Changes In Geometry Research Articles

Virtual Sensor for On-Line Hardness Assessment in TIG Welding of Inconel 600 Alloy Thin Plates.

Maintaining high-quality welded connections is crucial in many industries. One of the challenges is assessing the mechanical properties of a joint during its production phase. Currently, in industrial practice, this occurs through NDT (non-destructive testing) conducted after the production process. This article proposes the use of a virtual sensor, which, based on temperature distributions observed on the joint surface during the welding process, allows for the determination of hardness distribution across the cross-section of a joint. Welding trials were conducted with temperature recording, hardness measurements were taken, and then, neural networks with different hyperparameters were tested and evaluated. As a basis for developing a virtual sensor, LSTM networks were utilized, which can be applied to time series prediction, as in the analyzed case of hardness value sequences across the cross-section of a welded joint. Through the analysis of the obtained results, it was determined that the developed virtual sensor can be applied to predict global temperature changes in the weld area, in terms of both its value and geometry changes, with the mean average error being less than 20 HV (mean for model ~35 HV). However, in its current form, predicting local hardness disturbances resulting from process instabilities and defects is not feasible.

Stiffening of the human proximal pulmonary artery with increasing age.

Adverse effects of large artery stiffening are well established in the systemic circulation; stiffening of the proximal pulmonary artery (PPA) and its sequelae are poorly understood. We combined invivo (n = 6) with exvivo data from cadavers (n = 8) and organ donors (n = 13), ages 18 to 89, to assess whether aging of the PPA associates with changes in distensibility, biaxial wall strain, wall thickness, vessel diameter, and wall composition. Aging exhibited significant negative associations with distensibility and cyclic biaxial strain of the PPA (p ≤ 0.05), with decreasing circumferential and axial strains of 20% and 7%, respectively, for every 10 years after 50. Distensibility associated directly with diffusion capacity of the lung (R2 = 0.71, p = 0.03). Axial strain associated with right ventricular ejection fraction (R2 = 0.76, p = 0.02). Aging positively associated with length of the PPA (p = 0.004) and increased luminal caliber (p = 0.05) but showed no significant association with mean wall thickness (1.19 mm, p = 0.61) and no significant differences in the proportions of mural elastin and collagen (p = 0.19) between younger (<50 years) and older (>50) exvivo samples. We conclude that age-related stiffening of the PPA differs from that of the aorta; microstructural remodeling, rather than changes in overall geometry, may explain age-related stiffening.

Numerical Simulation and Thermal Analysis of Pressurized Hydrogen Vehicle Cylinders: Impact of Geometry and Phase Change Materials

This comprehensive study investigates the nuanced aspects of pressurized hydrogen vehicle cylinders during refueling, employing numerical simulation and thermal analysis. The examination encompasses the intricate dynamics influenced by cylinder geometry, mass flow rate variations, and the integration of phase change materials (PCMs). Simulations involving cylinders with diverse length-to-diameter ratios and inlet diameters highlight the impact of these parameters on temperature control. Notably, smaller length-to-diameter ratios prove effective for temperature regulation, while larger inlet diameters mitigate temperature rise. The study further explores the role of varying mass flow rates, revealing that an increasing flow rate during refueling results in the lowest temperature rise. In addition to geometry and mass flow rate considerations, the integration of PCMs is a focal point. Modeling and parametric analysis are employed to assess the feasibility of incorporating these materials. The study contributes valuable insights into optimizing the thermal performance and safety of hydrogen fuel systems. The holistic approach considers the interplay of geometry, mass flow rate dynamics, and the innovative use of PCMs, offering a multifaceted understanding of the factors influencing pressurized hydrogen vehicle cylinders.

