Emission Testing Research Articles

Effect of Graphene Nanoplatelets as Lubricant Additive on Fuel Consumption During Vehicle Emission Tests

Effect of Graphene Nanoplatelets as Lubricant Additive on Fuel Consumption During Vehicle Emission Tests

Experimental investigation on mechanical properties and strength criteria of frozen soft rock.

Excavation of underground engineering structures involving deeply buried water-rich soft rocks is generally carried out using the artificial freezing method. A series of undrained uniaxial and triaxial shear and creep tests were conducted on soft rocks under different confining pressures (0, 0.2, 0.5, and 1.0 MPa) at different freezing temperatures (room temperature, -5°C, -10°C, and -15°C). Test results indicate that the frozen soft rocks show strain softening characteristics. The stress-strain curve changes from a straight line to a curve as deviatoric stress constantly increases, while it decreases abruptly after the deviatoric stress reaches the peak and is slightly affected by the freezing temperature. At the same temperature, shear strength increases at a rate of 5.6 MPa/°C with increasing confining pressure; as freezing temperature decreases, the shear strength increases at 0.34 MPa/°C, and cohesion increases at 0.6 MPa/°C. Under the same confining pressure, the failure strain of soft rock decreases with the decrease of temperature. The Mohr-Coulomb (M-C) criterion can accurately describe the failure process of frozen soft rocks in the pre-peak stage, with a correlation coefficient greater than 0.98. Within the test stress range, soft rocks display attenuated stable creep deformation. Acoustic emission (AE) tests were conducted to further verify that the soft rocks show shear failure under load, with a shear plane showing an angle of 45° with the horizontal. The research findings provide technical support and theoretical reference for studying rock mechanical properties as well as for designing and carrying out underground freezing of rocks in a low-temperature environment.

Newborn screening for deafness genes with cord blood-based multicolour melting curve analysis.

The purpose of the research was to examine the prevalence rates of screening for genetics and hearing simultaneously in neonates and provide scientific evidence for the beneficial application of newborn screening in the Southeast China population. Between June 2015 and March 2023, 27,843 newborns were enrolled in the study. All participants were screened by otoacoustic emissions at 2days of age. Fifteen variant hotspots in the four deafness genes (GJB2, GJB3, SLC26A4 and MTRNR1) were detected using multicolour melting curve analysis. Newborn screening data were also analysed. In otoacoustic emissions testing, 244 newborns (0.88%) failed the secondary screening. According to genetic testing, 1307 (4.69%) newborns had at least one variant. GJB2 c.235delC (2.34%) and SLC26A4 c.919-2A>G (0.91%) were the major deafness-related variants in the Wenzhou area of Southeast China. In addition, a difference in the number of newborns with variants was observed between the passed and failed groups. The difference in the positive rate between the two groups was statistically significant (χ2=274.969, P<0.05). Newborn screening for deafness genes by cord blood-based melting curve analysis can be applied to genetic counselling, prenatal diagnosis, and genetic screening of newborns with sensorineural hearing impairment with an unknown cause. The new PCR melting curve analysis approach is more effective and more convenient than SNaPshot and MS-based assay testing. Furthermore, it has a lower cost and is more suitable for clinical testing.

Emission Reduction Characteristics of Heavy-Fuel Aircraft Piston Engine Fueled with 100% HEFA Sustainable Aviation Fuel.

With the projected expansion of the general aviation sector and recent breakthroughs in sustainable aviation fuels (SAF), accurately measuring emissions from novel aircraft engines powered by SAF is paramount for evaluating the role of aviation industry in emission reduction trends and environmental consequences. Current SAF research primarily centers on low blend ratios, neglecting data on 100% SAF. This study bridges this gap by experimentally determining emissions indices for gaseous pollutants (CO, CO2, HC, NOx), total particulate matter (PM) counts and sizes, and non-volatile particulate matter (nvPM) number and mass concentrations from a heavy-fuel aircraft piston engines (HF-APE) using hydroprocessed esters and fatty acids-derived SAF (HEFA-SAF), adhering to airworthiness-standard sampling and measurement protocols. Additionally, nvPM morphology and structure are analyzed to auxiliarily assess the emission reduction. The results demonstrate that HEFA-SAF stands out for its marked reduction in both CO and HC gaseous pollutant compared to RP-3 aviation kerosene (RP3), as well as effectively reduces PM emissions compared to Diesel and RP3 across all load conditions. Notably, HEFA-SAF significantly curbs the generation of both nucleation-mode and accumulation-mode PM. Specifically, the use of HEFA-SAF leads to a 43% and 24% decrease in average nvPM number concentration, and a 65% and 53% reduction in average nvPM mass concentration respectively, compared to Diesel and RP3. At 50% load, nvPM produced by HEFA-SAF exhibits distinct nanostructural properties, characterized by fewer exposed pores and active sites within agglomerated particles. Rigorous emission testing has conclusively validated the substantial benefits of 100% HEFA-SAF in reducing emissions, offering a compelling rationale for the development of airworthiness regulations and environmental oversight frameworks designed to foster sustainable aviation practices.

