Net Speed Research Articles

Changes in Water Surplus or Deficit and Possible Drivers in the North China Plain During 1961–2022

ABSTRACTIn the North China Plain (NCP), the assessment of water surplus or deficit (WSD), which is calculated as precipitation minus reference evapotranspiration (ET0), holds significant implications for water resource management and agricultural irrigation decision‐making, given the region's long‐standing severe shortage of water resources. However, the magnitude, trend and climatic drivers of WSD remain poorly understood in the NCP. This study analysed the spatial and temporal characteristics of WSD, and quantified the contribution of climatic factors to WSD based on the sensitivity and contribution rate analysis methods with climatic data from 75 meteorological stations. The result showed that: (1) Annual WSD decreased mainly in northeastern NCP and increased significantly in southern NCP during 1961–2022. Annual WSD increased slightly from 1961 to 2022 at a rate of 1.63 mm a−2 mainly due to the more significant decrease (−1.88 mm a−2) in ET0 compared to precipitation (−0.25 mm a−2). (2) In terms of the sensitivity of WSD to climatic factors, relative humidity had the highest sensitivity, followed by net radiation, wind speed, precipitation and average air temperature. (3) Significant declines of wind speed were the most dominant factor affecting WSD variation in most part of NCP during most of a year, and net radiation of four stations in the western high‐elevation regions played the most important role. This study enhances comprehension of the impact of climate change on WSD in the NCP and provides a reference for improving management of agricultural water resources under NCP's evolving climatic conditions.

Evaluation of crop water stress index of wheat by using machine learning models.

The Crop Water Stress Index (CWSI), a pivotal indicator derived from canopy temperature, plays a crucial role in irrigation scheduling for water conservation in agriculture. This study focuses on determining CWSI (by empirical method) for wheat crops in the semi-arid region of western Uttar Pradesh, India, subjected to varying irrigation treatments across two cropping seasons (2021-2022 and 2022-2023). The aim is to investigate further the potential of four machine learning (ML) models-support vector regression (SVR), random forest regression (RFR), artificial neural network (ANN), and multiple linear regression (MLR) to predict CWSI. The ML models were assessed based on determination coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE) under diverse scenarios created from eight distinct input combinations of six variables: air temperature (Ta), canopy temperature (Tc), vapor pressure deficit (VPD), net solar radiation (Rn), wind speed (U), and soil moisture depletion (SD). SVR emerges as the top-performing model, showcasing superior results over ANN, RFR, and MLR. The most effective input combination for SVR includes Tc, Ta, VPD, Rn, and U (R2 = 0.997, MAE = 0.901%, RMSE = 2.223%). Meanwhile, both ANN and MLR achieve optimal results with input combinations involving Tc, Ta, VPD, Rn, U, and SD (R2 = 0.992, MAE = 2.031%, RMSE = 3.705%; R2 = 0.759, MAE = 13.95%, RMSE = 19.98%, respectively). For RFR, the ideal input combination comprises Tc, Ta, VPD, and U (R2 = 0.951, MAE = 5.023%, RMSE = 9.012%). The study highlights the considerable promise of ML models in predicting CWSI, proposing their future application in integration into an irrigation decision support system (IDSS) for crop stress mitigation and efficient water management in agriculture.

Spatiotemporal evolution of dry and wet and quantitative analysis of the influence of meteorological factors based on MI and the FAO P–M model

