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Quantifying Energy Use across U.S. Water Sectors: A Scalable AI/ML-Driven Framework for Data Integration and Resilience Planning

This white paper explores opportunities to quantify and characterize energy use across major U.S. water sectors, including irrigation, water supply, and water treatment, with a focus on energy for water dimension. A scalable AI/ML-driven framework will be developed to harmonize fr...

Ghimire, G., Bhanja, S., and Martinez, R.

Energy Needs for Water Supply Expansion in Urban Areas

Rising urban water demand requires new water supply provisioning in cities. Understanding and quantifying the energy-intensity of new water supply options can help planners identify pathways for water supply expansion with manageable energy requirements. There is opportunity for ...

Deines, J., Catalano, A., Sinnott, V., Yoon, J., Sun, N., and Duan, Z.

Hybrid Additive Manufacturing and Overmolding of Polymer/Metal Lattices for Efficient Cooling Systems for Waterpower Applications

This proposal addresses the Water for Energy challenge by developing advanced hybrid thermal management structures that can reduce water consumption by 15-25% in cooling processes for power generation, energy storage, and power electronics. Further reductions are possible through ...

Talabi, S., Nawaz, K., and Hassen, A.

Employing AI-Enabled Prognostics for Energy-Water Resilience

This white paper focuses on strengthening the resilience and efficiency of hydropower systems at the energy-water nexus through AI-enabled prognostics and hardware-in-the-loop (HIL) simulation. It emphasizes integrating digital intelligence with physical infrastructure to optimize...

Zhao, S., Qiu, F., and Agalgaonkar, Y.

Material Science Driven Water Technology Innovation

The white paper explores multiple Energy-Water Resilience (EWR) topics, including water for energy, energy for water, and their intersections. It proposes low-cost, scalable water-based material processes to advance water technologies through materials innovation. The existing cha...

Chang, C., and Ajami, N.

Natural Materials as a Pathway to Affordable and Scalable Membrane Separation Technologies

This white paper focuses on developing affordable and scalable membrane separation technologies derived from natural materials for selective extraction of critical minerals (CMs), such as lithium, manganese, and barium, from geothermal brines. This approach integrates with geother...

Ho, T., and Sharan, P.

Operational Flexibility for Integrated Energy-Water Resilience

This white paper focuses on advancing operational flexibility as a pathway to integrated energy-water resilience. It addresses the persistent fragmentation between water and energy systems, where separate regulatory, operational, and investment frameworks limit co-optimization and...

Jackson, N., and Rao, N.

Water System Modernization using Advanced and Resilient Technologies (WaterSMART)

This white paper presents a comprehensive vision for modernizing U.S. water and water-energy infrastructure through advanced, resilient, and energy-integrated technologies. It highlights the pressing challenges posed by aging treatment plants, distribution systems, and stormwater ...

DeNeale, S., Chavez, L., and Chu, A.

Field-Validated, Grid-Interactive Irrigation for Energy-Water Resilience in Puerto Rico's Agricultural Experimental Stations

Puerto Rico's irrigation infrastructure depends primarily on electrically powered pumping and distribution systems, making agricultural water delivery highly vulnerable to grid instability and frequent outages. This white paper proposes the development and validation of grid-inter...

Plaza, J., and Andrade, F.

GORMan: A framework for Governance, Ontologies, and Risk Management of scalable, cross-sector integration of secure energy-water infrastructure information

This white paper addresses the inherent challenges in applying data-driven approaches to integrated energy-water solutions across the US due to the lack of standardization in collection, storage, governance, management, curation and risk mitigation among data owners across scales...

Fishler, H., May, A., Knight, K., and Rebillout, L.

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