Sectional Grain Drying Control With Modeled Airflow Delivery
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Solution Overview
Problem
Existing grain-drying systems in commercial settings face inefficiencies and quality issues due to uneven drying across sections of stored crops, leading to damage from inconsistent moisture and temperature conditions, with no existing systems addressing grain conditions on a section-by-section basis or utilizing advanced analytical models with machine learning and AI for real-time adjustments.
Innovation Solution
A post-harvest crop management platform that uses sensors and machine learning to analyze crop conditions within containers, models fluid flow patterns, and actuates multi-stack assemblies to achieve desired crop characteristics on a section-by-section basis, applying ambient air, heat, or other fluids for efficient drying and storage management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If ambient air is pushed from the bottom plenum of the container, then the grain-drying system can dry the stored crop, but the drying is uneven across sections and creates inconsistent moisture and temperature conditions
Solution Approach 1:
The container is divided into multiple sections with different packing densities (central high-density sections and perimeter low-density sections). The drying system applies different fluid delivery strategies to each section type, with higher fluid delivery to central sections and lower fluid delivery to perimeter sections, achieving uniform drying across heterogeneous sections
Solution Approach 2:
The system delivers fluid at different rates to different sections based on their specific characteristics. Central sections receive higher fluid delivery rates due to higher packing density, while perimeter sections receive lower rates. This localized adjustment of fluid delivery quality resolves the contradiction between overall drying efficiency and local moisture uniformity
2Productivity
If heat is applied from the bottom plenum area, then the grain-drying system can dry the stored crop, but heat damage and over-drying occur at the bottom near the heat source
Solution Approach 1:
The system pre-cools ambient air before it enters the plenum and uses this pre-cooled air as the drying fluid. This preliminary cooling action prevents the air from becoming excessively hot near the plenum, thereby preventing heat damage and over-drying at the bottom sections while still maintaining effective drying rates
Solution Approach 2:
The system changes the temperature parameter of the drying fluid by pre-cooling the ambient air before it enters the plenum. This parameter adjustment ensures that the fluid temperature remains suitable for drying without causing heat damage, resolving the contradiction between drying rate and heat damage prevention
3Productivity
If air delivery is concentrated at the bottom plenum, then the system can drive fluid flow through the crop, but air penetration ability decreases for sections further from the source
Solution Approach 1:
The system segments the fluid delivery approach by using multiple distributed outlets throughout the container rather than a single bottom plenum source. This segmentation allows air to be delivered more uniformly across different sections, maintaining penetration ability in both near and far sections while still driving overall fluid flow through the crop
Solution Approach 2:
The system transitions from a one-dimensional bottom-up fluid delivery approach to a multi-dimensional distributed delivery approach with outlets positioned at various locations and heights. This dimensional change enables air to reach distant sections more effectively while maintaining overall flow drive, resolving the contradiction between flow drive and penetration uniformity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach ensures consistent and efficient drying, reducing losses by maintaining crop quality through precise control of moisture and temperature, preventing spoilage and stress cracking, and optimizing storage conditions within containers.
Implementation Method 1
sampling conditions of the multiple sections of the crop within the container
Implementation Method 2
modeling a delivery of a fluid flow pattern to the crop within each section of the container
Implementation Method 3
delivering the fluid flow pattern to the crop in the multiple sections of the container
Implementation Method 4
heated on occasion to dry the stored crop
Implementation Method 5
applying ambient air, heat, or other fluids for efficient drying
Implementation Method 6
drying is occurring, and on a section-by-section basis
Implementation Method 7
actuate the multi-stack assembly to deliver the fluid flow pattern
Data Source
AI summary
A post-harvest crop management platform is provided for regulating conditions of an agricultural crop being dried and/or stored. The platform utilizes data collected from sensors positioned proximate to, or embedded within, an agricultural crop, and analyzes selected crop characteristics affecting the stored crop in multiple sections thereof. The platform identifies parameters relative to achieving a desired crop characteristic level in the agricultural crop, generates a profile of the selected crop characteristic across the multiple sections of the stored crop, and models an application of a fluid flow pattern to achieve the desired crop characteristic level in each section. The crop storage monitoring and management platform also actuates a multi-stack assembly, configured within the stored crop, to automatically apply the fluid flow pattern in one or more cycles that are adjustable to changing conditions within the stored crop in real time. The crop storage monitoring and management platform further integrates with, and connects to and communicates with, other systems within an autonomous field activity ecosystem.