Large-scale Tests Research Articles

Blade Vibration Difference-Based Circumferential Fourier Fitting Algorithm for Synchronous Vibration Parameter Identification of Rotation Blades

Blades are the core components of rotating machinery, and the blade vibration status directly impacts the working efficiency and safe operation of the equipment. The blade tip timing (BTT) technique provides a solution for blade vibration monitoring and is currently a prominent topic in research on blade vibration issues. Nevertheless, the non-stationary factors present in actual engineering applications introduce inaccuracies in the BTT technique, resulting in blade vibration measurement errors. The theory of blade vibration difference offers a new perspective for high-precision BTT techniques. This paper optimizes the traditional circumferential Fourier fitting (CFF) algorithm. According to the blade departure time measurement mechanism, four sets of BTT signals are obtained by two probes, six sets of blade vibration differences are established, and, then, a blade vibration difference-based circumferential Fourier fitting (BVD-CFF) algorithm for blade synchronous vibration parameter identification is proposed. Simulation studies demonstrate that the BVD-CFF algorithm exhibits superior anti-noise performance. Moreover, experimental investigations on a high-speed rotation blade vibration test rig and a large-scale centrifugal compressor test rig display that the engine order of blade synchronous vibrations obtained by the BVD-CFF algorithm are essentially the same as those obtained by the strain gauge method.

Study on the mechanical properties of geogrid-reinforced tunnel slag and particle breakage

The use of tunnel slag as roadbed filling can save resources and promote the sustainable and low-carbon development of transportation infrastructure.. To investigate the mechanical properties evolution law of tunnel slag as subgrade filler, SEM and large-scale triaxial tests were conducted to analyze its macroscopic, microscopic characteristics and particle breakage behavior. The study focuses on the impact of geogrid on the shear strength, deformation, and particle breakage of tunnel slag and its working mechanism. The results indicate that an increase in soft rock content reduces the shear strength and weakens its dilatancy. The average peak shear strength of grid reinforced dense specimens can be increased by 10%, and the residual shear strength can be increased by about 30%. The relative breakage index increases in an S-shaped pattern with increase in soft rock content. Higher confining pressure and soft rock content leads to more particle breakage, however, particle breakage in the reinforced specimens can be significantly reduced. The research findings contribute to the enhanced design and implementation of waste material repurposing, thereby advancing the sustainable development of infrastructure.

Reply to: "Give Patients the Choice to Test for DPD Deficiency Before Fluoropyrimidine Chemotherapy," "Large-Scale DPD Testing Should Be More Than an Option," and "A Big Problem With a Feasible Solution, Not a Small Problem With a Complex Solution".

Reply to: "Give Patients the Choice to Test for DPD Deficiency Before Fluoropyrimidine Chemotherapy," "Large-Scale DPD Testing Should Be More Than an Option," and "A Big Problem With a Feasible Solution, Not a Small Problem With a Complex Solution".

Distributed Unmanned Aerial Vehicle Cluster Testing Method Based on Deep Reinforcement Learning

In the process of the collaborative work of Unmanned Aerial Vehicle (UAV) clusters, the cluster communication node test is often carried out by a single-node test, which leads to poor topology and robustness of the overall network system, an imbalanced communication network load, and high complexity of the communication test, which seriously affects the diversified needs of current users and the efficiency of large-scale task processing. To solve this problem, a distributed method for UAV cluster testing, called UTDR (distributed UAV cluster Testing method by using Deep Reinforcement learning), based on the Deep Deterministic Policy Gradient (DDPG) is proposed in this work. The system management node is used to monitor the status of the UAV testing task execution node and bandwidth resources. By taking advantage of the method of continuous interaction between the agent and the environment, the future state of the node after processing the current task to be assigned is predicted and evaluated from the perspective of interpretability, so as to achieve the effectiveness and stability of the UAV cluster testing task collaborative execution. The experimental results show that our proposed method can ensure the stable operation of the UAV cluster, accurately predict the future state, and reduce the load degree and bandwidth resource consumption of the large-scale test task network system.

