Load Factor Research Articles

Analysis and Design of Cable Stayed Bridge

Cable Stayed Bridges are one of the most fascinating icons in the field of Engineering and are commonly used bridge typologies for spans between 200m and 1100mm due to their structural efficiency, cost and aesthetics. The basic structural form of a cable-stayed bridge is a series of overlapping triangles comprising the pylon, the cables, and the girder. All these members are under predominantly axial forces, with the cables under tension and both the pylon and the girder under compression. Axially loaded members are generally more efficient than flexural members. This contributes to the economy of the bridge. In this project, we have made an attempt to analyses a 200m span Cable Stayed Bridge using the STAAD Pro software based on the design parameters which includes the bending moment, shear force and displacement, Reaction Graph, Total Quantity Materail, etc. Key Words: Cable Stayed Bridges, Unknown Load Factor Optimization, Construction Stage Analysis, Influence Line Diagram (ILD), SFD BMD Diagram, Analysis Design.

Exploring gradual material rigidity degradation effects on the nonlinear coupled axial-transversal nonlinear response of a capacitive micro-beam

The accumulation of damage in materials due to crack propagation can lead them to unpredicted failures. This phenomenon is particularly relevant in materials science, engineering, and other fields where structures or components are subjected to repeated loading, cyclic stresses, or environmental factors. In this paper, the mechanical behavior of a microelectromechanical system subjected to cyclic loads has been modeled, when the stiffness of the material gradually is decreased. As a case study the dynamic response of a micro-beam to DC bias voltage as a static load and AC harmonic voltage as a cyclic load has been studied. The nonlinear coupled equations have been formed and converted to time-dependent ones using a spatial discretization method. Due to long-term integration over time, to achieve more accurate results besides direct 4th order Runge-Kutta integration method, a temporal decomposition method has been used to solve the coupled nonlinear ordinary differential equations. To realize this method, a temporal decomposed solution based on the physical nature of the problem is presented in the form of slow-growing terms and fast-altering harmonic terms with gradually-growing amplitudes. To find the coefficient of these terms a least square method has been utilized to minimize a cost function in a given dynamic time-interval, where the independency of the results to this interval has been assessed. Also, the nonlinear frequency behavior of the proposed model has been studied when the system has suffered various damages. Due to considering gradual rigidity degradation of the material interesting dynamic responses have been observed, that can help to expand the insight in the design of structures.

Inflow and outflow properties, not total gas fractions, drive the evolution of the mass–metallicity relation

ABSTRACT Observations show a tight correlation between the stellar mass of galaxies and their gas-phase metallicity (MZR). This relation evolves with redshift, with higher redshift galaxies being characterized by lower metallicities. Understanding the physical origin of the slope and redshift evolution of the MZR may provide important insight into the physical processes underpinning it: star formation, feedback, and cosmological inflows. While theoretical models ascribe the shape of the MZR to the lower efficiency of galactic outflows in more massive galaxies, what drives its evolution remains an open question. In this letter, we analyse how the MZR evolves over z = 0–3, combining results from the FIREbox cosmological volume simulation with analytical models. Contrary to a frequent assertion in the literature, we find that the evolution of the gas fraction does not contribute significantly to the redshift evolution of the MZR. Instead, we show that the latter is driven by the redshift dependence of the inflow metallicity, outflow metallicity, and mass loading factor, whose relative importance depends on stellar mass. These findings also suggest that the evolution of the MZR is not explained by galaxies moving along a fixed surface in the space spanned by stellar mass, gas-phase metallicity, and star formation rate.

