Multiple Regression and Big Data Analysis for Predictive Emission Monitoring Systems

Predictive Emission Monitoring Systems (PEMS) offer a cost-effective and environmentally friendly alternative to Continuous Emission Monitoring Systems (CEMS) for monitoring pollution from industrial sources. Multiple regression is one of the fundamental statistical techniques to describe the relationship between dependent and independent variables. This model can be effectively used to develop a PEMS, to estimate the amount of pollution emitted by industrial sources, where the fuel composition and other process-related parameters are available. It often makes them sufficient to predict the emission discharge with acceptable accuracy. In cases where PEMS are accepted as an alternative method to CEMS, which use gas analyzers, they can provide cost savings and substantial benefits for ongoing system support and maintenance. The described mathematical concept is based on the matrix algebra representation in multiple regression involving multiple precision arithmetic techniques. Challenging numerical examples for statistical big data analysis, are investigated. Numerical examples illustrate computational accuracy and efficiency of statistical analysis due to increasing the precision level. The programming language C++ is used for mathematical model implementation. The data for research and development, including the dependent fuel and independent NOx emissions data, were obtained from CEMS software installed on a petrochemical plant.

Acoustic Emission Monitoring and Microscopic Investigation of Cracks in ERCuNi Cladding

A corrosion resistant CuNi cladding was deposited on SM45C (equivalent to AISI1045) substrate by DC inverse arc welding. During the welding process, a three channel acoustic emission (AE) monitoring system was applied to detect the crack signals generating from both the cladding process and after cladding. Characteristics of the welding crack signal and noise signal had been analyzed systematically. Based on the record time of the signal, the solidification crack and delayed crack were distinguished. By two-dimensional AE source location, the crack position was located, and then investigated by scanning electron microscopy (SEM). Results showed that the AE system could detect the welding crack with high sensitivity and the two-dimensional source location could accurately determine the crack position. Microstructures of the cladding and heat affected zone (HAZ) were examined. Dendrites in the cladding and coarse grains in the HAZ were found.

Acoustic emission monitoring of rockbursts during TBM-excavated headrace tunneling at Jinping Ⅱ hydropower station

To better understand the mechanical properties of marble at Jinping II hydropower station, this paper examines the changes of brittle rocks in excavation damaged zones(EDZs) before and after excavation of tunnel with the tunnel boring machine(TBM). The paper attempts to employ the acoustic emission(AE) to study the AE characteristics and distribution of rockburst before and after TBM-excavated tunnel. It is known that the headrace tunnel #2, excavated by the drill-and-blast(D&B) method, is ahead of the headrace tunnel #3 that is excavated by TBM method. The experimental sub-tunnel #2–1, about 2000 m in depth and 13 m in diameter, between the two tunnels is scheduled. In the experimental sub-tunnel #2–1, a large number of experimental boreholes are arranged, and AE sensors are installed within 10 m apart from the wall of the headrace tunnel #3. By tracking the microseismic signals in rocks, the location, frequency, quantity, scope and intensity of the microseismic signals are basically identifed. It is observed that the AE signals mainly occur within 5 m around the rock wall, basically lasting for one day before tunnel excavation and a week after excavation. Monitoring results indicate that the rockburst signals are closely related to rock stress adjustment. The rock structure has a rapid self-adjustment capacity before and after a certain period of time during tunneling. The variations of rock stresses would last for a long time before reaching a fnal steady state. Based on this, the site-specifc support parameters for the deep tunnels can be accordingly optimized.

Study on Acoustic Emission Characteristics of Deformation Damage Process of Zirconia Ceramics

Zirconia ceramics have become increasingly widely used in recent years and are favored by relevant enterprises. From the traditional dental field to aerospace, parts manufacturing has been used, but there is limited research on the deformation and damage process of zirconia ceramics. This article analyzes the acoustic emission characteristics of each stage of ceramic damage from the perspective of acoustic emission, and explores its deformation process characteristics from multiple perspectives such as time domain, frequency, and EWT modal analysis. It is concluded that zirconia ceramics exhibit higher brittleness and acoustic emission strength than alumina ceramics, and when approaching the fracture, it tends to generate lower frequency acoustic emission signals.

Research on acoustic emission monitoring of pitting corrosion on 304 stainless steel

In order to study acoustic emission （AE） characteristics of pitting corrosion on 304 stainless steel under higher than normal temperature, pitting corrosion process of 304 stainless steel in 6° ferric chloride solution at 70° was monitored by AE technology. Conventional parameter-based approach and signal-based analysis were combined to deal with recorded AE signals, and micrographic observation was performed for further verification. The results showed that AE hit and energy increased gradually with time and reached the peak at certain time, and then declined and maintained a stable condition. Signal waveform was mainly composed of low-frequency （〈 100 kHz） flexural wave with larger amplitude and energy and high-frequency （〉 100 kHz） expansion wave with lower amplitude and energy. The research results have some certain significance for AE monitoring of pitting corrosion on 304 stainless steel under higher than normal temperature.

