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Categorization of Data Analytics Projects in Smart Manufacturing
No full textThe emergence of the Internet of Things and Industry 4.0 has transformed production processes, with data analytics and AI playing key roles. Smart Manufacturing projects often appear ambiguous due to interconnected terms. Data analytics is foundational, involving specific goals, evaluation of current infrastructure, and small-scale pilot projects. Having a structured map tailored to Smart Manufacturing is invaluable for identifying an optimal starting point for data analytics projects. The primary objective is to provide a comprehensive overview of data analytics in the context of Smart Manufacturing and to answer the research question regarding identified categories and data analytics projects
Mapping Habitat Structures of Endangered Open Grassland Species (E. aurinia) Using a Biotope Classification Based on Very High-Resolution Imagery
Full text linkAnalyzing habitat conditions and mapping habitat structures are crucial for monitoring ecosystems and implementing effective conservation measures, especially in the context of declining open grassland ecosystems in Europe. The marsh fritillary (Euphydryas aurinia), an endangered butterfly species, depends heavily on specific habitat conditions found in these grasslands, making it vulnerable to environmental changes. To address this, we conducted a comprehensive habitat suitability analysis within the Hainich National Park in Thuringia, Germany, leveraging very high-resolution (VHR) airborne, red-green-blue (RGB), and color-infrared (CIR) remote sensing data and deep learning techniques. We generated habitat suitability models (HSM) to gain insights into the spatial factors influencing the occurrence of E. aurinia and to predict potential habitat suitability for the whole study site. Through a deep learning classification technique, we conducted biotope mapping and generated fine-scale spatial variables to model habitat suitability. By employing various modeling techniques, including Generalized Additive Models (GAM), Generalized Linear Models (GLM), and Random Forest (RF), we assessed the influence of different modeling parameters and pseudo-absence (PA) data generation on model performance. The biotope mapping achieved an overall accuracy of 81.8%, while the subsequent HSMs yielded accuracies ranging from 0.69 to 0.75, with RF showing slightly better performance. The models agree that homogeneous grasslands, paths, hedges, and areas with dense bush encroachment are unsuitable habitats, but they differ in their identification of high-suitability areas. Shrub proximity and density were identified as important factors influencing the occurrence of E. aurinia. Our findings underscore the critical role of human intervention in preserving habitat suitability, particularly in mitigating the adverse effects of natural succession dominated by shrubs and trees. Furthermore, our approach demonstrates the potential of VHR remote sensing data in mapping small-scale butterfly habitats, offering applicability to habitat mapping for various other species
Direct Computation of Higher Order Mode Components from Successively Linearized Geometrically Nonlinear Beam Theory
Full text linkThe extended modal approach is a simplified nonlinear method for the steady and unsteady computation of geometrically nonlinear structural deflections that was developed for loads and flight dynamics analyses of highly flexible aircraft. Compared to the classical modal approach, which is based on the superposition of normal modes, the extensions include higher order stiffness terms and higher order mode components to account for nonlinearities both in the load displacement relationships (cubic stiffness terms) as well as in the geometrically nonlinear displacement field (large deflections and rotations of structural components). These extensions make the method particularly suitable for aeroelastic applications involving highly flexible structures and nonlinearities due to nonconservative loads. In this work, a new approach for the calculation of the higher order mode components is proposed which uses the nonlinear relationships between strains (or curvatures) and displacements from a geometrically nonlinear beam theory. The idea is to take the curvatures of a particular structural mode and to integrate them using successively linearized compatibility equations to compute the higher order mode components. In his way, the higher order mode components are directly obtained, and the costly pre-processing step with a series of nonlinear static simulations is circumvented
Efficient Nonlinear Dynamic Analyses of Aircraft Structural Components With Various Boundary Conditions Using the Koiter-Newton Model Reduction
Full text linkThe evolving designs and requirements of aircraft structural components has recently created an increased interest in application of nonlinear modelling techniques. While the finite element (FE) methods already incorporate the necessary mechanics to model nonlinear behavior in structures, a major drawback is the considerably higher computation cost in comparison to the linear counterparts. Reduced order modelling (ROM) techniques offer a solution to counter this limitation. The work presented here is focused on the Koiter-Newton (K-N) model reduction technique which is based on a cubically nonlinear mechanical model. The K-N method utilizes existing FE models as a starting point to generate equivalent ROM parameters and thus, can be applied to obtain ROMs for generic structures. The model validity is assessed by conducting nonlinear dynamic analyses of two models with different boundary conditions. Nonlinear frequency response analyses are conducted to demonstrate hardening effects in both the test cases. Comparisons to full FE analyses show significant reduction in computational times
Experimental Validation of Decentralized Control for Gust Load Alleviation in a Wind Tunnel
Full text linkThe concept of decentralized control of ailerons for gust load alleviation was validated in a wind tunnel experiment. Decentralized control uses remote electronic units near the ailerons, which measure the acceleration of the wing and are able to run a local control law. The proposed control laws are using the acceleration as an input to calculate aileron deflections to counteract the gust-induced accelerations of the wing. Using a model of the wing in the wind tunnel, these local control laws were designed and optimized according to defined quality criteria. The experimental results show a high reduction of the accelerations by 33.6 %, which in turn leads to a reduction of the wing root bending moment by 34.2 %. Thereby proving the concept of decentralized control from a flight physical point of view and demonstrating its effectiveness in alleviating gust loads
Beyond the Random Forest: How Deep Learning for Remote Sensing Monitors Trees
No full textData to track our planet's health has increased to hundreds of petabytes in volume through the ever increasing number and ever decreasing costs to deploy drones and satellites. National programs by USGS, USDA, NASA, ESA, and the European Commission make freely available multi- and hyperspectral imagery. However, intelligent manual inspection of these geospatial data and maps by human eye is impossible. Recent advances in deep neural networks dramatically boosted the accuracy and diversity of computer vision applications to the point that those achievements become practical tools at our fingertip.
