MétaCan
Menu
Back to cohort
Record W2256464641 · doi:10.2172/1073770

Super Boiler: Packed Media/Transport Membrane Boiler Development and Demonstration

2013· report· en· W2256464641 on OpenAlexaboutno aff
William E. Liss, David Cygan

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsBoiler (water heating)Flue gasCombustionWaste managementCombustorEngineeringHeat transferProcess engineeringNuclear engineeringEnvironmental scienceChemistry

Abstract

fetched live from OpenAlex

Gas Technology Institute (GTI) and Cleaver-Brooks developed a new gas-fired steam generation system the Super Boiler for increased energy efficiency, reduced equipment size, and reduced emissions. The system consists of a firetube boiler with a unique staged furnace design, a two-stage burner system with engineered internal recirculation and inter-stage cooling integral to the boiler, unique convective pass design with extended internal surfaces for enhanced heat transfer, and a novel integrated heat recovery system to extract maximum energy from the flue gas. With these combined innovations, the Super Boiler technical goals were set at 94% HHV fuel efficiency, operation on natural gas with <5 ppmv NOx (referenced to 3%O2), and 50% smaller than conventional boilers of similar steam output. To demonstrate these technical goals, the project culminated in the industrial demonstration of this new high-efficiency technology on a 300 HP boiler at Clement Pappas, a juice bottler located in Ontario, California. The Super Boiler combustion system is based on two stage combustion which combines air staging, internal flue gas recirculation, inter-stage cooling, and unique fuel-air mixing technology to achieve low emissions rather than external flue gas recirculation which is most commonly used today. The two-stage combustion provides lower emissions because of the integrated design of the boiler and combustion system which permit precise control of peak flame temperatures in both primary and secondary stages of combustion. To reduce equipment size, the Super Boiler's dual furnace design increases radiant heat transfer to the furnace walls, allowing shorter overall furnace length, and also employs convective tubes with extended surfaces that increase heat transfer by up to 18-fold compared to conventional bare tubes. In this way, a two-pass boiler can achieve the same efficiency as a traditional three or four-pass firetube boiler design. The Super Boiler is consequently up to 50% smaller in footprint, has a smaller diameter, and is up to 50% lower in weight, resulting in very compact design with reduced material cost and labor costs, while requiring less boiler room floor space. For enhanced energy efficiency, the heat recovery system uses a transport membrane condenser (TMC), a humidifying air heater (HAH), and a split-stage economizer to extract maximum energy from the flue gas. The TMC is a new innovation that pulls a major portion of water vapor produced by the combustion process from the flue gases along with its sensible and latent heat. This results in nearly 100% transfer of heat to the boiler feed water. The HAH improves the effectiveness of the TMC, particularly in steam systems that do not have a large amount of cold makeup water. In addition, the HAH humidifies the combustion air to reduce NOx formation. The split-stage economizer preheats boiler feed water in the same way as a conventional economizer, but extracts more heat by working in tandem with the TMC and HAH to reduce flue gas temperature. These components are designed to work synergistically to achieve energy efficiencies of 92-94% which is 10-15% higher than today's typical firetube boilers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.206
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicThermochemical Biomass Conversion ProcessesFrench-language works237,207