The activity-based approach to travel demand analysis and modeling, which has been developed over the past 30 years, has received tremendous success in transportation planning and policy analysis issues, capturing the multi-way joint relationships among socio-demographic, economic, land use characteristics, activity participation, and travel behavior. The development of synthesizing population with an array of socio-demographic and socio-economic attributes has drawn remarkable attention due to privacy and cost constraints in collecting and disclosing full scale data. Although, there has been enormous progress in producing synthetic population, there has been less progress in the development of population evolution modeling arena to forecast future year population. The objective of this dissertation is to develop a well-structured full-fledged demographic evolution modeling system, capturing migration dynamics and evolution of person level attributes, introducing the concept of new household formations and apprehending the dynamics of household level long-term choices over time. A comprehensive study has been conducted on demography, sociology, anthropology, economics and transportation engineering area to better understand the dynamics of evolutionary activities over time and their impacts in travel behavior. This dissertation describes the methodology and the conceptual framework, and the development of model components. Demographic, socio-economic, and land use data from American Community Survey, National Household Travel Survey, Census PUMS, United States Time Series Economic Dynamic data and United States Center for Disease Control and Prevention have been used in this research. The entire modeling system has been implemented and coded using programming language to develop the population evolution module named `PopEvol' into a computer simulation environment. The module then has been demonstrated for a portion of Maricopa County area in Arizona to predict the milestone year population to check the accuracy of forecasting. The module has also been used to evolve the base year population for next 15 years and the evolutionary trend has been investigated.
Quantum resilience makes two very important claims. First, resilience cannot be characterized without recognizing both the system and the valued function it provides. Second, resilience is not about disturbances, insults, threats, or perturbations. To avoid crippling infinities, characterization of resilience must be accomplishable without disturbances in mind. In light of this, quantum resilience defines resilience as the extent to which a system delivers its valued functions, and characterizes resilience as a function of system productivity and complexity. System productivity vis-à-vis specified “valued functions” involves (1) the quanta of the valued function delivered, and (2) the number of systems (within the greater system) which deliver it. System complexity is defined structurally and relationally and is a function of a variety of items including (1) system-of-systems hierarchical decomposition, (2) interfaces and connections between systems, and (3) inter-system dependencies.
Among the important features of quantum resilience is that it can be implemented in any system engineering tool that provides sufficient design and specification rigor (i.e., one that supports standards like the Lifecycle and Systems Modeling languages and frameworks like the DoD Architecture Framework). Further, this can be accomplished with minimal software development and has been demonstrated in three model-based system engineering tools, two of which are commercially available, well-respected, and widely used. This pragmatic approach assures transparency and consistency in characterization of resilience in any discipline.
This research, sponsored by National Academy of Construction, the Construction Industry Institute and Arizona State University, used structured interviews, a Delphi study and focus groups to explore: 1) potential benefit and industry interest in an open repository of best practices and 2) important elements of a framework/model that guides the creation, management and sustainment of an open repository of best practices.
This dissertation presents findings specifically exploring the term "Practices for Excellence", its definition, elements that hinder implementation, the potential value of an open online repository for such practices and a model to develop an open repository.