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Publications - 6374

Computer-aided Molecular and Process Design (CAMPD) for Ionic Liquid Assisted Extractive Distillation of Refrigerant Mixtures

M. M.Faruque Hasan Ashfaq Iftakher Rafiqul Gani

Publication Name: Computer Aided Chemical Engineering

Publication Date: 2024-01-01

Volume: 53

Issue: Unknown

Page Range: 1303-1308

Description:

Computer-aided Molecular and Process Design, CAMPD, is a technique that simultaneously optimizes the choice of materials, such as solvents, and the corresponding process configurations for many chemical separation processes. The technique involves formulating an equation-oriented optimization model representing the overall design problem, which then can be solved in many ways depending on the chemicals involved, the property and process models, and the complexity and size of the problem, among others. Due to the complexity and large-size of the problem, and a lack of predictive property models, we have applied a decomposition-based CAMPD strategy that involves solving a series of subproblems sequentially to reduce the overall search space, thereby reducing the computational burden. We illustrate our strategy through a case study involving the design of ionic liquids (ILs) as solvents for the extractive-distillation based separation of an azeotropic refrigerant mixture, R-410A. Separation of such mixtures is gaining increased interest due to the need to remove, substitute or reuse constituent refrigerant chemicals that have undesirable properties (such as high global warming potential, flammability, etc.). ILs are considered because of their designable properties as functions of their molecular structures. Based on available measured data, group-contribution based predictive property models have been developed and interfaced with the workflow of the proposed strategy. A set of promising ILs have been identified and their performance verified through process simulation.

Open Access: Yes

DOI: 10.1016/B978-0-443-28824-1.50218-0

Hierarchical fuzzy decision support methodology for packaging system design

Peter Foldesi Adrienn Buruzs Kata Vöröskoi Gergő Fogarasi Laszlo T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2020-01-01

Volume: 945

Issue: Unknown

Page Range: 85-96

Description:

In the field of logistics packaging (industrial-, or even customer packaging), companies have to take decisions on determining the optimal packaging solutions and expenses. The decisions often involve a choice between one-way (disposable) and reusable (returnable) packaging solutions. Even nowadays, in most cases the decisions are made based on traditions and mainly consider the material and investment costs. Although cost is an important factor, it might not be sufficient for finding the optimal solution. Traditional (two-valued) logic is not suitable for modelling this problem, so here the application of a fuzzy approach, because of the metrical aspects, a fuzzy signature approach is considered. In this paper a fuzzy signature modelling the packaging decision is suggested, based on logistics expert opinions, in order to support the decision making process of choosing the right packaging system. Two real life examples are also given, one in the field of customer packaging and one in industrial packaging.

Open Access: Yes

DOI: 10.1007/978-3-030-18058-4_7

Electrification of oil refineries through multi-objective multi-period graph-theoretical planning: A crude distillation unit case study

Ákos Orosz Bing Shen How Sin Yong Teng Abdulqader Bin Sahl Ferenc Friedler

Publication Name: Journal of Cleaner Production

Publication Date: 2024-01-01

Volume: 434

Issue: Unknown

Page Range: Unknown

Description:

Electrification using renewable energy sources is the key to paving a sustainable and cleaner future for the oil and gas sector, which is known to be a significant carbon dioxide emitter. Nevertheless, the suitability of the electrification designs heavily depends on the seasonal availability of renewable energy sources. This work proposes to use a multi-period graph-theoretical (P-graph) approach to determine the optimal retrofit strategy to achieve electrification with consideration of economic and environmental factors. Both single-period and multi-period models are considered via a graph-theoretical approach to rank and evaluate all the combinatorically feasible electrification pathways based on the overall performance. The effectiveness of the proposed method is developed using a crude distillation unit (CDU) case study adopted from a multinational company. The effectiveness of the proposed method is illustrated using a crude distillation unit (CDU) case study shown in three different scenarios that include prioritizing economic aspect (Scenario 1), prioritizing environmental aspect (Scenario 2), and considering equal importance of both aspects (Scenario 3). For single-period operation, the results showed a mix of natural gas and hydropower energy, exclusive use of onshore wind energy, and a mix of onshore wind energy and biogas cogeneration energy for Scenario 1, Scenario 2, and Scenario 3, respectively. In contrast, the multi-period model also utilized nuclear energy for Scenario 2 and Scenario 3 given the seasonal availability constraint. Following that, a sensitivity analysis is conducted to see the effect of the absence of the most influential energy sources on the optimal solution of each scenario and the top solutions under budget and CO2 emission constraints. Pareto analysis is outlined to offer an understanding of tradeoffs between differently prioritized solutions that decision-makers can select. The combination of the proposed analysis provides a systemic approach towards transforming traditional industries towards a cleaner future via electrification.

