The Atmospheric Lifetime (ALT) of a compound represents the potential for the atmospheric accumulation of chemicals. Chemicals with a long lifetime are more resistant to natural decomposition and remain in the environment for a longer period. Minimum Ignition Energy (MIE) is one of the most important properties when evaluating hazardous chemicals. Despite the significance of these environment and safety-related properties, currently, there are no group contribution (GC) models that enable their predictive modeling. The present research aims at filling this gap. To this end, experimental data were collected from literature and the GC model parameters were estimated using the weighted nonlinear least-squares regression. Two approaches were applied; in the step-wise approach the parameters of the first, second and third order GC models were estimated sequentially. By comparison, all these parameters were optimized simultaneously in the second approach. The estimated average relative error and correlation coefficient for ALT model were 45.28% and 0.9999 for the step-wise approach, and 26.16% and 0.9999 for the simultaneous approach, respectively. In the case of MIE, the average relative error and correlation coefficient were 16.70% and 0.9964 for the step-wise approach and 11.48% and 0.9999 for the simultaneous approach, respectively. The proposed models not only provide novel tools for the environmental/safety analysis of the common chemicals when experimental values are unavailable, but they could also be applied to computer-aided product design problems; thus contributing towards the development of improved and more sustainable industrial processes.

Liquefaction and then transportation to the market is one of the promising options for the utilization of associated natural gas resources which are produced in oil fields. However, the flow of such resources is normally unsteady. Additionally, the associated gas in one oil field may exhaust in a few years and the liquefaction plant should be moved to another oil field with different specifications. In order to tackle such challenges, liquefaction systems not only must be optimally designed and operated but also should be flexible with respect to the gas flow fluctuations. The flexibility analysis of such processes is usually ignored in the optimization studies. In this research, first, the economic performance of two small-scale liquefaction processes (a single mixed-refrigerant process, SMR, and a nitrogen expander process) was optimized and compared. The results showed that the SMR process is economically more attractive (49% lower lifecycle cost compared to the nitrogen expander process). As a post-optimization step, flexibility analysis was performed to investigate the ability of optimal designs in overcoming gas flow fluctuations. For this purpose, five-thousand feed samples with different flowrate and methane content were supposed which formed a feasibility-check region. The results showed that with respect to the design constraints, the optimal SMR process is more flexible and feasibly operates in the entire region. However, the nitrogen expander process cannot feasibly operate for the gas feed with high flowrate and low methane content.

The strategies of Inherently Safer Design (ISD) provide a conceptual approach in order to design equipment and processes with substantially improved safety level. However, this may lead to a less economically attractive design. This study aimed to obtain optimal decision parameters of a reactor network system to produce allyl chloride. The objective functions were the risk level, including the severity and the frequency of the accidents, which were associated with the hazards in the network and the economic profit of the process. Based on this optimization approach, an array of optimal solutions (called Pareto front) was obtained as a trade-off between the objectives under investigation. A final design point was ultimately selected using Shannon's entropy and Bellman-Zadeh's techniques of decision making in a fuzzy environment. Results showed that the optimum reactor network leads to a highly complex system and more process control difficulties. This result was inconsistent with the simplification strategy of Inherently Safer design. In order to deal with this problem, a sensitivity analysis was performed that yielded a decision guide to decide about the desirable level of the risk as well as the optimum design.

Inherently safer design is the new approach to maximize the overall safety of a process plant. This approach suggests some risk reduction strategies to be implemented in the early stages of design. In this paper a multi-objective optimization was performed considering economic, exergetic, and environmental aspects besides evaluation of the inherent safety level of a cascade refrigeration system. The capital costs, the processing costs, and the social cost due to CO2 emission were considered to be included in the economic objective function. Exergetic efficiency of the plant was considered as the second objective function. As a measure of inherent safety level, Quantitative Risk Assessment (QRA) was performed to calculate total risk level of the cascade as the third objective function. Two cases (ammonia and propane) were considered to be compared as the refrigerant of the high temperature circuit. The achieved optimum solutions from the multi objective optimization process were given as Pareto frontier. The ultimate optimal solution from available solutions on the Pareto optimal curve was selected using Decision Makings approaches. NSGA-II algorithm was used to obtain Pareto optimal frontiers. Also, three decision-making approaches (TOPSIS, LINMAP, and Shannon's entropy methods) were utilized to select the final optimum point. Considering continuous material release from the major equipment in the plant, flash and jet fire scenarios were considered for the CO2/C3H8 cycle and toxic hazards were considered for the CO2/NH3 cycle. The results showed no significant differences between CO2/NH3 arid CO2/C3H8 with respect to economic and exergy efficiency objectives. But the CO2/NH3 cycle was the inherently safer cascade system in comparison with the CO2/C3H8 one. This is mainly due to the jet fire scenario for the CO2/C3H8 cycle in which the effects are very severe in the farther distance as well as the areas close to the release point. (C) 2016 Elsevier Ltd. All rights reserved.

Membrane reactors are an advanced technology with vast application capacities for equilibrium limited endothermic reactions. The main propose of this study is to offer an optimized packed-bed membrane steam methane reforming (SMR) tubular reactor for sustainable CH4 conversion by implementing triple-objective optimization model based on optimum H2/CO ratio for low temperature Fischer-Tropsch (F-T) process. In this study a one dimensional pseudo-homogeneous model based on mass, energy, and momentum conservation laws is used to simulate the behavior of a packed-bed membrane reactor for production of syngas by SMR. In the optimization section, the proposed work explores optimal values of various decision variables that simultaneously maximize CH4 conversion, H2 selectivity, and CO selectivity by applying elitist non-dominated sorting genetic algorithm (NSGA-II). Pareto optimal frontier between triple objectives is obtained in three spaces and best optimal value is selected by using LINMAP, TOPSIS, Shannon's entropy and Fuzzy Bellman-Zadeh decision making methods. The final optimal solutions illustrate that the membrane reactor presents higher CH4 conversion which can be operated under milder conditions than the conventional reactor.

The economic viability of industrial processes strongly depends on their safe and reliable operation. The method of inherent safe process design enables systematic consideration of safety measures in order to ensure process safe operation at the early stages of process design. The challenge is that the economic measures that are often considered for the design of industrial processes are often incommensurable with the safety measures. In the present research, a novel framework is proposed in which the safety criteria are quantified based on consequence modeling and aggregated with the economic performance using multi-objective optimization programming. The developed methodology was applied to the design of a simple refrigeration cycle. The optimization algorithm was NSGA-II. The results suggested a strong trade-off between the competing economic and safety objectives in terms of Pareto frontiers that clearly quantified the required compromise. It was observed that only with a minor increase in the capital investment, it is possible to significantly improve the safety. While the case of the refrigeration cycle was selected as a demonstrating case, the research methodology is to large extend general and deemed to be acceptable to design and operation of other industrial processes. (C) 2016 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

•An optimization procedure is suggested integrating processing and accident costs.•Different design schemes can be evaluated taking costs into account.•Consequence modeling and an objective function are used in an optimization package.•A case study is provided and discussed.