Developing improved machine learning methods to predict the flow characteristics through vertical and horizontal transitions in open channels

ABSTRACT Transitions in an open channel refer to the change in flow behavior due to changes in the channel geometry. Determining flow characteristics through transitions is an important topic as it is necessary to guarantee the ideal hydraulic performance of water structures with low costs. This research focuses on the flow characteristics through vertical and horizontal transitions through experimental study and then utilizing machine learning to predict the flow characteristics. The proposed framework aims to develop both the cascade-forward artificial neural network (CFANN) model and the regression model to enhance the prediction of flow characteristics. The first model developed modifies the CFANN using dandelion optimizer (DO) to determine the ideal CFANN configuration. The second model used gene expression programming to develop statistical equations. The obtained CFANN–DO model has proven high accuracy in predicting the flow rates at various water loads and speeds achieving a coefficient of determination of approximately 100% for training data and 99.5% for testing data. Finally, predicting the characteristics of vertical and horizontal transitions in open channels is a critical issue. Manipulating these transitions can create a habitat for aquatic organisms, reduce erosion, and improve the overall environment.

Performance of AI-Based Phase Picking and Event Association Methods after the Large 2023 Mw 7.8 and 7.6 Türkiye Doublet

ABSTRACT On 6 February 2023, a devastating earthquake doublet consisting of Mw 7.8 and 7.6 events separated by about 9 hr struck the southeastern part of Türkiye. The developing aftershock sequence contained thousands of events during the first few days and overwhelmed the routine algorithms handling their detection and location. In addition, several stations temporarily lost real-time contact and came online again later. At the same time the Omori decay of the aftershock event rate reduced the event frequency and allowed for inclusion of progressively smaller-magnitude events with time. One possibility to help deal with such a complex situation is the use of machine learning (ML) methods to generate earthquake catalogs with a substantially higher number of events. Here, we present high-resolution earthquake catalogs derived with two ML association methods for the first five days of the aftershock sequence of this doublet. In terms of the number of reliably located events, the event catalog created from PhaseNet picks and the GENIE phase association method outperforms both the routine regional catalog and the second ML-derived catalog obtained from the GaMMA phase association method. Although both GaMMA and GENIE catalogs detect about 6 times more events than the routine catalog, GENIE associates on average about double the phases to a single event than GaMMA, which results in better constrained event locations. The spatiotemporal evolution of the event rates is sensitive to changes in the network geometry due to variable station availability. During the first few days, no decay of the event rate in the enhanced catalog is observed due to the inclusion of progressively smaller-magnitude events with time and increased station availability. This study indicates that ML-derived earthquake catalogs for challenging time periods like the early aftershock sequences of large earthquakes have the potential to significantly improve routine event catalogs.

Simple, and highly efficient edge-effect surface acoustic wave atomizer

Conventional surface acoustic wave (SAW) atomizers require a direct water supply on the surface, which can be complex and cumbersome. This paper presents a novel SAW atomizer that uses lateral acoustic wetting to achieve atomization without a direct water supply. The device works by simply pressing a piece of wetted paper strip against the bottom of an excited piezoelectric transducer. The liquid then flows along the side to the unmodified surface edge, where it is atomized into a well-converging mist in a stable and sustainable manner. We identified this phenomenon as the edge effect, using numerical simulation results of surface displacement mode. The feasibility of the prototype design was demonstrated by observing and investigating the integrated process of liquid extraction, transport, and atomization. We further explored the hydrodynamic principles of the change and breakup in liquid film geometry under different input powers. Experiments demonstrate that our atomizer is capable of generating high-quality fine liquid particles stably and rapidly even at very high input power. Compared to conventional SAW atomizer, the dispersion of mist width can be scaled down by 70%, while the atomization rate can be increased by 37.5%. Combined with the advantages of easy installation and robustness, the edge effect-based atomizer offers an attractive alternative to current counterparts for applications requiring high efficiency and miniaturization, such as simultaneous synthesis and encapsulation of nanoparticles, pulmonary drug delivery and portable inhalation therapy.

