Dataset Supporting: Dynamic Modeling of Poultry Litter Composting in High Mountain Climates using System Identification Techniques

General Description:
This dataset contains detailed measurements collected during two controlled experiments designed to study the dynamics of the composting process using the forced aeration technique. The dataset is divided into two main parts:

Experiment 1: Includes parameters such as temperatures (hot air and compost pile), relative humidity, and air and heat inputs.
Experiment 2: Complements the first experiment with oxygen levels in addition to the previously mentioned variables.
Both datasets are organized in a chronological format, with records that allow the analysis of trends and correlations among the studied variables.

Purpose:
The primary objective of this dataset is to facilitate the study of composting dynamics in high mountain environments using the forced aeration technique. It can be used for:

Bioprocess modeling.
Studies on energy optimization in biological and chemical processes.
Research in environmental biology, process engineering, and clean technologies.
Dataset Features:
Total Size:
Experiment 1: 4302 records and 8 variables.
Experiment 2: 3076 records and 9 variables.
Temporal Coverage: Records are organized by hour and minute over several days of experimentation.
Key Variables:
Hour and minute of the record.
Heater and compost pile temperatures.
Relative humidity.
Air and heat inputs.
Oxygen levels (in Experiment 2).
Days elapsed since the start of the experiment.
Available Formats:
The dataset is available in Excel format (.xlsx), with each experiment documented on separate sheets.

Access and Use:
Restrictions: Commercial use of the dataset requires prior authorization.
Potential Applications:
This resource is valuable for researchers in fields such as:

Environmental engineering and bioprocesses.
Design and optimization of thermal and environmental control systems.