The U.S. Space Force (USSF) is seeking proposals for the development of a Virtual Space Cargo Deployment Function (VS-CDF), an advanced digital twin platform designed to enhance logistics planning and simulation for space operations. The objective is to create an AI-enabled environment that supports real-time planning, optimization, and visualization of cargo deployment, addressing the complexities of space logistics and improving mission readiness. This initiative is critical for ensuring agile and efficient logistics operations in contested environments, aligning with the USSF's Mission Sustainment Strategy. Interested parties should note that the solicitation is set to open on July 23, 2025, with proposals due by August 20, 2025, and further details can be found at the provided source link.

## Description

The USSF requires advanced tools to plan, simulate, and execute logistics missions in the space domain. Current logistics modeling and planning systems are primarily designed for terrestrial operations and do not adequately account for the complexities of orbital mechanics, rapid launch events, intermodal cargo transfers, or the dynamic nature of space mobility. This limits planning agility, increases mission risk, and hinders the development of responsive and adaptive sustainment operations in line with Space Doctrine Publication 4-0 and the USSF Mission Sustainment Strategy.This topic seeks to develop a VS-CDF&mdash;a digital twin environment that enables real-time planning, simulation, optimization, and visualization of cargo deployment for space logistics. The VS-CDF should support both pre-mission and live mission phases, providing operational planners with AI-driven decision-support tools, immersive modeling capabilities, and integrated risk analytics. Key capabilities of the envisioned system may include:- AI-based cargo optimization, considering constraints such as vehicle configuration, mass, power, volume, payload dynamics, and orbital conditions;- Virtual mission planning and execution tools, enabling full-spectrum scenario modeling for rapid resupply, disaster response, and contingency operations;- Digital twin visualization and intuitive user interfaces, including 3D modeling, augmented/virtual reality integration, and multi-modal human-machine interfaces (e.g., gesture, voice, touchscreen);- Supply chain risk management and contingency simulation, to assess disruptions, prioritize routing, and inform cargo sequencing under degraded conditions;- System interoperability and integration with DoD logistics networks and space operations systems, including the Spaceport of the Future Common Operating Picture (COP) and Joint logistics nodes such as U.S. Transportation Command (USTRANSCOM), Major Command (MAJCOM), and Field Command (FLDCOM).The VS-CDF platform will enable more effective logistics decision-making for contested and distributed space operations, improving mission readiness, reducing deployment timelines, and enabling a shift toward predictive and energy-efficient sustainment practices.

## Objective

The objective for this effort is to develop an Artificial Intelligence (AI)-enabled digital twin platform to support space cargo deployment planning, simulation, and decision support for U.S. Space Force (USSF) logistics operations. The system&mdash;referred to as the Virtual Space Cargo Deployment Function (VS-CDF)&mdash;should enable mission planners to model, visualize, and optimize cargo movements across the full deployment lifecycle. Key capabilities include pre-mission scenario modeling, intelligent configuration of cargo based on vehicle, mission, and environmental constraints, and dynamic simulation of real-time logistics events and contingencies. The solution should support integration with existing U.S. Department of Defense (DoD) logistics, mobility, and space operations systems to improve agility, reduce mission risk, and enhance sustainment readiness in multi-domain operations.

## Phase I

This topic is intended for technology proven ready to move directly into Phase II. Therefore, Phase I awards will not be made for this topic. The applicant is required to provide detail and documentation in the Direct to Phase II (D2P2) proposal which demonstrates accomplishment of a &ldquo;Phase I-type&rdquo; effort, including a feasibility study. This includes determining, insofar as possible, the scientific and technical merit and feasibility of ideas appearing to have commercial potential. It must have validated the product-mission fit between the proposed solution and a potential U.S. Air Force (USAF) and/or USSF stakeholder. The applicant should have defined a clear, immediately actionable plan with the proposed solution and the U.S. Department of the Air Force (DAF) customer and end-user. The feasibility study should have:<ol><li> Clearly identified the potential stakeholders of the adapted solution for solving USAF and/or USSF need(s).</li><li> Described the pathway to integrating with DAF operations, to include how the applicant plans to accomplish core technology development, navigate applicable regulatory processes, and integrate with other relevant systems and/or processes.</li><li> Describe if and how the solution can be used by other DoD or Governmental customers.</li></ol>

