Innovative Testing Methods Research Articles

DMATCH: A novel integrated testing method for floating wind turbine dynamics – Potential error and its impact

With floating offshore wind turbines (FOWT) steadily advancing towards large-scale deployments in deep water, the traditional wave basin model testing method shows its shortage to fulfill the testing requirement. To enhance the effectiveness of model tests for FOWT, this paper introduces a distributed model testing method, dMATCH (distributed-Mooring-Aerodynamics-Testing-Control-Hydrodynamics). The dMATCH method separates the experiment into aerodynamic testing in the wind tunnel and hydrodynamic testing in the wave basin, achieving integrated coupling through real-time data transmission using a data exchange system. Errors in sensor acquisition and actuator actuation during data communication may impact the accuracy of experiments. To investigate the potential error and its impact within dMATCH, an integrated model testing system in the wave basin was constructed. Four load cases were established, introducing varying magnitudes of normally distributed random errors to simulate acquisition and actuation inaccuracies. The investigation revealed a positive correlation between errors in experimental results and those in acquisition and actuation. As error increased, result fluctuations became more pronounced. Within the current experimental framework, acquisition error had a greater influence on results compared to actuation error, with aerodynamic thrust being more sensitive to error than the pitch and surge motions of platform. When acquisition and actuation errors were controlled below 5%, the relative RMSE of the results remained below 5%. The dMATCH method proposed in this paper offers a new approach for integrated model testing of FOWT, and the study of potential error impact is crucial to ensuring the reliability of this innovative testing method.

Exploring Biomimetic Heat Pipes for Space Radiator Enhancement

This study investigates biomimetic heat pipes for space radiator applications, utilizing nature-inspired structures to potentially enhance heat transfer efficiency. The research addresses the imperative for improved heat dissipation mechanisms in nuclear space systems, crucial for effective thermal management. Heat pipes are passive heat transfer devices widely adopted for thermal control. The study aims to evaluate the effectiveness of a biomimetic heat pipe design in comparison to a traditional design while also validating the fabrication process through industry-made heat pipe comparisons. Innovative hot oil bath testing methods are employed to fabricate and test both heat pipe types, utilizing comprehensive thermal analysis, physical experiments, and validation techniques to assess heat transfer capabilities. Tests span varying temperature levels to analyze heat pipe behavior and performance. Findings suggest the potential for enhanced heat dissipation along the length of the biomimetic heat pipe, hinting at the biomimetic structure’s role in improving heat transfer. This study underscores the promise of biomimetic design principles and their potential for advancing heat pipe technology. Recommendations for further exploration include alternative materials, optimized testing procedures, and refined fabrication processes.

Construction d’une méthodologie d’évaluation clinique des dispositifs médicaux grâce aux outils de simulation et illustration à travers trois études

European regulations have recently moved towards more stringent requirements for demonstrating the safety and performance of medical devices (MDs). To apply an innovative testing method using medical simulation to the evaluation of three medical devices at different stages of their life cycle. The methodology for evaluating DMs using simulation is based on seven stages: definition of the context, training, construction of a scenario to test the DM, validation of the scenario, realization of the scenario, evaluation of the scenario by the players and validation and exploitation of the results. Our evaluation methodology enabled us to assess three DMs at different stages of their development: a respiratory protection device at the initial stage (prototype definition), a respiratory protection mask (prototype optimization) and bottle adapters (post-marketing). Simulation is a valuable tool for evaluating DM. The proposed methodology enables it to be used and adapted to different contexts. It responds to the specificities of clinical evaluation of this class of products, and helps to better anticipate certain risks.

