(562al) Systematic Synthesis of Wastewater Treatment Networks Using the P-Graph Approach | AIChE

(562al) Systematic Synthesis of Wastewater Treatment Networks Using the P-Graph Approach

Authors 

Yenkie, K. - Presenter, Rowan University
Pimentel, J. - Presenter, Grupo de Procesos Quimicos y Bioquimicos, Universidad Nacional de Colombia, Bogota, Colombia
Orosz, A., University of Pannonia
Friedler, F., Pazmany Peter Catholic University

Systematic
synthesis of wastewater treatment networks using the P-graph approach

Kirti Yenkie1, Jean Pimentel2
3
, Akos Orosz4, Ferenc Friedler2

1Department of Chemical Engineering, Henry M. Rowan College
of Engineering, Rowan University, NJ - 08028, USA

2Institute for Process Systems Engineering and
Sustainability, Pazmany Peter Catholic University, Budapest, Hungary

3Grupo de Procesos Quimicos y Bioquimicos, Department of
Chemical and Environmental Engineering, Universidad Nacional de Colombia,
Bogota, Colombia

4Department
of Computer Science and Systems Technology, University of Pannonia, Veszprém,
Hungary

Wastewater
treatment is an area of utmost importance to address the challenge of
decreasing freshwater resources. Traditionally, wastewater treatment consists
of three or four sequential stages: preliminary, primary, secondary and
tertiary [1]. Preliminary treatment is intended to
facilitate the removal of contaminants in the following stages. Primary
treatment mainly involves the withdrawal of settleable solids. The secondary treatment
is capable of removing pollutants such as chemicals and metals. In some cases,
a tertiary treatment might be used for further purification if the required
purity limits are not achieved during the first three stages. To create this
systematic approach for designing wastewater treatment networks, we rely on the
principles of mathematical modeling to generate an exhaustive enumeration of
all the possible technologies and their connections during the early stages of
design. This enables the generation of a maximal structure which consists of
all the treatment structures. Some of these structures would be non-intuitive
and could include reprocessing, and multiple technologies in parallel or series
to remove the same contaminant, which would not have been obtained via typical
design heuristics. Thus, the sequence of treatment technologies predicted using
this maximal structure would be based on holistic consideration and would not
lead to suboptimal solutions.

A
representative case study of a wastewater stream containing settleable solids
and chemicals is considered as the motivating example where the minimum purity
requirements for water reuse have been specified. Primary and secondary stages
were studied considering three types of technologies for the former, and four types
of technologies for the latter. In primary treatment, the technologies are
based on the particle size: sedimentation, filtration, and microfiltration;
whereas, in secondary treatment, the technologies are based on the ability to
remove chemicals, such as adsorption, disinfection, advanced oxidation process
and rotating biologic contactors. The contaminant removal efficiencies and cost
associated with the operation of these technologies were provided through
information collected from design literature [2], [3] and simulation software [4]. The primary and secondary treatment stages
were studied by means of the P-graph approach, which has been extensively
deployed to evaluate problems of combinatorial nature, such as supply chains,
evacuation routes design, and process network synthesis (PNS) [5]–[7]. This advantage is that not only the
best structure in terms of cost is obtained, but also a ranked list of all
feasible near-optimal solutions is created. This additional information can be
relevant when considering additional performance criteria, such as
controllability, operability, flexibility, sustainability, etc.

For
the primary stage, an initial structure was obtained by joining the input and
output materials with the technologies. The water rich streams leaving the
primary stage can be considered as potential input for the next stage. The
secondary structure is constructed for each of the water-rich leaving streams
from the primary stage by joining the plausible materials and technologies of the
secondary treatment stage. The resultant overall network consisting of the
initial and secondary structure is used as the input for the P-graph algorithm,
which determines the most cost-effective treatment process for a certain set of
parameters. Subsequently, a parametric study is carried out by changing the
feed water composition, with the objective of generating cost-effective process
structures which are also capable of satisfying the treatment requirements
under different inlet water conditions. Therefore, this work aims at providing
guidelines for the design of efficient wastewater treatment networks depending
on the inlet water composition and treated water requirements.

Key
words:
Wastewater
treatment, Process Network Synthesis, exhaustive enumeration, P-graph

References:

[1]  M. & E. Inc, G.
Tchobanoglous, F. L. Burton, and H. D. Stensel, Wastewater Engineering:
Treatment and Reuse
, 4th edition. Boston: McGraw Hill Higher Education,
2002.

[2]  G.
Towler and R. K. Sinnott, Chemical Engineering Design, Second Edition:
Principles, Practice and Economics of Plant and Process Design
, 2 edition.
Boston, MA: Butterworth-Heinemann, 2012.

[3]  G.
D. Ulrich and P. T. Vasudevan, Chemical Engineering Process Design and
Economics: A Practical Guide
. Process Pub., 2004.

[4]  D.
P. Petrides, Intelligen, Inc.: SuperPro Designer, Batch Process Simulation,
Environmental Impact Assessment
. Intelligen Inc, 2013.

[5]  I.
Heckl, F. Friedler, and L. T. Fan, “Solution of separation-network synthesis
problems by the P-graph methodology,” Computers & Chemical Engineering,
vol. 34, no. 5, pp. 700–706, May 2010.

[6]  H.
Cabezas, A. Argoti, F. Friedler, P. Mizsey, and J. Pimentel, “Design and
engineering of sustainable process systems and supply chains by the P-graph
framework,” Environ. Prog. Sustainable Energy, vol. 37, no. 2, pp.
624–636, Mar. 2018.

[7]  L.
Vance, H. Cabezas, I. Heckl, B. Bertok, and F. Friedler, “Synthesis of
Sustainable Energy Supply Chain by the P-graph Framework,” Ind. Eng. Chem.
Res.
, vol. 52, no. 1, pp. 266–274, Jan. 2013.