Min-max fuzzy model predictive tracking control of boiler-turbine system for ultra-supercritical units

To improve the control performance of nonlinear ultra-supercritical(USC)thermal power units,an improved min-max fuzzy model predictive tracking control(FMPTC)strategy is proposed.First,a T-S fuzzy model is established to approximate the dynamics of the nonlinear boiler-turbine system.Then,based on an extended fuzzy model containing state variables and output variables,a min-max FMPTC is derived for output regulation while ensuring the closed-loop system stability and the inputs in their given constraints.For greater controller design freedom,the developed controller adopts a new state-and output-based objective function.In addition,the observer estimation error is regarded as a bounded disturbance,ensuring the stability of the entire closed-loop control system.Simulation results on a 1000 MW USC boiler-turbine model illustrate the effectiveness of the proposed approach.

Exergy Analysis and Thermal Optimization of a Double-Turbine Regeneration System in a Ultra-Supercritical Double-Reheat Unit

Improving the primary steam parameters is one of the most direct ways to improve the cycle efficiency of a powergeneration system. In the present study, the typical problem connected to the excessively high superheat degree ofextraction steam in an ultra-supercritical (USC) double-reheat unit is considered. Using a 1000 MW power plantas an example, two systems (case 1 and case 2) are proposed, both working in combination with a regenerativesteam turbine. The thermal performances of these two systems are compared with that of the original systemthrough a heat balance method and an exergy balance strategy. The results reveal that the two coupled systemscan significantly reduce the superheat degree of extraction steam, turbine heat rate, and coal consumption of theunit and improve the energy utilization efficiency. These results will provide useful theoretical guidance to futureinvestigators wishing to address the general problem relating to energy conservation and modelling of the coupledextraction steam regenerative system of USC double-reheat units.

Fuzzy disturbance rejection predictive control of ultra-supercritical once-through boiler-turbine unit

In order to overcome the wide-range load tracking and unknown disturbance issues of an ultra-supercritical boiler- turbine unit, a fuzzy disturbance rejection predictive control approach is proposed using the techniques of fuzzy scheduling, model predictive control and extended state observer. Local state-space models are established on the basis of nonlinearity analysis and subspace identification. To eiJiance thedisturbance rejection capability of the controller, a extended state observer is employed to estimate unnown disturbances and model mismatches. The disturbance estimation ennaced local predictive controllers ae subsequently devised based on the local models, the performance of which is further strengthened by incorporating the fuzzy scheduling technique. The simulation results verify the merits of the proposed strategy in achieving satisfactory wide-range load tracking ad disturbance rejection performance.

Vibration of 1000-MW Ultra-Supercritical Turbine-Generator Unit with Simens Technology

The layout features of unit shafting and their effects on vibration, as well as evaluation criteria, were introduced for a 1000-MW ultra-supercritical turbine-generator unit with Simens technology. Based on vibration diagnosis and treatment for more than 10 units, some typical vibration faults were summarized, such as the vibration fluctuation of the high pressure (HP) rotor, abnormal vibration increases of the No.3 bearing pedestal and large vibration of the exciter rotor during its critical speed range. The vibration characteristics and the causes of faults and countermeasures were analyzed. Three applications for further illustration were given. The vibration fault identification method, control measures, and applications can provide a reference for vibration diagnoses and treatment of same type units.

Multi-model Predictive Control of Ultra-supercritical Coal-fired Power Unit

The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.

Sustained release of vascular endothelial growth factor A and basic fibroblast growth factor from nanofiber membranes reduces oxygen/glucose deprivation-induced injury to neurovascular units

Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.

The neurovascular unit-on-a-chip:modeling ischemic stroke to stem cell therapy

The neurovascular unit and stem cell therapy in ischemic stroke:Ischemic stroke,accounts for approximately 85% of all stroke incidents and is a major global health burden.It is the leading cause of disability and death worldwide,posing immense societal and economic challenges due to the long-term care required for stro ke survivors and the significant healthcare costs associated with its treatment and management(Amarenco et al.,2009).

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

GENERALIZED FORELLI-RUDIN TYPE OPERATORS BETWEEN SEVERAL FUNCTION SPACES ON THE UNIT BALL OF C^(N)

In this paper,we investigate sufficient and necessary conditions such that generalized Forelli-Rudin type operators T_(λ,τ,k),S_(λ,τ,k),Q_(λ,τ,k)and R_(λ,τ,k)are bounded between Lebesgue type spaces.In order to prove the main results,we first give some bidirectional estimates for several typical integrals.

