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Prevailing Climate Patterns for Concurrent High Temperature and Low Precipitation Days in Canada
No full textIn this work, we evaluated the changing frequency of concurrent daily High Temperature and Low Precipitation (HTLP) and its relationship with large-scale climate patterns across Canada. Our analysis showed a significant increase (up to 3 days/decade) in the Canadian Arctic and southern regions of British Columbia and an insignificant decrease in HTLP frequency in the Prairies of Saskatchewan and Manitoba during 1979–2018. We examined ten large-scale climate patterns influencing precipitation and temperature in Canada. Among these, four climate indices (the East Pacific-North Pacific Pattern, North Atlantic Oscillation, Oceanic Niño Index, and East Atlantic Pattern) were noted as significant influencers of HTLP frequency, ranked in descending order of influence. Our research holds significance in explaining the spatial dynamics of HTLP days and the role of large-scale climate patterns therein, providing valuable insights for future research on heatwaves and droughts, mitigation efforts, and policy changes tailored to vulnerable regions
SysML4Sec – methodology for security modeling in the context of large‐scale product development with multiple design levels
No full textIncreasing functionalities and the rising complexity of aircraft systems used by flight and cabin crews, passengers, maintenance staff, and other stakeholders necessitate a reconsideration of system development methodologies. This paper presents SysML4Sec, a model‐based security engineering method that integrates the systems engineering process (SEP) with the security engineering process (SecEP). Both processes operate concurrently and interactively within the same system model across all development levels. We detail SysML4Sec for model‐based security engineering using a consistent SysML approach and demonstrate SEP‐SecEP interactions in developing a passenger seat connectivity function with the SysML4Sec supporting ‘CATIA Magic Systems of Systems Architect’ tool. The ‘Magic Systems of Systems Architect’ tool provides a single source of truth where a system and security engineers could collaborate to design the system architecture and the associated preliminary security assessments as per the DO 326A aviation standard. It enables to define Assets to be protected, the Threat Conditions (TC), the Threat Scenarios (TS) and Security Measures (SM) which are specified in terms of effectiveness to reduce the risk
Port-Hamiltonian modeling of rigid multibody systems
No full textWe employ a port-Hamiltonian approach to model nonlinear rigid multibody systems subject to both position and velocity constraints. Our formulation accommodates Cartesian and redundant coordinates, respectively, and captures kinematic as well as gyroscopic effects. The resulting equations take the form of nonlinear differential-algebraic equations that inherently preserve an energy balance. We show that the proposed class is closed under interconnection, and we provide several examples to illustrate the theory
Lithium-ion battery degradation forecasting using data-driven time series models
No full textThe maritime industry faces significant challenges as it adapts from a major carbon emitter to a low-emission sector, intending to eventually achieve zero emissions. This transition requires innovative solutions for both new and old vessels, lithium-ion batteries show promise in achieving these goals. Battery management systems improve reliability and safety by monitoring voltage, current, and temperature through sensors. These parameters enable the prediction of remaining usable life, allowing for prompt maintenance and replacement before failure occurs. Publicly accessible lithium battery datasets provide a useful starting point for predictive degradation model development. This study investigates time series modeling methodologies for lithium-ion battery degradation, utilizing NASA’s battery degradation dataset. Three models viz. Autoregressive, Autoregressive Integrated Moving Average, and its extension using seasonality parameters were developed. They were tested with four train/test ratios to predict the remaining useful life values and assess the accuracy of the predicted degradation curve against experimental results. From the results, it was observed that the Autoregressive Integrated Moving Average model had the least combined average Root Mean Square Error values, resulting in a good overall degradation curve fitting, whereas the Seasonal Autoregressive Integrated Moving Average model was able to predict the End of Life values more accurately
Intelligente digitale Methoden zur Verlängerung der Nutzungsdauer der Nibelungenbrücke
