&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

Department of Chemical Engineering

World University root node

US Patent App. 17/059,242

System and method facilitating decision making for disinfectant dosing in water in water distribution networks

Journal of Water Resources Planning and Management

Closure to "influence of Dead-End Sections of Drinking Water Distribution Networks on Optimization of Booster Chlorination Systems" by Ahmed A. Abokifa, Abhilasha Maheshwari, Ravindra D. Gudi, and Pratim Biswas

Tanker-based distribution systems have been prevalent in developing countries to supply clean and pure water in different regions. To efficiently operate such tanker service systems, a large fleet of tanker trucks are required to transport water among several water sources, water treatment plants and consumers spanning across the regions. This requires tighter coordination between water suppliers, treatment plant operations, and user groups to use available water resources in a sustainable manner, along with the assurance of water quality and timely delivery. This paper proposes a novel formulation to assist decision-making for optimizing tanker-based water distribution systems and treatment operations, with an overall objective of minimizing the total operating cost such that all of the constraints related to the water demand, supply operations, and environmental and social aspects are honored while supplying water to a maximum number of users. The problem is formulated and solved as a mixed integer linear programming (MILP) optimization framework and captures all of the nuances related to (i) water availability limitations and quality constraints from different sources, (ii) maintaining water quality as it transports via tankers, (iii) water demands for various end-use purposes, and (iv) transportation across a water supply chain. The proposed novel framework is applied to a realistic urban model to find the optimal tanker delivery schedule, ensuring appropriate treatment and timely delivery of water. The results of the case study conducted on a representative-scale problem also elucidate several aspects of treatment plant operation and consumer demand fulfillment for the efficient planning and management of tanker-based water distribution systems. © 2020 American Chemical Society.

Industrial and Engineering Chemistry Research

A Short-Term Planning Framework for the Operation of Tanker-Based Water Distribution Systems in Urban Areas

Release of lead (Pb) in drinking water from lead service lines has been extensively studied in single pipes, and the importance of water chemistry has been reported. However, the impact of variations in water chemistry parameters during water supply from the treatment plant to the downstream distribution network is crucial to understand toward minimizing lead release rates and has not yet been researched. This study proposes a comprehensive framework for investigating the changes in dissolved lead concentrations resulting from variations in the concentration of water chemistry parameters (such as pH, orthophosphate, free chlorine disinfectant residual, dissolved inorganic carbon and natural organic matter). The framework accounts for changes in the chemistry as water flows in a typical, full-scale water distribution network from the treatment plant to the homes through iron distribution mains and lead service lines under dynamic hydraulic conditions. The approach comprises the development of a multispecies reactive transport model for simulating important water chemistry reactions in distribution mains using EPANET-MSX. This water chemistry model is coupled in the framework with a mass transfer-based model for lead release from service lines. The resulting trends of water chemistry parameters variations with water age are qualitatively verified with general trends from experimental and field studies. The influence of complex water chemistry on the spatial and temporal profile of lead levels are analyzed by generating holistic simulations for a full-scale water distribution network case study. Three relevant treatment scenarios of pH adjustment, disinfectant dosage, and orthophosphate addition are presented to reflect the importance of the causal relationship between water chemistry variations in distribution mains and dissolved lead release from service lines. A strong correlation is observed between % change in dissolved lead levels and variations in pH, free chlorine residual, and orthophosphate residual in distribution mains. Further, practical implications for the use of the proposed framework to identify lead release hotspots, suggest potential sampling locations, and optimize remedial treatment measures to control lead dissolution for safe water supply are discussed. © 2020 American Society of Civil Engineers.

