Responses of CH, NO, and NH emissions to different slurry pH values of 5.5-10.0: Characteristics and mechanisms.

Animal slurry storage is a significant source of greenhouse gas (GHG) and ammonia (NH) emissions. pH is a basic but key factor that could pose great influence on gas emissions, but the simultaneous evaluation of its influence on GHG and NH emissions and the understanding of its underlying mechanism are not enough. In this work, pH was adjusted between 5.

Probabilistic Structural Model Updating with Modal Flexibility Using a Modified Firefly Algorithm.

Structural model updating is one of the most important steps in structural health monitoring, which can achieve high-precision matching between finite element models and actual engineering structures. In this study, a Bayesian model updating method with modal flexibility was presented, where a modified heuristic optimization algorithm named modified Nelder-Mead firefly algorithm (m-NMFA) was proposed to find the most probable values (MPV) of model parameters for the maximum a posteriori probability (MAP) estimate. The proposed m-NMFA was compared to the original firefly algorithm (FA), the genetic algorithm (GA), and the particle swarm algorithm (PSO) through the numerical illustrative examples of 18 benchmark functions and a twelve-story shear frame model.

Responses of soil respiration and microbial community structure to fertilizer and irrigation regimes over 2 years in temperate vineyards in North China.

Fertilizer and irrigation regimes can profoundly affect soil carbon (C) emissions, which influence soil organic carbon (SOC) storage. However, information regarding the effects of fertilizer and irrigation management on the components of soil respiration (Rs) and the underlying microbial community characteristics in vineyard ecosystems remains limited. Therefore, a 2-year field experiment was conducted in a wine-grape vineyard (WGV) and a table-grape vineyard (TGV).

Structural Model Identification Using a Modified Electromagnetism-Like Mechanism Algorithm.

A modified electromagnetism-like mechanism (EM) algorithm is proposed to identify structural model parameters using modal data. EM is a heuristic algorithm, which utilizes an attraction-repulsion mechanism to move the sample points towards the optimal solution. In order to improve the performance of original algorithm, a new local search strategy, new charge and force calculation formulas, new particle movement and updating rules are proposed.

Probabilistic Updating of Structural Models for Damage Assessment Using Approximate Bayesian Computation.

A novel probabilistic approach for model updating based on approximate Bayesian computation with subset simulation (ABC-SubSim) is proposed for damage assessment of structures using modal data. The ABC-SubSim is a likelihood-free Bayesian approach in which the explicit expression of likelihood function is avoided and the posterior samples of model parameters are obtained using the technique of subset simulation. The novel contributions of this paper are on three fronts: one is the introduction of some new stopping criteria to find an appropriate tolerance level for the metric used in the ABC-SubSim; the second one is the employment of a hybrid optimization scheme to find finer optimal values for the model parameters; and the last one is the adoption of an iterative approach to determine the optimal weighting factors related to the residuals of modal frequency and mode shape in the metric.