The frequent occurrence of extreme climate events disrupts the regional water budget balance and leads to changes in the dry and wet conditions of the surface, making the water surplus and deficit more complex and variable. To explore the quantitative relationship between the spatiotemporal evolution of dry and wet conditions and meteorological factors in the Hexi Corridor under changing environmental conditions, the relative moisture index (MI) and FAO Penman–Monteith (FAO P–M) model were combined to construct a partial differential quantitative attribution model for dry and wet variations affected by climate factors in the Hexi Corridor. The results show that: (1) MI in the Hexi Corridor increased significantly (Z = 2.341) during 1960–2019, showing a wet-trend change, and the degree of drought increased from southeast to northwest in the Hexi Corridor. (2) The order of drought degree in four seasons is as follows: winter (− 0.95), spring (− 0.93), autumn (− 0.89) and summer (− 0.83). (3) The frequency of extreme drought, severe drought, moderate drought, and mild drought within 60 years of 21 meteorological stations accounted for 28.38%, 50.48%, 8.85%, and 7.38%, respectively, and the frequency above severe drought was the highest. (4) The sensitivity of meteorological factors gradually increased from northwest to southeast, and MI was the most sensitive to the change of precipitation (P), followed by net radiation (Rn), wind speed (u2), mean temperature (Tmean), relative humidity (RH) and maximum temperature (Tmax). MI was the least sensitive to the change of minimum temperature (Tmin). P is the most important meteorological variable that contributes to the increase of MI, followed by u2, Tmean, and Tmin. Rn, Tmax, and RH have the least influence, and the total contribution of the seven meteorological factors is 85.59%. Compared with the reference evapotranspiration, P is the main factor affecting the dry and wet variations in Hexi Corridor.

The synthesis of potential factors contributing to the asynchronous warming between air and shallow ground since the 2000s on the Tibetan Plateau

Atmospheric conditions, topsoil properties and land cover conditions play essential roles in ground surface temperature (GST), surface air temperature (SAT) and their differences (GST-SAT). They determine the strength of the thermal forcing of the lower atmospheric boundary and the distributions of frozen ground in cold regions. However, the relative importance of these factors at various time scales and the underlying physical mechanisms remain less well understood. Here, we investigate the spatiotemporal patterns of GST-SAT and examine 11 potential factors in three categories in influencing the GST-SAT variations from 1983 to 2019 over the Tibetan Plateau (TP) using boosted regression tree models. The results show that the TP has experienced asynchronous warming in GST and SAT since 2001: a warming hiatus in SAT but continued warming in GST, resulting in a significantly increasing trend in GST-SAT. The relative importance of the three categories that influence the GST-SAT spatial variation was: atmospheric variables (56.1 %) > shallow soil properties (24.4 %) > interfacial land cover features (19.5 %). The importance of the factors also varied with the combinations of annual, seasonal, daily, day-time and night-time time scales, manifested by positive or negative effects. The interdecadal changes of net radiation, precipitation, wind speed and soil moisture amplified the asynchronous warming between air and shallow ground over the TP since the 2000s. These findings provide an in-depth understanding of the spatiotemporal variations of GST-SAT and the underlying mechanisms. This study will benefit the development of the Earth system models on the TP.

An observational study on the microclimate and soil thermal regimes under solar photovoltaic arrays

The high demand for low-carbon energy sources to mitigate climate change has prompted a rapid increase in ground-mounted solar parks. The implementation of photovoltaic (PV) significantly impacted the local climate and ecosystem, which are both poorly understood. To investigate the effects of a typical solar park on the Gobi ecological system, local microclimate and soil thermal regimes were measured year-round under and between PV arrays, at an applied solar park sited in Xinjiang, China. Our results demonstrated their seasonal and diurnal changes. Under solar PV arrays, the mean annual net radiation and wind speed decreased by 92.68 % and 50.53 % respectively. In contrast, PV panels caused an increase of the rear sides air by 10.12 % with 0.87 °C. South-facing PV panels reduced wind speed with the prevailing northerly wind below. In addition, the relative humidity rapidly decreased when snow covered the ground, but slightly increased from April to September. We found the soil under PV panels was cooler and tended to be a sink of energy during spring and summer whereas was more often a source during autumn and winter compared with the soil between PV panels. Observed data developed the understanding of the energy processes of solar parks in Gobi ecosystems and provided evidence to support the sustainable management of the solar park.