Characterization testing of the Northrop Grumman MiniCoolerPlus (MCP)

Northrop Grumman Space Park (NGSP) introduced the Mini Cooler Plus (MCP) to their family of pulse tube cryocoolers in 2019 [1] and presented the details of its TRL6 qualification testing in 2022 [2]. The thermal mechanical unit (TMU) of the MCP is an extension of space-qualified pulse tube coolers, all of which are designed to provide a long life (ten-plus years) of delivering low-mass, high-cooling capacity for hyperspectral and infrared imaging payloads in tactical airborne and space applications. The cooler is of modular split configuration allowing flexibility in the compressor (wave generator) and cold head placements to meet the available envelope of packaging constraints. The cold head assembly can be oriented at any position relative to the compressor assembly, and the transfer line (length and shape) can be customized to individual applications. The TMU (thermo-mechanical unit) weighs less than 3kg and can lift 1.5 W at 45 K or 11 W at 110K with 150 W electrical input at 300 K reject. The thermal performance has been characterized as a function of input voltage and as a function of cold tip load and temperature at variety of heat sink temperatures of -20C, 0C, +20C and +40C. Functional testing of the MCP was performed to higher input powers and MCP performance data versus operating conditions were collected. An analytical expression for cold tip load (Qc), impedance (Z) and power factor (PF) as a function of reject temperature (Trej), cold tip temperature (Tc), frequency (f), and input power (Pac) were generated. These tests were repeated with third party control electronics. All results will be presented here.

Risk-based life cycle cost–benefit analysis for progressive collapse design of RC frame structures

Progressive structural collapse is a typical low-probability high-consequence event. Progressive collapse design can effectively improve the robustness of structures against accidental local damage and reduce the probability of collapse. However, progressive collapse design also increases the construction cost of buildings. Hence, it is necessary to conduct cost-benefit analyses for the progressive collapse design of building structures. This study first designs a reinforced concrete (RC) frame based on a progressive collapse design program that simultaneously optimizes material consumption and structural resistance. Then, the structural failure probability is quantified using an alternative path (AP) method-based fragility analysis that considers the structural uncertainties. Based on this, the life cycle costs and benefits of the structure designed with different design load factors are investigated. A four-story RC frame is used as an example. By considering the time value of money and threat probability, the break-even points and optimized design load factors for the progressive collapse design of the RC frame are analyzed. These research outcomes can help promote progressive collapse design in engineering practice and provide references for proposing scientific and reasonable design load factors.

Spatial assessment of pollutant loads for surface water quality management: a case study in Lai Chau city, Vietnam

The aim of this study is to present a method for estimating the pollutant load from different sources in an effort to provide improved information regarding water pollution and help control the surface water pollution, using Lai Chau city as a case study. The pollutant load was calculated in accordance with the Vietnam Environment Administration Decree No.154/2019 on the guidance for calculating the total pollutant load of river water. The pollutant sources include point sources (domestic wastewater, animal husbandry, industrial complexes and economic services) and surface sources (run-off from agricultural land uses) that generate wastes that potentially contaminate water bodies. The source locations were mapped and spatially joined with the drainage-basin map delineated from a Digital Elevation Model (DEM) to calculate the loads for the sub-basin units. Multivariate analysis then showed that the farming and domestic sources had the strongest positive loading factors for the sub-basins located in the city center and its fringe areas. Of these waste from animal husbandry account for up to 75.1% of total pollutant load. The main conclusion from the study’s results is that the management approach should be changed from the total controlling mode, which is currently applied in the city, to a source specific approach based on the pollutant discharge loads and the allocated capacities.

Nodal price-based demand response management via orderly time-of-use strategy for an unbalanced isolated microgrid considering voltage stability constraints

This paper scrutinizes the compatibility of voltage stability criteria with price-based demand response management (DRM) for a large-scale isolated microgrid considering severe dependency of constant-impedance loads (CILs) on nodal voltage magnitude. Meanwhile, a hybrid nodal pricing (HNP) scheme is developed to determine clearing prices for resources and time-of-use (TOU) tariffs for price-responsive loads. The proposed framework is composed of three ingredients including two optimization molds with the objective of actual net profit and recast operation expense sequentially solved in an iterative process together with one pay-off module. The energy schedules, unbalanced voltages and nodal prices are determined considering intermittency of renewable resources, unbalances, circuit limitations, and reactive power requirements. Two bus and line voltage stability indices as well as voltage profile management criterion are used to prevent voltage instability. Thus, load profile is corrected such that voltage stability can be upheld as well. The proposed method is implemented via a modified CIGRE benchmark. The simulation results demonstrate that load factor improves at least 4.30% under desirable stability margins. Moreover, total energy loss and line voltage unbalance rate (LVUR) decrease at least 1.02% and 10.03% respectively.

