RQ1
Map the optimization methods used for corrugated board and their economic and environmental contribution.
Back to ProjectHub
Audit · not reproduced
Review · not a simulation
Design & optimization
Corrugated board design optimization
Explore the recorded optimization results one case at a time. Compare the final summary with its iteration history, or watch the optimization sequence.
72 cases14,720 iteration framesOriginal research outputs
Published visual outputs
Data & files
This catalog indexes the published summaries, videos and optimizer iteration images. It is an asset index; it does not reconstruct numerical values from plots.
Verified 3 October 2026 · frame indices follow the original filenames; figures retain their original iteration labels. No physical time unit.
| Study | Case | Frame index | Summary | Video |
|---|---|---|---|---|
| Part A | C001 | 0–199 (200 frames) | Image | Video |
| Part A | C002 | 0–199 (200 frames) | Image | Video |
| Part A | C003 | 0–199 (200 frames) | Image | Video |
| Part A | C004 | 0–199 (200 frames) | Image | Video |
| Part A | C005 | 0–199 (200 frames) | Image | Video |
| Part A | C006 | 0–199 (200 frames) | Image | Video |
| Part A | C007 | 0–199 (200 frames) | Image | Video |
| Part A | C008 | 0–199 (200 frames) | Image | Video |
| Part A | C009 | 0–199 (200 frames) | Image | Video |
| Part A | C010 | 0–199 (200 frames) | Image | Video |
| Part A | C011 | 0–199 (200 frames) | Image | Video |
| Part A | C012 | 0–199 (200 frames) | Image | Video |
| Part A | C013 | 0–199 (200 frames) | Image | Video |
| Part A | C014 | 0–199 (200 frames) | Image | Video |
| Part A | C015 | 0–199 (200 frames) | Image | Video |
| Part A | C016 | 0–199 (200 frames) | Image | Video |
| Part A | C017 | 0–199 (200 frames) | Image | Video |
| Part A | C018 | 0–199 (200 frames) | Image | Video |
| Part A | C019 | 0–199 (200 frames) | Image | Video |
| Part A | C020 | 0–199 (200 frames) | Image | Video |
| Part A | C021 | 0–199 (200 frames) | Image | Video |
| Part A | C022 | 0–199 (200 frames) | Image | Video |
| Part A | C023 | 0–199 (200 frames) | Image | Video |
| Part A | C024 | 0–79 (80 frames) | Image | Video |
| Part A | C025 | 0–199 (200 frames) | Image | Video |
| Part A | C026 | 0–399 (400 frames) | Image | Video |
| Part A | C027 | 0–79 (80 frames) | Image | Video |
| Part A | C028 | 0–199 (200 frames) | Image | Video |
| Part A | C029 | 0–399 (400 frames) | Image | Video |
| Part A | C030 | 0–199 (200 frames) | Image | Video |
| Part A | C031 | 0–199 (200 frames) | Image | Video |
| Part A | C032 | 0–199 (200 frames) | Image | Video |
| Part A | C033 | 0–199 (200 frames) | Image | Video |
| Part B | C001 | 0–199 (200 frames) | Image | Video |
| Part B | C002 | 0–199 (200 frames) | Image | Video |
| Part B | C003 | 0–199 (200 frames) | Image | Video |
| Part B | C004 | 0–199 (200 frames) | Image | Video |
| Part B | C005 | 0–199 (200 frames) | Image | Video |
| Part B | C006 | 0–199 (200 frames) | Image | Video |
| Part B | C007 | 0–199 (200 frames) | Image | Video |
| Part B | C008 | 0–199 (200 frames) | Image | Video |
| Part B | C009 | 0–199 (200 frames) | Image | Video |
| Part B | C010 | 0–199 (200 frames) | Image | Video |
| Part B | C011 | 0–199 (200 frames) | Image | Video |
| Part B | C012 | 0–199 (200 frames) | Image | Video |
| Part B | C013 | 0–199 (200 frames) | Image | Video |
| Part B | C014 | 0–199 (200 frames) | Image | Video |
| Part B | C015 | 0–199 (200 frames) | Image | Video |
| Part B | C016 | 0–199 (200 frames) | Image | Video |
| Part B | C017 | 0–199 (200 frames) | Image | Video |
| Part B | C018 | 0–199 (200 frames) | Image | Video |
| Part B | C019 | 0–199 (200 frames) | Image | Video |
| Part B | C020 | 0–199 (200 frames) | Image | Video |
| Part B | C021 | 0–199 (200 frames) | Image | Video |
| Part B | C022 | 0–199 (200 frames) | Image | Video |
| Part B | C023 | 0–199 (200 frames) | Image | Video |
