Life cycle assessment of heated apron pavement system operations

Heated pavement systems (HPS) offer an attractive alternative to the cumbersome process of removing ice and snow from airport pavements using traditional snow removal systems. Although snow and ice removing efficiency and economic benefits of HPS have been assessed by previous studies, their environmental impact is not well known. Airport facilities offering public or private services need to evaluate the energy consumption and global warming potential of different types of snow and ice removal systems. Energy usage and emissions from the operations of hydronic heated pavement system using geothermal energy (HHPS-G), hydronic HPS using natural gas furnace (HHPS-NG), electrically heated pavement system (EHPS), and traditional snow and ice removal system (TSRS) are estimated and compared in this study using a hybrid life cycle assessment (LCA). Based on the system models assessed in this study, HPS application in the apron area seems to be a viable option from an energy or environmental perspective to achieve ice/snow free pavement surfaces without using mechanical or chemical methods. TSRS methods typically require more energy and they produce more greenhouse gas (GHG) emissions compared to HPS during the operation phase, under the conditions and assumptions considered in this study. Also, HPS operations require less energy and have less GHG emissions during a snow event with a smaller snowfall rate and a larger snow duration.     

A comparative life-cycle energy and emissions analysis for intercity passenger transportation in the U.S. by aviation,intercity bus,and automobile

Intercity passenger trips constitute a significant source of energy consumption, greenhouse gas emissions, and criteria pollutant emissions. The most commonly used city-to-city modes in the United States include aircraft, intercity bus, and automobile. This study applies state-of-the-practice models to assess life-cycle fuel consumption and pollutant emissions for intercity trips via aircraft, intercity bus, and automobile. The analyses compare the fuel and emissions impacts of different travel mode scenarios for intercity trips ranging from 200 to 1600 km. Because these modes operate differently with respect to engine technology, fuel type, and vehicle capacity, the modeling techniques and modeling boundaries vary significantly across modes. For aviation systems, much of the energy and emissions are associated with auxiliary equipment activities, infrastructure power supply, and terminal activities, in addition to the vehicle operations between origin/destination. Furthermore, one should not ignore the embodied energy and initial emissions from the manufacturing of the vehicles, and the construction of airports, bus stations, highways and parking lots. Passenger loading factors and travel distances also significantly influence fuel and emissions results on a per-traveler basis. The results show intercity bus is generally the most fuel-efficient mode and produced the lowest per-passenger-trip emissions for the entire range of trip distances examined. Aviation is not a fuel-efficient mode for short trips (<500 km), primarily due to the large energy impacts associated with takeoff and landing, and to some extent from the emissions of ground support equipment associated with any trip distance. However, aviation is more energy efficient and produces less emissions per-passenger-trip than low-occupancy automobiles for trip distances longer than 700–800 km. This study will help inform policy makers and transportation system operators about how differently each intercity system perform across all activities, and provides a basis for future policies designed to encourage mode shifts by range of service. The estimation procedures used in this study can serve as a reference for future analyses of transportation scenarios.     

Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

Greenhouse gas emissions from road construction: An assessment of alternative staging approaches

The greenhouse gas (GHG) emissions associated with road construction activities are analyzed. The main focus of this analysis is on the vehicle emissions associated with alternative project staging approaches, specifically a full closure of the road during construction, versus an intermittent road closure. The analysis includes the direct and upstream emissions associated with materials, construction equipment, mobilization of resources to the work site, and maintenance activity associated with the project over its lifetime. The analysis is based on one case study of a road project in New Jersey. The assumptions underlying the staging analysis are based on hypothetical approaches. Results provide an assessment of the main sources of project related emissions and the ability to minimize total project emissions by minimizing traffic disruption. In the analysis with a full closure of the road, traffic disruption accounts for 26% of total emissions, while with an intermittent road closure, traffic disruption accounts for only 2% of total emissions. The other main sources are from materials and life-cycle maintenance. The analysis demonstrates the feasibility of minimizing project related GHG emissions during road construction activities.     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.     

导电密封胶对不锈钢车体电阻点焊焊接性能影响研究

分析了电阻点焊原理,对相同的点焊搭接方式,分别采用3种工况进行焊接试验。3种工况分别采用相同焊接参数对搭接接触面涂导电密封胶和不涂导电密封胶的试件进行焊接;优化焊接参数后,对搭接接触面涂导电密封胶的试验件进行焊接。对3种工况下完成的焊接试件进行拉伸力检测试验、金相熔核尺寸检测和缺陷检测试验,对熔核直径、拉伸力、熔核内部缺陷的试验结果进行分析。试验结果表明:导电密封胶对电阻点焊的焊接性能存在影响;通过适当优化焊接参数,可以提高涂导电密封胶试件的焊接性能,焊接质量能够满足产品焊接要求。     

隧道瓦斯地段施工技术浅析

结合临吉高速公路S12合同段瓦窑岭隧道的瓦斯地段施工技术,从超前探孔、瓦斯监测、开挖支护及初衬等方面阐述了瓦斯隧道施工时的重点和注意事项。     

废气旁通阀开度对增压直喷汽油机部分负荷性能的影响

汽油机节气门产生的节流损失对增压发动机泵气损失的影响相当严重,尤其是在中小负荷时,针对这一问题采用试验的方法研究了中小负荷下旁通阀开度对增压直喷汽油机性能的影响。研究结果表明,在节气门开度较小的小负荷工况下,涡轮增压器不宜工作,否则排气背压过大,对发动机非常不利;而废气旁通阀全开可以减小排气背压,能使发动机的动力性和经济性提高3%左右。对废气旁通阀的合理控制可以实现发动机在自然吸气和涡轮增压两种模式之间的转换。     

海上油田伴生气用作燃料气的预处理方案研究

海上油田生产随着节能减排要求的提高,油田生产过程中的伴生气通过火炬排放的方式已不可取。详细介绍了伴生气去重烃化处理的技术过程。针对海上采油平台的特殊工况,提出了利用伴生气作为燃料的主机系统设计方案。     

不锈钢地铁车辆侧墙焊缝缺陷率分析

由于非熔透型激光叠焊工艺的局限性,侧墙焊缝处会产生内外钢板局部未焊透的现象即焊缝缺陷.为研究这种焊缝在不同缺陷率下的拉剪强度及其对车体静强度的影响,结合某不锈钢地铁车辆激光焊车体,通过建立不同焊缝缺陷率的车体有限元模型,分析各个工况下不同焊缝缺陷率的车体侧墙焊缝剪应力的变化,以此确定在静载工况下不锈钢激光焊车体侧墙焊缝缺陷率的限值.