Range Of Transportation Applications Research Articles

Catalytic arene-norbornene annulation (CANAL) ladder polymer derived carbon membranes with unparalleled hydrogen/carbon dioxide size-sieving capability

Hydrogen is an emerging energy source with a wide range of applications in transportation, electricity generation, and manufacturing of important chemicals such as ammonia and methanol. Hydrogen is commonly coproduced with CO2 using steam reforming of methane and its purification is typically achieved using energy-intensive processes such as pressure swing adsorption (PSA) and cryogenic distillation. Membrane technology with potentially lower energy consumption and lower carbon footprint could play an important role in developing a more sustainable hydrogen economy. In this study, we prepared carbon molecular sieve (CMS) membranes by the pyrolysis of a highly aromatic catalytic arene-norbornene annulation (CANAL)-Tröger's base ladder polymer of intrinsic microporosity precursor — CANAL-TB-1. CMS membranes obtained by pyrolysis between 600 and 900 °C displayed excellent gas separation performance for hydrogen/carbon dioxide separation and related applications. The CANAL-CMS-800 °C membrane showed a pure-gas hydrogen permeability of 41 Barrer with H2/CO2, H2/N2, and H2/CH4 selectivity values of 39, 1952, and >8200 at 35 °C. Increasing the pyrolysis temperature to 850 and 900 °C further boosted the selectivity. For example, the CANAL-CMS-900 °C exhibited a stable long-term mixed-gas performance over a period of 38 days with an unprecedented H2/CO2 selectivity of 174 and H2 permeability of 8.2 Barrer at 10 bar total feed pressure and 100 °C, which significantly exceeded the performance of previously reported polymers and related CMS membrane materials.

Mathematical Model and Simulated Annealing Algorithm for the Two-Dimensional Loading Heterogeneous Fixed Fleet Vehicle Routing Problem

This paper addresses the two-dimensional loading heterogeneous fixed fleet vehicle routing problem, which is a complex and unstudied variant of the classical vehicle routing problem and has a wide range of applications in transportation and logistics fields. In this problem, each customer demands a set of rectangular two-dimensional items, and the objective is to find the minimum cost delivery routes for a limited set of vehicles with different capacities, fixed and variable operating costs, and rectangular two-dimensional loading surfaces. We formulate a mixed integer linear programming model to obtain optimal solutions for small-scale problems. To obtain solutions for large-scale problems, we develop an algorithm based on simulated annealing and local search, which uses a collection of packing heuristics to address the loading constraints, and we also propose three new heuristics. We conduct experiments on benchmark instances derived from the two-dimensional loading heterogeneous fleet vehicle routing problem. The results indicate that the proposed model correctly describes the problem and can solve small-scale problems, that the new packing heuristics are effective in improving the collection of packing heuristics, and that the proposed simulated annealing algorithm can find good solutions to large-scale problems within an acceptable computational time. Hence, it can be used by logistic companies using a heterogeneous fixed fleet in the integrated planning of vehicle loading and routing.

Vehicular multihop intelligent transportation framework for effective communication in vehicular ad‐hoc networks

AbstractIn the smart city, the presence of intelligent transportation systems (ITS) is much essential. The emerging vehicular ad‐hoc networks (VANET) technology offers a wide range of applications in transportation, mobility, connectivity, and safety applications. In this decade, vehicular traffic is a prime hassle. The actual‐instant traffic data to drivers along with navigation system would facilitate vehicles to select an excellent path. This article proposes hybrid VANET architecture for effective communication between vehicles. The proposed hybrid architecture uses the multihop routing algorithm to permit vehicles to enlarge their driving performance and road safety. The proposed hybrid vehicular multihop routing algorithm with intelligent transportation system (Hybrid VMR‐ITS) allows the transportation system for instantaneous communications between vehicles and road‐side units (RSUs) and vehicles‐traffic servers effectively. The proposed work enhanced the whole spatial usage of a road network by reducing average vehicle travel costs with a reduced traffic overhead of 4%–9% compared with existing works.

A hybrid swarm algorithm based on ABC and AIS for 2L-HFCVRP

This paper mainly addresses the heterogeneous fleet capacitated vehicle routing problem with two-dimensional loading constrains (2L-HFCVRP). The 2L-HFCVRP is a combination of two NP-hard problems and has a wide range of applications in transportation and logistics fields. In this paper, we propose a hybrid swarm algorithm, which is a combination of Artificial Bee Colony (ABC) algorithm and Artificial Immune System (AIS) algorithm, to solve the 2L-HFCVRP. The proposed algorithm is allowed to search infeasible solutions and several efficient strategies are developed to escape from local optima. The extensive computational results on several well-known benchmark data sets verify the effectiveness of the proposed algorithm. The proposed algorithm is shown to outperform the best algorithms in the literature for 2L-HFCVRP instances.

