MétaCan
Menu
Back to cohort
Record W4415020465 · doi:10.63385/sriic.v1.i1.294

<b>Infrastructure-Integrated Photovoltaic-Thermal (IIPV/T) Systems for Anti-Icing Applications in Highway Bridges: A Sustainable Approach </b>

2025· article· en· W4415020465 on OpenAlexaffabout
Masoud Valinejadshoubi, Ashutosh Bagchi, Andreas Athienitis

Bibliographic record

VenueStandards-related Regional Innovation and International Cooperation · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsConcordia University
Fundersnot available
KeywordsPayback periodBridge (graph theory)Economic analysisWind powerElectric power systemHeating systemRenewable energy

Abstract

fetched live from OpenAlex

This paper investigates the potential of a novel, infrastructure-integrated photovoltaic/thermal (IIPV/T) system for winter road maintenance, using the Samuel De Champlain Bridge in Montreal as a case study. Vertically mounted bifacial PVT panels are integrated into the bridge’s side barriers, serving a dual role as wind protection structures and clean energy generators. The captured solar energy is used in real time and stored seasonally to power a hydronic heating system (HHP) for anti-icing the bridge deck.The system is modeled using NREL’s System Advisor Model (SAM) with Typical Meteorological Year (TMY) data for Montreal. Simulations estimate that approximately 45% of winter heat demand can be met directly from IIPV/T generation, while 20% is supplied via seasonal thermal storage, and the remaining 35% is surplus. A comparative energy analysis between the Champlain Bridge and an existing Swedish system is presented. Economic analysis indicates a payback period of 2.1–2.5 years, with additional benefits from grid-connected surplus electricity.This study demonstrates the technical and economic feasibility of using IIPV/T systems for sustainable anti-icing of large-scale infrastructure. Limitations such as structural load effects and detailed pipe heat losses are noted and recommended for future work.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.249
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueStandards-related Regional Innovation and International CooperationSame topicSmart Materials for ConstructionFrench-language works237,207