Conceptual Exploration of Waste Heat Recovery Solutions : A Case Study of Low-temperature Waste Heat in Gasket Manufacturing in Guangde, China
Bibliographic record
Abstract
CO2 emissions have a significant impact on the climate, with a substantial portion originating from the industrial sector. To address this, companies like Alfa Laval aim to reduce their greenhouse gas (GHG) emissions across the entire value chain, particularly in Scope 3, which includes emissions from their suppliers. To contribute to Scope 3 emissions reduction, this thesis focuses on exploring the potential for waste heat recovery (WHR) within a gasket manufacturing process (GMP) operated by a supplier to Alfa Laval. A mixed-methods approach combining qualitative and quantitative studies was employed and conducted through a case study and a literature study. The case study contained an interview,site visits, and empirical data collection from a specific gasket manufacturing facility located in Guangde, China. The literature study provided a deeper understanding of WHR concepts, mechanisms, and relevant technologies. The methodological framework consisted of four phases: Exploration, Case study, Conceptualization and Verification. A mapping of the GMP was conducted to identify the processes where waste heat had the potential to be utilized. The identified waste heat streams were examined to understand their potential in terms of form, temperature, flow rate, cleanliness, and availability. To estimate the magnitude of generated waste heat within the GMP, a quantification of waste heat was conducted. Conceptual solutions for heat recovery were then developed, tailored to the specific characteristics of each waste heat stream. These conceptual solutions were verified by estimating the potential reductions in energy usage, CO2 emissions, and costs. Five subprocesses were identified with waste heat potential for WHR: thermal oil boilers, compressors, presses, ovens and local exhaust ventilation (LEV) system. All waste heat streams were gaseous and low-temperature, all streams below 100 °C except for boilers, which reached a maximum temperature of 118 °C, with varying levels of contamination and availability. Despite these challenges, waste heat streams from boilers and compressors showed the greatest potential for WHR. Conceptual solutions for WHR included a preheating chamber for sensible preheating, anabsorption chiller to provide cooling, and an Organic Rankine Cycle (ORC) system to generate electricity. Additionally, a heat encapsulation solution was proposed to mitigate waste heat dispersion, representing an initial step toward improving waste heat management and addressing the high temperature work environmnet within the facility. Among the solutions, the absorption chiller and ORC system showed the highest potential for savings, while simultaneously addressing the high cooling and electricity demands within the GMP. The case study revealed communication and knowledge gaps in energy efficiency measures (EEMs) between supply chain partners. It also highlighted the high natural gas usage in the facility, suggesting that focusing on EEMs to reduce natural gas could significantly lower Scope 3 emissions. Future efforts should include further exploration of EEMs and energy management practices, improved communication, and studies to verify the technical feasibility and cost-effectiveness of the proposed WHR solutions. Lastly, it is crucial to conduct further studies on the conceptual solutions to verify them comprehensively. These solutions remain theoretical at this stage, with no computational modeling, simulations, or experimental verification undertaken. Consequently, there is a lack of evidence regarding their technical feasibility and cost-effectiveness. It is essential to consider all aspects before implementing a conceptual solution to ensure it is viable in the long run, and sustainable from economic, environmental, and social perspectives.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".