Can hydrogen be the sustainable fuel for mobility in India in the global context?

This article provides a critical assessment of H₂ from the standpoint of more widespread use as a sustainable fuel for Indian mobility applications in the global context. The potential techno-economic advantages of utilizing H₂ for automobiles rather than battery electric vehicles or conventional internal combustion engine vehicles are emphasized. The present assessment demonstrates that H₂ production, storage, and distribution costs are the primary challenges, and a significant improvement is still necessary for H₂ to compete either against the internal combustion engine vehicle or the battery electric vehicle to win the race, arguably. The secondary challenges have also been demonstrated, which include the cost of the fuel cell stack and the modifications associated with internal combustion engine vehicles, as well as regulatory and safety concerns, which impede the widespread usage of H₂. It is critical that policy-making for sustainable mobility in India is possible with the aid of a National H₂ Energy Road-Map. This in turn can achieve a cost target of $0.5/kg for H₂.     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.     

Numerical study of entropy generation in Darcy-Forchheimer (D-F) Bödewadt flow of CNTs

Three-dimensional Bödewadt flow (fluid rotates at a large enough distance from the stationary plate) of carbon nanomaterial is examined. Single walled and multi walled CNTs are dissolved in water and gasoline oil baseliquids. Darcy-Forchheimer porous medium is considered. Stationary disk is further stretched linearly in radial direction. Heat transfer effect is examined in presence of radiation and convection. Effect of viscous dissipation is accounted. Entropy generation rate is studied. By using adequate transformation (von Kármán relations), the flow field equations (PDEs) are transmitted into ODEs. Solutions to these ODEs are constructed via implementation of shooting method (bvp4c). In addition to Entropy generation rate, Bejan number, heat transfer rate (Nusselt number), skin friction and temperature of fluid are examined through involved physical parameters. Axial component of velocity intensifies with increment in nanoparticles volume fraction and ratio of stretching rate to angular velocity parameter while it decays with higher porosity parameter. Higher nanoparticles volume fraction and porosity parameter lead to decay in radial as well as tangential component of velocity. However it enhances with higher ratio of stretching rate to angular velocity parameter. Temperature of fluid directly varies with higher ratio of stretching rate to angular velocity parameter, radiation parameter, Eckert number, Biot number and nanoparticles volume fraction. Rate of Entropy generation is reduced with higher estimations of porosity parameter, nanoparticles volume fraction and radiation parameter. Skin friction coefficient decays with higher porosity parameter and ratio of stretching rate to angular velocity parameter. Intensification in porosity parameter, nanoparticles volume fraction and Biot number leads to higher Nusselt number. Prominent impact is shown by multiple-walled CNTs with gasoline oil basefluid than single-walled CNTs with water basefluid.     

A terrain risk assessment method for military surveillance applications for mobile assets

This study proposes an analytical and flexible terrain risk assessment method for military surveillance applications for mobile assets. Considering the risk as the degree of possibility of insurgent presence, the assessment method offers an efficient evaluation of risk in the surrounding terrain for military combat operating posts or observation posts. The method is designed for unmanned aerial vehicles as the surveillance assets of choice to improve the effectiveness of their use. Starting with the area map and geographical data, the target terrain is first digitized for space representation. Then the data of nine geographical parameters are used to formulate five contributing risk factors. These factors are incorporated in an analytical framework to generate a composite map with risk scores that reveal the potential high-risk spots in the terrain. The proposed method is also applied to a real-life case study of COP Kahler in Afghanistan, which was a target for insurgent attacks in 2008. The results confirm that when evaluated with the developed method, the region that the insurgents used to approach COP Kahler has high concentration of high-risk cells.     

