How the cap limit for food-crop-based biofuels may affect France’s stakeholders by 2030? A range-based multi-actor multi-criteria analysis

From 2012 to 2016, the long-term signal in the biofuel market changed almost once per year, leading to a drastic decrease in investments and contributing to multiple production unit closures in France and around Europe. The European Commission proposed a new renewable energy directive that includes a 3.8% cap limit on the contribution of food-crop biofuels by 2030. Given the role of biofuels in green growth, the bioeconomy, and renewable energy incorporation targets, how will this measure affect the stakeholders by 2030? Will it lead to, contribute to, or hamper their sustainability criteria? This paper aims to contribute to this debate by studying the case of France. To this end, our methodology—the range-based multi-actor multi-criteria analysis—aims to (1) explicitly consider the stakeholder groups and their sustainability criteria; (2) evaluate and compare how the cap limit will affect these sustainability criteria whether or not advanced biofuels are deployed by 2030; (3) capture the uncertainty of the context evolution and biofuel capacity to fulfil the stakeholders’ sustainability criteria by means of a Monte Carlo. The results suggest that the cap limit is a double-edged sword for the stakeholders and their sustainability criteria. Shifting towards advanced biofuels while limiting the food-crop biofuels is the better alternative for most of the stakeholders. Nevertheless, given biofuel policy instability and the lost confidence of investors, such a shift may not occur by 2030. In such a case, this paper demonstrates that the cap limit may highly and negatively affect the stakeholders and their sustainability targets, whereas fostering French food-crop biofuel production at its full capacity level constitutes a better alternative. As no alternative is suited to all actors simultaneously, this paper also studies the strengths and weaknesses of these alternatives from each stakeholder groups’ perspective.     

尼铁现代化项目中矩形空心桥台的优化设计

当前常用的时速200 km的铁路矩形空心桥台参考图中的桥台截面尺寸偏厚,安全富余量很大。为节约混凝土圬工量,希望在保证安全的前提下减少桥台截面尺寸。首先提出专门针对铁路矩形空心桥台台身截面计算的荷载图示,然后利用这一新的图示对拉伊铁路项目中使用的常规矩形空心桥台进行有限元分析,经过不断试算提出最优的截面尺寸。在钢筋用量基本不变的情况下,新尺寸桥台较原参考图中桥台的混凝土用量减少10%以上。对于项目所在地尼日利亚国水泥价格高昂的情况而言,桥台尺寸的这一优化将产生较大的经济效益。     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

Simulation on progressive collapse behaviour of whole ship model under extreme waves using idealized structural unit method

To ensure the safety of navigating ship, working loads and structural load-carrying capacity are two important aspects. In the present paper, a total simulation system combing load calculation and structural collapse analysis is applied to simulate progressive collapse behaviour of a single-hull Kamsarmax type bulk carrier. A three dimensional singularity distribution method is adopted to calculate pressure distribution with time history. A mixed structural model, collapse part simulated by ISUM elements and remaining part by elastic FEM elements with relative coarse mesh, is proposed for collapse analysis. Progressive collapse behaviour obtained by ISUM is good agreement with that by nonlinear software package, MARC. However, the calculation time of ISUM analysis is about 1/70 of MARC analysis. The applicability to structure system, high accuracy and sufficient efficiency of ISUM had been demonstrated.     

A regression and beam theory based approach for fatigue assessment of containership structures including bending and torsion contributions

Container shipping has been expanding dramatically during the last decade. Due to their special structural characteristics, such as the wide breadth and large hatch openings, horizontal bending and torsion play an important role to the fatigue safety of containerships. In this study the fatigue contributions from vertical bending, horizontal bending and torsion are investigated using full-scale measurements of strain records on two containerships. Further, these contributions are compared to results from direct calculations where a nonlinear 3D panel method is used to compute wave loads in time domain. It is concluded that both bending and torsion have significant impacts on the fatigue assessment of containerships. The stresses caused by these loads could be correctly computed by full-ship finite element analysis. However, this requires large computational effort, since for fatigue assessment purposes the FE analysis needs to be carried out for all encountered sea states and operational conditions with sufficient time steps for each condition. In this paper, a new procedure is proposed to run the structure finite element analysis under only one sea condition for only a few time steps. Then, these results are used to obtain a relationship between wave loads and structural stresses through a linear regression analysis. This relation can be further used to compute stresses for arbitrary sea states and operational conditions using the computed wave loads (bending and torsion moments) as input. Based on this proposed method for structure stress analysis, an efficient procedure is formulated and found to be in very good agreement with the full-ship finite element analysis. In addition it is several orders of magnitude more time efficient for fatigue assessment of containership structures.     

运梁河特大桥转体梁不平衡重称重试验分析

哈大客专运粮河特大桥跨既有线连续梁采用平转法施工,为确保转体顺利进行,转体前进行了T构不平衡重试验分析,文中介绍了一种转体构件不平衡重的测试方法和应用过程。结果表明,方法有效可行,可供同类工程借鉴。     

Comparing different contour methods with response-based methods for extreme ship response analysis

Environmental contours are often applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. They facilitate approximate long term analysis of critical structural responses in situations where computationally heavy and time-consuming response calculations makes full long-term analysis infeasible. The environmental contour method identifies extreme environmental conditions that are expected to give rise to extreme structural response of marine structures. The extreme responses can then be estimated by performing response calculations for environmental conditions along the contours.Response-based analysis is an alternative, where extreme value analysis is performed on the actual response rather than on the environmental conditions. For complex structures, this is often not practical due to computationally heavy response calculations. However, by establishing statistical emulators of the response, using machine learning techniques, one may obtain long time-series of the structural response and use this to estimate extreme responses.In this paper, various contour methods will be compared to response-based estimation of extreme vertical bending moment for a tanker. A response emulator based on Gaussian processes regression with adaptive sampling has been established based on response calculations from a hydrodynamic model. Long time-series of sea-state parameters such as significant wave height and wave period are used to construct N-year environmental contours and the extreme N-year response is estimated from numerical calculations for identified sea states. At the same time, the response emulator is applied on the time series to provide long time-series of structural response, in this case vertical bending moment of a tanker. Extreme value analysis is then performed directly on the responses to estimate the N-year extreme response. The results from either method will then be compared, and it is possible to evaluate the accuracy of the environmental contour method in estimating the response. Moreover, different contour methods will be compared.     

桥墩及桩基形式对墩底平转施工转盘设计的影响

以新建福厦(福州—厦门)高速铁路17500 t转体刚构为背景,采用实体有限元方法分析了不同桥墩类型及桩基布置对墩底平转转体中转盘受力的影响,并对桥墩及桩基进行了优化。结果表明:实体墩对上转盘受力最有利,其次是空心墩,最不利的是双薄壁墩;增加墩底实体段能够有效降低空心墩、双薄壁墩上转盘的主拉应力;随着墩底实体段高度的增加,主拉应力降低的幅度逐渐变小;球铰正下方有桩基时对下转盘底部受力更加有利;距离球铰中心越远,桩基受力越小,适当增加中桩桩径,可使各桩基应力状态更加均衡。     

车辆隔热壁K值计算中空气层的处理方法

对轨道交通车辆多层复合结构的隔热壁进行隔热性能理论计算与仿真计算的对比,对隔热壁内部空气层的隔热性能进行分析。结论为:在车辆多层复合结构的隔热壁K值计算中,当空气层厚度大于一定厚度时,流体自然对流对隔热壁的隔热性能影响较大。利用多项式密度(Polynomial Denisity)和Boussinesq模型两种算法,对所得结论进行了验证。     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.