Techno-economic Analysis (TEA) and Life Cycle Assessment (LCA) of a Low Temperature Closed-Cycle Grain Drying System
Bibliographic record
Abstract
The aim of this study was to understand the environmental and economic impact of the low temperature closed-cycle grain drying system by using techno-economic analysis (TEA) and life cycle assessment (LCA). For TEA, three scales including small (60 bu/batch), medium (600 bu/batch) and large (6000 bu/batch) were chosen for analysis the total annual drying cost and unit drying cost. For LCA, the greenhouse gasses (GHG) emission was the only environmental impact that considered in this study, since the electricity was the only energy source for this drying system. The TEA result shows that the drying costs for one bushel of corn were $0.62, $0.49, $0.46 for the small, medium and large scales of this drying system, respectively, and the drying cost could potentially be lower than grain elevators. The LCA results indicate that greenhouse gas emissions will increase along with the expansion of the drying system since the electricity comes from a local coal-based electricity plant, which potentially makes this drying system’s greenhouse gas emissions higher than other types of drying systems. Farmers can use this method to make decisions when handling their grain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".