Analysis of particle dispersion in a turbulent flow considering particle rotation

Non-spherical particles exist widely in natural and industrial fluid systems and the motions of nonspherical particles are significantly different from that of spherical particles.In this paper,a simplified model of non-spherical particles considering particle drag correction,lift,and rotation was established.Based on the Eulerian-Lagrangian simulation,the dispersion characteristics of spherical and nonspherical particles with different Stokes numbers in a high-speed turbulent jet were analyzed and compared considering the effect of particle rotation.The results show that,the differences in particle dispersion and radial velocity fluctuation between non-spherical particles and spherical particles in the jet are significant,especially when Stokes number is large.Moreover,the effects of different type of forces on the dispersion of non-spherical particles and spherical particles were compared in detail,which revealed that the change of the Magnus force caused by the increase in the angular velocity of non-spherical particles plays a dominant role in the differences of particle dispersion.

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

A data selection method for matrix effects and uncertainty reduction for laser-induced breakdown spectroscopy

Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal uncertainty.By selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification performance.When applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,respectively.These results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.

Effect of ambient pressures on laser-induced breakdown spectroscopy signals

Laser-induced breakdown spectroscopy(LIBS)is regarded as the future superstar for analytical chemistry and widely applied in various fields.Improving the quality of LIBS signal is fundamental to achieving accurate quantification and large-scale commercialization of LIBS.To propose control methods that improve LIBS signal quality,it is essential to have a comprehensive understanding of the influence of key parameters,such as ambient gas pressure,temperature,and sample temperature on LIBS signals.To date,extensive research has been carried out.However,different researchers often yield significantly different experimental results for LIBS,preventing the formation of consistent conclusions.This greatly prevents the understanding of influencing laws of key parameters and the improvement of LIBS quantitative performance.Taking ambient gas pressure as an example,this paper compares the effects of ambient gas pressure under different optimization conditions,reveals the influence of spatiotemporal window caused by inherent characteristics of LIBS signal sources,i.e.,intense temporal changes and spatial non-uniformity of laser-induced plasmas,on the impact patterns of key parameters.From the perspective of plasma spatiotemporal evolution,the paper elucidates the influence patterns of ambient gas pressure on LIBS signals,clarifying seemingly contradictory research results in the literature.

Way-out for laser-induced breakdown spectroscopy

Ever since its creation in 1963 [1], laser-induced breakdown spectroscopy(LIBS)has gained considerable attention due to its unique capability for real-time, in situ or online analysis [2, 3]. The future world is heading into the age of artificial intelligence(AI), and data would be the most valuable asset for human society [4].

A new stage of the Asian laser-induced breakdown spectroscopy community

Laser-induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique gaining much attention since it was created in 1962[1].In 2021,the 4th Asian Symposium on LIBS (ASLIBS) and the ten-year anniversary of Chinese Symposium on LIBS (CSLIBS) were jointly held in Qingdao,symbolizing the development of the Asian and Chinese LIBS communities into a new stage.Since the initiation of CSLIBS in Qingdao (2011) and ASLIBS in Wuhan[2](2015).

A review and evaluation of nonroad diesel mobile machinery emission control in China

China’s emission control for nonroad diesel mobile machinery(NDMM)must deal with a fast increase in stock as well as regulations that are two decades behind those for on-road vehicles.This study provides the first large-scale review and evaluation of China’s NDMM policies,along with emission measurements and an investigation on diesel fuel quality.The sulfur contents of the investigated diesel declined from 430 ppm(median value)in 2011 to6-8 ppm during the 2017-2018 period.The emission control of NO_(x)and PM greatly improved with the shift from the China II to China IV standards,as demonstrated by engine tests and field NO_(x)measurements.However,the NO_(x)emission factors for non-type-approved engines were approximately twice the limits of the China II standards.Emission compliance based on bench tests was not sufficient to control actual emissions because the field-measured NO_(x)emission factors of all machinery ranged from 24%to 225%greater than the respective emission limits for the engines.These circumstances adversely affected the effectiveness of the regulations and policies for China’s emission control of NDMM.Nevertheless,the policies on new and in-use NDMM,as well as diesel fuel quality,prevented NO_(x)and PM emissions amounting to 4.4 Tg and 297.8 Gg during the period 2008-2017,respectively.The emission management strategy contributed to enhancing the international competitiveness of China’s NDMM industries by promoting advanced technologies.For effective NDMM emission control in the future,portable testing and noncontact remote supervision should be strengthened;also,the issue of noncompliant diesel should be addressed through rigorous control measures and financial penalties.