Journal of Environmental Engineering (United States)

Framework for Evaluating the Impact of Water Chemistry Changes in Full-Scale Drinking Water Distribution Networks on Lead Concentrations at the Tap

Drinking water utilities are increasingly facing the challenges of maintaining water quality, and simultaneously complying with conflicting regulatory standards. One such challenge is the dosage of chlorine-based disinfectants which is typically regulated to prevent microbial growth in the water distribution systems, while limiting disinfection by-products (DBPs). On the other hand, chlorine residuals also influence the dissolution of lead into drinking water from corrosion scales in the pipe internals, as has been shown by previous studies. Hence, it is important to consider water lead levels (WLLs) while determining the appropriate chlorine dosage. This study proposes a multi-objective optimization framework to understand and balance the trade-offs between (i) minimizing total disinfectant dosage to reduce DBPs formation potential, and (ii) maximizing the volume of safe drinking water supply with respect to both WLLs and residual free chlorine concentrations. The approach comprises of the development of a dynamic simulation-optimization framework to account for the impact of spatial and temporal variations of network hydraulics and water chemistry on WLLs and residual free chlorine. The framework couples dynamic multi-species water quality simulations (pH, residual free chlorine, dissolved inorganic carbon, and orthophosphate concentration) with a multi-objective genetic optimization algorithm in an integrated MATLAB-EPANET-MSX platform. The application of the optimization formulation is demonstrated on a real-world distribution network case study. The resulting optimal solution set on pareto-plots are discussed for sensitivity of the trade-offs between the two objective functions, under various water chemistry conditions that have been suggested in earlier studies for minimizing lead release from plattnerite (PbO2) corrosion scales in lead service lines. The resulting optimal disinfectant dosage schedule, for pumping and booster station nodes in each case, provided insights on maintaining disinfectant residuals throughout the distribution system so as to prevent microbial growth as well as lead contamination events while limiting DBPs formation. Further, environmental implications related to the use of the proposed framework are also discussed. © 2020 Elsevier Ltd

Journal of Environmental Management

Optimization of disinfectant dosage for simultaneous control of lead and disinfection-byproducts in water distribution networks

Indian Institute of Technology Bombay

Decision Support Frameworks for Water Quality Management in Distribution Systems: Modelling and Optimization Approaches

This study investigates the optimization of free chlorine-based disinfectant dosage for controlling the dissolution of lead (Pb) while limiting disinfection by-products (DBPs) formation in water distribution networks. A dynamic optimization framework is developed in this study to account for the impact of spatial and temporal variations of network hydraulics and water chemistry on dissolved lead concentrations. Accordingly, a dynamic schedule of disinfectant dosage is proposed to minimize water lead levels and two-point chlorine residual violations in the network. The results suggest that optimization of water chemistry parameters such as pH and orthophosphate dosage provide an additional degree of freedom to be explored in the problem of optimizing disinfectant dosage for compliance with conflicting mandates regulating lead levels and DBPs concentration in drinking water. © 2020, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

IFAC-PapersOnLine

Control of lead contamination in water distribution networks: A dynamic optimization framework

The impact of implementing an advanced water quality model for simulating the dead-end sections of drinking water distribution networks on the outcomes of booster chlorination optimization is investigated. An advection-dispersion-reaction transport model that accounts for the realistic spatial distribution of water demands along dead-end pipes is linked to a genetic algorithm to find the optimal layout and operation of booster chlorination stations. The objective function is formulated and solved to find the optimal locations and chlorine dosing schedules of the booster stations that minimize the total costs of design and operation of the booster system, while maintaining a sufficient residual throughout the distribution network. The results highlight the importance of considering dispersive solute transport, as well as the excessive residence times encountered in the dead-end branches in the water quality simulations conducted for network optimization problems. While this study addresses the optimization of booster chlorination systems, its implications extend to a wide array of network optimization applications, including pump scheduling for water quality optimization, optimal sensor placement for reactive contaminant detection, and design of real-time boost-response systems. © 2019 American Society of Civil Engineers.