Mechanical Behavior and Failure Mechanism of Rock–Concrete Composites Under the Coupling Effect of Inclined Interface Angle and Ground Temperature

Surrounding rock and lining are composite structures with asymmetric mechanical properties. Understanding the mechanical properties and failure characteristics of rock–concrete composites is crucial for gaining insights into the mechanisms that induce disasters in deep-underground environments. Uniaxial compression and acoustic emission tests were conducted on rock–concrete composite specimens cured at temperatures of 20 °C, 40 °C, 60 °C, and 80 °C, with interface angles of 15°, 30°, 45°, 60°, 75°, and 90° respectively. The results indicated that the specimens’ strength decreased at increasing geothermal temperatures. The composites with an 80 °C curing temperature and a 60° interface angle exhibited the lowest strength. A higher geothermal temperature significantly reduced the number of cracks in the concrete component during composite failure and mitigated the influence of the inclined interface angle. The failure modes of the specimens include axial penetration splitting, interface shear, Y-shaped fracture, and interface splitting–concrete shear failure. Finally, a model relating the strength of the rock–concrete composite to the inclined interface angle and the geothermal temperature was derived and verified against the experimental results with a relative error of 9.8%. The findings have significant implications for the safety and stability of tunnels in high-temperature conditions.

Fabrication of Burner Rig and Testing of Thermal Barrier Coatings

This research explores the design and fabrication of burner rig to test Thermal Barrier Coatings (TBCs) aimed at enhancing the longevity and performance of gas turbines. Gas turbines, commonly used in aviation and power generation, face extreme operating conditions with high temperatures and thermal gradients that can lead to significant component damage. TBCs, ceramic coatings applied to engine components, play a crucial role in providing thermal insulation and mitigating thermal fatigue, oxidation, and thermal shock. The study involved designing a burner rig, modeled in Solid Works and fabricated from mild steel, to replicate the high temperature environment of gas turbines. The experimental setup was enhanced by the precise machining of components like the aluminum alloy 6061 substrate, achieved through EDM wire cutting. The study demonstrates how factors such as material selection, bond coat and topcoat thickness, porosity, and thermal cycling significantly influence TBC performance. Testing with the burner rig showed that TBCs can greatly enhance engine efficiency and lifespan by providing robust thermal insulation. Advanced monitoring techniques, including infrared thermography and acoustic emission testing, were employed to evaluate the behavior of TBCs under thermal cycling. The findings underscore the need for balancing thermal insulation with thermal stress resistance to maximize coating performance. This research serves as a foundation for further advancements in TBC materials and testing methodologies, with the goal of enhancing the operational efficiency, longevity, and environmental sustainability of gas turbine engines.

Evaluating the feasibility of estimating particulate mass emissions of older-model diesel vehicle using smoke opacity measurements

Real-world emissions of particulate matter (PM) and smoke opacity were studied for an older-model diesel pickup truck during four types of driving tests, namely fixed-point test, snap-acceleration test, road test, and hill road test (uphill/downhill). A portable emissions measurement system (PEMS) and an opacimeter were used to measure real-time concentrations of PM and smoke opacity, respectively, and simultaneously. Correlation analysis showed a significant positive association between PM and opacity, suggesting the feasibility of using an opacimeter to estimate PM mass emissions from diesel vehicles. Additionally, regression analyses were performed to evaluate the relationship between opacity and PM mass concentration. The results of this study indicate that PM emission concentrations from older-model diesel vehicles can be estimated with a reasonable accuracy by using a smoke opacimeter, which is a relatively simple and cost-effective method of emission testing, as an alternative to sophisticated PM measurement instruments.

