Fatigue behavior and influence factor analysis of the structure subject to multiaxial random loading

The fatigue behavior of the structure under multiaxial random loading is studied in this paper. The influence of different parameters on the fatigue behavior is mainly investigated. Firstly, the theoretical analysis for the stress response of the structure under multiaxial random vibration is developed, and the relationship of the stress responses between multiaxial and sequentially applied uniaxial random vibration is obtained, which indicates that the potential failure modes will be different. Then, the experiments are conducted to compare the failure mode between uniaxial and multiaxial inputs (uncorrelated). As anticipated, the experimental results show significantly difference in the fatigue life, failure position and the way of crack propagation. Finally, the correlation between different axial input loads and its influence on the failure mode are investigated experimently. Based on the experiment, the relationship between the failure mode and the correlation coefficient as well as the phase of the input loads are also obtained

Eighteen-Year Farming Management Moderately Shapes the Soil Microbial Community Structure but Promotes Habitat-Specific Taxa

Soil microbes have critical influence on the productivity and sustainability of agricultural ecosystems, yet the magnitude and direction to which management practices affect the soil microbial community remain unclear. This work aimed to examine the impacts of three farming systems, conventional grain cropping (CON), organic grain cropping (ORG), and grain cropping-pasture rotation (ICL), on the soil microbial community structure and putative gene abundances of N transformations using high-throughput 16S rRNA gene and ITS sequencing approaches. Two additional systems, a forest plantation (PF) and an abandoned agricultural field subject to natural succession (SUC), were also included for better assessment of the soil microbial community in terms of variation scale and regulatory importance of management intensity vs. plant type. Farming systems significantly affected the biodiversity of soil fungi but not bacteria, with Shannon index being the lowest in ORG. Bacterial and fungal communities in three cropping systems clustered and separated from those in PF and SUC, suggesting that management practices as such played minor roles in shaping the soil microbial community compared to plant type (i.e., woody vs. herbaceous plants). However, management practices prominently regulated habitat-specific taxa. Lecanoromycetes, a class of Ascomycota accounted for ∼10% of total fungal population in ORG, but almost nil in the other four systems. ORG also enriched bacteria belonging to the phyla, Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, and Gemmatimonadetes. Further, PICRUSt predicted that N-cycle community compositions varied with farming systems; compared to CON, ORG and ICL were more divergent from PF and SUC. Soil pH, together with inorganic N, extractable organic C, and soil organic C:N ratio explained < 50% of the total variations in both bacterial and fungal communities. Our data indicates that while moderately affecting the overall structure of the soil microbial community, management practices, particularly fertilization and the source of N (synthetic vs. organic), were important in regulating the presence and abundance of habitat-specific taxa

One-time nitrogen fertilization shifts switchgrass soil microbiomes within a context of larger spatial and temporal variation

Soil microbiome responses to short-term nitrogen (N) inputs remain uncertain when compared with previous research that has focused on long-term fertilization responses. Here, we examined soil bacterial/archaeal and fungal communities pre- and post-N fertilization in an 8 year-old switchgrass field, in which twenty-four plots received N fertilization at three levels (0, 100, and 200 kg N ha-1 as NH4NO3) for the first time since planting. Soils were collected at two depths, 0–5 and 5–15 cm, for DNA extraction and amplicon sequencing of 16S rRNA genes and ITS regions for assessment of microbial community composition. Baseline assessments prior to fertilization revealed no significant pre-existing divergence in either bacterial/archaeal or fungal communities across plots. The one-time N fertilizations increased switchgrass yields and tissue N content, and the added N was nearly completely removed from the soil of fertilized plots by the end of the growing season. Both bacterial/archaeal and fungal communities showed large spatial (by depth) and temporal variation (by season) within each plot, accounting for 17 and 12–22% of the variation as calculated from the Sq. root of PERMANOVA tests for bacterial/archaeal and fungal community composition, respectively. While N fertilization effects accounted for only ~4% of overall variation, some specific microbial groups, including the bacterial genus Pseudonocardia and the fungal genus Archaeorhizomyces, were notably repressed by fertilization at 200 kg N ha-1. Bacterial groups varied with both depth in the soil profile and time of sampling, while temporal variability shaped the fungal community more significantly than vertical heterogeneity in the soil. These results suggest that short-term effects of N fertilization are significant but subtle, and other sources of variation will need to be carefully accounted for study designs including multiple intra-annual sampling dates, rather than one-time “snapshot” analyses that are common in the literature. Continued analyses of these trends over time with fertilization and management are needed to understand how these effects may persist or change over time

Critical transition of soil microbial diversity and composition triggered by plant rhizosphere effects

