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Wpływ źródła inokulum i obróbki wstępnej na produkcję biowodoru w procesie fermentacji kwaśnej
No full textEffect of Recycling on the Environmental Impact of a High-Efficiency Photovoltaic Module Combining Space-Grade Solar Cells and Optical Micro-Tracking
No full textThe data presented in this study are available on request from the corresponding author. The data are not publicly available due to required consent of all project partners.This paper presents a life cycle assessment (LCA) analysis of a new, high-concentration photovoltaic (HCPV) technology developed as part of the HIPERION project of hybrid photovoltaics for efficiency record using an integrated optical technology. In the LCA calculations, the production stage of a full module was adopted as a functional unit. SimaPro version 9.00.49, the recent Ecoinvent database (3.8), and the IPCC 2021 GWP 100a environmental model were applied to perform the calculations. The environmental impact of the HCPV panel was determined for constructional data and for recycling of the main elements of the module. The results of the calculations show that recycling of PMMA, rubber, and electronic elements reduced the total carbon footprint by 17%, from 240 to 201 kg CO2-eq. The biggest environmental load was generated by the PV cells: 99.9 kg CO2eq., which corresponds to 49.8% (41.7% without recycling) of the total environmental load due to the large number of solar cells used in the construction. The emission of CO2 over a 25-year lifespan was determined from 17.1 to 23.4 g CO2-eq/kWh (20.4 to 27.9 without recycling), depending on the location. The energy payback time (EPBT) for the analyzed module is 0.87 and 1.19 years, depending on the location and the related insolation factors (Madrid: 470 kWh/m2, Lyon: 344 kWh/m2). The results of the calculations proved that the application of recycling and recovery methods for solar cells can improve the sustainability of the photovoltaic industry.This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 857775
Reconfigurable Interactive Environments for the Future of Work
No full textAutorka jest doktorantką Interdyscyplinarnej Szkoły Doktorskiej Politechniki Łódzkiej.Inevitable technological progress changes the very nature of work. On the one hand, more and more processes are subject to automation, and cooperating with a robotic workforce becomes an increasing challenge. On the other hand, society is increasingly embracing diversity, and there is an emerging social need to build diverse and inclusive spaces for work. My research attempts to answer these challenges by designing, implementing, and evaluating a novel type of work environment: an Interactive Reconfigurable Environment (IRE) IREs will leverage artificial intelligence techniques to dynamically adapt the physical surfaces around a user to provide an efficient, usable and inclusive interface. An adaptive work environment will support concentration and productivity while ensuring work safety in mixed environments - industrial, semi-automatic, automatic, and, above all, in situations of cooperation between people and autonomous agents.PhD is financed partially by the National Science Center through the Preludium-20 grant program (no. 2021/41/N/ST6/03676
3D Reconstruction of Non-Visible Surfaces of Objects from a Single Depth View – Comparative Study
No full textScene and object reconstruction is an important problem in robotics, in particular in planning collision-free trajectories or in object manipulation. This paper compares two strategies for the reconstruction of nonvisible parts of the object surface from a single RGB-D camera view. The first method, named DeepSDF predicts the Signed Distance Transform to the object surface for a given point in 3D space. The second method, named MirrorNet reconstructs the occluded objects’ parts by generating images from the other side of the observed object. Experiments performed with objects from the ShapeNet dataset, show that the view-dependent MirrorNet is faster and has smaller reconstruction errors in most categories
A Novel Learning Multi-Swarm Particle Swarm Optimization
No full textParticle swarm optimization (PSO) is one of the metaheuristic
optimization methods. Because of its many advantages, it is often used to
solve real-world engineering problems. However, in case of complex, multidimensional
tasks, PSO faces some problems related to premature convergence
and stagnation in local optima. To eliminate this inconveniences, in
this paper, a new learning multi-swarm particle swarm optimization method
(LMPSO) with local search operator has been proposed. The presented approach
was tested on a set of nonlinear functions and a CEC2015 test suite.
The obtained results were compared with other optimization methods
Ocena oddziaływania na środowisko. Teoria i praktyka
No full textŹródło BIP (https://politechnikalodzka.bip.gov.pl/dyscyplina-nauki-chemiczne-dr-hab/277853_dyscyplina-nauki-chemiczne.html
Modelowanie wpływu parametrów procesu na właściwości fizyko-chemiczne cząstek w suszeniu rozpryskowym
No full textŹródło BIP (https://politechnikalodzka.ssdip.bip.gov.pl/dyscyplina-inzynieria-chemiczna-dr-hab/277857_dyscyplina-inzynieria-chemiczna.html
Aktywność biologiczna związków fenolowych kaliny koralowej (Viburnum opu/us L.)
No full textŹródło BIP (https://politechnikalodzka.ssdip.bip.gov.pl/dyscyplina-technologia-zywnosci-i-zywienia-dr-hab/277862_dyscyplina-technologia-zywnosci-i-zywienia.html