Emission Testing Research Articles

Experimental and numerical studies on performance investigation of a diesel engine converted to run on LPG

With the growing environmental concerns and depletion of energy resources, considerable efforts are focused on developing ecofriendly and sustainable transportation systems. This includes the conversion of outdated diesel engines into ecofriendly liquefied petroleum gas (LPG) engines. In this study, a Euro-6 diesel engine mounted on a commercial vehicle (mega truck) was converted into a propane LPG engine. The combustion chamber was modified by changing the piston shapes (PSs), compression ratios (CRs), ignition system, throttle body, and injector design to enable operation using propane. The performance of the modified engines with two different PSs, PS1 and PS2, were experimentally investigated. In terms of the power, the engine designed using PS2 demonstrated better performance than PS1 under all operating speeds, except 2600 rpm. Particularly, PS2 outperformed PS1 by more than 10 Nm in the low-speed range of 1000–1600 rpm. Under full load, the PS2-equipped LPG engine achieved the maximum torque and power of 834 Nm at 1600 rpm and 170 kW at 2600 rpm, achieving 106 % and 86 % of the target torque and power, respectively. Additional exhaust gas emission tests were performed using the PS2-equipped LPG engine. The engine performance varied with the application of exhaust-gas recirculation. Moreover, the results of the world-harmonized stationary cycle mode tests confirmed the conformance of the modified LPG engine to all Euro-6 emission standards. Furthermore, simulation-based performance optimization was conducted considering two PSs and four CRs. Based on the simulations, PS1 achieved higher engine performance and lower CO2 and soot emissions, whereas PS2 had lower NO emissions. Additionally, increasing the CR improved the performance and reduced the CO2 and soot emissions for both PSs. These results indicate the possibility of developing LPG engines with performance comparable to diesel engines. In particular, the modified LPG engine proposed in this work may be installed on buses and trucks in the future and is anticipated to replace outdated medium-generator and marine engines.

EARLY DETECTION AND LONGITUDINAL OUTCOMES OF HEARING IMPAIRMENT IN NICU GRADUATES AT SDM COLLEGE OF MEDICAL SCIENCES AND HOSPITAL

Objective: Hearing impairment is a prevalent congenital anomaly, particularly in neonates in NICUs, due to various risk factors. Early detection through screening programs is crucial for developmental outcomes. Methods: A prospective observational study was conducted at SDM College of Medical Sciences and Hospital, involving 425 neonates. Otoacoustic Emissions (OAE) testing was used for early detection and longitudinal outcome assessment. Results: Out of 425 neonates, 95.3% passed the initial OAE screening. However, 4.7% failed, necessitating further evaluation. Notable risk factors included neonatal jaundice and perinatal asphyxia, particularly impacting neonates with lower birth weights. Conclusion: The study underscores the importance of early and universal hearing screening in NICU settings, emphasizing the need for tailored protocols to address specific neonatal risks.

Experimental investigation on diesel engine performance and emission characteristics using waste cooking oil blended with diesel as biodiesel fuel

Biodiesel production from waste cooking oil is a potential feedstock to alternative fuel sources. Produced alternative fuel sources were to have a strong emphasis on energy efficiency to substitute the declining world supply of fossil fuels while also improving emission characteristics in diesel engine applications. The development of industrialization and mechanization causes increased fossil fuel consumption and its usage. This study aimed at an experimental investigation of biodiesel blended fuel combustion efficiency for single-cylinder diesel engines under varying engine loads at constant engine speed 1500 rpm. The transesterification process was used to produce biodiesel from waste cooking oil using NaOH as catalysts. Biodiesel reaction takes place with oil to methanol ratio of 6:1 at 60 °C reaction temperature for 90 min with 600 rpm stirring speed while 90% yield gained. Eight sample biodiesel blends were prepared with percentage value B5%, B10%, B15%, B20%, B25%, B30%, B35%, B40% v/v and B100% to investigate the effect of biodiesels on engine performances. The experimental result reveals that the mixed biodiesel blends have lower average value in terms of brake torque, brake power, and brake thermal efficiency than diesel fuels as a percentage of 16.79%, 4.08%, and 27.9% respectively. In addition, the average BSFC of biodiesel blends was increased by 4.8% than baseline diesel fuel. Related to exhaust gases emission test results were shows that the average CO and HC emissions decreased by 52.2% and 60% with increasing loads and blends and the increment of CO2 and NOx by 28.1% and 45.4% respectively than baseline fuel with increasing blends and loads. Biodiesel derived from waste cooking oil was less costly and environmentally friendly and viable to substitute petro-diesel.

