Engine Speed Research Articles

Computational study of gas-dynamic approach for noise reduction in atwo-stroke engine’s exhaust system

BACKGROUND: The traditional approach to designing exhaust mufflers relies heavily on energy dissipation. In the "gas-dynamic" approach, the flow of exhaust gases is equalized by introducing long channel(s) into the muffler to separate impulses and shift them in time. It is assumed that such mufflers will provide noise reduction without creating significant backpressure. AIMS: To evaluate the potential of the "gas-dynamic" approach to reducing the noise level of two-stroke internal combustion engines. MATERIALS AND METHODS: The study was carried out using computational models. The processes in the gas-air tract of the piston engine were calculated using a one-dimensional (1D) model. The noise characteristic was the effective sound pressure at a specified point in the environment, calculated using 2D model of propagation of disturbances in elastic medium. The object of study was a two-stroke gasoline two-cylinder engine RMZ-551i, with a resonator (providing gas-dynamic supercharging) and a muffler. Initially, the parameters and sound pressure level of the engine with the stock muffler at full load and close to nominal engine speed were calculated. Then, the structure of the stock muffler was modified by adding a "tuned" channel between its two chambers. The parameters of the modified muffler were optimized based on the criterion of reducing gas pulsations at the outlet to the atmosphere. The noise reduction of the muffler implementing the gas-dynamic approach was evaluated relative to the stock muffler and expressed in terms of sound pressure levels in dB. Performance and levels of sound pressure were finally calculated over a wide range of engine speeds. RESULTS: According to the computational estimate, the optimal implementation of the gas-dynamic approach in the muffler reduces exhaust noise by 7 dB, while engine power decreases by 2.5%. Calculation of the sound pressure level based on the external speed characteristic showed that at an engine speed of 3000 rpm, the calculated sound pressure exceedsby 8 dB the minimum (99 dB) obtained for the optimally "tuned" muffler at an engine speed of 5000 rpm. It is suggested that the gas-dynamic approach with optimization is also applicable for uniform noise reduction over a wide range of engine speeds, with a more complex structure of the exhaustmuffler. CONCLUSIONS: Theoretical evaluation of a muffler with a tuned channel connecting its two chambers was carried out, with a two-stroke engine RMZ-551i with a stock muffler as a basis for comparison. At the optimum point on the speed characteristic, the exhaust noise was reduced by 7 dB, while the calculated power decrease was insignificant. The authorsnote the suitability of the methodology for rapid assessments and automated computational optimization of mufflers that utilize wave effects. They also point out the limitations of the models used, which require validation or rather calibration based on experimental data, and the need for the development of applied models of acoustic effects and measuring devices for domestic CAE packages.

Advancing Artificial Intelligence (AI) and Machine Learning (ML) Based Soft Sensors for In-Cylinder Predictions with a Real-Time Simulator and a Crank Angle Resolved Engine Model

In a previous research effort by this group, pseudo engine dynamometer data in multi-dimensional arrays were combined with dynamic equations to form a crank angle resolved engine model compatible with a real-time simulator. The combination of the real-time simulator and external targets enabled the development of a software-in-the-loop (SIL) environment that enabled near-real-time development of AI/ML and real-time deployment of the resulting AI/ML. Military applications, in particular, are unlikely to possess large quantities of non-sparse operational data that span the full operational range of the system, stove-piping the ability to develop and deploy AI/ML which is sufficient for near-real-time or real-time control. AI/ML has been shown to be well suited for predicting highly non-linear mathematical phenomena and thus military systems could potentially benefit from the development and deployment of AI/ML acting as soft sensors. Given the non-sparse nature of the data, it becomes exceedingly important that AI/ML be developed and deployed in near-real-time or real-time in parallel to a real-time system to overcome the inadequacy of applicable data. This research effort used parallel processing to reduce the training duration of the shallow artificial neural networks (SANN) and forest algorithms forming ensemble models. This research is novel in that the SIL environment enables pre-developed AI/ML to be adapted in near-real-time or develop AI/ML in response to changes within the operation of the applied system, different load torques, engine speeds, and atmospheric conditions to name a few. Over time it is expected that the continued adaptation of the algorithms will lead to the development of AI/ML that is suitable for real-time control and energy management.