The law of infrared radiation generation and evolution of coal-rock fracture under load

In order to study the formation mechanism and evolution law of infrared radiation (IR) of coal-rock. A mathematical model of pressure-IR for coal-rock under loading conditions was developed based on theories such as frictional heat generation and heat conduction. The results indicate that: (1) IR and stress exhibit a one-dimensional quartic function relationship, which is consistent with the strong correlation shown by the experimental data curve. As the loading stress increases, the infrared radiation temperature of the coal-rock surface increases. (2) From the simulation results, it can be seen that the increase in surface temperature of coal-rock is essentially influenced by the heat transfer of internal heat sources. The trend of temperature fluctuations is similar for both, with both increasing with ambient temperature and loading rate. And this characteristic change is independent of external loading factors. (3) The IR temperature varies in stages under different loading conditions. In addition, the surface temperature of the coal-rock before fracturing is affected by the frictional heat generation between cracks, resulting in an overall upward trend. When it is about to break, a precursor to the fracture appears. The final IR on the surface of coal-rock increased by 0.04–0.13 °C, which is consistent with the simulation results. It is consistent with the simulation results and reveals the evolution law of IR. The results of this work provide theoretical evidence for the prediction of dynamical disasters in coal and rocks.

Dynamic Load Analysis of Mine-Truck Using Multibody Dynamic Analysis Method

Abstract: Vehicle load distributed on front & rear axle assembly during various working conditions is one of the most important factors influencing working performance and service life of drive axle assembly. The dynamic load on axle assembly is higher compared to the rated load because of variations in vehicle speed and road surface conditions. Early failure of structural components is caused because of higher dynamic reaction forces due to uneven road profiles. The dynamic load calculation of axle assembly is presented in this paper for a Mine-truck with various road conditions and vehicle speeds. The road load conditions consist of grade, bump & path hole. Mine-truck with payload capacities of 63 Ton is considered for the study. The behaviour of vertical force is calculated for different vehicle speeds (3 - 12 km/hr.) of the machine on the front & rear axle assembly during running conditions. Multi-body dynamic Analysis tool ADAMS is used for this study. ADAMS helps to study the dynamics of moving parts and load distribution throughout mechanical systems during motion. The Mine-truck3D model was created with the help of computer-aided design (CAD) software. Major units of Mine trucks are considered to prepare 3D models like Cabin-engine mass, Bucket, front axle assembly, rear Axle assembly & tires. Multi-body vehicle models are prepared in simulation software ADAMS by importing 3D models prepared by computer-aided design (CAD) software. This provides guidelines for selecting dynamic load factors while designing structural parts of the vehicle.

A review: plastic analysis in structures

Purpose Brief introduction on the importance and the need for plastic analysis methods were presented in the beginning section of this review. The plastic method for analysis was considered to be the more advanced method of analysis because of its ability to represent the true behaviour of the steel structures. Then in the following section, a literature analysis has been carried out on the previous investigations done on steel plates, steel beams and steel frames by other authors. The behaviour of them under different types of loading were presented and are under the investigation of innovative new analysis methods. Design/methodology/approach Structure member connections also have the potential for plastic failure. In this study, the authors have highlighted a few topics to be discussed. The three topics in this study are T-end plate connections to a square hollow section, semi-rigid connections and cold-formed steel storage racks with spine bracings using speed-lock connections. Connection is one of the important parts of a structure that ensures the integrity of the structure. Finally, in this technical paper, the authors introduce some topics related to seismic action. Application of the Theory of Plastic Mechanism Control in seismic design is studied in the beginning. At the end, its in-depth application for moment resisting frames-eccentrically braced frames dual systems is investigated. Findings When this study involves the design of a plastic structure, the design criteria must involve the ultimate load rather than the yield stress. As the steel behaves in the plastic range, it means the capacity of the steel has reached the ultimate load. Ultimate load design and load factor design are the methods in the range of plastic analysis. After the steel capacity has reached beyond the yield stress, it fulfills the requirement in this method. The plastic analysis method offers a consistent and logical approach to structural analysis. It provides an economical solution in terms of steel weight, as the sections designed using this method are smaller compared with elastic design methods. Originality/value The plastic method is the primary approach used in the analysis and design of statically indeterminate frame structures.

