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Constant

A Constant Time Series defines a time–history where the load factor λ\lambda is independent of time:

λ(t)=cfactor\lambda(t) = c_\text{factor}

This is the simplest time series in Alpaca4d and is typically used when a load (or a group of loads) is applied with a constant intensity for the whole duration of the analysis.

🔧 Grasshopper component

The Constant Time Series (Alpaca4d) component creates an internal Alpaca4d time series that can be connected to load pattern or excitation components.

  • Input

    • LoadFactor: Constant scale factor $ c_\text{factor} $ applied to the reference loads in the associated load pattern.

      • Type: Number

      • Default: 1.0

      • Effect: All loads in the pattern are multiplied by this value at every analysis time step.

  • Outputs

    • TimeSeries: Alpaca4d Constant time series object, to be plugged into components that require a time series (e.g. load patterns, uniform excitation).

    • Graph: A curve/polyline representing the time series, useful for quick visual inspection in Grasshopper (flat line at $ \lambda = c_\text{factor} $).

📈 When to use a constant time series

  • Use it when

    • Loads are turned on and stay on for the entire analysis (e.g. dead loads, permanent equipment loads).

    • You want a constant base excitation scale factor during a time‐history analysis.

    • You are testing or debugging a model and want to keep the loading simple and time‑independent.

  • Do not use it when

    • The load needs to ramp up or down with time → use a Linear time series.

    • The load needs to follow a recorded signal or arbitrary function → use a Path / Time History time series.

    • The load is periodic → use a Trigonometric time series.

🔗 Relation to OpenSees

Alpaca4d’s constant time series is conceptually equivalent to the OpenSees Constant timeSeries:

timeSeries Constant $tag -factor $cFactor
timeSeries('Constant', tag, '-factor', factor=1.0)

where cFactor corresponds to the LoadFactor input in the Alpaca4d Grasshopper component.

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