基于Unity3D的油田抽油机三维可视化监控系统设计

针对抽油机监测形式单一、三维可视化程度低和联动性差的缺陷,引入信息―物理实时映射思想,开发了油田抽油机三维可视化监控系统。设计了抽油机数字空间,搭建虚实交互层设计架构;搭建三维可视化系统数据组成及关系框架;结合逆运动学,构建数学模型,基于五维模型和Unity 3D平台设计抽油机三维可视化系统总体架构;以游梁式抽油机为对象进行实验验证,实现了实时动态监测、虚实混合控制、运动轨迹追踪和在线预警等服务功能。为三维可视化监控在石油机械领域的落地应用和数字孪生系统的开发提供借鉴。

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Risk Factors for Mortality in Acute Kidney Injury in Intensive Care Units in Togo

Context: Acute kidney injury (AKI) in intensive care unit (ICU) is common and associated with very high mortality. In Togo, a tropical country with limited resources and only one nephrology department in the north, acute kidney injury seems to be a real tragedy with high mortality. Aims: to determine risk factors for mortality in acute kidney injury in the intensive care units. Methods and Material: We made a multicentric cross sectional study during 6 months in the four referral centers in northern Togo. Univariate and multivariate logistic regression was used to identify factors associated with mortality. Data were analyzed using RStudio 2023.04.1. Results: A total of 12.6% of patients admitted to intensive care had presented with AKI. The mean age was 49.6 ± 17.9. The sex ratio (M/F) was 2.1. Community-acquired AKI was in the majority (67.7%). Oligo anuria was the most frequent functional sign (38.4%). In our series, 81.6% of patients were in KDIGO stages 2 to 3. AKI was organic in 56.2% of cases. Mortality was 44.3%. In multivariate analysis, the main factors predictive of death were: respiratory distress (OR = 2.36;p Conclusions: Acute kidney injury in intensive care is common in northern Togo, and mortality is high. Identification of associated factors should help anticipate prognosis.

A Retrospective Analysis of Intoxicated Patients Admitted to the Intensive Care Unit: A Single-Institution Assessment in the Post-Pandemic Period

Background: The aim of this study was to evaluate the clinical and epidemiological characteristics of patients with acute intoxication admitted to the Intensive Care Unit (ICU). Material and Methods: An observational retrospective study was conducted on intoxicated patients who admitted to ICU between January 2022 and January 2024. Data were collected from the patients medical records. The demographic characteristics, causes of intoxications, clinical parameters, the mean stay in the ICU, treatment modalities and prognosis were recorded. Results: A total of 2875 critically ill patients were admitted during the study period, and 109 (3.79%) of them were acute intoxications. Their mean of ages was 38.09 ± 12.29. The female-to-male ratio was 1.37/1. Drugs were found to be the primary cause (62.39%) of intoxications, and analgesics, antidepressants, and antibiotics were the most frequent agents. Suicidal attempts were present in 66 patients, most of them were female (62.13%) and between 17 - 24 years (40.91%). The other common causes of intoxications were carbon monoxide (CO) (22.02%), methyl/ethyl alcohol (8.26%) and mushroom (5.50%). The mean stay in the ICU was 2.69 ± 0.89 days. Mechanical ventilation was applied to 10 of our patients. Renal replacement therapy was required in 6 patients. Despite all treatments, 6 of our patients died, and we found the mortality rate to be 5.50%. Conclusion: Intoxications were more frequent in young female patients and drugs were the most common cause with suicidal intent. Unfortunately, CO poisoning continues to be a very important problem in our city. These findings provided significant information about the characteristics of intoxications in Karabuk.

Cleaning of two mirrors in the first mirror unit using radiofrequency capacitively coupled plasma

First mirror(FM)cleaning,using radio frequency(RF)plasma,has been proposed to recover FM reflectivity in nuclear fusion reactors such as the International Thermonuclear Experimental Reactor(ITER).To investigate the influence of simultaneous cleaning of two mirrors on mirror cleaning efficiency and uniformity,experiments involving single-mirror cleaning and dual-mirror cleaning were conducted using RF capacitively coupled plasma in the laboratory.For the test and simultaneous cleaning of two mirrors,the FM and second mirror(SM),both measuring 110 mm×80 mm,were placed inside the first mirror unit(FMU).They were composed of 16 mirror samples,each with a dimension of 27.5 mm×20 mm.These mirror samples consist of a titanium-zirconium-molybdenum alloy substrate,a 500 nm Mo intermediate layer and a 30 nm Al_(2)O_(3) surface coating as a proxy for Be impurities.The cleaning of a single first mirror(SFM)and the simultaneous cleaning of the FM and SM(DFM and DSM)lasted for 9 h using Ar plasma at a pressure of 1 Pa.The total reflectivity of mirror samples on the DSM did not fully recover and varied with location,with a self-bias of−140 V.With a self-bias of−300 V,the total reflectivity of mirror samples on the SFM and DFM was fully recovered.The energy dispersive spectrometer results demonstrated that the Al_(2)O_(3) coating had been completely removed from these mirror samples.However,the mass loss of each mirror sample on the SFM and DFM before and after cleaning varied depending on its location,with higher mass loss observed for mirror samples located in the corners and lower loss for those in the center.Compared with SM cleaning,the simultaneous cleaning of two mirrors reduced the difference between the highest and lowest mass loss.Furthermore,this mass loss for the mirror samples of the DFM facing the DSM was increased.This indicated that mirror samples cleaned face to face in the FMU simultaneously could influence each other,highlighting the need for special attention in future studies.

