Design and Development of an Open-Source Virtual Reality Chemical Processing Plant
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is challenging to provide students studying in chemical engineering, biotechnology and other related fields with an opportunity to tour and interact with a full-scale chemical processing plant. To address this challenge, an open-sourced virtual reality (VR) chemical processing plant was designed and built to provide students with an experiential learning opportunity. The VR plant is modelled after an ampicillin processing facility complete with a piping and instrumentation diagram (P&ID). The initial student experience inside the VR plant is a tour of the plant, various plant features and unit operations. The tour enables students to freely tour the plant but also engages them in a “Quest” style experience where they need to search for specific areas and components within the plant. An EngPad was designed to provide learners with a help tool to assist their navigation and strengthen their understanding during the VR experience. Experiential learning theory was used to guide the design of the VR application and take students through the four learning modes of concrete experience, reflective observation, abstract conceptualization, and active experimentation. A focus group provided feedback on the design and user interaction of the VR experience. This paper will outline how design features and enhancements were selected based on their connection to experiential learning theory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it