Water distribution networks optimization considering unknown flow directions and pipe diameters

Water Distribution Networks (WDN) are present in a large number of industrial processes and urban centers. Reservoirs, pipes, nodes, loops, and pumps compose WDN and their design can be formulated as an optimization problem. The main objective is the minimization of the network cost, which depends on the pipe diameters and flow directions known a priori. However, in the design of new WDN in real industrial problems, flow directions are unknown. In the present paper, a disjunctive Mixed Integer NonLinear Programming (MINLP) model is proposed for the synthesis of WDN considering unknown flow directions. Two case studies are employed to test the model and global optimization techniques are used in its solution. Results show that the global optima WDN cost with the correct flow directions is obtained for the studied cases without the necessity of using additional software to calculate pressure drops and velocities in the pipes.The authors gratefully acknowledge the financial support from the National Council for Scientific and Technological Development —CNPq (Brazil), the Coordination for the Improvement of Higher Education Personnel —Process 88881.171419/2018-01 –CAPES (Brazil) and the Ministério de Economía, Industria y Competitividad CTQ2016-77968-C3-02-P (FEDER, UE)

HYBRID GENETIC ALGORITHM TO THE SYNTHESIS OF OPTIMAL HEAT EXCHANGER NETWORKS

In this paper a new systematic is proposed, interfacing Pinch Analysis and Genetic Algorithms (GA). Initially the optimal ∆Tmin is found by using a genetic algorithm. In a second step, with the optimal ∆Tmin, the pinch point is obtained, and the problem is divided in two regions, below and above it. The optimal HEN is obtained for each side of the pinch and the final HEN is achieved. An example from the literature was solved using the proposed systematic. Results show the applicability of the proposed methodology, obtaining a cost value lower than those presented in the literature

Deep sequencing of Suppression Subtractive Hybridisation drought and recovery libraries of the non-model crop Trifolium repens L.

Open Access Journal; Published online: 23 Feb. 2017White clover is a short-lived perennial whose persistence is greatly affected by abiotic stresses, particularly drought. The aim of this work was to characterize its molecular response to water deficit and recovery following re-hydration to identify targets for the breeding of tolerant varieties. We created a white clover reference transcriptome of 16,193 contigs by deep sequencing (mean base coverage 387x) four Suppression Subtractive Hybridization (SSH) libraries (a forward and a reverse library for each treatment) constructed from young leaf tissue of white clover at the onset of the response to drought and recovery. Reads from individual libraries were then mapped to the reference transcriptome and processed comparing expression level data. The pipeline generated four robust sets of transcripts induced and repressed in the leaves of plants subjected to water deficit stress (6,937 and 3,142, respectively) and following re-hydration (6,695 and 4,897, respectively). Semi-quantitative polymerase chain reaction was used to verify the expression pattern of 16 genes. The differentially expressed transcripts were functionally annotated and mapped to biological processes and pathways. In agreement with similar studies in other crops, the majority of transcripts up-regulated in response to drought belonged to metabolic processes, such as amino acid, carbohydrate, and lipid metabolism, while transcripts involved in photosynthesis, such as components of the photosystem and the biosynthesis of photosynthetic pigments, were up-regulated during recovery. The data also highlighted the role of raffinose family oligosaccharides (RFOs) and the possible delayed response of the flavonoid pathways in the initial response of white clover to water withdrawal. The work presented in this paper is to our knowledge the first large scale molecular analysis of the white clover response to drought stress and re-hydration. The data generated provide a valuable genomic resource for marker discovery and ultimately for the improvement of white clover

Deep sequencing of Suppression Subtractive Hybridisation drought and recovery libraries of the non-model crop Trifolium repens L.

Open Access Journal; Published online: 23 Feb. 2017White clover is a short-lived perennial whose persistence is greatly affected by abiotic stresses, particularly drought. The aim of this work was to characterize its molecular response to water deficit and recovery following re-hydration to identify targets for the breeding of tolerant varieties. We created a white clover reference transcriptome of 16,193 contigs by deep sequencing (mean base coverage 387x) four Suppression Subtractive Hybridization (SSH) libraries (a forward and a reverse library for each treatment) constructed from young leaf tissue of white clover at the onset of the response to drought and recovery. Reads from individual libraries were then mapped to the reference transcriptome and processed comparing expression level data. The pipeline generated four robust sets of transcripts induced and repressed in the leaves of plants subjected to water deficit stress (6,937 and 3,142, respectively) and following re-hydration (6,695 and 4,897, respectively). Semi-quantitative polymerase chain reaction was used to verify the expression pattern of 16 genes. The differentially expressed transcripts were functionally annotated and mapped to biological processes and pathways. In agreement with similar studies in other crops, the majority of transcripts up-regulated in response to drought belonged to metabolic processes, such as amino acid, carbohydrate, and lipid metabolism, while transcripts involved in photosynthesis, such as components of the photosystem and the biosynthesis of photosynthetic pigments, were up-regulated during recovery. The data also highlighted the role of raffinose family oligosaccharides (RFOs) and the possible delayed response of the flavonoid pathways in the initial response of white clover to water withdrawal. The work presented in this paper is to our knowledge the first large scale molecular analysis of the white clover response to drought stress and re-hydration. The data generated provide a valuable genomic resource for marker discovery and ultimately for the improvement of white clover.BBSRC Research GrantsPeer Revie

Framework for Embedding Process Simulator in GAMS via Kriging Surrogate Model Applied to C3MR Natural Gas Liquefaction Optimization