Efficiency of Dimensional Analysis in Predicting Compression Load–Settlement Relationship of Soft Clay Under a Rigid Foundation

Dimensional analysis is an effective tool for designing laboratory tests, and it is also a successful method to reasonably predict the results of large-scale or field tests, which are difficult and costly to perform, by considering the outcomes obtained from small-scale tests. This paper therefore focuses on predicting the compression load–settlement relationship of soft clay soil under a rigid foundation by dimensional analysis. For that purpose, a series of dimensionless pi (π) terms were first produced for the relevant problem by employing Buckingham’s pi (π) theorem via the MATLAB program. Secondly, the results of a small-scale physical test reported in the literature that investigated the load–settlement relationship of soft clay soil under a rigid foundation subjected to compression load were verified with the finite element method. Thereafter, the small-scale problem was scaled up several times using dimensionless terms, and the compression load–settlement relationship for the large-scale cases was investigated with both dimensional analysis and the validated finite element method. The findings indicate that dimensional analysis produces reasonably successful outcomes considering the computational ease. In addition, the MATLAB program presented in this paper is quite useful for those desiring to determine the dimensionless terms belonging to any sort of problem.

Temperature-sensitive intelligent gel to prevent coal spontaneous combustion: Large-scale simulation fire extinguishing experimental study

Coal spontaneous combustion seriously endangers mine safety production. In this study, a temperature-sensitive intelligent gel was synthesised from methylcellulose (MC), polyethene glycol (PEG) and sodium chloride (NaCl). The flow characteristics of temperature-sensitive intelligent gel (abbreviated as TSIG) under different conditions were analyzed by viscosity test. An infrared spectrometer also analyzed the microscopic flame retardant mechanism of temperature-sensitive intelligent gel. A large-scale simulation fire extinguishing test bench was designed at the coal mine site to analyze the flame retardant effect of the temperature-sensitive intelligent gel on coal oxidation reaction at different injection temperatures. The results show that the temperature-sensitive intelligent gel undergoes a liquid–solid phase transition at a temperature higher than 60 °C. When MC: PEG: NaCl = 1: 6: 5, the temperature-sensitive intelligent gel showed the best flow characteristics. The large-scale simulation fire extinguishing experiments show that the CO concentration is significantly reduced after the temperature-sensitive intelligent gel is injected at the coal temperature of 300–900 ℃, and both show excellent fire extinguishing effects. The addition of temperature-sensitive intelligent gel can inhibit the number of free radicals in the process of coal oxidation, block the chain reaction of coal spontaneous combustion, and comprehensively inhibit the process of coal spontaneous combustion. The research results provided theoretical support for the application of temperature-sensitive intelligent gel in coal spontaneous combustion areas. Additionally, they guided the design of temperature-sensitive intelligent gel to prevent coal spontaneous combustion technology.

Evaluating karst features and geological fault leakage risks based on geophysical method in Dongzhuang reservoir area, Shaanxi

Leakage along faults, particularly in karst area faults, is a critical concern that can prevent impounding a reservoir. The Laolong Mountain fault in the Dongzhuang Reservoir Project Area in Shaanxi Province, China, is a large fault that may impede the project. To assess whether concentrated leakage can occur along this fault, we used a comprehensive approach involving footrill exploration, an electromagnetic method, optical imaging techniques, water pressure testing, and large-scale groundwater tracer tests. Footrill exploration results revealed that the karst features predominantly comprise karst cavities with some fissures and karst caves. These formations are typically clustered along fractures with a linear joint density of 0.4–1.5 joints/m. The linear karst rate was 0.39 %, and the karst cavities have small diameters of only a few centimeters and depths not exceeding 15 cm. A geophysical exploration indicated that low resistivity values (approximately 200 Ω·m) on the north side of the fault zone's hanging wall, with the lowest values being approximately 100 Ω·m. The fault's footwall was noted to have higher resistivity (approximately 2000 Ω·m). The rock properties on either side of the fault zone differ considerably. The upper plate of the fault (downstream of the river) has high-resistance carbonate rock formations with a well-preserved structure, whereas the lower plate (upstream of the river) comprises low-resistance sandstone and mudstone formations with notable fragmentation at the fault's surface compression zone. Tracer tests indicated an eastward groundwater flow from Zuantian Ridge toward the Jing River in the west. The results suggest that eastward leakage along the Laolong Mountain fault and its influence zone is unlikely upon reservoir impoundment. The geophysical exploration method in this study integrated and cross-validated the footrill exploration, hydrological test, groundwater tracing, optical imaging, and other methods; it can thus serve as a reference for future research.

