TY - THES A1 - Münch, Justin T1 - Mehrwert von Methoden des Maschinellen Lernens für die simulative Bewertung der Versorgungssicherheit mit Elektrizität N2 - Politik und Wirtschaft sind auf eine fundierte, schnelle und flexible Bewertung der Ver-sorgungssicherheit mit Elektrizität als Grundlage strategischer Entscheidungen angewiesen. Dazu werden komplexe probabilistische Simulationsmodelle unter Einbeziehung einer hohen Anzahl möglicher Zukunftsszenarien verwendet. Allerdings schränken die langen Rechenlaufzeiten von mehreren Stunden pro Szenario die Analysetiefe ein. Zudem werden die Analysen durch die Prognose der zeitlich aufgelösten zukünftigen Randbedingungen erschwert. Die vorliegende Arbeit zeigt, dass sich mit Methoden aus dem Bereich des Maschinellen Lernens (ML) in Kombination mit angepassten Methoden des Design of Experiments die Kennzahlen der Versorgungssicherheit mit Elektrizität aus einem komplexen Simulationsmodell auf Basis rekursiver Faltungen sehr gut approximieren lassen. Die Zeitreduktion im Vergleich zum nativen Simulationsmodell ist sehr hoch, bei gleichzeitig hoher Genauigkeit. Auch im Bereich der Prognose zeitlich aufgelöster Randbedingungen demonstrieren die Ergebnisse ein erhebliches Verbesserungspotenzial von ML-Methoden im Vergleich zu klassischen Verfahren. Zusammengefasst sind die untersuchten und vorgeschlagenen ML-Methoden in der Lage, die Versorgungssicherheit mit Elektrizität komplexitätsgerecht (tausende von Zukunftsszenarien) in praktikabel kurzer Zeit (weniger als eine Stunde) detailliert zu analysieren. N2 - Politics and economics rely on a well-founded, rapid and flexible assessment of electricity supply security as a basis for strategic decisions. Complex probabilistic simulation models incorporating a large number of possible future scenarios are used for this purpose. However, the long simulation runtimes of several hours per scenario limit the depth of analysis. In addition, the analyses are complicated by the forecasting of time-resolved future boundary conditions. This work demonstrates that machine learning (ML) methods, combined with adapted Design of Experiments (DoE) techniques, allow for a highly accurate approximation of electricity supply security metrics obtained from a complex simulation model based on recursive convolutions. The time reduction compared to the native simulation model is very high, while maintaining a high degree of accuracy. In the area of forecasting time-resolved boundary conditions, the results also demonstrate that ML methods offer considerable potential for improvement over classical methods. In summary, the investigated and proposed ML methods are capable of performing a detailed analysis of the security of electricity supply that is commensurate with its complexity (thousands of future scenarios) within a practical amount of time (less than an hour). T3 - Promotionskolleg NRW mit Hochschule Düsseldorf - 1 KW - Deep Learning KW - Machine Learning KW - Artificial neural networks KW - Metamodeling KW - Surrogate modeling KW - Probabilistic simulation KW - Regression KW - Security of electricity supply KW - times series forecasting Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-58306 N1 - Bochum, Dissertation, Promotionskolleg NRW mit Hochschule Düsseldorf PB - Hochschule Düsseldorf CY - Düsseldorf ER - TY - JOUR A1 - S, Kasiviswanathan A1 - Shajahan, Mohamed Iqbal A1 - R, Bharathiraja A1 - Murali, Arun Prasad A1 - Benim, Ali Cemal T1 - Comprehensive overview of phase change materials in electronics, building, and solar applications JF - Engineering Research Express N2 - Phase change materials (PCMs) are a viable way to improve energy efficiency and thermal control in a variety of sectors. With an emphasis on their function in thermal control, this review article offers an in-depth review of PCM applications in electronics, buildings and solar energy systems. PCMs are used in electronics to control device temperatures, which lowers the risk of overheating and increases operational efficiency by 10% to 25%. Through latent heat storage and release in reaction to temperature changes, PCMs are incorporated into walls, floors, and roofs in building