Stage Efficiency Research Articles

Study on flow characteristics of leakage in the last stage inner blade tip clearance of steam turbine

Internal steam leakage in steam turbines from the high-pressure side to the low-pressure side through clearances causes loss, resulting in reduced efficiency and potentially compromising the safe operation of the turbine. Therefore, a comprehensive understanding of the flow characteristics of leakage through blade tip clearances is crucial to improve the efficiency of steam turbines. In this paper, the last stage blades of the low-pressure cylinder of a certain 600 MW ultra-supercritical steam turbine unit were studied. A wet steam flow model and a turbulence model were established, and the flow characteristics of the last stage under different inlet parameters, outlet parameters, and tip clearance sizes were analyzed. The results showed that an increase in the clearance size affects the inlet and outlet steam angles of the rotor blades, with significant changes occurring near the blade tip. The main flow velocity inside the rotor blade channel fluctuates violently starting from the 70% axial position. The high entropy region is located near the exit flow region of the rotor blade, with its range expanding as the clearance size increases. The entropy change is significant at 60% blade height and above, with more intense changes occurring in the blade tip area. The relative leakage amount and efficiency change uniformly with clearance variation. Generally, for every 0.1% increase in clearance height, the relative leakage amount increases by ∼0.31%–0.42%, and the stage efficiency decreases by 0.34%–0.44%. The results of this study can provide a theoretical basis and guidance for improving the flow efficiency of steam turbines.

Fabrication Tradeoff Based Optimal Synthesis of Winding Configurations for Planar Transformer in CLLC DC–DC Converter

Adhering to the objective of modelling and selecting the most optimal winding configuration for a high frequency planar transformer (HFPT) for auxiliary charging systems for more electric aircrafts (MEA) this paper elucidates numerous fabrication and design-based constraints and correlations to enable parametric modelling of various magnetic components. Instead of providing generalized solutions, this paper thoroughly characterizes all possible winding configurations for HFPT employed in a bidirectional CLLC DC/DC converter. A detailed analytical study is presented for each component and verified using several instances of 3D Finite Element Analysis (FEA) based model to synthesize the effective field and current density distribution in the windings. Several design-based trade-offs are graphically explained with various criteria pertaining to optimal winding selection to study the interdependence of the resultant parameters on hardware specifications, such as the PCB thickness and its fabrication layout, air gaps and conductor thickness. The paper presents a comprehensive comparison between the analytical, simulation and experimental analysis that portrays a strong agreement between these models with an average mismatch of up to 6.2%. An experimental prototype of CLLC converter rated for 1kW nominal power, operating at 500kHz resonant frequency is developed with the optimal HFPT characteristics that yields a peak efficiency of 98.49% with magnetics stage efficiency of 99.31%.

Effect of wear damage on aero-thermal performance of the film-cooled squealer tip in a turbine stage

Effects of wear damage on the aerodynamic performance, heat transfer and film cooling effect in the squealer tip region of a gas turbine stage were investigated under engine condition. Two wear parameters, including the starting-location of wear ( sl) and wear depth ( wd), were introduced to describe the degree of wear damage. Three starting-locations of wear ( sl = 32% C ax, 58% C ax and 79% C ax) and three wear depths ( wd = 0.33 mm, 0.67 mm and 1.0 mm) were selected to compute the heat transfer coefficient and film cooling effectiveness on the squealer tip at four blowing ratios ( M = 0.25, 0.5, 0.75 and 1.0). The pressure loss and isentropic efficiency of the turbine stage were calculated to assess the aerodynamic performance degradation induced by the tip wear. The results indicate that the pressure loss in the blade passage near tip region is increased and the stage efficiency is decreased with the increase of wd. Compared to the original design case at M = 0.75, the pressure loss in the rotor blade passage is increased by 7.39% and the stage efficiency is decreased by 2.22% at most after wear. As wd increases, the area-averaged heat transfer coefficient on the cavity floor is increased and film cooling effectiveness is decreased. For the worn cases at M = 0.25, 0.5, 0.75 and 1, the area-averaged heat transfer coefficient on the cavity floor is increased respectively by 87.7%, 62.3%, 71.3% and 88.0% at most, and the area-averaged film cooling effectiveness is decreased respectively by 37.2%, 26.8%, 26.7% and 22.2% at most, as compared to the original design cases.