In situ observation and reduction of hot-cracks in laser additive manufacturing

Cracking during Laser Additive Manufacturing is a problem for many higher-strength aluminium alloys, including AA6061. Here, we used a pulsed laser with ramp-down power modulation to improve the cracking resistance by about 50% compared to the use of a rectangular pulsed laser. Using synchrotron in situ X-ray imaging at 100,000 images s−1, ground truth data was obtained about changes in melt pool geometry, solidification rate, and thermal gradients were calculated. An analytical hot cracking model was developed to show that these changes lead to a decreased hot tear susceptibility. Therefore, laser pulse modulation can be an effective tool to reduce crack susceptibility of alloys. More fundamentally, the results demonstrate that modifying thermal conditions provides a pathway to crack elimination in LAM and the model established in our study sets the foundation for further complex laser manipulation in modifying the printability and resulting mechanical properties of hard-to-process alloys in Laser Additive Manufacturing.

Sliding Layer Formation during Tribological Contact between Expanded Graphite and Stainless Steel—A Pilot Study

The sliding layer created during operation of the expanded graphite–steel combination has had a huge impact on the effectiveness of the friction process, and thus on the sustainable development of society. Knowledge of the factors determining the properties of the sliding layer will make it possible to reduce friction resistance in the future through the proper design and selection of sliding pairs for given applications. This paper studies the effect of the moisture content of expanded graphite on the formation of a sliding layer on a stainless steel surface. The tests were carried out in static contact for 30 s and dynamic contact for 15 and 30 min, for loads of 10, 20, and 30 N and speeds of 25 and 50 mm/s. To determine the changes in surface geometry due to material transfer, the Ra roughness value of the surface of stainless steel samples was measured. In order to realize the purpose of the work and evaluate the effect of moist rings on the resulting sliding layer, the results of the surface roughness of stainless steel samples working with dry and moist graphite rings were compiled. The obtained results show that the presence of water in the stainless steel-expanded graphite friction node affects the formation of a sliding layer. The resulting layer reduces the surface roughness of the cooperating materials and prevents their accelerated wear. After 5 min of work with the water-soaked graphite counter-sample, depending on the applied friction conditions, a reduction in the surface roughness of the stainless steel sample was achieved in the range of 11–18% compared to the initial value. After 30 min of operation, the surface roughness decreased by 3 to 25%. Pilot studies have shown that operating conditions influence the formation of a sliding layer in the stainless steel-expanded graphite tribological contact. This confirms the validity of conducting further research in this area.

Estimation of riverbank erosion by combining channel morphological models with AI techniques

Simulating riverbank erosion involves modeling the complex interactions between water flow, sediment transport, and bank stability. The present study employs a novel approach, combining the Self Organizing Map (SOM) algorithm and the Long Short-Term Memory (LSTM) network, to capture the behavior of riverbank erosion. A two-stage training procedure is promoted to enhance predictive accuracy and emphasize the need for preprocessing input data related to hydrological conditions, geomorphological features, and soil properties. Pivotal variables that can characterize changes in channel geometry are designed as the output targets, such as the vertical displacement of the riverbed, the horizontal displacement of the riverbank, and the channel width. The goal of this study is to create an alternative to addressing challenges associated with predicting riverbank erosion by utilizing new training methods of artificial intelligence (AI) models. The proposed method performs well in assessing three output variables, showing low mean relative errors, less than 0.081, and high correlation coefficients above 0.981, along with R-squared values over 0.963. These results highlight the effectiveness of this method in accurately describing cross-sectional changes. The proposed method is designed with practical applications in mind, satisfying the need for methods that are not only accurate but also operationally efficient.

