Conventional Testing Methods Research Articles

Efficacy of Unconventional Penetration Testing Practices

The financial and confidential cost of cyberattack has presented a significant loss to the organization and government where the privacy of worthless information has become vulnerable to cyber threat. In terms of efforts implemented to avoid this risk, the cyberattack continues to evolve, making the cybersecurity systems weekend. This has necessitated the importance of comprehensive penetration testing, assessment techniques, and tools to analyze and present the currently available unconventional penetration techniques and tactics to test and examine their key features and role in supporting cybersecurity and measure their effectiveness. The importance of cyberspace and its value make it an eminent target for attackers to exploit any vulnerability they may encounter in the respective system. Due to the cybersecurity risks, robust security measures need to be put in place to protect the system in question. Penetration testing is one such security measure that aims to uncover the security vulnerabilities in the system. Due to the dynamic aspect of cyberspace and technology, advanced or more unusual penetration testing mechanisms need to be employed to deal with the emerging vulnerabilities and security threats in cyberspace. This research explores and utilizes the conventional and unconventional penetration testing methods and identifies the study's main objectives to improve the current penetration testing techniques to increase security effectiveness and efficiency. It also calculates vulnerabilities and risks based on Common Vulnerability Scoring System (CVSS) scores and their impact on confidentiality, integrity, and availability. It proposes a Wi-Fi penetration testing approach based on Kali Linux. It also highlights the conventional and unconventional penetration testing approaches and justifies the essence of penetration testing over cyberattack cases. Due to the dynamic changes in technology, the conventional penetration testing method does not seem to be efficient to achieve its goal.

Measuring Dynamic Young’s Modulus of Low-Density Foam Concrete Using Resonant Frequency Test

Abstract Foam concrete is a cellular material mainly used in construction. Because of the low-strength feature of foam concrete, conventional concrete testing methods such as strength measurement are insufficient to characterize the key material attributes of foam concrete, especially for the low-density foam that is commonly designed for functional purposes. Inspired by the nondestructive feature of resonant frequency test, this study investigates the feasibility of using this method to evaluate the dynamic Young’s modulus of foam concrete, especially at the low-density range. Three variables that typically alter foam concrete mechanical properties are considered for evaluating the robustness of this approach—bulk density, water-to-cementitious ratio, and fly ash replacement ratio. The fundamental transverse frequency is found to be most suitable for determining the foam modulus. The experimental results demonstrate good accuracy of using this approach for measuring the dynamic Young’s modulus of different foam concrete samples. It is also confirmed that the foam modulus can be accurately designed if the bulk density of this material and solid modulus of its base cement paste are known.

AISI P20 steel under VHCF testing conditions

As more complex materials, structures and machines are created and applied in the modern world, the importance and complexity of fatigue testing methods become more indispensable for any mechanical project. This study focuses on an AISI P20 Steel in the Very High Cycle Fatigue (VHCF) regime, between 106 to 109 cycles, under different loading conditions: Tension-compression, pure torsion, and multiaxial tension/torsion. To reach such a considerable high number of cycles, no conventional fatigue testing method is energy and time reliable. Therefore, the present study conducted ultrasonic fatigue testing methods under 20kHz. Each stress type fatigue method was reached from its respective and different ultrasonic fatigue setup. Significant testing associated conditions and methodology, such as temperature, frequency and displacement, were carefully controlled, recorded, and made similar for all three methods. Stress-life results, material behaviour throughout fatigue testing and fracture surfaces for each stress type were compared for behaviour and damage correlation between pure torsion, tension-compression and the multiaxial combination of the two, tension-torsion. After all conducted fatigue tests, the obtained fatigue crack surfaces were analyzed by optical and scanning electron microscope (SEM) and compared between methods. Each tested method presented fatigue fracture surfaces with associated fracture morphologies similar to classic fatigue methods. The novel tension-torsion ultrasonic fatigue fractures showed both axial and torsion fatigue fracture dependencies and complexities, proving the induced stress field of interest.