Combination of in-/and ex-situ damage detection methods to investigate the forming behavior of fiber-metal-laminates

In this study, the forming behavior of fiber-metal laminates (FML) is investigated by a combination of different (in- and ex-situ) measurement techniques. Using FML-samples consisting of aluminum and carbon fiber reinforced polyamide-6, deep-drawing tests were employed at high temperatures. It can be concluded a conventional approach based on the forming limit curve (FLC) is not suitable to predict the failure initiated in the multi-material setup as principal strains cannot differentiate the strain in aluminum and CFRP and lack sensitivity to detect other relevant failure modes, such as debonding as well as debonding in between layers. To better understand the failure behavior due to forming of FML, an experimental setup, that based on the Nakajima-test, was developed, using in-situ acoustic emission testing, 3D digital image correlation as well as ex-situ X-ray computed tomography. The combined results from all methods helped to gain a deeper insight into how thermoplastic FML behave during deep drawing at elevated temperatures especially focusing on evolving damage inside the hybrid material

Testing the strength of thin feather-edge monolithic multilayered zirconia crowns: A pilot study with a novel acoustic test

Intoduction: Limited research has explored the mechanical characteristics of recently introduced multilayered monolithic zirconia (MZC) crowns with feather-edge margins design. Moreover, most of the conventional techniques for evaluating the mechanical behavior of brittle dental ceramics rely on destructive tests, making it impossible to precisely evaluate real strength values due to premature crack initiation detection failure. Objectives: The main objective of the study was to assess the load capacity of translucent multilayered monolithic zirconia crowns with feather-edge margin thicknesses of 0.4 mm and 0.5 mm. Additionally, the research introduced a novel non-destructive acoustic emission testing (AET) technique in the laboratory to identify early cracks in dental ceramics. Methods: Forty multilayered zirconia crowns produced using computer-aided design and computer-aided manufacturing (CAD/CAM) technology were evenly divided into two groups, each with distinct feather-edge margin thicknesses: 0.5 mm (group 1) and 0.4 mm (group 2). These crowns were securely cemented onto customized polymethyl methacrylate (PMMA) dies using a universal restorative glass ionomer. Subsequently, the crowns underwent a compressive axial loading test, controlled by an innovative AET crack detection system rooted in the principles of non-destructive laboratory testing. Fractographic analysis was conducted to determine the location of crack or eventual fracture. Results: The proportion of MZCs with a crack was statistically higher than the proportion with a fracture in the whole sample (p<0.001). In addition, the results showed that the crowns in group 1 exhibited higher loading values than those in group 2. The mean loading capacity in group was 911.2 N ± 614.7 N. Two locations of crack and fracture were registered: occlusal and marginal. No statistical association was observed between the two groups for the location of cracks or fractures. Conclusions: The feather-edge crowns with a 0.5 mm margin thickness had a higher loading capacity than those with a 0.4 mm. However, the latter supports loads that exceed occlusal force in the oral cavity suggesting that 0.4 mm feathered edge MZCs may be a valid and less invasive alternative to thicker margins. The novel load-to-fracture AET setup proved effective in detecting early crack initiation, suggesting it as a promising method for assessing the mechanical properties of brittle materials prior to failure, potentially impacting the field of dentistry. However more advanced research is needed to enhance the accuracy of the proposed technique. Clinical implications: The examined MZC demonstrates the ability to withstand occlusal forces in a patient’s mouth, offering clinical practitioners the option of embracing minimally invasive dentistry through the use of 0.4 mm feather-edge MZC in their treatment options. Furthermore, the positive results from the innovative acoustic emission testing technique, facilitating early crack detection, indicate a promising future for studying the behavior of brittle materials in dental laboratory testing.