Exploratory Factor Analysis for Items Measuring of The Tax Auditors’ Performance

Tax auditors play an essential role in tax audits to ensure governments can overcome non-tax compliance issues and protect tax revenues for the nation. Tax auditors are expected to perform their tasks efficiently and effectively in examining the taxpayer’s declaration. The tax auditors' performance determines the success of tax audit implementation. Several factors can influence the tax auditors’ performance, including auditors’ effort, professional skepticism and task complexity. Therefore, this study aims to develop a valid and reliable research instrument to measure tax auditors’ performance using the Exploratory Factor Analysis and internal reliability test (Cronbach’s Alpha). A total of 100 tax auditors from the Inland Revenue Board of Malaysia and the Royal Malaysian Customs Department were selected as respondents to participate in this study. The data was collected using the online Google Forms with 5 Likert scales and was analysed using IBM-SPSS Version 27. The results show that out of 34 developed items, only 30 remained as constructed items. The remaining items were deleted due to the low loading factor of less than 0.40. Thus, this study validated the research instrument to proceed with the Confirmatory Factor Analysis (CFA) in the following step using the validated research instrument.

Development and validation of a scale to measure social isolation in adolescents.

There is a lack of questionnaires specifically designed to assess social isolation in adolescents. We developed and validated a self-report measure of social isolation in adolescents, the Social Isolation Questionnaire (QIS). A literature review on social isolation and mental health in adolescents indicated 20 questions to form QIS. Two cross-sectional surveys with 48 and 1135 adolescents, respectively, evaluated the reproducibility and validity of QIS. The Bland-Altman plot did not indicate a systematic difference between measurements 15 days apart. Bartlett's sphericity test verified a correlation between the questions and the Kaiser-Meyer-Olkin test showed good adequacy (.896) to the factor analysis. Exploratory factor analysis suggested the exclusion of three questions (loading factors <0.3), and eigenvalues (4.9-0.8) indicated that the questionnaire should be composed of three factors (dimensions). The Cronbach's alpha indicated high internal consistency of the 17 questions (0.850 overall; Dimensions: 0.815 'feeling of loneliness'; 0.760 'friendship'; and, 0.680 'Family support'). The QIS score ranged from 0 to 131 (maximum social isolation score). The correlation between QIS and depressive symptoms (r = .543) indicated the construct validity of QIS. We evaluated QIS in the Portuguese version, thus translation and cultural adaptation are necessary to evaluate the questionnaire in other settings. We constructed and validated the QIS questionnaire, a self-administered questionnaire to assess social isolation in adolescents, composed of three dimensions; feelings of loneliness, friendship and family support. The QIS questionnaire seems a very promising tool to support practitioners and researchers in assessing social isolation among adolescents.

An Indonesian Version of Mental Toughness Index: Testing Psychometric Properties in Athletes and Non-athletes

To date, the mental toughness index (MTI) has been adopted in five different languages ​​but there has been no attempt to adapt and test it in the Indonesian context. On the other hand, the study of mental toughness is experiencing an upward trend but there are problems with the measurement tools used. This research aims to adapt and test the MTI to the Indonesian context by involving athletes and non-athletes as well as gender differences. There were 400 participants, with details of the athlete group = 211 people (Mage = 19.18 years, SD = 1.06, Male = 146, Female = 65), non-athlete group = 189 people (Mage = 23.38 years, SD = 7.11, Male = 144, Female = 45), and based on gender, male = 290 people (Mage = 21.38 years, SD = 5.41), while female = 110 people (Mage = 20.61 years, SD = 5.24). MTI was tested using confirmatory factor analysis (CFA) with maximum likelihood (ML) assisted by the IBM SPSS v.26 and IBM Amos v. programs. 22. Overall, the Indonesian version of MTI (MTIid) shows model fit, namely the values ​​obtained are CFI = .967, TLI = .954, GFI = .966, SRMR = .034, and RMSEA = .069. Eight items in the MTIid have a convergent validity value that is statistically significant (p &lt; 0.001) and the loading factor is very good (λ = .563 to .759), three items are in the excellent category, two items are very good, and three items are good. The internal consistency reliability of the MTIid was excellent (CR = .864; α = .862). MTIid is a valid and reliable measuring tool for measuring aspects of mental toughness, both in groups of athletes and non-athletes and based on gender differences (male and female). Keywords: Mental toughness, psychometric, validation, sport psychology, athlete, non-athlete.