The Importance of Heat Storage for Estimating Lake Evaporation on Different Time Scales: Insights From a Large Shallow Subtropical Lake

AbstractThe change in heat storage (Gc) is an essential component of a lake's energy balance, and its importance for lake evaporation (Ew) has been widely recognized. However, the effect of Gc on Ew exhibits diversity across time dimensions. The controls on Gc and the effects of Gc on Ew estimates at different time scales remain largely unexplored. To address these gaps, we identified the primary controls on Gc at an eddy covariance site in a large shallow lake (Lake Taihu) and quantified the role of Gc in estimating Ew on three (hourly, daily, and monthly) time scales based on two energy balance‐based Ew models. Our results indicate that the diurnal variation of Gc is dominated by net radiation and peaks around noon, while the seasonal variation of Gc is mainly controlled by air temperature and peaks in spring. In contrast, the daily variation of Gc is subjective to a confluence of factors—net radiation, wind speed, and relative humidity—displaying more stochasticity than that on the other two time scales. We also found that the importance of Gc for Ew estimates decreases as the time scale extends. Compared to the two models disregarding Gc, considering the effect of Gc enhances the average Kling‐Gupta efficiency (KGE) values of the two models by 1.33, 0.42, and 0.08 on the three time scales, respectively. Overall, this study highlights the importance of time scales in evaluating the effect of Gc on Ew estimates.

Meteorological influences on PM2.5 variation in China using a hybrid model of machine learning and the Kolmogorov-Zurbenko filter

Quantitatively evaluating the contribution of meteorology and emissions to PM2.5 reduction during the Three-year Action Plan to Fight Air Pollution (2018–2020) is important to guide future emission control measures in China. In this study, a Kolmogorov-Zurbenko (KZ) filter and an artificial neural network (ANN) combined model was used to separate the meteorology-influenced PM2.5 concentration by considering seven meteorological factors including boundary layer height, surface pressure, surface net solar radiation, total precipitation, atmospheric temperature, wind speed and wind direction in China. To compensate for the black-box nature of the ANN, the Shapley additive explanation (SHAP) value was introduced to explain the effect of each meteorological factor on long-term PM2.5 concentration. Results showed that PM2.5 concentration decreased by 14% from 2018 to 2020 in China with annual average concentrations of 37.19, 35.28, and 31.94 μg/m3, respectively. Although the decline in PM2.5 was mainly due to emission reductions (58% for all of China), the contribution of prevailing meteorological conditions should not be ignored, especially in some regions such as Northeast China, which had the highest contribution of meteorology (58%) on PM2.5 reduction. In general, the contributions of meteorological conditions to the long-term trend of PM2.5 varied greatly by region and season. SHAP analysis indicated that temperature, surface pressure and boundary layer height were the dominant meteorological factors affecting long-term PM2.5 with contributions of 65%, 11% and 6% on average. We also found that regions with larger average PM2.5 concentration were more affected by emission changes than by meteorology. Therefore, we recommend the continuation of emission control measures in heavily polluted regions such as North and Central China.

Divergent response to abiotic factor determines the decoupling of water and carbon fluxes over an artificial C4 shrub in desert

Knowledge on relationship and determinants of water and carbon dioxide (CO2) exchange is crucial to land managers and policy makers especially for the desertified land restoration. However, there remains highly uncertain in terms of water use and carbon sequestration for artificial plantation in desert. Here, continuous water and carbon fluxes were measured using eddy covariance (EC) in conjunction with hydrometeorological measurements over an artificial C4 shrub, Haloxylon ammodendron (C. A. Mey.) Bunge, from July 2020 to 2021 in Tengger Desert, China. Throughout 2021, evapotranspiration (ET) was 189.5 mm, of which 85% (150 mm) occurred during growing season, that was comparable with the summation of precipitation (132.2 mm), dew (33.5 mm) and potential other sources (e.g. deep subsoil water). This ecosystem was a strong carbon sink with net ecosystem production (NEP) up to 446.4 g C m−2 yr−1, much higher than surrounding sites. Gross primary production (GPP, 598.7 g C m−2 yr−1) in this shrubland was comparable with that of other shrublands, whereas ecosystem respiration (Re, 152.3 g C m−2 yr−1) was lower. Random Forest showed that environmental factors can explain 71.56% and 80.07% variation of GPP and ET, respectively. Interestingly, environmental factors have divergent effect on water and carbon exchange, i.e., soil hydrothermic factors (soil moisture content and soil temperature) determine the magnitude and seasonal pattern of ET and Re, while aerodynamics factors (net radiation, atmospheric temperature and wind speed) determine GPP and NEP. As such, divergent response of abiotic factors resulted in the decoupling of water and carbon exchange. Our results suggest that H. ammodendron is a suitable species for large-scale afforestation in dryland given its low water use but high carbon sequestration. Therefore, we infer that artificial planting H. ammodendron in dryland could provide an opportunity for climate change mitigation, and the long-term time series data is needed to confirm its sustainable role of carbon sequestration in the future.