Impact of Shortening Real Driving Emission (RDE) Test Trips on CO, NOX, and PN10 Emissions from Different Vehicles

Impact of Shortening Real Driving Emission (RDE) Test Trips on CO, NOX, and PN10 Emissions from Different Vehicles

The Acoustic Emission Testing in the Evaluation of Fracture Toughness of Brittle Materials.

Evaluating the fracture resistance of dental ceramics is essential for assessing their behavior. This study aimed to validate a custom load-to-fracture test for assessing fracture strength compared to a conventional method. Acoustic emission testing, a non-destructive (ND) lab test, was employed to evaluate the fracture toughness (FT) of brittle materials by capturing sound waves generated by crack formation in failing samples. A total of 130 samples, divided into three types (glass sheets, zirconia sheets, and monolithic zirconia crowns), were tested. The fracture loads were measured using both custom and conventional methods. The mean fracture loads for glass sheets were 650.46 N ± 110.38 (custom) compared to 691.41 N ± 155.92 (conventional). For zirconia sheets, the values were 95.25 N ± 7.78 (custom) vs 112.75 N ± 31.26 (conventional). Monolithic zirconia crowns showed mean fracture loads of 1108.99 N ± 327.89 (custom) compared to 1292.52 N ± 271.42 (conventional). Statistically significant differences were evident in all three types, indicating lower values with custom testing for all samples. The custom testing demonstrated an advantage in identifying cracks at lower loads, thereby enhancing the accuracy of fracture load values. Despite its limitations, the study suggests that the custom setup could be a viable alternative to conventional fracture load testing of brittle materials. However, further testing with more materials is recommended to enhance the results' accuracy and generalizability. The findings indicate that the custom load-to-fracture test can provide more accurate measurements of FT in dental ceramics, which is crucial for predicting their clinical performance and longevity. How to cite this article: Haddad C, Eng JG, Zoghbi AE. The Acoustic Emission Testing in the Evaluation of Fracture Toughness of Brittle Materials. J Contemp Dent Pract 2024;25(7):617-623.

Air Pollutant Emissions of Passenger Cars in Poland in Terms of Their Environmental Impact and Type of Energy Consumption

The increasing number of vehicles operating in Poland, especially passenger vehicles, justifies the need to conduct air pollution emission tests in the context of the impact of vehicles on the natural environment. Firstly, this article reviews the publications related to air pollutant emissions and passenger vehicles traveling on Polish roads. However, it presents a special method using advanced research equipment to determine air pollutant emissions. The above research methods are justified in implementing clean transport zones. Real Driving Emissions represent an essential procedure in the implementation of clean transport zones in Poland, verifying the actual emissions of air pollutants and modeling this phenomenon using the results of real air pollutant emissions. The results of this research state that establishing a link between a vehicle’s air pollutant emissions and its age can support making transport or delivery planning more sustainable and choosing less carbon-intensive means of transport to reduce the negative impact of transport on the environment. The scientific novelty of the proposed solutions is the verification of the actual emissions of Euro 6 vehicles and the modeling of air pollutant emissions as a function of speed and acceleration. The research results are included in this article and will become input data for further analysis in examining the impact of vehicle operating age on air pollution emissions. Consequently, the novelty of the present research also lies in its focus on the verification of the impact of operating age, particularly in the context of vehicles exceeding 15 years of age, on air pollutant emissions. By establishing a correlation between a vehicle’s air pollutant emissions and its operating age, it becomes possible to make transport or delivery planning more sustainable. Furthermore, the selection of less carbon-intensive means of transport can contribute to reducing the negative impact of transport on the environment.

