Classical Experiments Research Articles

Optimizing microseismic monitoring: a fusion of Gaussian–Cauchy and adaptive weight strategies

Abstract In mining mineral resources, it is vital to monitor the stability of the rock body in real time, reasonably regulate the area of ground pressure concentration, and guarantee the safety of personnel and equipment. The microseismic signals generated by monitoring the rupture of the rock body can effectively predict the rock body disaster, but the current microseismic monitoring technology is not ideal. In order to address the issue of microseismic monitoring in deep wells, this research suggests a machine learning-based model for predicting microseismic phenomena. First, this work presents the random spare, double adaptive weight, and Gaussian–Cauchy fusion strategies as additions to the multi-verse optimizer (MVO) and suggests an enhanced MVO algorithm (RDGMVO). Subsequently, the RDGMVO-Fuzzy K-Nearest Neighbours (RDGMVO-FKNN) microseismic prediction model is presented by combining it with the FKNN classifier. The experimental section compares 12 traditional and recently enhanced algorithms with RDGMVO, demonstrating the latter’s excellent benchmark optimization performance and remarkable improvement effect. Next, the FKNN comparison experiment, the classical classifier experiment, and the microseismic dataset feature selection experiment confirm the precision and stability of the RDGMVO-FKNN model for the microseismic prediction problem. According to the results, the RDGMVO-FKNN model has an accuracy above 89%, indicating that it is a reliable and accurate method for classifying and predicting microseismic occurrences. Code has been available at https://github.com/GuaipiXiao/RDGMVO.

Fractional-Order Boosted Hybrid Young's Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization.

Inspired by classical experiments that uncovered the inherent properties of light waves, Young's Double-Slit Experiment (YDSE) optimization algorithm represents a physics-driven meta-heuristic method. Its unique search mechanism and scalability have attracted much attention. However, when facing complex or high-dimensional problems, the YDSE optimizer, although striking a good balance between global and local searches, does not converge as fast as it should and is prone to fall into local optimums, thus limiting its application scope. A fractional-order boosted hybrid YDSE, called FYDSE, is proposed in this article. FYDSE employs a multi-strategy mechanism to jointly address the YDSE problems and enhance its ability to solve complex problems. First, a fractional-order strategy is introduced into the dark edge position update of FYDSE to ensure more efficient use of the search potential of a single neighborhood space while reducing the possibility of trapping in a local best. Second, piecewise chaotic mapping is constructed at the initial stage of the population to obtain better-distributed initial solutions and increase the convergence rate to the optimal position. Moreover, the low exploration space is extended by using a dynamic opposition strategy, which improves the probability of acquisition of a globally optimal solution. Finally, by introducing the vertical operator, FYDSE can better balance global exploration and local exploitation and explore new unknown areas. The numerical results show that FYDSE outperforms YDSE in 11 (91.6%) of cec2022 sets. In addition, FYDSE performs best in 8 (66.6%) among all algorithms. Compared with the 11 methods, FYDSE obtains the optimal best and average weights for the 20-bar, 24-bar, and 72-bar truss problems, which proves its efficient optimization capability for difficult optimization cases.

An asynchronous, hands-off workflow for looking time experiments with infants.

The study of infant gaze has long been a key tool for understanding the developing mind. However, labor-intensive data collection and processing limit the speed at which this understanding can be advanced. Here, we demonstrate an asynchronous workflow for conducting violation-of-expectation (VoE) experiments, which is fully "hands-off" for the experimenter. We first replicate four classic VoE experiments in a synchronous online setting, and show that VoE can generate highly replicable effects through remote testing. We then confirm the accuracy of a state-of-the-art gaze annotation software, iCatcher+ in a new setting. Third, we train parents to control the experiment flow based on the infant's gaze. Combining all three innovations, we then conduct an asynchronous automated infant-contingent VoE experiment. The hands-off workflow successfully replicates a classic VoE effect: infants look longer at inefficient actions than efficient ones. We compare the resulting effect size and statistical power to the same study run in-lab and synchronously via Zoom. The hands-off workflow significantly reduces the marginal cost and time per participant, enabling larger sample sizes. By enhancing the reproducibility and robustness of findings relying on infant looking, this workflow could help support a cumulative science of infant cognition. Tools to implement the workflow are openly available. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Multi-factor coupling analysis of electric field distribution in electrochemical machining with electrolyte suction tool