ANALYSIS OF LUBRICANT OIL DEGRADATION AND SOUND PRESSURE LEVEL FOR CI ENGINE USING BLEND FUELS

Long-term engine running has been the subject of extensive research on the deterioration of engine oil. In contrast, it is not fully clear what effect synthetic and biofuels will have. Modern engines, traditional fuels and lubricants should be used to provide a research basis for characterizing novel fuel-related phenomena in engines. This study makes an effort to characterize how lubricating engine oil behaves over the course of its service life using data on friction and wear. Every 20 hours, oil samples from the engine were obtained to evaluate its chemical makeup. On a reciprocating test rig, friction and wear measurements were taken. Kinematic viscosity, density, and wear metals such as cadmium (Cd), cobalt (Co), and lead (Pb) were measured for the lubricant oil analysis. In general, n-pentanol aids in the reduction of engine wear debris, contamination, and lubricating oil oxidation. According to the findings of this study, a D60WCO20Pe15 ternary combination can be used in a diesel engine without any alteration. The sound pressure level (SPL) increased by 7.8 dB at engine speed of 1300 RPM in the case of the DF95WCO5. However, when compared to base line, the average SPL of D60WCO20Pe15 ternary blend was 4.3 dB lower.

Performance of Motorcycle Fueled with Pertalite‒LDPE Pyrolytic Oil Blendings

Plastic use has expanded substantially, and its waste is primarily disposed of in landfills, which further harm ecosystems owing to inadequate waste management. Pyrolysis, which converts plastic waste into liquid fuel, is one of the potential chemical recycling alternatives for plastic. The purpose of this study is to determine the viability of using pyrolytic oil from an LDPE grocery bag as an alternative fuel for a four-stroke spark ignition motorcycle engine. The LDPE grocery bag was pyrolyzed at 500 oC at a heating rate of 3 oC/min, and the condensed pyrolytic vapor's characteristics were determined. Torque, power, and fuel consumption were investigated using a four-stroke spark ignition motorbike powered by pertalite‒LDPE pyrolytic oil blends. The results reveal that the properties of LDPE pyrolytic oil and pertalite were considerably different; hence, when the blending fuel was applied to the motorcycle, the engine torque and power decreased at low engine speed (2000‒3500 rpm), about equal at medium speed (3500‒5500 rpm), and increased at high engine speed (5500‒8500 rpm). Furthermore, the greater blending fuel greatly reduced fuel usage due to the high viscosity of the LDPE pyrolytic oil.

Impact of Using n-Octanol/Diesel Blends on the Performance and Emissions of a Direct-Injection Diesel Engine

This study evaluates the viability of n-octanol as an alternative fuel in a direct-injection diesel engine, aiming to enhance sustainability and efficiency. Experiments fueled by different blends of n-octanol with pure diesel were conducted to analyze their impacts on engine performance and emissions. The methodology involved testing each blend in a single-cylinder engine, measuring engine performance parameters such as brake torque and brake power under full-load conditions across a range of engine speeds. Comparative assessments of performance and emission characteristics at a constant engine speed were also conducted with varying loads. The results indicated that while n-octanol blends consistently improved brake thermal efficiency, they also increased brake-specific fuel consumption due to the lower energy content of n-octanol. Consequently, while all n-octanol blends reduced nitrogen oxide emissions compared to pure diesel, they also significantly decreased carbon monoxide, hydrocarbons, and smoke opacity, presenting a comprehensive reduction in harmful emissions. However, the benefits came with complex trade-offs: notably, higher concentrations of n-octanol led to a relative increase in nitrogen oxide emissions as the n-octanol ratio increased. The study concludes that n-octanol significantly improves engine efficiency and reduces diesel dependence, but optimizing the blend ratio is crucial to balance performance improvements with comprehensive emission reductions.