One memristor–one electrolyte-gated transistor-based high energy-efficient dropout neuronal units

Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.

Counting the Unit Solutions of Certain Quartic Diagonal Congruence Modulo n

Given a positive integer n and the residue class ring Z_(n)=Z/nZ,we set Z_(n)^(x)to be the group of units in Z_(n),i.e.,Z_(n)^(x)={x∈Z_(n):ged(x,n)=1}.Let N_(m)(n)be the number of solutions of x_(1)^(4)+…+x_(m)^(4)≡0(mod n)with x_(1),…,x_(m)∈Z_(n)^(x).In this note,we determine an explicit expression of N_(m)(n).This extends the results of Sun and Yang in 2014.

Analysis of the Erosion-Corrosion Mechanism of the Air Cooler in a Hydrocracking Unit:A Numerical and Experimental Study

Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.

The Regulatory Role and Mechanism of Circadian Rhythm in Hemoglobin Co-cultured Neurovascular Unit

Objective Intracranial hemorrhage(ICH),the second most common subtype of stroke,exacerbates the disruption of the blood-brain barrier(BBB),leading to vasogenic edema,plasma protein extravasation,and infiltration of neurotoxic substances.The clearance capacity of the brain plays a crucial role in maintaining BBB homeostasis and facilitating patient recovery after hemorrhage.This study aimed to investigate the effect of circadian rhythms on BBB function,neuronal damage,and clearance capabilities.Methods The transwell model and hemoglobin were co-cultured to simulate the BBB environment after ICH.After intervention with different light groups,neuronal apoptosis was determined,glial phagocytosis was analyzed,the expression of endogenous clearing-related proteins aquaporin 4(AQP4)and low-density lipoprotein receptor-related protein 1(LRP1)was detected by western blotting and immunofluorescence dual standard method,and the expression of the tight junction protein occludin and melatonin receptor 1A(MTNR1A)was quantitatively analyzed.Results Circadian rhythms play a key role in maintaining the integrity of the BBB,reducing oxidative stress-induced neuronal damage,and improving microglial phagocytosis.Meanwhile,the expression of occludin and MTNR1A in neurovascular unit(NVU)co-cultured with hemoglobin improved the expression of AQP4 and LRP1,the key proteins in the NVU's endogenous brain clearance system.Conclusion Circadian rhythm(alternating black and white light)protects the NVU BBB function after ICH,promotes the expression of proteins related to the clearance of the hematoma,provides new evidence for the clinical treatment of patients recovering from ICH,and improves the circadian rhythm to promote brain metabolism and hematoma clearance.

Maternal Mortality Rates among Im/Migrant Populations in the United States

Introduction: Maternal mortality rates have more than doubled in the U.S over the last two decades, making it one of the few places in the world where maternal mortality is increasing. Differences in maternal mortality among certain races and ethnicities are known but few studies examine maternal mortality among immigrants. Since immigrants represent 13.7% of the U.S. population, it is essential to examine immigrant subsets to understand maternal mortality among this vulnerable population. Methods: A literature search identified 318 articles on maternal mortality and immigrants, with 12 articles from the U.S. The keywords included maternal mortality, United States, migrants, asylum seekers, immigrants, and disparities. Maternal mortality statistics were obtained from the World Health Organization and Center for Disease Control. Results: Studies analyzed in this review found an overall lower maternal mortality rate among immigrant women compared to U.S.-born women, except for Hispanic immigrant women. Black women had the highest maternal mortality rate, regardless of immigration status. Conclusion: Although the literature points to lower maternal mortality among immigrants, the data is still somewhat mixed, making it challenging to draw comprehensive conclusions. Additional research examining maternal mortality among Im/migrants in the U.S. is needed to guide future training among healthcare professionals and policymakers.