Thermoset Polymer Reinforced With Silica Micro and Nanoparticles

Abstract Fiber-reinforced composites (FRCs) have been used to replace conventional materials in a wide range of applications in transportation and civil engineering. The dispersion of nanoparticles and microparticles into epoxy matrix phase has been widely investigated to enhance the mechanical properties of hybrid FRCs. The nanoparticles generate large attractive forces among themselves, providing a significant tendency to agglomerate. A chemical treatment based on diallyldimethylammonium chloride (PDDA) was evaluated to disperse the silica nanoparticles within the epoxy polymer. A microstructural analysis was conducted to better assess the results. Experimental analysis was carried out based on the analysis of variance (ANOVA) and Tuckey test in order to verify the effect of PDDA treatment, silica particle size (micro and nano), and silica particle inclusion (1, 2, and 3.5 wt.%) on the mechanical properties of epoxy polymer commonly used as matrix phase in FRCs. The PDDA treatment was able to disperse the silica nanoparticles. The incorporation of 1 wt. % of silica micro or 1 and 2 wt. % of nanoparticles slightly improved the tensile strength and modulus of the epoxy polymer.

A hybrid meta-heuristic algorithm for solving real-life transportation network design problems

The network-design problem (NDP) has a wide range of applications in transportation, telecommunications, and logistics. The idea is to efficiently design a network of links (roads, optical fibres, etc.) enabling the flow of commodities (drivers, data packets, etc.) to satisfy demand characteristics. Various exact and heuristic methods such as branch and bound, Tabu search, genetic algorithm (GA), ant system (AS) have been developed to address the NDP which is a highly intractable combinatorial problem. The literature has yet to address the NDP in real-size networks. In this study, we propose a new meta-heuristic algorithm for solving large NDPs by hybridising GA and AS methods. The applicability of the proposed meta-heuristic approach to real-size networks is demonstrated at two different sites. First, we use a large real-life problem for the city of Winnipeg, Canada and show that our heuristic method produces exact solutions very efficiently. Second, we evaluate the performance of the proposed algorithm using the data of Sioux Falls (a benchmark in the literature). While the proposed approach produces solutions similar to the other available methods in the literature, it is superior for developing solutions in large-size NDPs.

Uncertainty Issues in Integrating Geographic Information Systems and the Global Positioning System for Transportation

The Global Positioning System (GPS) and geographic information systems (GIS) have been integrated for a wide range of transportation applications. When a linear datum is not implemented into the applications, a route measure is indirectly determined with snapped GPS-derived coordinates along roadway centerlines. Thus, uncertainties in output information are subject to various types of error and error sources in GPS and roadway centerline maps and their propagation through spatial operations. A method for uncertainty analysis is presented. The method estimates the quality of output information from GPS- and GIS-integrated applications for transportation. The method involves an analytical GPS error model and an error propagation model, assuming that a test roadway centerline map is representative of roadway centerline maps with the same nominal scale. In the case study, the method was applied to a winter maintenance application and a travel time study. The optimum input data set for each application was determined by sensitivity analysis that explored the impact of positional uncertainties on variations of output information computed from distance-based and non-distance-based computation models. Results indicated that the winter maintenance application required accurate input data because uncertainties in output information were accumulated as winter maintenance vehicles repeatedly treated roadways. However, for the travel time study, consistent output information was computed with a minute level of accuracy, so positional uncertainties in input data had a negligible impact on output information.

3CR12 Stainless steel aid design of Coachwork Walker ambulance and welfare vehicle

3CR12 was introduced into the transport industry by Duple International when, three years ago, they utilised the low cost stainless steel to fabricate the spaceframes for their Integral 425 coaches. Since then 3CR12, which is supplied by Cromweld Steels Ltd, has been used in a wide range of transport applications where the proven structural properties of the steel offer safety, strength and design economy.

A scenario approach to airport evaluation in remote communities: with particular reference to the Pilbara region of Australia

Coordinated development of aviation facilities and services is critical for geographically remote communities. Improvements in aviation capability can be assisted by an analytical base for determining the implications of alternative configurations of air services in terms of links to be served, airport/aerodrome investment, type of flight equipment and flight frequency. We outline a method for identifying airport supply configurations to meet air service demand to and from the Pilbara region of north-west Australia. The approach emphasises minimum levels of demand required from a community in order to justify provision of air services of a given scenario. The method is influenced by the paucity of data on demand in remote communities, and the consequent risk of relying solely on demand-side forecasts of patronage levels. It is therefore particularly useful in assessing transport systems associated with remote resource development projects which are notable for the rapidity of change which they can bring. The approach has relevance to a wide range of transport applications.

Constrained Entropy Models; Solvability and Sensitivity

The paper presents an analysis of the constrained entropy maximization model from the point of view of geometric programming. While the original entropy maximization model consists of maximizing the entropy of a system subject only to constraints that the solution be a probability measure, the models considered here contain an additional set of linear constraints. These constrained models have been the subject of a wide range of applications in transportation and geographical analysis. Using the duality theory of geometric programming, we develop the dual to the constrained model, which as in the case of the original model is unconstrained except for the positivity restrictions on the dual variables. In addition, this duality theory enables us to study the solvability of the model and the impact of changes in the model parameters on the solution. The sensitivity analysis provides approximations to the optimal solution to problems with perturbed data without requiring the re-solving of the model. This analysis is appropriate for changes in the right hand sides of the constraints, the coefficients in the constraints, and the objective function coefficients. Since the constraint coefficients correspond to the objective function exponents in the primal geometric program, the analysis provides a means of studying such changes is any geometric program. The computational aspects of the procedures are illustrated on a trip distribution problem.