Kirti M. Yenkie

55326302900

Publications - 5

Towards the synthesis of reliable and resilient complex networks

Ákos Orosz Kirti M. Yenkie Jean Pimentel Andres Castellar-Freile

Publication Name: Current Opinion in Chemical Engineering

Publication Date: 2025-09-01

Volume: 49

Issue: Unknown

Page Range: Unknown

Description:

Process synthesis methodologies have traditionally focused on optimizing the economic criteria. However, owing to the complexity of real systems, external factors, such as expected or unexpected events or disturbances, negatively affect the performance of optimal networks. In this context, it becomes essential to consider the effect of such events on the performance of the network in the early design stages. This work presents a comprehensive review of the contributions related to this relevant topic, focusing on two widely utilized indicators: reliability and resilience. Reliability focuses on the probability of system failures due to disturbances, and resilience analyzes the behavior of the system after disturbances and its capacity to recover over time. Relevant contributions are reviewed, which present deterministic and stochastic methods to estimate these indicators, with a special focus on the design phase. Moreover, this work also presents a perspective on using machine learning methods on complex systems datasets as an emerging direction for enhancing the estimation of these properties. This contribution highlights recent advancements in this field and emphasizes the relevance of resilience and reliability as key metrics for developing safer processes with improved operability.

Open Access: Yes

DOI: 10.1016/j.coche.2025.101172

Systematic Method of Retrofitting Wastewater Transportation Systems for Enhanced Reliability

Ákos Orosz Kirti M. Yenkie Jean Pimentel Andres Castellar-Freile

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 1075-1080

Description:

While the treatment of wastewater is an important issue that received significant attention in the past decades, improving the related technologies is only one part of a more complex task. Domestic wastewater is usually transported via the city's sewer system, and in many places, it is combined with rainwater. This means that disturbances, such as heavy rainfall or failures in the pipeline system, can lead to floods of polluted wastewater. Thus, it is important to design such transportation systems to be reliable. This work presents a methodology for generating several potential extensions to retrofit an existing water transportation network and increase its reliability. Reliability and feasibility evaluation is performed via the P-graph framework, after which the nondominated networks are collected. Results of the presented case study show that reliability can be increased 3 times by adding only some of the possible extensions to the network. The methodology proposed analysed 512 plausible retrofitting alternatives, from which 20 are non-dominated networks. This range of alternatives provides designers with insightful information to decrease water pollution and the vulnerability of wastewater systems.

Open Access: Yes

DOI: 10.3303/CET24114180

Enabling technology models with nonlinearities in the synthesis of wastewater treatment networks based on the P-graph framework

Ákos Orosz Kirti M. Yenkie Jean Pimentel Emmanuel A. Aboagye Mihály Csaba Markót Heriberto Cabezas Ferenc Friedler

Publication Name: Computers and Chemical Engineering

Publication Date: 2022-11-01

Volume: 167

Issue: Unknown

Page Range: Unknown

Description:

Designing effective wastewater treatment networks is challenging because of the large number of treatment options available for performing similar tasks. Each treatment option has variability in cost and contaminant removal efficiency. Moreover, their mathematical models are highly nonlinear, thus rendering them computationally intensive. Such systems yield mixed-integer nonlinear programming models which cannot be solved properly with contemporary optimization tools that may result in local optima or may fail to converge. Herein, the P-graph framework is employed, thus generating all potentially feasible process structures, which results in simpler, smaller mathematical models. All potentially feasible process networks are evaluated by nonlinear programming resulting in guaranteed global optimum; furthermore, the ranked list of the n-best networks is also available. With the proposed tool, better facilities can be designed handling complex waste streams with minimal cost and reasonable environmental impact. The novel method is illustrated with two case studies showing its computational effectiveness.

Open Access: Yes

DOI: 10.1016/j.compchemeng.2022.108034

The P-graph approach for systematic synthesis of wastewater treatment networks

Ákos Orosz Kirti M. Yenkie Jean Pimentel Heriberto Cabezas Ferenc Friedler

Publication Name: Aiche Journal

Publication Date: 2021-07-01

Volume: 67

Issue: 7

Page Range: Unknown

Description:

Wastewater treatment consists of three or four sequential stages: preliminary, primary, secondary, and tertiary. Each stage can comprise multiple alternative technologies that can perform the same tasks with different efficiencies, operating times, and costs. Thus, we propose a systematic approach for designing wastewater treatment networks by utilizing principles of mathematical modeling and generating an exhaustive enumeration of all the possible technologies and their connections during the early stages of designing a treatment facility. Some of these structures are nonintuitive and include recycling, reprocessing, bypasses, and multiple technologies in parallel or series to remove the same contaminant. The nonintuitive structures with multiple technologies may provide a measure of resilience compared to typical heuristic designs. Thus, the combination of P-graph methodology and the sequence of treatment technologies predicted via the optimization algorithm from the maximal structure is based on holistic considerations and does not lead to suboptimal solutions.

Open Access: Yes

DOI: 10.1002/aic.17253

Efficient Design and Sustainability Assessment of Wastewater Treatment Networks using the P-graph Approach: A Tannery Waste Case Study

Ákos Orosz Kirti M. Yenkie Jean Pimentel Emmanuel A. Aboagye Heriberto Cabezas Ferenc Friedler

Publication Name: Chemical Engineering Transactions

Publication Date: 2021-01-01

Volume: 88

Issue: Unknown

Page Range: 493-498

Description:

In the tannery industry approximately, 30 - 35 m3 of wastewater (WW) is generated per ton of rawhide processed. The WW comprises high concentrations of salts, ammonia, dye, solvents, and chromium. Of particular interest is chromium, which has been proven to cause dermatological, developmental, and reproductive issues on exposure. Thus, there is a need for appropriate treatment of the tannery WW before it is discharged for natural remediation. However, designing a treatment process is multifaceted due to the availability of multiple technologies that can perform similar tasks and the complex composition of waste streams. This necessitates the treatment to be performed in stages namely, primary, secondary, and tertiary. In some cases, pretreatment is required to enhance the recovery in the following stages. Due to the combinatorial nature of this problem, the P-graph approach, which uses principles from graph theory, can be used to synthesize a treatment pathway by selecting appropriate technologies at each stage, while meeting required purity specifications. Furthermore, the P-graph approach can provide alternate feasible treatment structures ranked based on Economics as well as Sustainability indicators, such as the Sustainable Process Index (SPI). In this work, a tannery WW case study is investigated with multiple stages and treatment technologies. A complex maximal structure is generated comprising all possible technologies, flows, connections, bypasses, mixers, and splitters. The models for each technology involve capital and operating costs, efficiency, and SPI at each stage of the treatment process. This problem is formulated in P-graph and solved using the Accelerated Branch-and-Bound algorithm.

Open Access: Yes

DOI: 10.3303/CET2188082