The temporal variability of Io’s hotspots

We investigate the variability of the power emission of Io’s hotspots by using recent Juno/JIRAM infrared observations. The Jovian Infrared Auroral Mapper (JIRAM) is an imaging spectrometer which began observing Jupiter in August 2016. Although observing Jupiter’s moons is not its primary objective, JIRAM can use the frequent opportunities to observe Io (up to once per orbit) to gather infrared images and spectra of its surface. The present study uses the data acquired by JIRAM during the last 2 years, including the location and morphology of Io’s hotspots, and the temporal variability of the total output. A new photometric model for the hotspots and the dayside surface has been developed, which permits us to disentangle the temporal variability from the changes in the observation geometry. While the latitudinal dependence of the power output is not well constrained, low-latitude hotspots show a significantly more intense temporal variability and greater temperature.

Experimental Verification of Geometric Changes Caused by the Release of Residual Stresses for Large-Scale Welded Frames.

This paper presents geometric analyses of welded frames after free relaxing and vibratory stress relief (VSR). The tested frames were components of a prototype packaging machine. Two types of relaxation were carried out to remove stresses introduced as a result of the welding process. One of the frames was subjected to free relaxation, while the other one was subjected to accelerated vibration relaxation. Detection of the frame geometry changes was performed using a photogrammetric system. In addition, an evaluation of the geometry change was conducted for fifteen variants of a steel frame support. A comparative analysis of the geometric deviations of the frames after free and vibratory stress relief confirmed the assumption that the frame post vibration stress relief better reproduces the nominal dimensions. Nevertheless, it should be emphasized that after vibratory stress relief, the frame is not subject to further deformation, which is a desirable effect. In the case of free relaxing, the frame undergoes dimensional changes in a random manner. In summary, carrying out accelerated vibratory stress relief allows for control of spontaneous dimensional changes in the designed frame of a packaging machine resulting from spontaneous relaxation of stresses arising from the welding process. The shortening of the relaxation process of the welded frame is also an unquestionable advantage.

Development of an indirect measurement method for the Contact Tube to Workpiece Distance (CTDW) in the Direct Energy Deposition – Arc (DED-ARC) process for different arc types

During the layer-by-layer build-up in the Direct Energy Deposition (DED) - Arc additive manufacturing (AM) process, the distance between the contact tube and the workpiece, effectively the welded layer, changes. Since the weld paths are predefined by the path planning software, a constant Contact Tube to Workpiece Distance (CTWD) and weld bead height is assumed. However, even small changes in geometry, such as crossovers of weld paths, result in higher weld beads than assumed. Similarly, an incorrectly assumed bead height as input to the path planning will result in a change in the CTWD. The sum of the deviations of the real weld geometries from the assumed ones in the path planning can greatly influence the CTWD. This implies that the dimensional accuracy may be significantly compromised. This research presents an approach for a general indirect measurement method using the welding current to obtain the CTWD during the actual welding process. A real-time process control method is implemented and validated using the mechanically controlled short arc and the pulsed arc process. Varying process parameters are used to validate the general applicability for a specific material. For the mechanically controlled short arc process, the model underestimates the measured CTWD by a mean error of 3.4 mm. The pulse process is overestimated by a mean error of 2.2 mm. The standard deviation for the pulse process with 1.3 mm is slightly smaller than for the short arc process with 1.7 mm.

Analysis of the Impact of Geometry Modifications on the Fit of Splined Shaft Connections Manufactured Using Selected AM Methods

Broadly, understood additive manufacturing techniques expand the spectrum of production of machine parts that are used in various types of devices. However, the requirements to ensure dimensional and shape accuracy require the determination of appropriate material allowances or clearances to enable correct assembly. For the above reasons, the study presents an analysis of the impact of the assumed geometry modifications on the possibility of assembling a splined connection manufactured using selected AM techniques. The work focused on the analysis of changes in geometry resulting from the technology used. Using the Atos II Triple Scan optical measurement system and Gom Inspect software, the possibility of installation was determined for four variants of the splined shaft connection geometry, resulting from the technologies used.

Unveiling the Multielectron Acceptor Properties of π-Expanded Pyracylene: Reversible Boat to Chair Conversion.