Experimental study of wear and rolling contact fatigue in railway wheel steels coupled with various brake block materials: Insights from innovative small-scale testing

This study presents a comprehensive analysis using an innovative testing method of two wheel steels paired with cast iron and organic composite brake block materials. By conducting tests under consistent conditions and varying in duration, the study examines temperature profiles, friction coefficients, surface characteristics, weight loss, and microstructural changes in wheel samples, emphasizing the distinct behaviour of these materials in braking applications and the damage evolution over time. The results demonstrate that organic composite brake samples outperform those in cast iron, showcasing smoother wheel sample surfaces and stable friction coefficients. Weight loss analysis reveals the environmental benefits of organic composite brakes, emitting fewer particulates than cast iron counterparts. Microstructural examinations uncover the formation of a Thermal White Etching Layer (T-WEL) on wheel samples tested with cast iron samples, leading to cracks and material detachment. Conversely, extended use of organic composite samples led to a "thermal fuse effect", impacting their efficiency and suggesting the need of careful temperature management in sustained braking scenarios. Despite significant differences in wheel steels, the study underscores the critical role of brake material in braking improvements. The findings not only enhance the scientific understanding of brake material behaviour but also introduce an innovative, cost-effective, and fast 4-contact machine testing method.

Optimized biomarker evaluation and molecular testing in the era of breast cancer precision medicine

ABSTRACT Ground breaking advances in medicine, driven in part by major technologic developments in molecular biology have led us to a new model for cancer care that has been termed personalized, or precision medicine. Precision medicine is a model for making medical decisions that employs an innovative clinical approach and advanced tumor testing methods that are tailored to understanding an individual patient’s tumor biology and the molecular drivers of their disease. This medical model includes a combination of diagnostic testing and specific treatment options that can be offered to patients at presentation and in theory throughout the course of their disease as new mutations arise with the development of disease recurrence. Although the precision medicine model offers incredible potential to transform cancer care, these advances are only meaningful when they reach the correct patients. The evolving paradigm of precision medicine is changing the practice of pathology, and the pathology community needs to be mindful of these changes because every tissue specimen represents a patient’s life, and those patients are depending on the pathology community to handle their tissue correctly. The diagnostic tests performed in the pathology laboratory for precision medicine are increasingly complex, and pathologists along with the entire laboratory and clinical communities need to take steps to ensure that the right diagnosis is given to the right patient to inform the right treatment options, at the right time, along every step of the continuum of care for cancer patients. While hormone receptors and human epidermal growth factor receptor 2 (HER2) overexpression and/or amplification have been the mainstay for risk-stratification, and treatment decision making in breast cancer since the early 2000’s, the seminal work on gene expression by Perou and colleagues in the early 2000’s opened the door for molecular testing in the prognostic and predictive assessment of breast cancer. Molecular testing is now part of the standard of care in the precision medicine model for breast cancer care. In this article, the reader will gain a better understanding of how the lack of standardization of pre-analytic factors has the potential to negatively impact the quality of the tissue specimen for downstream biomarker and molecular testing, which ultimately can negatively affect patient care. The reader will also gain insight into the current climate surrounding molecular testing in breast cancer.

A novel machine learning-based artificial intelligence method for predicting the air pollution index PM2.5

Accurate prediction of the Particulate Matter 2.5 (PM2.5) plays a crucial role in the accurate management of air pollution and prevention of respiratory diseases. However, PM2.5 as a time series is extremely difficult to accurately predict. In this paper, a Hybrid Integration (HIG) algorithm that combines data pre-processing, time-series decomposition, signal decomposition, a prediction module, a matching strategy, and a hybrid integrated optimization algorithm is proposed. First, the optimal parameters for the four individual models were selected by integrating multiple evaluation perspectives. Additivity was then determined by Seasonal and Trend decomposition using LOWESS (STL), followed by refinement decomposition using signal decomposition. The four new sequences were reconstructed using Range Entropy (RangeEn) and mapped to the models. Additionally, Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) methods were optimized using the HIG algorithm. The results show that the HIG-RNN and HIG-LSTM are more advantageous than the ordinary method in terms of reasonable weight assignment. Finally, an innovative confusion test method was developed to test the stability of the prediction direction. To ensure generalizability, validation was performed using PM2.5 data from two regions of China. The results show that the method significantly improves the prediction performance and provides a powerful tool for policy formulation and management.