No full textIntelligent digital methods for extending the service life of the Nibelungen Bridge. To extend the service life of structures while maintaining their structural safety and functionality, effective monitoring and maintenance concepts are necessary. Within the scope of the Priority Program 2388 “Hundred Plus – Extending the Service Life of Complex Structures through Intelligent Digitalization” (SPP 100+), funded by the German Research Foundation (DFG), interdisciplinary methods including digital models, digital linkages, and condition indicators, have been investigated and validated on the Nibelungen Bridge in Worms. First, two structural health monitoring systems and their combination are described in detail, with particular focus on the fusion of accelerometer data. Subsequently, innovative data-driven simulation methods are presented to determine the complete temperature field of the bridge superstructure. In addition, various numerical solutions covering different element types and levels of detail are introduced. Finally, methods for managing knowledge about the bridge's condition are presented. The methods were developed relatively independently of each other and validated at the NBW. In the next step, all methods will be integrated to support the maintenance of the NBW.Um die Lebensdauer von Bauwerken unter Wahrung derer Standsicherheit und Funktionsfähigkeit zu verlängern, bedarf es effektiver Monitorings- sowie Instandhaltungskonzepte. Im Rahmen des von der Deutschen Forschungsgemeinschaft (DFG) geförderten Schwerpunktprogramms 2388 „Hundert plus – Verlängerung der Lebensdauer komplexer Baustrukturen durch intelligente Digitalisierung“ (kurz: SPP 100+) werden hierfür innovative, interdisziplinäre Methoden entwickelt und an der Nibelungenbrücke in Worms (NBW) validiert. Der vorliegende Beitrag stellt einige dieser neuentwickelten digitalen Methoden vor. Unter anderem umfasst dies zwei Systeme des Structural Health Monitoring (SHM) und deren zielorientierte Verknüpfung von mehreren Beschleunigungsmessdaten zur umfassenden Zustandsbewertung. Ergänzend werden innovative datenbasierte Simulationsmethoden zur Bestimmung des Temperaturfelds des Brückenüberbaus vorgestellt sowie mehrere Finite-Elemente-Modelle unterschiedlicher Detailtiefe präsentiert und miteinander verglichen. Abschließend werden innovative Methoden zum
Verwalten des Bestandswissens von Brückenbauwerken diskutiert. Die Methoden wurden überwiegend unabhängig voneinander entwickelt und an der NBW validiert. Im nächsten Schritt werden die Methoden integriert, um die Instandhaltung der NBW zu unterstützen
Generative adversarial networks for downscaling hourly precipitation in the canadian prairies
No full textDeveloping robust downscaling methods is essential for maximizing the applicability of climate model outputs in engineering design and climate mitigation, particularly in a changing climate. This study evaluates four deep learning model configurations for downscaling, focusing on their structure, functionality, and ability to capture localized convective events in the Canadian prairies. These model configurations aim to downscale coarse‐resolution climate model outputs (∼200 km) to the finer spatial resolution of regional climate models (∼50 km) for hourly precipitation. We introduce advanced metrics to assess the fidelity of precipitation downscaling, examining both marginal statistics and spatiotemporal dependencies. A U‐Network (UNET) captures spatial and temporal dependencies efficiently while three generative adversarial networks (GANs) configurations incorporate a critic network to enhance the realism of generated fields. The study also evaluates the effects of a thresholding layer to constrain precipitation values and a convolution long short‐term memory layer in the GAN critic to better capture temporal dependencies. Results show that all four model configurations effectively capture spatial dependencies, with the simplest GAN architecture outperforming others in preserving temporal dependencies. Latitudinal correlations are better preserved than longitudinal across all models. While UNET produces overly smoothed fields, GANs generate more detailed outputs when downscaling Coupled Model Intercomparison Project phase 6 projections. By optimizing deep learning models for this region, the study provides key insights into future precipitation trends, enabling the identification of localized storms. These findings are critical for improving infrastructure resilience across catchments in the prairies
The role of residual Hydrogen Peroxide for biological applications of polymeric N-oxides
No full textPolymers with N-oxide groups find applications in the biomedical field because they are highly hydrated in water, are considered to be nontoxic, and have stealth properties. Additional antimicrobial activity of polymeric N-oxides has also been reported, and it is currently unclear if this activity is a general feature of polymeric N-oxides or a special property of selected derivatives. N-Oxides are often prepared by oxidation of tertiary amines with hydrogen peroxide, which is notoriously difficult to remove from the resulting polymeric N-oxides. This study analyzes the role of residual oxidant in polymeric N-oxides for antimicrobial activity. Sensitive quantification reveals a significant release of hydrogen peroxide from oxidized polymers in solution and grafted on polyethylene or polyamide. The release of hydrogen peroxide from these polymers can lead to concentrations exceeding the minimum inhibitory concentrations (MICs) for Staphylococcus aureus and Escherichia coli. It can thus compromise microbiological assays. Rigorous removal of hydrogen peroxide leads to polymeric N-oxides with no antibacterial activity. Antibacterial effects of polymeric N-oxides against planktonic bacteria are primarily attributed to residual hydrogen peroxide, rather than to the intrinsic activity of the N-oxide functionality. Poly(N-oxide)-modified surfaces are therefore inert low-fouling materials with tunable, transient antibacterial functionality through controlled hydrogen peroxide release