Experimental and Numerical Study on Cavitation Effects in Centrifugal Pumps

Experimental and numerical investigations of the centrifugal pump performance at non-cavitating and cavitating flow conditions were carried out in the present study. Experiments were performed by applying a vacuum to a closed-loop system to investigate the effects of the net positive suction head available (NPSHa), flow rate, water temperature and pump speed on the centrifugal pump performance. Accordingly, many of the important parameters concerning cavitation phenomenon were calculated. Also, the noise which is accompanied by cavitation was measured. Numerical analysis was implemented for two phase flow (the water and its vapor) using a 2-D simulation by ANSYS FLUENT software to investigate the internal flow of centrifugal pump under cavitating conditions. It was observed that with decreasing NPSHa, the values of the pump head, flow rate and efficiency initially remain constant, but with further reduction in NPSHa these parameters will decrease. Also, it was found that at 3% head drop the percentage drop of the flow rate is less than 2% whereas the percentage drop of the efficiency is greater than 3%. Numerically, it was noticed that the cavitation regions appear at the leading edge of suction side of the impeller blades which represents the lowest pressure area inside the computational domain of the centrifugal pump.

Nonlinear dynamics and bifurcations of a planar undulating magnetic microswimmer.

Swimming microorganisms such as flagellated bacteria and sperm cells have fascinating locomotion capabilities. Inspired by their natural motion, there is an ongoing effort to develop artificial robotic nanoswimmers for potential in-body biomedical applications. A leading method for actuation of nanoswimmers is by applying a time-varying external magnetic field. Such systems have rich and nonlinear dynamics that call for simple fundamental models. A previous work studied forward motion of a simple two-link model with a passive elastic joint, assuming small-amplitude planar oscillations of the magnetic field about a constant direction. In this work, we found that there exists a faster, backward motion of the swimmer with very rich dynamics. By relaxing the small-amplitude assumption, we analyze the multiplicity of periodic solutions, as well as their bifurcations, symmetry breaking, and stability transitions. We have also found that the net displacement and/or mean swimming speed are maximized for optimal choices of various parameters. Asymptotic calculations are performed for the bifurcation condition and the swimmer's mean speed. The results may enable significantly improving the design aspects of magnetically actuated robotic microswimmers.

Gap filling of turbulent heat fluxes over rice–wheat rotation croplands using the random forest model

Abstract. This study investigated the accuracy of the random forest (RF) model in gap filling the sensible (H) and latent heat (LE) fluxes, by using the observation data collected at a site over rice–wheat rotation croplands in Shouxian County of eastern China from 15 July 2015 to 24 April 2019. Firstly, the variable significance of the machine learning (ML) model's five input variables, including the net radiation (Rn), wind speed (WS), temperature (T), relative humidity (RH), and air pressure (P), was examined, and it was found that Rn accounted for 78 % and 76 % of the total variable significance in H and LE calculating, respectively, showing that it was the most important input variable. Secondly, the RF model's accuracy with the five-variable (Rn, WS, T, RH, P) input combination was evaluated, and the results showed that the RF model could reliably gap fill the H and LE with mean absolute errors (MAEs) of 5.88 and 20.97 W m−2, and root mean square errors (RMSEs) of 10.67 and 29.46 W m−2, respectively. Thirdly, four-variable input combinations were tested, and it was found that the best input combination was (Rn, WS, T, P) by removing RH from the input list, and its MAE values of H and LE were reduced by 12.65 % and 7.12 %, respectively. At last, through the Taylor diagram, H and LE gap-filling accuracies of the RF model, the support vector machine (SVM) model, the k nearest-neighbor (KNN) model, and the gradient boosting decision tree (GBDT) model were intercompared, and the statistical metrics showed that RF was the most accurate for both H and LE gap filling, while the LR and KNN model performed the worst for H and LE gap filling, respectively.