Mechanism of signal uncertainty generation for laser-induced breakdown spectroscopy

Relatively large measurement uncertainty severely hindered wide application for laser-induced breakdown spectroscopy(LIBS),therefore it is of great importance to understand the mechanism of signal uncertainty generation,including initiation and propagation.It has been found that the Auctuation of plasma morphology was the main reason for signal uncertainty.However,it still remains unclear what mechanism leads to laser-induced plasma morphology fluctuation.In the present work,we employed three fast-imaging cameras to capture three successive plasma images fromn a same laser-induced Titanium alloy plasma,which enables us to understand more clearly of the plasma evolution process especially for the early plasma evolution stage when plasma and surrounding gases interact drastically.Seen from the images,the plasma experienced an increasing morphological fuctuation as delay time increased,transforming from a“stable plasma”before the delay time of 100 ns to a“fuctuating plasma”after the delay time of 300 ns.Notably,the frontier part of plasma showed a significant down-ward motion from the delay time of 150 ns to 200 ns and crashed with the lower part of the plasma,making the plasma fatter and later even splitting the plasma into two parts,which was considered as a critical process for the transformation of“stable plasma”to“unstable plasma”.By calculating the correlation coefficient of plasma image pairs at successive delay times,it was found that the higher the similarity between two plasma at early stage,the more similar at later stage;this implied that the tiny plasma fuctuation earlier than the critical delay time(150-200 ns)was amplifed,causing a large plasma fluctuation at the later stage as well as LIBS measurement uncertainty.The initation of slight fluctuation was linked with Rayleigh-Taylor Instability(RTI)due to the drastic material interpenetration at the plasma-ambient gas interface at earlier stage(before 50 ns).That is,the uncertainty generation of LIBS was proposed as:plasma morphology fluctuation was inevitably trigged by RTI at the early stage and the tiny fuctuation was amplified by the back pressed downward process of plasma frontier material,leading to severe morphology fluctuation as well as LIBS signal uncertainty.

Coordinated Operation of Concentrating Solar Power Plant and Wind Farm for Frequency Regulation

As a dispatchable renewable energy technology, the fast ramping capability of concentrating solar power (CSP) can be exploited to provide regulation services. However, frequent adjustments in real-time power output of CSP, which stems out of strategies offered by ill-designed market, may affect the durability and the profitability of the CSP plant, especially when it provides fast regulation services in a real-time operation. We propose the coordinated operation of a CSP plant and wind farm by exploiting their complementarity in accuracy and durability for providing frequency regulation. The coordinated operation can respond to regulation signals effectively and achieve a better performance than conventional thermal generators. We further propose an optimal bidding strategy for both energy and frequency regulations for the coordinated operation of CSP plant and wind farm in day-ahead market (DAM). The validity of the coordinated operation model and the proposed bidding strategy is verified by a case study including a base case and sensitivity analyses on several impacting factors in electricity markets.

Local and regional contributions to PM_(2.5) in the Beijing 2022 Winter Olympics infrastructure areas during haze episodes

The 2022 Winter Olympics is scheduled to take place in Beijing and Zhangjiakou,which were defined as OIAs(Olympic infirastructure areas)in this study.This study presents the characteristics and source apportionment of PM_(2.5) in the OIAs,China.The entire region of China's Mainland,except for the OIAs,was divided into 9 source regions,including four regions in the BTH(Beijing-Tianjin-Hebei)region,the four provinces surrounding the BTH and the remaining areas.Using CAMx/PSAT,the contributions of the nine regions to the PM_(2.5) concentration in the OIAs were simulated spatially and temporally.The simulated source apportionment results showed that the contribution of regional transportation was 48.78%,and when PM_(2.5) concentration was larger than 75μg/m^(3) central Hebei was the largest contributor with a contribution of 19.18%,followed by Tianjin,northern Hebei,Shanxi,Inner Mongolia,Shandong,southern Hebei,Henan and Liaoning.Furthermore,the contribution from neighboring regions of the OIAs was 47.12%,which was nearly twice that of long-range transportation.Haze episodes were analyzed,and the results presented the importance of regional transportation during severe PM_(2.5) pollution periods.It was also found that they were associated with differences in pollution sources between Zhangjiakou and Beijing.Regional transportation was the main factor affecting PM_(2.5) pollution in Zhangjiakou due to its low local emissions.Stagnant weather with a low planetary boundary layer height and a low wind velocity prevented the local emitted pollutants in Beijing from being transported outside,and as a result,local emissions constituted a larger contribution in Beijing.

Dynamic modelling and simulation of a post-combustion CO_(2) capture process for coal-fired power plants

Solvent-based post-combustion capture technologies have great potential for CO_(2)mitigation in traditional coal-fired power plants.Modelling and simulation provide a low-cost opportunity to evaluate performances and guide flexible operation.Composed by a series of partial differential equations,first-principle post-combustion capture models are computationally expensive,which limits their use in real time process simulation and control.In this study,we propose a first-principle approach to develop the basic structure of a reduced-order model and then the dominant factor is used to fit properties and simplify the chemical and physical process,based on which a universal and hybrid post-combustion capture model is established.Model output at steady state and trend at dynamic state are validated using experimental data obtained from the literature.Then,impacts of liquidto-gas ratio,reboiler power,desorber pressure,tower height and their combination on the absorption and desorption effects are analyzed.Results indicate that tower height should be designed in conjunction with the flue gas flow,and the gas-liquid ratio can be optimized to reduce the reboiler power under a certain capture target.