Evaluation and Prediction of Fatigue Damage Initiation Life of CFRP Quasi-isotropic Laminate in the Very High Cycle Region

Carbon fiber reinforce plastics (CFRP) have been applied to structural materials of blades of wind turbines and aircraft turbine engines. These blades may suffer from very high cycle fatigue up to more than 107 cycles. However, conventional fatigue testing methods consume longer period in excess of 1 year for obtaining only 1 fatigue data in the very high cycle region. In this study, axial ultrasonic fatigue tests were conducted up to 109–1010 cycles. The results showed that no fatigue limit was found up to 109 cycles. Fatigue damage initiation life was compared with results obtained by a hydraulic serve fatigue testing machine to discuss the strain rate dependency and the feasibility of the prediction of fatigue damage initiation life by using a modified Walker model.

A review on the application of artificial intelligence in the mix design optimization and development of self-compacting concrete

Obtaining the strength-oriented mix design, balanced proportions of the additional constituents of Self Compacting Concrete (SCC) has remained a time-consuming, approximated, and repetitive work. In addition, the conventional evaluation methods have raised the challenges of accuracy and interpretation of the results, thereby limiting SCC applications. Nevertheless, in the past few years, researchers are working to overcome these challenges by incorporating the optimization methods and prediction models for the mix designing using artificial intelligence (AI) concepts and modern optimization methods, namely artificial neural network (ANN). This paper reviews the recent advances in integrating the AI methods to obtain mix design of the SCC ingredients and the strength prediction of the optimized mixtures. The review revealed that an appropriate AI-based optimization method could provide the optimum proportions of the varying constituents of SCC effectively and accurately. Moreover the AI-based methods supported the construction and utilization of the models to predict the strength and durability properties. On the other hand, the review highlighted the need to extend the AI concepts to automate the conventional testing methods of SCC mixes. The review also provides essential information about the innovative futuristic work required to refine the SCC mix design and performance further using AI methods.

A New Model to Predict the Slippage Coefficient of Tracked Vehicles During Steering

Tracked vehicles during steering are always subjected to track slippage relative to the ground. Studies show that an excessive slippage coefficient reduces the steering ability of tracked vehicles and increases the risk of soil shear failure. Accordingly, fast and accurate tests of the slippage coefficient of tracked vehicles under different ground conditions can be effectively referenced to select track parameters and reach optimal operation. Aiming to resolve shortcomings of the conventional testing method in determining the slippage coefficient of tracked vehicles, a novel method is proposed in the present study. Then the trajectory of an arbitrary point on the tracked vehicle during steering was analyzed. Moreover, the time of vehicles steering around and the speed of track sprocket were measured, and the slippage coefficient of tracked vehicles steering on the specific ground condition was determined. Meanwhile, the slippage coefficient of the tracked combined harvester steering under different ground conditions was explored using the conventional method. The obtained results were compared quantitatively, and the accuracy of the established model was verified. The performed analyses demonstrate that the proposed method has a simple structure and can be effectively applied to various complicated working conditions. This method is expected to lay a theoretical basis to establish an online testing system for the slippage coefficient of tracked vehicles during steering.

Systematic study of the effects of lithium deficiencies on the crystal structure and electrochemical performance of Li-rich materials

A series of Li-rich materials with lithium deficiencies are obtained by a mild sol-gel and high-temperature calcination method. We use conventional test methods, such as X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and X-ray photoelectron spectroscopy, to analyze the crystal structure and morphology of as-prepared materials. The results show that the Li1.1Mn0.54Co0.13Ni0.13O2 (named L1.1) displays superior electrochemical performance, that is, the discharge capacities are 303.9 and 145 mAh g−1 at rate of 0.1 C and 5 C, respectively. The excellent rate capability is mainly attributed to the formation of lithium vacancy and the formation of distorted lattice fringes, which enlarged the Li slab and changed the local structures in the L1.1 material.