Assessing the cost-effectiveness of electric vehicles in European countries using integrated modeling

Electric vehicles (EVs) are considered alternatives to internal combustion engines due to their energy efficiency and contribution to CO₂ mitigation. The adoption of EVs depends on consumer preferences, including cost, social status and driving habits, although it is agreed that current and expected costs play a major role. We use a partial equilibrium model that minimizes total energy system costs to assess whether EVs can be a cost-effective option for the consumers of each EU27 member state up to 2050, focusing on the impact of different vehicle investment costs and CO₂ mitigation targets. We found that for an EU-wide greenhouse gas emission reduction cap of 40% and 70% by 2050 vis-à-vis 1990 emissions, battery electric vehicles (BEVs) are cost-effective in the EU only by 2030 and only if their costs are 30% lower than currently expected. At the EU level, vehicle costs and the capability to deliver both short- and long-distance mobility are the main drivers of BEV deployment. Other drivers include each state’s national mobility patterns and the cost-effectiveness of alternative mitigation options, both in the transport sector, such as plug-in hybrid electric vehicles (PHEVs) or biofuels, and in other sectors, such as renewable electricity.     

实施油气回收的必要性和技术方案的探讨

简要介绍油气回收技术;从环保和增加经济效益的角度,以福建炼化公司的实际情况为例提出了油气回收的方案,并对实行该方案的必要性和经济效益做了分析;希望增强炼化企业对油气回收问题的重视,达到安全生产、改善环境和节约能源的目的。     

Trace elements in particles of motor vehicle exhaust in Shanghai

A nuclear microprobe with high spatial resolution and high analytical sensitivity was applied to analyze trace elements,especially lead,in vehicle exhaust of Shanghai city.The result shows that the chemical composition and its corresponding x-ray relative intensity are different among different vehicle exhausts.There are many kinds of metal elements in particles of vehicle exhaust.most are harmful to people,such as Ti,Cr,Mn,Pb,etc.We found that the lead concentration was 6820μg/g and the bromine concentration was 5300μg/g in the exhaust from Santana using leaded gasoline(SULG).which is higher than any other kinds of vehicle exhausts.We have also detected the minimum lead in the particles of unleaded gasoline and its content varies from one to another.Its mean concentration was 450μg/g and the highest reached 6210μg/g.The unleaded gasoline‘s Pb existed in the whole particle while the leaded gasoline‘s enriched in the surface of the particle and was more harmful to the human beings.     

催化裂化汽油选择性加氢脱硫催化剂RSDS-1的开发

介绍了用于催化裂化汽油选择性加氢脱硫催化剂RSDS-1的研究开发，考察了载体、活性组元、金属原子比以及助剂对催化剂选择性的影响。研究结果表明，催化裂化汽油中烯烃的加氢饱和受扩散限制；Co—Mo组合对烯烃饱和的能力相对较弱；较高的Co／Mo原子比有利于提高催化剂选择性；助剂的加入对催化剂选择性有明显的影响；RSDS—1催化剂用于催化裂化汽油选择性脱硫，对不同原料油适应性好，脱硫率可达80％，RON损失小于2个单位，且可长周期稳定运转。     

A novel MINLP-based representation of the original complex model for predicting gasoline emissions

The Environmental Protection Agency (EPA) introduced Reformulated Gasoline (RFG) requirements as a measure to reduce emissions from gasoline-powered vehicles in certain geographic areas. As part of this effort, the EPA developed empirical models for predicting emissions as a function of gasoline properties and established statutory baseline emissions from a representative set of gasolines. All reformulated gasoline requires certification via this model, known as the Complex Model, and all refiners and importers calculate emissions performance reductions from the statutory baseline gasoline. The current representation of the Complex Model is extremely difficult to implement within refinery operations models or to use in combination with models for designer gasoline. RFG and boutique fuels are key driving forces in the North American refining industry.The RFG models introduce increasingly complex constraints with the major limitation that they are implicitly defined through a series of complicated disjunctions assembled by the EPA in the form of spreadsheets. This implicit and cumbersome representation of the emissions predictive models renders rigorous optimization and sensitivity analysis very difficult to address directly. In this paper, we discuss how the federal government requirements for reformulated gasoline can be restated as a set of mixed-integer nonlinear programming (MINLP) constraints with the aid of disjunctive programming techniques. We illustrate the use of this model with two simple example fuel blending problems.