This study investigates the impact of hydrogen supplementation on the performance, efficiency, and emissions of a spark-ignition internal combustion engine, with a specific focus on knock phenomena. A Nissan HR16DE engine was modified to operate in a dual-fuel mode using gasoline (E95) and high-purity hydrogen. Hydrogen was injected via secondary manifold injectors and managed through a reprogrammable MoTeC ECU, allowing precise control of ignition timing and fuel delivery. Experiments were conducted across various engine speeds and loads, with hydrogen mass fractions ranging from 0% to 30%. Results showed that increasing hydrogen content enhanced combustion intensity, thermal efficiency, and stability. Brake specific fuel consumption decreased by up to 43.4%, while brake thermal efficiency improved by 2–3%. CO, HC, and CO₂ emissions were significantly reduced. However, NO_x emissions increased with higher hydrogen concentrations due to elevated combustion temperatures. Knock tendency was effectively mitigated by retarding ignition timing, ensuring peak in-cylinder pressure occurred at 14–15° CAD aTDC. These findings demonstrate the potential of hydrogen supplementation to reduce fossil fuel use and greenhouse gas emissions in spark ignition engines, while highlighting the importance of precise combustion control to address challenges such as knock and NO_x formation.

This work addresses challenges related to camera 3D localization while reconstructing a 3D model of an ear. This work explores the potential solution of using a cap, specifically designed not to obstruct the ear, and its efficiency in enhancing the camera localization for structure-from-motion (SfM)-based object reconstruction. The proposed solution is described, and an elaboration of the experimental scenarios used to investigate the background textures is provided; data collection and software tools used in the research are reported. The results show that the proposed method is effective, and using the cap with texture leads to a reduction in the camera localization error. Errors in the 3D location reconstruction of the camera were calculated by comparing cameras localized within typical ear reconstruction situations to those of higher-accuracy reconstructions. The findings also show that caps with sparse dot patterns and a regular knitted patterned winter hat are the preferred patterns. The study provides a contribution to the field of 3D modeling, particularly in the context of creating 3D models of the human ear, and offers a step towards more accurate, reliable, and feasible 3D ear modeling and reconstruction.

Photogrammetry depends critically on the quality of the images used to reconstruct accurate and detailed 3D models. Selection of high-quality images not only improves the accuracy and resolution of the resulting 3D models, but also contributes to the efficiency of the photogrammetric process by reducing data redundancy and computational demands. This study presents a novel approach to image quality evaluation tailored for photogrammetric applications that uses the key point descriptors typically encountered in image matching. Using a LightGBM ranker model, this research evaluates the effectiveness of key point descriptors such as SIFT, SURF, BRISK, ORB, KAZE, FREAK, and SuperPoint in predicting image quality. These descriptors are evaluated for their ability to indicate image quality based on the image patterns they capture. Experiments conducted on various publicly available image datasets show that descriptor-based methods outperform traditional no-reference image quality metrics such as BRISQUE, NIQE, PIQE, and BIQAA and a simple sharpness-based image quality evaluation method. The experimental results highlight the potential of using key-point-descriptor-based image quality evaluation methods to improve the photogrammetric workflow by selecting high-quality images for 3D modeling.

The utilization of “green” hydrogen in transportation areas gives rise to production- and supply infrastructure-related challenges; therefore, its wider application in automotive transport would lead to higher demand with cost reduction and a faster expansion of the hydrogen refuelling network. This study presents energy and environmental performance indicators analyses of a Nissan Qashqai J10 engine during the Worldwide Harmonised Light Vehicles Test Cycle (WLTC), replacing conventional fossil gasoline with dual-fuel (D-F) gasoline and hydrogen. Numerical modelling was conducted using AVL Cruise™ (Version R2022.2) software, utilizing the torque, fuel consumption, and environmental performance data of the HR16DE engine obtained through experimental testing across a wide range of loads and speeds on an engine test bench. The experimental investigation was carried out in two stages: using pure gasoline (G100); injecting a hydrogen additive into the intake air, constituting 5% of the gasoline mass (G95H5). Following similar stages, numerical modelling was conducted using the vehicle’s technical specifications to calculate engine load and speed throughout the WLTC range. Instant fuel consumption and pollutant emissions (CO, CH, NO_x) were determined for various driving modes using experimental data maps. CO₂ emissions were calculated considering fuel composition and consumption. By integrating the instant values, the total and specific fuel consumption and emissions were calculated. As a result, this study identified the effect of a 5% hydrogen additive in improving engine energy efficiency, reducing incomplete combustion products and lowering greenhouse gas (CO₂) emissions under various driving modes. Finally, the results were compared with the requirements of EU standards.

This study investigates the effect of hydrogen injection pressure on combustion, energy, and emission characteristics of a spark-ignition engine under stoichiometric operating conditions. Experiments were performed on a four-cylinder Nissan HR16DE engine at 2500 rpm and 0.48 MPa brake mean effective pressure using gasoline and hydrogen-enriched blends containing 10%, 20%, and 30% hydrogen by mass. Hydrogen was injected into the intake manifold at pressures of 1.2, 1.4, 1.6, and 1.9 bar, while spark timing was adjusted to maintain peak in-cylinder pressure at 14–15 CAD after top dead center. Results showed that hydrogen mass fraction had a much stronger influence on engine performance than injection pressure. Increasing hydrogen content intensified combustion, shortened ignition delay, increased heat release rate and in-cylinder temperature, and reduced brake-specific fuel consumption by up to 36% compared with pure gasoline. Hydrogen enrichment also reduced HC and CO₂ emissions, but increased NO_x emissions. Effect of injection pressure was secondary and depended on hydrogen concentration. Under the investigated conditions, the lowest tested pressure, 1.2 bar, was generally the most favorable, especially at lower hydrogen fractions. Overall, hydrogen injection pressure acted mainly as a mixture formation control parameter, while hydrogen mass fraction remained the dominant factor determining engine behavior.