Availability simulation model of complex electromechanical systems with the consideration of testability parameters

This paper proposes a stochastic MFBD (maintenance function block diagram) to describe fault diagnosis dynamic behavior of availability fluctuation evaluation for complex electromechanical system, which considers comprehensive diagnostic parameters, maintenance process and resource. The availability evaluation of complex electromechanical systems is achieved by simulation method. Firstly, the faults are divided into several types according to the quantity relationship represented by testability parameters and the logic sequence of fault-related activities is modeled. Math models describing the uncertainty between activities are established, which are embedded within MFBD. The stochastic MFBD is transformed into a simulation model designed via PI (process interaction) algorithm. Finally, a discrete-event simulation example for availability analysis of complex electromechanical system is provided and the accuracy and applicability of the proposed method are verified

Application of Relative Risk of Meteorological Factors in Power Grid Electricity Load Forecasting

[Introduction] Accurate and efficient short-term electricity load forecasting is a prerequisite for ensuring the safe and reliable operation of power system, and it is also the basis for the rational arrangement of power generation plans in the power grid. Therefore, studying the relationship between meteorology and electricity load is of great significance for load forecasting. [Method] Based on the electricity load data at 15 min intervals during the period between January 1 of 2013 and December 31 of 2021 provided by the State Grid Hebei Electric Power Co., Ltd. as well as the corresponding meteorological observation data of Shijiazhuang station, this paper analyzed the temporal variation characteristics of daily peak electricity load in Shijiazhuang, and in particular, the meteorological conditions corresponding to the samples with a daily peak electricity load that was 10% higher than that of the previous day were analyzed. The Spearman's rank correlation method was used to analyze the correlation between daily peak electricity load in Shijiazhuang and the meteorological factors of the previous day, and significantly correlated meteorological factors were identified. The response curves of the significantly correlated meteorological factors to the next day's peak electricity load were drawn using the smooth curve fitting method, and the analysis revealed the changing trend of daily peak electricity load with the variations of meteorological factors, as well as the response thresholds. For different threshold ranges, the relative risk of meteorological factors to the changes of the daily peak electricity load was calculated based on the Poisson distribution. On this basis, the variation magnitudes of daily peak electricity load caused by per unit change in each meteorological factor within different threshold ranges in Shijiazhuang were calculated, that is, the quantitative impacts of the changes in different meteorological factors on the variation of daily peak electricity load were revealed. [Result] Taking temperature as an example, when the daily average, maximum and minimum temperatures are higher (lower) than the thresholds, the relative risk to the next day′s peak electricity load increases (decreases) by 2.25% (0.62%), 1.92% (0.57%) and 2.07% (0.60%) respectively for every 1 °C increase in temperature. [Conclusion] Based on the relative risk of different meteorological factors to daily peak electricity load in Shijiazhuang, a method for predicting the next day′s peak electricity load is proposed. The test performed using the daily electricity load and meteorological data of Shijiazhuang in 2022 reveals that the prediction effect can meet the needs of daily electricity meteorological service

Synthesis and Photoluminescence Properties of Porous Silicon Nanowire Arrays

Herein, we prepare vertical and single crystalline porous silicon nanowires (SiNWs) via a two-step metal-assisted electroless etching method. The porosity of the nanowires is restricted by etchant concentration, etching time and doping lever of the silicon wafer. The diffusion of silver ions could lead to the nucleation of silver nanoparticles on the nanowires and open new etching ways. Like porous silicon (PS), these porous nanowires also show excellent photoluminescence (PL) properties. The PL intensity increases with porosity, with an enhancement of about 100 times observed in our condition experiments. A “red-shift” of the PL peak is also found. Further studies prove that the PL spectrum should be decomposed into two elementary PL bands. The peak at 850 nm is the emission of the localized excitation in the nanoporous structure, while the 750-nm peak should be attributed to the surface-oxidized nanostructure. It could be confirmed from the Fourier transform infrared spectroscopy analyses. These porous SiNW arrays may be useful as the nanoscale optoelectronic devices

Analiza gotowości systemu wieloelementowego składającego się z różnych wygaszalnych podsystemów typu k-z-n:G stanowiących rezerwę ciepłą