Angle Scattering Method for Soot Concentration Measurement under Ultra-Low Emissions Condition

Aiming at the problem of soot concentration measurement under ultra-low emission conditions,a forward small angle soot concentration measurement method is proposed.Taking a typical boiler emission of 0.1μm-3.0μm bimodal distribution soot as an object,the particle scatter simulation calculation under different parameters is carried out,and the influence of detection angle and particle size on the angular scatteringmeasurement of ultra-low emission soot is analyzed.The influence of detection angle and particle size on the angular scatteringmeasurement of ultra-lowemission soot is analyzed.Preferably,thewavelength of incident light is 650 nm,and the forward detection angle parameter is 15◦for the design of forward small angle soot concentration measurement system.An experimental system for measuring soot with standard concentration is built.Experiments of particle concentration measurement of 1.0μm and 3.0μm under ultra-low emission conditions are carried out.The results show that the average deviation of soot concentration measurement is less than 0.10 mg/m3 under the condition of ultra-low emission by using 15◦of forward detection,which provides an effective way for monitoring ultra-low emission soot concentration in coal-fired power plants.

Suggestion on further strengthening ultra-low emission standards for PM emission from coal-fired power plants in China

China has established the largest clean coal-fired power generation system in the world by accomplishing the technological transformation of coal-fired power plants(CFPPs)to achieve ultra-low emission.The potential for further particulate matter(PM)emission reduction to achieve near-zero emission for CFPPs has become a hotspot issue.In this study,PM emission from some ultra-low emission CFPPs adopting advanced air pollutant control technologies in China was reviewed.The results revealed that the average filterable particulate matter(FPM)concentration,measured as the total particulate matter(TPM)according to the current national monitoring standard,was(1.67±0.86)mg/m^(3),which could fully achieve the ultra-low emission standard for key regions(5 mg/m^(3)),but that achieving the near-zero emission standard was difficult(1 mg/m^(3)).However,the condensable particulate matter(CPM),with an average concentration of(1.06±1.28)mg/m^(3),was generally ignored during monitoring,which led to about 38.7%underestimation of the TPM.Even considering both FPM and CPM,the TPM emission from current CFPPs would contribute to less than 5%of atmospheric PM_(2.5) concentrations in the key cities and regions in China.Therefore,further reduction in FPM emission proposed by the near-zero emission plan of CFPPs may have less environmental benefit than emission control of other anthropogenic sources.However,it is suggested that the management of CPM emission should be strengthened,and a national standard for CPM emission monitoring based on the indirect dilution method should be established for CFPPs.Those measurements are helpful for optimal operation of air pollutant control devices and continuously promoting further emission reduction.

Characterization of odorous charge and photochemical reactivity of VOC emissions from a full-scale food waste treatment plant in China

Food waste treatment plants （FWTPs） are usually associated with odorous nuisance and health risks, which are partially caused by volatile organic compound （VOC） emissions. This study investigated the VOC emissions from a selected full-scale FWTP in China. The feedstock used in this plant was mainly collected from local restaurants. For a year, the FWTP was closely monitored on specific days in each season. Four major indoor treatment units of the plant, including the storage room, sorting/crushing room, hydrothermal hydrolysis unit, and aerobic fermentation unit, were chosen as the monitoring locations. The highest mean concentration of total VOC emissions was observed in the aerobic fermentation unit at 21,748.2-31,283.3 μg/m^3, followed by the hydrothermal hydrolysis unit at 10,798.1-23,144.4 μg/m^3. The detected VOC families included biogenic compounds （oxygenated compounds, hydrocarbons, terpenes, and organosulfur compounds） and abiogenic compounds （aromatic hydrocarbons and halocarbons）. Oxygenated compounds, particularly alcohols, were the most abundant compounds in all samples. With the use of odor index analysis and principal components analysis, the hydrothermal hydrolysis and aerobic fermentation units were clearly distinguished from the pre-treatment units, as characterized by their higher contributions to odorous nuisance. Methanthiol was the dominant odorant in the hydrothermal hydrolysis unit, whereas aldehyde was the dominant odorant in the aerobic fermentation unit. Terpenes, specifically limonene, had the highest level of propylene equivalent concentration during the monitoring periods. This concentration can contribute to the increase in the atmospheric reactivity and ozone formation potential in the surrounding air.

Preparation of Sulfur-doped PANI/TiO2 Nanowires and Its Sensing Properties to Mercury

TiO2 nanowires were successfully prepared via a simple hydrothermal method and a layer of sulfurized polyaniline（PANI） was loaded onto their surface to prepare a sensor of elemental mercury at room temperature. The sulfurized PANI/TiO2 composite sensor has a high sensitivity to mercury in a range of density from 5.57 mg/m3 to 126.18 mg/m3 at room temperature. The response time and recovery time are relatively short. We also investigated the sensitivity and response time to other interfering gases, such as NO2, SO2 and NH3. And the sulfurized PANI/TiO2 composite material shows a good selectivity for element mercury. The microscopic structure of the sensor was inves- tigated via X-ray diffraction（XRD）, scanning electron microscopy（SEM） and energy dispersive X-ray analysis （EDAX）. The sulfurized PANI/TiO2 composite material shows a high sensitive response, and good selectivity to element mercury, which is promising for the application in the detection of element mercury.