Automatic sleep staging algorithm for stochastic depth residual networks based on transfer learning

The existing automatic sleep staging algorithms have the problems of too many model parameters and long training time, which in turn results in poor sleep staging efficiency. Using a single channel electroencephalogram (EEG) signal, this paper proposed an automatic sleep staging algorithm for stochastic depth residual networks based on transfer learning (TL-SDResNet). Firstly, a total of 30 single-channel (Fpz-Cz) EEG signals from 16 individuals were selected, and after preserving the effective sleep segments, the raw EEG signals were pre-processed using Butterworth filter and continuous wavelet transform to obtain two-dimensional images containing its time-frequency joint features as the input data for the staging model. Then, a ResNet50 pre-trained model trained on a publicly available dataset, the sleep database extension stored in European data format (Sleep-EDFx) was constructed, using a stochastic depth strategy and modifying the output layer to optimize the model structure. Finally, transfer learning was applied to the human sleep process throughout the night. The algorithm in this paper achieved a model staging accuracy of 87.95% after conducting several experiments. Experiments show that TL-SDResNet50 can accomplish fast training of a small amount of EEG data, and the overall effect is better than other staging algorithms and classical algorithms in recent years, which has certain practical value.

On the issue of creating the optimal last stage of powerful steam turbines of nuclear power plants

THE PURPOSE. To estimate the most effective length of the working blade of the last stage of a powerful wet-steam turbine in terms of obtaining its maximum efficiency and to optimize the parameters of this stage in the design mode. For this stage, perform multi-mode optimization to select the main characteristics of the stage operating with maximum efficiency according to a given model daily load schedule.METHODS. When solving this problem, the method of calculating the axisymmetric flow of steam in the flow part of the turbine stage as an inviscid single-phase working fluid relative to a stationary guide device and rotating with an angular velocity ω of the impeller used, and the losses energy calculated according to the axisymmetric method of the MPEI.RESULTS. The article describes the relevance of the topic, discusses the features of the use of the author's software in solving the tasks. The characteristics of the stages with different lengths of the working blades presented and the results of their calculation in the nominal mode are given. A model daily schedule selected for a nuclear power plant turbine operating in the central region of Russia. The results of calculations of variable modes of the last stage of the turbine operating according to this daily schedule presented.CONCLUSION. The choice of the maximum length of the working blade is limited not only by its strength characteristics, but also by the increase in wave losses in the gratings due to an increase in the optimal available heat drop, or rather the associated increase in supersonic speeds near the meridional contours. So for a high-speed turbine To-1200-6,8/50 the maximum efficiency of the last stage is achieved at a length of 1400 mm, both when the turbine is configured with both three two-flow LPC and four. Selection of the main characteristics of these stages, such as the available heat drop, the degree of reactivity, etc. it should be made taking into account the variable operating modes of the turbine on the basis of the forecast of daily schedules of loads of turbine units. When using a typical daily load schedule, the average internal relative efficiency in the range of operating modes according to this schedule is higher by 0.6 % when choosing a 10% increased available heat drop compared to the optimal one in the design mode.

