城市110KV户内变电站声场数值模拟

摘要：城市户内变压器运转时会产生噪声,严重时会影响到周围居民的正常工作和生活。文章简单阐述了变压器噪声产生和传播机理。并以南昌市某户内变电站为例,使用声振软件Va One,基于统计能量方法,对经过吸声材料处理后的户内变声场进行仿真模拟。模拟结果表明：经过添加特殊吸声材料处理后的户内变电站,在大门外,仿真数据与实测值吻合良好;在大门内、外,声压级差值仿真结果与预期效果能够符合。     

Aircraft initial mass estimation using Bayesian inference method

Aircraft mass is a crucial piece of information for studies on aircraft performance, trajectory prediction, and many other topics of aircraft traffic management. However, It is a common challenge for researchers, as well as air traffic control, to access this proprietary information. Previously, several studies have proposed methods to estimate aircraft weight based on specific parts of the flight. Due to inaccurate input data or biased assumptions, this often leads to less confident or inaccurate estimations. In this paper, combined with a fuel-flow model, different aircraft initial masses are computed independently using the total energy model and reference model at first. It then adopts a Bayesian approach that uses a prior probability of aircraft mass based on empirical knowledge and computed aircraft initial masses to produce the maximum a posteriori estimation. Variation in results caused by dependent factors such as prior, thrust and wind are also studied. The method is validated using 50 test flights of a Cessna Citation II aircraft, for which measurements of the true mass were available. The validation results show a mean absolute error of 4.3% of the actual aircraft mass.     

A traffic noise model for road intersections in the city of Cartagena de Indias,Colombia

Road traffic noise models are fundamental tools for designing and implementing appropriate prevention plans to minimize and control noise levels in urban areas. The objective of this study is to develop a traffic noise model to simulate the average equivalent sound pressure level at road intersections based on traffic flow and site characteristics, in the city of Cartagena de Indias (Cartagena), Colombia. Motorcycles are included as an additional vehicle category since they represent more than 30% of the total traffic flow and a distinctive source of noise that needs to be characterized. Noise measurements are collected using a sound level meter Type II. The data analysis leads to the development of noise maps and a general mathematical model for the city of Cartagena, Colombia, which correlates the sound levels as a function of vehicle flow within road intersections. The highest noise levels were 79.7 dB(A) for the road intersection María Auxiliadora during the week (business days) and 77.7 dB(A) for the road intersection India Catalina during weekends (non-business days). Although traffic and noise are naturally related, the intersections with higher vehicle flow did not have the highest noise levels. The roadway noise for these intersections in the city of Cartagena exceeds current limit standards. The roadway noise model is able to satisfactorily predict noise emissions for road intersections in the city of Cartagena, Colombia.     

The contribution of road traffic to particulate matter and metals in air pollution in the vicinity of an urban road

A detailed investigation was conducted to study the sources of particulate matter in the vicinity of an urban road in Žilina. To determine the amount of particulate matter (PM₁₀, PM_2.5 and PM₁) present in the ambient air, a reference gravimetric method was used. The main objective of this contribution was to identify the sources of these particles by means of statistical methods, specifically principal component analysis (PCA), factor analysis (FA), and absolute principal component scores (APCS), as well as using the presence of 17 metals in the particulate matter (Na, Mg, Al, Ca, V, Cr, Fe, Mn, Ni, Cu, Zn, As, Mo, Sb, Cd, Ba, Pb). To identify the metals in the particulate matter samples and to determine their abundances, spectroscopic methods were used, specifically inductively coupled plasma mass spectrometry (ICP-MS). Each of these metals may come from a specific source, such as the burning of fossil fuels in fossil fuel power plants; local heating of households; the burning of liquefied fossil fuels in the combustion engines of vehicles; the burning of coal and wood; non-combustion related emissions resulting from vehicular traffic; resuspension of traffic-related dust; and industry. Diesel vehicles and non-combustion emissions from road traffic have been identified as two key sources of the particulate matter. The results reveal that non-combustion emissions, which are associated with the elements Na, Fe, Mn, Ni, Zn, Mo, Sb, Cd, and Pb, are the major contributors, followed by combustion emissions from diesel vehicles, which are associated with the elements Mg, Ca, and Ba.     