Interlaboratory Validation of Toxicity Testing Using the Duckweed Lemna minor Root-Regrowth Test.

Simple SummaryDuckweed (Lemna minor) is commonly used as a phytotoxicity test organism, adopted by the main international standardization organizations (ISO, OECD, USEPA, ASTM). For duckweed tests, measurements of fronds or biomass are usually preferred with a standard exposure period of at least 7 days. The proposed root- regrowth test differs from other internationally standardized methods in several important aspects: (a) the test can be performed within 72 h; (b) the test vessel was a 24-well cell plate; (c) the required volume of test water samples was 3 mL; (d) roots were excised before exposure and newly developed roots then measured. The validation of the new test method by interlaboratory comparison tests confirmed that the Lemna root bioassay is valid and reliable. The root growth test is therefore a valuable tool for rapid toxicity screening of wastewater effluents and hazardous pollutants in natural waters because it is simple to perform, quick to conduct, cost-effective to operate, and can have operational benefits for testing time, since management decisions need to be made promptly in the event of unpredictable pollution events.The common duckweed (Lemna minor), a freshwater monocot that floats on the surfaces of slow-moving streams and ponds, is commonly used in toxicity testing. The novel Lemna root- regrowth test is a toxicity test performed in replicate test vessels (24-well plates), each containing 3 mL test solution and a 2–3 frond colony. Prior to exposure, roots are excised from the plant, and newly developed roots are measured after 3 days of regrowth. Compared to the three internationally standardized methods, this bioassay is faster (72 h), simpler, more convenient (requiring only a 3-mL) and cheaper. The sensitivity of root regrowth to 3,5-dichlorophenol was statistically the same as using the conventional ISO test method. The results of interlaboratory comparison tests conducted by 10 international institutes showed 21.3% repeatability and 27.2% reproducibility for CuSO4 and 21.28% repeatability and 18.6% reproducibility for wastewater. These validity criteria are well within the generally accepted levels of <30% to 40%, confirming that this test method is acceptable as a standardized biological test and can be used as a regulatory tool. The Lemna root regrowth test complements the lengthier conventional protocols and is suitable for rapid screening of wastewater and priority substances spikes in natural waters.

Recent insights in corrosion science from atomic spectroelectrochemistry

AbstractA fundamental understanding of corrosion mechanisms is the key to developing suitable corrosion protection approaches, and for the prediction of service life of metallic structures. However, conventional corrosion testing methods such as mass loss and electrochemical testing do not guarantee estimation of "true" corrosion rate and often mask the underlying mechanisms, due to either low sensitivity or a lack of element‐resolved information. Relatively recent work in corrosion science has led to the development of a new class of corrosion testing approaches, namely atomic spectroelectrochemistry; whereby direct insight of dissolution and corrosion mechanisms can be obtained during electrochemical testing. Atomic spectroelectrochemistry provides real‐time and element resolved dissolution rate of material via coupling electrochemical flow cell with inductively coupled plasma – atomic spectroscopy. This concise review discusses the basic working principle of atomic spectroelectrochemistry and its recent applications in corrosion science to understand the true underlying corrosion mechanisms of a range of metallic materials.

Evolution of Antibacterial Drug Screening Methods: Current Prospects for Mycobacteria.

The increasing resistance of infectious agents to available drugs urges the continuous and rapid development of new and more efficient treatment options. This process, in turn, requires accurate and high-throughput techniques for antimicrobials’ testing. Conventional methods of drug susceptibility testing (DST) are reliable and standardized by competent entities and have been thoroughly applied to a wide range of microorganisms. However, they require much manual work and time, especially in the case of slow-growing organisms, such as mycobacteria. Aiming at a better prediction of the clinical efficacy of new drugs, in vitro infection models have evolved to closely mimic the environment that microorganisms experience inside the host. Automated methods allow in vitro DST on a big scale, and they can integrate models that recreate the interactions that the bacteria establish with host cells in vivo. Nonetheless, they are expensive and require a high level of expertise, which makes them still not applicable to routine laboratory work. In this review, we discuss conventional DST methods and how they should be used as a first screen to select active compounds. We also highlight their limitations and how they can be overcome by more complex and sophisticated in vitro models that reflect the dynamics present in the host during infection. Special attention is given to mycobacteria, which are simultaneously difficult to treat and especially challenging to study in the context of DST.

