Application of Chemical Tracing Experiment Technique in Leakage Detection of Hydraulic Engineering

[Objective] The research aimed to study the application of chemical tracing experiment technique in leakage detection of hydraulic engineering.[Method] According to the current situation of Sanyuan Western Suburb Reservoir in Xianyang City of Shaanxi Province,three sections （L1,L2 and L3） were set.KI was selected as the chemical tracer to carry out the tracing and detection research.[Result] There was no obvious leakage phenomenon in L1,L2 and L3 sections.The impermeability of rock in some dam abutments was bad.[Conclusion] The leakage reason of Western Suburb Reservoir was that the impermeability of rock in some dam abutments couldn’t satisfy seepage requirement.After the reservoir was put into operation,the water level in front of dam rose,and the ground water level of dam abutment also rose.The penetration water pressure correspondingly increased,and the water content of bank slope at the downstream of dam increased.

Principles of Technology for Bottling Medicinal Mineral Waters of Sairme Using the Example of Source №3a

Sairme mineral water, one of the famous mineral waters in Georgia, is renowned for its exceptional healing properties. The distinctiveness and therapeutic benefits of the naturally sourced mineral water, known as “Sairme”, stem from its rich array of microelements, notably including iron and manganese. Since 1948, the bottling of Sairme mineral water has been a prominent activity. Named after the Sairme deposit, this mineral water is packaged in various formats to cater to diverse consumer preferences. The bottling process involves transporting the mineral water from wells to the bottling plant through pipelines. Prior to bottling, the mineral water undergoes meticulous processing stages in adherence to current Georgian and international regulations. This process ensures that the concentration of trace elements in the bottled water is minimized, maintaining its purity and quality. Given the importance of preserving the microelements present in bottled mineral water, our research is dedicated to optimizing the technological process. Our objective is to safeguard the valuable microelements while ensuring the highest standards of quality and safety in the final product.

Asian Honey Bees Use Trace Amount Chemical to Avoid Danger

While foraging,animals can form inter-and intra-specific social signaling(i.e.one organism using signals to alert another about danger)networks to avoid similar predators.Honey bee sting alarm pheromones are multi-component blends,for instance isopentyl acetate(IPA),octyl acetate(OA),benzyl acetate(BA),etc.However,the

Quantitative Analysis of the Silk Moth＇s Chemical Plume Tracing Locomotion Using a Hierarchical Classification Method

The silk moth （Bombyx mori） exhibits efficient Chemical Plume Tracing （CPT）, which is ideal for biomimetics. However, there is insufficient quantitative understanding of its CPT behavior. We propose a hierarchical classification method to segment its natural CPT locomotion and to build its inverse model for detecting stimulus input. This provides the basis for quantitative analysis. The Gaussian mixture model with expectation-maximization algorithm is used first for unsupervised classification to decompose CPT locomotion data into Gaussian density components that represent a set of quantified elemental motions. A heuristic behavioral rule is used to categorize these components to eliminate components that are descriptive of the same motion. Then, the echo state network is used for supervised classification to evaluate segmented elemental motions and to compare CPT locomotion among different moths. In this case, categorized elemental motions are used as the training data to estimate stimulus time. We successfully built the inverse CPT behavioral model of the silk moth to detect stimulus input with good accuracy. The quantitative analysis indicates that silk moths exhibit behavioral singularity and time dependency in their CPT locomotion, which is dominated by its singularity.

Particulate matter characterization in a steelworks using conventional sampling and innovative lidar observations

Particulate matter （PM） emissions from steelworks cause public concern. Although end-of-pipe and pro- cess integrated measures have led to a significant drop in emissions of large particles from stacks, fine aerosols were not specifically considered, nor were emissions from fugitive and open sources. In this study, we deployed aerosol samplers together with a scanning ultra-violet （UV） lidar to characterize total suspended particles （TSP）, PM10, and PM2.5, in emissions from a large integrated steelworks in Spain over a 16-day period. We determined the content of carbonaceous, soluble inorganic, mineral dust, and metal species. A positive matrix factorization was carried out on our dataset. Despite mineral dust being predominant in all size fractions, the steelworks was clearly a source of carbonaceous species, resulting in production of secondary inorganic aerosols. In particular, stack emissions were a major contributor of fine particles, while open sources dominated the emissions of TSP, yielding up to 80% of particles larger than PM10. UV lidar provided 2D maps of aerosols in real time, with an ability to detect PM emissions and to visualize complex plumes. We suggest that air quality management of steelworks needs to focus on controlling large and coarse oarticle emissions, esoeciallv those from onen sources.