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Hydrogen—An Alternative Fuel for Automotive Diesel Engines Used in Transportation. SUSTAINABILITY 2020. [DOI: 10.3390/su12229321] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Considering the current environmental restrictions, particularly those imposed on fossil fuel exploitation, hydrogen stands out as a very promising alternative for the power and transportation sectors. This paper investigates the effects of the employment of hydrogen in a K9K automotive diesel engine. Experiments were conducted at a speed of 2000 min−1 with various engine load levels of 40%, 55%, 70%, and 85%; several quantities were monitored to evaluate the performance with hydrogen use in terms of brake-specific energetic consumption (BSEC), fuel economy, maximum pressure, and heat-release characteristics. It was found that at 55% engine load, the engine efficiency increased by 5.3% with hydrogen addition, achieving a diesel fuel economy of 1.32 kg/h. The rate of increase of the peak pressure and maximum pressure started to increase as a consequence of the higher fuel quantity that burned in the premixed combustion phase, while still remaining within reliable operational limits. The accelerated combustion and augmented heat release rate resulted in a combustion duration that was reduced by 3° CA (crank angle degree), achieving a mass fraction burned percentage of 10% to 90% earlier in the cycle, and the combustion variability was also influenced. Hydrogen use assured the decrease of CO2, HC, NOx, and smoke emission levels in comparison with classic fueling.
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An Intelligent Advisory System to Support Managerial Decisions for A Social Safety Net. ADMINISTRATIVE SCIENCES 2019. [DOI: 10.3390/admsci9030055] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Social investment programs are designed to provide opportunities to the less privileged so that they can contribute to the socioeconomic development of society. Stakeholders in social safety net programs (SSNPs) target vulnerable groups, such as the urban poor, women, the unemployed, and the elderly, with initiatives that have a transformative impact. Inadequate policy awareness remains a challenge, resulting in low participation rates in SSNPs. To achieve all-inclusive development, deliberate policies and programs that target this population have to be initiated by government, corporate bodies, and public-minded individuals. Artificial intelligence (AI) techniques could play an important role in improving the managerial decision support and policy-making process of SSNPs and increasing the social resilience of urban populations. To enhance managerial decision-making in social investment programs, we used a Bayesian network to develop an intelligent decision support system called the Social Safety Net Expert System (SSNES). Using the SSNES, we provide an advisory system to stakeholders who make management decisions, which clearly demonstrates the efficacy of SSNPs and inclusive development.
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Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway. SUSTAINABILITY 2019. [DOI: 10.3390/su11113057] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
To support the rapid growth of demand in passengers and freight, separating trucks and passenger-cars is a potential solution to improve traffic efficiency and safety. The primary purpose of this paper is to comprehensively assess the multilane separate freeway at Huludao Toll Station in Liaoning Province, China. Based on the configuration and segmentation of the freeway near a toll station, a six-step guidance strategy is designed to adapt to the separate organization mode. Five conventional traffic scenarios are designed in the Vissim platform for comparative analysis between different guidance strategies. To investigate the vehicle-to-infrastructure (V2I) environment, a microscopic testbed is established with cooperative car-following and lane-changing models using the MATLAB platform. The numerical simulation results show that the guidance strategy significantly improves efficiency and safety, and also reduces emissions and fuel consumption. Meanwhile, pre-guidance before toll channels outperforms the scenario only applied with guidance measures after toll plaza. Compared to conventional conditions, the assessment of pollutant emissions and fuel consumption also embodies the superiority of the other five scenarios, especially in the sections of toll plaza and channels with the lowest efficiency and safety level. Generally, all indexes indicate that the cooperative V2I technology is the best alternative for multilane separate freeways.
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