Machine learning-based prediction of combustion behavior in HCCI engines using hydrogen-rich fuels

Impact of initial structure on O2 plasma surface engineering and electrocatalytic behavior of ZIF-67

Enhancing the engineering behaviour of residual Bringelly shale using alkali-activated treatment

Moisture- and temperature-induced changes in microstructure and stabilization products remain a concern, requiring further study to clarify their effects on the engineering behavior of stabilized soils. Thus, this study aims to evaluate the engineering response of stabilized high-plasticity clay to moisture- and temperature-driven environmental conditioning, using hydrated lime (L) and lime sludge (S) under four sequences: freezing-thawing (FT), wetting-drying (WD), freezing-thawing-wetting-drying (FTWD), and wetting-drying-freezing-thawing (WDFT). Expansive soils were treated with a total dosage of 8% of L and S mixtures (4L4S and 6L2S) and evaluated through UCS and repeated load triaxial tests, further supported by microstructural and mineralogical analyses. Both 4L4S- and 6L2S-treated specimens exhibited improved engineering performance compared to the untreated soil due to short-term strength gains and long-term pozzolanic reactions. Importantly, the addition of lime sludge, a calcite-rich material, did not hinder the stabilization process, as 4L4S specimens achieved UCS values comparable to those of specimens treated with 5% hydrated lime. Both the treated specimens retained their integrity throughout the environmental conditioning phases, whereas the untreated specimens collapsed during the early stages. Among these durability studies, FT caused the most severe deterioration, due to substantial soil swelling during freezing. In contrast, coupled durability conditions caused relatively less damage, due to limited ice lens formation post drying phase, resulting in better engineering properties. Microstructural and mineralogical analyses were performed, which revealed the formation of cementitious gels, binding soil particles and enhancing the structural stability and durability of the treated specimens. Also, key variations in the mineral content, and related microstructure of the stabilized soils through thermogravimetric analysis were observed after different environmental conditionings. This explains the influence of the mineral contents and microstructure of stabilized soils on the long-term performance. • The effectiveness of lime sludge as partial replacement to hydrated lime for stabilizing expansive clays is established. • Different impacts of the coupled and uncoupled environmental durability cycles are investigated. • Microstructural and mineralogical investigations revealed the influence of environmental stressors on the long-term performance. • Need for the appropriate choice of durability protocols is recommended.

Investigation the flow field and combustion behavior in a small-scaled methanol elliptical rotary engine: effects of ignition timing and engine speed

Band gap engineering and auxetic behavior in Cu-substituted ZnO: A first-principles analysis

• Ternary diesel–waste oil–higher alcohol blends were experimentally evaluated. • Octanol and butanol affected combustion stability and in-cylinder behavior. • DWO20 achieved higher thermal efficiency at low–medium engine loads. • DWB20 emitted more CO 2 due to the carbon-rich treated waste oil. • Alcohol blends lowered NO X via latent heat effects, except at 50% load. The transition from conventional fossil-based fuels to renewable alternatives holds great promise in advancing more sustainable transportation. This present experimental study investigates the effects of high-chain alcohol-based fuels, octanol and butanol, under conditions of treated waste engine oil and diesel fuels in a compression ignition (CI) engine on combustion, performance and emission parameters. Three fuel blends were examined at varying pedal positions (20–50%), with a 10% increment. The tested fuel blends were a pure diesel combustion (D100), a ternary blend of diesel-treated waste engine oil (TWEO)-butanol (60:20:20-DWB20), and a ternary blend of diesel-TWEO-octanol (60:20:20-DWO20). The waste engine oil was improved by acid-clay treatment, allowing it to be used in the fuel blend. Key findings revealed that incorporating butanol and octanol into the treated waste oil–diesel blends produced in-cylinder pressure and heat release rates comparable to those of pure diesel. Additionally, CO 2 emissions were lower for the octanol-containing blend at lower pedal positions, while the butanol-containing blend exhibited reduced HC and NO X emissions compared to pure diesel. The outcomes of this work are pertinent to the efforts of renewable alternative fuels in the pursuit of clean and effective combustion technologies for future powertrain systems.

This study investigated the functional group transformation of asphalt modified using Escherichia coli through mixing and coating methods as a biological self-healing approach for pavement materials. The experimental research was conducted under controlled laboratory conditions using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscope (SEM), and hydrophobicity analysis to evaluate chemical, morphological, and surface performance changes. The mixing method promoted dominant internal interactions within the asphalt matrix, indicated by increased O–H functional groups and homogeneous bacterial distribution. In contrast, the coating method generated stronger surface reactions characterized by higher C–O intensity, enhanced biomineralization activity, and localized CaCO3 formation on the asphalt surface. SEM observations revealed that the coating method formed denser biofilm structures, contributing to improved hydrophobicity and accelerated microcrack healing performance. Comparative analysis demonstrated that bacterial application mechanisms significantly influenced asphalt chemical evolution and engineering behavior. The findings indicate that biologically modified asphalt using Escherichia coli possesses considerable potential for sustainable, adaptive, and self-healing pavement systems through optimized bacterial treatment strategies.

