Development of a Finite–element Stored Grain Ecosystem Model

Abstract

An axisymmetric finite-element model was developed that predicts the heat, mass, and momentum transfer that occurred in upright corrugated steel storage structures due to conduction, diffusion, and natural convection using realistic boundary conditions. Weather data that included hourly total solar radiation, wind speed, ambient temperature, and relative humidity were used to model the temperature, moisture content, dry matter loss, and maize weevil development during storage with no aeration, and with ambient and chilled aeration. Periods of aeration were simulated assuming a uniform airflow rate through the grain mass. Heat and mass balances were used to calculate the temperature and absolute humidity in the headspace and plenum based on solar radiation, wind speed, ambient conditions, air infiltration, convective heat and mass transfer from the grain surface, and permeable boundaries that allowed natural convection currents to cross grain surfaces. A heat balance was used to estimate the wall temperature. The type of weather data in terms of solar radiation and frequency of data appear to be important when predicting the grain temperature, moisture content, dry matter loss, and maize weevil development.

Where in the value chain are we losing the most food? The case of wheat in Jordan

“…Storage losses are best estimated using models such as the PHAST-FEM (Montross et al 2002), as they use biophysical relationships based on historical ambient and in-bin temperature, relative humidity (RH), pest activity and grain biology. Due to the lack of in-bin temperature and RH measurements in the Jordanian silos, an attempt was made to carry out physical measurements for storage losses using rudimentary methods.…”

Relationship of Shelled Corn Fungal Susceptibility to Carbon Dioxide Evolution and Kernel Attributes

“…Thus, corn with high fungal susceptibility is at greater risk for fungal growth when exposed to such conditions. For example, when corn is kept in storage for extended periods of time (10 months to several years), moisture condensation caused by unfavorable headspace conditions (Montross et al 2002) and increases in grain temperature from factors such as solar radiation or high ambient temperatures can create conditions conducive to fungal growth. Also, when U.S. corn is exported overseas, it may pass through subtropical and tropical climates.…”

Economics of Integrated Insect Management in Stored Corn

“…Throne (1994) estimated regression equations for the duration of development, fecundity, and survival rates for maize weevil. Using ThroneÕs equations, researchers have built computer simulation models for maize weevil (Maier et al 1996;Arthur et al , 2001Meikle et al 1999;Montross et al 2002). Based on a time-varying distributed delay model (Mantesh 1976) for tracking insects through all developmental stages and for simulating variation in developmental time, Montross et al (2002) developed a complex and highly data-intensive model that they called postharvest aeration and storage simulation toolÐÞnite element model (PHAST-FEM).…”

“…The PHAST-FEM model developed by Montross et al (2002) was used to generate the data that is needed to estimate the state relationships. The PHAST-FEM model used weather data which are taken from 1961 to 2005 observations of ambient temperature, ambient relative humidity, wind speed, and solar radiation for the Evansville area from the National Solar Radiation Data Base.…”