基于整车道路强化腐蚀试验的工况探讨

试验工况是否科学,可以通过对国内外常用试验方法的工况进行对比,发现其存在的差异性及侧重点,并通过调研对试验工况数据切合度进行验证。只有制定出合理的试验工况,才能为腐蚀数据库提供科学的数据支持。     

Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.     

Comparative evaluation of sizing of metal hydride (MH) hydrogen storage tank filled with different alloys

This study presents a comparative analysis of sizing of metal hydride tank filled with different alloys. Alloys include solid solutions and intermetallic compounds of the generic families AB₅, AB₂, AB, A₂B. The effects of the different alloys on the sizing of metal hydride hydrogen storage tanks are complicated and depend on many factors. In this paper, a thermoeconomic optimization analysis with a simple algebraic formula was presented for the estimation of optimum metal hydride tank surface area for heat transfer enhancement. The optimum area of the metal hydride tank filled with commercially available different alloys (LaN₅, Ti_0,98Zr_0,02V_0,43Fe_0,09Cr_0,05Mn_1,5, TiFe, Mg₂NiH₄) was evaluated and compared by the developed method. The optimum net savings and the value of payback were determined for four alloys. It is found that mathematical model can be employed for the determination of optimum metal hydride tank design and increasing net savings according to alloy types. The optimum areas of the tanks filled with four alloys (LaN₅, Ti_0,98Zr_0,02V_0,43Fe_0,09Cr_0,05Mn_1,5, TiFe, Mg₂NiH₄) were calculated as 0.136, 0.130, 0.133, and 0.173 m², respectively. The optimum net savings for tanks filled with four alloys (LaN₅, Ti_0,98Zr_0,02V_0,43Fe_0,09Cr_0,05Mn_1,5, TiFe, Mg₂NiH₄) are about 461.0, 409.3, 419.6, and 979.6 $ and the values of payback are about 1.98, 2.1, 2.17, and 1.37 years, respectively. Excessive area of the metal hydride tank would not be as economical as the optimum tank area. Thermal management of metal hydride tank must be designed for optimum points calculated at which maximum savings occur.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

Identifying and modeling key trade-offs between hydrogen fuel cell and electric vehicles

Through a sensitivity analysis, the trade-off between vehicle range and CO₂ emissions is investigated as a function of electric emissions coefficient. Various powertrains were analysed for use in a small crossover sport utility vehicle. Gasoline, gasoline electric hybrid, diesel, fuel cell and battery electric vehicles (BEVs) were considered. Using various upstream fuel pathways and a model for vehicle performance, emissions and energy use were estimated. The hydrogen fuel cell vehicle was found preferable to BEVs under conditions of high CO₂ emissions per kW-hr and a high vehicle range requirement. The BEV was preferable for all other conditions.     

基于灰色模糊理论的流域水电规划环境影响综合评价

结合模糊优选理论和灰色关联分析方法,提出灰色模糊综合评价法,该方法将灰色关联分析作为优属度确定的隶属度计算方法;提出理想环境序列建立遵循的原则,引入梯形模糊数实现定性指标量化并采用变异系数法确定评价指标权重.应用灰色模糊综合评价法对黄河流域河段水电规划的高坝方案和多级开发方案进行了比选研究,计算了两个方案的优属度及其开发性因子、稳定性因子、保护性因子、经济活力因子、社会可接受因子、环境风险因子等6个指标层优属度,结果表明,多级开发方案总体优于高坝方案;多级开发方案的保护性远好于高坝开发方案,而高坝方案的开发性略好于多级开发方案,稳定性、经济活力、社会可接受、环境风险等因子两种方案比较接近.评价结果与流域实际情况比较符合,证明该方法是一种有效的方法.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

应用CALINE4模式估算机动车排放污染物的浓度——以济南市主干道为例

随着经济的快速发展,机动车排气污染已成为我国城市空气污染的重要来源,而且在一定时段,机动车排气污染已成为空气污染最主要的污染源之一。以济南市经十路为例,采用实地调查的方法,得出各时段的车流量,选用大气环评助手EIAA中的CALINE4模式对机动车尾气中的主要污染物CO、NOx、THC的排放浓度进行估算,得出3种污染物CO、NOx、THC最大值均出现在7:00—8:00之间,最小值均出现在12:00-13:00之间,排放强度由大到小为:CO、THC、NOx。     

Preferred modes of travel among older adults: What factors affect the choice to walk instead of drive?

Introduction

There are many factors that influence older adults' travel choices. This paper explores the associations between mode of travel choice for a short trip and older adults' personal characteristics.

Methods

This study included 406 drivers over the age of 64 who were enrolled in a large integrated health plan in the United States between 1991 and 2001. Bivariate analyses and generalized linear modeling were used to examine associations between choosing to walk or drive and respondents' self-reported general health, physical and functional abilities, and confidence in walking and driving.

Results

Having more confidence in their ability to walk versus drive increased an older adult's likelihood of walking to make a short trip by about 20% (PR = 1.22; 95% CI: 1.06-1.40), and walking for exercise increased the likelihood by about 50% (PR = 1.53; 95% CI = 1.22-1.91). Reporting fair or poor health decreased the likelihood of walking, as did cutting down on the amount of driving due to a physical problem.

Discussion

Factors affecting a person's decision to walk for exercise may not be the same as those that influence their decision to walk as a mode of travel. It is important to understand the barriers to walking for exercise and walking for travel to develop strategies to help older adults meet both their exercise and mobility needs. Impact on Industry: Increasing walking over driving among older adults may require programs that increase confidence in walking and encourage walking for exercise.     

Seat Belt Use in States and Territories with Primary and Secondary Laws -- United States, 2006

Problem

Motor-vehicle crashes are a leading cause of death in the United States. In the event of a crash, seat belts are highly effective in preventing serious injury and death.

Methods

Data from the 2006 Behavioral Risk Factor Surveillance System were used to calculate prevalence of seat belt use by state and territory and by type of state seat belt law (primary vs. secondary enforcement).

Results

In 2006, seat belt use among adults ranged from 58.3% to 91.9% in the states and territories. Seat belt use was 86.0% in states and territories with primary enforcement laws and 75.9% in states with secondary enforcement laws.

Discussion

Seat belt use continues to increase in the United States. Primary enforcement laws remain a more effective strategy than secondary enforcement laws in getting motor-vehicle occupants to wear their seat belts.