Effects of Circumferential and Interaction Angles of Hydrogen Jets and Diesel Sprays on Combustion Characteristics in a Hydrogen–Diesel Dual-Fuel CI Engine

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. The recommendation for φ=0°+θ=7.5° as a power-optimized configuration is logical. However, the trade-off analysis (90% power retention at φ=15°) needs clarification: Is this based on absolute MEP or thermal efficiency? A normalized performance-emission Pareto front would enhance practicality.
2. The reported 29.6% NOx reduction at φ=15° aligns with Zeldovich-dominated thermal NOx pathways. However, the absence of N2O or prompt NO contributions (plausible under hydrogen-rich conditions) should be discussed.
3. The grid independence study and experimental validation for baseline diesel combustion are adequate. However, the absence of validation data for hydrogen-diesel dual-fuel cases (e.g., in-cylinder pressure/HRR under HES=40%) weakens confidence in simulated results.
4. The RNG k-ε model is appropriate for engine-scale simulations, but the lack of Large Eddy Simulation (LES) or hybrid RANS-LES comparisons (common in dual-fuel studies) limits insight into cycle-to-cycle variability.
5. Figure 6: Species distribution colormaps lack scale consistency (e.g., H2 mass fractions vary across cases). Normalized scales or Δ metrics would improve comparability.
6. Figure 7: Radar charts (ψ_flame, UI_T) are visually cluttered. Subplots or tabulated correlation coefficients would better convey parameter relationships.
7. Equation numbering errors (e.g., duplicate "(9)") and undefined variables (e.g., m_i in Eq. 12) hinder reproducibility.

 

 

Author Response

1. The recommendation for φ=0°+θ=7.5° as a power-optimized configuration is logical. However, the trade-off analysis (90% power retention at φ=15°) needs clarification: Is this based on absolute MEP or thermal efficiency? A normalized performance-emission Pareto front would enhance practicality.

Response:

Thank you for this insightful comment. Since the CFD simulations in this study focus on the period between intake valve closing (IVC) and exhaust valve opening (EVO), the primary emphasis is placed on in-cylinder mixing and combustion processes. As a result, engine performance indicators such as mean effective pressure (MEP) and thermal efficiency, which are typically available from full-cycle engine experiments or one-dimensional simulations, cannot be directly obtained.

The work output calculated in this study is based on the integration of in-cylinder average gas pressure over the closed-valve period. The objective is not to reproduce full-cycle performance metrics, but rather to provide guidance on the optimal φ and θ configurations from the perspective of high-pressure cycle work output.

In response to the reviewer’s suggestion, we have added an analysis of a normalized performance–emission trade-off to further support the discussion. This new content is highlighted in red and can be found on page 12 (Lines 411–427) and page 20 (Lines 555–563) of the revised manuscript.

2. The reported 29.6% NOx reduction at φ=15° aligns with Zeldovich-dominated thermal NOx pathways. However, the absence of N2O or prompt NO contributions (plausible under hydrogen-rich conditions) should be discussed.

Response:

Thank you for this insightful comment. In response to the observed 29.6% NOx reduction under the φ = 15° condition and its consistency with the thermal NOx formation pathway described by the Zel’dovich mechanism, we have added a preliminary explanation in the revised manuscript from the perspective of thermal NOx suppression. 1) HO₂-Mediated NO to NO₂ Conversion: Under hydrogen-enriched conditions, especially in regions where low-temperature combustion or incomplete combustion occurs, a significant amount of HO₂ can be generated via the reaction H + O₂ + M → HO₂ + M. This enhances the conversion of NO to NO₂ and reduces the overall thermal NOx formation [Li H., Liu S., Liew C., et al., An investigation on the mechanism of the increased NO₂ emissions from H₂-diesel dual fuel engine, International Journal of Hydrogen Energy, 2018, 43(7): 3837–3844].

N₂O Pathway (Intermediate Mechanism): 2) In hydrogen-rich environments—particularly in low-temperature or partially reacted combustion zones—N₂O can act as an important precursor to NO. Nitrogen and atomic oxygen can combine in the presence of a third body to form N₂O (N₂ + O + M → N₂O + M), which subsequently reacts with atomic oxygen to form NO. Additionally, reactions such as N₂ + HO₂ → N₂O + OH also contribute to this pathway [Lopatin O. P., Chemistry of the process of formation of nitrogen oxides in the combustion chamber of gas-diesel, Journal of Physics: Conference Series, 2020, 1515(5): 052004]. 3) Prompt NO Pathway: Prompt NO formation typically arises from the reaction of hydrocarbon radicals (e.g., CH) with molecular nitrogen near the flame front. While this pathway is more common in conventional hydrocarbon combustion, the addition of hydrogen in a diesel-hydrogen dual-fuel system enhances the concentration of reactive radicals (e.g., CH, OH) and increases flame front reactivity, which may indirectly accelerate the formation of prompt NO [Moussa S. G., Leithead A., Li S. M., et al., Emissions of hydrogen cyanide from on-road gasoline and diesel vehicles, Atmospheric Environment, 2016, 131: 185–195].