Rapid and nondestructive watermelon (Citrullus lanatus) seed viability detection based on visible near-infrared hyperspectral imaging technology and machine learning algorithms.

The improper storage of seeds can potentially compromise agricultural productivity, leading to reduced crop yields. Therefore, assessing seed viability before sowing is of paramount importance. Although numerous techniques exist for evaluating seed conditions, this research leveraged hyperspectral imaging (HSI) technology as an innovative, rapid, clean, and precise nondestructive testing method. The study aimed to determine the most effective classification model for watermelon seeds. Initially, purchased watermelon seeds were segregated into two groups: One underwent sterilization in a dehydrator machine at 40°C for 36h, whereas the other batch was stored under favorable conditions. Watermelon seeds' spectral images were captured using an HSI with a charge-coupled device camera ranging from 400 to 1000nm, and the segmented regions of all samples were measured. Preprocessing techniques and wavelength selection methods were applied to manage spectral data workload, followed by the implementation of a support vector machine (SVM) model. The initial hybrid-SVM model achieved a predictive accuracy rate of 100%, with a test set accuracy of 92.33%. Subsequently, an artificial bee colony (ABC) optimization was introduced to enhance model precision. The results indicated that, with kernel parameters (c, g) set at 13.17 and 0.01, respectively, and a runtime of 4.19328s, the training and evaluation of the dataset achieved an accuracy rate of 100%. Hence, it was practical to utilize HSI technology combined with the PCA-ABC-SVM model to detect different watermelon seeds. As a result, these findings introduce a novel technique for accurately forecasting seed viability, intended for use in agricultural industrial multispectral imaging. PRACTICAL APPLICATION: The traditional methods for determining the condition of seeds primarily emphasize aesthetics, rely on subjective assessment, are time-consuming, and require a lot of labor. On the other hand, HSI technology as green technology was employed to alleviate the aforementioned problems. This work significantly contributes to the field of industrial multispectral imaging by enhancing the capacity to discern various types of seeds and agricultural crop products.

Air-conditioning load characteristics and grey box predicting model in subway stations

With the continuous expansion of metro, energy conservation of air-conditioning system in subway stations draws the attention of the whole world. Most of the researches are focused on improving the energy efficiency of the system, while the load characteristics of subway stations are paid little attention. The inaccurate load prediction in the designing of air-conditioning system results in redundancy and low operating efficiency. Therefore, accurately predicting the air-conditioning load is crucial for energy saving in subway stations. In this paper, an innovative three-stage subway air-conditioning load test method was proposed and implemented in nine subway stations in Qingdao. Based on the test data, the special air-conditioning load characteristics of subway stations as underground buildings were analyzed. The results showed that electrical equipment load accounted for the largest part, reaching 53.7 %, while only 42 % of the equipment power was converted into air-conditioning load. The positive role of the envelope should not be ignored, especially in the case of entrance and exit walls, which bore almost all of the fresh air load. Based on the three-stage test, a grey box model was established and the error was validated to be within 6 %. With this model, the load of air-conditioning system can be calculated by inputting passenger flow, power of electrical equipment and public area. This paper provides a reference for the design and operation of air-conditioning system in subway stations.

Revealing the mechanism of crack initiation and propagation in CGHAZ of S690QL welded joints through low-temperature impact tests with gradient setting of pendulum angle

As the most brittle areas of welded S690QL high-strength steel structures, coarse-grained heat-affected zone (CGHAZ) was crucial for the structural integrity of components. This paper designed an innovative low-temperature impact testing method with a gradient setting of pendulum angle to investigate the micro-mechanism of crack initiation and propagation in the CGHAZ of S690QL welded joints. The results reveal that continuous blocky M−A constituents were distributed along prior austenite grain boundaries (PAGBs), leading to stress concentration and crack initiation. During low-temperature impact processes, cracks propagate in a transgranular mode along {100} or {110} crystal planes. Due to the interaction between compressive stress and the crack tip, regions with high kernel average misorientation (KAM) such as PAGBs can divert the crack. The coarsening of prior austenite grains in the CGHAZ leads to a diminished hindering effect of PAGBs on crack propagation. The findings elucidate the complex relationship between microstructure and impact toughness of CGHAZ, providing insights into crack behavior and mechanisms in CGHAZ.