Physical confinement and cell proximity increase cell migration rates and invasiveness: A mathematical model of cancer cell invasion through flexible channels

Cancer cell migration between different body parts is the driving force behind cancer metastasis, which is the main cause of mortality of patients. Migration of cancer cells often proceeds by penetration through narrow cavities in locally stiff, yet flexible tissues. In our previous work, we developed a model for cell geometry evolution during invasion, which we extend here to investigate whether leader and follower (cancer) cells that only interact mechanically can benefit from sequential transmigration through narrow micro-channels and cavities. We consider two cases of cells sequentially migrating through a flexible channel: leader and follower cells being closely adjacent or distant. Using Wilcoxon’s signed-rank test on the data collected from Monte Carlo simulations, we conclude that the modelled transmigration speed for the follower cell is significantly larger than for the leader cell when cells are distant, i.e. follower cells transmigrate after the leader has completed the crossing. Furthermore, it appears that there exists an optimum with respect to the width of the channel such that cell moves fastest. On the other hand, in the case of closely adjacent cells, effectively performing collective migration, the leader cell moves 12% faster since the follower cell pushes it. This work shows that mechanical interactions between cells can increase the net transmigration speed of cancer cells, resulting in increased invasiveness. In other words, interaction between cancer cells can accelerate metastatic invasion.

MEMBANDINGKAN KECEPATAN SINYAL WIFI ID DENGAN SINYAL WIFI WARUNG KOPI MENGGUNAKAN NET SPEED MONITOR

In this modern era, of course we are no strangers to advanced technology called the internet. To be able to connect data globally, an intermediary is needed which is commonly called an internet signal. Because a job is affected by how fast the internet signal is, this study aims to compare the signal strength at the maximum distance of the internet signal between wifi id and wifi coffee shop. Determination of QoS parameters is done by measuring internet access speed with Net Speed Monitor and measuring Upload and Download. Factors affecting the difference in signal speed are the type of device, the transmission medium and the resistance.

Analysis and Research on Internal Factors of Stock Price Fluctuation of Chinese Listed Companies Based on ANN-BRF Model

Affected by the new corona epidemic, China ' s stock market fluctuates frequently, and stock price fluctuations lead to obstacles to corporate financing, which is not conducive to establishing a good corporate image. In order to provide ideas for enterprises to stabilize the stock price, this paper establishes the influence of internal financial factors on the stock price fluctuation of listed companies based on the artificial neural network-radial basis function (ANN-RBF) model. Based on grounded theory, this paper constructs an index system of stock price fluctuation factors, including 14 indicators from four aspects from the perspective of internal enterprises. Based on the financial data of the Lingnan Pharmaceutical Industry from 2008 to the third quarter of 2021, this paper integrates the financial index system into ANN to explore the impact of corporate financial indicators on stock prices. The results show that net asset growth rate (0.87), retained earnings (0.68) and speed ratio (0.929) are the leading financial indicators affecting stock prices. In addition, this paper helps to study the accuracy of RBF neural network in predicting stock prices of listed companies.

