Ballistic Vests

Technology Roadmap Sections and Deliverables

The selected technology that Team 6 will be spending the remainder of the semester on developing a technology road map is ballistic vest technology (specifically for military and law enforcement applications).

Clear and unique identifier:

• 2BV - Ballistic Vests

This indicates that we are dealing with a “level 2” roadmap at the product level.

Roadmap Overview

The working principle and architecture of Ballistic Vests is depicted in the below.

A ballistic vest works by absorbing the kinetic energy from a high-speed projectile (bullet or shrapnel from an explosion) at the point of impact over a wide area. The ballistic vest is meant to spread the kinetic energy by displacing it across the ballistic vest materials in a process called material deformation. The deformation occurs in two-fold, deformation of the ballistic vest materials as the bullet absorbs the kinetic energy and deformation of the bullet itself, called mushrooming. The remainder of the energy is consumed as heat.

This technology is a lifesaving technology to aid military personnel and law enforcement during their daily activities. A ballistic vest is typically worn on an individual’s chest and is meant to be replaced after it has taken an impact (from high speed projectile or mishandling of vest e.g. dropped) or date of manufacturing has expired. There are six levels of protection (Type I, Type IIA, Type II, Type IIA, Type III, and Type IV). The history of personal armor dates back to 500 BC when chain mail/coat mail was used as a form of individual protection from slashing blows by an edged weapon (e.g. swords). Modern day individual body armor is meant to protect from high speed projectiles. New fibers were discovered in the 1960’s for the possibility to make resistant vests and DuPont developed Kevlar ballistic fabric in the 1970s.

Design Structure Matrix (DSM) Allocation

The 2-BV tree that we can extract from the DSM above shows us that the Ballistic Vest (2BV) is part of a larger company-wide initiative on electrification of flight (1ELE), and that it requires the following key enabling technologies at the subsystem level: 3CFP Carbon Fiber Polymers, 3HEP Hybrid Electric Propulsion and 3EPS Non-Propulsive Energy Management (e.g. this includes the management of the charge-discharge cycle of the batteries during the day-night cycle). In turn these require enabling technologies at level 4, the technology component level: 4CMP components made from CFRP (spars, wing box, fairings …), 4EMT electric machines (motors and generators), 4ENS energy sources (such as thin film photovoltaics bonded to flight surfaces) and 4STO (energy storage in the form of lithium-type batteries).

Roadmap Model using OPM

We provide an Object-Process-Diagram (OPD) of the 2SEA roadmap in the figure below. This diagram captures the main object of the roadmap (Solar-Electric Aircraft), its various instances including main competitors, its decomposition into subsystems (wing, battery, e-motor …), its characterization by Figures of Merit (FOMs) as well as the main processes (Flying, Recharging).

An Object-Process-Language (OPL) description of the roadmap scope is auto-generated and given below. It reflects the same content as the previous figure, but in a formal natural language.

Figures of Merit

The table below show a list of FOMs by which solar electric aircraft can be assessed. The first four (shown in bold) are used to assess the aircraft itself. They are very similar to the FOMs that are used to compare traditional aircraft which are propelled by fossil fuels, the big difference being that 2SEA is essentially emissions free during flight operations. The other rows represent subordinated FOMs which impact the performance and cost of solar electric aircraft but are provided as outputs (primary FOMs) from lower level roadmaps at level 3 or level 4, see the DSM above.

Besides defining what the FOMs are, this section of the roadmap should also contain the FOM trends over time dFOM/dt as well as some of the key governing equations that underpin the technology. These governing equations can be derived from physics (or chemistry, biology ..) or they can be empirically derived from a multivariate regression model. The table below shows an example of a key governing equation governing (solar-) electric aircraft.