A Review of the Existing Potentials in Biodiesel Production in Iran

Robust sustainable canola oil-based biodiesel supply chain network design under supply and demand uncertainty

The excessive consumption of fossil fuels has sparked debates and caused environmental damage, leading the global community to search for a suitable alternative. To achieve sustainable development goals and prevent harmful climate scenarios, the world needs to increase its use of renewable energy. Biodiesel, a clean and eco-friendly fuel with a high flash point and more lubrication than petroleum-based fuels, and without the emission of harmful environmental gases, has emerged as one of the fossil fuel alternatives. To promote the mass-level production of biodiesel, a sustainable supply chain (SC) that does not depend on laboratory production is necessary. For this purpose, this research proposes a multi-objective mixed-integer non-linear mathematical programming (MINLP) model to design a sustainable canola oil-based biodiesel supply chain network (CO-BSCND) under supply and demand uncertainty. This mathematical model aims to minimize the total cost (TC) and total carbon emission while maximizing the total number of job opportunities simultaneously. A scenario-based robust optimization (SBRO) approach is applied to deal with uncertainty. The proposed model is implemented in a real case study in Iran, and numerical experiments and sensitivity analysis are conducted to demonstrate its applicability. The results of this research demonstrate that designing a sustainable supply chain network for the production and distribution of biodiesel fuel is achievable. Moreover, this mathematical modeling makes mass-scale production of biodiesel fuel a possibility. In addition, the SBRO method adopted in this research enables managers and researchers to explore the design conditions of the supply chain network by controlling the uncertainties that affect it. This approach allows the chain's performance to be as close as possible to the actual conditions. As a result, the SBRO method enhances the efficiency of the supply chain network and boosts productivity toward achieving desired goals.

An Evaluation of the Petroleum Investment Environment in African Oil-Producing Countries Based on Combination Weighting and Uncertainty Measure Theory

Recognizing that the evaluation of the overseas petroleum investment environment is affected by many uncertain factors and that there are problems with current evaluation methods, this paper proposes a mathematical evaluation model of an overseas oil resources investment environment, based on a combination of the weighting and uncertainty measure theory. Combining international investment environment theory with the characteristics of the petroleum industry, this paper establishes an evaluation index system for the overseas petroleum investment environment and the linear uncertainty measure function of each index. Using the subjective weight obtained using an analytic hierarchy process together with the objective weight obtained using the entropy weight method, the optimal weight of each evaluation index was obtained using minimum relative information entropy. A multi-index evaluation matrix of the top 12 oil-producing countries in Africa was calculated. Finally, the credible degree recognition criterion was used to judge the order and level of the oil investment environment. This model provides an effective method for the evaluation of the overseas petroleum investment environment. The results show that Nigeria and Angola have the best investment climate, followed by Algeria, Egypt, and Libya. In general, Africa is an important strategic partner of China and is rich in oil resources. Although Africa’s oil industry is fraught with complex challenges and headwinds, challenges also present opportunities.

Spray Behavior, Combustion, and Emission Characteristics of Jet Propellant-5 and Biodiesel Fuels with Multiple Split Injection Strategies

This study focuses on an analysis of the spray behavior, combustion, and emission characteristics of jet propellant-5 (JP-5) and biodiesel fuels with single-injection timing and multiple split injection strategies in a common rail direct injection (CRDI) single-cylinder diesel engine system. The analysis includes visualization of the spray and combustion. Multiple split injection strategies (e.g., double, triple, quadruple, and quintuple) were considered by equally distributing the fuel injection amount within the single-injection. Injection of biodiesel has a delayed start (0.2 ms) as well as shorter spray tip penetration compared with JP-5. As the fuel injection timing was approached to the top dead center (TDC), the engine performance and combustion efficiency improved. Retarding the injection timing contributed to an increase in carbon dioxide (CO2) (JP-5: max. 2.6% up, BD100: max. 1.5% up) and a decrease in carbon monoxide (CO) (JP-5: max. 93% down, BD100: max. 91% down) and nitrogen oxides (NOx) (JP-5: max. 83% down, BD100: max. 82% down). In comparison with JP-5, biodiesel showed disadvantages from the point of its combustion and emission characteristics for all injection timings. The quadruple-injection strategy, in which fuel injection was performed four times, showed excellent combustion, engine performance, and combustion efficiency. The CO2 emissions were highest with the quadruple-injection strategy (JP-5: 6.6%, BD100: 5.8%). The CO emissions of biodiesel decreased as the pulses of split injection extended, and a significant reduction of 83.8% was observed. NOx increased as the number of split injections increased (JP-5: max. 37% up, BD100: max. 52% up). JP-5 was a longer ignition delay than that of biodiesel from combustion flame visualization results. The final combustion in the multiple-injection strategy showed a typical diffusion combustion pattern.