A systematic approach to the optimal design of chemical plants with waste reduction and market uncertainty

Sepiacci, Piernico; Depetri, Valentina; Manca, Davide

doi:10.1016/j.compchemeng.2016.11.032

Cited by 12 publications

(9 citation statements)

References 44 publications

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“…At the same value of temperature, 60 • C, and 0.1074 kmol/h, the cumulated DEP4 is equal to 1.06 × 10 8 USD. The order of magnitude of this DEP4 is even higher than the one obtained by Sepiacci et al [16], who obtained a six-order DEP4 while applying this methodology in a petrochemical process. Figure 12 shows the behavior of the PEI.…”

Section: Economic Optimalcontrasting

confidence: 54%

“…DEP4 cumulated Figure 10 shows, on the y-axis, the value of the cumulated DEP4 (USD), and on the x-axis it shows the time series of market quotations. Each bar represents the value of the DEP4 calculated by Particularly for the case of the Electric Energy (Figure 9d), we present a brief predictive model where A = 2.98, B = 1.316, and C = 0.81 (Sepiacci et al [16]), in Equation (8). The predictive nature of this model is given by its dependency with the forecasted prices of NG.…”

Section: Optimal Economic and Environmental Friendly Designmentioning

confidence: 99%

“…Conceptual process design (CD) consists of the selection of proper operation units, their sequences, and the recycling structure needed to obtain a specified product [15]. However, Sepiacci et al [16] explain that this conventional method is no longer representative when considering market uncertainty, demand and offer fluctuations, and the price instability of commodities and utilities. Then, Manca and Grana [17] introduced the benefits of dynamic conceptual design (DCD).…”

Section: Introductionmentioning

confidence: 99%

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Optimal Design of a Carbon Dioxide Separation Process with Market Uncertainty and Waste Reduction

2019

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The aim of this work is to optimize the conceptual design of an amine-based carbon dioxide (CO2) separation process for Enhanced Oil Recovery (EOR). A systematic approach is applied to predict the economic profitability of the system while reducing the environmental impacts. Firstly, we model the process with UniSim and determine the governing degrees of freedom (DoF) through a sensitivity analysis. Then, we proceed with the formulation of the economic problem, where the employment of econometric models allows us to predict the highest dynamic economic potential (DEP). In the second part, we apply the Waste Reduction (WAR) algorithm to quantify the environmental risks of the studied process. This method is based on the minimization of the potential environmental indicator (PEI) by using the generalization of the Waste Reduction algorithm. Results show that the CO2 separation plant is promising in terms of economic revenues. However, the PEI value indicates that the higher the profitability, the larger the environmental risk. The optimal value of the DEP corresponds to 0.0274 kmol/h and 60 °C, with a plant capacity according to the mole flow rate of the produced acid gas. In addition, the highest environmental risk is observed at the upper bounds of the DoF.

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Section: Economic Optimalcontrasting

confidence: 54%

Section: Optimal Economic and Environmental Friendly Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Design of a Carbon Dioxide Separation Process with Market Uncertainty and Waste Reduction

2019

Self Cite

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“…Este balance establece que el impacto ambiental potencial puede ingresar al sistema, salir del sistema, generarse dentro del sistema y acumularse dentro del sistema. Esta expresión genera una serie de índices [27], que son el de generación de posibles impactos ambientales y el índice de salida de posibles impactos ambientales, a su vez cada uno de los índices anteriores, pueden ser expresados de dos formas diferentes: para el de salida, se presentan la tasa total de producción de impacto y la producción de impacto total por masa de productos, estos índices permiten comparar procesos alternativos en términos de su efecto potencial sobre el medio ambiente externo al proceso [28]; de manera similar para el de generación, están la tasa total de generación de impacto y el impacto total generado por masa de producto, estos nos permiten comparar diferentes procesos en términos de su generación de nuevos impactos ambientales potenciales dentro del proceso [29]. Los diseños con más valores bajos de índice PEI representan una mejor eficiencia ambiental.…”

Section: Evaluación Ambiental Mediante El Algoritmo De Reducción De Residuos (War)unclassified

Evaluación ambiental de la producción de microperlas de quitosano modificadas con TiO2 y magnetita usando el algoritmo de reducción de residuos (WAR)

Vásquez¹,

González-Delgado²

2021

revion

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En la actualidad, los bioadsorbentes modificados con nanopartículas han tomado relevancia como posible opción en el tratamiento de aguas contaminadas debido a su bajo costo, abundancia natural y alta eficiencia. Se han diseñado procesos a escala industrial para producir microperlas modificadas de quitosano; sin embargo, estos deben ser analizados bajo criterios de sostenibilidad antes de una posible implementación. En este trabajo se evaluó el desempeño ambiental de un proceso a escala industrial usando el algoritmo WAR, que sirva como sustento para posibles proyectos económicos. Se simuló el proceso usando el software Aspen Plus ® para obtener información del proceso como flujos másicos y energéticos. La evaluación se realizó utilizando el software WARGUI. Se cuantificó el Impacto potencial ambiental (PEI) de cuatro casos de estudio mediante cuatro enfoques de impactos. Este análisis arrojó valores negativos en los PEI totales generados y se encontraron valores de tasa hasta 5740 PEI/h para la tasa de PEI de salida. En las categorías toxicológicas no hubo valores apreciables (entre -212 y -1,21 PEI/h) para ningún caso debido a la baja presencia de sustancias tóxicas en el proceso. En las categorías atmosféricas, los PEI se deben mayormente al uso de combustibles. El gas natural tuvo el mejor desempeño ambiental reportando bajos valores para las tasas de PEI de generación y salida (-308, 4970 PEI/h, respectivamente). Debido a lo anterior, es posible afirmar que el proceso tiene un desempeño ambiental aceptable.

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“…They proposed the so-called "Waste reduction (WAR) algorithm". The remarkable thing is that implementation of concept "sustainable development as a criterion for the functioning of CES" is still a work in progresssee, for example, (Petrescu & Cormos (2015), Sepiacci at al. (2017), etc.…”

Section: Introductionmentioning

confidence: 99%

Design of Sustainable Industrial Water Networks: 1. Genesis of the Systematic Methods

Shakhnovsky

Квітка

2019

WPT STN

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The first part of the work is devoted to the review of the history of development and analysis of modern methods of project decision support in the sustainable design of industrial water networks: water usage networks, water treatment networks. Modern methods of computer-aided design of chemical-engineering systems were classified. The industrial water economy system as an integral part of the chemical-engineering system and as an object of design was considered. The modern conceptual and superstructure methods of designing water networks were described.

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A systematic approach to the optimal design of chemical plants with waste reduction and market uncertainty

Cited by 12 publications

References 44 publications

Optimal Design of a Carbon Dioxide Separation Process with Market Uncertainty and Waste Reduction

Optimal Design of a Carbon Dioxide Separation Process with Market Uncertainty and Waste Reduction

Evaluación ambiental de la producción de microperlas de quitosano modificadas con TiO2 y magnetita usando el algoritmo de reducción de residuos (WAR)

Design of Sustainable Industrial Water Networks: 1. Genesis of the Systematic Methods

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