Comparative Analysis of the Effect of Different Nucleic Acid Extraction Methods on SARS-CoV-2 Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction Results

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative agent of Coronavirus diseases-2019 (COVID-19) disease. Rapid and accurate detection of the virus is vital to prevent transmission and effectively manage the pandemic. The gold standard diagnostic method for this agent is the real-time reverse transcription polymerase chain reaction (qrRT-PCR) test conducted on respiratory tract samples and one of the most critical steps affecting the sensitivity of this test is the nucleic acid extraction stage. However, restrictive factors such as reagent supply and storage conditions limit the testing capacity. Therefore, innovative and cost-effective alternatives are needed to speed up testing and minimize pre-processing steps. The aim of this study was to evaluate the impact and applicability of different methods to enhance the efficiency of the nucleic acid extraction stage in the SARS-CoV-2 qrRT-PCR test. As an alternative to the routinely used viral nucleic acid extraction buffer (vNAT), the modified vNAT method (MvNAT), which includes centrifugation, the R1-R2 kit and the heat treatment (HT) method, was applied to 118 respiratory tract samples. Samples determined with threshold cycle values of (Cq) of ≤ 35 (n= 10), > 35 (n= 42), indeterminate (n= 56) in routine results and negative controls (n= 10) were included in the study. The RNA quantities obtained after extraction for each method were measured and recorded using a spectrophotometric measurement device. All samples were processed using the SARS-CoV-2 qrRT-PCR kit targeting the RdRp region. The results were statistically analyzed using unpaired and paired t-tests and results with a p-value of < 0.05 were considered statistically significant. Excluding negative control samples, while the standard method yielded a Cq value of 48.1% (mean Cq value (Cqmean)= 39.5 ± 6.9) for a total of 108 samples, the MvNAT method produced a Cq value of 11.1% (Cqmean= 38.4 ± 5.2), the R1-R2 kit yielded 14.8% (Cqmean= 35.9 ± 7.1) and HT method resulted in 25% (Cqmean= 31.4 ± 6.3). When the variability in target gene Cq values was analyzed in all samples compared to the standard method, the HT method significantly provided lower Cq values (n= 16; p= 0.007; paired t-test) while the MvNAT method and R1-R2 kit yielded higher Cq values (n= 6; p= 0.025, n= 11; p= 0.004; paired t-test). Sensitivity rates were MvNAT= 31.6%, R1-R2= 57.9%, HT= 84.2%, with 100% specificity for all three methods. The HT method demonstrated a positive extraction efficiency because it is fast, easy and not dependent on reagents. Although this method provided lower Cq values than the standard method, especially in samples with a high viral load, it should be considered that it also has the potential to yield false-negative results in samples with Cq> 35. With this study, it was concluded that the extraction phase of the SARS-CoV-2 qrRT-PCR test can be carried out using various methods that do not require kits or reagents, such as the HT method. However, it is believed that multicenter studies involving a larger number of samples are necessary to standardize the test and assess the possibility of false negatives.

Study on Imagery Modeling of Solid Wood Chairs in Big Data

With the continuous improvement of living quality and aesthetics, people have increasingly higher requirements for furniture products. Excellent solid wood chairs are one of the most representative products in the furniture industry. To enhance space and taste, the design of chairs may significantly impact consumers’ emotional experiences and purchase decisions. This study aims to evaluate how the modeling imagery of solid wood chairs affects consumers’ preferences and emotional experiences. The development of the current era is inseparable from the analysis of big data. Firstly, a representative sample is obtained by multidimensional scaling (MDS), analyzed, and evaluated by factor analysis. Moreover, five groups of adjective vocabulary are selected to describe the modeling imagery of solid wood chairs, such as “balanced and coordinated”, “unique and novel”, “practical and simple”, “quality and detailed”, and “traditional and plain”. Further, the triangular fuzzy theory is applied to analyze and discuss the twelve types of solid wood chairs in the five groups of adjective vocabulary. Then, the study verifies that the differences are significant in the evaluations of the 12 samples in the “unique and novel” and “quality and detailed” groups, and small in the groups of “traditional and plain”, “balanced and coordinated”, and “practical and simple”. Through comprehensive comparisons, five groups with similar modeling imagery are created, and solid wood chairs with different modeling imagery should be placed in suitable spaces. According to the results of this study, the evaluation of the modeling imagery of solid wood chairs cannot solely rely on subjective judgments. However, it can be reasonably refined through data analysis and mathematical algorithms. It can also scientifically and effectively reflect the potential perception needs of consumers on the modeling imagery of solid wood chairs, as well as help to improve the design efficiency of the furniture product development stage.