Influence of compression ratio on the performance characteristics of a spark ignition engine

In this study, the influence of the compression ratio on the performance characteristics of a gasoline engine was investigated in detail using COMSOL simulations. Four compression ratios — 8, 9, 10 and 11 — were investigated at different engine speeds between 1000 and 1800. The analysis focused on power output, braking performance and fuel consumption in order to decipher the complicated relationships between compression ratios and engine dynamics. The results showed a significant increase in power output with increasing compression ratio, highlighting the delicate balance required for optimal power generation. Braking power increased with higher compression ratios, indicating a potential improvement in braking performance. In addition, the study showed a correlation between increased fuel consumption and higher compression ratios, highlighting the need for strategic fuel-saving measures. These results contribute to the understanding of gasoline engine behavior and provide insights into the trade-offs that need to be made when adjusting the compression ratio. Recommendations include experimental validation, exploration of dynamic compression control, research into integrated braking systems, investigation of sustainable fuel strategies and a focus on multi-metric optimization. The observed increase in power output at higher compression ratios highlights an important aspect of engine optimization. Engineers and researchers need to carefully consider compression ratio adjustments to ensure optimal power generation while maintaining efficiency. This insight can guide the development of engines that strike an ideal balance between power and fuel efficiency.

Experimental Investigation of Energy Analysis of Methanol-Gasoline Mixtures at Different Torque Values

Despite the increasing use of petroleum-based fuel as a result of ever-increasing energy demands, the search for alternative fuels remains important. In this study, in a Lombardini LGW 523 brand 2-cylinder 4-stroke water-cooled engine, different volumetric ratios of methanol and gasoline fuel mixtures (M10, M20, M30, M40) were used at 4 different torque values (5, 10, 15, 20 Nm) at a constant 3000 engine speed. It is discussed. As a result of the study, engine performance, emission and energy analysis examination was carried out experimentally. Keywords: Energy, exergy, internal combustion engine, methanol fuel

Predictive modeling of engine performance and emissions for castor oil ethyl ester biodiesel blends: A Gaussian process regression approach

Replacing fossil fuels with cleaner alternatives is essential. This study examines a biodiesel-diesel blend containing 8 % castor oil ethyl ester (COEE8) and its impact on engine performance, combustion characteristics, and exhaust emissions. A single-cylinder diesel engine was tested under consistent conditions: an engine speed of 1500 rpm, varying engine loads (25 %, 50 %, and 75 % of maximum torque), and compression ratios (16, 17, and 18). Engine-out emissions were measured with Testo flue gas analyzers. The results showed that COEE8 combustion significantly decreased HC, CO, and smoke emissions compared to diesel fuel but increased NOx emissions. Additionally, COEE8 exhibited comparable brake-specific fuel consumption (BSFC) and brake thermal efficiency (BTE) to diesel fuel. The optimal engine operating parameters were determined using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), a multi-objective optimization technique. Due to limited data availability, Gaussian Process Regression (GPR), a machine learning algorithm for small datasets, modeled the multi-objective functions with compression ratio and engine load as input variables. The GPR model demonstrated high prediction performance across all output parameters (BSFC, BTE, HC, smoke, NOx, and CO) for both diesel and COEE8 fuels, with average coefficients of determination (R2) of 0.9896 and 0.9953, respectively, indicating a strong correlation between predicted and actual values. The mean absolute percentage error (MAPE) was also low, averaging 3.11 % and 2.26 %, respectively, demonstrating the model's accuracy. Using the GPR model, the NSGA-II identified the optimal trade-off between NOx and smoke index for both diesel and COEE8 fuels. The optimal compression ratio was 16 for both fuels, while the optimal engine load varied, ranging from 20 % to 30 % for COEE8 and around 30 % (almost 40 %) for diesel fuel.

In-cylinder flow evolution in the horizontal plane of a motoring compression ignition engine

This study used the two-dimensional particle image velocimetry technique to quantify the in-cylinder horizontal plane velocity field evolution in a swirl-supported light-duty single-cylinder diesel engine. The data were acquired at a constant engine speed of 1600 revolutions per minute. For each case, the distance of the laser sheet from the fire deck was varied (z = 5, 10, and 20 mm) to investigate the axial variations in the flow field during the flow evolution in the compression stroke. A vortex identification algorithm was used to detect the swirl center and its deviation from the rigid body rotation. A Bessel fit was obtained using the experimental data. The result revealed that the in-cylinder flow was not axisymmetric. The swirl center approached the geometrical center as the piston approached the top dead center. The flow evolved at the farthest plane from the fire deck. The axial diffusion of angular momentum resulted in the formation of the swirl flow structure in the plane closer to the fire deck. Angular momentum analysis of a simplified geometry has been presented to explain the swirl amplification. The estimated results were compared with the experimental results to show the momentum stratification in the engine cylinder later in the compression stroke.