Over the years, microbial community composition in the rhizosphere has been extensively studied as the most fascinating topic in microbial ecology. In general, plants affect soil microbiota through rhizodeposits and changes in abiotic conditions. However, a consensus on the response of microbiota traits to the rhizosphere and bulk soils in various ecosystems worldwide regarding community diversity and structure has not been reached yet. Here, we conducted a meta-analysis of 101 studies to investigate the microbial community changes between the rhizosphere and bulk soils across various plant species (maize, rice, vegetables, other crops, herbaceous, and woody plants). Our results showed that across all plant species, plant rhizosphere effects tended to reduce the rhizosphere soil pH, especially in neutral or slightly alkaline soils. Beta-diversity of bacterial community was significantly separated between into rhizosphere and bulk soils. Moreover, r-strategists and copiotrophs (e.g. Proteobacteria and Bacteroidetes) enriched by 24-27% in the rhizosphere across all plant species, while K-strategists and oligotrophic (e.g. Acidobacteria, Gemmatimonadete, Nitrospirae, and Planctomycetes) decreased by 15-42% in the rhizosphere. Actinobacteria, Firmicutes, and Chloroflexi are also depleted by in the plant rhizosphere compared with the bulk soil by 7-14%. The Actinobacteria exhibited consistently negative effect sizes across all plant species, except for maize and vegetables. In Firmicutes, both herbaceous and woody plants showed negative responses to rhizosphere effects, but those in maize and rice were contrarily enriched in the rhizosphere. With regards to Chloroflexi, apart from herbaceous plants showing a positive effect size, the plant rhizosphere effects were consistently negative across all other plant types. Verrucomicrobia exhibited a significantly positive effect size in maize, whereas herbaceous plants displayed a negative effect size in the rhizosphere. Overall, our meta-analysis exhibited significant changes in microbial community structure and diversity responding to the plant rhizosphere effects depending on plant species, further suggesting the importance of plant rhizosphere to environmental changes influencing plants and subsequently their controls over the rhizosphere microbiota related to nutrient cycling and soil health

Multi-Input-Multi-Output Continuous Swept-Sine Vibration Test Realization by Inverse Multistep Prediction Model

As frequency-varying sine excitations in rotating machines are always emerging during run-ups and shutdowns, the multi-input-multi-output (MIMO) swept-sine test is of utter significance in product validation. At present, swept-sine vibration tests are mostly conducted with frequency-domain methods, where drive spectra are generated and updated by frequency response function (FRF), and drive signals are then generated with sinusoid oscillators. In this paper, a time-domain approach using an inverse system method based on a multistep prediction model is developed to realize the MIMO continuous swept-sine vibration test. First, the multistep prediction model of the original system is estimated in the time domain. Then, the inverse multistep prediction model is derived. After that, this model is truncated to guarantee the robustness of the inverse system and the smoothness of the generated drive signals. At last, the proposed method is validated by a simulation example with a cantilever beam and an actual test by using a three-axis shaker. The results show that the MIMO continuous swept-sine vibration test can be operated effectively by the proposed method

A simplified modelling and analysis of six degree of freedom random vibration test

status: Published onlin

Multiple-input multiple-output non-stationary non-Gaussian random vibration control by inverse system method

This paper investigates the control method for multi-input multi-output non-stationary non-Gaussian random vibration test with the specified references composed of stationary power spectra, moving root mean square distributions and moving kurtosis distributions. The objective of random vibration test is to force the response signals of test structure to satisfy the specified references within tolerances. An inverse system method in time domain is used to guarantee the control of response time-frequency characteristics independently and simultaneously. The evolutionary spectrum theory is utilized to establish the matrix representation of non-stationary non-Gaussian input-output relationships of a linear dynamic system in frequency domain. To analyze a non-stationary non-Gaussian vibration signal, two sets of random numbers named moving root mean square and moving kurtosis are used to modulate a stationary random signal. The transformation process theory is utilized to obtain moving root mean square and moving kurtosis by a moving root mean square distribution and a moving kurtosis distribution respectively. The control algorithms are presented to update the drive signals according to the deviations between responses and references. A numerical example by a cantilever beam and a biaxial vibration test are carried out and the results demonstrate the feasibility and validity of the proposed methods.status: publishe

Supercurrent-induced charge-spin conversion in spin-split superconductors

We study spin-polarized quasiparticle transport in a mesoscopic superconductor with a spin-splitting field in the presence of coflowing supercurrent. In such a system, the nonequilibrium state is characterized by charge, spin, energy, and spin-energy modes. Here we show that in the presence of both spin splitting and supercurrent, all these modes are mutually coupled. As a result, the supercurrent can convert charge imbalance, which in the presence of spin splitting decays on a relatively short scale, to a long-range spin accumulation decaying only via inelastic scattering. This effect enables coherent charge-spin conversion controllable by a magnetic flux, and it can be detected by studying different symmetry components of the nonlocal conductance signal.peerReviewe

Multi-exciter stationary non-Gaussian random vibration test with time domain randomization

© 2018 Elsevier Ltd This paper presents a new control method for multi-input multi-output stationary non-Gaussian random vibration test using time domain randomization. The control objectives are composed of response skewnesses, kurtoses and power spectral densities. The generation process of stationary and coupled reference non-Gaussian signals by specified reference skewnesses, kurtoses and spectra is analyzed. The reference non-Gaussian signals combined with system frequency response functions are then utilized to obtain the desired drive signals for dynamic inputs, in which the inverse system method in the frequency domain is employed. The primary advantages of the proposed methods are the high computational efficiency and simultaneous control of the time-frequency characteristics of response signals. In consideration of system cross coupling characteristics manifested in coherence and phase coefficients, the skewness and kurtosis tuning steps for each control channel are formulated by using a sequential phase modification method. The relationships between reference skewnesses, kurtoses and spectra are discussed and they reveal that the reference spectra have an influence on the settings of reference skewnesses and kurtoses, which implies that proper settings of reference skewnesses, kurtoses and spectra are necessary. A numerical example and a triaxial vibration test are provided and the results show the validity and feasibility of the proposed method.status: publishe