Analysis of the circular economy efficiency of China's industrial wastewater and solid waste - based on a comparison before and after the 13th Five-Year Plan

The circular economy has been incorporated into China's Five-Year Plan as an important policy tool for sustainable development with the aim of resolving the conflicts among economic growth, energy shortages, and environmental pollution. This research introduces industrial waste emission and recycling indicators into the window two-stage DDF recycle model, explores industrial circular economy efficiency in 30 provinces of China from 2011 to 2019 in the two stages of production and recycle, and focuses on efficiency improvement and stability during the 13th Five-Year Plan period. The results show the following. (1) During the study period, especially during the 13th Five-Year Plan, the circular economy efficiency in most provinces is positively improved, and its improvement is more significant in the central and western provinces. (2) Production stage efficiency is higher than recycle stage efficiency. Whether measured in the overall process, the production stage, or the recycle stage. In mean efficiency, the east is better than the central, and the west is the worst. (3) In terms of efficiency stability during the policy period, the central is the most stable, the east is the second most stable, and the west is the least stable. Shanghai and Tianjin present high efficiency and high stability; Zhejiang, Anhui, and Qinghai present high efficiency, but low stability; and Ningxia, Yunnan, and Xinjiang perform poorly in terms of efficiency values and stability. (4) Each province could adapt to its own situation, accelerate the adjustment of the industrial structure, optimize the energy consumption structure, and improve the overall resource utilization efficiency and recycling efficiency. The government could tilt the resource layout towards provinces with development difficulties, and meanwhile promote efficient development of recycling policies with dividends that address regional imbalances.

Carbon Footprint Assessment and Efficiency Measurement of Wood Processing Industry Based on Life Cycle Assessment

The contradiction between economic development and the ecological barrier function of the wood processing sector is increasingly deepening. However, China has not yet established a life cycle database for the wood processing industry, which makes it difficult to scientifically evaluate its carbon emission efficiency. Therefore, based on the panel data of 31 provinces (autonomous regions and municipalities) in China from 2014 to 2020 published in the China Statistical Yearbook, this paper combined a life cycle assessment and dynamic network slacks-based model, and the carbon emission efficiency of different stages was measured from the multidimensional perspective of labor, energy, capital input, and economic and ecological benefits output. The results show that: (1) The overall carbon emission efficiency is 0.6161, and the coastal and northwest regions have higher efficiency; (2) The efficiency levels of Inner Mongolia, Shanghai, and another four provinces have been increasing while other regions have significant differences; (3) Beijing, Jiangsu, and the other four provinces are at an effective level overall. The most serious efficiency loss is at the processing stage. These findings provide an important reference for promoting the low-carbon cycle development of China’s wood processing industry and the formulation of policies in various regions.

Fintech and energy efficiency: Evidence from OECD countries

This study aims to analyze the impact of financial technology (Fintech) on energy efficiency. Using data from the OECD national panel for 2000–2018, this study examines the direct and indirect effects of fintech on energy efficiency using the undesirable super-efficiency three-stage SBM model. The results show that: (1) The overall trend of energy efficiency in the third stage after adjustment is close to that of the first stage, and the average values decrease. (2) Fintech directly contributes to the improvement of energy efficiency in OECD countries. And it indirectly enhances energy efficiency by increasing renewable energy consumption or environmental management patents. (3) Fintech companies specializing in the energy sector or located in North America can contribute more significantly to energy efficiency. The results may provide useful information regarding the development of fintech and energy efficiency in OECD countries.