The tail segments are required by the performance but not the accomplishment of various modes of Drosophila larval locomotion

The tail plays important roles in locomotion control in many animals. But in animals with multiple body segments, the roles of the hind body segments and corresponding innervating neurons in locomotion control are not clear. Here, using the Drosophila larva as the model animal, we investigated the roles of the posterior terminal segments in various modes of locomotion and found that they participate in all of them. In forward crawling, paralysis of the larval tail by blocking the Abdb-Gal4 labeled neurons in the posterior segments of VNC led to a slower locomotion speed but did not prevent the initiation of forward peristalsis. In backward crawling, larvae with the Abdb-Gal4 neurons inhibited were unable to generate effective displacement although waves of backward peristalsis could be initiated and persist. In head swing where the movement of the tail is not obvious, disabling the larval tail by blocking Abdb-Gal4 neurons led to increased bending amplitude upon touching the head. In the case of larval lateral rolling, larval tail paralysis by inhibition of Abdb-Gal4 neurons did not prevent the accomplishment of rolling, but resulted in slower rolling speed. Our work reveals that the contribution of Drosophila larval posterior VNC segments and corresponding body segments in the tail to locomotion is comprehensive but could be compensated at least partially by other body segments. We suggest that the decentralization in locomotion control with respect to animal body parts helps to maintain the robustness of locomotion in multi-segment animals.

PENGARUH LAMA WAKTU TAHAN NORMALIZING PADA BAJA ST 41 PENGELASAN FRICTION WELDING TERHADAP SIFAT MEKANIS

The development and application of science and technology, especially in the industrial world, is currently experiencing very rapid progress, especially in the world of welding. Welding is the process of joining two or more metal parts using heat energy. In the current era, welding developments are increasingly developing, such as liquid welding, resistance welding, solid welding, and forging welding. For solid welding, there are friction welding and cold welding. The joining process using friction welding involves friction factors, pressing force, and surface quality. To improve the mechanical properties of steel after welding, Normalizing heat treatment is carried out, namely a heat treatment process on steel which aims to refine the grain, homogenize the structure and obtain steel with mechanical properties as desired, or called normalization. This research method uses the Experimental Testing method. This sample was obtained from the normalizing friction welding process which was tensile tested, namely samples with varying holding times of 15 minutes, 30 minutes and 45 minutes with an engine speed of 2100 rpm and a pressure of 35 MPa with tensile testing of the material and microphotographs. The results of the friction welding research are as follows. The normalizing holding time of 15 minutes produces a maximum tensile stress value of 325.16 N/mm2, the fracture that occurs is in the form of a ductile fracture, the normalizing holding time of 30 minutes produces a maximum tensile stress value of 327.66 N/mm2, the fracture that occurs is in the form of a fracture ductile, the normalizing holding time of 45 minutes produces a maximum tensile stress value of 329.53 N/mm2, the fracture that occurs is in the form of a ductile fracture. The long holding time of normalizing will increase the tensile strength of the steel and tensile test fractures mostly occur in the weld area

EFFECT OF IGNITION TIMING CHANGES ON EXHAUST EMISSIONS IN KEN AROK URBAN CAR FUELED BY ETHANOL E100

ABSTRACT The depletion of fossil fuel reserves, as well as the increasing air pollution that occurs in Indonesia, greatly affects the energy crisis. This study aims to test, analyze, and determine the right ignition timing and injection timing so as to reduce HC and CO exhaust emissions pollution with E100 ethanol fuel. The test method in this study uses ignition timing independent variables (10.5⁰, 12.5⁰, 14.5⁰, 16.5⁰) and is carried out at 1500, 2000, 3000, 4000 RPM engine speed. The results of this study can be seen that the ignition timing variable has an influence on HC and CO exhaust emissions. at 1500 RPM rotation, the lowest HC and CO exhaust emissions are obtained at 16.5⁰ ignition timing with a value of HC 260 ppm and CO 0.12%. Then for the highest exhaust gas results there is at 12.5⁰ ignition timing with a value of HC 310 ppm and CO 0.16%. Keywords: exhaust emissions, ethanol, ignition timing