Abstract The present study evaluates the combustion behavior, vibration response, performance and emission parameters of a diesel engine using with conventional diesel, a 20% Juliflora biodiesel blend (JUB20), and JUB20 supplemented with hydrogen at a constant flow rate of 8 lpm. Piston geometry was modified in an engine with SSVP and SSCVP and compared against the standard piston. Juliflora biodiesel (JUB20) was optimized using machine learning (Random Forest) technique by considering reaction temperature, methanol‐to‐oil ratio, reaction time, and catalyst concentration, and fuel properties were measured as per ASTM standards. Initially, engine tests were conducted with diesel and JUB20 fuel but we observed a lower BTE with biodiesel blended fuel then induction of hydrogen gas through inlet manifold was carried. Next, conventional piston was replaced with two altered pistons such as SSVP (Symmetrical Spline‐V piston) and SSCVP (Symmetrical Stepped Curved‐V piston) to conduct engine tests using JUB20 fuel with and without hydrogen gas. The highest BTE was recorded with JUB20 + HYD + SSCVP fuel that is. 9.82% compared to JUB20 fuel and lowest BSFC that is, 21.62% was obtained at peak load condition. Enhanced combustion efficiency was observed with hydrogen and a redesigned piston, attributed to the enhanced turbulence and homogeneity in the air–fuel mixture. Emission parameters such as CO, CO 2 , and HC were drastically reduced with hydrogen addition and piston modification. This combined technology enhanced combustion efficiency but showed a marginal rise in NOx emissions. Vibration tests were conducted to evaluate engine amplitude. Comparisons were made across all fuel samples.

Sensitivity analysis of diesel engine design parameters using zero-dimensional simulations

Engineering and environmental behavior performance of magnesium potassium phosphate cement binder solidification/stabilization Zn-Cu contaminated soils

Natural stone not only endures; it records cultural memory. Bakırköy Küfeki Stone, a Miocene biosparitic limestone, historically quarried near present-day Bakırköy where is a district in Istanbul, and as the relevant lithology is most commonly found within the boundaries of this district, the stone has been named accordingly underpinned the architectural fabric of Istanbul’s Historical Peninsula (UNESCO World Heritage Site), spanning the Roman and Ottoman eras (e.g. city walls, aqueducts, major churches and mosques). Rapid urbanization has removed access to the original quarries. As a result, recent restorations have often substituted lithologies that mimic color/texture but differ in provenance and engineering behavior, which may hasten decay and compromise authenticity. This study assesses Bakırköy Küfeki Stone as a Global Heritage Stone Resource (GHSR) nominee by documenting its historical use, quarry distribution, geological context, and by characterizing mineralogical–petrographic, geochemical, and physico-mechanical characteristics (XRPD, WD-XRF, density, water absorption, porosity, uniaxial compressive, tensile, and abrasion strengths, frost resistance). Findings indicate a calcite-dominated, porous stone that is workable when freshly extracted yet hardens with time, a behavior consistent with its long service life but also with observed deteriorations such as erosion, dissolution, black crust (gypsum) formation, granular disintegration, and biological colonization under humid, polluted urban atmospheres. We discuss weathering pathways, restoration outcomes, and risks posed by non-equivalent replacements. To sustain both material integrity and urban identity, the paper proposes identifying and qualifying new sources that match the original stone potentially in Türkiye (e.g. Çanakkale) and in abroad using standardized testing and performance-based acceptance criteria. Formal GHSR recognition would, in turn, support better sourcing, documentation, and conservation planning across Istanbul’s heritage assets.

This work investigates the influence of hybrid NiO-SiO2 nanoparticles on the engine behavior of biodiesel derived from waste sunflower oil and evaluates the experimental outcomes using a data-driven modeling approach. Biodiesel was produced via transesterification and doped with nanoparticles at concentrations of 50, 75, and 100 ppm. Performance and emission tests were conducted on a single-cylinder diesel engine operating at constant speed under varying loads. Specific fuel consumption, brake thermal efficiency, CO, HC, NOx, smoke opacity, and exhaust gas temperature were recorded and analyzed. The incorporation of nanoparticles improved combustion quality and contributed to substantial reductions in harmful emissions. The WSOB20 blend containing 100 ppm NiO-SiO2 provided the most balanced results, decreasing CO, HC, and smoke emissions by 39.50%, 39.40%, and 35.20%, respectively, relative to diesel fuel, while preserving competitive thermal efficiency. A linear regression model developed for CO prediction produced a low mean squared error (1.08 × 10-5), indicating strong predictive capability. The findings confirm that hybrid nanoparticle additives can enhance biodiesel performance while supporting accurate emission forecasting.