Load Bearing Capacity and Failure Analysis of Fibrous Plaster Wads

ABSTRACT Fibrous plaster is a culturally significant material used in high-status buildings from the late nineteenth century. Fibrous plaster ceilings are typically suspended using load-bearing fibrous plaster wads, which are attached to roof structure components. Understanding the behaviour of wads is highly significant, with important safety implications emphasised by the partial collapse of the Apollo Theatre ceiling in 2013. This study demonstrates an original, innovative test method for fibrous plaster wads that enables quantification of load capacities, with manufactured specimens representative of historic in situ wads. The methodology is rigorously evaluated for traditional and alternative wad designs, reinforced with hessian scrim or continuous fibre glass (CFG) mat, with and without steel wires in looped (untwisted) or looped-twisted configurations. Tensile tests generated load-displacement characteristics and determined failure modes including cracking of plaster, deformation and tearing of fibrous reinforcement, and if present, plastic failure of a wire. Results demonstrate that hessian performs better than CFG in axial tension and inclusion of a wire increases tensile load capacity and ductility. An industry standard repair wad with hessian and looped-twisted wire can typically support 3 kN. Looped wire performed better in isolation than looped-twisted wire, with higher peak loads and greater ductility, while looped-twisted wire carried a greater load as part of a fibrous plaster composite wad. The test methodology and findings have revealed new insights into the mechanical behaviour of wads which will inform commercial practice and conservation of historic buildings, preserving important heritage and promoting safe longevity.

Effect of curvature ratio on curved microchannel heat sinks

This work studies the influence of curvature ratio on flow and heat transfer in curved microchannel heat sinks, and introduces an innovative thermal test method that can be integrated into the micro heat sink and other micro-devices. The thermal performance was rigorously evaluated using a comprehensive set of parameters, including Reynolds number, Nusselt number, Poiseuille number. Within the scope of the study, microchannel heat sink with larger curvatures exhibit superior comprehensive thermal performance, but this also leads to an increase in flow resistance within a controllable range. However, larger curvatures are also constrained by machining precision, mechanical stability, and fabrication costs.

Challenges and future trends of forensic toxicology to keep a cut above the rest.

Forensic toxicology faces several challenges in research and daily practice, including new drugs and futuristic technologies requiring innovative testing methods and continuous education and training of professionals. One of the most pressing issues in recent years is the emergence of novel psychoactive substances, often created by modifying the chemical structure of existing drugs to produce compounds with similar effects that are not yet regulated and lack standardized references. To overcome this challenge, forensic toxicologists have employed a range of analytical methods, including qualitative and quantitative analysis using highly sensitive technologies such as liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS), which are the most reliable and accurate methods for detecting drugs in biological samples. Liquid chromatography coupled with tandem mass spectrometry (LC-MS-MS) is becoming the gold standard for detecting controlled substances, their derivatives and metabolites. Despite advancements in testing methods, challenges persist in forensic toxicology. As such, the field must invest in research and development to improve testing methods, utilize cutting-edge technologies, increase funding for training programs, and promote multidisciplinary interactions.