Extraction and characterization of Cucumis melon seeds (Muskmelon seed oil) biodiesel and studying its blends impact on performance, combustion, and emission characteristics in an internal combustion engine

This study examines the performance, combustion, and emissions characteristics of a single-cylinder internal combustion diesel engine when fueled with a blend of diesel and biodiesel derived from muskmelon seeds. The kinematic viscosity of the extracted muskmelon seed oil was 6.1 cSt at 40 °C, which is higher than the kinematic viscosity of petroleum diesel of 2.6 cSt. Muskmelon biodiesel was further analyzed using thin-layer chromatography (TLC) and high-voltage separator tests. A comparison of the fuel properties of muskmelon biodiesel with conventional diesel fuel revealed that muskmelon biodiesel could be used alone or in a diesel–biodiesel blend to fuel compression diesel engines. In this study, muskmelon seed biodiesel was blended with diesel fuel at proportions of 10 %, 20 %, and 50 % (BD10, BD20, and BD50, respectively). At a relatively low rotational speed of 1200 rpm, the brake thermal efficiency (BTE) of the engine operated with BD10 and BD20 blends were 36.1 % and 36.0 %, respectively, while the brake-specific fuel consumption (BSFC) of the two blends were 0.260 kg/kWh, and 0.262 kg/kWh, respectively. These values closely resemble those typically observed in diesel fuel engines. Indeed, the average BTE of the BD20 blend was only 3.24 % less than the average BTE of diesel fuel. Diesel fuel generates less NOx and SO2 emissions compared to biodiesel blends: BD100 emitted the most NOx pollution of all fuels tested. In addition, BD10 released significantly more SO2 emissions compared to the other fuels tested. However, the BD20 blend outperformed all other blends in terms of CO, NOx, and SO2 emissions at high engine speeds. The only exception was H2S emissions, which were higher than BD50 and BD100. BD20 also exhibited significantly reduced CO emissions compared to diesel fuel, while BD10 emitted significantly more CO emissions than the other biodiesel blends. Our findings revealed that BD20 exhibited the best engine performance and lower emissions among all fuels tested. In other words, BD20 is the ideal fuel blend for use in diesel engines and does not require any alterations to the engine. Muskmelon waste seeds represent a non-edible waste stream that can be exploited in the production of biodiesel fuel, allowing for the upcycling of a potentially problematic thermochemical conversion feedstock. This potentially valuable use for waste muskmelon seeds in the energy sector could address the wastefulness associated with this particular waste stream.

Characteristics of hydrogen enrichment on RNG combustion under various engine speeds in a retrofitted gas engine

Renewable natural gas (RNG) is attractive for energy policy goals in the world. A regional system is designed to explore RNG combustion for power generation in localities. Generally, 50 % methane (CH4) and 50 % carbon dioxide (CO2) in volume are utilized to represent RNG for investigations. However, CO2 reduces the burning rate and narrows the flammability limits, thus decreasing the engine thermal efficiency. Therefore, how to increase the thermal efficiency of RNG combustion through adding H2 or changing engine speed is the main task here. This study investigates a port fuel injection (PFI) engine fueled with hydrogen (H2) blended into the RNG. In order to obtain the higher efficiency, the effect of engine speed on combustion characteristics should be clarified as well as H2 influence demonstrated. Therefore, 1500, 2000 and 2500 revolutions per minute (rpm) of engine speed were tested. When H2 was added, the volume percentage changed from 5 % to 20 % by keeping the volume ratio of CH4 and CO2 at 1:1. Finally, combustion characteristics of CH4, CH4+CO2 and CH4+CO2+H2 were compared and discussed. Results showed that compared with H2, engine speed could only increase the efficiency slightly. “Arched” and “fish-hook” curves are fitted respectively to select the optimal working region. Through cylinder pressure analysis, engine speed could enlarge the Pmax only at some certain but increase coefficient of variation (COV) gradually. However, H2 increases Pmax but decreases COV significantly. Moreover, NOx decreases gradually with engine speed owing to the short reaction duration in combustion. However, NOx increases again with higher H2 concentration. Among the current conditions, for higher efficiency and lower NOx, three conditions are finally selected to be recommended for running.

