Thermodynamic and transport properties of ethylene and propylene

Vashchenko, D M; Voinov, Yu F; Voityuk, B; Dregulyas, E K; Kolomiets, A Ya; Labinov, Solomon D.; Морозов, А.; Neduzhii, I A; Provotar, V P; Soldatenko, Yu A; Storozhenko, E J; Khamara, Yu I

doi:10.6028/nbs.ir.75-763

Cited by 8 publications

(3 citation statements)

References 2 publications

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“…As one can see in Figure 10, the heat capacities of saturated liquid, Cp liq , and saturated vapor, Cp vap , increase asymptotically near the critical point. This behavior has been shown experimentally for propylene [26] and also other products [27,28]. The densities can also change significantly near the critical point, as shown in Figure 11.…”

Section: Model Adaptationsupporting

confidence: 74%

Process Hazard Analysis Based on Modeling and Simulation Tools

2022

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Chemical and oil processes are intrinsically sources of potential hazards. Although traditional qualitative hazard identification methods are simple, systematic, and flexible, such methodologies present limitations related to the inherent subjectivity, dependence on the team’s level of experience, and widespread time consumption of the members involved. In this context, the present work aims to develop a systematic way to use computational modeling and simulation tools for hazard identification. After extensive literature review, the present work proposes a methodology based on the association of the main points of previous works, with new contributions regarding the preparation for the simulations and the characterization of the minimum set of process variables that can enable appropriate interpretation of the results. The propene polymerization process (LIPP-SHAC process) was used as a case study to illustrate the proposed procedure. The paper explores how the model can be adapted for safety analyses and simulations for different hazard scenarios. The results obtained with different models are discussed and compared to those obtained with a traditional hazard identification approach to discuss how computational process modeling and simulation tools can sum to heuristic analysis. In conclusion, the use of simulations complementing the human-based approach can indeed enhance the understanding of mechanisms of hazardous scenarios, lessen conservative decision-making, and avoid overlooking device failures that can pose a severe hazard to the process.

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Section: Model Adaptationsupporting

confidence: 74%

Process Hazard Analysis Based on Modeling and Simulation Tools

2022

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“…At T % 150 K their results agree with ours within ±0.1%, but with increasing temperature they deviate by up to À0.2% which exceeds the claimed uncertainty of 0.05%. The data of Vashchenko et al [60] at T % 240 K show scatter and deviations within the given uncertainty of about ±0.15%, and the values of Manley and Swift [61] deviate systematically by about À0.1%. In the liquid region at T = 340 K, the data of Parrish and Sitton [62] show systematic deviations of up to about À0.1% which is within the given uncertainty of ±0.2%.…”

Section: Propylenementioning

confidence: 96%

“…The comparison of the new (p, q, T) values of propylene with selected measurements of other experimentalists [58][59][60][61][62][63][64] is presented in figure 3 for the homogeneous regions. The diagrams show the deviations between measured values and values calculated from a preliminary equation of state developed in our group by Overhoff and Wagner [27].…”

Section: Propylenementioning

confidence: 99%