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In der diesem Bericht zugrundeliegenden Diplomarbeit wurde das raumklimatische Verhalten der Muschelgrotte im Neuen Garten in Potsdam in Abhängigkeit von verschiedenen Lüftungsszenarien und unter Berücksichtigung der über den Fußboden eindiffundierenden Feuchte untersucht. Bevor das Raumklima untersucht und das hygrothermische Verhalten des Bauwerks mittels Simulationen bewertet wurde, wurden im Rahmen einer Bauaufnahme geotechnische und bauphysikalische Untersuchungen vorgenommen. In den hygrothermischen Gebäudesimulationen wurde der bauphysikalischen Interaktion zwischen dem Raumklima und dem feuchtebelasteten Fußboden besondere Aufmerksamkeit gewidmet. Abschließend wurden Möglichkeiten zur Reduzierung der Raumluft- und Oberflächenfeuchte sowie feuchtetechnischen Situation des Fußbodens herausgestellt.
This case study presents an innovative approach for explaining wildfire susceptibility through a web-based Geospatial eXplainable Artificial Intelligence (GeoXAI) system. By addressing limitations in traditional GeoXAI tools, such as the lack of geographical context for model predictions and local explanation, this system integrates state-of-the-art XAI methods with open-source geospatial technologies. Applied to the wildfire-prone regions of Berlin and Brandenburg, Germany, the system combines environmental, topographic, and meteorological features derived from high-resolution geospatial data for training a Random Forest (RF) model. The web-based GeoXAI system enables interactive exploration of the model output and its features, allowing users to visualize wildfire susceptibility, examine feature contributions, and correlate predictions with spatial patterns through post-hoc interpretability. By employing post-hoc explanation methods like SHAP, the system offers clear insights into model predictions by analyzing feature contributions after training, which helps users better understand AI-driven outcomes. Designed with a user-centered approach, the platform promotes trust and usability through transparent predictions, interactive geovisualizations, and local explanations, allowing users to navigate spatial data intuitively by exploring overviews, focusing on specific regions, and accessing detailed insights on demand. This work highlights the potential of combining GeoXAI with machine learning to improve decision-making in wildfire prevention and management.
Das ECF-Schienenbefestigungssystem wird bei festen Fahrbahnsystemen aus Stahl eingesetzt, bei denen ein Höhenausgleich durch aufgeschweißte und in Vergussmaterial eingebettete Gewindebolzen erfolgt. Unter außerplanmäßig hoher Beanspruchung können Teilabrisse oder Komplettabrisse dieser Bolzen auftreten. Zur Erkennung eines Abrisses unter laufendem Verkehr bedarf es einer robusten Prüfmethode.
Im Rahmen der vorliegenden Untersuchung wurde eine sensorbasierte, transiente Thermografie zur kontinuierlichen Überwachung der Aufschweißbolzen entwickelt und bewertet. Die Methode basiert auf der gezielten Erwärmung des Bolzenkopfes durch eine Heizpatrone und der Erfassung der resultierenden Wärmeausbreitung in der Grundplatte. Durch schrittweises Einschneiden der Bolzen konnten charakteristische Temperaturgradienten erzeugt werden, die eine differenzierte Identifikation von Teilabrissen und Ablösungen ermöglichen. Die methodische Einfachheit, Robustheit und Kosteneffizienz der eingesetzten Sensorik prädestinieren die Methode für diesen Anwendungsfall, weshalb sie auch aktuell an einer Eisenbahnüberführung eingesetzt wird.
In order to mitigate the risk posed by discharge of untreated wastewater and enhance the quality of wastewater prior to its release or reuse, it is important to adopt nature based treatment technologies. The current study was performed with objective to treat the primary treated sewage collected from a traditional Moving Bed Biofilm Reactor (MBBR) based Sewage treatment plant (STP) by using a two-stage French Type Vertical Flow Constructed Wetland (FVFCW). This pilot-scale study was undertaken in Banaras Hindu University Campus Varanasi, Uttar Pradesh. The wetland unit was a two-stage Vertical Flow Constructed Wetland system (VFCW) filled with two different filter media gravel & sand and planted with two different macrophytes Canna indica and Typha latifolia which was operated for Sustainable treatment of primary sewage. The VFCW was operated at three different Hydraulic loading rate (HLR) i.e. 1800, 2700, 3600 L/day for nine months. The VFCW performed for the treatment of different physicochemical parameters at given loading rates. The maximum removal efficiency of 72.37, 76.47, 100, 87.23, 41.41, 40.77 27.07% was recorded for COD, BOD, Turbidity, TSS, TDS, Phosphate and Ammonia respectively. Most of the Parameters showed maximum removal efficiency at HLR 2700 L/day. The study suggested that Experimental VFCW can be a sustainable solution for wastewater treatment in remote and rural areas of India as well small colonies due to its eco-friendly, cost-effective, low maintenance cost and lack of operational expertise.
In conventional constitutive models for granular materials, calibration involves estimating a few parameters within known mathematical expressions. In contrast, data-driven constitutive models couple the model structure and parameters. Addressing this fundamental difference, the development of constitutive models based on Physics-encoded Neural Networks (PeNN) is guided from the perspective of conventional model development, highlighting similarities and differences. The crucial physical information that influences PeNN is explained, and the incorporation of three key state boundary surfaces in pressure-porosity space - critical state, loosest state, and densest state - via physics-informed deep learning is detailed. Physics-informed calibration is performed using the augmented Lagrangian method; then, the calibrated models undergo extensive drained and undrained simulations. Results indicate that using only physical information from state boundary surfaces, without data within these boundaries, fails to calibrate data-driven models; thus, boundary surface information represents partial physical information. While combining partial physical information with reasonably distributed data can improve model development under limited experimental data, adding more partial physical information and data does not necessarily enhance the results. The finding aims to bridge the gap between conventional and data-driven constitutive models, hopefully increasing the reliability and interpretability of data-driven models.
