J. Eric Dietz

Reaction kinetics and chemical changes during polymerization of multifunctional (meth)acrylates for the production of highly crosslinked polymers used in information storage systems

Abstract Crosslinked polymer samples of a wide range of triacrylates, tetraacrylates, pentaacrylates and of their corresponding methacrylates were prepared by u.v. photopolymerization of the monomers using 2,2-dimethoxy-2-phenyl-acetophenone as a photoinitiator. The monomers studied varied in rank, pendant group size and structure, and functionality or number of double bonds. The reaction kinetics was followed by differential photocalorimetry. Autoacceleration and autodeceleration phenomena were observed depending on the structure and molecular complexity of the monomer used. Conversion after 1 h, conversion at peak reaction rate, induction time, and time at peak reaction rate were dependent on the rank and functionality of the monomers used. Volume shrinkage during the reaction was measured by a modified thermomechanical analysis experiment and correlated to calorimetric data. A delay in volume shrinkage during polymerization was observed and correlated to rank and functionality. Dynamic mechanical studies were used to determine α, β, γ relaxations and linear expansion coefficients which were correlated to the polymer network structure.

Using Mobile Robots to Establish Mobile Wireless Mesh Networks and Increase Network Throughput

We discuss the proof of concept that gives mobile robotic units the ability to provide a mobile wireless mesh network providing wireless service to end-clients and also demonstrate the ability to increase the throughput of this mobile wireless mesh system by autonomously reducing the hop count required for network traffic to transit through. In doing so, this proof-of-concept contributes to future development of a robust system which can be deployed and utilized in different situations and industry.

Using directional antennas as sensors to assist fire-fighting robots in large scale fires

Humans will replace human labor with new robotics technologies, especially where humans can be placed in danger situations or task domains. Evolving sensor and robotic technologies allow the transfer of humans from mundane, dangerous or difficult tasks, leaving robots to apply their specific capabilities to replace humans daily routines or hazardous tasks. Commonly, humans work in teams to resolve difficult scenarios, such as the aftermath of some natural or man-made disaster. Communication between each and every team member is critical to resolve relief efforts or remediation, in most disasters. This research presents robotic technology developed to remediate the long lead time to re-establish or develop network infrastructure in the case of a disaster situation. The specific application and test domain of this research, is with fire fighting.

Combining multiple, inexpensive GPS receivers to improve accuracy and reliability

GPS is a technology that allows for accurate tracking of various parameters, namely speed and location. These parameters are important to many applications, such as autonomous vehicles. In order to make a successful autonomous vehicle, it is necessary to be able to quantify its performance. Tracking a vehicle with GPS is an effective, well-established way to accomplish that. However, the consumer-level GPS technology available today is not accurate enough to provide useful data about a vehicles speed and position with respect to something as restricted as a race track or a sidewalk. To attempt to solve this problem, the goal of this research is to significantly improve the accuracy of GPS, using only inexpensive GPS receivers and the supporting electronic components. Data from individual receivers will be merged, which will provide a more accurate tracking system capable of fine enough detail to provide useful data for many applications.

Modeling of a Regional Hub Reception Center to improve the speed of an urban area evacuation

The city of Chicago, Illinois is making strides to become more prepared for large-scale disasters. One idea is called a Regional Hub Reception Center (RHRC), which converts an existing facility into a temporary shelter for evacuees in the event of a 10-kiloton nuclear blast being detonated in the center of downtown. The RHRC will provide the evacuees with basic needs and register them for assignment at a more permanent shelter. The Regional Catastrophic Planning Team needs to know if its estimates for time, personnel, and resources are accurate. The best and most reliable way to test what will be needed is to perform simulations. However, large full-scale simulations are time consuming and expensive. A computer-generated model, however, can accurately simulate many variables and scenarios to test the RHRC quickly, cheaply, and repetitively to make it more effective if used. A computer modeling software tool, called AnyLogic, is a multi-paradigm modeling program that allows users to build agent-based, discrete event, and system dynamics models. The modeling paradigm that best suits the simulation of an RHRC is discrete event modeling. This is because a discrete event model represents a chronological sequence of events. When an event occurs in a discrete event model, it represents a change to the entire system. An RHRC is a chronological sequence of events and a system of systems that are constantly changing. As evacuees move through the RHRC, they flow through a predefined set of points, ranging from registration, to care, to shelter assignment, and many others. The data provided is supported by research or by personal field experience where research has not yet been performed. A model is a simulation of the real world. Though it does not represent the 100% of the variables that could occur in an actual simulation, it takes into consideration as many as possible to provide the most accurate results. The RHRC AnyLogic model is a simulation that estimates resource needs and processes of an RHRC. The RHRC model created to support this paper was developed using data collected by all students in Dr. J. Eric Dietzs Homeland Security Seminar graduate level class at Purdue University in the spring semester of 2012. The purpose of this study is to determine if the goals of the Regional Catastrophic Planning Team are attainable based upon the data collected.

