Environmental performance analysis of railway infrastructure using life cycle assessment: Selecting pavement projects based on global warming potential impacts

Ribeiro, Filipe Batista; Nascimento, Filipe Almeida Corrêa do; Silva, Marcelino Aurélio Vieira da

doi:10.1016/j.jclepro.2022.132558

Cited by 17 publications

(9 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…𝑎𝑐 𝐻 1 = −0.019486552(0.019𝑇 + 5.85 − 0.61) + 0.027388788(0.002𝑇 + 1.73 − 0.49) + 0.032389172(0.009𝑇 + 2.76 − 0.61) − 0.009833314(0.087𝑇 + 0.59 − 2.57) − 0.052408375(−0.0003𝑇 + 2.7 − 0.08) + 0.005938666(0.18𝑇 + 4.56 − 12.1) + 0.018097023(0.094𝑇 + 4.26 − 6.49) + 0.221498705 (9) where 𝑇 is the time, in days, corresponding to the geometric maintenance frequency to be analysed.…”

Section: Definition Of the Model For Predicting Accelerations As A Fu...mentioning

confidence: 99%

“…For example, abrasion will cause progressive fracture of the ballast material; cracks and breaks will appear in the sleeper structure, damaging the support and fastening of rails; and fatigue and wear of the rails' structures will be developed due to high mechanical stress [2][3][4][5][6][7]. Such degradations that are developed in the physical structure of components, in conjunction with other factors, such as settlement of the track bed, deterioration of the ballast layer, and the influence of the climate, cause a progressive loss of the ideal spatial arrangement of the track components along the railway section, thus characterizing the geometric degradation [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Contribution to Railway Track Maintenance Planning from the Analysis of Dynamic Movements of Trains

Seraco

Neto

2023

Civ Eng J

View full text Add to dashboard Cite

Dynamic movements of trains in relation to the track have a significant impact on the displacement stability of rail vehicles, having effects inclusive of operational safety. Although there are numerous approaches to track maintenance planning, most of them are based solely on long-term geometric degradation assessments without taking into account any dynamic parameters in assessing operational safety or establishing means to predict future rolling stock accelerations relative to the track in order to develop safer maintenance plans. This paper introduces a method of track maintenance planning based on geometric degradation modeling and prediction of rolling stock vertical and horizontal acceleration. The goal is to establish how frequent geometric maintenance is necessary to ensure operational safety under geometric and dynamic criteria. This approach is based on regression models defined from geometric and dynamic inspection data. The method was applied in a passenger railway and obtained expressive results that corroborated the need of considering dynamic aspects on maintenance planning, as sections of the analyzed railway were identified with operation becoming unsafe, under the dynamic criterion, before the geometric safety tolerances are reached. This work is intended not only to propose a planning method but also to present to the scientific and technical communities a novel approach to be explored and developed in future research. The obtained results, therefore, do more than confirm quantitatively the relevance of this analysis; they also demonstrate qualitatively how promising the development of this thematic field is. In this regard, this work also presents in its conclusions some research opportunities to be explored for the development of this theme. Doi: 10.28991/CEJ-2023-09-02-02 Full Text: PDF

show abstract

Section: Definition Of the Model For Predicting Accelerations As A Fu...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Contribution to Railway Track Maintenance Planning from the Analysis of Dynamic Movements of Trains

Seraco

Neto

2023

Civ Eng J

View full text Add to dashboard Cite

show abstract

“…The remaining 79% of trash accumulated in landfills or the natural environment is thrown out and deposited on refuse landfills or aquatic ecosystems 7 . The singularly inappropriate approach to plastic solid waste directly contributes to a surge in CO 2 emissions, 8,9 which in turn contributes to global warming and brings a grievous threat to the environment and health of living things on earth 10–12 . Worldwide, the development of degradable materials, 13–15 has become the “hot spot” to deal with the ecological and environmental problems caused by nondegradable plastics 16,17 …”

