BATTELLE ENERGY ALLIANCE, LLC

• FLUOR MARINE PROPULSION, LLC

  UEI CWHMVCX7K1N6

  $9.7M

  Subcontractor to this prime · 6 sub-awards · latest Mar 24, 2026

  • Department of Energy
  • “CONSEQUENCE-DRIVEN CYBER-INFORMED ENGINEERING VULNERABILITY ASSESSMENT”
  • “INL BLANKET RELEASE 13: MOOSE SUPPORT”
  • “WORK RELEASE 12”
• CONSOLIDATED NUCLEAR SECURITY LLC

  UEI EWV8QKG1JUV7 · not in the directory yet

  $845.8K

  Subcontractor to this prime · 3 sub-awards · latest Jul 16, 2026

  • Department of Energy
  • “HIP SERVICES”
  • “SERVICES”
• UNIVERSITY OF MONTANA

  UEI DAY7Z8ZD48Q3 · not in the directory yet

  $600K

  Subcontractor to this prime · 1 sub-award · latest Apr 14, 2025

  • Department of the Air Force
  • “DIGITAL TWIN APPROACH IS BASED ON MERGING TWO EXISTING MODELING METHODS: FIRST-PRINCIPLES AND DATA-DRIVEN. MERGING TWO MODELING TECHNIQUES ALLOWS A MORE COMPLETE MODEL AS THE TWO APPROACHES COMPLEMENTS EACH OTHER COMBINING THEIR STRENGTHS AND ELIMINATING WEAKNESSES. THE FIRST-PRINCIPLES MODELING RELIES ON EITHER ORDINARY OR PARTIAL DIFFERENTIAL EQUATIONS DERIVED FROM KNOWN PHYSICS OR HUMAN PHYSIOLOGY LAWS AND PRINCIPLES. WHILE BEING A POWERFUL TOOL IN INVESTIGATING SYSTEM’S RESPONSE TO DIFFERENT INPUTS, THE FIRST-PRINCIPLES SYSTEMS DO NOT USE THE MOST CURRENT DATA AND CANNOT REFLECT THE IMMEDIATE CONDITIONS OF HUMAN PHYSIOLOGY. ALSO, THE FIRST-PRINCIPLES MODEL MAY NOT CONSIDER ALL FACTORS AFFECTING HUMAN’S RESPONSE TO STRESS AS SOME OF THEM ARE NOT KNOWN OR TWO COMPLEX TO DERIVE. ON THE OTHER HAND, THE ARTIFICIAL INTELLIGENCE/MACHINE LEARNING (AI/ML) -BASED DATA-DRIVEN MODELS CAN USE THE MOST RECENTLY COLLECTED DATA TO PRODUCE PARAMETERS PREDICTIONS AND CAN BE ADAPTED TO THE MOST IMMEDIATE DATA. HOWEVER, THESE DATA-DRIVEN ALGORITHMS TEND TO OVERFIT THE DATA AND MOST OF THEM LACK EXPLAINABILITY. DATA OVERFITTING LEADS TO MODELS WHICH PERFORM VERY WELL WITHING THE RANGE OF TRAINING DATA, HOWEVER, BREAKS DOWN ONCE THE NEW DATA ARE OUTSIDE OF THE HISTORICAL DATA. THE LACK OF EXPLAINABILITY UNDERMINES TRUST IN THESE MODELS AND LEADS TO RELUCTANCE IN ACCEPTING THEM FOR HUMAN-SAFETY RELATED APPLICATIONS. THE DIGITAL TWIN APPROACH ADDRESSES THE WEAKNESSES OF THESE TWO MODELING APPROACHES AND ALSO OFFERS AN OPPORTUNITY TO PROVIDE AN ANTICIPATORY PHYSIOLOGIC GUIDANCE TO THE MILITARY PERSONNEL BY FIRST APPLYING THE ANTICIPATED GUIDANCE TO THE TWIN MODEL PRIOR ADVISING IT TO THE PERSONNEL. THIS PROJECT WILL DEVELOP DIGITAL TWIN MODELS BASED ON PHYSICS-INFORMED DEEP NEURAL NETWORKS (PIDNNS). THE PHYSICS-INFORMED DEEP NEURAL NETWORKS (PIDNNS) WILL CONSIST OF THE FIRST-PRINCIPLE SCENARIO MODEL DEVELOPED AT USARIEM AND DATA-DRIVEN PART REPRESENTED BY A DEEP NEURAL NETWORK DEVELOPED”
• PANTEXAS DETERRENCE, LLC

  UEI SPG7J8395CJ5

  $68.5K

  Subcontractor to this prime · 1 sub-award · latest May 7, 2026

  • Department of Energy
  • “OTHER PROFESSIONAL SERVICES”

No reported sub-awards as a prime contractor.

No active exclusion on record (checked Nov 14, 2026).

Agencies generally may not award to excluded parties, and primes may not subcontract with them above the threshold in FAR 52.209-6 (except COTS items) without a compelling reason reported to the contracting officer (FAR 9.405, 9.405-2). Some exclusion types apply only to specific programs: read the record on SAM.gov.

No confirmed match on the Consolidated Screening List (screened Nov 13, 2026).

The list combines Commerce, State and Treasury export-control and sanctions lists. A “no match” result is a name-and-address screen, not an export-compliance determination.