| Part B | C024 | 0–199 (200 frames) | Image | Video |
| Part B | C025 | 0–199 (200 frames) | Image | Video |
| Part B | C026 | 0–199 (200 frames) | Image | Video |
| Part B | C027 | 0–199 (200 frames) | Image | Video |
| Part B | C028 | 0–199 (200 frames) | Image | Video |
| Part B | C029 | 0–199 (200 frames) | Image | Video |
| Part B | C030 | 0–199 (200 frames) | Image | Video |
| Part B | C031 | 0–199 (200 frames) | Image | Video |
| Part B | C032 | 0–199 (200 frames) | Image | Video |
| Part B | C033 | 0–199 (200 frames) | Image | Video |
| Part B | C034 | 0–79 (80 frames) | Image | Video |
| Part B | C035 | 0–199 (200 frames) | Image | Video |
| Part B | C036 | 0–399 (400 frames) | Image | Video |
| Part B | C037 | 0–79 (80 frames) | Image | Video |
| Part B | C038 | 0–199 (200 frames) | Image | Video |
| Part B | C039 | 0–399 (400 frames) | Image | Video |
Paper evidence audit
Gaussian-process sampling for corrugated boards
This panel transcribes the published design domain, response definitions and evaluation budget. It is source evidence, not a replay: the recorded optimization images above are not a Gaussian-process acquisition trace.
- Evaluations
- 1000
- 200 LHS + 800 active
- Candidates / step
- 1000
- Reported candidate pool
- E_z,eff
- Effective through-thickness modulus
- Reported MSE: 5.24 kPa²
- t_eff
- Effective thickness
- Reported MSE: 1 mm²
| Variable | Symbol | Minimum | Maximum |
|---|---|---|---|
| Flute thickness | t | 0.005 m | 0.02 m |
| Flute amplitude | a | 0.001 m | 0.01 m |
| Flute wavelength | λ | 0.0001 m | 0.002 m |
Material constants and replay requirements
| E₁ | 1,709,000,000 Pa |
|---|---|
| E₂ | 918,000,000 Pa |
| E₃ | 8,995,000 Pa |
| G₁₂ | 485,000,000 Pa |
| ν₁₂ | 0.4 — |
| G₁₃ | 31,070,000 Pa |
| G₂₃ | 26,230,000 Pa |
| ν₁₃ | 0.001 — |
| ν₂₃ | 0.001 — |
Still missing for an exact replay
- The evaluated 1000-row design and response table
- Gaussian-process kernel and fitted hyperparameters
- Random seed and exact candidate archive
- Per-iteration acquisition values and selected candidates
Review evidence map
How the recorded work fits the wider field
The 2023 review organizes corrugated-board optimization across history, manufacturing, structural design, objectives and algorithms. This map connects those review lenses to evidence already exposed in ProjectHub; it is not a solver, dataset or reproduced paper result.
RQ2
Trace how those methods evolved and identify the drivers behind the change.
RQ3
Identify state-of-the-art limitations that point to future optimization trends.
Five review lenses
- Early stages of corrugated-board optimization
- Advances in board design and manufacturing
- Structural design optimization
- Optimization objectives
- Numerical optimization algorithms
| Project evidence | Class | Boundary |
|---|---|---|
| 72-case recorded explorer → | Recorded optimizer outputs | The source frames are not a dataset extracted from the review and do not prove coverage of every method it surveys. |
| Gaussian-process paper audit → | Single-paper parameter and budget audit | The audit is not an EHVI replay and the recorded frames are not a Gaussian-process trace. |
| Corrugated-board FEM → | Executed reduced model plus source-bounded FEM audits | Reduced calculation, paper evidence and solver outputs remain separate evidence classes. |
Findings and execution boundary
- The reviewed field shifted from trial-and-error and expert-led practice towards data-centred computational methods.
- Finite-element analysis, surrogate models and numerical algorithms broadened the available methods, without establishing one dominant approach.
- Multidisciplinary methods entered from adjacent engineering fields.
- The review identifies broader shape, topology, environmental and multi-objective treatment as areas needing further work.
Read the publisher record · CC BY 4.0 ↗Published 2023-11-03 · Ricardo Fitas, Heinz Joachim Schaffrath and Samuel Schabel