Investigation the performance of a new fuel produced from the phthalocyanine-gasoline mixture in an internal combustion engine

The study involved the utilization of novel developed six distinct fuel, denoted as, PG5, PG10, PG15, PG20, PG25, and PG30 and G100 (pure gasoline). These fuels were derived from various blends of gasoline and phthalocyanines. Experimental investigations were conducted to assess the internal combustion engine's performance in terms of both energy and exergy. The mixtures underwent testing across a range of engine speeds, spanning from 1400 rpm to 3000 rpm. Notably, optimal performance across all fuels and engine speeds was consistently observed at 2600 rpm. In terms of energy and exergy efficiency assessments for all fuels and engine speeds, PG25 fuel demonstrated the highest efficiency levels, with 35% energy efficiency and 33% exergy efficiency at 2600 rpm. Conversely, G100 fuel exhibited the lowest energy and exergy efficiency at the same engine speed, registering values of 27% and 24%, respectively. Meanwhile, with regard to exhaust exergy, G100 fuel demonstrated the highest exhaust energy at 10.69 kW, occurring at 3000 rpm, whereas PG25 fuel exhibited the lowest exhaust exergy, measured at 3.09 kW. It has been observed that N2 gas, one of the exhaust components that affects the exergy of exhaust gases, affects the exhaust exergy to a large extent and this ratio is approximately 50%. In addition, the sustainability index value for all fuels was found to be at most 2600 rpm. It was calculated as 1.50 for PG25 fuel and 1.32 for G100 fuel.

Experimental study of quaternary blends with diesel/palm-oil biodiesel/ethanol/diethyl ether for optimum performance and emissions in a light-duty diesel engine using response surface methodology

Quaternary fuel blend consisting of diesel, palm-oil biodiesel (POB), diethyl ether (DEE), and ethanol is a promising low-carbon fuel solution for diesel engines. In this study, the effects of DEE, ethanol, and engine load on the brake specific fuel consumption (BSFC), nitrogen oxides (NOx), carbon monoxide (CO), and unburned hydrocarbons (UHCs) emissions of a light-duty diesel engine were statistically analyzed using analysis of variance (ANOVA). Desirability-based response surface methodology (RSM) optimization was then employed to determine the optimum quaternary fuel blend. The desired optimum quaternary fuel blend was found to be 6.78 vol% DEE and 20.00 vol% ethanol at an operating engine load and speed of 31.36 % and 2000 rpm, respectively. The engine out responses of BSFC and NOx, CO, and UHCs emissions for the optimal solution were 490.58 g/kWh, 326.84 ppm, 0.300 vol%, and 156.95 ppm, respectively. Validation of the optimized parameters was conducted through actual engine experiments and the errors were less than 5 %. The results suggest that the optimum quaternary blend can be a cleaner alternative for light-duty diesel engine applications.

Particle filter performance of soot-loaded diesel particulate filter and the effect of its regeneration on the particle number and size distribution

The DPF regeneration is crucial for reducing backpressure, minimizing negative impacts on engine power and fuel economy, but the changes in particulate emission characteristics it brings are worth studying. In this study, the influence of DPFs with different soot loadings on exhaust back pressure and particle emission characteristics, as well as the particle number emission, particle size distribution, and thermal field distribution characteristics during regeneration was investigated based on engine bench test. Results reveal that the exhaust back pressure increases linearly with the engine speed, as well as the soot loading. The increase of DPF soot loading leads to a considerable increase in the reduction efficiency of particle number (PN) and particulate matter emissions, especially for the accumulation mode particles. Moreover, the performance in reducing nucleation mode particles is markedly better than that of accumulation mode ones, and this effect is greatly influenced by the engine operating conditions. At the beginning of DPF regeneration, the PN concentration increases sharply, especially the nucleation mode particles. After regeneration, the PN emissions decrease by two orders of magnitude. During regeneration, the particle size distribution exhibits a unimodal distribution, with the peak value increasing considerably and shifting toward smaller particle sizes. After regeneration, the particle size of the PN peak value slightly decreases and markedly shifts toward larger sizes, the accumulation mode particle concentration increases by 7.2 times, and the nucleation mode particle concentration increases by 2.6 times. Before the DPF regeneration, the axial temperature gradually decreases along the direction of the airflow, and the radial temperature gradually decreases from the center to the edge. During regeneration, the highest temperature occurs in the center of the DPF cross-section, whereas the temperature peak at the outlet interface occurs at the middle position of the DPF. The findings of this paper can provide scientific references to formulation and optimization of DPF regeneration strategies.

