A Non-Probabilistic Solution for Uncertainty and Sensitivity Analysis on Techno-Economic Assessments of Biodiesel Production with Interval Uncertainties

Tang, Zhangchun; Xia, Yanjun; Xue, Qi Wen; Liu, Jie

doi:10.3390/en11030588

Cited by 14 publications

(6 citation statements)

References 70 publications

(95 reference statements)

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“…Machine operation and physical parameters cause some uncertainty in the experimental results [44] so that uncertainty analysis is needed [45]. Uncertainty error analysis is a type of characteristic analysis which is analogous to the deviation of the experimental output response that can be solved effectively [46].…”

Section: Methodsmentioning

confidence: 99%

Engine Performance Using Blended Fuels of Biodiesel and Eco Diesel

Idris¹,

Husin²,

Hermawan³

et al. 2023

Energy Engineering

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Diesel engines is an internal combustion engine with high thermal efficiency, which also uses biodiesel fuel, an environmentally friendly, non-toxic, and low sulfur content. Biodiesel has been around for a long time due to its similar characteristics to diesel fuels which has limited availability. However, several disadvantages are associated with biodiesel, such as poor volatility and high viscosity, which reduces engine performance. Therefore, this study was carried out to improve the diesel engine performance by mixing biodiesel with ecodiesel (ED), an additive produced from natural ingredients that is dissolvable in biodiesel. The biodiesel fuel properties used are density 860 kg/m 3 , dynamic viscosity 4.50E-06 m 2 /s, cetane number 45, and flashpoint 52°C. The results showed that biodiesel-ED mixture could improve engine performance and the optimum performance was at a speed of 3000 rpm on 43.30 (kW), 124.93 (N.m) of the engine torque, and 2.45E -5 (kg/kW.s) of the specific fuel consumption. According to paired sample t-test, the difference in the engine performance is only experienced in the torque, which has a significant increase in the composition of the biodiesel+ED by 0.07 gr mixture.

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Section: Methodsmentioning

confidence: 99%

Engine Performance Using Blended Fuels of Biodiesel and Eco Diesel

Idris¹,

Husin²,

Hermawan³

et al. 2023

Energy Engineering

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show abstract

“…In order to obtain a better understanding of the importance of the different factors of the model in its response, the procedure known as Sensitivity Analysis (SA) can be very useful in order to develop, evaluate, and improve complex models [49][50][51][52]. There are two main approaches in SA: local and global [53].…”

Section: Methodsmentioning

confidence: 99%

Sensitivity of a Dynamic Model of Air Traffic Emissions to Technological and Environmental Factors

Buendia-Hernandez

Bevia

Alvarez-Garcia

et al. 2022

IJERPH

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In this study, we introduce a sensitivity analysis of modelled CO2 aviation emissions to changes in the model parameters, which is intended as a contribution to the understanding of the atmospheric composition stabilization issue. The two variable dynamic model incorporates the effects of the technological innovations on the emissions rate, the environmental feedback, and a non-linear control term on the passengers rate. The model parameters, estimated from different air traffic sources, are subject to considerable uncertainty. The stability analysis of Monte Carlo simulations revealed that, for certain values of the non-linear term parameter and depending on the type of flight, the passengers number at some equilibrium points exceeded its initial value, while the emissions level was below the initial corresponding one. The results of two global sensitivity analyses indicated that the influence of the non-linear term prevailed on the passengers number rate, followed distantly by the environmental feedback. For the emissions rate, the non-linear term contribution dominated, with the technological term influence placing second.

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“…Sources of Uncertainty 30 [112] Economic key factors 31 [113] Economic key factors 32 [114] Number of people inside the room 33 [115] Estimate feedstock requirements, costs, life-cycle energy usage, greenhouse gas emissions for grower payments and field operations, and major parameters associated with the transportation of corn stover feedstock 34 [116] Technical and economic parameters 35 [117] Technical parameters and environmental uncertainties 36 [118] Price of biodiesel and feedstock, the efficiency of biodiesel conversion, and operating costs 37 [119] Post-combustion CO 2 capture techno-economic parameters 38 [69] Technical, economic, and environmental parameters (electricity and heat loads, wind and PV generation, EE unit factors for EE evaluation)…”

Section: Referencementioning

confidence: 99%

Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review

Barahmand

Eikeland

2022

Sustainability

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Researchers have long been interested in developing new economic assessment methods to provide credible information and facilitate the sustainable development of new technologies and products. The techno-economic analysis (TEA) and the life cycle cost analysis (LCCA) are the most widely used approaches for modeling and calculating processes’ economic impacts. A simulation-based TEA is a cost-benefit analysis that simultaneously considers technical and economic factors. In addition, the method facilitates the development of the entire project and provides a systematic approach for examining the interrelationships between economic and technological aspects. When it comes to economic studies, it is intimately bonded with uncertainty. There are numerous uncertainty sources, classified in various ways. The uncertainty reflects “an inability to determine the precise value of one or more parameters affecting a system.” The variability refers to the different values a given parameter may take. This implies that a probability density function (PDF), for instance, can be employed to estimate and quantify the variability of a given parameter. The bias refers to “assumptions that skew an analysis in a certain direction while ignoring other legitimate alternatives, factors, or data.” The present study identifies the frequency with which TEA/LCCA studies address uncertainty and gaps within the selected papers through a scoping review. The results indicate that the uncertainty associated with economic factors and model uncertainties were the main sources of uncertainty in TEA and LCCA. Moreover, possibilistic approaches such as the Monte Carlo methodology were the most frequently used tool to cope with the uncertainties associated with LCCA and TEA.

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A Non-Probabilistic Solution for Uncertainty and Sensitivity Analysis on Techno-Economic Assessments of Biodiesel Production with Interval Uncertainties

Cited by 14 publications

References 70 publications

Engine Performance Using Blended Fuels of Biodiesel and Eco Diesel

Engine Performance Using Blended Fuels of Biodiesel and Eco Diesel

Sensitivity of a Dynamic Model of Air Traffic Emissions to Technological and Environmental Factors

Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review

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