In order to leverage advances made in body-armor materials, as well as to further the design landscape, considering body armor as a complete human-centric system is becoming more prevalent. This trend necessitates a greater focus on human systems integration (HSI) and human-centric design. Digital human models (DHMs) provide a powerful tool for HSI, but modeling-and-simulation tools, let alone DHMs, have rarely been used with body armor. With respect to analysis, this is changing. New methods for evaluating body armor from a biomechanical perspective have been developed within the SantosTM DHM. It is now possible to import digital models of body-armor systems, place them on an avatar, simulate various tasks (i.e., running, aiming, etc.), and then virtually evaluate the armor's effect on performance, balance, mobility, bulk, etc. However, with respect to design, there are no available simulation tools to help users balance the goals of maximizing mobility and survivability concurrently. In response to these growing needs, there are two new areas of work being proposed and discussed. First, this work leverages a series of new virtual evaluation capabilities for Personal Protective Equipment (PPE) and implements a filter that automatically evaluates and selects from a library of designs the most advantageous PPE system based on user-selected objectives and constraints. Initial tests have shown realistic results with minimal computational demand. Secondly, this thesis proposes a new method for armor-system topology optimization that optimizes not only biomechanical metrics but also external (to the DHM system) metrics from potentially complex injury and protection models. The design variables for this optimization problem represent the position on the body of small body-armor elements. In addition, the existence of each element is modeled as a variable, such that unnecessary elements are determined and removed automatically. This inclusion of location in combination with the traditional existence variable is a novel inclusion to the topology optimization method. Constraints require that no two elements overlap. The objective functions that govern where the armor elements are moved must be general enough to function with any external data, such as survivability. Thus, a novel process has been developed for importing external data points (i.e., stress at points in the body resulting from a blast simulation) and using regression analysis to represent these points analytically. Then, by using sequential quadratic programming for gradient-based optimization, the armor elements are automatically positioned in order to optimize the objective function (i.e., minimize potential injury). This new approach allows any metric to be used in order to determine general body-armor concepts upstream in the design process. This system has the potential to become especially useful when trying to optimize multiple objectives simultaneously, the results of which are not necessarily intuitive. Thus, given a specified amount of material, one can determine where to place it in order to, for example, maximize mobility, maximize survivability, and maximize balance during a series of specified mission-critical tasks. The intent is not necessarily to provide a final design with one "click"; accurately considering all aspects of hard and soft armor is beyond the scope of this work. However, these methods work towards providing a design aid to help steer system concepts. Test cases have been successfully run to maximize coverage of specific external data for internal organs (and thus survivability) and mobility, while minimizing weight. The weight metric has also been successfully used as a constraint in the optimal armor design. In summary, this work provides 1) initial steps towards an automated design tool for body armor, 2) a means for integrating different analysis models, and 3) a unique example of human-in-the-loop analysis and optimization.