True and false positive HIV point of care test results in a prospective multinational study of at-risk African women: implications for large-scale repeat HIV testing in HIV prevention programs.

Accurate HIV point of care testing is the cornerstone of prevention and treatment efforts globally, though false (both negative and positive) results are expected to occur. We assessed the spectrum of true and false positive HIV results in a large prospective study of HIV incidence in African women using three contraceptive methods tested longitudinally in Eswatini, Kenya, South Africa, and Zambia. HIV serologic testing was conducted quarterly using two parallel rapid HIV tests. When one or both tests were positive, additional confirmatory testing was conducted, including HIV enzyme immunoassay (EIA) and ribonucleic acid (RNA). 7730 women contributed 48,234 visits: true positive results occurred at 412 visits (0.9%) and false positives at 96 visits (0.2%). Of 412 women with HIV seroconversion, 10 had discordant (i.e., one negative and one positive) rapid tests and 13 had undetectable HIV RNA levels. Of 62 women with false positive rapid HIV results, most had discordant rapid testing but six (9.7%) had dually-positive rapid results and four (6.5%) had false positive or indeterminate EIA results. The positive predictive value of dual positive rapid results was 98.3%. Although the majority of rapid test results were accurate, false positive results were expected and occurred in this population of initially HIV seronegative individuals tested repeatedly and prospectively. When HIV infection occurred, not all cases had textbook laboratory results. Our findings highlight the importance of confirmatory testing, particularly for individuals undergoing repeat testing and in settings where the point prevalence is expected to be low.

Development of Lectora Inspire Based Learning Media to Improve Learning Outcomes of Light and Its Properties

This research aims to determine the feasibility of Lectora Inspire-based learning media based on assessments from media experts and material experts; determine the effectiveness of using Lectora Inspire media in science subjects. This type of research is research and development (R&D) with the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development model. At the development stage, learning media is tested for suitability through the assessment of 1 media expert and 1 material expert. Next, the implementation stage goes through two stages, namely small-scale testing and large-scale testing. The results of the research show that the level of media appropriateness based on the assessment of media experts is in the very feasible category with a score of 91.66%, while based on the assessment of material experts it is in the category very decent with a score of 88.46%. The significance level obtained is 0.004 on a small scale and 0.00 on a large scale, which means there is a significant difference. Meanwhile, the level of effectiveness obtained on a small scale is 70% and on a large scale it is 62%, which means that the media is in the quite effective category. Therefore, the Lectora Inspire learning media is very suitable and quite effective for use in science learning, light and its properties

Extending Conflict-Based Search for Optimal and Efficient Quadrotor Swarm Motion Planning