## Phase II

Under this D2P2 effort, the awardee will develop and demonstrate a functional VS-CDF&mdash;a digital twin software environment designed to support end-to-end planning, simulation, and decision support for space cargo logistics. The system will serve as a planning and analytics platform for mission stakeholders across the USSF and joint logistics enterprise, enabling predictive modeling, AI-based optimization, immersive visualization, and integration with real-time operational data. The Phase II objectives include: - Develop an operational prototype of the VS-CDF digital twin environment, capable of simulating and optimizing cargo deployment across multiple mission types and logistics scenarios;- Implement AI-enabled tools for cargo configuration, route planning, mission timeline optimization, and contingency response;- Enable collaborative mission planning, supporting multi-user interaction across Joint, Coalition, and interagency logistics teams;- Validate system functionality using live or historically representative DoD logistics data, assessing system accuracy, adaptability, and decision impact under realistic operational conditions.Expected deliverables include:- A fully functional prototype of the VS-CDF system, integrated with representative DoD logistics networks and space operations systems (e.g., USTRANSCOM, MAJCOM, FLDCOM);- Embedded AI models for cargo optimization, risk analysis, and scenario adaptation;- Immersive visualization and user interface components, including 3D modeling, augmented reality/virtual reality (AR/VR) elements, or intuitive controls (as appropriate to the approach);- A demonstration campaign conducted through logistics exercises, simulations, or wargames to assess mission utility;- A final report documenting test results, user feedback, system performance metrics, and integration outcomes;- A transition and commercialization roadmap outlining next steps for operational deployment and dual-use adoption.The completed prototype will provide the USSF with a decision-support environment tailored to the unique challenges of space mobility and sustainment logistics. By enabling simulation-driven planning, risk-informed decision-making, and AI-powered optimization, the VS-CDF will enhance agility, readiness, and operational energy efficiency across both DoD and commercial logistics operations.

## Phase III: Dual Use Applications

The expected Phase III effort will focus on transitioning the VS-CDF from a prototype to an operationally deployed capability supporting both military and commercial logistics ecosystems. The platform will serve as a decision support and simulation tool for complex, multi-domain cargo deployment planning&mdash;bridging the gap between terrestrial logistics systems and emerging space mobility operations. Military applications include:- Provide a mission-ready logistics decision support environment for Space Systems Command (SSC), USTRANSCOM, MAJCOM, FLDCOM, and Joint logistics planners;- Support operational planning and rapid deployment activities, including contingency logistics and distributed sustainment in contested domains;- Integrate into training environments and exercise campaigns to enhance warfighter readiness and simulate space logistics missions under real-world constraints;- Align with the USSF&rsquo;s emphasis on sustainment agility, operational energy efficiency, and predictive supply chain planning.Commercial applications include:- Serve as a logistics optimization and simulation tool for aerospace, satellite launch, and space mobility companies managing commercial cargo operations;- Enable advanced supply chain modeling and risk assessment for global logistics providers, intermodal transport planners, and commercial shipping networks;- Support digital twin integration for defense contractors, airlines, and manufacturers seeking AI-based cargo planning and routing solutions;- Extend to STEM education and academic research, offering a virtualized space logistics environment for training, experimentation, and collaboration.For the transition plan, the DoD adoption will be pursued through coordination with SSC, USTRANSCOM, MAJCOM, and FLDCOM for integration into operational planning tools and logistics networks. Commercial transition pathways will include partnerships with aerospace firms, logistics technology providers, and digital twin software vendors. The system will also be designed for interoperability with existing AI-based logistics tools, supporting scalable deployment across both DoD and private-sector operations.The expected Technology Readiness Level (TRL) at Phase III Entry is TRL 8 or 9, following successful operational demonstration and validation.

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