D.2 Modeling

D.2 – Modeling

Asset Performance Models

Support condition- or performance-based management strategies through the development of models to forecast asset performance over time.  Use modeling outcomes to improve asset life-cycle planning strategies selection and TAM investment and resource allocation decisions.

Common asset performance models include:

  • Improvement Benefit Models which anticipate future asset condition and/or performance for a given TAM investment.
  • Asset Deterioration Models which forecast future condition or performance of the asset, assuming no TAM investment.

Development of these models is ideally based upon statistical analysis of trusted work and performance history, however where trusted data is not available, expert opinion can be used to develop or refine asset performance models.

In combination, these models form the backbone of TAM investment optimization and prioritization analysis.

TAM Optimization and Prioritization Analysis

DOT asset management systems are often used to conduct network-level optimization analysis of potential investment strategies or treatment options. 

Key inputs to these analysis are:

  • Current Inventory and Condition necessary to baseline the analysis and establish the potential investment options.
  • Asset Performance Models which are discussed in detail above.
  • Treatment Rules and Costs defining the conditions under which a specific TAM treatment may be applied (e.g. triggering conditions) and the costs of those interventions.
  • Analysis Parameters including the:
    • Analysis Horizon, or the number of years to analyzed.
    • Analysis Objective, for example, to maximize benefit, or minimize treatment cost.
    • Analysis Constraints, such as minimum performance expectations or maximum funding limits.

For assets where condition or performance-based management is not available, age-based or reactive management techniques can be useful.  These approaches can still rely upon network-level analysis to prioritize investment options based on available asset information, associated prioritization factors, and existing funding and resources.

Cross-Asset Resource Analysis

Output from asset-specific investment optimizations can be combined and analyzed to identify optimal distribution of resources across asset and program areas.  In this approach, a DOT must relate performance outcomes from individual asset programs, to a common benefit or value (typically based on overarching agency goals and objectives).  With these relationships established, trade-off analysis can be completed to optimized the total agency benefit or value based on asset-specific outcomes modeled at various potential investment levels.

Important Terminology

The following terms are used within this Section.

Analysis Parameters:

Key inputs to agency asset management or investment optimization analysis, such as asset deterioration rates, treatment condition reset values, treatment unit costs, or analysis time horizons.

Investment Optimization:

Analysis techniques applied to select ideal TAM investments for a given analysis horizon, objective, and set of constraints.

Investment Prioritization:

Screening and ranking techniques used to establish TAM investment priorities.

Conceptual Examples
Modeling Techniques
Deterministic Modeling

A relatively simple and commonly used modeling approach in TAM. Deterministic modeling applies regression analysis to develop “best-fit” equations to characterize asset performance change over time or based on TAM investment.

Probabilistic Modeling

Useful to incorporate uncertainty by provide a distribution of possible strategies.  In TAM application, probabilistic models are most applicable to network-level analysis (such as setting funding expectations or needs).