Cannabinoid receptors as new targets for HTLV-1 associated myelopathy (HAM/TSP) treatment

Background/AimThe roles of endocannabinoids are described in immune modulation and neuroprotection. HTLV-1-associated myelopathy (HAM/TSP) is an inflammatory neurodegenerative disease. Therefore, in this study, the interactions of HTLV-1 regulatory factors and host cannabinoid receptors (CBRs) were evaluated in HAM/TSP. MethodsNineteen HAM/TSPs, 22 asymptomatic carriers (ACs), and 18 healthy controls (HCs) were enrolled. RNA was extracted from PBMCs and then reverse-transcribed to cDNA. The gene expression of CB1R and CB2R, as well as HTLV-1 proviral load (PVL), Tax and HTLV-1 basic leucine zipper factor (HBZ) were assessed by RT-qPCR. ResultsThe mean expression of CB1R in ACs (8.51 ± 2.76) was significantly higher than HAMTSPs (1.593 ± 0.74, p = 0.05) and also HCs (0.10 ± 0.039, p = 0.001). The CB2R gene expression level in ACs (2.62±0.44) was significantly higher than HAM/TSPs (0.59 ± 0.15, p = 0.001) and HCs (1.00 ± 0.2, p = 0.006). Meanwhile there was a strong correlation between CB1R and CB2R gene expression levels in the HCs and HAM/TSPs (p = 0.001). HTLV-1-Tax expression in HAM/TSPs (386 ± 104) was higher than ACs (75 ± 32) and statistically significant (p = 0.003). While HTLV-1-HBZ was only expressed in three AC subjects and five HAM/TSPs, thus it cannot be analyzed. ConclusionThe up-regulation of CB2R has immunomodulatory effects in inflammatory reactions. While CB1R as a neuroprotective agent may suppress inflammatory reactions in ACs, preventing HAM/TSP. It seems that, like multiple sclerosis (MS), cannabinoid medications are beneficial in HAM/TSP.

Identification of Potential Injury Risk Factors and Prediction Model Construction of Athletes using Data Mining Algorithm

Identification of potential injury risk factors and construction of prediction models for athletes using data mining algorithms involve analyzing various factors such as biomechanical, physiological, and environmental variables to determine their correlation with injury occurrences. Data mining techniques, such as decision trees, logistic regression, or neural networks, are then applied to identify patterns and relationships within the data. By integrating this information, predictive models can be developed to forecast the likelihood of athletes sustaining injuries based on their individual characteristics and training conditions. This paper introduces a novel approach for athlete injury risk prediction using the Noninvasive Data Mining Model with Multi-relational and Multi-dimensional Clustering (Ni-DMMMC) algorithm. By leveraging advanced data mining techniques, Ni-DMMMC aims to identify hidden relationships between various athlete characteristics, including biomechanical risk, training load, physiological markers, and environmental factors, to predict injury susceptibility accurately. Through multi-relational and multi-dimensional clustering, the algorithm effectively categorizes athletes into distinct clusters based on their unique risk profiles. These clusters provide valuable insights into the diverse injury risk profiles present within athlete populations, enabling targeted intervention strategies and personalized athlete management approaches. The proposed approach holds significant promise for enhancing injury prevention efforts, optimizing athlete performance, and improving overall well-being in sports medicine practice. athletes in Cluster 1 exhibit high biomechanical risk (0.85), moderate training load (0.60), low physiological markers (0.25), and moderate environmental risk (0.45), while athletes in Cluster 2 display moderate biomechanical risk (0.70), high training load (0.90), high physiological markers (0.80), and low environmental risk (0.30). These numerical values serve as indicators for assessing an athlete's injury risk profile comprehensively.