Open Access: Yes

DOI: 10.1016/j.jclepro.2023.140179

The effect of initial pattern on competitive exclusion

Éva V.P. Rácz János Karsai

Publication Name: Community Ecology

Publication Date: 2006-08-01

Volume: 7

Issue: 1

Page Range: 23-33

Description:

We used cellular automata models to investigate the effect of initial pattern geometry on competition. We measured the average proportion of sites with foreign neighbours to track interspecific segregation during pattern development. Our simulation results show that intraspecific aggregation can considerably slow down the extinction of the weaker competitor. A series of experiments was performed to estimate the expected time to extinction for the weaker species. The perimeter-to-area ratio of the initial configuration proved to be an adequate determinant of expected time to-extinction. Furthermore, we demonstrated that the degree of aggregation is closely related to the local density dependence of the colonization functions.

Open Access: Yes

DOI: 10.1556/ComEc.7.2006.1.3

Numerical study on the micro-mechanical behaviour of artificial granular materials

Majid Movahedi Rad M. Amine Benmebarek

Publication Name: Proceedings of the 2020 Session of the 13th Fib International Phd Symposium in Civil Engineering

Publication Date: 2020-01-01

Volume: Unknown

Issue: Unknown

Page Range: 86-93

Description:

Numerical models for the simulation of the micro-mechanical behaviour of granular assemblies have a wide range of applications, for instance in material science, process engineering, environmental engineering, railway engineering and geotechnical engineering (in this study we examined one macro-grain but what important is behaviour of granular assemblies). In this examination, experimental tests and numerical computations using the discrete element method (DEM) are carried out to evaluate the micro-mechanical behviour of the granular materials. For this purpose, artificial materials are taken into consideration for experimental Brazilian laboratory tests, and then according to the experimental results the DEM model is calibrated. Artificial crushable materials are produced by mixing cement and silt according to their mass ratio, in which cement can provide bonding and silt is the main filling material. In the DEM model, a 3D crushable granular material 'macro-grain' is built up from a large number of micro-grains which are associated according to crushable parallel bond properties. The behaviour of the single crushable grains and the fragmentation patterns under different contact configuration and load position are studied. The DEM simulation results show that the contact configuration type and load position affect the fragmentation patterns and loading capacity.

Open Access: Yes

DOI: DOI not available

A novel numerical investigation of fiber Bragg gratings with dispersive reflectivity having polynomial law of nonlinearity

Dragan Pamucar Hira Tariq Faisal Javed Mamo Abebe Ashebo Maria Iftikhar Wiaojan Qiao Mansour Shrahilii

Publication Name: Scientific Reports

Publication Date: 2025-12-01

Volume: 15

Issue: 1

Page Range: Unknown

Description:

Fiber Bragg gratings represent a pivotal advancement in the field of photonics and optical fiber technology. The numerical modeling of fiber Bragg gratings is essential for understanding their optical behavior and optimizing their performance for specific applications. In this paper, numerical solutions for the revered optical fiber Bragg gratings that are considered with a cubic-quintic-septic form of nonlinear medium are constructed first time by using an iterative technique named as residual power series technique (RPST) via conformable derivative. The competency of the technique is examined by several numerical examples. By considering the suitable values of parameters, the power series solutions are illustrated by sketching 2D, 3D, and contour profiles. The results obtained by employing the RPST are compared with exact solutions to reveal that the method is easy to implement, straightforward and convenient to handle a wide range of fractional order systems in fiber Bragg gratings. The obtained solutions can provide help to visualize how light propagates or deforms due to dispersion or nonlinearity.

Open Access: Yes

DOI: 10.1038/s41598-025-12437-1

Fuzzy models, identification and applications

János Botzheim Laszlo T. Koczy

Publication Name: Iccc 2005 IEEE 3rd International Conference on Computational Cybernetics Proceedings

Publication Date: 2005-12-01

Volume: 2005

Issue: Unknown

Page Range: 13-19

Description:

This paper gives a brief overview of fuzzy model identification techniques. The paper discusses how the membership functions of a fuzzy system can be extracted from an input/output data (pattern) set without human interference. There are several methods used for rule extraction known from the literature. The bacterial algorithm is an evolutionary technique that was inspired by the microbial evolution phenomenon. The Levenberg-Marquardt algorithm is an advanced gradient type optimization method that has been developed initially for neural networks and is introduced here for the optimization of the fuzzy rule base. Fuzzy clustering is presented also as another alternative way for the rule extraction. In the part describing the model the fuzzy rule interpolation method and the approach of hierarchical rule bases are introduced. Combining fuzzy rule interpolation with the use of hierarchically structured fuzzy rule bases leads to the reduction of the fuzzy algorithms' complexity. Hierarchical fuzzy modeling by clustering techniques is also introduced in the paper.