Changes in Auditory Performance Following a Virtual Reality Music Concert.

The purpose of this study was to evaluate threshold and suprathreshold auditory risk from a newly popular platform of music concert entertainment; virtual reality (VR) headsets. Recreational noise exposure to music is the primary source of hearing hazard in young-adults, with noise doses of in-person concert venues and music festivals well in excess of the recommended daily exposure recommendation from the National Institute for Occupational Safety and Health. While research on the relationship between personal music players and noise-induced hearing loss risk is abundant, no study has yet evaluated noise-induced hearing loss risk from VR headsets, which are newest to the commercial market at this time. Thirty-one young-adult participants (18 to 25 years) with normal-hearing sensitivity (0 to 16 dB HL) experienced a VR music concert and participated in three data collection timepoints: Session A preexposure, Session A post-exposure, and Session B post-exposure. Participants underwent baseline testing for audiometry (0.25 to 20 kHz), distortion product otoacoustic emission testing (1 to 10 kHz), and Words-in-Noise testing. Participants then wore a commercially available VR headset (Meta Quest 2) and experienced a freely available online VR music concert (via the video-sharing website "YouTube"). The VR music concert duration was 90 min set to maximum volume, which yielded an average sound level equivalent of 78.7 dBA, max sound level of 88.2 dBA, and LC peak sound level of 98.6 dBA. Post-exposure testing was conducted immediately at the conclusion of the VR concert, and again within 24 hr to 1 week after the exposure. Participants also answered a questionnaire that estimated noise exposure history (National Acoustics Laboratory "Noise Calculator"). Post-exposure deficit was not observed in DPOAEs or Words-in-Noise score (p's > 0.05). However, statistically significant temporary post-exposure deficit was observed in audiometry at 4, 8, and 12.5 kHz (p's < 0.05) (mean differences: 2 to 3 dB HL). Twenty-four hours and 1-week post-exposure measurements revealed no permanent changes from baseline measurements (p's > 0.05) aside from one spurious difference at 12.5 kHz. Males tended to exhibit a significantly higher noise history score on average than females. The primary, secondary, and tertiary sources of noise hazard history in this young-adult cohort included amplified music. These preliminary data suggest that VR music concerts-which are likely to produce a substantially lower noise dose than in-person music concerts-may still be capable of producing at least slight, temporary threshold shifts on the order of 2 to 3 dB HL. Future research should include VR headsets in personal music player risk assessment, as the VR music concert platform is increasing rapidly in popularity among young-adults.

NOx reduction scenarios under real-world driving conditions for light-duty diesel vehicles

This study analyze analyzes the impact of stringent emissions regulations on future NOx reductions. Using scenario analysis, NOx emissions of diesel light-duty vehicles from 2019 to 2040 are estimated using emission factors from real driving emissions data. The baseline scenario assumes current regulations will be maintained, while other scenarios assess the impact of implementing specific Euro standards as final regulations. If Euro 5 regulations are implemented by 2040, cumulative emissions will increase by 229.1 % compared to the baseline scenario. Implementing Euro 6 a/b/c regulations will increase by 156.2 %, while Euro 6 d-temp and Euro 6 d regulations will increase by 8.4 % and 0.7 %, respectively. These findings highlight the significant contribution of real driving emission test introduced with Euro 6 d-temp to NOx reduction. Furthermore, they indicate that Euro 6 d regulation has already achieved emission levels similar to those of the upcoming Euro 7 regulation.