Novel two-tone measurement of the nonlinearity and memory effects of mixers in different amplitude regions of large carrier signals.

The conventional two-tone test method cannot measure the amplitude and phase of IM3 products under different operating conditions. The nonlinearity and memory effects of mixers under different operating conditions have not been characterized in existing research. This paper presents a new two-tone measurement method for characterizing the nonlinearity and memory effects of mixers under the excitation of large carrier signals of different amplitudes. This new test method differs from the conventional two-tone test in that the two-tone test signal is superimposed on a large carrier signal. The role of the large carrier signal is to excite mixers into different operating conditions. The amplitude and phase of the IM3 product of the mixer could be measured to characterize the nonlinearity and memory effects under different operating conditions using this method. This novel method is based on a vector network analyzer (VNA) and signal generator (SG). Compared with the conventional method of only using a spectrum analyzer and SG, the VNA can remove the system error through a calibration algorithm to ensure the accuracy of the IM3 product measurement results. The measurement results, for the first time, demonstrated the nonlinearity and memory effects of mixers in different amplitude regions of a large carrier signal. These findings are advantageous and can facilitate further research to simplify the digital pre-distortion model of mixers under different operating conditions.

Antimicrobial Drug-Resistant Salmonella in Urban Cats: Is There an Actual Risk to Public Health?

The present study was undertaken to investigate the presence of Salmonella spp. in the faeces of client-owned cats in urban areas and to evaluate the risk that is posed to public health. Fresh faecal samples were collected directly from the rectums from 53 diarrhoeic and 32 non-diarrhoeic cats. The samples were individually screened for the presence of Salmonella spp. using standard methods and, in the case of positive findings, the resulting typical colonies were then biochemically confirmed using the VITEK®2 automated system. Subsequently, all of the Salmonella spp. isolates were molecularly tested for the presence of the invA gene. All of the isolates were serotyped using the slide agglutination technique according to the White–Kauffmann–Le Minor scheme. The phenotypic antimicrobial susceptibility profile of the isolated strains was obtained from the VITEK®2 system using specific cards from the Gram-negative bacteria. A total of 16 of the samples (18.82%) tested positive for Salmonella spp. according to conventional and molecular testing methods. Serotyping of the Salmonella isolates showed the presence of three serotypes, namely S. enteritidis (n = 9; 56.3%), S. typhimurium (n = 4; 25%), and S. kentucky (n = 3; 18.8%). All of the tested strains showed strong resistance towards cefazolin, cefepime, ceftazidime, and ceftriaxone. Additionally, resistance (listed in descending order of strength) was observed to trimethoprim/sulfamethoxazole (11/16; 68.8%), ampicillin (10/16; 62.5%), ampicillin/sulbactam (9/16; 56.3%), gentamicin (9/16; 56.3%), nitrofurantoin (8/16; 50.0%), and amikacin (5/16; 31.3%). No resistance was expressed against ciprofloxacin, ertapenem, imipenem, levofloxacin, piperacillin/tazobactam, and tobramycin. The results of this study highlight a substantial public health issue and medical concern, especially in vulnerable people, such as children, the elderly, and immunocompromised individuals.