Section: Introductionmentioning

confidence: 99%

“…7 The singularly inappropriate approach to plastic solid waste directly contributes to a surge in CO 2 emissions, 8,9 which in turn contributes to global warming and brings a grievous threat to the environment and health of living things on earth. [10][11][12] Worldwide, the development of degradable materials, [13][14][15] has become the "hot spot" to deal with the ecological and environmental problems caused by nondegradable plastics. 16,17 Poly (glycolic acid) (PGA), 18,19 a synthetic polymer material with high-level biodegradability, makes it an ideal and versatile material for developing biodegradable and bio-mass derived plastics to replace nondegradable plastics.…”

mentioning

confidence: 99%

A hybrid deep learning framework driven by data and reaction mechanism for predicting sustainable glycolic acid production performance

Zhou

Feng

et al. 2023

AIChE Journal

View full text Add to dashboard Cite

Selective oxidation at low temperatures without alkali of biomass is a promising and sustainable avenue to manufacture glycolic acid (GA), a biodegradable functional material to protect the environment. However, producing glycolic acid with high selectivity and yield using the traditional research and development approach is timeconsuming and labor-intensive. To this context, a hybrid deep learning framework driven by data and reaction mechanisms for predicting GA production was proposed, considering the lack of related reaction mechanisms in the machine learning algorithms. The proposed hybrid deep learning framework involves the kinetic reaction mechanism, catalyst properties, and reaction conditions. Results showed that the fully connected residual network exhibited superior performance (average R 2 = 0.98) for the prediction of conversion rate and product yields. Then, the multi-objective optimization and experimental verification guided the research are carried out. The experimental verification is comparable to the modeling results, with errors of less than 4% for conversion rate and GA yields. The life cycle assessment further identifies that using the optimized operating parameters, the fossil energy demand and greenhouse emissions have decreased by 2.96% and 3.00%, respectively. This work provides new insight and strategy to accelerate the engineered selective oxidation for desired GA production.

show abstract

“…By improving sustainable [19][20][21] rail-based mobility, the share of travel with high environmental performance [22][23][24], such as rail transport, collective road transport [25,26], or shared systems, can make a significant contribution to reducing the many negative impacts [27][28][29][30], such as pollutant emissions [31] and climate impacts [32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Using Detailing Concept to Assess Railway Functional Safety

Bondarenko¹,

Campisi

Tesoriere

et al. 2022

Sustainability

View full text Add to dashboard Cite

The ability to assess the risks of the functional safety of railway tracks allows harmonizing characteristics of track elements under certain operating conditions under certain maintenance for the efficient use of the track structure throughout its life cycle. The concept of detailing conditions of the interaction of the rolling stock and railway track was used for the productive solution of tasks of infrastructure functional safety assessment. The paper formed an approach to the analytical solution of determination problems of deformability parameters over time using the elastic waves theory. The formation method of interconnections between the technical and economic aspects of the operation of railway infrastructure was proposed. The criteria of deformability work and intensity of use were utilized for the effective use of the track structure through its life cycle. The results of calculations are presented to assess changes in the deformability behaviour of the track elements and structure when the force and speed parameters of the operating conditions change, as well as the algorithm of the method for estimating the operation deformability of the railway track. Thus, the proposed approach can be adapted to optimize objects by railway functional safety assessment at the stage of object operation simulation.

show abstract

Environmental performance analysis of railway infrastructure using life cycle assessment: Selecting pavement projects based on global warming potential impacts

Cited by 17 publications

References 40 publications

Contribution to Railway Track Maintenance Planning from the Analysis of Dynamic Movements of Trains

Contribution to Railway Track Maintenance Planning from the Analysis of Dynamic Movements of Trains

A hybrid deep learning framework driven by data and reaction mechanism for predicting sustainable glycolic acid production performance

Using Detailing Concept to Assess Railway Functional Safety

Contact Info

Product

Resources

About