Electrochemical machining (ECM) technology holds significant potential for applications in high accuracy engineering and manufacturing. To confine the electrolyte region during ECM and mitigate the effects of reaction products and heat generation, an electrolyte suction tool has been proposed. However, the complex electric field distribution on the anode surface during the application of pulse voltage, limits the further utilization of ECM with suction tool. A multi-physics simulation model is established to calculate the region of electrolyte confinement by the suction tool, current density distribution within the electrolyte region, and material removal. The model considers the combined effects of polarization and double layer, and all key parameters are calibrated through classical electrochemical testing experiments rather than fitted based on the predicted results. This study elucidates the transient response of current density on the anode surface during the application of pulse voltage. The simulation accuracy is validated by comparing experimental and simulated current waveforms, as well as material removal profiles under different pulse parameters and electrode shapes. This research is of great significance for improving surface precision and controllability of complex structures in ECM with suction tool, promoting its further application in the field of precision machining.

Material Parameter Identification for a Stress-State-Dependent Ductile Damage and Failure Model Applied to Clinch Joining

Similar to bulk metal forming, clinch joining is characterised by large plastic deformations and a variety of different 3D stress states, including severe compression. However, inherent to plastic forming is the nucleation and growth of defects, whose detrimental effects on the material behaviour can be described by continuum damage models and eventually lead to material failure. As the damage evolution strongly depends on the stress state, a stress-state-dependent model is utilised to correctly track the accumulation. To formulate and parameterise this model, besides classical experiments, so-called modified punch tests are also integrated herein to enhance the calibration of the failure model by capturing a larger range of stress states and metal-forming-specific loading conditions. Moreover, when highly ductile materials are considered, such as the dual-phase steel HCT590X and the aluminium alloy EN AW-6014 T4 investigated here, strong necking and localisation might occur prior to fracture. This can alter the stress state and affect the actual strain at failure. This influence is captured by coupling plasticity and damage to incorporate the damage-induced softening effect. Its relative importance is shown by conducting inverse parameter identifications to determine damage and failure parameters for both mentioned ductile metals based on up to 12 different experiments.

Improved Amott Method to Determine Oil Recovery Dynamics from Water-Wet Limestone Using GEV Statistics

Counter-current spontaneous imbibition of water is a critical oil recovery mechanism. In the laboratory, the Amott test is a commonly used method to assess the efficacy of brine imbibition into oil-saturated core plugs. The classic Amott-cell experiment estimates ultimate oil recovery, but not the recovery dynamics that hold fundamental information about the imbibition mechanisms. Retention of oil droplets at the outer core surface and initial production delay are the two key artifacts of the classic Amott experiment. This retention, referred to here as the “external-surface oil holdup effect” or simply “oil holdup effect”, often results in stepwise recovery curves that obscure the true dynamics of spontaneous imbibition. To address these holdup drawbacks of the classic Amott method, we modified the Amott cell and experimental procedure. For the first time, using water-wet Indiana limestone cores saturated with brine and mineral oil, we showed that our improvements of the Amott method enabled accurate and reproducible measurements of oil recovery dynamics. Also for the first time, we used the generalized extreme value (GEV) statistics to describe oil production histories from water-wet heterogeneous limestone cores with finite initial water saturations. We demonstrated that our four-parameter GEV model accurately described the recovery dynamics, and that optimal GEV parameter values systematically reflected the key characteristics of the oil–rock system, such as oil viscosity and rock permeability. These findings gave us a more fundamental understanding of spontaneous, counter-current imbibition mechanisms and insights into what constitutes a predictive model of counter-current water imbibition into oil-saturated rocks with finite initial water saturation.

