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    Wyświetlanie 1-4 z 4
    Tytuł:
    Microcellular Oblate Propellant with Skin-core Structure Deterred by Poly(neopentanediol adipate)
    Autorzy:
    Ding, Yajun
    Ying, Sanjiu
    Xiao, Zhongliang
    Wu, Wenlong
    Li, Chunzhi
    He, Yun
    Powiązania:
    https://bibliotekanauki.pl/articles/358225.pdf
    Data publikacji:
    2020
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Przemysłu Organicznego
    Tematy:
    SC-CO2
    microcellular oblate propellant
    skin-core structure
    poly(neopentanediol adipate) deterring
    combustion performance
    Opis:
    In order to solve the issues of high muzzle flash, smoke, residue, migration rate and carcinogenicity of double-base oblate propellants deterred by dibutyl phthalate (DBP), skin-core structure microporous oblate propellants to replace DBP deterring technology were fabricated in the present work by supercritical carbon dioxide (SC-CO2) foaming technology. Poly(neopentanediol adipate) (NA) was employed as the deterrent to modify the combustion properties because of ist lower migration rate in storage. Scanning electron microscopy (SEM) was used to observe the morphology of the microporous oblate propellants generated by different processing conditions, and the combustion properties were investigated by closed bomb tests. The SEM images indicated that the skin region displayed smaller cell diameters and lower cell density compared with cells in the core region. The closed bomb tests demonstrated that it was feasible to adjust the progressive combustion performance by controlling the skin-core structure and the NA deterred layer. The burning time values of the original, the microcellular, and the NA deterred samples were 3.45, 2.14, and 4.20 ms, respectively. Microcellular oblate propellants, with a skin-core structure foamed by SC-CO2 and deterred by NA, provides a novel and promising method to realize progressive combustion performance.
    Źródło:
    Central European Journal of Energetic Materials; 2020, 17, 1; 49-65
    1733-7178
    Pojawia się w:
    Central European Journal of Energetic Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Mechanism and optimum pressure for sliding-mode nanogenerator
    Autorzy:
    Yun, Hang
    He, Ren
    Powiązania:
    https://bibliotekanauki.pl/articles/2204139.pdf
    Data publikacji:
    2023
    Wydawca:
    Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
    Tematy:
    triboelectric nanogenerator
    ab initio calculation
    optimum pressure
    recovered energy
    Opis:
    Triboelectric nanogenerator has extensive applicability because of its capability of harvesting mechanical energy and flexible working modes. To research the optimum pressure and improve the recovered energy of the sliding-mode triboelectric nanogenerator, a contact model of the Al/PTFE tribo-pair is studied by ab initio calculation and finite element simulation. The F-atom of PTFE is proved to be the electron accepter and the charges transferred can be predicted by Bader charge analysis. The mathematical relation between interfacial distance, charges transferred and contact pressure can be fitted. By Gauss’s law, the electric field is simulated and the regeneration energy of the sliding-mode triboelectric nanogenerator can be evaluated by the total electric energy and friction loss. Finally, an optimum pressure can be set to the upper or lower limit of working pressure corresponding to larger recovered energy. And less friction coefficient and larger contact area are also effective methods for recovering energy.
    Źródło:
    Polish Journal of Chemical Technology; 2023, 25, 1; 35--39
    1509-8117
    1899-4741
    Pojawia się w:
    Polish Journal of Chemical Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Photovoltaic power prediction based on improved grey wolf algorithm optimized back propagation
    Autorzy:
    He, Ping
    Dong, Jie
    Wu, Xiaopeng
    Yun, Lei
    Yang, Hua
    Powiązania:
    https://bibliotekanauki.pl/articles/27309934.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    BP neural network
    photovoltaic power generation
    PSO–GWO model
    PSO–GWO–BP prediction model
    particle swarm optimization
    gray wolf optimization
    back propagation
    standard grey wolf algorithm
    Opis:
    At present, the back-propagation (BP) network algorithm widely used in the short-term output prediction of photovoltaic power stations has the disadvantage of ignoring meteorological factors and weather conditions in the input. The existing traditional BP prediction model lacks a variety of numerical optimization algorithms, such that the prediction error is large. The back-propagation (BP) neural network is easy to fall into local optimization thus reducing the prediction accuracy in photovoltaic power prediction. In order to solve this problem, an improved grey wolf optimization (GWO) algorithm is proposed to optimize the photovoltaic power prediction model of the BP neural network. So, an improved grey wolf optimization algorithm optimized BP neural network for a photovoltaic (PV) power prediction model is proposed. Dynamic weight strategy, tent mapping and particle swarm optimization (PSO) are introduced in the standard grey wolf optimization (GWO) to construct the PSO–GWO model. The relative error of the PSO–GWO–BP model predicted data is less than that of the BP model predicted data. The average relative error of PSO–GWO–BP and GWO–BP models is smaller, the average relative error of PSO–GWO–BP model is the smallest, and the prediction stability of the PSO–GWO–BP model is the best. The model stability and prediction accuracy of PSO–GWO–BP are better than those of GWO–BP and BP.
    Źródło:
    Archives of Electrical Engineering; 2023, 72, 3; 613--628
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evaluation of differential serum expression of three factors and pulmonary function in patients with silicosis
    Autorzy:
    Zhu, Ying
    Duan, Xia Yu
    Cheng, Yun Qi
    Yao, Xin Jing
    Xu, Hong
    Zhang, Kui Sheng
    Li, Feng Shi
    Yang, Fang
    Liu, Liang He
    Yuan, Xiang Ju
    Powiązania:
    https://bibliotekanauki.pl/articles/2086531.pdf
    Data publikacji:
    2021-08-05
    Wydawca:
    Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
    Tematy:
    silicosis
    pulmonary function
    early diagnosis
    ROC
    PTPN2
    factor B
    Opis:
    ObjectivesSilicosis is a chronic occupational lung disease. As was previously found by the authors, some proteins increased in the lung tissue of activated rats, and protein tyrosine phosphatase non-receptor type 2 (PTPN2), factor B, and vaccinia-related kinase 1 (VRK1) showed highly differential expressions.Material and MethodsIn this study, serum and bronchoalveolar lavage fluid samples were collected from patients with silicosis and healthy people to verify the expression of PTPN2, factor B, and VRK1. The diagnostic value of differentially expressed proteins for silicosis was judged.ResultsThe expression levels of serum PTPN2, VRK1, and factor B in patients with silicosis were significantly higher than those in the control group (p < 0.01). Higher serum PTPN2 and factor B concentrations significantly and negatively correlated with the ratio of forced expiratory volume in 1 s to forced vital capacity (FEV1/FVC), maximum vital capacity (VCmax), FEV1, and FVC, suggesting that the high expression of PTPN2 and factor B is associated with decreased pulmonary ventilation function and restrictive ventilatory impairment in patients with silicosis. All area under curve (AUC) measurements generated from single detection events were >0.744, with PTPN2 reaching the highest value (0.858). The AUC, sensitivity, and specificity for the combined diagnosis using factor B and PTPN2 were 0.907, 86.91% and 85.07%, respectively, for factor B and PTPN2. The 3 differentially expressed proteins are potential classes of predictive biomarkers for silicosis.ConclusionsRegarding the economy and test practicality, the best diagnostic combination is factor B and PTPN2 for the analysis of AUC, sensitivity and specificity.
    Źródło:
    International Journal of Occupational Medicine and Environmental Health; 2021, 34, 4; 527-540
    1232-1087
    1896-494X
    Pojawia się w:
    International Journal of Occupational Medicine and Environmental Health
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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