Laser surface quenching (LSQ) is gaining popularity in engineering applications, but it generates non-negligible carbon emissions. However, existing research mostly focuses on quenching performance. Little attention has been paid to carbon emissions of LSQ process. In this study, we build an experimental platform including fiber laser system (IPG YLR-4 kW) and carbon emission measurement system for a synergistic study of environmental impacts and processing quality in LSQ. Based on the L (4) Taguchi matrix, LSQ experiments are conducted on the shield disc cutter. The influences of laser power, scanning speed, and defocusing distance on carbon emissions and hardening effects are studied. The carbon emission efficiency of LSQ is analyzed and compared with the competitive technology. The geometry and the maximum average hardness (MAH) of LSQ high-hardness zone (HHZ) are studied. A comprehensive evaluation considering carbon emissions and hardening effects is conducted. The results show that the maximum value of carbon emission is 1.4 times the minimum value. The maximum depth and width of HHZ are respectively 0.507 and 3.254 mm. The maximum MAH is 3.5 times the hardness of base metal. Compared to the average experimental responses, the experiment with the highest comprehensive score respectively increases by 26.4%, 17.1%, and 30.3% in depth, width, and MAH of HHZ, and reduces by 5.8% in carbon emissions.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s11356-023-26981-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Graphitic Carbon Nitride-Supported Layered Double Hydroxides (GCN@FeMg-LDH) for Efficient Water Splitting and Energy Harvesting.
ACS Appl Mater Interfaces
January 2025
Department of Environmental Engineering, Kwangwoon University, Seoul 01897, Republic of Korea.
The advancement of highly efficient and cost-effective electrocatalysts for electrochemical water splitting, along with the development of triboelectric nanogenerators (TENGs), is crucial for sustainable energy generation and harvesting. In this study, a novel hybrid composite by integrating graphitic carbon nitride (GCN) with an earth-abundant FeMg-layered double hydroxide (LDH) (GCN@FeMg-LDH) was synthesized by the hydrothermal approach. Under controlled conditions, with optimized concentrations of metal ions and GCN, the fabricated electrode, GCN@FeMg-LDH demonstrated remarkably low overpotentials of 0.
View Article and Find Full Text PDFReactivity of Wet scCO toward Reservoir and Caprock Formations under Elevated Pressure and Temperature Conditions: Implications for CCS and CO-Based Geothermal Energy Extraction.
Energy Fuels
January 2025
Geothermal Energy and Geofluids Group, Institute of Geophysics, Department of Earth and Planetary Sciences, ETH Zurich, Zurich 8092, Switzerland.
Carbon capture and storage (CCS) and CO-based geothermal energy are promising technologies for reducing CO emissions and mitigating climate change. Safe implementation of these technologies requires an understanding of how CO interacts with fluids and rocks at depth, particularly under elevated pressure and temperature. While CO-bearing aqueous solutions in geological reservoirs have been extensively studied, the chemical behavior of water-bearing supercritical CO remains largely overlooked by academics and practitioners alike.
View Article and Find Full Text PDFPrediction of energy consumption in four sectors using support vector regression optimized with genetic algorithm.
Heliyon
January 2025
Department of Electrical and Electronic Engineering, Bangladesh University of Business and Technology, Dhaka-1216, Bangladesh.
Effectively managing and optimizing energy resources to accommodate population growth while minimizing carbon emissions has become increasingly intricate. A proficient approach to this dilemma is accurately predicting energy usage and emissions across diverse sectors. This paper unveils a genetic algorithm (GA)-optimized support vector regression (SVR) model designed to (i) predict electricity generation, (ii) predict energy consumption in four primary sectors-residential, industrial, commercial, and agricultural, and (iii) estimate sector-specific carbon emissions.
View Article and Find Full Text PDFEmpowering climate resilience: A people-centered exploration of Thailand's greenhouse gas emissions trading and sustainable environmental development through climate risk management in community forests.
Heliyon
January 2025
College of Politics and Governance, Mahasarakham University, Kantharawichai District, Mahasarakham, 44150, Thailand.
The imperative of addressing climate change has accentuated the pivotal role of reducing greenhouse gas emissions and harnessing the potential of community forests. This study meticulously explores the governance structures and mechanisms underpinning greenhouse gas emissions trading within community forests, aimed at curbing carbon emissions, and enhancing adaptive capacities in Thailand. With a central focus on cultivating enduring climate resilience, this research delves into the interplay of community perspectives with greenhouse gas emissions trading mechanisms, while also dissecting the genesis of sustainable strategies in the Thai context.
View Article and Find Full Text PDFEnvironmental and Economic Assessment of Wind Turbine Blade Recycling Approaches.
ACS Sustain Resour Manag
January 2025
Sandia National Laboratories, Albuquerque, New Mexico 87123, United States.
Wind energy offers a low emission source of energy while also being among the cheapest forms of electricity generation in the United States. While most materials in a wind turbine can be recycled at the end of their life, large composite blades are often treated as waste, leading to potential strains on regional landfills, a loss of durable materials, and forfeiture of embodied energy. Numerous approaches exist for recycling composite wind blades at various levels of technological and commercial maturity.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!