Design and application of CNN for emission detection through thermal imagery

Motorcycle exhaust emissions (EE) that do not meet regulatory standards present a significant environmental and public health issue, particularly given the rising number of motorcycles in densely populated areas. These emissions release pollutants such as carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx), which contribute to poor air quality and have adverse effects on human health. Traditional emission testing methods using gas analyzers, while commonly used, face limitations such as sensitivity to environmental fluctuations, the necessity for frequent recalibration, and an intensive testing process requiring specialized expertise. This study addresses these issues by developing an innovative method for emission detection using Convolutional Neural Networks (CNN) applied to thermal images of motorcycle exhausts. The research method involves five key stages: data acquisition, dataset formation, CNN model design and training, model testing, and validation. Thermal images were gathered from 27 motorcycles, representing various brands and engine configurations common in Indonesia, and each image set included 100 samples for both emission-compliant and non-compliant categories. By analyzing thermal patterns, the CNN model was trained to accurately detect combustion patterns indicative of emission status based on the lambda value. This approach enables the model to generalize across different motorcycle models, offering practical adaptability for widespread implementation. The results demonstrate that the CNN model delivers high predictive accuracy, precision, recall, and F1-score, making it a robust tool for assessing motorcycle emission compliance. This CNN-based approach provides a practical solution for real-time, large-scale emission monitoring and regulatory enforcement, reducing dependency on conventional methods. Its scalability and adaptability position it as a valuable advancement in emission monitoring technology, with significant potential for supporting environmental standards and improving air quality management

Quantitative Analysis of Basalt Damage Under Microwave Radiation Utilizing Uniaxial Compression and Nuclear Magnetic Resonance (NMR) Experiments

Microwave-assisted rock breaking is recognized as an effective technology for reducing tool wear and enhancing rock-breaking efficiency. In this study, basalt rock was irradiated with a microwave power of 3 kW and 6 kW for 30 s, 60 s, 90 s, and 120 s. Subsequently, uniaxial compression, uniaxial loading and unloading, and acoustic emission tests were performed. The damage evolution of basalt was assessed through non-destructive acoustic testing methods and nuclear magnetic resonance (NMR) techniques. The results showed that the P-wave velocity, uniaxial compressive strength (UCS), and modulus of elasticity (E) exhibited varying degrees of deterioration as the microwave radiation time increased. An increase in microwave radiation time and power led to heightened acoustic emission activity in basalt and a significant rise in the proportion of shear cracks during uniaxial compression. From an energy perspective, microwave irradiation decreased the energy storage capacity of the basalt specimen prior to its peak point, with increased power and duration. At a microscopic level, porosity and the macroporous fractal dimension increased with extended microwave radiation time and power, indicating that microwave irradiation facilitated the growth of larger fractal pore structures. The findings of this study offer scientific insights for the application of microwave-assisted rock crushing.

Application of Machine Learning to Predict CO2 Emissions in Light-Duty Vehicles.

Climate change caused by greenhouse gas (GHG) emissions is an escalating global issue, with the transportation sector being a significant contributor, accounting for approximately a quarter of all energy-related GHG emissions. In the transportation sector, vehicle emissions testing is a key part of ensuring compliance with environmental regulations. The Vehicle Certification Agency (VCA) of the UK plays a pivotal role in certifying vehicles for compliance with emissions and safety standards. One of the primary methods employed by the VCA to measure vehicle emissions for light-duty vehicles is the Worldwide Harmonized Light Vehicles Test Procedure (WLTP). The WLTP is a global standard for testing vehicle emissions and fuel consumption, and sensors are crucial in ensuring accurate, real-time data collection in laboratories. Using the data collected by the VCA, regression machine learning models were trained to predict CO2 emissions in light-duty vehicles. Among six regression models tested, the Decision Tree Regression model achieved the highest accuracy, with a Mean Absolute Error (MAE) of 2.20 and a Mean Absolute Percentage Error (MAPE) of 1.69%. It was then deployed as a web application that provides users with accurate CO2 emission estimates for vehicles, enabling informed decisions to reduce GHG emissions. This research demonstrates the efficacy of machine learning and AI-driven approaches in fostering sustainability within the transportation sector.

Nonlinear interaction and compounding factors of vehicle parameters influencing exhaust pollution.