Holistic analysis of glyphosate formulations with nuclear magnetic resonance, similarity calculations and differential NMR

Glyphosate is the most widely used herbicide in the world. Due to varying formulations, common adulteration and illegal trade there is an extreme need to monitor the composition of formulations to ensure the safety. Similarity calculations and differential NMR allowed the assessment of all organic compounds of the mixture, down to the detection limit in the submicrogram range. Glyphosate, isopropylamine and polyoxyethylene tallow amines (POEA) were among the compounds detected together with components classified as impurities such as methanol and acetone. The quantities of the analyzed compounds range from several dozens of milligrams of glyphosate down to submicrogram quantities of methanol and acetone in the NMR tube. Glyphosate was quantified using a fitted calibration curve that, in comparison to classic qNMR experiments, needed shorter measuring times. Among the co-formulants, the one of greatest environmental interest is polyoxyethylene tallow amine especially because it might be more harmful than glyphosate itself. This work illustrates the value of NMR, with calculation of similarities and differential NMR for the rapid comparison and assessment of samples, taking into account major and minor components in the formulations, many of these being industrial secrets.

Rigor and objectivity as foundations of the rationality of physics in Evandro Agazzi

In current epistemology, there are two opposing attitudes towards the empirical sciences. Onthe one hand, they appear as an essential tool for the advancement of knowledge. On the otherhand, there is doubt about the metaphysical and epistemological bases of this confidence inscientific knowledge, which has led science down paths of skepticism and pragmatism. This paper aims to contribute philosophically to the rationality and ontological status of physics, taking as a starting point some works of the philosopher of science Evandro Agazzi. The article presented hereintroduces Agazzi’s thought and the core issues of his epistemology. It then defines the concepts of rigor and objectivity as understood by Agazzi, and finally establishes criteria of rigor and objectivity for physics, showing how they are verified in two classical experiments. Based on these ideas, it is shown that physics, as the science it is, has criteria of rigor and objectivity that allow it to effectively reach the real, thus responding to the formalist and pragmatist challenge. Thus, the article does notexhaust itself in a description of Agazzi’s thought, but will apply his ideas to the concrete field of physics, making explicit ideas that have not been sufficiently made explicit by the Italian philosopher.

A Modular Variable Temperature FT-IMS Instrument Optimized for Gas-Phase Ion Chemistry Applications.

The latest iteration of modular, open-source rolled ion mobility spectrometers was characterized and tailored for heated ion chemistry experiments. Because the nature of ion-neutral interactions is innately linked to the temperature of the drift cell, heated IMS experiments explicitly probe the fundamental characteristics of these collisions. While classic mobility experiments examine ions through inert buffer gases, doping the drift cell with reactive vapor enables desolvated chemical reactions to be studied. By using materials with minimal outgassing and ensuring the isolation of the drift tube from the surrounding ambient conditions, an open-source drift cell outfitted with heating components enables investigations of chemical reactions as a function of temperature. We show here that elevated temperatures facilitate an increase in deuterium incorporation and allow for hydrogen/deuterium exchanges otherwise unattainable under ambient conditions. While the initial fast exchanges get faster as temperature is increased, the slow rate which rises from the kinetic nonlinearity though to be attributed to ion-neutral clustering, remains constant with no change in mobility shifts. Additionally, we show the analytical merit of multiplexing mobility data by comparing the performance of traditional signal-averaging and FT-IMS modes.

An experiment for the study of projectile motion

The classic demonstration experiment of the motion of a point mass thrown at an angle to the horizon is studied. Several measurements of the range of a projectile launched sphere are carried out and compared with the results that were obtained by an analytical approach. The sphere’s motion can be treated as two independent movements, a linear uniform movement in the horizontal direction and a uniformly accelerated motion in the vertical direction. The value of launching velocity obtained by kinematics is compared with those predicted by the law of mechanical energy conservation. The conclusion is that the model of a frictionless sliding sphere is far from explaining the experimental result. The model could be improved proposing that the sphere rolls without sliding (pure rolling) on the platform including the rotational kinetic energy. Finally, the fact that the sphere does not settle completely on the launch rail was considered using an effective radius of rotation. Observed from the three proposed models, the last one is the closest to the obtained experimental value. These activities can also improve students’ understanding of the concept of projectile motion.