Adsorption and recovery of the fumigant sulfuryl fluoride from air
No full textGlobal emissions of the fumigant and greenhouse gas sulfuryl fluoride (SO2F2) are rising, partly due to its unfiltered venting to the atmosphere after fumigation. Although European law demands emission control for SO2F2, this currently has little practical consequence, due to a lack of feasible separation methods for SO2F2 from air. An evaluation of the state-of-the-art shows that gas adsorption has a high potential to be practically implemented to mitigate SO2F2 emissions from fumigation. In a screening of different commercial adsorbents, the activated carbon Air CC 816 and the zeolite HiSiv 3000 indicated promising adsorption capacities for SO2F2, in dry and humid air. Thereby, this study presents the first comprehensive screening of commercial adsorbents
for SO2F2 recovery in general and the first report on SO2F2 adsorption on activated carbons and zeolites under humid conditions. Air CC 816 and HiSiv 3000 appear to primarily adsorb SO2F2 physically, allowing a recovery for possible reuse and omitting catalytic decomposition of SO2F2. For the zeolite HiSiv 3000, SO2F2 isotherms and mass transfer kinetics are measured and used to derive the adsorption enthalpy. On this zeolite, water and SO2F2 exhibit co-adsorption behaviour where water displaces SO2F2. Based on experimental characterization, a concept for an adsorptive recovery on HiSiv 3000 is designed, suggesting the suitability of hot gas desorption with additional external heat input, or steam desorption, for SO2F2 recovery. Finally, a first field test for SO2F2
adsorption after container fumigation already showed promising breakthrough times on HiSiv 3000
Environmental and chemical ageing of epoxy resins cured with bio-based amino acids
No full textTo achieve efficient and sustainable use of raw materials and energy, structures made of lightweight composites and thermosetting polymers are widely used. For sustainability, it is especially mandatory to extend the operating life of structures and components even under harsh conditions. Recently, the transformation from petrochemical to biobased resources is ongoing, to further improve sustainability. However, because of the more polar state of many biobased raw materials, it should be ensured, that they are not lacking in long-term use. In this study, specifically, the evolution of absorption and thermo-mechanical properties such as tensile strength or glass transition temperature (Tg) are analysed after ageing in demineralised water and chemicals (acetone, isopropanol, hydraulic oil) for L-arginine-cured epoxy compared to fully petro-based epoxies. The changes in properties due to physical ageing (molecular relaxation) and diffusion reveal a complex interplay between plasticization, physical ageing and possible chemical degradation. In particular, water absorption promotes strength-reducing plasticization and strength-increasing molecular relaxation on different time scales. This complex interplay is found for both types of epoxies and is in good agreement with what was previously found for classical epoxy. At the same time, the plasticizing effect of water also significantly reduces the Tg, as the water ingress into the molecular structure which increases chain distances and facilitates molecular movements. Furthermore, the resistance of the arginine-cured epoxy against different chemicals is particularly high and the diffusion retarded. Evidence for chemical degradation due to acetone diffusion is detected for both epoxy types via FTIR-analysis
High-temperature He+ Irradiation of Low-iron-bearing olivine: laboratory simulations of space weathering on Mercury
No full textThe surface of Mercury is highly space weathered, and the products of space weathering are different than on the Moon. Here we simulate the interaction of solar wind ions with the surface of Mercury by implanting low-iron-bearing (∼3 wt% Fe) olivine slices with 4 keV He⁺ ions both under ambient conditions and at 450 °C during the irradiation. The sample irradiated under ambient conditions shows a ∼140 nm thick partially amorphous layer on top of the grain with high concentrations of bubbles and cavities. However, the sample irradiated at 450 °C has a 110-140 nm thick polycrystalline layer with 1-5 nm sized nanoparticles of metallic iron and no bubbles or cavities. Mg atoms are preferentially sputtered from the ion-damaged layer present on the sample irradiated under ambient conditions, but no difference in composition is seen between the crystalline olivine and the ion-damaged layer in the sample irradiated at 450 °C. In addition, a thin amorphous film deposited on a micro-electromechanical systems-based chip is heated up to 1200 °C in situ inside a transmission electron microscope for a few milliseconds, and it produced nanoparticles of size 5-30 nm. Our results show that solar wind irradiation of low-iron-bearing olivine in the equatorial regions of Mercury will produce nanoparticles of iron whose sizes will be larger than that on the surface of the Moon and that the size will further increase during impacts of dust particles. Solar-wind-implanted He can diffuse out of regolith grains and can be a source of He observed in the exosphere of Mercury