Multi-agent pathfinding has been extensively studied by the robotics and artificial intelligence communities. The classical algorithm, conflict-based search (CBS), is widely used in various real-world applications due to its ability to solve large-scale conflict-free paths. However, classical CBS assumes discrete time–space planning and overlooks physical constraints in actual scenarios, making it unsuitable for direct application in unmanned aerial vehicle (UAV) swarm. Inspired by the decentralized planning and centralized conflict resolution ideas of CBS, we propose, for the first time, an optimal and efficient UAV swarm motion planner that integrates state lattice with CBS without any underlying assumption, named SL-CBS. SL-CBS is a two-layer search algorithm: (1) The low-level search utilizes an improved state lattice. We design emergency stop motion primitives to ensure complete UAV dynamics and handle spatio-temporal constraints from high-level conflicts. (2) The high-level algorithm defines comprehensive conflict types and proposes a motion primitive conflict detection method with linear time complexity based on Sturm’s theory. Additionally, our modified independence detection (ID) technique is applied to enable parallel conflict processing. We validate the planning capabilities of SL-CBS in classical scenarios and compare these with the latest state-of-the-art (SOTA) algorithms, showing great improvements in success rate, computation time, and flight time. Finally, we conduct large-scale tests to analyze the performance boundaries of SL-CBS+ID.

Large-scale field model testing of the effects of soft rock water content on the bearing performance of tunnel-type anchorages

Large-scale field model testing of the effects of soft rock water content on the bearing performance of tunnel-type anchorages

Development of Project Based Learning E-Modules in Chemistry Learning Design Course Using Flipbook Builder Application

The purpose of this study was to develop a project-based learning e-module in chemical learning design courses using the flipbook builder application. The method used in this research is the Research and Development method to develop project-based learning e-modules in chemical learning design courses using the flipbook builder application. The e-module media development model used in this study, namely the ADDIE model which consists of 5 stages including analysis, design, development, implementation, and evaluation. The subjects used in this study were students of the Chemistry Education Study Program at Jambi University who had taken a chemistry learning design course, namely 15 students in the small scale test and 30 students in the large scale test. Based on the feasibility test assessment of project-based learning e-modules in chemistry learning design courses that have been developed on a small scale, the score is 89.33 with very high criteria, while the large-scale feasibility test scores 91.83 with very high criteria.

Fire Resilience of Load-Bearing Wall Made of Hollow Timber Elements

During a fire load, a charred layer forms on the timber elements, which is a natural protection against fire, so that a certain level of fire resistance could be achieved by using elements with a larger cross-section. However, this modus of fire protection is not always suitable. One of the most commonly used fire protection systems are fire protection boards. In this work, a large-scale fire test was carried out on a protected load-bearing wall made of hollow elements under the effect of sustained mechanical loads and fire exposure. Different stages of charring were observed. The test was aborted at the 91st minute due to a decrease in the load-bearing capacity and integrity criteria. The allowable average temperature rise on the non-exposed side of the specimen (140 K) was not exceeded until the 91st minute of the test, and the allowable maximum temperature rise on the non-exposed side of the specimen (180 K) was not exceeded until the 90th minute of the test. The loss of specimen integrity occurred at the 90th minute of the test. For surfaces protected by fire-resistant panels, it should be considered that the onset of charring is delayed until a certain time. According to EN 1995-1-2, charring can start before the fire protection is removed, but at a lower charring rate than the rates up to the time of failure of the fire protection. The expression proposed in EN 1995-1-2 shows relatively accurate results for certain systems and thicknesses of fire protection linings. However, it does not consider the presence of more than one lining layer or the full range of lining thicknesses themselves. For the wall described in this paper, the predicted failure time of the fire boards would therefore be 41.5 min, which is not consistent with the results of the experiment (51 min). The results of the calculation model according to EN 1995-1-2 did not fully agree with the results of the fire test on the protected load-bearing wall.

A Position-Sensitive Mixture Item Response Model

Standard item response theory (IRT) models are ill-equipped for when the probability of a correct response depends on the location in the test where an item is encountered—a phenomenon we refer to as position effects. Unmodeled position effects complicate comparing respondents taking the same test. We propose a position-sensitive IRT model that is a mixture of two item response functions, capturing the difference in response probability when the item is encountered early versus late in the test. The mixing proportion depends on item location and latent person-level characteristics, separating person and item contributions to position effects. We present simulation studies outlining various features of model performance and end with an application to a large-scale admissions test with observed position effects.

