DON26TZ01-NV015 TITLE: Advancing Human Modeling Tools for Enhanced Performance and Survivability in Austere Environments

COMPONENT TECHNOLOGY PRIORITY AREA(S): Advanced Materials;Human-Machine Interfaces;Sustainment

PROJECTED CMMC LEVEL REQUIREMENT: Level 2 (Self)

OBJECTIVE: Develop an advanced suite of parametric human modeling tools incorporating USN/USMC aircrew anthropometric databases, empirical posture data, and 3D scans.

DESCRIPTION: The goal of this STTR topic is to leverage newly available data and advances in digital human modeling to improve modeling fidelity for USN/USMC and other DOW aircrew to improve acquisition outcomes. Resulting improvements to operational and environmentally appropriate protective clothing and equipment size, design, and tariffing (i.e., determination of how much of each size needs to be procured and distributed) will yield significant benefits to Fleet readiness and sustainment, safety, performance, protection, and affordability.

Digital Human Modeling (DHM) applications and tools are used to design and assess items for the DOW including protective clothing, footwear, body armor, flight equipment (e.g., helmets, oxygen masks, survival vests, G-suits, torso harnesses, etc.), seating, restraint systems, workstations, cockpits, controls, ground vehicles, and much more. Using this technology early in the product lifecycle is essential to reducing development cost and schedule and informing design tradeoff decisions. Historically, use of DHM has been subject to a variety of limitations that affect model fidelity, which is how well the model represents reality. These limitations result in reduced utility of the technology when the limitations are understood, but more concerning are the potential adverse outcomes where the limitations have either not been understood or have been ignored. This is concerning for all types of design applications, but especially problematic in aviation where safety of flight is crucial. There is an abundance of feedback from aircrew regarding poor fit or lack of availability of the sizes of protective clothing and operational equipment they need. They experience pain and injury, reducing performance and impacting readiness. There is now the potential to exponentially improve DHM capabilities due to a variety of advances in 3D scanning, model development, and availability of aircrew population specific anthropometric data and empirical posture data representing real-world conditions for military aircrew.

Limitations to current DHM capabilities related to the users include issues with intuitiveness of the tools, the degree of expertise required for effective use, and the significant amount of time it takes to develop expertise. There is a shortage of expert users in both the DOW and industry. Manikins used in DHM analysis are commonly selected from built-in software libraries with inappropriate anthropometric measurements for the population and/or design being evaluated. DHM users with a poor understanding of anthropometry often fail to consider the multivariate nature of anthropometric accommodation ignoring the need to consider more than one measurement at a time and neglecting the critical interactions of the measurements. Users positioning/posturing manikins routinely use guesswork in the absence of empirical data to account for clothing and flight equipment, restraint systems, cushion compression, flesh compression, and postural variation. They often have a limited understanding of aircrew operations and/or environment leading to incorrect assumptions when setting up their models.

For some DHMs the anthropometric measurements that can be adjusted are not the ones that matter for design application and the underlying anthropometric data used in the application may not represent the target population. Multivariate use cases have been developed and in use on DOW aircraft acquisition programs since the mid-90s [Ref 1], but manikins representing the use cases are often not included in DHM manikin libraries causing users to default to inappropriate use of the manikins that are available. Until recently, the only USN/USMC aircrew anthropometric data available was from a 1960s database that did not include women. Currently, there are no DHM applications that include USN/USMC aircrew anthropometric data or associated multivariate use cases.

Another important consideration is that the commercially available DHM applications allow for analysis of one or more manikins, to include a family of multivariate use cases, but do not allow for parametric modeling of an entire population needed to accurately quantify the accommodation levels of a design.

The NAWCAD Human Systems Engineering Department has recently completed an aircrew/aviator anthropometric survey and is also collaborating with the USAF on the Seat Specific Posture Model (SSPM) Project to collect empirical posture data to improve modeling fidelity. This project was initially intended for the purpose of developing an aviation specific postural analysis tool in the RAMSIS DHM but will be useful for other applications as well. One example that this STTR topic proposes is that this aircrew data be used in in the development of aviation-specific parametric accommodation models. The US Army has successfully developed this type of modeling tool for ground vehicles with a great many advantages to their acquisition programs and alleviation of many of the limitations documented above [Refs 2,3,4].