In this work, the chemical reduction of a hybrid pyracylene-hexa-peri-hexabenzocoronene (HPH) nanographene was investigated with different alkali metals (Na, K, Rb) to reveal its remarkable multielectron acceptor abilities. The UV-vis and 1H NMR spectroscopy monitoring of the stepwise reduction reactions supports the existence of all intermediate reduction states up to the hexaanion for HPH. Tuning the experimental conditions enabled the synthesis of the HPH anions with gradually increasing reduction states (up to -5) isolated with different alkali metal ions as crystalline materials. The single-crystal X-ray diffraction structure analysis demonstrates that the highly negatively charged HPH anions (-4 and -5) exhibit a drastic geometry change from boat-shaped (observed in the neutral parent, mono- and dianions) to a chair conformation, which was proved to be fully reversible by NMR spectroscopy. DFT calculations show that this geometry change is induced by an enhanced interaction between the coordinated metal ions and negatively charged HPH core in the chair conformation.

The three-dimensional structure of DapE from Enterococcus faecium reveals new insights into DapE/ArgE subfamily ligand specificity

DapE is a Zn2+-metallohydrolase recognized as a drug target for bacterial control. It is a homodimer that requires the exchange of interface strands by an induced fit essential for catalysis. Identifying novel anti-DapE agents requires greater structural details. Most of the characterized DapEs are from the Gram-negative group. Here, two high-resolution DapE crystal structures from Enterococcus faecium are presented for the first time with novel aspects. A loosened enzyme intermediate between the open and closed conformations is observed. Substrates may bind to loose state, subsequently it closes, where hydrolysis occurs, and finally, the change to the open state leads to the release of the products. Mutation of His352 suggests a role, along with His194, in the oxyanion stabilization in the mono-metalated Zn2+ isoform, while in the di-metalated isoform, the metal center 2 complements it function. An aromatic-π box potentially involved in the interaction of DapE with other proteins, and a peptide flip could determine the specificity in the Gram-positive ArgE/DapE group. Finally, details of two extra-catalytic cavities whose geometry changes depending on the conformational state of the enzyme are presented. These cavities could be a target for developing non-competitive agents that trap the enzyme in an inactive state.

Mechanical behavior of graded combined auxetic-honeycomb structures

Various methods such as geometry changes can improve the energy absorption of auxetic structures. In this article, the mechanical behavior of graded combined auxetic-honeycomb structures is investigated through various models of grading. In the graded angle method, the best samples are selected for construction and experimental after performing numerical simulations, and this method comprises both the all-auxetic and honeycomb-auxetic graded angle techniques. Additionally, it is proven that energy absorption can be further increased by adding a reinforced core to the cells of the re-entrant structure. Finally, optimal models for energy absorption are developed by combining the best models of graded angle, graded thickness, and reinforced core. The best of them is the all-auxetic unilateral graded angle with rhombic core auxetic (UGA-A)+(RCA) sample with energy absorption that is three times higher than HAR, which can be utilized in various industrial and sports applications.

Large Deflection Analysis of Functionally Graded Beam by Using Combining Method

In this study, the large deflection behavior of a circular cross-section beam is examined using the Combining Method (CM). The CM is a numerical solution method that uses block diagrams in the Matlab-Simulink program and weighting coefficients in the Differential Quadrature Method (DQM). The beam material considered is Functionally Graded Material (FGM). Boundary conditions of the beam are taken as clamped-free (C-F) and a singular load is assumed to be applied from the free end of the beam. Geometric nonlinear analysis is performed while calculating the large deflection equations of the beam and performing numerical analysis. The effects of increasing the force applied to the beam, changing the beam cross-section in the longitudinal direction, and changing the material index of the FGM on the extreme deflection behavior of the beam were examined. For comparison purposes, the results obtained from CM are compared with the results obtained from both SolidWorks-Simulation and Ansys-Workbench programs. As a result of the analysis, increasing the applied force causes the x and y coordinates of the end point of the beam to decrease. The change in geometry and material index greatly affects the large deflection occurring in the beam.