A Fuzzy Approach for Assessing Transportation Infrastructure Security

The security of any transportation infrastructure can be defined as a combination of threat likelihood, infrastructure resilience, and consequence. In view of their inherently dynamic and highly unpredictable nature, threat likelihood and consequence data is difficult to determine with certainty. Due to this problem, this paper presents a new fuzzy methodology to qualitatively determine the overall security level, in terms of a security rating, for transportation infrastructure by duly considering the uncertainties of the environmental threats it faces, its resilience to damage, and the consequences of the infrastructure damage. The method is useful when data is unavailable or imprecise, allowing the security rating to be determined using a qualitative expert-assigned level that each factor contributes to overall security. The evaluation of the security factors are represented as fuzzy triangular numbers with accompanying membership rules that define the extent of contribution by each factor to overall infrastructure security. Through a case study, the paper applies the methodology to illustrate how general data can be used in the method to determine the overall security of specific infrastructure.

A multi-criteria methodology for measuring the resilience of transportation assets

Purpose Transportation project evaluation and prioritization use traditional performance measures including travel time, safety, user costs, economic efficiency and environmental quality. The project impacts in terms of enhancing the infrastructure resilience or mitigating the consequences of infrastructure damage in the event of disaster occurrence are rarely considered in project evaluation. This paper aims to present a methodology to address this issue so that in prioritizing investments, infrastructure with low security can receive the attention they deserve. Second, the methodology can be used for prioritizing candidate investments from a budget that is dedicated specifically to security enhancement. Design/methodology/approach In defining security as the absence of risk of damage from threats due to inherent structural or functional resilience, this paper uses security-related considerations in investment prioritization, thus introducing robustness in such evaluation. As this leads to an increase in the number of performance criteria in the evaluation, the paper adopts a multi-criteria analysis approach. The paper’s methodology quantifies the overall security level for an infrastructure in terms of the threats it faces, its resilience to damage and the consequences in the event of the infrastructure damage. Findings The paper demonstrates that it is feasible to develop a security-related measure that can be used as a performance criterion in the evaluation of general transportation projects or projects dedicated specifically toward security improvement. Through a case study, the paper applies the methodology by measuring the risk (and hence, security) of each for multiple infrastructure assets. On the basis of the multiple types of impacts including risk impacts (i.e. increase in security) because of each candidate investment, the paper shows how to prioritize security investments across the multiple infrastructure assets using multi-criteria analysis. Originality/value The overall framework consists of the traditional steps in risk management, and the paper’s specific contribution is in the part of the framework that measures the risk. The paper shows how infrastructure security can be quantified and incorporated in the project evaluation process.

Active shooter mitigation for gun-free zones

Active shooting violence poses a serious threat to public safety. The outcome is tragic due to the large number of casualties and injuries that can occur as well as the lasting emotional devastation it causes. This study examines the impact of active shooters in gun-free zones. Gun-free zones include all areas where the general public is forbidden to carry firearms. The goal of an active shooter is to shoot, at random, as many people as possible in the shortest amount of time. This makes gun-free zones a likely target since no one inside is permitted to carry a gun. The study uses a computer simulation program, called AnyLogic®, to create a lifelike gun-free zone workplace. Using the agent-based simulation model, different policy decisions are tested against one another. Those policy decisions include a default scenario in which no safety protocol is in place other than law enforcement response, a security guard scenario in which an armed security guard is present, a concealed carry scenario in which employees are allowed to carry concealed weapons, and a locked door scenario in which all interior doors are locked. The study demonstrates how response time has the largest impact of any variable in ensuring the least amount of casualties in an active shooting situation. Response time and number of casualties can be decreased depending upon the policy chosen. The purpose of this study is to allow policy makers to compare the costs and benefits of policies for their respective gun-free zones in order to make more informed decisions which could save lives.

Energy overhead of the graphical user interface in server operating systems

Evidence of graphical user interface server operating system energy overhead is presented. It is posed that data centers would have substantial energy savings by eliminating graphical user interface operating systems.

Lithium-Ion Battery Cell Health Monitoring Using Vibration Diagnostic Test.

With their superior advantages of high capacity and low percentage of self-discharge, lithium-ion batteries have become the most popular choice for power storage in electric vehicles. Due to the increased potential for long life of lithium-ion batteries in vehicle applications, manufacturers are pursuing methodologies to increase the reliability of their batteries. This research project is focused on utilizing non-destructive vibration diagnostic testing methods to monitor changes in the physical properties of the lithium-ion battery electrodes, which dictate the states of charge (SOC) and states of health (SOH) of the battery cell. When the battery cell is cycled, matter is transported from one electrode to another which causes mechanical properties such as thickness, mass, stiffness of the electrodes inside a battery cell to change at different states of charge; therefore, the detection of these changes will serve to determine the state of charge of the battery cell. As mass and stiffness of the electrodes change during charge and discharge, they will respond to the excitation input differently. An automated vibration diagnostic test is developed to characterize the state of charge of a lithium-ion battery cell by measuring the amplitude and phase of the kinematic response as a function of excitation frequency at different states of charge of the battery cell and at different times in the life of the cell. Also, the mechanical properties of the electrodes at different states of charge are obtained by direct measurements to develop a first-principles frequency response model for the battery cell. The correlation between the vibration test results and the model will be used to determine the state of charge of the cell.Copyright