The National Science Foundation funds a Texas A&M project to build AI digital twins of small and mid-sized water systems
The National Science Foundation made a standard grant to the Texas A&M Engineering Experiment Station in College Station. The work is AI enabled digital twins of freshwater infrastructure under cascading hazards. The award record carries an award date of September 9th, 2026 and a start date of September 15th, 2026. It expires on August 31st, 2029. Sudipta Chowdhury is the principal investigator. The abstract describes water infrastructure that is getting harder to run. It names aging assets and deferred maintenance. It names climate driven hazards and power outages and water quality variability. A disruption that starts in one component can propagate through the connected networks. The abstract says current utility practice leans on monitoring systems and historical records and reactive emergency protocols. Those give limited ability to anticipate how a local anomaly escalates. The award sits in the foundation's Division of Civil, Mechanical, and Manufacturing Innovation.
How to take part
A federal research award carries no comment window. The award record is public and searchable by its own number, and it names the awardee institution and the principal investigator. The Texas A&M Engineering Experiment Station is a state agency and a member of the Texas A&M University System, whose governing board meets in public.
Where
1 county. In College Station-Bryan.
Timeline
- decided
Award date on the federal award record
- effective
Start date on the federal award record
- Today
- expires
Expiration date on the federal award record
1069 days out
How this decision moved
One dated line per check, oldest first. A line that says nothing changed means somebody looked and it had not.
- 2026-09-20
Admitted to the record. The federal award record carries the dates, the awardee, the principal investigator and the abstract that states the objective.
- 2026-09-23
The digital twin project still aims at the small and mid-sized systems that have the least to spend on one.
- 2026-09-26
The A&M digital twin project is still aimed at the small and mid-sized water systems.
The evidence
Every fact above rests on one of these. The words are the source's own.
Collaborative Research: AI-Enabled Digital Twins for Resilient Freshwater Infrastructure and Communities under Cascading HazardsNSF award record 2640086, title Primary source, official · api.nsf.gov
The objective of this project is to support research on a new AI-enabled cyber-physical-social paradigm for predicting, managing, and mitigating cascading disruptions in freshwater infrastructure systems.NSF award record 2640086, abstract Primary source, official · api.nsf.gov
Current utility practices often rely on monitoring systems, historical records, and reactive emergency protocols that provide limited ability to anticipate how local anomalies escalate into broader service disruptions.NSF award record 2640086, abstract Primary source, official · api.nsf.gov
Questions about this decision
Answered from the record itself. Every answer is assembled from stored fields, so an answer the record has no basis for is left out rather than guessed.
What is this decision?
The National Science Foundation made a standard grant to the Texas A&M Engineering Experiment Station in College Station. The work is AI enabled digital twins of freshwater infrastructure under cascading hazards. The award record carries an award date of September 9th, 2026 and a start date of September 15th, 2026. It expires on August 31st, 2029. Sudipta Chowdhury is the principal investigator. The abstract describes water infrastructure that is getting harder to run. It names aging assets and deferred maintenance. It names climate driven hazards and power outages and water quality variability. A disruption that starts in one component can propagate through the connected networks. The abstract says current utility practice leans on monitoring systems and historical records and reactive emergency protocols. Those give limited ability to anticipate how a local anomaly escalates. The award sits in the foundation's Division of Civil, Mechanical, and Manufacturing Innovation.
Who decides it?
U.S. National Science Foundation decides. The record names the deciding body for every entry it carries.
Can the public take part?
A federal research award carries no comment window. The award record is public and searchable by its own number, and it names the awardee institution and the principal investigator. The Texas A&M Engineering Experiment Station is a state agency and a member of the Texas A&M University System, whose governing board meets in public. No dated public window is on the record. The deciding body is named and reachable.
Where in Texas does it apply?
It covers Brazos County in the College Station-Bryan, TX area.
Has it been decided?
It has been decided. The dates on the item page carry when.
What happens next?
The next dated step is expires, on August 31st, in 1069 days.
When did it start?
The earliest date on its record is September 9th, 2026.
What kind of decision is it?
It is filed under land, water and permitting.
What sources back it?
One source backs it. It is primary.
Is it on the ERCOT grid?
Yes. It sits inside the ERCOT interconnection.
When was it last checked?
Every fact on it was last verified against its source on September 26th, 2026.
Cite this
Texas AI Docket, The National Science Foundation funds a Texas A&M project to build AI digital twins of small and mid-sized water systems. Tracked since September 9th, 2026. Last verified September 26th, 2026. https://texasaidocket.com/item/tx-2026-0176/. Reuse permitted under CC BY 4.0 with attribution. The same entry is in the docket JSON as item tx-2026-0176.
Beat
Filed under Land, water and permitting, with every other decision on that beat.