Suppression of Cadra cautella (Lepidoptera: Pyralidae) development by phytosanitary irradiation doses and their impacts on physiochemical and microbiological quality of dates.

Cadra cautella is a serious insect pest of stored figs and dates. The irradiation sensitivity of different development stages of C. cautella and large-scale testing of the proposed irradiation quarantine doses (50-500 Gy), were investigated. The impact of a PI dose of 400 Gy on the physiochemical and microbiological quality of dry dates (Bartamoda cv.) stored at room temperature was also investigated. An irradiation dose of 100 Gy prevented egg hatching in the F1 generation when 1-3 days old eggs were irradiated. Irradiation doses of 200 and 300 Gy prevented adult emergence when 2nd and 4th instar larvae were irradiated. When the pupae stage was irradiated, an irradiation dose of 400 Gy prevented the hatchability of F1 generation, indicating that this stage was the most radio-tolerant. The results of large-scale testing of the proposed phytosanitary irradiation dose (400 Gy) applied to 18, 0000 pupae resulted in no reproduction (zero hatching of F1 generation). There were no significant differences in the physiochemical properties of stored dates during the storage period at room temperature. Stable ESR signal intensity was recorded for 6 months in all parts of the irradiated fruits, and the intensity was highest in the kernel. The PI dose of 400 Gy also slightly reduced all microorganisms' counts. In conclusion, the dose level of 400 Gy stopped the reproduction potential of C. cautella. and they maintained the quality characteristics of dry date Bartamoda fruits during storage at room temperature for 6 months in tightly closed packages.

Hydrokinetic energy applications within hydropower tailrace channels: Implications, siting, and U.S. potential

Hydropower tailrace channels are unique and attractive locations for hydrokinetic energy harvesting due to fast currents, scheduled flow releases, proximity to existing structural and electrical infrastructures, and low risk of additional environmental impacts. However, energy-extracting devices create flow resistance, inducing a small but measurable water level increase which may diminish the available hydraulic head and reduce hydropower generation, defeating the initial value proposition. This study combines a one-dimensional momentum balance approach with the backwater equation for surface-varying open channel flow to analyze the water level increase and determine the optimal turbine siting distance that maximizes the net power production (balancing hydropower loss vs. hydrokinetic gain), as a function of the channel hydraulic conditions and the hydrokinetic turbine characteristics. Finally, using a subset of sites from the U.S. hydropower fleet, we provide a high-level estimation of the hydrokinetic potential available in tailraces in the United States and discuss two case studies. This work advocates for the adoption of hydrokinetic turbines downstream of dams as an opportunity to increase energy production at existing plants and Non-Powered Dams (NPDs) with minimal structural intervention, and, alternatively, as viable sites for large-scale field testing for hydrokinetic devices.

Aerodynamic and codification study of low-rise buildings: Part I – Fully elevated structures

Elevated residential buildings are widely used in cyclone- and hurricane-prone coastal regions, such as Australia and the United States, as an effective solution to mitigate both storm surge damage and the impacts of extreme winds. The recent edition of ASCE 7–22 introduced wind design provisions for elevated structures for the first time, but these provisions remain under ongoing refinement. This study aims to assess the adequacy of the current ASCE 7–22 wind pressure coefficient provisions for elevated structures by conducting large-scale boundary layer wind tunnel tests at FIU's Wall of Wind Facility. The tests explored the aerodynamics of elevated buildings with varying heights and aspect ratios. Eight 1:10 scale gable-roof buildings were constructed based on post-hurricane damage reports, and peak pressure coefficients (GCp) were estimated for the floor, roof, and walls. These values were compared against the existing ASCE 7–22 provisions, revealing a significant underestimation of the external pressure coefficients. Based on the results, this study proposes increasing the GCp boundaries of specific zones by 50%–127% and introduces two new floor zones for more accurate estimation of wind pressure coefficients on elevated buildings. These findings have broad implications for improving the wind performance of elevated structures, particularly in cyclone- and hurricane-prone regions globally. It is envisioned that the results of this study, along with those in the companion paper, will be considered by the ASCE 7 Subcommittee on Wind Loads for potential inclusion in the next edition of ASCE 7–28, contributing to more resilient building designs.