Industrial equipment or systems are usually constructed as a multi-component series system with k-out-of-n:G subsystems to fulfill a specified function. As a common type of standby, warm standby is considered in the multi-component series system with k-outofn:G standby subsystems. When a subsystem fails, the non-failed subsystems are shut off and cannot fail, which is defined as suspended animation (SA). If the SA is ignored the non-failed subsystems are assumed to keep working in the SA time, which will cause inaccuracy in the availability analysis for the system. In this paper, we focus on the SA to construct an availability model for a multi-component series system with k-out-of-n:G warm standby subsystems. Multiple continuous time Markov chains are constructed to model the system availability. A Monte Carlo simulation has been carried out to verify our method. Several interesting findings are obtained. 1) The failure rates of subsystems with SA and their limits are derived. 2) The closed-form expressions for the stationary availability of the system and subsystems, mean time to failure, mean time to repair and stationary failure frequency are obtained considering SA. 3) The system stationary availability is a monotone function for its parameters. 4) The SA effect on the stationary availability should be emphasized in two cases, one is both the value of n/k and the failure rate of active components in a k-out-of-n subsystem are relatively large or small, the other is both the value of n/k and the repair rate are relatively small.Aby urządzenia i systemy przemysłowe mogły pełnić swoje określone funkcje, zwykle buduje się je w postaci wieloelementowych systemów szeregowych składających się z podsystemów typu k-z-n: G. W pracy rozważano zagadnienie rezerwy ciepłej w wieloelementowym systemie szeregowym składającym się z podsystemów rezerwowych typu k-z-n: G. W przypadku awarii jednego z takich podsystemów, pozostałe, działające podsystemy wyłącza się, dzięki czemu nie mogą one ulec uszkodzeniu. Procedurę taką określa się, przez analogię z organizmami żywymi mianem anabiozy (suspended animation) lub wygaszania. Pominięcie zjawiska wygaszania, prowadzi do założenia, że podsystemy, które nie uległy uszkodzeniu pracują w czasie wygaszenia, co skutkuje nieprawidłowościami w analizie gotowości systemu. W artykule koncepcję wygaszania podsystemów wykorzystano do budowy modelu gotowości wieloelementowego systemu szeregowego składającego się z podsystemów typu k-z-n: G stanowiących rezerwę ciepłą. W celu zamodelowania gotowości systemu, skonstruowano łańcuchy Markowa z czasem ciągłym. Przedstawioną metodę zweryfikowano za pomocą symulacji Monte Carlo. Uzyskano szereg interesujących wyników. 1) Obliczono intensywność uszkodzeń podsystemów wygaszonych i ich wartości graniczne. 2) Wyprowadzono, z uwzględnieniem procedury wygaszania, wyrażenia w postaci zamkniętej dla stacjonarnej gotowości rozważanego systemu i podsystemów oraz określono średni czas do uszkodzenia, średni czas do naprawy oraz stacjonarną częstotliwość uszkodzeń. 3) Gotowość stacjonarna systemu jest funkcją monotoniczną dla parametrów wejściowych systemu. 4) Należy podkreślić wpływ wygaszania na stacjonarną gotowość systemu w dwóch przypadkach: gdy stosunek n/k i intensywność uszkodzeń aktywnych elementów k-tego spośród n podsystemów są względnie niskie lub względnie wysokie, oraz gdy stosunek n/k i intensywność napraw są względnie niskie

Glycyrrhizic acid alleviates the meconium-induced acute lung injury in neonatal rats by inhibiting oxidative stress through mediating the Keap1/Nrf2/HO-1 signal pathway

Meconium aspiration syndrome (MAS) is a disease closely related to inflammation and oxidative stress. Glycyrrhizic acid (GA) is a triterpenoid isolated from licorice with multiple bioprotective properties. In the present study, impacts of GA against MAS rats, as well as the potential mechanism, will be investigated. MAS model was established on newborn rats, followed by the treatment of 12.5, 25, and 50 mg/kg GA. The wet/dry weight ratio of lung tissues was calculated. The production of IL-6, IL-1β, TNF-α, malonaldehyde (MDA), superoxide dismutase (SOD), glutathione (GSH) was measured using ELISA assay. HE staining was used to evaluate the pathological state of lung tissues and TUNEL assay was used to detect the apoptotic state. The protein expression of Nrf2, Keap1, HO-1, Bcl-2, Bax, and cleaved-Caspase3 was measured by Western blotting assay. The elevated W/D ratio, release of inflammatory factors, lung injury score, and apoptotic index, as well as the activated oxidative stress and suppressed Keap1/Nrf2/HO-1 pathway, in MAS rats were significantly alleviated by GA. After introducing the inhibitor of Nrf2, ML385, the protective property of GA on the pathological state, apoptotic index, and oxidative stress in MAS rats was pronouncedly abolished. Taken together, glycyrrhizin alleviated GAH in rats by suppressing Keap1/Nrf2/HO-1 signaling mediated oxidative stress

Data Envelopment Analysis with Uncertain Inputs and Outputs

Data envelopment analysis (DEA), as a useful management and decision tool, has been widely used since it was first invented by Charnes et al. in 1978. On the one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. This paper will consider DEA in uncertain environment, thus producing a new model based on uncertain measure. Due to the complexity of the new uncertain DEA model, an equivalent deterministic model is presented. Finally, a numerical example is presented to illustrate the effectiveness of the uncertain DEA model