3. The grid independence study and experimental validation for baseline diesel combustion are adequate. However, the absence of validation data for hydrogen-diesel dual-fuel cases (e.g., in-cylinder pressure/HRR under HES=40%) weakens confidence in simulated results.

Response:

Thank you for this insightful comment. This study employs computational simulations to predict and investigate the combustion characteristics and emission performance of engines equipped with dual-layer orifice nozzle configurations. While our current work has not yet incorporated physical prototypes of this nozzle configuration (engine bench testing was therefore not conducted). Upon successful fabrication/acquisition of this nozzle configuration, we will conduct engine dynamometer testing and perform model validation against the current simulation framework.

4. The RNG k-ε model is appropriate for engine-scale simulations, but the lack of Large Eddy Simulation (LES) or hybrid RANS-LES comparisons (common in dual-fuel studies) limits insight into cycle-to-cycle variability.

Response:

Thank you for this insightful comment. While cycle-to-cycle variability represents a critical and scientifically meaningful research topic, the current study specifically focuses on investigating nozzle configuration effects on combustion characteristics and emission performance. In subsequent research phases, we plan to incorporate advanced turbulence modeling techniques such as Large Eddy Simulation (LES) to systematically analyze combustion process variations across operational cycles and quantify cyclic variability mechanisms.

5. Figure 6: Species distribution colormaps lack scale consistency (e.g., H2 mass fractions vary across cases). Normalized scales or Δ metrics would improve comparability.

Response:

Thank you for this insightful comment. To improve the comparability of species distribution results presented in Figure 7 and Figure 1, we have applied normalized scales and updated both figures accordingly. The normalization reference values for C₆H₁₇, H₂, NOₓ, and soot are based on their respective maximum mass fractions during the combustion process, which are 0.459, 0.0378, 0.000163, and 0.00119, respectively. The explanation of the normalization approach has been incorporated into the manuscript on Lines 441 to 445.

6. Figure 7: Radar charts (ψ_flame, UI_T) are visually cluttered. Subplots or tabulated correlation coefficients would better convey parameter relationships.

Response:

Thank you for this insightful comment. We have added Tables 5 and 8, which provide detailed quantitative data related to the mixing and combustion processes.

7. Equation numbering errors (e.g., duplicate "(9)") and undefined variables (e.g., m_i in Eq. 12) hinder reproducibility.

Response:

Thank you for this insightful comment. We have reviewed and revised the equation numbering, and ensured that all variables are properly defined. In particular, the definition of the variable mi has been added on page 4, lines 184–185.

Reviewer 2 Report

Comments and Suggestions for Authors

 

The manuscript sustainability-3600325 presents a 3D CFD investigation of H2–diesel dual-fuel combustion in a CI engine using CONVERGE, focusing on the effects of circumferential angle (φ) and interaction angle (θ) between H2 jets and diesel sprays. The injector system uses coaxial H2 and diesel injection, and the authors simulate different jet interaction configurations to evaluate their impact on the in-cylinder flow, the mixture formation, also ignition delay, combustion phasing, emissions (NOx and soot), and engine performance metrics. Their work identifies optimal geometric configurations for maximizing power output while reducing emissions. Below this reviewer listed some questions and comments for the authors:

1. The abstract should be a total of about 200 words maximum
   Ref. 38 is cited as previous experimental result for validation however, the list of refs only has 34. Please revise it all.
   Please add more details related to the validated against experimental data or previous studies using a similar hydrogen–diesel configuration. Did the authors conducted this experimental results in 38 or was from the literature?
   The authors used IMEP, ignition delay, and CA50 but it’s not always clear how combustion stability (e.g., COV, pressure rise rate) is affected.
   Also, related to the previous question, please specify which submodels were used for NOx and soot predictions in CONVERGE
   In my opinion, section 3.1 covers the meshing and model setup in detail, but the emissions formation models (NOx and soot submodels) are somewhat less described in the manuscript.
   In pg. 8 at l.277 the authors mention mesh refinement, but was any mesh sensitivity study performed or reported? Please comment.
   Why was only a single engine speed/load condition considered? Do authors expected similar optimal jet angles under other operating points?
   This reviewer kindly asks the authors to explain why certain φ or θ configurations reduce NOx but increase soot, or vice versa, from a combustion kinetics or mixing standpoint.
   Also, was the injection timing (for both diesel and H2) kept constant during all configurations?
   DId the authors analyze about the computational cost (runtime, mesh cell count) of each case they studied? If not in the scope of the paper, please comment.
   Section 4, of conclusion, reiterates findings but it should also present some numerical highlights like including 1–2 quantified outcomes (e.g. configuration XX reduced NOx by Y% and soot by Z%... please consider.

 

Author Response

1. The abstract should be a total of about 200 words maximum. Ref. 38 is cited as previous experimental result for validation however, the list of refs only has 34. Please revise it all.

Response:

Thank you for this insightful comment. We have removed the previously excessive background content from the abstract and have thoroughly reviewed and updated the reference numbering across the entire manuscript.