There have also been significant advances to head, hand, and body models that can be leveraged to greatly improve DHM state of the art and acquisition outcomes [Refs 5-11]. Integration of aircrew-specific anthropometric and 3D scan databases would ensure modeling efforts reflect the intended population. Aviators are a distinctly different population and appropriate representation of them in modeling applications is essential. Model input parameters can be adjusted to represent the goals of the modeling effort (i.e., desired accommodation levels and target population or subpopulation) with adjustable demographic variables such as sex, age, and race/ethnicity. Modeling tools can incorporate the ability to consider not only traditional 2D anthropometric measurements, but 3D shape and/or non-traditional measurements with the goal of improving size design and fit prediction [Refs 12, 13]. Through new and affordable 3D body scanning technologies [Refs 14,15], it is possible for an individual’s specific anthropometry as well as their feedback on fit and preferred size to be run through an artificial intelligence (AI) algorithm to allow for ongoing improvements in size design, fit prediction, and tariffing. There have been advances in the development of head models that do not include hair artifacts [Ref 16], an important consideration in design. Improvements of head and hand models for dynamic or functional fit can improve the ability to digitally evaluate if masks maintain a seal when pilots talk or change facial expression and if gloves are designed appropriately for all pilot tasks, not just one static hand position. Posable manikins representing intended individuals or populations (multivariate use cases) can be easily customized and imported into any CAD environment or DHM software application for a variety of uses.

It is important to note that the proposed tools are meant to be supplemental not duplicative of other modeling tools currently available or in development. Having these proposed modeling tools be interoperable or integrated with existing or emerging tools is highly desirable.

What makes these tools unique from existing/emerging modeling tools:

• Inclusion of USN/USMC aircrew anthropometric databases and 3D scans.

• Inclusion of SSPM project aircrew posture and reach data.

• Solution is not computationally and/or time prohibitive to use.

• Fills a gap in providing a solution that does not require an artisan modeler to make use of the models (easy to learn, simple user interface).

• Leveraging existing models/methods for expeditious transition.

• Models to be exported in common file formats to be interoperable with a broad range of CAD/DHM applications. No specific software applications are required.

• Not strictly PPE focused but also applicable to clothing design.

• Includes accommodation modeling tool for aircraft cockpits and workstations.

• Will represent digital twins of individuals like other modeling tools, but will also provide population virtual assessment of fit, size design, tariffing recommendations, and report population accommodation levels.

• Will allow for principal component analysis on a population and representation of boundary cases customized for specific applications.

• Includes ability to import anthropometric data for a group of participants and create bivariate plots for visual comparison to aircrew population data.

• Models will be web-hosted and freely/easily available to DOW civilians and contractors.

• Intention is to have web-hosted instructional materials, user forum, document library, and subject matter expert information to encourage best practices and collaboration.

• Framework will be built in to allow import of other population databases so other military populations including foreign military partners can be represented.

The proposed suite of tools would need to be easy to use, affordable, and easily accessed (e.g., hosted webapps and/or downloadable standalone applications) to facilitate practitioner usage and standardization. Accompanying guidance in the form of teaching materials, a user forum, links to relevant papers and reports, and a registry for subject matter experts and facilities wishing to be listed would be beneficial inclusions. The ability to create visualizations should also be considered. Allowing the import of anthropometry in a .CSV file for overlay with existing anthropometric databases in the form of bivariate plots of key anthropometric measurements is extremely helpful for population comparisons as well as confirming that human participants used for physical assessments adequately represent the target population. This proposed effort also seeks to put a framework in place that will allow incorporation of data from other populations and use of the models for other applications and users to include the entire DOW, foreign military partners, NASA, industry, and academia.

PHASE I: Identify, discuss, and demonstrate an approach to develop new or update existing models to create a suite of tools that will improve modeling fidelity for aviation applications. Ensure that the approach would seek to address limitations of the current state of the art as well as leverage recent improvements where feasible within the scope of this topic. Include plans for development and testing of prototypes to be developed during Phase II.

PHASE II: Develop and demonstrate prototype parametric aviator head, hand, and body shape models as well as an accommodation model tool. Provide access to the prototype for evaluation by end-user DOW subject matter experts (SMEs).

PHASE III DUAL USE APPLICATIONS: Upon completion of modeling tool development, the tools will be web hosted and made freely available to DOW users (civilian and contractors), vendors, and academia. They will have immediate benefit to numerous programs/platforms (e.g., PMA-202, Joint Strike Fighter), Human Systems SMEs, and DOW manufacturers/suppliers. Accompanying guidance in the form of teaching materials, a user forum, links to relevant papers and reports, and a registry for subject matter experts and facilities wishing to be listed are desired inclusions. The USN will not incur an ongoing webhosting cost. Model improvements (e.g., incorporation of new/additional scans and anthropometry, customization or new development of a tool for a specific application that was outside the scope of the STTR, etc.) may provide follow-on funding opportunities by Program Offices or other DOW entities. The STTR partners may choose whether they would like to make the tools freely available to the public or charge a fee for use for other organizations that may find the tools useful.

Other commercial opportunities include expanding the populations represented by the tools to include foreign military and civilian populations.