My presentation invites you onto a journey of my research exploring deep learning for aerial photos and laser scans in order to generate an inventory of urban forests in New York City [1], discover ancient agriculture in the Negev desert of Israel [2], and an attempt to estimate global biomass [3]. I hope to spark fruitful discussions with peers from ecology on how to utilize AI for environmental good to protect and treasure our green spaces.
[1] https://elib.dlr.de/187233
[2] https://elib.dlr.de/190710
[3] https://elib.dlr.de/19150
Fusion of geospatial information from remote sensing and social media to prioritise rapid response actions in case of floods
Full text linkEfficiently managing complex disasters relies on having a comprehensive understanding of the situation at hand. Immediately after a disaster strikes, it is crucial to quickly identify the most impacted areas to guide rapid response efforts and prioritise resource allocation effectively. Utilising early-stage estimations of impacted regions, derived from indicators such as building distribution, hazard zones or geo-social media reports, can aid in planning data collection initiatives to enhance situational awareness. Consequently, there is a need to improve the availability and accuracy of early-stage impact indicators and to integrate them into a coherent spatial and temporal analysis framework that enables identification of disaster-affected areas. In this study, a method is proposed that is tailored to quickly identifying disaster hotspots, especially in situations where detailed damage assessments or very high-resolution satellite images are not readily available. The approach leverages the H3 discrete global grid system and uses a log-linear pooling method coupled with an unsupervised hyperparameter optimization routine to fuse information on flood hazard extracted from medium-resolution satellite images with disaster-related data from Twitter and freely available supplementary geospatial data on exposed assets. The performance of the method is evaluated by comparing its outcomes against detailed damage assessments conducted during five real-world flood disasters. The results indicate that it is possible to determine the areas most affected by a flood solely based on readily available proxy information. Code and test data are available from: https://github.com/MWieland/h3h
Mars in Short: Past and Present Geology and Climate - Chapter 2
No full textMars is easily observed in the sky due to its reddish colour and has therefore been the target of inspiration since the early history of mankind. It is the second smallest planet in the Solar System (diameter: ca. 6790 km), and the fourth and farthest terrestrial planet from the Sun (230 million km). Mars differs from Earth regarding several parameters (Table 2.1). Mars has been exposed to dramatic geological processes throughout its history. Today, the surface of Mars is characterized by extreme contrasts, such as the Martian dichotomy between the northern and the southern hemisphere, huge canyons, and some of the highest volcanoes in the Solar system (Fig. 2.1). The first map of the surface of Mars was drawn in 1840 by Johann Heinrich von Mädler. Since then, many improvements have been made, based on data from space missions to Mars. Now Mars has become the target of what may become one of mankind’s most advanced technical and scientific endeavours: the first human mission to another planet in the Solar System. Knowledge about its present and past geology and environment is crucial for this endeavour and our understanding of how Mars was formed, how it developed throughout time, whether a form of life has ever existed on Mars
Open Testbed Vessel - Reusable and generic test carrier architecture for maritime testbeds
Full text linkMaritime test carriers are widely used for testing of assistance systems and autonomy systems on vessels. But in general, these test carriers are designed to test one System under Test. Especially with advancing development, a change in necessary functionalities may arise. This could include the introduction of novel sensors, actuators, navigation systems or other System under Test, which requires an extensible test carrier. To ensure extensibility and reusability, a test carrier system architecture is needed, that allows the integration of different Systems under Test, sensors and actuators taking also into account the complexity of these Systems of Systems. This paper presents a test carrier system architecture, which fulfills the requirements of reusability, portability and extensibility based on a zone-oriented Electrical/Electronic architecture from the automotive domain. The presented test carrier system architecture uses a central gateway in combination with zone domain controllers, governing specific functional zones of the test carrier. Furthermore, the integration and placement of Systems under Test inside the test carrier system architecture is identified. Finally, the test carrier system architecture is applied on two test carriers of a physical testbed and evaluated through three different use cases including an additional latency evaluation