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Development and application of a two-dimensional water quality model for the
Daqinghe River Mouth of the Dianchi Lake 总被引:1,自引:1,他引:0
Water quality models are important tools to support the optimization of aquatic ecosystem rehabilitation programs and assess their efficiency. Basing on the flow conditions of the Daqinghe River Mouth of the Dianchi Lake, China, two-dimensional water quality model was developed in the research. The hydrodynamics module was numerically solved by the alternating direction iteration (ADI) method. The parameters of the water quality module were obtained through the in situ experiments and the lab analyses that were conducted from 2006 to 2007. The model was calibrated and verified by the observation data in 2007. Among the four modelled key variables that were water level, CODcr, NH3-N and PO4-P, the minimum value of the coefficient of determination (CoD) was 0.69, which mean the model performed reasonably well. The developed model was then applied to simulate the water quality changes at the downstream cross-section assuming that the designed restoration programs were implemented. According to the simulated results, the restoration programs could cut down the loads of CODcr and PO4-P about 15%, however, they would have very little effect on the NH3-N removal. Besides, the water quality at the outlet cross-section would be still in class V (3838-02), indicating more measures should be taken to further reduce the loads. The study demonstrated the capability of water quality models to support aquatic ecosystem restorations. 相似文献
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基于仿真的新建污水处理厂工艺参数调试 总被引:1,自引:0,他引:1
基于ASM2D模型建立了上海某新建污水厂倒置AAO流程的数学模型,并采用该厂进、出水设计数据对模型进行校正,其中,ASM2D各组分浓度分布参考文献值.同时,通过仿真计算研究了不同温度下进水流量、污泥回流比、混合液回流比及进水流量分配比对出水总化学需氧量(TCOD)、氨氮(SNH3)、总氮(TN)、总磷(TP)及总悬浮颗粒物(TSS)的影响.结果表明,研究获得的定性和定量两方面结果可供该厂在工艺参数调试中作参考.计算机仿真技术在新建污水厂工艺参数调试中的应用可以减少调试时间,降低调试费用,取得良好的经济效益与环境效益. 相似文献
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Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes. 相似文献
85.
S. N. Nnamchi M. M. Mundu J. D. Busingye J. U. Ezenwankwo 《International Journal of Green Energy》2019,16(6):450-467
Simulation of helio-photovoltaic system is continuously undergoing revolution through diverse parameter modifications which closely mimic the experimental data. In retrospect, the current work has presented a nonlinear modification of equivalent circuit parameters and simulated the same for different semiconductors (crystalline and thin films); furthermore, established a mathematical relation between the coefficients of solar irradiance and module temperature (SIMT); moreover, investigated the influence of SIMT on the model parameters. The simulation upshot reveals that increment in solar irradiance (SI) intensifies the output current whereas an increase in module temperature (MT) diminishes the output voltage; the SIMT coefficients developed validated well with the manufacturers data; the influence of SI was evident on the photon current, diode current, and shunt resistance whereas the effect of MT was pronounced on the diode current, ideality factor, and shunt resistance. Thus, the provision made by this work is essential for advanced design and simulation of helio-photovoltaic systems. 相似文献
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本文通过试验,阐明了舍汞固废(危废)焙烧过程中汞的迁移情况,并得到了焙烧治理技术的最佳工艺参数为:焙烧温度600℃、焙烧时间5h、炉内压力-50Pa—100Pa;焙烧后固废中残留汞含量小于0.0015%;汞回收率达95%左右。 相似文献
90.
优化、RSA和GLUE方法在非线性环境模型参数识别中的比较 总被引:6,自引:2,他引:4
参数识别是数学模型应用的前提,本文对非线性环境模型常用的3种参数识别方法进行了比较分析.优化方法是出现最早、应用最广泛的参数识别方法之一.但在观测误差存在的情况下,采用优化方法识别的最优参数进行模型预测,存在很大的决策风险.考虑到这种不足,RSA方法和GLUE方法摒弃了识别单一最优参数的传统思维,而把识别参数扩大到多点组成的参数集.RSA方法与GLUE方法不同的是,RSA方法把可行的参数点看成是同等接受的,而GLUE方法则根据模拟值与实测值的差别,确定其似然度,代表参数的可信度水平.除参数识别以外,RSA方法和GLUE方法也是全局灵敏度分析的重要工具. 相似文献