An Experimental Assessment Using Acoustic Emission Sensors to Effectively Detect Surface Deterioration on Steel Plates

Acoustic emission (AE) testing is used for the continuous evaluation of structural integrity and the monitoring of damage evolution in structural components and materials. During operation, the environmental and loading conditions of metal structures can result in corrosion and surface wear damage. The early detection of surface degradation flaws is crucial, as they can serve as local stress concentration points, leading to crack initiation and failure. In this work, the effectiveness of AE in monitoring corrosion and surface wear flaw formation was experimentally evaluated. AE sensors were installed on steel test plates during the artificial induction of corrosion and surface wear in order to detect and record the generated AE signals. Corrosion-related AE signals typically exhibit low amplitude, count, and energy values. The direct detection of active corrosion can be challenging in noisy environments, but it can be carried out under certain conditions using dedicated AE sensor groups. Surface-wear-related AE signals exhibit high amplitude, energy, and count values, with long duration values that are associated with wear and grinding conditions. It was found that AE sensors can be utilised to detect corrosion and surface degradation events. The effectiveness of the AE method in detecting surface degradation in noisy environments can be improved by implementing a filtering methodology. This will limit the recording of noise-related signals that can mask out actual surface degradation AE events.

Research on input parameter optimization for NOx deep learning prediction model

Optimizing the input parameters for NOx prediction model is instrumental in enhancing the precision and efficacy of the prediction model. This paper focuses on the input variables of the data-driven diesel engine NOx prediction model. According to the diesel engine NOx generation mechanism, at first relevant variables are selected, then the similarity method and parameter sensitivity method are compared to optimize the input variables. Firstly, this paper conducted a real-road emission test of a heavy-duty diesel vehicle, and proposed a data-driven deep learning model for predicting diesel engine NOx emissions based on the experimental data. The experimental data were processed using an Attention-Mechanism based Convolutional Neural Networks-Long Short-Term Memory (AM-CNN-LSTM) model. Subsequently, input parameters were selected according to the sensitivity weights assigned to each parameter in the preliminary model. This approach refined the modeling data and excluded variables not pertinent to NOx emission prediction. The AM-CNN-LSTM model prediction performance has been improved with 2% increase of model R2 as well as the model training time is reduced by 23%, and the types of parameters required to train the model are reduced by 50%. It accomplished this by effectively reducing data dimensions, discarding non-essential variables for NOx prediction, and diminishing computational complexity. Six input parameters were identified as pivotal in reconstructing the modeling data for accurate NOx prediction: engine speed, torque, EGR valve position, exhaust flow rate, air mass flow rate, and oil temperature. In optimizing the NOx prediction model, it is crucial to determine an optimal number of input parameters. Excessive parameters do not enhance model accuracy, while an insufficient number impairs the model’s ability to precisely emulate the NOx generation process, leading to diminished predictive accuracy.

Assessing the influence of actual LNG emission factors within the EU emissions trading system

The shipping sector has been incorporated into the European Union Emissions Trading System (EU-ETS). Undoubtedly, the carbon emission factor is a critical consideration when determining carbon allowances in the EU-ETS, known as EU Allowances (EUAs). In this study, an all-performance carbon emission test was conducted on a marine LNG engine to investigate the differences between the actual carbon emission factor and the reference value. It was observed that the actual carbon emission factor is smaller than the reference value. The test results indicate a discrepancy of approximately 3%, resulting in potential savings of 10,000 to 20,000 dollars in EUAs for a ship consuming 2000 tonnes of LNG fuel annually. Furthermore, variations in the carbon emission factor were observed under different engine operational conditions, fluctuating by around 2% at constant revolutions per minute (RPM). This suggests the need for more suitable emission testing methods to accurately reflect actual emissions and better achieve emission control goals.

Damage-tolerance design for composite high-pressure hydrogen vessels when AE testing is applied

An approach was proposed to design high-pressure composite hydrogen vessels for fuel cell vehicles with damage tolerance. In addition, a stacking-sequence optimization method was developed, which was built upon the damage tolerance design. A no-growth approach, damage categorization, and residual strength requirements were proposed for the damage-tolerance design method for highpressure hydrogen vessels, which were implemented in the damage-tolerance design method for composite aircrafts. The initial burst pressure was set at 180% of normal working pressure (NWP) assuming that the structural health monitoring (SHM) system with acoustic emission (AE) testing would immediately detect the occurrence of fiber breakage. Stacking-sequence optimization was then conducted to minimize vessel thickness and meet the residual strength requirements. The results show that the thickness of the vessel can be reduced by introducing a damage-tolerant design. Moreover, the proposed method for an optimal design based on the damage-tolerance design method is effective.