Unequal nitrogen translocation pattern caused by clonal integration between connected ramets ensures necessary nitrogen supply for young Moso bamboo growth

The rapid growth of young Moso bamboo ( Phyllostachys edulis ), a giant woody clonal plant, depends on consistent nutrient supply through clonal integration. However, the effects of clonal integration on nutrient translocation and allocation in Moso bamboo remain unclear. We established an in situ study model unit consisting of a young bamboo ramet, a mature bamboo ramet, and an interconnected rhizome to study nitrogen (N) translocation and allocation using the 15 N isotope labeling method. The results showed 15 N translocation was bidirectional between interconnected Moso bamboo ramets; however, more 15 N was translocated from the mature to the young ramet than vice versa in winter. The N translocation rate within the donor ramet was faster when the young was donor ramet, and N translocation rate from the donor to the recipient ramet was faster when young bamboo was the recipient ramet. Demand-driven source-sink relationships between connected ramets determined the net flow direction and speed of N translocation. Therefore, an “unequal N translocation pattern between the young and connected mature ramets” was proposed, in which N was preferentially translocated from the mature to the young ramet to meet its growth demand in winter. Our findings provide new insights into the underlying mechanism of Moso bamboo growth and N clonal integration network in Moso bamboo forests and could serve as a guide for precision fertilization in forest management. • N translocation was bidirectional with net flow from the mature to the young ramet. • N translocation within the ramet was faster when the young was donor or recipient ramet. • Demand-driven source-sink relationships determined net N flow direction and speed. • Unequal N translocation between young and mature ramets ensures young ramet growth.

Generating Synthetic Monthly Net Radiation Data Conditioned on Wind Speed

Aims: This study aimed at generating synthetic monthly net radiation data conditioned on wind speed over Port Harcourt, Benue, Kano and Enugu in Nigeria.
 Duration of Study: The daily maximum and minimum Relative-Humidity, maximum and minimum air temperature, solar radiation and wind speed data was obtained from the International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria for the period of thirty-four (34) years (1977-2010).
 Method: The Penman-Monteith (FAO-56) step by step method was used to compute the daily net radiation. The autocorrelation function was used to establish the fact that net radiation and wind speed exhibit the Markov property. Lastly, a two – state Markov Chain model and an indicator function of energy balance and imbalance was developed and used in the course of this work.
 Results: The finding reveals that net radiation is surplus over the study areas. The Lag one autocorrelation coefficient confirms the fact that an actual day net radiation and wind speed state depends on the previous day’s state. The monthly steady state probabilities of surplus net radiation conditioned on low wind speed is higher compared to monthly steady state probabilities of surplus net radiation conditioned on high wind speed. The indicator function of energy balance or imbalance reveals that there is energy imbalance over study areas.
 Conclusion: The generated synthetic net radiation data conditioned on wind speed preserved the characteristics of actual net radiation data when compared as observed in the study. This data is essential in the study of climate change, weather monitoring, agricultural meteorology and estimation of evapotranspiration.

Vegetation greening and climate change promote an increase in evapotranspiration across Siberia

• Evapotranspiration (ET) increased with a trend of 0.54 ± 1.38 mm/a from 2000 to 2020. • Greening is the predominant driver of ET variations. • Surface net radiation and wind speed are vital climate factors of ET variations. The greening of the Arctic and pan-Arctic regions in recent decades has been widely confirmed, while the details regarding the greening feedback effects involving the water and energy cycles are still vague. Evapotranspiration (ET), a vital process in the water and energy cycles, strongly corresponds to vegetation activities. Hence, in this study, we chose Siberia as the study area and, based on the Penman–Monteith–Leuning (PML) model, revealed the contribution of greening to ET. Moreover, the effects of the water vapour pressure deficit, surface net radiation ( R n ) and wind speed ( U m ) on ET were evaluated. The results indicated that from 2000 to 2020, the annual ET in Siberia was 248.2 ± 94.1 mm, and the trend was 0.54 ± 1.38 mm/a. Greening was the major driver of ET variations; its contribution was 0.79 ± 0.76 mm/a, and its relative contribution was 37%. Among the other analysed climate factors, ET was sensitive to R n and U m ; these factors contributed 0.51 ± 0.85 mm/a and −0.38 ± 0.54 mm/a, respectively, to ET variation, and their relative contributions were 33% and 19%, respectively. The effect of the water vapour pressure deficit was slight (0.29 ± 0.22 mm/a, 11%), indicating that ET was hardly constrained by the water supply in Siberia. These results quantify the importance of greening on ET variations and highlight the important effects of R n and U m on ET in cold region terrestrial ecosystems. Furthermore, this study improves our understanding of the mechanism by which evapotranspiration varies and is valuable for predicting and evaluating the Arctic water cycle in “Arctic amplification”.