Estimating soil chemical properties by diffuse reflectance spectroscopy: Promise versus reality

AbstractDiffuse reflectance spectroscopy in the visible and near‐infrared (VNIR) spectral range has increasingly been utilised in recent years to measure soil properties, including organic carbon and macronutrient content, cation exchange capacity, pH, and even trace metal concentration. Proponents have even suggested that conventional laboratory soil testing methods can ultimately be replaced by these less laborious and more rapid spectroscopic methods. However, to this point in time, reflectance spectroscopy has not demonstrated accuracy comparable to that of conventional physical–chemical testing methods. This review explains why correlations between VNIR spectral features and specific chemical properties within selected sets of soil samples are indirect at best and therefore cannot be trusted more universally to predict soil chemical properties in larger and less homogeneous sample sets. Because mathematical manipulation of the raw spectral data has become increasingly complex and obscure to the users, particularly when machine learning is employed, the possibility exists that the correlations found and the predictions made are based on chance relationships resulting from overfitting the spectral data to include random noise in addition to any real trends. It is concluded that, for real‐world soil testing for agronomic and environmental purposes (e.g. available nutrient and trace metal levels), spectral reflectance methods are not sufficiently reliable to replace conventional testing. Conversely, these reflectance methods show utility and convenience in measuring general trends across landscapes in levels of soil organic matter, carbonates, soluble salts and specific clay minerals.Highlights VNIR reflectance spectroscopy is reviewed as a method to measure soil properties. Estimating most soil chemical properties by VNIR relies on indirect or proxy correlations. Complex regression models used in predicting soil properties may overstate accuracy. Reflectance spectroscopy has lower reliability and extrapolability than conventional soil testing.

AUTOMATED SEGMENTATION OF COVID-19 REGIONS FROM LUNG CT IMAGES USING WATERSHED ALGORITHM AND CLASSIFICATION USING MACHINE LEARNING CLASSIFIERS

The COVID-19 pandemic originated in Wuhan, China in December 2019 and has since affected over 200 countries worldwide. The highly contagious Coronavirus primarily affects the respiratory system, causing pulmonary inflammation that can be visualized through medical imaging such as CT and X-rays. Conventional testing methods include PCR and antibody tests. Shortage of test kits in hospitals as well as time taken for results to be received can be compensated through medical imaging. Therefore, there is a need for an automated system, which is accurate and robust in detection of Covid-19 from medical radiographs for clinical practice. The objectives of our study are as follows: (i) To segment the lung CT images using a hybrid watershed and fuzzy c-means algorithm. (2) To extract various textural features using the GLCM algorithm. (iii) To implement machine learning classifiers for classification of COVID and non-COVID image classes. Our dataset consisting of 60 chest CT images of COVID-19 and non-COVID-19 patients was pre-processed and segmented using a hybrid watershed and fuzzy c-means algorithm. Then, textural features were extracted from the segmented ROI using the GLCM algorithm. Finally, the images were classified into COVID and non-COVID classes using three machine learning classifiers namely Naïve Bayes, SVM and K-star. Naïve Bayes classifier achieved the highest accuracy of 95%, while SVM achieved 93% accuracy. The ROC curves were also obtained, with AUC of 0.98. Thus, our proposed system has shown promising results in the classification of lung CT images into the two classes namely COVID and non-COVID.

Assessment of Accelerated Cyclic Electrochemical Technique Compared to Conventional Industrial Testing Methods