Using Network DEA to Explore the Effect of Mobile Payment on Taiwanese Bank Efficiency

In order to explore the potential influence of new mobile payment services on the Ephesus model developed by Kao and Hwang (2008), we investigated the relative performance of 19 Taiwanese banks from 2018 to 2021. The network efficiency was divided into two parts: management efficiency and profitability efficiency. Only one bank achieved total efficiency from 2019 to 2021. The stage efficiencies showed increments during the first three years (2018–2020), but they declined in 2021. Most banks had low efficiency in the management stage and high efficiency in the profitability stage, suggesting that there are weaknesses in the management of physical resources but high awareness that mobile payment services can be exploited to achieve high profitability. Our results prove that mobile payment is a potential and profitable new service that Taiwanese banks should take advantage of. Comparing the results between the CCR model and the NDEA model, we observed that the NDEA model has more explanatory power, as it provides insight into the internal structure of the working process of Taiwanese banks.

Study on economical efficiency of ocean energy generation in China

Ocean energy, as a kind of renewable resource, plays an important role in China’s low-carbon development and meeting its goal of “carbon peaking and carbon neutrality”. The paper aims to calculate the cost of ocean power generation in China and make a medium and long-term forecast. Meanwhile, the offshore wind power development experience and the Levelized Cost of Energy (LCOE) cost pricing model is used for analysis and verification. The results shows that it features a high cost without economical efficiency in the initial stage; With the continuous expansion of installed capacity, the cost will be significantly lowered but the economical efficiency is moderate; the cost will fall significantly when the installed capacity reaches to a 100 MW level, and it has strong economical efficiency. The government should provide policy and financial support for ocean power generation industry; enterprises need to strengthen technological innovation and complete the industrial chain to improve the economical efficiency of scale utilization.

Прогнозирование эффективности эмбриологического этапа вспомогательных репродуктивных технологий по микробному составу эякулята

Obtaining enough good and excellent quality embryos is one of the key factors for achieving pregnancy using assisted reproductive technologies. This work was aimed at developing a mathematical model for predicting good and excellent quality embryos based on semen microbiota assessment in normozoospermia. The study included 127 men whose semen was used for in vitro fertilization (IVF). Patients were divided into 2 groups depending on the proportion of good-quality blastocyst developed on the 5th day of culturing (good-quality blastocyst development rate, GBDR). The 1st group included 57 patients with GBDR ≥ 40%, the 2nd group included 70 patients with GBDR &lt; 40%. All patients’ semen was assessed at the day of fertilization. Semen parameters were evaluated in accordance with the WHO standards and semen microbiota composition was determined by means of real-time PCR. Discriminant analysis was used for development of the prognostic model. We developed a method for predicting efficiency of the embryological IVF stage in normozoospermia: EGO-Pro-N prognostic index (Embryos of GOod and Excellent quality Prognosis in Normozoospermia). If the EGO-Pro-N value is greater than 0.212, the probability of receiving GBDR ≥ 40% is low. Conversely, if the EGO-Pro-N value is less than or equal to 0.212, the probability is high. Sensitivity and specificity of the method were 71.9% and 70.0% respectively, accuracy was 70.9%. The developed model allows us to predict good and excellent quality embryos based on comprehensive semen microbiota assessment in normozoospermia before IVF.

Modifications of double-rim geometry to improve thermal performance of squealer tip in a turbine stage

The double-recessed (i.e. double-rim) design is an alternative to improve thermal performance of the squealer tip. In this paper, the aero-thermal performance of double-rim squealer tip in a turbine stage was numerically investigated under engine condition. The heat transfer and film cooling effect between the double-rim squealer tip and conventional squealer tip were compared to show the superior thermal characteristic of double-rim design. The interactions between the leakage flow and coolants were analyzed to address the heat transfer reduction and film cooling improvement for the double-rim configuration. To further reduce the thermal load on double-rim squealer tip, the height and arc length of the inner rim were modified to increase the coolant accumulations in squealer cavities. The results show that the tip and pressure side cooling flow is well attached on the cavity floor and suction side rim of double-rim squealer tip as compared to the conventional squealer tip. With the proper arrangement of inner rim height and arc length, the modified double-recessed squealer tip helps to reduce the area-averaged heat transfer coefficient by 90.3%, and improve the film cooling effectiveness by 49.6%, while the isentropic stage efficiency is almost not affected, as compared to the conventional squealer tip.