Influence of Dead-End Sections of Drinking Water Distribution Networks on Optimization of Booster Chlorination Systems

Refineries are increasingly compelled to play an imperative role in achieving sustainable management of water as mandated by sustainable development goals (SDGs). Existing optimization models lack the ability to addresses this challenge of obtaining optimal refinery water network configuration for problems of industrial scale due to difficulty in application of complex solution algorithms of mixed integer non-linear problem (MINLP) formulations to large dimensions. Therefore, the optimization formulation in this work exploits process engineering derived constraints to build an integrated superstructure, which results in a simplified non-linear problem (NLP), and thus reduces computational complexity. Further, to substantially minimize fresh water consumption, the proposed model incorporates novel features of a modern refinery complex viz. distributed effluent treatment plant based on total dissolved solids (TDS) levels in waste water, segregation of sour water treatment based on phenolics content in condensate stream, and minimizing cooling tower blowdown rates by optimizing the cycles of concentration in cooling tower operation. The formulation is demonstrated for optimal water routing and economic benefits of the proposed approach through a representative case study of a real refinery complex. Towards the goal of zero liquid discharge, an efficient new scheme of recycling treated water to the boiler feed water system and cooling tower make up water requirements in optimal ratios, has been suggested from the results of the proposed model. Sensitivity of water reallocation in optimal refinery water network with respect to crude quality and desalter performance is also presented through application of proposed optimization framework in the case studies. © 2019 Elsevier Ltd

Journal of Cleaner Production

Systems engineering based advanced optimization for sustainable water management in refineries

Disinfectants are typically used in water distribution networks (WDNs) to maintain the microbiological quality of potable water throughout the network. Disinfectant residual levels in such large distribution networks need to be maintained within the prescribed bounds to address two major problems: (1) preventing microbial regrowth, and (2) minimizing harmful disinfection by-product (DBP) formation resulting from high levels of the disinfectant itself. These requirements pose a two-point constrained control problem of disinfectant residual levels. Another important aspect of consideration is that such WDNs exhibit spatial and temporal variations in water quality at different points in the network. Therefore, conventional systems engineering tools such as modeling, optimization, and control need to be adapted to accommodate these variations for water quality management in distribution networks. In this paper, we propose a novel zone control based approach to address the two-point quality control problem. Further, to combat the spatial complexity, we combine the zone control approach with a decentralized optimization strategy, namely, the model coordination method, which has been widely proposed to solve large-scale optimization problems. The resulting novel formulation is proposed here to address the aforementioned problems in operational optimization of booster chlorination water distribution systems by using a realistic multispecies model developed from a previous study. We demonstrate the efficacy of this approach on a real-scale distribution network of Cherry Hill Brushy Plains (CH/BP) (EPANET Example network 2). © 2018 American Society of Civil Engineers.

Coordinated decentralization-based optimization of disinfectant dosing in large-scale water distribution networks

Abstracts of AIChe Annual Meet

Optimization Based Improved Water Recycle Strategies for Modern Oil Refineries

Providing potable drinking water, with sufficient free residual chlorine to prevent microbial regrowth and contaminant by-product formation, is of utmost importance for municipal authorities. This work aims towards water quality control as it transports through water distribution networks. Presence of excessive chlorine (used as disinfectant worldwide) in water causes the generation of carcinogenic disinfectant by-products such as Tri-halo methane (THMs). On the other hand, lower chlorine levels in water results in microbial contamination. Hence, this leads to a two-point constraint control problem of maintaining free residual chlorine levels under the upper and lower bounds, by suitably optimizing the disinfectant dosage at booster stations. However, transport delay and complex interrelations present amongst the nodes in large water distribution network, makes it difficult to design a global feedback control system. Therefore, in this work we have proposed to decentralize the system by clustering demand nodes of the network based on concentration sensitivity matrix analysis. Further, input-output pairs for decentralized controllers were mapped with the knowledge of interactions between manipulating and control variables using partial correlation analysis. We also considered the results of partial correlation analysis to generate communication links which will be implemented for higher level co-ordinated decentralized control to account for dynamic, non-negligible interactions as disturbances to local control units. The proposed three step clustering-mapping strategy and mathematical formulation for two point control by optimized dosage is successfully verified for the steady state case on a prototype distribution example network. © 2020 CCWI 2017 - 15th International Conference on Computing and Control for the Water Industry. All rights reserved.