In this study, the effects of fuel blend ratio and engine speed on the performance and emissions of a spark-ignition (SI) engine fueled with gasoline-isopropanol blends were experimentally investigated, modeled, and optimized. Despite the potential benefits of gasoline-alcohol blends for SI engines, many response-surface-based studies adopt simplified surrogate models and fixed second-order formulations, which may not adequately capture coupled and non-linear effects, particularly when experimental data are limited. To address this gap, a data-driven multi-model strategy is adopted to systematically evaluate seven multivariate polynomial regression structures for each response, instead of imposing a single fixed-form model. Model performance is assessed using a hold-out validation scheme, and the model with the highest predictive accuracy is selected for each response as the final predictive model, enabling accurate prediction of torque, fuel consumption (FC), and carbon monoxide (CO), hydrocarbons (HC), and carbon dioxide ([Formula: see text]) emissions. As an additional contribution, a multi-objective scalarized function constructed from normalized response values is minimized using a PID-based search algorithm (PSA) to simultaneously maximize torque, power, and brake thermal efficiency (BTE) while minimizing FC, CO, HC, [Formula: see text], and brake-specific fuel consumption (BSFC). The results indicate that increasing the isopropanol ratio has pronounced and non-linear effects on engine behavior: torque and power increase up to an intermediate isopropanol fraction and then decrease at higher ratios, BSFC rises with increasing isopropanol content, and HC, CO, and [Formula: see text] emissions decrease as the isopropanol share increases. The optimization identifies an optimal operating condition at a 50% isopropanol-50% gasoline blend and an engine speed of 2783 rpm. Overall, the study delivers a compact modeling-optimization framework for gasoline-isopropanol operation in SI engines and supports the design of more efficient and environmentally friendly fuel strategies based on alternative fuel usage.

Dry powder inhalers (DPIs) are established drug–device combination products in which therapeutic performance is governed by the interaction between formulation properties, device engineering, and patient-specific inhalation behavior. Although advances in particle engineering and inhaler design have improved dose delivery and aerosol performance, real-world effectiveness remains limited by variability in inspiratory flow, inhalation technique, and disease state. These challenges underscore the need for a systems-based approach that recognizes DPIs as integrated delivery platforms rather than conventional dosage forms. The emergence of digital health technologies, including embedded sensors, connectivity, data analytics, and software-driven feedback, has enabled the development of digitally enabled or “smart” DPIs. Such products have the potential to function as connected combination products, supporting inhalation monitoring, adherence assessment, and personalized therapy. From a regulatory perspective, the integration of digital components introduces considerations related to software as a medical device (SaMD), data integrity, cybersecurity, interoperability, and lifecycle management, as outlined in evolving FDA and EMA digital health and combination product frameworks. This review summarizes the current status of DPI technology in the context of digital health integration, with emphasis on formulation–device–patient interactions, clinically relevant digital functionalities, and performance evaluation. Key regulatory expectations for development, validation, and post-market oversight of digital DPIs are discussed, including alignment with quality by design and risk-based regulatory approaches. Finally, future perspectives are presented to identify scientific and regulatory gaps that must be addressed to enable next-generation digital DPIs capable of delivering reliable, patient-centric, and outcome-driven inhalation therapy. Keywords: Dry powder inhalers; Digital health technologies; Software as a medical device; Regulatory consideration; Quality by design

This study was conducted to elucidate the combined effects of intake-air temperature (IAT), excess air ratio (λ), and fuel blend composition on the combustion behavior of an HCCI engine. Three butanol/diethyl ether blends (B15, B30, and B45) were systematically evaluated at a constant engine speed of 1000rpm and a compression ratio of 12. The IAT was varied between 35°C and 65°C in 15°C increments, while different λ values were applied to each blend to capture a broader spectrum of operating conditions. The findings demonstrate clear differences in combustion behavior and performance among the blends. Specifically, increasing the diethyl ether content in the B15 blend, together with higher IAT, advanced in-cylinder pressure development, heat-release rate, start of combustion, and CA50. It also provided the widest stable λ operating range, although PRRₘₐₓ reached 14bar/°CA at rich conditions, exceeding the knock safety limit. In contrast, relative to the B15 blend, a butanol fraction of 45% retarded ignition timing while achieving optimal combustion phasing between 7° and 11° after TDC. This shortened the combustion duration by approximately 59%, improved indicated thermal efficiency by nearly 20%, and reduced knocking by about 70%. The blend also achieved the highest IMEP of 6.27bar, maintaining cyclic variability below 10% and ensuring stable combustion even at elevated IAT values. Additionally, the lowest emission levels were observed for the B15 blend at 65°C, with CO and HC concentrations of 0.065% and 171 ppm, respectively, whereas CO₂ emissions showed the opposite trend, increasing as CO decreased. Overall, the results identify B45 as the most effective blend for maximizing efficiency and combustion stability, while B15 provides the broadest λ operating window, highlighting a measurable trade-off between efficiency optimization and operating flexibility in HCCI engines.

