8 Jan 2024

RISC TAMER Framework: Resilient Installation Support Against Compound Threats Analysis and Mitigation for Equipment and Resources Framework

Every day, decision-makers must allocate resources based on the best available information at the time. Military installations face a variety of threats which challenge sustained functionality of their supporting and supported deployable systems. Considering the compounding and interdependent impacts of the threats, both specified (what is known) and unspecified (what is not known) and the investments needed to address these threats adds value to the decision-making process. Current risk management practices are generally evaluated via scenario analyses that do not consider compound threats, resulting in limited risk management solutions. Current practices also challenge the ability of decision-makers to increase resilience against such threats. The Resilient Installation Support against Compound Threats Analysis and Mitigation for Equipment and Resources (RISC TAMER) Framework establishes a decision support structure to identify and categorize system components, compound threats and risks, and system relationships to provide decision-makers with more complete and comprehensive information from which to base resilience-related decisions, for prevention and response. This paper focuses on the development process for RISC TAMER framework to optimize resilience enhancements for a wide variety of deployable systems in order to implement resilience strategies to protect assets, to increase adaptability, and to support power projection and global operations.

25 Jun 2020

PUBLICATION NOTICE: A Generalized Approach for Modeling Creep of Snow Foundations

ABSTRACT:  When an external load is applied, snow will continue to deform in time, or creep, until the load is removed. When using snow as a foundation material, one must consider the time-dependent nature of snow mechanics to understand its long-term structural performance. In this work, we develop a general approach for predicting the creep behavior of snow. This new approach spans the primary (nonlinear) to secondary (linear) creep regimes. Our method is based on a uniaxial rheological Burgers model and is extended to three dimensions. We parameterize the model with density- and temperature-dependent constants that we calculate from experimental snow creep data. A finite element implementation of the multiaxial snow creep model is derived, and its inclusion in an ABAQUS user material model is discussed. We verified the user material model against our analytical snow creep model and validated our model against additional experimental data sets. The results show that the model captures the creep behavior of snow over various time scales, temperatures, densities, and external loads. By furthering our ability to more accurately predict snow foundation movement, we can help prevent unexpected failures and extend the useful lifespan of structures that are constructed on snow.