Dynamical Tests of a Deep Learning Weather Prediction Model

Abstract Global deep learning weather prediction models have recently been shown to produce forecasts that rival those from physics-based models run at operational centers. It is unclear whether these models have encoded atmospheric dynamics or simply pattern matching that produces the smallest forecast error. Answering this question is crucial to establishing the utility of these models as tools for basic science. Here, we subject one such model, Pangu-Weather, to a set of four classical dynamical experiments that do not resemble the model training data. Localized perturbations to the model output and the initial conditions are added to steady time-averaged conditions, to assess the propagation speed and structural evolution of signals away from the local source. Perturbing the model physics by adding a steady tropical heat source results in a classical Matsuno–Gill response near the heating and planetary waves that radiate into the extratropics. A localized disturbance on the winter-averaged North Pacific jet stream produces realistic extratropical cyclones and fronts, including the spontaneous emergence of polar lows. Perturbing the 500-hPa height field alone yields adjustment from a state of rest to one of wind–pressure balance over ∼6 h. Localized subtropical low pressure systems produce Atlantic hurricanes, provided the initial amplitude exceeds about 4 hPa, and setting the initial humidity to zero eliminates hurricane development. We conclude that the model encodes realistic physics in all experiments and suggest that it can be used as a tool for rapidly testing a wide range of hypotheses.

The Roles of Thomson and Rutherford in the Birth of Atomic Physics:The Interaction of Experiment and Theory

AbstractThe discovery of the electron in 1897 by J. J. Thomson meant that the atom was no longer the smallest unit of matter. This led to a set of responses both experimental and theoretical which consolidated a new branch of physics—atomic physics. What were the tools available at the time to address atomic physics and how were they deployed? The research begins with Thomson who sought to describe a structure of the atom that accommodates both mechanical and electromagnetic properties, but he had little experimental data to base it on. It was indeed an experimental finding which paved the way for the modern conception of the structure of the atom—Rutherford's scattering experiment. A complex relation between theory and experiment in a new domain of physics is uncovered. While the revolutionary discovery of the electron was the result of a classical propagation experiment, the discovery of the concentrated charge at the center of the atom was an outcome of a scattering experiment—a bombardment technique. This technique has turned out to be the hallmark of experimental atomic physics.

Air speed and direction affect metabolic and thermoregulatory responses during walking and running in a temperate environment.

Revisiting classical experiments on the impact of air resistance on metabolic rate, we aimed to overcome limitations of previous research, notably: low participant numbers (n = 1-3), highly turbulent wind, and confounding effects of rising body temperature. In a custom-built wind tunnel with reduced turbulence, 14 participants (8 males, 6 females) walked (5 km·h-1) and ran on a treadmill (70%V̇o2max) at 0, 2, 4, and 6 m·s-1 headwind or tailwind in a counterbalanced design, with rest breaks between each exposure to avoid rises in body core temperature. Oxygen consumption (V̇o2) exhibited strong linear relationships versus wind direction, dynamic pressure, and air speed squared (Vwr2), lower in magnitude for headwind than tailwind. A moderate linear relationship was observed between heart rate, wind direction, dynamic pressure, and Vwr2. Below 4 m·s-1, the effect of wind was well within inter- and intraindividual variation and equipment uncertainty, and only at wind speeds ≥4 m·s-1 did the differences in physiological responses reach statistical significance. Our data indicate that at running speeds below 4 m·s-1 (14.4 km/h), indoor treadmills and outdoor running are comparable in terms of the metabolic impact of air movement relative to the person. However, this does not extend to the thermoregulatory effect of wind, with outdoor running providing a higher cooling rate due to the self-generated wind created during running. By removing the confounding impact of core temperature rises, the observed effects of headwind were lower and those of tailwind larger than observed previously. In the context of middle-distance running, the headwind created by running at 21.5 km·h-1 would result in a 2.2% increase of V̇o2. A relative tailwind of the same speed would lead to a 3.1% reduction.NEW & NOTEWORTHY Revisiting classical work by Pugh and Davies on the metabolic effects of air speed and direction, shortcomings in the original studies were addressed. Using more participants, less turbulent wind, and avoiding confounding effects of work-induced core temperature increases, new equations describing the impact of air speed/direction were developed. This study observed a lower impact of headwind and a larger impact of tailwind in the absence of an exercise-induced core temperature increase.