A monolithic gallium nitride‐based two‐phase synchronous buck converter with high operating frequency

AbstractThe need for a high‐frequency and high‐efficiency gallium nitride (GaN)‐based buck converter that can be controlled directly by a low swing pulse width‐modulated (PWM) signal, without the need for additional buffers or preamplifiers, poses a significant challenge in the field of power conversion and dynamically power supply applications. To solve this problem, this letter presents a monolithic two‐phase synchronous buck converter, fabricated using a 0.25‐um GaN‐on‐Si process, integrated both the drivers and power stage transistors, without requiring additional buffers or preamplifiers. So, the proposed converter can be directly controlled by a PWM signal with a swing of only 1 V (−0.5 to 0.5 V). At a 100‐MHz switching frequency, the converter achieves a maximum output power of 12 W with a power stage efficiency of 82%. The converter includes two identical half‐bridge Monolithic Microwave Integrated Circuit (MMICs), and with the frequency multiplication property of multi‐phase topology, the equivalent switching frequency can reach 200 MHz in the open‐loop operating mode. The experimental results show that the converter can track a 40‐MHz bandwidth envelope signal (256 QAM, 6 dB PAPR) with 80.1% efficiency.

Liver elastography can predict degree of advanced fibrosis for autoimmune hepatitis in biochemical remission.

The aim was to analyze the concordance of liver stiffness measurement (LSM) either by transient elastography (TE) or ARFI with liver biopsy in autoimmune hepatitis (AIH) patients with biochemical remission and to identify those with histological remission. Liver biopsy is still the golden standard for AIH diagnosis. However, it is an invasive procedure and these patients, most of the time, require many biopsies, so it would be valuable to search for noninvasive method that could select all these patients and keep under observation. Thirty-three patients with AIH were submitted for liver biopsy to evaluate histological remission after at least 18 months of normal aminotransferases. The efficiency of LSM and fibrosis stages was tested by a receiver operating characteristic curve analysis (AUROC). One patient (3%) was F0, 6 (18.2%) were F1, 8 (24.2%) were F2, 10 (30.3%) were F3, and 8 (24.2%) were F4, according to METAVIR. Thirteen of thirty-three (39.4%) patients did not achieve histological remission. AUROC for F4 stage was 0.83 (IC: 0.76-0.99) for TE and 0.78 (IC: 0.65-0.95) for ARFI. Optimal LSM cutoff values were 12.3 kPa (Se=87.5%, Sp=88%) for TE and 1.65 m/s (Se=87.5%, Sp=76%) for ARFI. The tests were unable to differentiate patients with histological activity from those in histological remission (P< 0.05). TE and ARFI accurately identify liver fibrosis by METAVIR score in AIH patients with biochemical remission. No cutoff value was detected to indicate whether the patient achieved histological remission.

The efficiency evaluation and influencing factor analysis of regional green innovation: a refined dynamic network slacks-based measure approach

PurposeThis study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.Design/methodology/approachA two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.FindingsOn average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.Originality/valueThis study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

Assessment of a hybrid technology for liquid fuel dimethyl aminoethyl azide wastewater treatment