Monitoring of GFRP pipelines in Power Plants using acoustic emission testing

In coal-fired power plants, the flue gas is transported through fibreglassreinforced pipelines to cooling towers during the combustion of the respective raw material, which often serve as a marker for a power plant in the landscape. These glass-fibre reinforced pipelines are located at great heights and can have very large diameters. Up to now, testing has been carried out as part of inspections during planned shutdowns and is associated with corresponding costs. The article discusses the use of acoustic measurement methods based on a 4-month installation at the Niederaußem power plant. Measurement results based on the acoustic emission analysis were shown. For the acoustic emission measurements, a repaired site was instrumented and different parameters like hit/event rates, acoustic energies as well as weighted peak frequencies of the acoustic signals were recorded over the monitoring period of 4 months at power plant Niederaußem. In a second power plant Neurath a 5-month AE monitoring were carried out. This measurement results were discussed as well.

Failure monitoring and classification from acoustic emission tests on impact-damaged hydrogen composite pressure vessels

Composite overwrapped pressure vessels (COPV) for hydrogen will play an important role in emission free mobility and energy storage. The DELFIN project (2018 – 2022) was set up with the goal of developing improved COPVs that are lighter, cheaper and more durable. A key aspect of this project was to conduct full-scale impact tests with different gas pressure levels that were used to evaluate the vessels’ crash performance and to verify numerical impact simulations. These tests were followed by controlled pressure experiments until the burst pressure was reached. The procedure was monitored with acoustic emission testing (AT) and subsequent computer tomography (CT). The residual COPV stability and the AT results are compared to different scenarios regarding the impact energies and impact angles. The event localization from AT shows a clear correlation of the emitted energy with the damaged areas. We classify the recorded signals into groups that can be related to the failure mechanism and compare those to the pressure evolution before failure of the COPV. All tests indicate that large impact energies lead to a significant reduction of the burst pressure of COPVs, whereas a higher internal pressure can have a stabilizing effect that reduces the damaging effect.

Performance analysis of dual-fuel engines using acetylene and microalgae biodiesel: The role of fuel injection timing

This study evaluates the impact of varying fuel injection timing (FIT) and dual-fuel modes on the performance and emissions of a compression ignition (CI) engine under different load conditions. The biodiesel used was derived from Chlorella protothecoides microalgae through a two-step transesterification process, and its elemental composition was characterized using gas chromatography-mass spectrometry (GC-MS). Acetylene gas was introduced into the engine intake manifold at a rate of 3 L per minute (LPM), while a blend of 20 % methyl ester from Chlorella protothecoides (B20 MEOA) served as the primary injected fuel. To predict engine performance and emission characteristics, advanced machine learning models were employed and evaluated using four statistical criteria, including R-squared, mean absolute error (MAE), and mean squared error (MSE). Experimental results indicated that the optimal configuration involved a dual-fuel mode combining B20 MEOA with acetylene gas and an advanced FIT of 25° before top dead center (bTDC). Performance analysis revealed that under all load conditions, the specific fuel consumption (SFC) decreased by 7.3 %, while brake thermal efficiency (BTE) increased by 1.6 % compared to conventional diesel. Emission testing showed a 7.6 % rise in nitrogen oxide emissions, alongside significant reductions in unburned hydrocarbons (12.5 %), carbon monoxide (25.6 %), and smoke intensity (7.5 %) relative to standard diesel operation. Optimization of the engine parameters ensured that key metrics, such as brake power (BP) and brake-specific fuel consumption (BSFC), remained within acceptable limits. The random forest model outperformed other machine learning models, demonstrating superior accuracy in predicting performance and emissions across all statistical measures. This study underscores the potential of combining advanced biodiesel blends with optimized FIT strategies to improve engine efficiency and emissions control, offering a promising approach for sustainable dual-fuel engine operations.