A new discrete element method for small adhesive non-spherical particles

Small adhesive particles with non-spherical shapes are common in natural and industrial processes. However, it is challenging to accurately simulate the dynamic behaviors of non-spherical particulate systems, not only due to the complex local geometry at the contact region but also to the non-linear coupling between the van der Waals adhesion and the elastic deformation. In this paper, we develop a discrete element method (DEM) framework for small non-spherical particles. Particularly, we present a simple algorithm for solving the implicit equations of the dimensionless generalized JKR model, to accurately resolve the local surface geometry at the contact region and the strong coupling between the elastic deformation and the surface adhesion. New explicit expressions are established for the pull-off force, overlap and minor-to-major ratio of the contact ellipse, to naturally capture the pull-off point upon collision. Then the actual contact parameters including the contact radius, curvatures and overlap are used to modify the interparticle interactions, including the normal elastic-adhesive-dissipative force and sliding-rolling-twisting resistances. Finally, the framework is quantitatively validated by four random packing problems, including adhesive spheres, ellipsoids, spherocylinders and dimers, and the representative non-adhesive ellipsoids. Both the microscopic and macroscopic properties of packings agree well with a large number of classic theories, experiments and simulations, showing the satisfactory accuracy and effectiveness. The newly developed adhesive DEM framework has the full capability to dynamically simulate the collision-related behaviors of complex shaped particles in the presence of van der Waals adhesion and frictional forces.

Studying and improving reasoning in humans and machines

In the present study, we investigate and compare reasoning in large language models (LLMs) and humans, using a selection of cognitive psychology tools traditionally dedicated to the study of (bounded) rationality. We presented to human participants and an array of pretrained LLMs new variants of classical cognitive experiments, and cross-compared their performances. Our results showed that most of the included models presented reasoning errors akin to those frequently ascribed to error-prone, heuristic-based human reasoning. Notwithstanding this superficial similarity, an in-depth comparison between humans and LLMs indicated important differences with human-like reasoning, with models’ limitations disappearing almost entirely in more recent LLMs’ releases. Moreover, we show that while it is possible to devise strategies to induce better performance, humans and machines are not equally responsive to the same prompting schemes. We conclude by discussing the epistemological implications and challenges of comparing human and machine behavior for both artificial intelligence and cognitive psychology.

Toward Building a Virtual Laboratory to Investigate Rainfall Microphysics at Process Scales

Abstract A 3D numerical model was built to serve as a virtual microphysics laboratory (VML) to investigate rainfall microphysical processes. One key goal for the VML is to elucidate the physical basis of warm precipitation processes toward improving existing parameterizations beyond the constraints of past physical experiments. This manuscript presents results from VML simulations of classical tower experiments of raindrop collisional collection and breakup. The simulations capture large raindrop oscillations in shape and velocity in both horizontal and vertical planes and reveal that drop instability increases with diameter due to the weakening of the surface tension compared with the body force. A detailed evaluation against reference experimental datasets of binary collisions over a wide range of drop sizes shows that the VML reproduces collision outcomes well including coalescence, and disk, sheet, and filament breakups. Furthermore, the VML simulations captured spontaneous breakup, and secondary coalescence and breakup. The breakup type, fragment number, and size distribution are analyzed in the context of collision kinetic energy, diameter ratio, and relative position, with a view to capture the dynamic evolution of the vertical microstructure of rainfall in models and to interpret remote sensing measurements. Significance Statement Presently, uncertainty in precipitation estimation and prediction remains one of the grand challenges in water cycle studies. This work presents a detailed 3D simulator to characterize the evolution of drop size distributions (DSDs), without the space and functional constraints of laboratory experiments. The virtual microphysics laboratory (VML) is applied to replicate classical tower experiments from which parameterizations of precipitation processes used presently in weather and climate models and remote sensing algorithms were derived. The results presented demonstrate that the VML is a robust tool to capture DSD dynamics at the scale of individual raindrops (precipitation microphysics). VML will be used to characterize DSD dynamics across scales for environmental conditions and weather regimes for which no measurements are available.