The Accelerated Cyclic Electrochemical Technique (ACET), which has been adopted as the ISO 17463 standard, has attracted great attention in industry as a promising tool for the rapid assessment of paints and organic coatings on metallic substrates. The protocol consists of Electrochemical Impedance Spectroscopy (EIS) and Relaxation Voltammetry (RV) to observe the gradual degradation of a coated sample. The peculiarity of the test lies in the use of cathodic polarization (CP) as a major stress factor allowing a strong acceleration of failure and the quantitative evaluation of both water uptake and coating adhesion, within a limited test time. Indeed, ACET has been reported as a successful method for studying the effect of cure temperature, phosphate and ZMP pigments and surface pretreatments on the protective properties of painted systems. Moreover, a good agreement with conventional accelerated tests was shown.In this work, we confirm that the results of ACET on water uptake correlate well with Humidostatic Chamber (HC) tests performed in accordance to ISO 6270. Conversely, some disagreement is observed with Neutral Salt Spray (NSS) test ISO 9227. As a matter of fact, ACET can reproduce coating performance in NSS only if electrolyte can reach the substrate and cathodic delamination occurs. Accordingly, we highlight that the main limitation of ACET is how quick electrolyte reaches the substrate, so that this technique fails to classify high thickness and/or high resistive coatings.In the attempt to overcome this intrinsic shortcoming of the test, we propose the modification of ACET by using a sample with a 2×1 mm crosscut (sACET, where s stands for scribed), i.e. with a similar approach as in the REAP (Rapid Electrochemical Assessment of Paint) test. Results are illustrated in Figure 1 for two different coated systems (S1 and S2) tested in the NSS chamber for 720 h and by sACET for 6 cycles (inset). The delaminated area around the scratch was measured as 37 and 18 cm2 in NSS, 3.41 and 2.80 cm2 in sACET for S1 and S2, respectively, with a similar trend of increase in both tests. EIS measurements in the sACET protocol allow to track the gradual increase of delaminated area by the variation of charge-transfer resistance (Rct ) before and after subsequent degradation steps as shown in Figure 1c. Therefore, whenever the regular ACET test fails or is not able to provide reliable results, we recommend that scratched samples be used for the assessment of both coating water adsorption and adhesion strength. Figure 1

Prediction of viral symptoms using wearable technology and artificial intelligence: A pilot study in healthcare workers.

Conventional testing and diagnostic methods for infections like SARS-CoV-2 have limitations for population health management and public policy. We hypothesize that daily changes in autonomic activity, measured through off-the-shelf technologies together with app-based cognitive assessments, may be used to forecast the onset of symptoms consistent with a viral illness. We describe our strategy using an AI model that can predict, with 82% accuracy (negative predictive value 97%, specificity 83%, sensitivity 79%, precision 34%), the likelihood of developing symptoms consistent with a viral infection three days before symptom onset. The model correctly predicts, almost all of the time (97%), individuals who will not develop viral-like illness symptoms in the next three days. Conversely, the model correctly predicts as positive 34% of the time, individuals who will develop viral-like illness symptoms in the next three days. This model uses a conservative framework, warning potentially pre-symptomatic individuals to socially isolate while minimizing warnings to individuals with a low likelihood of developing viral-like symptoms in the next three days. To our knowledge, this is the first study using wearables and apps with machine learning to predict the occurrence of viral illness-like symptoms. The demonstrated approach to forecasting the onset of viral illness-like symptoms offers a novel, digital decision-making tool for public health safety by potentially limiting viral transmission.

An Improved Calibration Method to Determine the Strain Coefficient for Optical Fibre Sensing Cables

The strain coefficient of an optical fibre sensing cable is a critical parameter for a distributed optical fibre sensing system. The conventional tensile load test method tends to underestimate the strain coefficient of sensing cables due to slippage or strain transfer loss at the fixing points during the calibration procedure. By optimizing the conventional tensile load test setup, the true strain of a sensing cable can be determined by using two sets of displacement measuring equipment. Thus, the strain calculation error induced by slippage or strain transfer loss between a micrometre linear stage and sensing cable can be avoided. The performance of the improved calibration method was verified by using three types of sensing cables with different structures. In comparison to the conventional tensile load test method, the strain coefficients obtained by the improved calibration method for sensing cables A, B, and C increase by 1.52%, 2.06%, and 1.86%, respectively. Additionally, the calibration errors for the improved calibration method are discussed. The test results indicate that the improved calibration method has good practicability and enables inexperienced experimenters or facilities with limited equipment to perform precise strain coefficient calibration for optical fibre sensing cables.

Elemental analysis by Metallobalance provides a complementary support layer over existing blood biochemistry panel-based cancer risk assessment.