One of the main causes of air pollution, particularly in large cities, is vehicles due to it continued use of hydrocarbon fuels. The understanding of nonlinear interactions of vehicle parameters uncovers more realistic relationships for enhancing formulation of strategies to address vehicle-related pollution. Thus, the study aims to evaluate the interaction and quadratic effect of vehicle parameters on Hydrocarbon (HC), Carbon dioxide (CO2), Carbon monoxide (CO), and Nitrogen oxide (NOx) emissions. The SV-5Q Vehicle Exhaust Gas Analyzer was used to collect emission concentrations data from one thousand and two (1002) light-duty petrol vehicles at three (3) government-accredited vehicle inspection sites in Accra, Ghana. Pollution control devices, maintenance frequency, and vehicle age were also collected. The linear regression analysis revealed that vehicle age showed a positive linear relationship with CO emissions. Maintenance frequency, on the other hand, demonstrated a negative linear relationship with both CO and HC emissions. The interaction between vehicle age and maintenance frequency positively impacted CO and HC emissions, while the interaction between vehicle age and emission technology had a negative effect on CO. Additionally, the combined effect of frequency of maintenance and emission technology significantly reduced CO emissions but increased HC emissions. Notably, the quadratic effect of vehicle age positively influenced CO emissions. Similarly, CO, HC, and NOx emissions were positively correlated with the squared effect of emission technology. Stricter emissions standards, encouraging frequent maintenance and testing of vehicular exhaust emissions, and doing away with over-aged vehicles are recommended to control and reduce vehicular exhaust emissions.

Self-Healing of Microcracks and Scratches in a Carbon-Fiber Reinforced Epoxy Vitrimer by Conventional or Remote Heating.

This study addresses the extension of the service life of carbon-fiber reinforced epoxies by inducing thermal healing of microcracks through the use of a vitrimer as a polymeric matrix. Our aim was to explore the feasibility of using a blend of selected carboxylic acids (citric, glutaric, and sebacic acids) and commercial monomers to design a matrix specifically developed for technological implementation in composites with the ability of intrinsic repair of microcracks under moderate (even remote) heating treatments. The selection of the formulation (the acid blend, catalysts, and monomers) was the result of an exhaustive prescreening analysis of processing requisites and final properties. The glass transition temperature of the cured vitrimer composite measured by differential scanning calorimetry (DSC) is 94 °C, a value lying in the range required for several technological applications, whereas stress relaxation to (1/e) of the initial value took ∼4.7 h at 180 °C and only 1.1 h at 200 °C. Composites containing 50 vol % of carbon fibers could be successfully prepared by compression molding. Acoustic emission tests proved the formation and partial healing of microcracks during tensile tests performed until 350 MPa. Surface scratches could also be healed by remote activation using near-infrared irradiation (NIR). These first results under nonoptimized thermal cycles are a proof of concept that microcrack and scratch healing can be produced in high glass-transition temperature epoxy-based carbon-reinforced composites.

Changes in Plasma Levels of Prestin and Otolin-1 in Dental Students.

Dentists and dental professionals report a high prevalence of noise-induced hearing loss (NIHL) and related symptoms. Chronic exposure to high-frequency dental instrument sounds, which can damage the outer hair cells (OHCs) of the cochlea, is strongly linked to their NIHL. Similarly, dental students in teaching clinics often report symptoms associated with NIHL. In this study, we measured plasma levels of prestin and otolin-1, two biomarkers associated with inner ear health, in first-year (D1) and third-year (D3) dental students. D1 students were selected for their relatively short exposure to dental clinics, while D3 students represented a group with substantial cumulative exposure. First-year (M1) medical students, who have no exposure to dental instruments, served as the negative controls, while dental faculty, many of whom are diagnosed with NIHL or self-report hearing problems, served as the positive controls. Thirty-one students (D1=11, D3=8, M1=12) and 10 dental faculty volunteered for the study. Participating students completed an online survey about their hearing health, exposure to excessive sounds within and outside school, and use of hearing protection. Sound levels of medical Osteopathic Manipulative Medicine (OMM) and dental Simulation (SIM) labs while in session were recorded with a calibrated sound meter. Plasma levels of prestin and otolin-1 were quantitated using commercial ELISA kits. The sound level of in-session OMM lab was significantly higher (72.64 ± 1.69 dBA) than SIM lab (65.37 ± 3.97 dBA). Both medical and dental students experienced similar exposure to outside school noises; however, dental students had significantly longer exposure to high-frequency dental instrument sounds in the SIM lab (12.3 hours/week; 74.93-80.51 dBA). Plasma prestin levels were lowest in D3 students (559.88 ± 24.91 ng/ml), followed by D1 students (576.27 ± 71.44 ng/ml). Negative control M1 students had higher levels (675.73 ± 90.23 ng/ml), while the positive control dental faculty group exhibited the highest prestin levels (727.71 ± 128.65 ng/ml). Prestin levels in D3 students were significantly lower than those in M1 students, and the dental faculty group had significantly higher prestin levels than both D1 and D3 students. No differences in otolin-1 levels were observed among the groups. Our finding that D3 students, with greater experience using dental instruments in the SIM lab, exhibited the lowest plasma prestin levels may indicate a protective mechanism by the OHCs, downregulating its expression to reduce the risk of NIHL. This is in line with the findings in the dental faculty, who self-reported NIHL or hearing problems and exhibited the highest prestin levels. The lack of changes in plasma otolin-1 levels across groups, combined with students self-reporting excellent hearing health, may offer alternate view of subclinical inner ear damage among dental students. Future studies incorporating audiometry and otoacoustic emission tests along with the inner ear biomarkers may provide better understanding of NIHL in dental students.