applications to improve thermal comfort and cut energy use by 15% to 30%. By storing thermal energy for steady power generation, PCMs increase the dependability and efficiency of solar energy systems by 8%–20%. This review examines the basic ideas behind PCMs, assesses various PCM (such as organic, inorganic, and eutectic PCMs), and details about real-world applications in these energy management fields. Important issues are examined, such as material compatibility, cost-effectiveness, and long-term stability. In order to maximize performance in these crucial applications, the conclusion emphasizes the need for improvements in cost-effective PCM formulations for the improved thermal conductivity (0.2–0.7 W m−1·K−1), and adaptive control systems. KW - Energieeffizienz KW - Temperaturregelung KW - Elektronik KW - Latentwärmespeicher KW - Sonnenenergie Y1 - 2026 U6 - https://doi.org/10.1088/2631-8695/ae342a SN - 2631-8695 VL - 8 IS - 3 PB - IOP Publishing ER - TY - CHAP A1 - Reich, Marius A1 - Rathjen, Patrick A1 - Adam, Mario ED - Henrik, Lund ED - Brain Vad, Mathiesen ED - Østergaard, Poul Alberg ED - Thellufsen, Jakob Zinck ED - Brodersen, Hans Jørgen T1 - Precomputed ML Surrogates for Energy System Design: Methodology and In-Depth Evaluation T2 - Book of Abstracts 2025: 11th International Conference on Smart Energy Systems, 16-17 September 2025. Copenhagen KW - SmartPrior KW - Energy supply systems KW - Design Optimization KW - Metamodeling KW - Time Series Data Y1 - 2025 UR - https://vbn.aau.dk/ws/portalfiles/portal/796346412/SESAAU2025_Book_of_Abstracts.pdf PB - Aalborg University CY - Aalborg ER - TY - CHAP A1 - Reich, Marius A1 - Patrick, Rathjen A1 - Adam, Mario ED - Lund, Henrik ED - Mathiesen, Brian Vad ED - Østergaard, Poul Alberg ED - Thellufsen, Jakob Zinck ED - Brodersen, Hans Jørgen T1 - Harnessing Machine Learning for Rapid Optimization: Integration of Time Series Data into Prior Approximation of Energy System Simulations T2 - Book of Abstracts :10th International Conference on Smart Energy Systems KW - SmartPrior KW - Energy supply systems KW - Rule based simulation KW - Design Optimization KW - Metamodeling KW - Time Series Data Y1 - 2024 UR - https://vbn.aau.dk/ws/portalfiles/portal/749867139/SESAAU2024_Book_of_Abstracts.pdf PB - Aalborg University CY - Aalborg ER - TY - CHAP A1 - Reich, Marius A1 - Prusas, Benedikt A1 - Adam, Mario ED - Lund, Henrik ED - Mathiesen, Brian Vad ED - Østergaard, Paul Alberg ED - Brodersen, Hans Jørgen T1 - Prior-Approximation of Rule-Based Energy System Simulation for Fast Design Optimization T2 - Book of Abstracts: 9th International Conference on Smart Energy Systems. Aalborg Universitet KW - Energy supply systems KW - Rule based simulation KW - Design Optimization KW - Metamodeling KW - SmartPrior Y1 - 2023 UR - https://vbn.aau.dk/ws/portalfiles/portal/548360793/BoA-2023FINAL-2.pdf PB - Aalborg University CY - Aalborg ER - TY - CHAP A1 - Gottschald, Jonas A1 - Reich, Marius A1 - Adam, Mario ED - Lund, Henrik ED - Mathiesen, Brian Vad ED - Østergaard, Paul Alberg ED - Brodersen, Hans Jørgen T1 - Lessons Learned: On the Potentials and Challenges of a Model Predictive Controlled DHN Heat Supply T2 - Book of Abstracts: 9th International Conference on Smart Energy Systems. Aalborg Universitet KW - District Heating KW - Machine Learning KW - Model Predictive Control KW - Monitoring KW - BestHeatNet Y1 - 2023 UR - https://vbn.aau.dk/ws/portalfiles/portal/548360793/BoA-2023FINAL-2.pdf SP - 87 EP - 87 PB - Aalborg University CY - Aalborg ER - TY - INPR A1 - Deckert, Carsten A1 - Schomaker, Rahel M. A1 - Grasmik, Jeanna T1 - Universalism and Innovation: The Influence of Impartiality and Inclusiveness on National Innovativeness T2 - Queios N2 - The innovative capacity of a country is a key factor in its economic development. While classical approaches primarily emphasize technological and economic aspects, cultural and moral influences are increasingly coming into focus in research. In particular, the treatment of out-groups and the intensity of in-group preferences play a crucial role, as expressed in the societal contrast between social cohesion and individual freedom. A central aspect