Publications

Complex systems are comprised of technical, social, political and environmental factors as well as the programmatic factors of cost, schedule and risk. Testing these systems for enhanced security requires expert knowledge in many different fields. It is important to test these systems to ensure effectiveness, but testing is limited to due cost, schedule, safety, feasibility and a myriad of other reasons. Without an effective decision framework for Test and Evaluation (T&E) planning that can take into consideration technical as well as programmatic factors and leverage expert knowledge, security in complex systems may not be assessed effectively. Therefore, this paper covers the identification of the current T&E planning problem and an approach to include the full variety of factors and leverage expert knowledge in T&E planning through the use of Bayesian Networks (BN).

As MIL-STD-810G, Environmental Engineering Considerations and Laboratory Tests, and subsequent versions have incorporated multiple-degree-of-freedom (MDOF) vibration test methodologies, it is important to understand the history and factors that drove the original decision in MIL-STD-810 to focus on single-degree-of-freedom (SDOF) vibration testing. Examining the thought process behind early MIL-STD-810 vibration test methods is useful when considering MDOF testing now that it is feasible with today's technology and documented in MIL-STD-810. This paper delves into the details of the decision made in the 1960s to develop the SDOF vibration testing standards in MIL-STD-810 beyond the limitations of technology at the time. This paper also considers the implications for effective test planning today considering the advances in test capabilities and improvements in understanding of the operational environment.

Abstract not provided.

This paper discusses the factor analysis that provides the basis for development and use of Bayesian Network (BN) models to support qualification planning in order to predict the suitability of Six Degrees of Freedom (6DOF) vibration testing for qualification. Qualification includes environmental testing such as temperature, vibration and shock to support a stochastic argument about the suitability of a design. Qualification is becoming more complex because it involves significant human expert judgment and relies on new technologies that have often never been fully utilized to support design assessment. Technology has advanced to the state where 6DOF vibration tests are possible, but these tests are far more complex than traditional single degree of freedom tests. This challenges systems engineers as they strive to plan qualification in an environment where technical and environmental constraints are coupled with the traditional costs, risk and schedule constraints. BN models may provide a framework to aid Systems Engineers in planning qualification efforts with complex constraints. Previous work identified a method for building a BN model for the predictive framework. This paper discusses validation efforts of models derived from the factor analysis and summarizes some recommendations on the factor analyses from industry subject matter experts.

The purpose of this presentation is to describe the current research in the use of Bayesian Network (BN) models to support Qualification Planning in order to predict the suitability of Six Degrees of Freedom (6DOF) vibration testing for qualification. Qualification includes environmental testing such as temperature, vibration, and shock to support a stochastic argument about the suitability of a design. Qualification is becoming more complex and restricted yet new technologies are available but not fully utilized. Technology has advanced to the state where 6DOF vibration shakers and control systems capable of high frequency tests are possible, but the problem using these systems is far more complex than traditional single degree of freedom tests. This challenges Systems Engineers as they strive to plan qualification in an environment where technical, environmental, and political constraints are coupled with the traditional cost, risk and schedule constraints. This research focuses on developing a predictive analysis framework for Six Degrees of Freedom (6DOF) vibration qualification. Specifically, this presentation covers the research approach utilizing Bayesian logic to identify and relate the driving factors affecting successful 6DOF tests. The presentation will cover the key factors and their inter-relationships. The goal of this research is to develop a statistically based decision aid for assessing 6DOF suitability. BN models may provide the framework to aid Systems Engineers in planning qualification efforts with complex constraints.

Abstract not provided.

This paper discusses the results of a study to determine the impact of culture on engineering. The study took place during the 2015 Nonlinear Mechanics and Dynamics Summer Research Institute, a six-week research program sponsored by Sandia National Laboratories and the University of New Mexico consisting of 24 graduate students participating in seven different projects. Twenty-two of the participants and two of the mentors were interviewed to study the effects of cultural background on engineering processes and interactions. The results of this study indicate that cultural differences drive engineering practices.

Abstract not provided.

This paper discusses the viability of using Bayesian Network (BN) models to support qualification planning in order to predict the suitability of Six Degrees of Freedom (6DOF) vibration testing for qualification. Qualification includes environmental testing such as temperature, vibration, and shock to support a stochastic argument about the suitability of a design. Qualification is becoming more complex and restricted yet available new technologies are not fully utilized. Technology has advanced to the state where 6DOF vibration shakers and control systems capable of high frequency tests are possible, but the problem using these systems is far more complex than traditional single degree of freedom (SDOF) tests. This challenges systems engineers as they strive to plan qualification in an environment where technical, environmental, and political constraints are coupled with the traditional cost, risk and schedule constraints. New technologies are also available for systems engineers to combine technical understanding with cost, risk and schedule factors to aid in decision making for complex problems such as qualification planning. BN models may provide the framework to aid Systems Engineers in planning qualification efforts with complex constraints. This paper discusses related work, the current approach and results of this research.