A novel collision detection method based on current residuals for robots without joint torque sensors: A case study on UR10 robot

Existing model-based collision detection methods rely on accurate torque dynamic parameters identified using measured joint torques. However, for robots lacking joint torque sensors, only joint currents can be measured, and joint torques must be estimated through the linear relationship between joint currents and joint torque constants. This way can lead to cumulative identification errors in torque dynamic parameters, thereby diminishing the performance of model-based collision detection algorithms. To tackle this challenge, this article proposes an innovative collision detection method based on current residuals, which represent the disparities between measured joint currents and predicted joint currents computed by current dynamic parameters. Then, a dynamic threshold method for current residuals is designed to mitigate the impact of modeling errors at zero-speed direction changes on collision detection performance. Additionally, a suppression strategy based on online load identification and compensation is introduced to reduce the interference of non-collision load factors on collision detection signals. The proposed method mitigates the accumulation of errors on torque dynamic identification resulting from inaccuracies in joint torque constants, ultimately enhancing collision detection performance for robots without joint torque sensors. Extensive experiment results validate the correctness and effectiveness of this approach.

Effect of Full Implementation of Domestic Solar Water Heaters on the Electricity Peak Load in Libya

Electricity plays an important role in the contemporary life, and it has become indispensable nowadays. Reducing the peak electricity load and increasing the load factor have been considered as one of the main tasks that have to be accomplished by both electricity generation-side and demand-side managements.The residential sector of Libya consumes over 31% of the total sold electricity, and 29.8% of that is delivered to the electric water heating load. This is an inefficient way of electricity utilization. Usually, the electricity supplier in Libya used to increase the local generation capacity or import electricity from neighboring countries. Both solutions did not resolve the problem. This work attempts to investigate the effect of replacing electric water heaters in the residential sector of Libya by solar water heaters on reducing the electricity peak load and increasing the load factor. The results show that on average 3% of the peak load demand can be saved. This is equivalent to 149.5 MW of reduced power. The study also revealed that the annual amount of energy saved is up to 2.55TWh, and the load factor is improved by 2% (i.e. from 65% to 67%). This saved energy is equivalent to a power plant with a nominal capacity of 448 MW considering a load factor of 0.65.

Высокотехнологичное автосборочное производство

In modern automotive production, high-tech robotic complexes and assembly lines are widely used for all four main production stages: pressing, welding, coating and assembly. The paper views industrial robot-assisted high-tech incomplete vehicle production using robotic manipulators. Studies have been conducted on the efficiency and productivity of automotive production through the use of a robotic assembly. Studies have been conducted on the efficiency and productivity of automotive production using a robotic assembly. A brief overview of scientific works on automation of production using robotic systems is presented. The discussed robotic complexes include various robots: assemblers, manipulators, auxiliary robots. The payback period of the robotic complex ranges from three to five years. Robotic complexes are successfully used in various factories, e.g. 115 robots are used at Volkswagen, 112 robots are used at Renault, 106 robots are used at Nissan. The average time period for assembling one basic vehicle product at the factory is 25 hours. The main characteristics of a robotic automobile assembly such as cycle of the assembly line; work pace; assembly line load factor are viewed. The influence of the main characteristics of the assembly line on productivity in robotic automotive production is estimated. The results show an increase in product output of up to 10% with an increase in the load factor by one tenth. The robotic assembly line efficiency calculation for automotive production shows that within five years the increase in net profit when using just one robotic assembly line will amount to about five million rubles. In addition, the output of products will significantly increase with RPA in automotive production. The effectiveness of using a robotized assembly line in automotive production is also shown.