Despite the benefit of early cancer screening, Japan has one of the lowest cancer screening rates among developed countries, possibly due to there being a lack of “a good test” that can provide sufficient levels of test sensitivity and accuracy without a large price tag. As a number of essential and trace elements have been intimately connected to the oncogenesis of cancer, Metallobalance, a recent development in elemental analysis utilizing the technique of inductively coupled plasma mass spectrometry has been developed and tested as a robust method for arrayed cancer risk screening. We have conducted case-control epidemiological studies in the prefecture of Chiba, in the Greater Tokyo Area, and sought to determine both Metallobalance screening’s effectiveness for predicting pan-cancer outcomes, and whether the method is capable enough to replace the more conventional antigen-based testing methods. Results suggest that MB screening provides some means of classification potential among cancer and non-cancer cases, and may work well as a complementary method to traditional antigen-based tumor marker testing, even in situations where tumor markers alone cannot discernibly identify cancer from non-cancer cases.

Laboratory Study on Non-Destructive Evaluation of Polyethylene Liquid Storage Tanks by Thermographic and Ultrasonic Methods

High-density polyethylene (HDPE) above-ground storage tanks (AST) are used by highway agencies to store liquid deicing chemicals for the purpose of road maintenance in the winter. A sudden AST failure can cause significant economic and environmental impacts. While ASTs are routinely inspected to identify signs of aging and damage, current methods may not adequately capture all defects, particularly if they are subsurface or too small to be seen during visual inspection. Therefore, to improve the ability to identify potential durability issues with HDPE ASTs, additional non-destructive evaluation (NDE) techniques need to be considered and assessed for applicability. Specifically, this study investigates the efficiency of using infrared thermography (IRT) as a rapid method to simultaneously examine large areas of the tank exterior, which will be followed by closer inspections with conventional and phased array ultrasonic testing (UT) methods. Results show that IRT can help to detect defects that are shallow, specifically located within half of the tank’s wall thickness from the surface. UT has the ability to detect all defects at any depth. Moreover, phased array UT helps to identify stacked defects and characterize each defect more precisely than IRT.

Permeability measurements using rate-transient analysis (RTA): Comparison with different experimental approaches

Reservoir engineers commonly apply rate-transient analysis (RTA) and pressure-transient analysis (PTA) methods to analyze multi-fracture horizontal wells (MFHWs) completed in unconventional reservoirs quantitatively for reservoir and hydraulic fracture properties. Data from core analysis techniques are commonly used to provide important input for RTA-PTA models. However, conventional laboratory techniques (i.e., steady-state and non-steady-state fluid flow) do not reproduce the operating conditions that MFHWs are subjected to in the field. In the current work, laboratory techniques that better reproduce these boundary conditions are explored and compared to more traditional core analysis methods.For this study, RTA methods are applied to gas produced from core plugs and PTA methods are applied to gas injection-fall-off data at the start of the core test before gas production. While the RTA method has been previously described by the authors, the application of the PTA method to provide an early, and fast, estimate of permeability is unique to this study. Further, our previous experimental setup for performing RTA was modified to accommodate not only the use of both RTA/PTA methods, but also the use of conventional core analysis methods (steady-state and non-steady-state methods) to allow for direct comparison of all methods.For both RTA and PTA core tests, the observed flow-regime sequence is transient linear flow followed by boundary-dominated flow, which is the same sequence that is commonly observed in the field for MFHWs producing from low-permeability and shale reservoirs. Two independent permeability values were estimated using the slope of the square root time plot and the time at the end of linear flow for each test. The pore volume of the samples were also estimated using the RTA method. Permeability and pore volume values obtained from the RTA method, referred to as ‘RTAPK’ previously, were in good agreement with those obtained from more conventional core testing methods (average coefficient of variation = 8%). The derived permeabilities from the time at the end of linear flow during the fall-off test were close to other permeabilities. In contrast, the square root time plot (fall-off) resulted in significantly higher permeabilities attributed to the experimental artifact caused by substantial dead volume in the injection port. The primary advantage of the RTA core analysis method is the accelerated test-time. For samples with permeability values ranging between 0.1 and 3 mD, the apparent gas permeabilities can be estimated in less than 3 to 10 minutes using both fall-off and production data.