Mit der Anmeldung des Patents DRP Nr. 197773 legte der Großherzogliche Zimmerermeister Otto Hetzer (1849 – 1911) im Jahr 1906 den Grundstein für die Entwicklung von Brettschichtholz wie es heute bekannt ist. Seine innovative Bauweise führte nicht nur zu einer Holzersparnis bei den Konstruktionen, sondern auch zu einer Entwicklung, ohne die der heutige Ingenieurholzbau nicht so leistungs- und konkurrenzfähig wäre. Mangelnde Erkenntnisse über historische Brettschichtholzkonstruktionen führen immer wieder zum Abriss dieser bedeutenden Bauwerke und Zeugnisse ingenieurtechnischer Schaffenskraft. Der vorliegende Beitrag dient zur Erweiterung des Wissenstands über historisches Brettschichtholz sowie naturbasierte Klebstoffe. Gleichfalls wird der Frage nachgegangen, wie historische Brettschichtholzkonstruktionen im Kontext der aktuellen Normung erhalten werden können und auf welche Besonderheiten im Zuge dessen geachtet werden muss.
Versuchsbasierte Entwicklung eines Bemessungskonzeptes zur Risssanierung in Massivlehmbauten (ERiMa)
(2025)
Das ERiMa-Projekt der Fachhochschule Potsdam verfolgt das Ziel, ein praxistaugliches Konzept für die Planung, Bemessung und Ausführung der statisch wirksamen Risssanierung von Massivlehmbauten zu entwickeln. Im Fokus steht die Übertragung des aus dem Mauerwerksbau etablierten Verfahrens der Rissvernadelung auf den Lehmbau, wobei die spezifischen materialtechnischen und baustatischen Eigenschaften von Lehm berücksichtigt werden. Im Rahmen des Forschungsprojekts werden Auszugsversuche durchgeführt, bei denen verschiedene Kombinationen von Untergründen, Ankerstäben und Mörteltypen untersucht werden. Darüber hinaus sind unter anderem noch Materialanalysen und FEM-Simulationen im Forschungsprogramm vorgesehen. Ziel ist es, die relevanten Einflussfaktoren zu identifizieren, um langfristig einen Tragfähigkeitsnachweis für die Rissvernadelung in Massivlehm unter Berücksichtigung der Stoffvielfalt von Lehmwänden zu entwickeln. Dadurch soll eine belastbare Nachweisführung für instandgesetzte Wandkonstruktionen aus Lehm gewährleistet werden.
In infrastructure planning and construction, modeling the subsoil and its associated uncertainty is a fundamental task of geotechnical engineers. However, probabilistic methods and tools for quantifying and displaying the uncertainty of the subsoil models are rarely used in practice where deterministic interpolation dominates. In digital planning using Building Information Modeling (BIM), the probabilistic approach supports creating a discipline model in which the uncertainties of the spatial layer structure are statistically quantified to evaluate the georisks in the design and execution of civil constructions. This article presents a case study using a combination of Sequential Gaussian Simulation (SGSIM) and Sequential Indicator Simulation (SISIM) to account for uncertainties in soil layer geometry. In a case study at the Munich Town Hall, a geostatistical approach is applied and validated based on 70 bore logs, whereby the probabilities for the occurrence of a particular layer are spatially quantified. The case study illustrates the methodology‘s great potential and benefits compared to the conventional deterministic approach based on interpolation procedures.
In the development of the industry, it is important to study the world experience in solving the above problems, to get acquainted with comprehensive measures aimed at solving the problems of transport infrastructure in various megacities of the world;
Further development of the highway network outside the city, reconstruction of their sizes and traffic sections according to the necessary technical parameters and corresponding prospective traffic intensity;
It is recommended to take into account the forecast data on the increase in the level of motorization of the population and the forecast of an increase in the number of cars in accordance with economic indicators in the street and road scheme of the general plan of the city;
Strict observance of the SNK rule 2.01.07-03 – "infrastructure first, then construction";
Development of the residential area in small residential areas, the length of the sides of which does not exceed 250 m between street intersections;
Construction of a residential area with small-sized residential blocks, the length of the side between the intersections of which does not exceed 250 m;
Development of scientifically based schemes for long-term planning of the street and road network of the city of Nukus, according to it, optimal planning of urban passenger transport, development of transport hubs to improve the city's links with external transit routes or organization based on experience.
In this research work, the technical condition of the road surface of the Khalka road in the city of Tashkent was studied on the basis of clear evidence, and the priority directions for solving problems in the transport system and the problems arising in the road surface of the city streets were studied in detail and we can draw general conclusions:
The main part of the street-road network of the Republic of Uzbekistan is made up of asphalt concrete roads, and almost 30% of them are under repair as of January 1, 2023.
98.5% of road surfaces in Tashkent are asphalt concrete, the remaining 1.5% are concrete, of which 38% of road surfaces are in need of repair as of January 1, 2023.
The maximum and minimum value of air temperature is of great importance in the design of city streets, and it is considered as the main factor in the correct selection of the type of pavement and operational activities.
The complex use of geotextile, geonet and geogrid innovative materials extends the service life of the road surface by 20% and reduces maintenance costs during the service period by 2%.
Silkouting of the pavement reduces the costs required for traditional maintenance by almost 17% and completely protects the pavement from external factors.
In order to extend the service life of the road surface and maintain the integrity of the surface in the event of an unexpected technical accident, it is advisable to use it in a complex manner together with all the measures mentioned above.