Acoustic emission for monitoring of fatigue damage in concrete elements of wind turbine towers

Wind energy has become an important player in the energy transition in Germany. Towers of onshore wind turbines are often designed as hybrid structures: the lower part is made of prestressed concrete whereas the upper part is made of steel tubes. The tall structures are permanently subjected to dynamic loads. A research project of BAM as part of the joint project WinConFat-Structure focusses on the development of techniques to monitor fatigue damage evolution in the concrete part. Results of a previous project show that a combination of ultrasonic and acoustic emission testing can give an indication for critical conditions near the end of the fatigue life of the concrete. In the ongoing project acoustic emission sensors have been installed at the base and at the transition piece between concrete and steel of a hybrid wind turbine tower. Beside of acoustic emission measurement the sensor spacing allows for measuring the concrete ultrasonic velocity along the circumference in both levels. Additional measurements like strain, temperature, inclination, or acceleration allow for comparison of environmental loads and change of acoustic properties of the concrete. The paper focusses on first acoustic measurements recorded since December 2023 in comparison to operating data of the wind turbine.

Implementation of An Application-Based Motor Vehicle Exhaust Emission Level Detection System

Currently, air conditions on earth are getting worse over time due to the impact of air pollution. One example of air pollution is motor vehicle exhaust emissions. Exhaust gas emissions are the result of combustion residue in motor vehicle engines that use fuel. Motor vehicle exhaust emissions contain carbon monoxide (CO), hydrocarbons (HC), carbon dioxide gas (CO2) which have a negative impact on the environment and living creatures. This research will create a motor vehicle exhaust emission detection device. In this design, an Arduino microcontroller was used and the manufacture of this tool used an MQ-7 gas sensor to detect carbon monoxide (CO) gas, an MQ-2 sensor to detect hydrocarbon gas (HC), and an MQ-135 to detect carbon dioxide (CO2) gas. The emission test results will be sent to the application, this data includes plate number, vehicle type, vehicle brand, vehicle year and emission test results. The results of the carbon monoxide (CO) gas sensor calibration test taken from 5 data showed an error of 5.51%. The results of the hydrocarbon (HC) gas sensor calibration test taken from 5 data showed an error of 4.23%. The results of the carbon dioxide (CO2) gas sensor calibration test taken from 5 data showed an error of 1.06%. In the implementation of the tool and application, the test results were obtained for 15 vehicles. Where the highest hydrocarbon (HC) gas content value was 412 ppm, the highest carbon monoxide (CO) gas content value was 1.48%, and the highest carbon dioxide (CO2) gas content value was 21.4%.

Investigation of high percentage of dimethyl ether on biodiesel usage in a diesel engine

Demand for cleaner energy sources both as additive and alternative fuels that can substitute or contribute to the usage of conventional fuels is growing. Researchers have mainly focused on improving or finding a renewable fuel from vegetable oil or addition of chemicals and alcohols for IC engine. This study analyzed the effects of a high percentage of dimethyl ether (DME) combined with biodiesel in a diesel engine. Transesterification method was selected for conversion of pure safflower oil to biodiesel. DME was blended with biodiesel at concentrations of 50% and 25% on a volume basis, respectively. Engine performance and emissions tests demonstrated that the thermal efficiency values were increased at high load operation when the engine was fueled with high percentage of DME. Furthermore, compared to conventional diesel, there has been a notable decrease in NOx emissions. Nevertheless, the introduction of DME blend had negligible effects on CO2 emissions. However, when using a high ratio of DME blend, HC emissions were found to increase, whereas a low ratio of DME blend resulted in decreased HC emissions. Apart from these, some irregularities were observed both on heat release rate and cylinder pressure especially for 50% of DME usage. Finally, the values for both brake-specific fuel consumption and mass fuel of DME-blended fuels were deteriorated.