Abstract Dimethyl aminoethyl azide (DMAZ) is a liquid fuel in the space industry. Although this fuel is non-carcinogenic, its wastewater suffers from some hazardous pollutants, such as sodium azide (NaN3). A hybrid process of coagulation–flocculation and chemical reaction with nitrous acid was applied for the wastewater treatment. The Taguchi method was used for the process optimization. Coagulant concentration, rapid mixing intensity, duration time, CAMP number and settlement time were found to be effective parameters for the efficiency of the former process. Turbidity and total suspended solids (TSS) of the wastewater were used to track the removal efficiency in the first stage. The complete removal efficiency was achieved. In the latter process, NaN3 was removed using a reaction with nitrous acid. pH of the wastewater was optimized as the controlling factor in the second process. Biochemical oxygen demand (BOD), chemical oxygen demand (COD) and NaN3 removals of 98.9, 98.2 and 96.3% were obtained under the optimum conditions, respectively. As a result, a reduction of 91.9% in turbidity, 98.5% in TSS, 98.5% in BOD, 98.1% in COD and 96.7% in NaN3 concentration were observed in the output of the wastewater.

Full-Scale Experimental Study on the Effect of CO2 Flooding on Storage-Seepage Capacity of Tight Sandstone Reservoirs.

In the CO2 flooding stage of tight sandstone reservoirs, the CO2-crude oil-rock interaction causes asphaltene deposition and mineral dissolution effect, which would affect the reservoir performance and reservoir physical property. To reveal the variation law of reservoir performance and percolation capacity in the CO2 flooding stage, the core samples of typical tight sandstone reservoirs with different permeability levels were selected. An indoor physical flow simulation experiment of CO2 flooding was then performed. The change in reservoir performance characteristics in the CO2 flooding stage of the tight sandstone reservoir was quantitatively evaluated, and the evolution law of reservoir macroscopic seepage ability during the CO2 flooding process was revealed. The experimental results show that the damage degree of CO2-crude oil-rock interaction on reservoir foundation performance is negatively correlated to the initial permeability of the reservoir. The lower the initial permeability of core samples, the greater would be the damage degree of the experimental process on the effective porosity and permeability of rock samples. However, in reservoirs with relatively high permeability (0.5-0.6 mD), the physical properties of rock samples improved after CO2 flooding with an average increase in effective porosity and permeability by 4.54 and 10.23%, respectively. The damage degree of reservoir effective porosity is slightly affected by CO2 injection pressure, while the damage degree of permeability has a significant negative correlation with injection pressure. In the high-pressure miscible flooding stage of 30 MPa, the organic matter deposition caused by the interaction of CO2-crude oil-rock causes the highest degree of damage to the permeability of rock samples (up to 33.33%). Moreover, the flooding efficiency in the CO2 flooding stage of a tight sandstone reservoir is positively correlated with the reservoir permeability and CO2 injection pressure. In the near-miscible flooding stage to miscible flooding stage, the flooding efficiency increases rapidly. After entering the miscible flooding stage, the growth rate in flooding efficiency decreases gradually with the increase in injection pressure.

Training set designs for prediction of yield and moisture of maize test cross hybrids with unreplicated trials.

Unreplicated field trials and genomic prediction are both used to enhance the efficiency in early selection stages of a hybrid maize breeding program. No results are available on the optimal experimental design when combining both approaches. Our objectives were to investigate the effect of the training set design on the accuracy of genomic prediction in unreplicated maize test crosses. We carried out a cross validation study on basis of an experimental data set consisting of 1436 hybrids evaluated for yield and moisture for which genotyping information of 461 SNP markers were available. Training set designs of different size, implementing within environment prediction, within year prediction, across year prediction, and combinations of data sources across years and environments were compared with respect to their prediction accuracy. Across year prediction did not reach prediction accuracies that are useful for genomic selection. Within year prediction across environments provided useful correlations between observed and predicted breeding values. The prediction accuracies did not improve when adding to the training set data from previous years. We conclude that using all data available from unreplicated tests of the current breeding cycle provides a good accuracy of predicting test crosses, whereas adding data from previous breeding cycles, in which the genotypes are less related to the tested material, has only limited value for increasing the prediction accuracy.