Concurrent multiresponse multifactorial screening of an electrodialysis process of polluted wastewater using robust non-linear Taguchi profiling

Besseris, George J.

doi:10.1016/j.chemolab.2020.103997

Cited by 6 publications

(9 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Taguchi-type L 9 (3 4 ) OA [24] will be examined because it meets the described requirements. Moreover, it has been previously implemented and investigated in a wastewater electrodialysis study [22,45]. The filtrated drainage wastewater was mainly intended for irrigation purposes in farming.…”

Section: Main Featuresmentioning

confidence: 99%

“…The synchronous screening of the three water-quality indices against the four controlling ED-factors may need to be transformed to an expression meaningful according to the regular Taguchi modelling [24,45]. The first comment is that the examined (original) dataset [22] is in an unreplicated form in both available datasets.…”

Section: Data Manipulation Issues and New Approach Benefitsmentioning

confidence: 99%

“…On the other hand, the removed sodium content should be maximized. Since all three water quality characteristics are either percentages or ratios, SNR expressions are not relevant anyway, but the omega transformation might be considered instead [45]. The omega transformation becomes meaningful even for a lone observation per recipe run.…”

Section: Data Manipulation Issues and New Approach Benefitsmentioning

confidence: 99%

“…Water quality indices are primarily expressed in ratio or percentage-based scales. They are more complex data types and, hence, they may require more specialized multiparametric treatments [45].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Micro-Clustering and Rank-Learning Profiling of a Small Water-Quality Multi-Index Dataset to Improve a Recycling Process

Besseris

2021

Water

View full text Add to dashboard Cite

The efficiency improvement of wastewater recycling has been prioritized by ‘Goal 6’ of the United Nations Sustainable Development initiative. A methodology is developed to synchronously profile multiple water-quality indices of a wastewater electrodialysis (ED) process. The non-linear multifactorial screener is exclusively synthesized by assembling proper R-based statistical freeware routines. In sync with current trends, the new methodology promotes convenient, open and rapid implementation. The new proposal unites the ‘small-and-fast’ data-sampling features of the fractional multifactorial designs to the downsizing, by microclustering, of the multiple water quality indices—using optimized silhouette-based classification. The non-linear multifactorial profiling process is catalyzed by the ‘ordinalization’ of the regular nominal nature of the resulting optimum clusters. A bump chart screening virtually eliminates weak performances. A follow-up application of the ordinal regression succeeds in assigning statistical significance to the resultant factorial potency. The rank-learning aptitude of the new profiler is tested and confirmed on recently published wastewater ED-datasets. The small ED-datasets attest to the usefulness to convert limited data in real world applications, wherever there is a necessity to improve the quality status of water for agricultural irrigation in arid areas. The predictions have been compared with other techniques and found to be agreeable.

show abstract

Section: Main Featuresmentioning

confidence: 99%

Section: Data Manipulation Issues and New Approach Benefitsmentioning

confidence: 99%

Section: Data Manipulation Issues and New Approach Benefitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Micro-Clustering and Rank-Learning Profiling of a Small Water-Quality Multi-Index Dataset to Improve a Recycling Process

Besseris

2021

Water

View full text Add to dashboard Cite

show abstract

“…In addition, ED methods have been proposed for desalinating drainage wastewaters for agricultural reuse [408], and the experimental screening/optimisation has been studied [409].…”

Section: Municipal Wastewater and Other Effluentsmentioning

confidence: 99%

Electrodialysis Applications in Wastewater Treatment for Environmental Protection and Resources Recovery: A Systematic Review on Progress and Perspectives

et al. 2020

View full text Add to dashboard Cite

This paper presents a comprehensive review of studies on electrodialysis (ED) applications in wastewater treatment, outlining the current status and the future prospect. ED is a membrane process of separation under the action of an electric field, where ions are selectively transported across ion-exchange membranes. ED of both conventional or unconventional fashion has been tested to treat several waste or spent aqueous solutions, including effluents from various industrial processes, municipal wastewater or salt water treatment plants, and animal farms. Properties such as selectivity, high separation efficiency, and chemical-free treatment make ED methods adequate for desalination and other treatments with significant environmental benefits. ED technologies can be used in operations of concentration, dilution, desalination, regeneration, and valorisation to reclaim wastewater and recover water and/or other products, e.g., heavy metal ions, salts, acids/bases, nutrients, and organics, or electrical energy. Intense research activity has been directed towards developing enhanced or novel systems, showing that zero or minimal liquid discharge approaches can be techno-economically affordable and competitive. Despite few real plants having been installed, recent developments are opening new routes for the large-scale use of ED techniques in a plethora of treatment processes for wastewater.

show abstract

Datacentric Similarity Matching of Emergent Stigmergic Clustering to Fractional Factorial Vectoring: A Case for Leaner-and-Greener Wastewater Recycling

Besseris

2023

Applied Sciences

View full text Add to dashboard Cite

Water scarcity is a challenging global risk. Urban wastewater treatment technologies, which utilize processes based on single-stage ultrafiltration (UF) or nanofiltration (NF), have the potential to offer lean-and-green cost-effective solutions. Robustifying the effectiveness of water treatment is a complex multidimensional characteristic problem. In this study, a non-linear Taguchi-type orthogonal-array (OA) sampler is enriched with an emergent stigmergic clustering procedure to conduct the screening/optimization of multiple UF/NF aquametric performance metrics. The stochastic solver employs the Databionic swarm intelligence routine to classify the resulting multi-response dataset. Next, a cluster separation measure, the Davies–Bouldin index, is used to evaluate input and output relationships. The self-organized bionic-classifier data-partition appropriateness is matched for signatures between the emergent stigmergic clustering memberships and the OA factorial vector sequences. To illustrate the proposed methodology, recently-published multi-response multifactorial L9(34) OA-planned experiments from two interesting UF-/NF-membrane processes are examined. In the study, seven UF-membrane process characteristics and six NF-membrane process characteristics are tested (1) in relationship to four controlling factors and (2) to synchronously evaluate individual factorial curvatures. The results are compared with other ordinary clustering methods and their performances are discussed. The unsupervised robust bionic prediction reveals that the permeate flux influences both the UF-/NF-membrane process performances. For the UF process and a three-cluster model, the Davies–Bouldin index was minimized at values of 1.89 and 1.27 for the centroid and medoid centrotypes, respectively. For the NF process and a two-cluster model, the Davies–Bouldin index was minimized for both centrotypes at values close to 0.4, which was fairly close to the self-validation value. The advantage of this proposed data-centric engineering scheme relies on its emergent and self-organized clustering capability, which retraces its appropriateness to the fractional factorial rigid structure and, hence, it may become useful for screening and optimizing small-data wastewater operating conditions.

show abstract

Concurrent multiresponse multifactorial screening of an electrodialysis process of polluted wastewater using robust non-linear Taguchi profiling

Cited by 6 publications

References 65 publications

Micro-Clustering and Rank-Learning Profiling of a Small Water-Quality Multi-Index Dataset to Improve a Recycling Process

Micro-Clustering and Rank-Learning Profiling of a Small Water-Quality Multi-Index Dataset to Improve a Recycling Process

Electrodialysis Applications in Wastewater Treatment for Environmental Protection and Resources Recovery: A Systematic Review on Progress and Perspectives

Datacentric Similarity Matching of Emergent Stigmergic Clustering to Fractional Factorial Vectoring: A Case for Leaner-and-Greener Wastewater Recycling

Contact Info

Product

Resources

About