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- Automated Modal Analysis for Tracking Structural Change during Construction and Operation Phases (1)
- Electrochemical impedance spectra (1)
- Ethyl (diethoxymethyl)phosphinate derivatives (1)
- Flame retardant (1)
- Flexible polyurethane foam (1)
- Gas diffusion layers (1)
- HT-PEFC (1)
- Lattice Boltzmann simulation (1)
- Phosphoric acid (1)
- Structure-flame retardancy relationship (1)
Organisationseinheit der BAM
Phosphoric acid as the electrolyte in high-temperature polymer electrolyte membrane fuel cell plays an essential role in ist performance and lifetime. Maldistribution of phosphoric acid in the catalyst layer (CL) may result in performance degradation. In the present study, pore-scale simulations were carried out to investigate phosphoric acid’s multiphase flow in a cathode CL. A reconstructed CL model was built using focused ion beam-SEM images, where distributions of pore, carbon support, binder, and catalyst particles can be identified. The multi-relaxation time lattice Boltzmann method was employed to simulate phosphoric Acid invading and leaching from the membrane into the CL during the membrane electrode assembly fabrication process. The predicted redistribution of phosphoric acid indicates that phosphoric acid of low viscosity or low wettability is prone to leaching into the CL.
The effective transport properties and the active electrochemical active surface area (ECSA) were computed using a pore-scale model. They were subsequently used in a macroscopic model to evaluate the cell performance. A parametric study shows that cell performance first increases with increasing phosphoric acid content due to the increase of ECSA. However, further increasing phosphoric acid content results in performance degradation due to mass transfer limitation caused by acid flooding.
Three novel liquid ethyl (diethoxymethyl)phosphinate derivatives (EDPs) were synthesized and incorporated into flexible polyurethane foams (FPUFs). The flame retardancy of FPUFs were evaluated by limiting oxygen index (LOI), vertical burning and cone calorimetry tests, and the results indicated the structure-flame retardancy relationship of EDPs. Among these EDPs, P-(diethoxymethyl)-N-phenylphosphonamidate (EDPPA) exhibited the best flame retardant effect, methyl 3-((diethoxymethyl)(ethoxy)phosphoryl)propanoate (EDPMA) the second, and ethyl phenyl (di-ethoxymethyl)phosphonate (EDPPO) the worst. When the incorporation of EDPPA was 10 wt%, the FPUFs could self-extinguish and pass the vertical burning test. Meanwhile, the LOI value of FPUF-PA increased to 23.6% with 20 wt% loading of flame retardant. According to the investigation of volatiles during the thermal degradation of FPUFs and the morphologies of char residues after cone test, we inferred the pos- sible flame retardant mechanism. The results indicated that EDPs could release phosphorus-containing compounds in the gas phase, which would generate phosphorus-containing radicals and play the role of radical scavenger. In the condensed phase, EDPs can promote the formation of dense, intact and thermal stably char layer on the surface of FPUFs. Moreover, we found that the structure influence on flame retardancy was attributed to the atoms linked to the central phosphorus. Our results indicate that these EDPs are promising flame retardants in FPUFs that can be applied to improve the flame retardancy of FPUFs in various practical applications.
Automated modal analysis for tracking structural change during construction and operation phases
(2019)
The automated modal analysis (AMA) technique has attracted significant interest over the last few years, because it can track variations in modal parameters and has the potential to detect structural changes. In this paper, an improved density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean the abnormal poles in a stabilization diagram. Moreover, the optimal system model order is also discussed to obtain more stable poles. A numerical Simulation and a full-scale experiment of an arch bridge are carried out to validate the effectiveness of the proposed algorithm. Subsequently, the continuous dynamic monitoring system of the bridge and the proposed algorithm are implemented to track the structural changes during the construction phase. Finally, the artificial neural network (ANN) is used to remove the temperature effect on modal frequencies so that a health index can be constructed under operational conditions.