nonidealized

Nonidealized describes models, analyses, or descriptions that do not rely on simplifying ideal conditions. It emphasizes realism by incorporating imperfections, constraints, and complexities that are present in actual systems. In contrast, idealized representations may assume frictionless contact, perfectly rigid bodies, linear responses, noiseless data, or infinite precision. The nonidealized approach is often pursued to improve predictive accuracy, applicability, and robustness, even though it typically increases mathematical or computational complexity.

In physics and engineering, nonidealization appears in real-gas and real-fluid models that account for interactions, as well as in electronics with components exhibiting voltage drops, tolerances, leakage, and parasitics. In optics, nonideal lenses produce aberrations; in mechanics, friction, backlash, stiffness variations, and temperature effects are included. In economics and social sciences, nonidealized analyses consider market frictions, bounded rationality, and heterogeneous agents. In data analysis, real-world data include noise, outliers, missing values, and nonstationarity, requiring robust methods and validation.

Methodological considerations often accompany nonidealized modeling, including empirical calibration, experimentation, parameter estimation, and uncertainty quantification. While it can enhance external validity and relevance to practice, it may reduce elegance and tractability, making results harder to interpret or reproduce. The choice between idealized and nonidealized representations depends on goals, data availability, and acceptable levels of risk or error.

See also: idealization; nonidealization in the philosophy of science.