Polymer Capsules with Volatile Organic Compounds as Reference Materials for Controlled Emission.

Encapsulation of volatile organic compounds (VOCs) that could evaporate at a defined rate is of immense interest for application in emission reference materials (ERMs). Polyurethane/polyurea microcapsules with various VOC active ingredients (limonene, pinene, and toluene) were successfully produced by interfacial polymerization with Shirasu porous glass membrane emulsification in a size range between 10 and 50 μm. The effect of surfactant, VOC, monomer(s) type, and ratio has a great effect on the formulation process and morphology of capsules. The type of VOC played a significant role in the encapsulation efficiency. Due to the difference in vapor pressure and VOC/water interfacial tension, the formulation for encapsulation was optimized for each individual VOC. Furthermore, to achieve effective stability of the large droplets/capsules, a combination of ionic and nonionic surfactants was used. Optical and scanning electron microscopy, Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), were used to characterize the optimized microcapsules. The results showed that the obtained microcapsules exhibited a spherical shape and core-shell morphology and featured characteristic urethane-urea bonds. The amount of encapsulated VOC ranges between 54 and 7 wt %. The emission tests were performed with the help of the emission test chamber procedure (EN 16516). The limonene-loaded polyurethane/polyurea microcapsules show a change in emission rate of less than 10% within 14 days and can be considered as a potential candidate for use as an ERM.

Effect of crack defects on interlaminar shear properties of cross-laminated timber (CLT)

ABSTRACT Cross-laminated timber (CLT) has become one of the most popular engineering wood products in construction because of its excellent physical and mechanical properties. In this study, the short-span three-point bending test combined with acoustic emission test was used to study the effect of cracks on the inter-layer shear properties and fracture path of CLT. Crack length and crack location was used as influencing factors. Macro and micro failure patterns are analysed. The results show that the crack length had significant effects on the interlaminar shear strength and the initial failure load. The load-strain curve and acoustic emission location fracture paths were characterised by a rolling-shear failure stage, an instability stage, and a tensile failure stage of the tensile-side outer layer of the CLT. With the increase of crack length, the initial-failure load and inter-layer-shear strength were reduced due to the variations of crack-initiation location and crack-propagation path. The research of this study has certain guiding significance for the safe use of CLT in practical engineering.

Towards predictive maintenance of hydrogen pressure vessels based on multi-sensor data

In this paper, we report on a sensor network for structural health monitoring (SHM) of Type IV composite overwrapped pressure vessels (COPVs) designed for hydrogen storage. The sensor network consists of three different SHM sensing technologies: ultrasonic guided waves (GW), acoustic emission (AE) testing, and distributed fiber optic sensors (DFOS). We present an experimental setup for a lifetime test, where a COPV is subjected to cyclic loading. Data from all sensors are collected and centrally evaluated. The COPV failed after approximately 60,000 load cycles, and the sensor network proved capable of detecting and localizing the damage even before the failure of the COPV. This multi-sensor approach offers significantly more channels of information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including artificial intelligence (AI)-based evaluation. This not only has a positive effect on operational costs but enhances safety through the early identification of critical conditions in the overall system in real-time. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin.