An interval-parameter two-stage optimization model for CO_(2) collection,distribution,transportation,utilization,and storage planning

Geological carbon dioxide (CO_(2)) utilization and storage have been widely recognized as one of the important options to deliver greenhouse gas emissions reduction. Reasonable planning is critical to promote CO_(2) utilization and storage. However, CO_(2) emissions gas collection exhibits a stochastic probability distribution, and CO_(2) utilization and storage features fluctuation demands, which have gone beyond current determine planning techniques. To fulfill the current research gap, this study develops an interval-parameter two-stage programming-based CO_(2) collection, distribution, transportation, utilization, and storage optimization model, integrating interval parameter planning and two-stage planning into a general framework. Therefore, the model can address uncertainties expressed as random probabilistic distributions and discrete intervals, tackle dynamic facilities capacity expansion issues, develop optimal predefined CO_(2) distribution policy, and generate recourse schemes to address gas shortage or gas surplus issues. The model is examined by a typical hypnotical case study in China. The results revealed that the model could generate a set of first-stage reasonable CO_(2) distribution and facilities capacity expansion schemes to maximum system benefits and the highest feasibility. Besides, a set of two-stage CO_(2) outsourcing purchases and facilities capacity expansion in reserve storage regions solutions were also generated to address the gas oversupplies and shortage issues. The modeling approach enriches the current CO_(2) utilization and storage distribution research content under multiple uncertainties.

A calibration-free model for laser-induced breakdown spectroscopy using non-gated detectors

Calibration-free(CF)laser-induced breakdown spectroscopy(LIBS)is normally only applicable for gated detectors due to its dependence on the assumption of a steady-state plasma.However,most currently available LIBS systems are equipped with non-gated detectors such as chargecoupled device(CCD),which degrades the accuracy of CF method.In this paper,the reason for the less satisfactory quantification performance of CF for LIBS with non-gated detectors was clarified and a time-integration calibration-free(TICF)model was proposed for applications with non-gated detectors.It was based on an assumed temporal profile of plasma properties,including temperature and electron density,obtained from another pre-experiment.The line intensity at different time during the signal collection time window was estimated with self-absorption correction according to the temporal profile of the plasma properties.The proposed model was validated on titanium alloys and compared with traditional CF.The accuracy of elemental concentration measurement was improved significantly:the average relative error of aluminum and vanadium decreased from 6.07%and 22.34%to 2.01%and 1.92%,respectively.The quantification results showed that TICF method was able to extend the applicability of CF to LIBS with non-gated detectors.

Highly spatial and temporal bottom-up vehicle emission characterization and its control in a typical ecology-preservation area

The Chishui River Valley is a microscale ecology-preservation area with industrial clusters.The significance of evaluating vehicular emissions has been gradually highlighted with the rapid development of the local transportation and tourism sectors.This study provides the first estimates based on both bottom-up and top-down approaches.The annual total emissions of CO,NOx,hydrocarbons(HC),PM10,and PM2.5 in 2019 were 347.8,189.6,46.3,6.9,and 6.3 Mg,respectively.Trucks contributed the most(55%)to the NOx emissions,followed by heavy-duty passenger vehicles(26%).In contrast,light-duty passenger vehicles and motorcycles generated 75%of the HC emissions.The superior accuracy of highly spatial and temporal bottom-up estimates versus top-down estimates is validated by the similar variation trends of hourly emission intensities and enhanced concentrations relative to background observations for both NOx and CO,with Pearson correlation coefficients between the intensities and concentrations ranging from 0.79 to 0.85.Historical HC emissions peaked in 2013,followed by a sharp decline in 2014 and a continuous rise since then,whereas NOx emissions have kept increasing since 2010.These indicated the necessity and urgency of effective vehicular emission mitigations.Based on scenario analysis,traffic restrictions combined with upgrading the emission standards of admitted vehicles will possess huge emission reduction potentials.Future recommendations about establishing a low emission zone in the valley and supporting policies were introduced.

Improving thermal stability of LiNbO_(3)based electro-optical electric field sensor by depositing a TiO_(2)film

Electro-optic electric field sensors based on LiNbO3 are widely used for the measurement of electric fields or transient voltages.However,the working bias of the sensor is influenced by the temperature due to the thermo-optic effect of LiNbO_(3).An athermal electrooptic electric field sensor was demonstrated by coating a thin layer of TiO_(2)film which has a negative thermo-optic coefficient,on the common-path interferometer based sensor to compensate LiNbO_(3)'s positive thermo-optic coefficient.Both calculation and experimental studies were conducted.The experimental results reasonably agree well with the calculated values,and the results show the sensor coated with a 640 nm thick TiO_(2)film has a much smaller temperature dependence of 0.011°/℃compared to the initial value of 0.1°/℃.