of this debate is the moral dimension, particularly the tension between universalism, relativism, and particularism. This study examines the impact of universalism on a country's innovativeness by situating the concept within cultural theory and analyzing it empirically. The findings provide new insights into the relationship between cultural values and innovation potential with regard to moral capital in a society. Y1 - 2026 U6 - https://doi.org/10.32388/KNI4FN PB - Qeios Ltd ER - TY - GEN T1 - 1045 - Vierte Satzung zur Änderung der Prüfungsordnung für den Masterstudiengang „Umweltingenieurwesen“ an der Hochschule Düsseldorf vom 18.02.2026 N2 - Aufgrund der §§ 2 Abs. 4, 64 Abs. 1 des Gesetzes über die Hochschulen des Landes Nordrhein-Westfalen (Hochschulgesetz - HG) vom 16.09.2014 (GV. NRW. S. 547) in der aktuell gültigen Fassung hat die Hochschule Düsseldorf die folgende Ordnung als Satzung erlassen. T3 - Amtliche Mitteilungen : Verkündungsblatt der Hochschule Düsseldorf - 1045 KW - Amtliche Mitteilungen Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-60857 CY - Düsseldorf ER - TY - GEN T1 - 1044 - Erste Satzung zur Änderung der Prüfungsordnung für den Bachelorstudiengang Haus-, Energie- und Anlagentechnik (HEAT) an der Hochschule Düsseldorf vom 18.02.2026 N2 - Aufgrund der §§ 2 Abs. 4, 64 Abs. 1 des Gesetzes über die Hochschulen des Landes Nordrhein-Westfalen (Hochschulgesetz - HG) vom 16.09.2014 (GV. NRW. S. 547) in der aktuell gültigen Fassung hat die Hochschule Düsseldorf die folgende Ordnung als Satzung erlassen. T3 - Amtliche Mitteilungen : Verkündungsblatt der Hochschule Düsseldorf - 1044 KW - Amtliche Mitteilungen Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-60846 CY - Düsseldorf ER - TY - JOUR A1 - Bergmann, Marie A1 - Haddad-Thoelke, Pascale A1 - Jeong, Haeran A1 - Kappeler, Ron A1 - Altug, Hicran A1 - Oberwinster, Lukas A1 - Boogaard, Hanna A1 - Pohl, Tobias A1 - Soppa, Vanessa A1 - Ogurtsova, Katherine A1 - Joss, Meltem Kutlar A1 - Andersen, Zorana Jovanovic A1 - Hoffmann, Barbara T1 - Systematic review and meta-analysis on the health effects of long-term exposure to ultrafine particles JF - European Respiratory Review N2 - Background Ultrafine particles (≤100 nm diameter) may have a higher toxicity than larger particles but are still not regulated nor part of routine air pollution monitoring. So far, health effects of long-term exposure to ambient ultrafine particles are not well understood, owing to a lack of exposure data and epidemiological studies. Methods We conducted a systematic review and meta-analysis on the health effects of long-term exposure to ultrafine particles, including studies published until December 2024. A meta-analysis was conducted for outcomes with at least four available effect estimates. Confidence in the body of evidence was evaluated using the Office of Health Assessment and Translation method. Results We identified 85 studies investigating various mortality, morbidity and subclinical outcomes. In meta-analyses of single-pollutant models, we found positive associations with natural mortality (hazard ratio 1.06, 95% CI 1.04–1.08) and C-reactive protein (10.14% increase (95% CI −0.51–21.99%) per 10 000 pt·cm−3 increase in long-term exposure to ultrafine particles, with low and inadequate levels of evidence, respectively. The remaining studies revealed overall limited evidence for adverse effects on a wide range of outcomes. Less than half of the studies adjusted for co-pollutants. Conclusion The evidence base on long-term health effects of ultrafine particles has increased substantially in the past decade, while the overall evidence for independent effects of long-term ultrafine particle exposure remains inadequate to low. More studies are needed to draw firm conclusions about the independent adverse effects of long-term ultrafine particles on various health end-points, with a special focus on the influence of co-pollutant adjustment. KW - Luftreinhaltung KW - Schadstoffbelastung KW - Luftverunreinigender Stoff KW - Feinstaub KW - Auswirkung Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-60272 SN - 1600-0617 VL - 35 IS - 179 PB - European Respiratory Society ER -