Role of BP-ANN in simulating greenhouse gas emissions from global aquatic ecosystems via carbon component-environmental factor coupling

Inland waters (IW), estuarine areas (EA), and offshore areas (OA) function as aquatic systems in which the transport of carbon components results in the release of greenhouse gases (GHGs). Interconnected subsystems exhibit a greater greenhouse effect than individual systems. Despite this, there is a lack of research on how carbon loading and its components impact GHG emissions in various aquatic systems. In this study, we analyzed 430 aquatic sites to explore trade-off mechanisms among dissolved organic carbon (DOC), particulate organic carbon, dissolved inorganic carbon (DIC), and GHGs. The results revealed that IW emerged as the most significant GHG source, possessing a comprehensive global warming potential (GWP) of 0.78 ± 0.08 (10−2 Pg CO2-ep ha−1 year−1) for combined carbon dioxide, methane, and nitrous oxide. This surpassed the cumulative potentials of EA and OA (0.35 ± 0.05 (10−2 Pg CO2-ep ha−1 year−1)). Additionally, structural equation modeling indicated that GHG emissions resulted from a combination of carbon component loading and environmental factors. DOC exhibited a positive correlation with GWPs when influenced by biodegradable DOC. Total alkalinity and pH influenced DIC, leading to elevated pCO2 in aquatic systems, thereby enhancing GWPs. Predictive modeling using backpropagation artificial neural networks (BP-ANN) for GWPs, incorporating carbon components and environmental factors, demonstrated a good fit (R2 = 0.6078, RMSEaverage = 0.069, p > 0.05) between observed and predicted values. Enhancing the estimation of aquatic region feedback to GHG changes was achieved by incorporating corresponding water quality parameters. In summary, this study underscores the pivotal role of carbon components and environmental factors in aquatic regions for GHG emissions. The application of BP-ANN to estimate greenhouse effects from aquatic regions is highlighted, providing theoretical and experimental support for future advancements in monitoring and developing policies concerning the influence of water quality on GHG emissions.

Multi-objective optimization of farmland water level and nitrogen fertilization management for winter wheat cultivation under waterlogging conditions based on TOPSIS-Entropy

Aiming at the problems of reduced winter wheat yield and aggravation of nitrogen leaching pollution caused by the waterlogging in the Middle-Lower Yangtze Plain, China, a two-year field experiment with three farmland water levels (W40, W60, W80) and three nitrogen application rates (N150, N225, N300) as well as a non-waterlogged treatment (CK) was carried out, to investigate the coupling effects of farmland water level and nitrogen application rate on the plant growth, grain yield, crop water productivity (WPC) and nitrogen load with waterlogging conditions. Three man-made waterlogging events were applied at winter wheat jointing-booting stage, heading-flowering stage and grain filling stage, respectively. The results indicated that with the farmland water level decreased from −40 cm to −60 cm and the nitrogen application rate increased from 150 kg∙ha−1 to 225 kg∙ha−1, the plant height, aboveground dry matter, leaf area index, spike length, grain yield, effective panicles, grain number per ear, 1000-grain weight and WPC in the waterlogging field increased significantly. However, since the nitrogen application rate exceeded 225 kg∙ha−1 and farmland water level lowered more than −60 cm, the favorable effects of nitrogen application rate and farmland water level for winter wheat growth and production reduced. Additionally, both the nitrogen load and partial factor productivity of nitrogen (PFPN) increased with the decline of farmland water level, while the nitrogen load increased and the PFPN decreased with the increasing nitrogen application rate. The raise of nitrogen rate from 150 kg∙ha−1 to 225 kg∙ha−1 was beneficial to plant growth, however, the increase of nitrogen application resulted in the decrease of PFPN and increase of drainage nitrogen loads. Compared with the water farmland water level of −40 cm and nitrogen application rate of 150 kg∙ha−1, the increase of nitrogen application rate and the decrease of farmland water level in the range of 50%-100% resulted in yield raise by 5.78%-32.29% approximately and the increase of nitrogen load by 36.20%-178.44% approximately. The comprehensive evaluation with TOPSIS-Entropy method for plant growth, grain yield, WPC, PFPN and nitrogen loads suggested that, the appropriate nitrogen application rate for winter wheat in the waterlogging areas of Middle-Lower Yangtze Plain in China was 225 kg∙ha−1, and the proper farmland water level was lowering to −80 cm in wet year and −60 cm in dry year within 3 days after waterlogging.