Modified environmental contour method for predicting long-term extreme responses of bottom-fixed offshore wind turbines

Predicting extreme responses is very important in designing a bottom-fixed offshore wind turbines. The commonly used method that account for the variability of the response and the environmental conditions is the full long-term analysis (FLTA), which is accurate but time consuming. It is a direct integration of all the probability distribution of short-term extremes and the environmental conditions. Since the long-term extreme responses are usually governed by very few important environmental conditions, the long-term analysis can be greatly simplified if such conditions are identified. For offshore structures, one simplified method is the environmental contour method (ECM), which uses the short-term extreme probability distribution of important environmental conditions selected on the contour surface with the relevant return periods. However, because of the inherent difference of offshore wind turbines and ordinary offshore structures, especially their non-monotonic behavior of the responses under wind loads, ECM cannot be directly applied because the environmental condition it selects is not close to the actual most important one.The paper presents a modified environmental contour method (MECM) for bottom-fixed offshore wind turbine applications. It can identify the most important environmental condition that governs the long-term extreme. The method is tested on the NREL 5 MW wind turbine supported by a simplified jacket-type support structure. Compared to the results of FLTA, MECM yields accurate results and is shown to be an efficient and reliable method for the prediction of the extreme responses of bottom-fixed offshore wind turbines.     

一种自适应网格模糊交互多模型算法（英文）

This paper studies the algorithm of the adaptive grid and fuzzy interacting multiple model(AGFIMM) for maneuvering target tracking, while focusing on the problems of the fixed structure multiple model(FSMM) algorithm's cost-efficiency ratio being not high and the Markov transition probability of the interacting multiple model(IMM) algorithm being difficult to determine exactly. This algorithm realizes the adaptive model set by adaptive grid adjustment, and obtains each model matching degree in the model set by fuzzy logic inference. The simulation results show that the AGFIMM algorithm can effectively improve the accuracy and cost-efficiency ratio of the multiple model algorithm, and as a result is suitable for engineering applications.     

车客渡船舱室噪声预报与控制

针对新设计的100 m级海峡车客渡船开展舱室噪声预报和控制研究。使用统计能量分析（SEA）软件VA One预报所有舱室的噪声,由经验公式得到喷水激励、主辅机、泵体和风机等设备的结构噪声和空气噪声,并加载间接式通风空调口振动的实测值。采用特性分析的方法讨论结构噪声和空气噪声的传播方式,结果表明,结构噪声比空气噪声传播得更远。分析不同舱室的主要噪声来源,发现船舶下层结构,即艏楼甲板以下舱室的噪声主要来自机舱内,而上层建筑舱室的主要噪声则间接来自通风空调口。对于噪声超标的舱室,采取敷设阻尼材料和吸声材料以及加装消声器的减振降噪措施。研究表明,统计能量法适用于船舶设计阶段的噪声预报和声学优化计算,所得数据可为今后100 m级实船设计提供参考依据。     

轿车制动性能统计分析与改进措施

利用数理统计方法，对409辆在用奥迪100轿车制动性能台试验测所得大量样本数据进行统计分析，揭示了该型轿车8项制动性能的统计特征和内在规律性，建立了相应的分布密度函数和分布函数模型。模型公式可以对制动性能的分布情况和相关概率进行准确的描述，计算结果与实测数据高度相符。本文研究还指出了车辆制动性能等方面存在的一些问题并提出了有针对性的改进措施和建议。     

分布式水下多传感器多目标模糊跟踪融合方法

水下多传感器多目标跟踪系统往往是一个不同类传感器融合系统,且其目标航迹包含有不确定和模糊信息.本文首先利用模糊隶属度函数和模糊逻辑推理技术,进行分布式水下多传感器多目标航迹模糊融合关联决策,并利用有效数据处理和分层融合估计相结合的方法,以实现不同类传感器高精度融合跟踪估计.     

英语阅读中含蓄意义探析

把握好阅读中语意暗含，是读者必须掌握的较复杂的高层次阅读技能之一，从4个方面以实例阐析了如何挖掘阅读理解中语意暗含，以帮助读者全面准确地理解原文．