas has the best indicators and represents the best business model for small milk farms in the territory of Republika Srpska.
Ključne besede: Agriculture, Milk farming, Cheese production, Cost-Benefit Analysis, Real Options Approach, Monte Carlo Simulation
Objavljeno v DKUM: 13.03.2025; Ogledov: 0; Prenosov: 15
Celotno besedilo (7,79 MB)