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Transport of people and goods has always been associated with the generation of some form of pollution, whether atmospheric, sound or visual. Managing the urban environment presents a major challenge: preserving environmental resources and also ensuring decent living conditions for the current population and for future generations. In the era of motorized and carbonized transport, vehicles are the main source of emission of atmospheric pollutants, mainly in large urban centers and important precursors of ozone. An important advance in minimizing vehicle emissions was the introduction of cleaner and additive fuels into the Brazilian market. The purpose of this paper is to study the effect of the Dienitro additive on the NO_x and CO emissions in buses of collective transport, Diesel S-50 exhaust gas recirculation (EGR) and S-10 with selective catalytic reduction (SCR) and EGR systems. Measurements of CO and NO_x gas emissions were carried out using a gas analyzer in S50 and S10 diesel buses with an EGR and SCR systems from a company operating in the collective transport of Biguaçu.

In this study, 20 measurements were performed without additives and 20 measurements with additivation in each bus, making it possible to calculate the average emission rate of CO and NO_x, pollutant gases with toxic effect.

The usage of Dienitro additive in diesel engines resulted in a significant reduction in the emission of polluting gases, carbon monoxide (CO) and nitrogen oxide (NO_x), thus being efficient in reducing the emissions of these gases.

The Dienitro additive was first tested on diesel engines by public transport buses, and there is great potential for reducing the emission of toxic gases.

Nitrogen oxides (NO_x) have been considered as primarily responsible for many serious environmental problems. Removing NO is the key task to remove NO_x hazards. To clarify, NO removal process for pitch-based spherical-activated carbons (PSACs), an online prediction and optimization technique in real-time based on support vector machine algorithm in regression (support vector regression [SVR]) is discussed. The purpose of this paper is to develop a predictor and optimizer system on selective catalytic reduction of NO (SCRN) using experimental data and data-driven SVR intelligence methods.

Predictor and optimizer using developed SVR have been proposed. To modify the training efficiency of SVR, the authors especially customize batch normalization and k-fold cross-validation techniques according to the unique characteristics of PSACs model.

The results present that SVR provides a property regression model since it can linkage linear and non-linear process and property relationships in few experimental data sets. Also, the integrated normalization and k-fold cross-validation show a satisfying improvement and results for SVR optimization. The predicted results of predictor and optimizer in single and double factor systems are in excellent agreement with the experimental data.

SCRN-PO for predicting and optimization SCRN problems is developed by data-driven methods. The outperformed SCRN-PO system is used to predict multiple-factors property parameters and obtain optimum technological parameters in real-time. Also, experiment duration is greatly shortened.

Ammonia injection grid (AIG) is used as an input device for ammonia which reacts with NO_x in the selective catalytic reduction (SCR) reactor. However, non-uniform concentration distribution of ammonia could produce partially poisoning or deposits of the catalyst. In this work, for making ammonia widely distributed throughout the flue gas and fully mixed, an optimization method of AIG is proposed.

Depending on the complexity of fluid flow, the relation between the concentration distributions of ammonia and the geometric parameters of AIG is nonlinear. Based on a certain amount of AIG samples, the computational fluid dynamics (CFD) simulations are applied to propose the agent model which describes the functional relation of the deviation of ammonia concentration and the geometric parameters of AIG. The optimization model of AIG based on the agent model is established. The optimized AIG based on the agent model can be used to produce uniform concentration distributions of ammonia, especially in the case that velocity distribution of flue gas is non-uniform.

For qualitatively confirming this optimization method, the three-dimensional CFD simulation of the optimized AIG is carried out. The results reveal that the diffusion process of ammonia gas is consistent with the development of the local vortices, which have a certain relation with the velocity distribution of the flue gas. The unequal ammonia injection designed by the optimization based on the agent model promotes a better mixing of ammonia and flue gas.

In this work, first, the method for optimizing AIG based on the agent model is proposed. Second, the three-dimensional CFD modeling and simulation of the optimized AIG is carried out, and the mixing effects of ammonia and flue gas are presented.

Mahindra Trucks and Bus Division (MTBD) of Mahindra & Mahindra is at an interesting stage of its evolution. Having gone through a bad patch with a product that was not quite up to the mark, it appears to have got the product right by early 2018 and truck sales had been going up in the country for the previous four years. While Mahindra & Mahindra as a company is a large firm with revenues of more than USD 15 billion, MTBD itself is a small player (INR 2400 crore, USD 350 million) within the firm and in an Indian truck industry that is dominated by goliaths, Tata Motors and Ashok Leyland that between them had more than 81% market share and a customer mindset that was loath to leave the comfort of a known brand. The case provides data on product specifications, prices, marketing communication, channels, positioning, the context and competition. The intention is to use the case to go through the steps involved in evaluating and developing and creating a marketing plan for MTBD to increase its market share from the 4% in 2018 to an intended 8% in 2022.

Purpose – The shipping industry is generally recognised as having better fuel efficiency than other transport modes. In many regions of the world, therefore, policy has promoted shipping as the preferred freight transport mode of choice. In recent years, however, environmental problems associated with shipping have emerged. Several influential analyses have revealed the impact of shipping on air quality, particularly in the form of emissions of sulphur, nitrogen oxides and particulate matter, all of which have adverse consequences for human health.

Methodology/approach – An extensive environmental profile of shipping is provided, focusing specifically on the atmospheric pollution that is directly attributable to shipping operations.

