A Lehigh team is working on a 3-year, $264,000 grant from the US Army to build optimization algorithms for automating the design of layouts for ammunition support activities. The research team consists of Professors Bob Storer, Larry Snyder, and Luis Zuluaga from ISE, Mike Spear from CSE, and PhD student Ruby Zhuo.
The main focus of the research is the design of field-based ammunition supply points (ASPs) and ammunition transfer points (ATPs). There is an obvious need for expediency in the design and construction of these facilities in field operations. The current process of laying out theater field storage facilities is a manual, time consuming, and labor-intensive process that relies extensively on the experience of ammunition Chief Warrant (CW) Officers. Aided by mapping and graphical software, the designer can plan the ASP design by locating the various facilities on a map, observing the flaws in the design, and then reconfiguring the design in a “manual” trial and error procedure. This process is time consuming, and offers little guarantee of the ultimate quality and effectiveness of the design. In short, it presents an ideal opportunity for automated optimization algorithms.
The main issue in designing ASPs is the need to separate, at a safe distance, multiple explosive storage units from each other and from roads, buildings and other vulnerable sites. Quantity Distance (QD) rules, established by the Department of Defense, are a set of guidelines that determine the required distance between an explosives storage facility and another exposed facility. These distances are dependent on the hazard class division (HCD) and the quantity of net explosive weight (NEW) being stored at a storage unit. Different distance requirements exist depending on the nature of the sites. For example, there are different requirements for distances from public roads, inhabited building, and other explosive storage sites.
In the approach taken by the team, one assumes that each of the individual facilities/elements of the ASP that need to be located (both storage units and other exposed sites) are known, including the contents of each storage unit. Given this information, the minimum distance requirements can be calculated, and each facility will be located so as not to violate minimum distance requirements and optimize the area used or an appropriate measure of risk.