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This paper introduces MorphoGen — an integrated reliability-based topology optimization and nonlinear finite element analysis system for 2D and 3D domains. The system’s key innovation is its seamless prototyping of scientific formulations for computational problems in topology optimization. Its layered and object-oriented architecture, based on the template method design pattern, facilitates effortless modifications of algorithms and the introduction of new types of finite elements, materials, and analyses. MorphoGen also offers flexible handling of objective functions and constraints during topological optimization, enhancing its adaptability. It empowers researchers and practitioners to explore a wide range of engineering challenges, fostering a deeper understanding of complex structural behaviors and efficient design solutions.There are many topology optimization software and open source codes, especially based on the classical SIMP method. Unlike these codes our package is freely distributed among users and since it is distributed on the MIT licence, which allows for its easy modification depending on the particular needs of the users. For this purpose, we use the topology optimization algorithm proposed for the first time in our previous paper (Blachowski et al., 2020). The algorithm is based on a fully stress design-based optimality criteria and can be applied for topology optimization of either linearly elastic and elastoplastic structures. Additionally, the novelty of the proposed system is related to its ability of solving optimal topology under various constraints such as displacement, stresses and fatigue in both deterministic and probabilistic cases.Another application are modular structures, which reduce design complexity and manufacturing costs as well as rapid reconfiguration. However, in the realm of structural optimization, modular systems are more challenging due to various: modes of operation of the modules and the stresses configurations. Moreover, this area of research is dramatically less explored.Thus the effectiveness of MorphoGen for structural engineering is demonstrated with examples of topological shape optimization of two Extremely Modular Systems: a planar robotic manipulator Arm-Z and spatial free-form ramp Truss-Z.

The goal of this study was to develop a model describing the relationship between the ground-displacement-caused tremors induced by underground mining, and mining and geological factors using the Random Forest Regression machine learning method. The Rudna mine (Poland) was selected as the research area, which is one of the largest deep copper ore mines in the world. The SAR Interferometry methods, Differential Interferometric Synthetic Aperture Radar (DInSAR) and Small Baseline Subset (SBAS), were used in the first case to detect line-of-sight (LOS) displacements, and in the second case to detect cumulative LOS displacements caused by mining tremors. The best-prediction LOS displacement model was characterized by R2 = 0.93 and RMSE = 5 mm, which proved the high effectiveness and a high degree of explanation of the variation of the dependent variable. The identified statistically significant driving variables included duration of exploitation, the area of the exploitation field, energy, goaf area, and the average depth of field exploitation. The results of the research indicate the great potential of the proposed solutions due to the availability of data (found in the resources of each mine), and the effectiveness of the methods used.

Due to an urgent need to reduce the fast-progressing climate changes, a rapid, standardized and replicable solution for the infrastructure restructuring of the heat demand coverage of buildings at the district and city levels must be developed. As more and more communities in Europe, especially in Germany, are obligated to have plans for coverage of the heat demand, city planners and energy agencies seek a tool that will help them to design the first drafts of heating network routes, which can supply whole districts and cities with renewable energy. ArcGIS Pro Tools like Least-Cost-Path Analysis (LCPA) and Closest Facility (CF) allow us to find the shortest and “cheapest” way between the heat source and heat consumers in the analyzed areas. Starting from the community level, through the district, county, voivodeship and whole-country levels, the replication of the methods for generating district heating (DH) network infrastructure can be achieved. The proposed LCPA- and CF-based methods help to design the most suitable and efficient DH networks in the analyzed areas. As only a few open-source data inputs, like street networks and building footprints, are needed, the methods can be implemented in all communities in the country of Poland. In this paper, one example of one community in Wroclaw county, called Siechnice, and its surroundings is presented.

The goal of this study was to develop a model describing the relationship between the ground-displacement-caused tremors induced by underground mining, and mining and geological factors using the Random Forest Regression machine learning method. The Rudna mine (Poland) was selected as the research area, which is one of the largest deep copper ore mines in the world. The SAR Interferometry methods, Differential Interferometric Synthetic Aperture Radar (DInSAR) and Small Baseline Subset (SBAS), were used in the first case to detect line-of-sight (LOS) displacements, and in the second case to detect cumulative LOS displacements caused by mining tremors. The best-prediction LOS displacement model was characterized by R2 = 0.93 and RMSE = 5 mm, which proved the high effectiveness and a high degree of explanation of the variation of the dependent variable. The identified statistically significant driving variables included duration of exploitation, the area of the exploitation field, energy, goaf area, and the average depth of field exploitation. The results of the research indicate the great potential of the proposed solutions due to the availability of data (found in the resources of each mine), and the effectiveness of the methods used. [ABSTRACT FROM AUTHOR]

Discontinuous deformations, such as sinkholes, pose significant challenges in post-mining areas due to their unpredictable nature and potential hazard to surface development and the safety of local communities. Therefore, monitoring the post-mining regions should be treated as a continuing task. This study addresses the ongoing problem of sinkhole formation in the former “Przyjaźń Narodów – Szyb Babina” (Babina) lignite mine located in the glaciotectonic region of Muskau Arch in western Poland. The research uses airborne and terrestrial laser scanning methods to identify and monitor discontinuous deformations, focusing on a newly discovered sinkhole. The methodology involves differential analysis of Digital Elevation Models (DEMs) and their derivatives obtained from airborne laser scanning (ALS) and periodic terrestrial laser scanning (TLS) measurements. The results of ALS DEM analysis allowed the successful identification of 75 confirmed sinkholes, the largest measuring 12.8 m in diameter and 4.8 m deep. Whereas, differential DEM analysis indicated new sinkholes that developed between 2011 and 2020 in the area of shallow underground mining. Two-year TLS monitoring of the new sinkhole showed no progression in its dimensions. However, localised erosion processes associated with water transport were detected. The study shows that sinkhole formation processes are active 5 decades after the end of mining and highlights the importance of continuous monitoring of post-mining areas with advanced laser scanning methodss. [ABSTRACT FROM AUTHOR]