Bayesian hierarchical hypothesis testing in large-scale genome-wide association analysis.

Variable selection and large-scale hypothesis testing are techniques commonly used to analyze high-dimensional genomic data. Despite recent advances in theory and methodology, variable selection and inference with highly collinear features remain challenging. For instance, collinearity poses a great challenge in genome-wide association studies involving millions of variants, many of which may be in high linkage disequilibrium. In such settings, collinearity can significantly reduce the power of variable selection methods to identify individual variants associated with an outcome. To address such challenges, we developed a Bayesian hierarchical hypothesis testing (BHHT)-a novel multiresolution testing procedure that offers high power with adequate error control and fine-mapping resolution. We demonstrate through simulations that the proposed methodology has a power-FDR performance that is competitive with (and in many scenarios better than) state-of-the-art methods. Finally, we demonstrate the feasibility of using BHHT with large sample size (n∼ 300,000) and ultra dimensional genotypes (∼ 15 million single-nucleotide polymorphisms or SNPs) by applying it to eight complex traits using data from the UK-Biobank. Our results show that the proposed methodology leads to many more discoveries than those obtained using traditional SNP-centered inference procedures. The article is accompanied by open-source software that implements the methods described in this study using algorithms that scale to biobank-size ultra-high-dimensional data.

Experimental investigation on the local damage behavior of reinforced concrete-stainless steel membrane composite material structures subjected to large-scale missile impact

Large-scale membrane liquefied natural gas (LNG) storage tanks may experience missile impacts caused by wind or explosions during operation. However, the damage and dynamic response of reinforced concrete (RC) and stainless steel membrane (SSM) composite structures of the tank under such impacts remain unclear. This study addresses this gap by investigating the damage characteristics and dynamic responses of RC-SSM composite structures through eight large-scale missile impact tests. The findings reveal that the RC plates exhibit penetration, scabbing, and perforation damage. Failures at the interface between the SSM insulation system and the RC component are attributed to reverse tensile stress exerted on the rear surface of the RC plate, coupled with rebar-induced actions, ultimately resulting in detachment of its protective layer. Additionally, indirect effects from concrete conical plugs and scab fragments contribute to damage in the SSM insulation system. The impact loads cause the corrugations and knots of the stainless steel membrane to flatten, effectively absorbing a significant amount of impact energy. This observation suggests that the corrugated membrane exhibits superior impact resistance compared to flat films. To meet the requirements of "airtightness," this study establishes five damage modes and proposes an evaluation methodology for RC-SSM composite structures under large-scale missile impacts.

Novel sampling strategy for regular nucleic acid testing in low risk areas during epidemics

Large-scale regular nucleic acid testing (NAT) such as Regular-1/7, played a crucial role in the successful and sustained containment of COVID-19 in China, enabling rapid case detection in low-risk areas. However, Regular-1/7 strategies are extremely costly and time-consuming. To address these challenges and facilitate the broader implementation of large-scale NAT during outbreaks of highly contagious diseases with long incubation periods, we propose a novel sampling strategy called Weighted Hub and Time Sampling (WHTS). This strategy considers the intensity of social activity, the degree of social overlap, and the time interval since the last NAT for each individual. Based on a scale-free contact network model, we simulated the spread of scenario in a community and compared the performance of the WHTS strategy to the Regular-1/7 strategy in terms of cost reduction and shorter alert time. The results show that WHTS-1/14 strategy can save half of the cost, and WHTS-1/7 strategy can alert 1.0 days in advance, compared to Regular-1/7 strategy. Additionally, The WHTS-1/14 strategy also achieves promising results under various scenarios, even though it samples half as many people as the Regular-1/7 strategy. Our study offers a valuable reference for large-scale testing in future efforts to manage emerging infectious diseases.