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• Integrated optimization model for biomass-based renewable hydrogen production systems is proposed. • We calculate and evaluate the biomass utilization potential of a certain area. • We made predictions through chemical reaction kinetics and thermodynamic models. • Inventory model is embedded in it to decide the optimal production and operation management. • The effectiveness of the model was tested through a mixed biomass project in Sichuan Province, China. In this study, we propose a novel optimization method for designing and operating various types of biomass-based renewable hydrogen production systems. To this end, we considered the coupling of multiple biomass hybrid utilization processes for hydrogen production. First, we calculated and evaluated the biomass utilization potential of a given area. Second, we predicted the biomass gasification products using chemical reaction kinetics and thermodynamic models. Finally, we determined the optimal annual total cost of the hydrogen production supply chain by optimizing the microscopic operation of the biomass gasification plant. Through the proposed method, it is possible to effectively conduct a comprehensive assessment of regional biomass material hydrogen production; moreover, the optimal design of the biomass hydrogen production supply chain can also be determined based on the availability of biomass and hydrogen demand. More precisely, the logistics operations under fluctuating demand conditions were realized, enabling strategic decision-making for planning a biomass hydrogen production system. To validate the model, a case study analysis of biomass hydrogen production, to be launched in Sichuan Province, China, is presented. [ABSTRACT FROM AUTHOR]

Landslide modeling based on seismic signal characteristics is an effective method to study landslide evolution. The scientific challenge lies in how to systematically characterize and reconstruct the entire landslide evolution process using the recorded seismic data. We selected the 2017 "6.24" Xinmo landslide as a case study. Empirical mode decomposition (EMD) is used to analyze the seismic signals from 14 seismic stations near the landslide area. Numerical simulations using two-dimensional discrete element methods (DEM) are performed to simulate landslide dynamics using the calculated kinetic energy profile. After analyzing the short-time Fourier transform (STFT) and fast Fourier transform (FFT) characteristics of the signal, the landslide process is reconstructed and compared with the DEM simulation. The landslide process is observed to consist of a stationary stage, slipping stage, transition stage, entrainment-transportation stage, and a deposition stage. This is the first study that uses seismic signals to identify a transition stage, which is a feature that is difficult to constrain from field survey and analysis alone. Landslide development and movement in the transition stage are discussed considering the sedimentology of the study area. This study provides improved theoretical guidance for the reconstruction and characterization of landslide processes by seismic signals. • Seismic signals generated by the Xinmo landslide (Sichuan - China) were analyzed. • 5 stages of landslide were recognized from spectral variations of seismic recording. • One transition stage was identified between first slipping and entrainment stage. • Discrete element simulations supported the landslide process reconstruction. [ABSTRACT FROM AUTHOR]