Rigorous black-box simulations are useful to describe complex systems. However, it cannot be directly integrated into mathematical programming models in some algebraic modeling environments because of the lack of symbolic formulation. In the present paper, a framework is proposed to embed the Aspen HYSYS process simulator in GAMS using kriging surrogate models to replace the simulator-dependent, black-box objective, and constraints functions. The approach is applied to the energy-efficient C3MR natural gas liquefaction process simulation optimization using multi-start nonlinear programming and the local solver CONOPT in GAMS. Results were compared with two other meta-heuristic approaches, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), and with the literature. In a small simulation evaluation budget of 20 times the number of decision variables, the proposed optimization approach resulted in 0.2538 kW of compression work per kg of natural gas and surpassed those of the PSO and GA and the previous literature from 2.45 to 15.3 %.The authors acknowledge the National Council for Scientific and Technological Development – CNPq (Brazil), processes 148184/2019-7, 440047/2019-6, 311807/2018-6, 428650/2018-0, and Coordination for the Improvement of Higher Education Personnel – CAPES (Brazil) for the financial support

Optimization of water distribution networks using a deterministic approach

Water distribution networks (WDNs) are the main component of industrial and urban water distribution systems and are currently formed by pipes, nodes and loops. In this article, a deterministic mathematical programming approach is proposed, aiming to minimize the cost of looped WDNs, considering known pipe lengths and a discrete set of commercially available diameters. The optimization model constraints are mass balances in nodes, energy balances in loops and hydraulic equations, in such a way that no additional software is needed to find the appropriate pressure drops and water velocities. Generalized disjunctive programming is used to reformulate the discrete optimization problem to a mixed-integer nonlinear programming (MINLP) problem. The GAMS (General Algebraic Modeling System) environment is used to solve the problem. Four cases are studied to test the applicability of the model and the results show compatibility with the literature.This study was financially supported by the Coordination for the Improvement of Higher Education Personnel (CAPES) (Brazil) [processes 88887.217374/2018-00 and 88881.171419/2018-01] and the National Council for Scientific and Technological Development (CNPq) (Brazil) [processes 428650/2018-0 and 440047/2019-6]; and by the Conselho Nacional de Desenvolvimento Científico e Tecnológico and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

An Advanced Control Strategy for the Evaporation Section of An Integrated First- and Second-Generation Ethanol Sugarcane Biorefinery

The sugarcane crushing stage is one of the most important technologies being developed at the moment. In this paper, the control of the multiple-stage evaporation system was addressed, as it is a crucial stage in the first- and second-generation ethanol production from sugarcane. A neural network model was proposed based on a dynamic phenomenological model developed in EMSO (Environment for Modeling, Simulation and Optimization). The phenomenological model was used to build a neural network prediction model for an MPC (Model Predictive Control) scheme using a DMC (Dynamic Matrix Control) algorithm. Simulations were carried out to evaluate the performance for tracking the set-point. Also, disturbance rejection tests were performed, considering different step disturbances. The analysis demonstrated that the MPC scheme performed well in the tests and showed superiority when compared to classical PID controllers. This work is licensed under a Creative Commons Attribution 4.0 International License

MINLP model for work and heat exchange networks synthesis considering unclassified streams

The optimal synthesis of work and heat exchange networks (WHENs) is deeply important to achieve simultaneously high energy efficiency and low costs in chemical processes via work and heat integration of process streams. This paper presents an efficient MINLP model for optimal WHENs synthesis derived from a superstructure that considers unclassified streams. The derived model is solved using BARON global optimization solver. The superstructure considers multi-staged heat integration with isothermal mixing, temperature adjustment with hot or cold utility, and work exchange network for streams that are not classified a priori. The leading advantage of the present optimization model is the capability of defining the temperature and pressure route, i.e. heating up, cooling down, expanding, or compressing, of a process stream entirely during optimization while still being eligible for global optimization. The present approach is tested to a small-scale WHEN problem and the result surpassed the ones from the literature.The authors LFS, CBBC, and MASSR acknowledge the National Council for Scientific and Technological Development – CNPq (Brazil), processes 148184/2019-7, 440047/2019-6, 311807/2018-6, 428650/2018-0, and Coordination for the Improvement of Higher Education Personnel – CAPES (Brazil) for the financial support. The author JAC acknowledge financial support from the “Generalitat Valenciana” under project PROMETEO 2020/064

A pinch-based method for defining pressure manipulation routes in work and heat exchange networks

Aiming for more energetically efficient and sustainable solutions, academic attention to work and heat integration (WHI) has grown in the last decade. Simultaneous models for work and heat exchanger network (WHEN) synthesis often derive from heat integration (HI) frameworks. However, it can be noted that simultaneous optimization models for WHI are considerably more complex to solve than in the HI case. The design of efficient pressure manipulation routes (i.e., allocation and sizing of compression and expansion machinery) in process streams prior to heat exchange match allocation can make the optimization procedure more efficient. This work proposes a systematic procedure based on a model that employs Pinch Analysis concepts for defining these routes based on capital and operating cost targets. The solution approach is a hybrid meta-heuristic method based on Simulated Annealing (SA) and Particle Swarm Optimization (PSO). The obtained routes are then converted into a HI problem by fixing pressure manipulation unit sizes. The detailed HI solution is finally transferred into a WHI optimization model as initial design. In the two tackled examples, the total annual costs (TAC) predicted by the Pinch-based model differed by 0.5% and 1.2% from the final optimized WHEN obtained in the detailed WHI framework.The authors gratefully acknowledge the financial support from the Coordination for the Improvement of Higher Education Personnel – Processes 88887.360812/2019–00 and 88881.171419/2018–01 – CAPES (Brazil) and the National Council for Scientific and Technological Development – Processes 305055/2017–8, 428650/2018–0 and 311807/2018–6 – CNPq (Brazil)