Effect of Temperature on Calcium‐Based Chemical Garden Growth

AbstractHydrothermal vents maintain far‐from equilibrium conditions that may have provided the necessary settings for the origin of life. To understand reactions under these physicochemical conditions, scientists have turned to the classic demonstration experiment, chemical gardens. The self‐organization of precipitate tubes separates high and low pH environments similarly to the naturally occurring geological structures. Here, we report calcium‐based chemical gardens forming in solutions containing anions of silicate, carbonate, or a mixture of the two in 100 °C and 23 °C environments. Under high temperature conditions, chemical gardens tend to have faster average growth velocities and form taller structures. We measure the composition of the precipitate tubes using Fourier transform infrared spectroscopy and find the formation of all polymorphs of calcium carbonate along with calcium silicates.

Investigation of preference for local and global processing of Capuchin-monkeys (Sapajus spp.) in shape discrimination of mosaic arrangements.

Classical experiments using hierarchical stimuli to investigate the ability of capuchin monkeys to integrate visual information based on global or local clues reported findings suggesting a behavioral preference for local information of the image. Many experiments using mosaics have been conducted with capuchin monkeys to identify some of their perceptual phenotypes. As the identification of an image in a mosaic demands the integration of elements that share some visual features, we evaluated the discrimination of shapes presented in solid and mosaic stimuli in capuchin monkeys. Shape discrimination performance was tested in 2 male adult capuchin monkeys in an experimental chamber with a touchscreen video monitor, in three experiments: (i) evaluation of global and local processing using hierarchical stimuli; (ii) evaluation of target detection using simple discrimination procedures; (iii) evaluation of shape discrimination using simple discrimination and delayed matching-to-sample procedures. We observed that both monkeys had preferences for local processing when tested by hierarchical stimuli. Additionally, detection performance for solid and mosaic targets was highly significant, but for shape discrimination tasks we found significant performance when using solid figures, non-significant performance when using circle and square shapes in mosaic stimuli, and significant performance when using Letter X and Number 8 shapes in mosaic stimuli. Our results are suggestive that the monkeys respond to local contrast and partly to global contrast in mosaic stimuli.

Identity and inequality misperceptions, demographic determinants and efficacy of corrective measures

By conducting two waves of large-scale surveys in the United Kingdom and Germany, we investigate the determinants of identity and inequality misperceptions. We first show that people substantially overestimate the share of immigrants, Muslims, people under the poverty line, and the income share of the richest. Moreover, women, lower-income, and lower-educated respondents generally have higher misperceptions. Only income share misperceptions are associated more with people who place themselves on the left of the political spectrum. In contrast, the other three misperceptions are more prevalent among those who place themselves to the right. We then attempt to correct misperceptions by conducting a classic controlled experiment. Specifically, we randomly assign respondents into a treatment group informed about their initial misperceptions and a control group left uninformed. Our results indicate that information treatments had some corrective effects on misperceptions in Germany but were ineffective in the United Kingdom. Moreover, information treatments in Germany were more effective for men, centrists, and highly educated respondents. There is also no evidence of spill-over effects: correcting one misperception does not have corrective effects for the other misperceptions.

Recent Developments in the Use of High Pressures for the Production of Nanostructured Materials

The use of pressure to achieve superior properties in metals, especially for use in a range of weaponry, has a long history dating back to the artisans of ancient China and many parts of Asia. Nevertheless, scientific principles were not introduced until the classic experiments conducted by Nobel Laureate Professor Percy Bridgman at Harvard University almost 100 years ago and these experiments led directly to the development of metal processing through the procedure now known as high‐pressure torsion (HPT). This review provides a brief overview of the historical evolution of pressure as a convenient tool in metal‐working and then summarizes the major features associated with the processing of metals by HPT and, more recently, the torsional straining of stacked disks in HPT to produce a range of hybrid materials. Finally, there is a brief report on the development of the relatively new processing procedure of tube high‐pressure shearing (t‐HPS) which may be used for the fabrication of metal matrix composites.