2. Please add more details related to the validated against experimental data or previous studies using a similar hydrogen–diesel configuration. Did the authors conducted this experimental results in 38 or was from the literature?

Response:

Thank you for this insightful comment. As noted, reference [33] (previously [38] in the original manuscript) is not from our research group. To clarify this, we have added a description of the study background and experimental conditions on page 6, lines 254–258. All combustion system parameters used in the current simulation study are aligned with those of the referenced engine.

3．The authors used IMEP, ignition delay, and CA50 but it’s not always clear how combustion stability (e.g., COV, pressure rise rate) is affected.

Response:

Thank you for this insightful comment. This study does not investigate cycle-to-cycle variations; instead, it focuses on analyzing the combustion and emission characteristics of a single engine cycle. In response to the reviewer’s comments, pressure rise rate curves have been added in Figures 4(b) and 9(b).

4． Also, related to the previous question, please specify which submodels were used for NOx and soot predictions in CONVERGE

Response:

Thank you for this insightful comment. The NOx prediction was conducted using the Thermal NOx model (Extended Zeldovich mechanism), while the Hiroyasu model was employed for soot formation. In response to the reviewer’s comments, descriptions of these models have been added on page 4, lines 168–172 and 176–177.

5. In pg. 8 at l.277 the authors mention mesh refinement, but was any mesh sensitivity study performed or reported? Please comment.

Response:

Thank you for this insightful comment. As suggested by the reviewer, we have added Figure 2(a), titled "The computed average in-cylinder pressure across varying mesh densities," to demonstrate the mesh independence analysis. The relevant explanation has been incorporated into the paragraph preceding Figure 2.

6. Why was only a single engine speed/load condition considered? Do authors expected similar optimal jet angles under other operating points?

Response:

Thank you for this insightful comment. We acknowledge the limitation of investigating only a single operating condition in this study. The primary objective at this stage is to explore the influence of the interfering dual-layer spray configuration. Future work will systematically examine injection angle optimization strategies under a range of operating conditions.

7. This reviewer kindly asks the authors to explain why certain φ or θ configurations reduce NOx but increase soot, or vice versa, from a combustion kinetics or mixing standpoint.

Response:

Thank you for this insightful comment. We agree that the observed trade-off between NOx and soot emissions under specific φ/θ combinations warrants further discussion from both combustion kinetics and fuel-air mixing perspectives. We have now included an expanded explanation in the revised manuscript (see Page 18, Lines 512–530). The key mechanisms are summarized below: 1) Combustion Temperature & Equivalence Ratio Distribution: The interaction angular offset between the hydrogen and diesel sprays (with moderate θ interference) results in relatively stronger local interactions between the high-reactivity hydrogen jet and the diesel-rich zones. This promotes earlier ignition and faster heat release. The locally rich combustion zones and enhanced heat release tend to raise the peak flame temperature moderately, yet in some regions, increased mixing with excess hydrogen leads to a locally lower oxygen concentration and leaner environment, suppressing the NO formation pathway. 2) Soot Formation Enhancement due to Quenching & Overlap: The overlapping spray plumes at this φ/θ combination also lead to higher fuel residence times and partial quenching in the central impingement region. Diesel entrainment into cooler or partially reacted zones can promote the formation of soot precursors such as C₂H₂, especially under fuel-rich and low-O₂ conditions. Moreover, the hydrogen jet may locally elevate temperatures without sufficiently oxidizing soot precursors, leading to higher soot mass fraction [Wang Y, Gu M, Zhu Y, et al. A review of the effects of hydrogen, carbon dioxide, and water vapor addition on soot formation in hydrocarbon flames[J]. International Journal of Hydrogen Energy, 2021, 46(61): 31400-31427.]. 3) Trade-off Mechanism (NOx–Soot): The competing behavior observed — NOx reduction and soot increase — aligns with the classic trade-off in dual-fuel systems where richer mixtures or delayed oxidation suppress NOx but hinder soot oxidation.

8．Also, was the injection timing (for both diesel and H2) kept constant during all configurations?

Response:

Thank you for this insightful comment. The injection timings for both diesel and hydrogen were fixed across all simulation cases. A corresponding clarification has been added on page 7, line 277-278 of the manuscript.

9. DId the authors analyze about the computational cost (runtime, mesh cell count) of each case they studied? If not in the scope of the paper, please comment.

Response:

Thank you for this insightful comment. The computational simulations were conducted on a Dell PowerEdge R730 chassis configured with dual Intel Xeon E5-2682 v4 CPUs (2.5 GHz base frequency, 64 total threads), 128 GB DDR4 memory, and an NVIDIA GeForce RTX 3090 GPU (24 GB GDDR6X). Parallel computing utilized 52 threads, with the Case C simulation requiring 26 hours and 12 minutes to complete. A corresponding explanation has been added on page 8, lines 300 to 304 of the manuscript.

10. Section 4, of conclusion, reiterates findings but it should also present some numerical highlights like including 1–2 quantified outcomes (e.g. configuration XX reduced NOx by Y% and soot by Z%... please consider.

Response:

Thank you for this insightful comment. The conclusions have been revised according to the reviewer’s comments.