 

 

 

REFERENCES:

1. Da Silva, G. V.; Zehner, G. F. and Hudson, J. A. "Comparison of univariate and multivariate anthropometric design requirements methods for flight deck design application." Ergonomics, 63(9), 2020, pp. 1133-1149. https://doi.org/10.1080/00140139.2020.1765029
2. Reed, M. P. and Ebert, S. M. "The seated soldier study: Posture and body shape in vehicle seats [Technical Report]." University of Michigan, Ann Arbor, Transportation Research Institute, 2013. http://deepblue.lib.umich.edu/handle/2027.42/109725
3. Reed, M. P. and Ebert, S. M. "Development of Driver Posture Prediction and Accommodation Models for Military Vehicles: Fixed-Eye-Point, Out-of-Hatch, and Highly Reclined Driver Configurations [Technical Report]." University of Michigan, Ann Arbor, Transportation Research Institute, 2020. http://deepblue.lib.umich.edu/handle/2027.42/163365
4. Huston, F. J. I. and Zielinski, G. L. (n.d.). "Fixed Eye Point (FEP): Driver CAD Accommodation Model Verification Report (Version 1.0)." U.S. Army Ground Vehicle Systems Center, July 13, 2021. https://apps.dtic.mil/sti/citations/trecms/AD1144687 and https://apps.dtic.mil/sti/trecms/pdf/AD1144687.pdf
5. Reed, M. P. and Jones, M. L. H. "A Parametric Model of Cervical Spine Geometry and Posture [Technical Report]." University of Michigan, Ann Arbor, Transportation Research Institute, 2017. http://deepblue.lib.umich.edu/handle/2027.42/137652
6. Reed, M. P.; Jones, M. L. H. and Park, B. D. "Modeling People Wearing Body Armor and Protective Equipment: Applications to Vehicle Design." Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Vol. 826, 2019, pp. 596–601. Springer International Publishing. https://doi.org/10.1007/978-3-319-96065-4_63
7. Reed, M.; Raschke, U.; Tirumali, R. and Parkinson, M. "Developing and Implementing Parametric Human Body Shape Models in Ergonomics Software." https://www.semanticscholar.org/paper/Developing-and-Implementing-Parametric-Human-Body-Reed-Raschke/a60ae2987f8f55872e937505c404222b4d4c6f1f
8. Park, J.; Ebert, S.; Reed, M. and Hallman, J. "Statistical Models for Predicting Automobile Driving Postures for Men and Women Including Effects of Age. Human Factors, 58(2), 2015, pp. 261-278." https://doi.org/10.1177/0018720815610249
9. Parkinson, M. and Reed, M. "Creating virtual user populations by analysis of anthropometric data." International Journal of Industrial Ergonomics, 40, 2010, pp. 106-111. https://doi.org/10.1016/j.ergon.2009.07.003
10. Reed, M. and Parkinson, M. "Modeling Variability in Torso Shape for Chair and Seat Design." Proceedings of the ASME Design Engineering Technical Conference (Vol. 1), 2008. https://doi.org/10.1115/DETC2008-49483
11. Tambwekar, A.; Park, B.-K. D.; Kusari, A. and Sun, W. "Three-Dimensional Posture Estimation of Vehicle Occupants Using Depth and Infrared Images." Sensors, Basel, Switzerland, 24(17), 2024, p. 5530. https://doi.org/10.3390/s24175530
12. Yu, M.; Griffin, L.; Durfee, W. K. and Arnold, S. "Face anthropometry for filtering facepiece respirators: Analysis of the association between facial dimensions and respirator fit." Annals of Work Exposures and Health, 68(3), 2024, pp. 312-324. https://doi.org/10.1093/annweh/wxae005
13. Griffin, L.; Sokolowski, S.; Savvateev, E.; Bhuyan, M. A.-U.-A. and Roese, N. "Comparison of Glove Specifications, 3D Hand Scans, and Sizing of Sports Gloves for Athletes." Proceedings in the 3DBODY.TECH 2019 - 10th Int. Conf. and Exhibit on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 22-23 Oct. 2019, pp. 109-118. https://doi.org/10.15221/19.109
14. "BioHuman: PassFit, Portable 3D Anthropometry System." (n.d.). University of Michigan Transportation Research Institute. http://humanshape.org
15. Park, B.-K. and Reed, M. "A Model-based Approach to Rapid Estimation of Body Shape and Postures Using Low-Cost Depth Cameras." Proceedings of the 3DBODY.TECH 2017 - 8th Int. Conf. and Exhibit on 3D Body Scanning and Processing Technologies, Montreal QC, Canada, 11-12 Oct. 2017, pp. 281-287. https://doi.org/10.15221/17.281.
16. Park, B.-K. D.; Corner, B. D.; Hudson, J. A.; Whitestone, J.; Mullenger, C. R. and Reed, M. P. "A three-dimensional parametric adult head model with representation of scalp shape variability under hair." Applied Ergonomics, 90, January 2021, 103239. https://doi.org/10.1016/j.apergo.2020.103239

KEYWORDS: Digital Human Modeling; Human Systems; Protective Clothing; Protective Equipment; Cold Weather Gear; Aircrew

TPOC 1
Lori Basham
lori.l.basham2.civ@us.navy.mil

TPOC 2
Kenneth Ritchey
kenneth.j.ritchey2.civ@us.navy.mil