Findings – It is important, however, to place the environmental profile of the shipping industry into the context of exactly how much transport work it does. This makes it clear that where shipping is a viable modal alternative then, in relative terms and most contexts, it still retains significant environmental advantages over other modes. The industry and its regulators have been slow, however, to improve its environmental profile and maintain its inherent advantage. Technical and operational measures which the industry may implement unilaterally are analysed, but these are deemed insufficient to stem the adverse tide of environmental concerns. Regulation is a necessity. Recently implemented regulatory measures are analysed, together with possible scenarios for the future regulation of greenhouse gas emissions. The IMO approach of global regulation is supported in preference to regionally based regulatory policies. There is also a danger that regulatory intervention may distort mode choice contexts.

Originality/value – The provision of an extensive environmental profile of shipping and an examination of this profile in relation to the importance of this transport mode to the global economy.

This study aims to analyze simplified methods for modelling the flow through perforated elements (i.e. porous baffle interface and porous region), searching for a faster and easier way to simulate these components. The numerical simulations refer to a muffler geometry available in literature as a case study.

The installation of scrubber onboard ships to satisfy the International Maritime Organization emissions regulations is a reliable and efficient solution. However, scrubbers have considerable dimensions, interfering with other exhaust line components. Therefore, scrubber installation in the funnels requires integration with other elements, for example, silencers. Perforated pipes and plates represent the main elements of scrubber and silencers. The study of their layout is, therefore, necessary to reduce emissions and noise. Numerical simulations allow evaluating the efficiency of integrated components.

The study highlights that velocity and pressure predicted by the simplified models have a strong correlation with the resistance coefficients. Even though the simplified models do not accurately reproduce the flow through the holes, the use of such models allows a fast and easy comparison between concurrent muffler geometries, giving aid in the early design phases.

The lack of general guidelines and comparisons in the literature between different modelling strategies of perforated elements supports the novelty of the present work and its impact on design applications. Study the flow inside scrubbers and mufflers is fundamental to evaluate their performances. Therefore, having a simple numerical method is suited for industrial applications during the design process.

The purpose of this paper is to discuss the performance of a proposed machine design for an in‐wheel motor with the required torque‐speed characteristic.

Calculation of the winding factor of the machine with the star of slots theory is performed first. The field weakening capability of the machine is investigated and the operating speed range is determined. The tooth contour modeling method for calculating the performance of the machine with a limited number of elements is introduced. The method is used to construct two models of different complexity and the results obtained with the models are compared with the results obtained by finite element models.

The 14 pole 12 slot in‐wheel PMSM discussed in this paper is able to meet the stringent performance requirements. The results obtained with the tooth contour models show good agreement with the results obtained with finite element models despite the limited number of elements. Increasing the number of elements in the model allows for modeling of armature reaction and increases the accuracy of the model.

This work can be continued with investigating the possibilities to model the armature reaction more accurately.

This paper proposes a modeling method which accurately describes the performance of a PMSM with limited number of elements. With this method, the calculation procedure can be easily used for optimization of the machine design.

The article investigates factors associated with the relative success in adopting two specific alternative marine energies (liquefied natural gas [LNG] and electric batteries) in the Norwegian ferry market. This specific market segment is an interesting case study as its national-flagged fleet boasting the largest number of ships using alternative marine energies in comparison with the other countries of the region and the world.

A database tracking the yearly deployment of ships using a different combination of LNG and electric batteries was built from shipping lines’ online information and grey literature. The technological adoption approach was used to categorize different groups of users at each step of the adoption process and identify which factors separate the early adopters from the other groups of end-users. The compiled data allow tracing the changing distribution of Norwegian ferry operators along the conceptualized technology adoption curve.

Results indicated that the Norwegian ferry market matches required conditions to pass the “chasm” of uncertainties associated with transitioning to new technology. Some disparities between the adoption of LNG and the electric batteries in the Norwegian ferry markets are observed.

To the authors’ knowledge, no study has explored the adoption of new energies in the maritime industry based on the technology adoption process through a similar perspective. The analysis is helpful to shed light on the barriers associated with a high level of uncertainties when it comes to adopting new marine energies.

This work aims to investigate the effects of neglecting, modelling or partly resolving turbulent fluctuations of velocity, temperature and concentrations on the predicted turbulence-chemistry interaction in urea-selective non-catalytic reduction (SNCR) systems.

Numerical predictions of the NO conversion efficiency in an industrial urea-SNCR system are compared to experimental data. Reactor models of varying complexity are assessed, ranging from one-dimensional ideal reactor models to state-of-the-art computational fluid dynamics simulations based on the detached-eddy simulation (DES) approach. The models use the same reaction mechanism but differ in the degree to which they resolve the turbulent fluctuations of the gas phase. A methodology for handling of unknown experimental data with regard to providing adequate boundary conditions is also proposed.

One-dimensional reactor models may be useful for a first quick assessment of urea-SNCR system performance. It is critical to account for heat losses, if present, due to the significant sensitivity of the overall process to temperature. The most comprehensive DES setup evaluated is associated with approximately two orders of magnitude higher computational cost than the conventional Reynolds-averaged Navier–Stokes-based simulations. For studies that require a large number of simulations (e.g. optimizations or handling of incomplete experimental data), the less costly approaches may be favored with a tolerable loss of accuracy.

Novel numerical and experimental results are presented to elucidate the role of turbulent fluctuations on the performance of a complex, turbulent, reacting multiphase flow.