TOPIC CALL 5.pdf

CB BAA HDTRA122S0002 CALL 5

THE PROPOSAL SUBMISSION DEADLINE FOR THE

FOLLOWING TOPIC IS JUNE 25, 2024 AT 2:00PM EASTERN

DAYLIGHT TIME (EDT).

THE DEADLINE TO SUBMIT QUESTIONS RELATED TO THE

FOLLOWING TOPIC IS MAY 14, 2024.

CBI-01: Digital Twin for Chemical and Biological Sensors – from Proof-of-concept to Operational Twins

Background:

The Digital Battlespace Management Division within the Joint Science and Technology Office for Chemical and Biological Defense (JSTO CBI) is actively conducting research and development (R&D) for chemical and biological defense (CBD) to provide decision support to the Joint Force. Research efforts include traditional software solutions for decision support and situational awareness, as well as incorporating extended reality (XR) technologies to improve operational effectiveness and CBD readiness. Leveraging XR, in combination with Department of Defense (DoD) accredited transport and dispersion and human health effects models, has the potential to provide users with an immersive experience that emulates a CB threat environment.

Additionally, digital replicates of CB sensors can demonstrate the performance and response of various detection technologies in CB-contested operations, thereby allowing for quick and cost-effective improvement of capabilities. The digital replicates of CB sensors can also be leveraged for various applications from Artificial Intelligence/Machine Learning (AI/ML) model development to testing in synthetic environments to inform future developments. Furthermore, an effective and efficient linkage between digital and physical sensors can allow for remote operation and maintenance of the sensors.

JSTO is interested in exploring the feasibility and utility of generating a CB sensor digital twin as well as the sensor’s underlying behavior and response model (BRM). The term “digital twin” can have various meanings depending on the application and industry. The following two definitions, modified from cited references, are included to provide a common understanding of the term and assist the offerors in realizing the scope of the research objective.

Definition 1 – A digital twin is an integrated multi-physics, multi-scale, probabilistic simulation of CB sensors that uses the best available physical models, sensor updates, history, etc., to mirror the life of its operating twin. (Adapted from [1])

Definition 2 – A digital twin is a dynamic and self-evolving digital/virtual model or simulation of a real-life CB sensor representing the exact state of its physical twin at any given point of time via exchanging the real-time data as well as keeping the historical data. It is not just the digital twin that mimics its physical twin, but any changes in the digital twin are mimicked by the physical twin too. (Adapted from [2])

While the term digital twin is often used synonymously with a 3D model, based on the above two definitions, it is clear that a digital twin is more than a visualization model (Computer-aided Design CAD/ Computer-aided Engineering CAE) or simple simulation. For example, there can be physics-based models reflecting sensor behaviors and responses to various analytes/environmental conditions, data exchanges between the digital and physical twins, and a need to reflect the change in state [of the digital twin] on the physical twin.

Objectives:

JSTO CBI is looking to develop sensor digital twins and the associated BRMs for CBD. The desired characteristics/capabilities of the sensor digital twins and BRMs include but are not limited to:

The sensor digital twin shall –

• Accurately reflect and emulate sensor responses under various operational and environmental conditions based on BRM predictions.

• Allow real-time data exchanges between the digital twin and physical sensor.

• Support archiving historical data.

• Allow changes to the physical twin to be reflected in the digital twin, and vice versa.

The sensor BRMs shall –

• Accurately predict sensor responses under various operational and environmental conditions that may not be captured by datasets used in the model development process.

• Be generalizable to a wide variety of CB sensors, to the extent possible.

o It is recognized that different BMRs may be needed for different sensing modalities; nevertheless, the ability to extend the BRMs developed for one CB sensor to other CB sensors that leverage the same sensing modality with minimum model retraining is desired.

• Generate sensor response outputs, including spectra if the modeled sensor generates spectral responses, in correspondence to operational and environmental conditions.

The following should be considered when responding to this topic:

• Proposal should include clear description on technical approach with sufficient details and supporting references.

• Offerors are encouraged to partner across technical disciplines; it is envisioned that the project team shall include technical expertise in sensors/analytical chemistry, AI/ML, XR, and computer programming/coding.

• Agile development process and modular design are expected throughout the technical approach, design, delivery, and schedule.

• Developments of digital twins and BRMs shall focus on U.S. DoD-employed sensors or the parallel commercially available version. The proposal should include clear information on the sensors, including manufacturer and sensor model.

• Analytes: the digital twins and BRMs should reflect sensor behaviors and responses for traditional agents and their simulants.

Proposed Development Path:

The DoD employed field sensors of interest for digital twin and BRM development include but are not limited to the following modalities:

• Fourier-transform Infrared spectroscopy (FTIR)

• Ion mobility spectrometer

• Mass spectrometer

• Photo ionization detectors

Due to the nascent R&D related to digital twins for CBD, the following stages of development are expected for EACH sensor:

• Stage 1 (S1): Develop and demonstrate a prototype digital twin and BRM

• Stage 2 development includes two parallel paths:

o Stage 2A (S2A): Mature S1 digital twin to develop a prototype remote operation and maintenance capability and refine the BRM to improve the fidelity of predicted sensor responses (e.g., environmental conditions, sensor placement).

o Stage 2B (S2B): Once S1 prototype digital twins/BRMs for more than one sensor are developed, the awardee shall explore how the digital twins/BRMs interact with each other, the environment, and other virtual capabilities (e.g., decision support tools) in a synthetic environment.

Integration of digital twins/BRMs with other virtual platforms, particularly

Virtual Reality Tactical Assault Kit (VRTAK), shall be proposed.

In the following section and hypothetical schedule (provided for general understanding purposes only), stages of development are annotated with “Sensor-Stage” (e.g. FTIR-S1, sensor #2-S2B)

Awardee is expected to start with FTRI-S1 for digital twin and BRM development. Expansion of development to other sensing modalities can be in parallel or subsequent to FTIR-S2A development. S2B development shall not start until multiple S1 prototype digital twins/BRMs are developed.

Subject to funding availability, multiple proposals may be selected for FTIR-S1 development. A description of each phase and sample timeline is provided for reference only to aid in proposal development. While FTIR-S1 development should be limited to 12-months, the remaining phase durations, the timing of third-party testing, and the number of digital twins/BRMs under development is at the discretion of the offeror.

JSTO CBI will conduct independent, third-party testing of the digital twins and BRMs periodically throughout the effort. Selected partners shall provide necessary information, documentation, and prototypes to assist third-party evaluation. The third-party testing is not in lieu of developer’s testing and evaluation. Interested offerors should include quality assurance/quality control (QA/QC) and/or developer test and evaluation plan.

Impact:

This effort will deliver a sensor data analytics capability that provides the Joint Force with a comprehensive understanding and assessment of the CB-contested environment for improved situational awareness of the threat and hazard area.

References:

[1] Shafto, M et al., DRAFT Modeling, Simulation, Information Technology & Processing Roadmap Technology Area 11, November 2010. National Aeronautics and Space Administration. https://www.nasa.gov/pdf/501321main_TA11-MSITP-DRAFT-Nov2010- A1.pdf [2] Singh, M et al., Digital Twin: Origin to Future. Appl. Syst. Innov. 2021, 4, 36.

https://doi.org/10.3390/asi4020036