The paper presents the development of an instructional test bench designed to support the training of marine cadets in the operation and maintenance of tugboat propulsion systems powered by diesel engines. The test bench, developed by the authors and implemented at the Naval Academy “Mircea cel Bătrân” in Constanța, Romania, is intended to enhance practical understanding of propulsion system components and operating principles. The installation enables instruction on the construction and operation of four-stroke internal combustion engines, as well as on the correct monitoring of key parameters associated with a marine diesel engine, reversing gearbox, and hydraulic brake. Successive loading of the engine can be performed, allowing the analysis of engine behaviour and power development under controlled operating conditions. The test bench comprises a diesel engine, reversing gearbox, axial shaft, and a downsized hydraulic brake coupled through a multiplier gearbox for emulating the propeller load. A custom-designed automation and control system is implemented, providing local and remote command consoles together with a replicating display for parameter monitoring. Auxiliary systems include compressed air supply, fuel storage and delivery, exhaust gas evacuation, cooling, and lubrication systems for both the engine and the brake.

Review of the engineering behaviour of fly ash-based geopolymers in soil stabilization studies

Abstract The growing demand for carbon‐neutral fuels has driven increased research into hydrogen (H 2 )‐assisted biodiesel combustion. Engine performance, combustion, and emissions were studied using algae biodiesel blends with H 2 enrichment at 3 and 6 LPM. A graph neural network (GNN) model was also developed to link experimental dual‐fuel data with engine behavior predictions. Experiments of six biodiesel blend ratios and two H 2 flow rates were performed at five different loads (0–100%), evaluating performance, combustion, and emissions. Due to the lower calorific value of the fuel, the brake thermal efficiency (BTE) reduced by 6.1% with a higher biodiesel mixture, and 6 LPM H 2 enhanced the engine performance by 3.7% and compensated for the thermal energy loss. The H 2 enrichment enhanced peak pressure and heat release rate (HRR) by 6–6.4%, compensating for losses from biodiesel usage. Overall, nitrogen oxides (NO x ) emissions increased by 23.1% with B100 and 3.6% for 6 LPM H 2 addition. Hydrocarbons (HC) were reduced by 87.5%, carbon monoxide (CO) by 28.8%, and the total amount of smoke decreased by 27.1% with the B100 + 6 LPM H 2 condition. A 90‐node heterogeneous GNN using 38 physics‐informed features achieved R 2 >0.95 and RMSE <5% for five simultaneous outputs, effectively capturing nonlinear interactions between hydrogen and biodiesel. Overall, H 2 enhances the performance and clean‐burning potential of algae biodiesel, significantly reducing key pollutants while causing a modest increase in NO x . The developed GNN framework provides an efficient predictive tool for optimizing H 2 biofuel dual‐fuel engines and supports the advancement of low‐carbon combustion technologies.

This research investigates the effects of Neem biodiesel and hydrogen-enriched air on the emissions and performance of a common-rail direct-injection diesel engine operating under variable load conditions of 25%, 50%, 75%, and 100%. The aim is to improve engine efficiency and promote sustainable energy solutions. Several Neem biodiesel blends (B10-B30) were initially evaluated, and B15 was selected for comprehensive analysis due to its optimal performance. Hydrogen as a gaseous fuel was subsequently inducted into the inlet air at rates of 3.34 to 9.27 liters per minute to assess its influence on engine behavior. Key parameters, including Brake Thermal Efficiency (BTE), Brake Specific Fuel Consumption (BSFC), and emissions of carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx), were analyzed. The B15 blend exhibited a BSFC of 0.27 kg/kWh and a BTE of 31.38% at full load. With hydrogen supplementation at 5.19 liters per minute, BTE increased to 33.31% and BSFC decreased to 0.25 kg/kWh. NOx and CO emissions were reduced to 488 ppm and 0.04%, respectively, while HC emissions remained unchanged. Hydrogen’s high flame speed and broad flammability range contributed to emission reductions; however, higher hydrogen levels led to higher NOx emissions, necessitating ongoing monitoring to comply with regulations. The ANN model, trained on experimental data, was very good at predicting performance and emissions, suggesting it could be used for real-time combustion diagnostics and fuel optimization. In summary, adopting dual-fuel systems utilizing hydrogen and Neem biodiesel offers significant potential to reduce the environmental impact of diesel engines.