An intelligent spinal soft robot with self-sensing adaptability

Self-sensing adaptability is a high-level intelligence in living creatures and is highly desired for their biomimetic soft robots for efficient interaction with the surroundings. Self-sensing adaptability can be achieved in soft robots by the integration of sensors and actuators. However, current strategies simply assemble discrete sensors and actuators into one robotic system and, thus, dilute their synergistic and complementary connections, causing low-level adaptability and poor decision-making capability. Here, inspired by vertebrate animals supported by highly evolved backbones, we propose a concept of a bionic spine that integrates sensing and actuation into one shared body based on the reversible piezoelectric effect and a decoupling mechanism to extract the environmental feedback. We demonstrate that the soft robots equipped with the bionic spines feature locomotion speed improvements between 39.5% and 80% for various environmental terrains. More importantly, it can also enable the robots to accurately recognize and actively adapt to changing environments with obstacle avoidance capability by learning-based gait adjustments. We envision that the proposed bionic spine could serve as a building block for locomotive soft robots toward more intelligent machine-environment interactions in the future.

Experimental investigation of engine performance and emissions, and characterization, of waste transformer oils and diesel blends with biodiesel produced from olive oil wastes in a CI engine

In this study, five different fuel blends were prepared by mixing biodiesel obtained from olive oil wastes using transesterification method, waste transformer oil, and Euro diesel in different ratios. The important physicochemical properties of the prepared fuel blends and produced biodiesel were determined by gas chromatography, Fourier transform infrared spectroscopy, and thermogravimetric analysis/differential scanning calorimetry analyses, and their characterizations were carried out. Then, the effects of the prepared fuel blends on engine performance and emission characteristics were investigated in a compression ignition engine. The experiments were performed with five different fuel blends (TD30, TD30B10, TD30B20, TD30B30, and D100) at 1000, 1500, 2000, and 2500 rpm. At all speeds, each fuel blend produced an average torque value that was highest for D100 fuel and lowest for TD30 fuel The average BP value produced by each fuel at all engine speeds was highest in D100 fuel and lowest in TD30 fuel. The results of the experiments showed that there was a 23.98% decrease in the average NOx emissions of TD30 fuel blend compared to the average NOx emissions of D100 fuel at all engine speeds. It was observed that all important fuel properties such as density, kinematic viscosity, and pour and cloud points of all fuel blends met the fuel standards.

Multi-objective RSM-based optimization of diesel-diethyl ether blends in diesel engine to achieve sustainable development goals

With the plummeting reserves of fossil fuels at present, there has been a growing imperative for sustainable energy technologies over the last couple of decades. This imperative highlight the need for a shift towards renewable sources, not just to fulfill the current energy demands but also to lessen environmental degradation, fostering an eco-conscious and sustainable future. One way to accomplish such a goal is the utilization of diesel-diethyl ether (D-DEE) blends, instead of neat diesel in compression ignition (CI) engines. This study presents the multi-objective RSM-based analysis and optimization of D-DEE blends (0,5 and 10 %. vol) at manifold engine speeds (1200, 1400, and 1600 rpm). The responses that were recorded in this research included brake power (B.P), brake thermal efficiency (BTE), brake-specific fuel consumption, and CO2 emissions. The results demonstrated an increment in brake power as well as brake thermal efficiency, along with the enhanced CO2 emissions whereas the BSFC decreased while using the Di-ethyl ether enrichment in a 4-stroke CI engine. Upon implementing optimization parameters, the results illustrated the optimal blend ratio of 9.5786 %. vol at 1600 rpm, along with the associated values of B.P, BTE, BSFC, and CO2 emissions which were, 1.26726 kW, 20.861 %, 0.3354, and 7.837 % vol., respectively for this optimized fuel. This study addresses the lack of research on optimizing engine conditions for diesel-DEE blends in CI engines, specifically focusing on diethyl ether as a renewable fuel. Using response surface methodology (RSM), it aims to bridge this gap and contribute to the understanding of optimal blend utilization. The current research also aligns with the attainment of an important sustainable development goal (SDG) which includes the availability of responsible consumption (SDG 12) and improved power generation, contributing towards a greener and cleaner future.