Dual fuel retrofit LNG for Indonesia’s Greenhouse Gas Strategy Case: Fulfilment of engine requirements on existing vessels in accordance with class requirements

Abstract The global maritime industry is transitioning towards sustainability to meet stringent environmental standards under IMO’s MARPOL Annex VI and the Paris Agreement. LNG emerges as a promising marine fuel, significantly reducing sulfur oxides (SOx), nitrogen oxides (NOx), and particulate emissions compared to traditional fuels. Indonesia, a major LNG exporter, aims to utilize LNG domestically under its Long-term Strategy for Low Carbon &amp; Climate Resilience 2050. Adopting LNG in Indonesia’s maritime sector faces challenges, especially retrofitting existing diesel engines. Technical hurdles include ensuring engine compatibility, modifying fuel systems, and conducting comprehensive on-board testing due to limited infrastructure. Regulatory frameworks like Biro Klasifikasi Indonesia (BKI) Rules and the NOx Technical Code 2008 amendments provide the guidance for emissions compliance and testing. This paper discusses methodologies to overcome these challenges, emphasizing robust testing protocols and sea trials to validate engine performance and emissions under real-world conditions. Collaboration among stakeholders is essential to facilitate Indonesia’s transition to sustainable maritime practices. Future advancements in LNG technology and infrastructure will bolster Indonesia’s energy security and contribute to global emissions reduction targets in maritime transport.

Development and Characterization of an Environmentally Friendly Soy Protein-Modified Phenol–Formaldehyde Resin for Plywood Manufacturing

Most wood-based panels were currently prepared using aldehyde-based adhesives, making the development of natural, renewable, and eco-friendly biomass-based adhesives a prominent area of research. Herein, the phenolic resin was modified using a soybean protein isolate (SPI) treated with a NaOH/urea solution through a copolymerization method. The physicochemical properties, chemical structure, bonding properties, and thermal properties of the soybean protein-modified phenolic resin (SPF-U) were analyzed using Fourier transform infrared spectroscopy, thermogravimetric analysis, and formaldehyde emission tests. The results indicated that the molecular structure of the soy protein isolate degraded after NaOH/urea solution treatment, while the gel time was gradually shortened with increasing NaOH/urea solution-treated soy protein isolate (SPI-U) dosages. Although the thermal stability of the soy protein isolate was lower than that of the phenolic resin, the 20% SPF-U resin demonstrated better thermal stability than other modified resins. The PF modified with 30% SPI-U (SPF-U-3) exhibited the lowest curing peak temperature of 139.69 °C than that of the control PF resin. In addition, all modified PF resins exhibited formaldehyde emissions ranging from 0.18 to 0.38 mg/L when the SPI-U dosage varied between 20% and 50%, thereby meeting the E0 plywood grade standard (≤0.5 mg/L).

Uniaxial Compressive Failure Characteristics and Fractal Analysis of Mud–Sand Composite Rock Samples Based on Acoustic Emission Tests

In order to study the influence of rock combination types on their mechanical properties and failure characteristics, uniaxial compression tests of single rock samples and combined rock samples were conducted. Acoustic emission (AE) signals during the test process were collected, and the differences in AE signals of single rock samples and combined rock samples were studied based on the fractal theory. The results showed that the peak strength, elastic modulus, peak strain, and failure degree of the combined rock samples are all between those of the two single rock samples. The AE ringing count gradually increases with the loading process and suddenly increases to the maximum when the rock sample fails. During this process, the phase trajectory volume corresponding to the ringing count shows an evolution law of first decreasing and then increasing, while the correlation dimension corresponding to the ringing count signal shows an overall evolution law of first increasing and then decreasing. The results indicate that the phase trajectory volume, correlation dimension, and crack changes have a consistent dynamic change. Therefore, the phase trajectory and correlation dimension are effective tools to describe the pore change characteristics of rock combinations.

Non-Destructive Testing in Engineering

Non-destructive testing (NDT) methods are a group of tests allowing one to detect external (surface) as well as internal defects of a structure. It is mandatory to test any material prior to taking into use for engineering purpose or other uses; whether it meetsthe laid down requirement as perstandard specification or not to help in financial saving and prevent failure in service. This review article provides the earlier, recent advances and research about Non-Destructive Testing (NDT) such as Visual Inspection (VI), Liquid Penetration Testing (LPT), Magnetic Particle Inspection (MPI), Ultrasonic Testing (UT), Radiographic Testing (RT), Acoustic Emission Testing (AET), etc in various fields.