Experimental study on compressive strength of in situ concrete tested with arc pressure method

The innovative arc pressure testing method (APTM) is adopted in this study to obtain the strength of in situ concrete and reduce damage to the concrete structure. This method is related to the double shear plane of the concrete core. A specific APTM apparatus is used to apply loads in order to obtain the approximate pure shear stress and shear strength of the concrete core. Factors affecting the strength of concrete, such as aggregate type and concrete moisture, were found not to have an impact of the applicability of APTM. The compressive strength range of the tested cube concrete samples is 20–60 MPa. The reliability and repeatability of APTM are superior to in situ testing techniques such as Schmidt hammer (SRH) and pull-off testing methods. The experimental results indicate that APTM is suitable for in situ testing of concrete compressive strength of prefabricated buildings and beam–column joints in dense steel structures. Compared with other testing methods, its accuracy is much higher and the damage to the structure is minimised.

Comparative deep learning studies for indirect tunnel monitoring with and without Fourier pre-processing

In the last decades, the majority of the existing infrastructure heritage is approaching the end of its nominal design life mainly due to aging, deterioration, and degradation phenomena, threatening the safety levels of these strategic routes of communications. For civil engineers and researchers devoted to assessing and monitoring the structural health (SHM) of existing structures, the demand for innovative indirect non-destructive testing (NDT) methods aided with artificial intelligence (AI) is progressively spreading. In the present study, the authors analyzed the exertion of various deep learning models in order to increase the productivity of classifying ground penetrating radar (GPR) images for SHM purposes, especially focusing on road tunnel linings evaluations. Specifically, the authors presented a comparative study employing two convolutional models, i.e. the ResNet-50 and the EfficientNet-B0, and a recent transformer model, i.e. the Vision Transformer (ViT). Precisely, the authors evaluated the effects of training the models with or without pre-processed data through the bi-dimensional Fourier transform. Despite the theoretical advantages envisaged by adopting this kind of pre-processing technique on GPR images, the best classification performances have been still manifested by the classifiers trained without the Fourier pre-processing.

High-Temperature Mechanical Characterization of Materials for Extreme Environments

The growth of advanced technologies involves the development of materials that can withstand extreme environmental conditions, particularly elevated temperatures. This paper presents an in-depth examination of the mechanical properties of materials designed specifically for use in high-temperature environments, such as however confined to aviation, nuclear-powered reactors, and electrical power systems. Relevant significance is associated with assessing the mechanical robustness, resilience to deformation under constant stress, and ability to cope with high temperatures over a longer time for these materials. This study explores recent developments in materials science, focusing on the products made in alloys, ceramics, and composite materials such as nickel-based superalloys, silicon carbide (SiC), and composite based on zirconium diboride (ZrB2). A significant focus is placed on innovative testing methods, including high-temperature tensile tests, thermal shock resistance assessment, and fatigue testing, as these play a critical role in evaluating the performance of substances under challenging conditions. Further, this study explores the consequences of these findings on the choice of materials and the design process in engineering applications. Titanium superalloy operates effectively at lower temperatures, whereas Nickel-based 70% of the initial strength when heated to a higher temperature of 1100°C superalloy behaves superior under more extreme conditions.

Current Status of Molecular Diagnosis of Hereditary Hemolytic Anemia in Korea.

Hereditary hemolytic anemia (HHA) is considered a group of rare hematological diseases in Korea, primarily because of its unique ethnic characteristics and diagnostic challenges. Recently, the prevalence of HHA has increased in Korea, reflecting the increasing number of international marriages and increased awareness of the disease. In particular, the diagnosis of red blood cell (RBC) enzymopathy experienced a resurgence, given the advances in diagnostic techniques. In 2007, the RBC Disorder Working Party of the Korean Society of Hematology developed the Korean Standard Operating Procedure for the Diagnosis of Hereditary Hemolytic Anemia, which has been continuously updated since then. The latest Korean clinical practice guidelines for diagnosing HHA recommends performing next-generation sequencing as a preliminary step before analyzing RBC membrane proteins and enzymes. Recent breakthroughs in molecular genetic testing methods, particularly next-generation sequencing, are proving critical in identifying and providing insight into cases of HHA with previously unknown diagnoses. These innovative molecular genetic testing methods have now become important tools for the management and care planning of patients with HHA. This review aims to provide a comprehensive overview of recent advances in molecular genetic testing for the diagnosis of HHA, with particular emphasis on the Korean context.

