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Sustainable design and control of a multi-sourced radiant heating system: Non-linear optimization under thermal comfort constraints

2025· article· en· W4406064605 on OpenAlexaffabout
Mohamed H. Anwer, Muhammed A. Hassan, Mahmoud A. Kassem, Mohamad T. Araji

Bibliographic record

VenueEnergy Conversion and Management · 2025
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsThermal comfortRadiant heatingThermalControl (management)Environmental scienceTemperature controlArchitectural engineeringEngineeringRadiant heatComputer scienceControl engineeringMeteorologyMaterials scienceThermodynamicsPhysics

Abstract

fetched live from OpenAlex

• A non-linear optimizer is developed for a tri-source radiant floor heating system. • Thermal comfort constraints are applied to the system with two forms of storage. • The system achieves lifecycle costs of 420.7 k CAD and an average PMV of −0.12. • The LCOH of the system (0.143 CAD/kWh) is below those of gas and coal systems. • Lifecycle emissions (330.2 tons) are 47% lower than those of the gas-only system. The demand for energy-efficient heating solutions in buildings is increasing consistently, necessitating tools to determine the system’s optimal design and operation, while ensuring occupant comfort. This study develops a novel thermal comfort-constrained capacity-operation optimization framework for a multi-source (solar collectors, a biomass boiler, and a gas boiler) radiant floor heating system, addressing the limitations of existing literature that typically focus on non-linear optimization of single-source systems. The system incorporates two forms of thermal storage, namely a water tank and a thermally active floor slab, which magnifies the system’s non-linearities. Hence, a non-linear interior-point optimization algorithm (Ipopt) is implemented in MATLAB® to minimize lifecycle costs (LCC). Unlike conventional approaches, the developed optimization framework has three novel features: i) it captures the dynamics and complex interactions between heat generation, storage, and consumption components, ii) it constrains temperature levels to ensure energy quality while simultaneously solving thermal comfort equations at each time step, accounting for the dynamic response of the building in subsequent steps, and iii) it balances various operational and sizing decision variables, capturing the bi-directional impacts of optimal system capacity and management. The results reveal that the tri-source system achieves an LCC of approximately 0.42 mil. CAD (Canadian dollars), equivalent to 0.3 mil. USD, and a competitive levelized cost of heat (LCOH) of 0.143 CAD kWh −1 (0.1 USD kWh −1 ), maintaining a stable operative temperature between 19 °C and 25 °C, with an average predictive mean vote (PMV) of −0.12, and total lifecycle CO 2 emissions of 330.15 tons. Comparative analyses with simpler design variations indicate that the gas-only system incurs the lowest LCC at 0.302 mil. CAD (0.21 mil. USD), yet its emissions are nearly twice those of the tri-source system. Among renewable options, the solar-biomass system offers the best balance of economic (LCC of 0.506 mil. CAD or 0.36 mil. USD), environmental (110.9 tons of CO 2 ), and comfort metrics (mean PMV of −0.12).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations4
Published2025
Admission routes2
Has abstractyes

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