Attributions of Evapotranspiration and Gross Primary Production Changes in Semi-Arid Region: A Case Study in the Water Source Area of the Xiong’an New Area in North China

Investigating the attributions of evapotranspiration (ET) and gross primary production (GPP) changes is of great importance for regional, sustainable water resources and ecological management in semi-arid regions. Based on the simulation conducted during 2000–2019 by improving water-carbon coupling Distributed Time Variant Gain Model, the trends of ET and GPP were estimated and the driving factors were identified via 10 experimental scenarios in the water source area of the Xiong’an New Area in North China. The results show significant increases both in ET and GPP by 2.4 mm/a and 6.0 gC/m2/a in the region, respectively. At the annual scale, increasing precipitation dominates the ET uptrend. Air temperature, humidity and the interactive effects also contribute to the ET uptrend, and the contributions are 12.8%, 2.0% and 2.3%, respectively, while elevated atmospheric CO2 concentration (eCO2) and solar dimming lead to ET changes of about −7.2% and −12.4%, respectively. For the GPP changes, the increase in GPP is mainly caused by eCO2, increasing precipitation and rising temperature with the contributions of 56.7%, 34.8% and 27.8%, respectively. Solar dimming, humidity and windspeed contribute −6.8%, −4.8% and −3.5% of the GPP changes. Compared to climate change, land use and cover change has smaller effects on both ET and GPP for the few changes in land coverage. At the seasonal scale, ET and GPP increase to a greater extent during the growing season in spring and summer than in autumn and winter. Precipitation, temperature and eCO2 are generally the main causes for ET and GPP changes. Meanwhile, the decreasing humidity and rising temperature are dominant factors for ET and GPP increases, respectively, in winter. Furthermore, solar dimming has strong effects on ET reduction in autumn. The contribution of the interactive effects is much higher on a seasonal scale than annual scale, contributing to considerable decreases in ET and GPP in spring, increases in ET in autumn and winter, and an increase in GPP in winter. This study highlights the importance of considering water-carbon coupling on the attributions of ET and GPP changes and the differentiation of the effects by the abovementioned influential factors at annual and seasonal scales

An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory

Scientific support depot location and reasonable spare parts transportation are the keys to improving the support level of complex systems. The current equipment support system has the problems of chaotic warehouse layout and low efficiency of spare parts. The reliability and completeness of spare parts’ historical data are hard to believe. In order to deal with the cognitive uncertainty caused by the asymmetry of data, this paper adopts the uncertainty theory to optimize the depot location and transportation volume. Under the constraints of shortage rate, supply availability, average logistic delay time, and inventory limit, the uncertain chance-constrained model of equipment supporting depot is established. The optimization model is transformed into a deterministic model by using the inverse uncertainty distribution. The genetic algorithm is used to optimize the solution of this model. Finally, the practicability and operability of the model method are verified through the example analysis

Predicting Habitat Suitability and Adaptation Strategies of an Endangered Endemic Species, <i>Camellia luteoflora</i> Li ex Chang (Ericales: Theaceae) under Future Climate Change

Camellia luteoflora Li ex Chang is an endangered plant endemic to the East Asian flora with high ornamental value as well as phylogenetic and floristic research value. Predicting the impact of climate change on its distribution and suitable habitat is crucial until scientific conservation measures are implemented. Based on seven environmental variables and 17 occurrence records, this study optimized the MaxEnt model using the kuenm data package to obtain the optimal parameter combinations (RM = 1.3, FC = LPT) and predicted the potential distribution pattern of C. luteoflora in various future periods. The results revealed that the mean diurnal range, temperature annual range, and precipitation of the wettest month were the influential factors determining the distribution pattern of C. luteoflora, contributing 60.2%, 14.4%, and 12.3% of the variability in the data, respectively. Under the current conditions, the area of suitable habitats for C. luteoflora was only about 21.9 × 104 km2. Overall, the suitable area around the C. luteoflora distribution points will shrink in a circular pattern in response to future global warming, but some potentially suitable distribution areas will expand and migrate to higher latitudes and the Hengduan Mountains region, representing a survival strategy for coping with climate change. It is hypothesized that the future climate refugia will be the highly suitable area and the Hengduan Mountains region. Furthermore, a retrospective validation method was employed to assess the reliability of the predictions and estimate the model’s predictive performance in the future. This study proposes a survival strategy and adaptation measures for C. luteoflora in response to climate change, and the proposed measures can be generalized for application in conservation planning and restoration processes. We also recommend that future studies incorporate factors such as the anthropogenic disturbances and associated socio-economic activities related to C. luteoflora into the model and to further predict the distribution pattern for C. luteoflora in response to historical climatic changes, tracing the evolutionary history of its population