Age-Invariant Face Recognition Using FaceNet and Multi-task Cascaded Convolutional Networks (MTCNN)

In an era where face recognition technology serves as a cornerstone for security, surveillance, and human-computer interaction, the persistence of age-related variations in facial appearance presents a significant challenge. This research introduces an innovative solution that amalgamates the capabilities of the FaceNet deep learning model with Multi-task Cascaded Convolutional Networks (MTCNN) to achieve precise and robust face recognition across diverse age groups. Leveraging FaceNet's prowess in extracting distinctive features from facial images and mapping them to a high-dimensional feature space for efficient face matching, our system incorporates MTCNN as a pre-processing step to accurately detect and align faces, effectively mitigating age-related changes in facial geometry. Crucially, this novel approach obviates the need for age-specific databases and age group categorization, rendering it a versatile and practical solution for age-invariant face recognition. Rigorous experimentation on benchmark datasets underscores the system's resilience and accuracy across a broad spectrum of age groups, culminating in state-of-the-art results in age-invariant face recognition. The implications of this proposed approach are profound, promising to fortify security measures and enhance user experiences in applications such as access control, personal identification, and customer service, while ensuring dependable and accurate face recognition, irrespective of an individual's age. Key Words: Face recognition, face aging, generative adversarial networks

Predicting the artificial dynamical acceleration of binary hydrocarbon mixtures upon coarse-graining with roughness volumes and simple averaging rules.

Coarse-grained (CG) molecular models greatly reduce the computational cost of simulations allowing for longer and larger simulations, but come with an artificially increased acceleration of the dynamics when compared to the parent atomistic (AA) simulation. This impedes their use for the quantitative study of dynamical properties. During coarse-graining, grouping several atoms into one CG bead not only reduces the number of degrees of freedom but also reduces the roughness on the molecular surfaces, leading to the acceleration of dynamics. The RoughMob approach [M. K. Meinel and F. Müller-Plathe, J. Phys. Chem. B 126(20), 3737-3747 (2022)] quantifies this change in geometry and correlates it to the acceleration by making use of four so-called roughness volumes. This method was developed using simple one-bead CG models of a set of hydrocarbon liquids. Potentials for pure components are derived by the structure-based iterative Boltzmann inversion. In this paper, we find that, for binary mixtures of simple hydrocarbons, it is sufficient to use simple averaging rules to calculate the roughness volumes in mixtures from the roughness volumes of pure components and add a correction term quadratic in the concentration without the need to perform any calculation on AA or CG trajectories of the mixtures themselves. The acceleration factors of binary diffusion coefficients and both self-diffusion coefficients show a large dependence on the overall acceleration of the system and can be predicted a priori without the need for any AA simulations within a percentage error margin, which is comparable to routine measurement accuracies. Only if a qualitatively accurate description of the concentration dependence of the binary diffusion coefficient is desired, very few additional simulations of the pure components and the equimolar mixture are required.

Inversion isomerism induced by the Pseudo Jahn-Teller Effect in X2CE molecules (X = H, F; E = O, S, Se) in their reduced and excited states

The pseudo-Jahn-Teller effect (PJTE) is employed to reveal the origin of molecular geometry changes induced by reduction and excitation, using a series of X2CE molecules (X = H, F, Cl; E = C, S, Se) as examples. Their nuclear configuration is planar with C 2v symmetry in the ground electronic state. However, when reduced, they acquire a nonplanar pyramidal structure with an elongated C-E bond in their ground and lowest excited electronic states 1A2 and 3A2. It is shown that these distortions are due to the PJT mixing of the reference electronic states with appropriate excited states via the b 1 vibrational mode. The PJTE is shown to reasonably parametrize the adiabatic potential energy curve ε(Qb 1) along the instability coordinate Qb 1.