Open Access: Yes

DOI: 10.1109/ICCCYB.2005.1511538

Pregnancy-induced gait alterations: meta-regression evidence of spatiotemporal adjustments

Yaodong Gu Gusztáv Fekete Minjun Liang Dong Sun András Kovács Yang Song Zhenghui Lu Xin Li Yi Yuan

Publication Name: Frontiers in Bioengineering and Biotechnology

Publication Date: 2024-01-01

Volume: 12

Issue: Unknown

Page Range: Unknown

Description:

During pregnancy, women undergo significant physiological, hormonal, and biomechanical changes that influence their gait. The forward shift of the center of mass and increased joint loads often result in a “waddling gait,” elevating the risk of falls. While gait changes during pregnancy have been documented, findings across studies remain inconsistent, particularly regarding variations at different pregnancy stages. This systematic review and meta-analysis aimed to quantify the impact of pregnancy stages on spatiotemporal gait parameters. A comprehensive literature search across six databases (PubMed, Web of Science, Scopus, EBSCO, Embase, and Cochrane Library) was conducted to identify studies on pregnancy and gait, and data on publication details, methodology, participant characteristics, gait outcomes, and study limitations were extracted. Out of 4,581 initial records, 21 studies met the inclusion criteria. The meta-analysis revealed significant changes in gait parameters during pregnancy, with decreases in stride length (effect size = −0.29) and gait speed (effect size = −0.55), and increases in stride width (effect size = 0.45), cycle time (effect size = 0.38), and double support time (effect size = 0.41). Meta-regression analyses indicated that gestational weeks significantly impacted stride length (β = −0.03 [95% CI, −0.055 to −0.002], p < 0.05) and stride width (β = 0.02 [95% CI, 0.003 to 0.039], p < 0.05), while no significant effects were found for cycle time, double support time, or gait speed. In conclusion, pregnancy leads to significant changes in gait patterns, with a notable increase in stride width and a decrease in stride length as gestation progresses, suggesting these adjustments are strategies for maintaining balance and stability in response to physiological changes. The analysis also emphasizes that while gestational age influences gait adaptations, other factors such as pelvic girdle pain, footwear, and psychological influences play crucial roles. Understanding these complex gait changes can inform interventions and guidelines to support mobility and safety for pregnant women throughout their pregnancy.

Open Access: Yes

DOI: 10.3389/fbioe.2024.1506002

Mathematics self-efficacy, learning approaches, academic performance in the light of the number of failed attempts

Nárcisz Kulcsár

Publication Name: Sefi 48th Annual Conference Engaging Engineering Education Proceedings

Publication Date: 2020-01-01

Volume: Unknown

Issue: Unknown

Page Range: 286-296

Description:

Mathematics is a language for expressing physical, chemical and engineering laws nevertheless engineering students often perform poorly in mathematics. Studying can be influenced by several different social, cognitive and non-cognitive factors which all can have an impact on students' academic performance. Many researches revealed positive effects of mathematics self-efficacy on mathematics achievement. Similar results can be found among learning approaches, students using deep-approach achieve better results. It is legitimate to question whether there is a relationship between self-efficacy and learning approaches. My research focused on the interrelationship between two aspects of mathematics self-efficacy (mastery experience, physiological state), learning approaches (deep strategy, deep motive, surface strategy, surface motive) and achievement. This research also examined the variance of self-efficacy, learning approaches and achievement in relation to the number of failed attempts. 306 undergraduate engineering students at a Hungarian university took part in the study. To examine the above mentioned question the study employed quantitative approach and data were collected using two questionnaires during the semester. The self-efficacy scale was adapted from a variety of sources and was modified to local conditions. To measure learning approaches the Revised Two Factor Study Process Questionnaire was rephrased to the domain of mathematics and to the local conditons. The data were analysed quantitatively using descriptive statistics, bivariate correlation, partial correlation, and regression analysis. The results show that self-efficacy, learning approaches and academic achievement were strongly correlated with each other. Students who have higher level self-efficacy use deep strategy in learning and have deep motives, while students classified as low in self-efficacy adopted surface learning approaches. A new variable was introduced which has not been investigated yet in other researches: the number of failed attempts. A significant correlation between the mentioned variables and the number of attempts was identified. My results demonstrate the importance of such kind of learning environment which fosters self-efficacy and deep learning approach.

Open Access: Yes

DOI: DOI not available