Control of expansive soil desiccation cracks via helical auxetic yarn

Soil shrinkage leads to cracking of expansive soil during desiccation. Prevention of crack propagation in soil is of paramount importance. This research examines the effect of auxetic yarns, in control of expansive soil desiccation cracks. In this study, auxetic yarns with optimal properties were produced. Using an innovative test method, the influence of auxetic yarn structure on the prevention of soil crack propagation was investigated. It was found that the inclusion of auxetic yarns in the expansive soil results in a 9.94% reduction in crack propagation of the soil. In order to confirm the positive effect of auxetic yarns on the behavior of the soil samples, pull-out test was conducted on the auxetic yarns incorporated in the soil samples. The interaction between the soil and the auxetic yarn was found to be much higher than the interaction between the equivalent non-auxetic yarn and the same soil. This was not only attributed to the transverse expansion of auxetic yarn, but also to the helical structure that occurs in such yarn during the pull-out. The auxetic effect of the yarn results in a 27.3% increase in the force needed to pull the yarn from the soil matrix.

Testing the impacts of renewable energy, natural resources rent, and technological innovation on the ecological footprint in the USA: Evidence from Bootstrapping ARDL

For the past few decades, there has been a vibrant discussion on the connection between natural resources and the quality of the surrounding environment. It has been established that many wealthy economies with natural resources have had favourable progress in technology and economy. Still, the main challenges are how renewable energy, natural resources, and technological innovation in leading natural resources abundant countries such as the USA affect environmental quality. To this end, this paper investigates the impact of natural resources rent, technological innovation, renewable energy, and economic growth on the ecological footprint in the USA from 1970 to 2019. The findings obtained using an innovative testing method known as Bootstrapping ARDL indicate that renewable energy sources improve environmental quality, but natural resources worsen it. The results also affirm that technological innovation is significantly associated with ecological quality. The results have important policy implications for policymakers regarding natural resources and technology innovation toward ecological quality enrichment, being necessary advances in sustainable growth after the COVID-19 process.

Development of the test method for wind turbine blade subcomponent under combined bending and torsion loads

The conventional full-scale wind turbine blade testing method is unable to study the detailed structural response of blades' key subcomponents under complex loads. Therefore, developing an efficient and reliable blade subcomponent testing method is of great significance for investigating the structural characteristics of blades. This paper develops an innovative blade subcomponent test method framework, which is capable of studying the structural response under combined bending and torsion load conditions. A high-fidelity finite element model corresponding to the framework that considers nonlinear factors is established. This study further investigated the influence of boundary conditions on the results. The results showed that the test method proposed in this paper is reasonable, and the experiment based on this method is successfully conducted. The contact nonlinearity and size effects will affect the accuracy of the test results, which can be avoided by adjusting the size of the clamp.

High-Throughput Lithium Plating Quantification for Fast Charging Battery Design

Fast charging of most commercial lithium-ion batteries is limited due to fear of lithium plating on the graphite anode, which is difficult to detect and poses significant safety risk. Here we demonstrate the power of simple, accessible, and high-throughput cycling techniques to quantify irreversible Li plating spanning data from over 100 cells. We first demonstrate a protocol for Li|Graphite half-cells to observe the effects of energy density, charge rate, temperature, and State-of-Charge (SOC) on lithium plating and provide an interpretable empirical equation for predicting the plating onset SOC. We then design a method to quantify in-situ Li plating for commercially relevant Graphite|LiNi0.5Mn0.3Co0.2O2 (NMC) cells and compare with results from the experimentally convenient Li|Graphite configuration. Ex-situ mass spectrometry titration is used to validate the in-situ analysis methods. This work showcases innovative testing methods and data processing that enable rapid battery engineering.