Analysis of the Contact Area for Three Types of Upper Limb Strikes.

Performance in strike combat sports is mostly evaluated through the values of the net force, acceleration, or speed to improve efficient training procedures and/or to assess the injury. There are limited data on the upper limb striking area, which can be a useful variable for contact pressure assessment. Therefore, the aim of this study was to determine the contact area of the upper limb in three different strike technique positions. A total of 38 men and 38 women (n = 76, 27.3 ± 8.5 years of age, 73.9 ± 13.8 kg of body weight, 173.3 ± 8.4 cm of body height) performed a static simulation of punch with a fist, palm strike, and elbow strike, where three segments of the right upper limb were scanned. The analysis of 684 images showed a correlation (r = 0.634) between weight and punch technique position in men and significant differences in elbow strike (p < 0.001) and palm strike (p < 0.0001) between women and men. In both groups, the palm demonstrated the largest area and the elbow the smallest one. These data may be used to evaluate strike contact pressure in future studies in forensic biomechanics and assessment of injury in combat sports and self-defense.

Influence of Evaporator Superheating and Pressure on the Performance ORC with R134a

This research examines the heat sources using a low-temperature organic Rankine cycle thermodynamic analysis. The effect of increasing the temperature and pressure at the expander input is explored. The performance of an ORC system using R134a was investigated thermodynamically. The expander's input temperature ranged from 55 to 85 degrees Celsius. Pressures in the evaporator range from 0.4 to 0.6 MPa. The software used was Engineering Equation Solver. The temperature and pressure of evaporation have an impact on cycle characteristics including net power production, irreversibility, rotational speed, and thermal and exergy efficiency. At constant evaporator pressure of 0.6 MPa and rising temperature, the thermal efficiency drops to 3.907%, whereas at constant evaporator temperature and expander pressure of 0.4-0.6 MPa, the thermal efficiency rises to 3.907%. When the exergy efficiency is 0.6MPa at constant evaporator pressure, raising the temperature leads to an increase in exergy efficiency of 18.81% -18.89%. At 85℃ and a pressure of 0.4-0.6 MPa, the effect of increasing exergy efficiency was between 2.185% and -18.89% at constant evaporator temperature. The findings of the research reveal that the ORC power plant is a good choice for energy generation. R134a is suitable for the ORC system.

Design and Test of Marine Engine Safety Management Model Based on “Reverse Management”

_ The main purpose of this study is to improve the level of marine safety management. The safety checklist and reverse management model are used to check and measure marine safety. The results indicate that the test results are M1 = 88.705 and M2 = 95.164 respectively (M2 &amp;gt; M1), suggesting that the reverse management safety model has played a positive role in the actual operation. It has been concluded the reverse management model can improve the safety level of marine engineering management, but not all factors are significantly improved. This paper summarizes the working principle of reverse management, which is feasible in practical application. Introduction In recent years, fishing vessel accidents occur frequently in China (Jiangqun 2008; Huadang 2011; Yuanjiao 2015). For example, there are nearly 20,000 fishing boats in Liaoning Province. Most of them are equipped with a four-wheel hydraulic winder favored by the majority of fishermen for its advantages of large pulling force and fast net pulling speed. However, there are also serious safety risks, such as finger breaking in light cases and arm breaking in heavy cases (Dage et al. 2004). Most of the wooden fishing boats above 60 hp in Hebei Province have purchased four-wheel winders and eliminated the original two-wheel ones. Through actual case, it has played a role in increasing work efficiency and improving economic benefits. However, we can also see that the number of casualties of fishing boat crew has increased significantly. According to preliminary statistics, there were more than 120 net gear accidents in 2000 in the whole province, seriously injuring more than 30 crew members, which seriously affected the fishery safety situation (Qiang 2002). These situations are closely related to ship automation.