Search Results (218)

As the global demand for clean and efficient energy continues to grow, the development of advanced energy storage technologies is becoming increasingly important. This study explores the influence of the dead volume coefficient and pulse-width modulation (PWM) control strategy on the performance of a piston expander in a micro-compressed air energy storage system. Simulation results showed that low dead volume values, combined with short air supply durations with PWM values between 0.1 and 0.2, led to improved energy utilization. This was achieved through complete piston strokes and stable power output. In contrast, high dead volume values and high PWM settings, such as 0.9, resulted in incomplete air expansion, excessive air consumption, and a significant reduction in overall system efficiency, even though peak power output may increase. Sensitivity analysis confirmed that PWM had a major impact on efficiency, with the highest value of 0.76 achieved for a dead volume coefficient of 0.05 and a PWM value of 0.2. Under these operating conditions, the expander delivered a generated power output of 970 W. Additionally, PWM enabled flexible control of power output, without requiring modifications to the system’s physical design. The study highlights the importance of adjusting the air admission strategy to match the internal volume characteristics. Full article

To address the multipath delay estimation problem in distributed hydrophone passive localization systems, a global energy minimization-based method is proposed in this paper. In this method, correlation pulses are treated as tracking targets, and their trajectories are estimated from correlograms formed by multiple frames. Specifically, an energy function is designed to jointly encode pulse similarity, motion continuity, trajectory persistence, data fidelity, and regularization, thereby reformulating multipath delay estimation as a global optimization problem. In order to balance the discreteness of observations and the continuity of trajectories, the optimization process is implemented alternating between discrete association (solved via $\alpha$-expansion) and continuous trajectory fitting (using weighted cubic splines). Furthermore, a dynamic hypothesis space expansion strategy based on trajectory merging and splitting is introduced to improve robustness while accelerating convergence. By exploiting both the intrinsic characteristics of correlation pulses in multi-frame processing and the physical properties of motion trajectories, the proposed method achieves higher tracking accuracy without requiring prior knowledge of the number of delay trajectories in a noisy environment. Numerical simulations under various noise conditions and sea trial results validate the superiorities of the proposed multipath delay estimation method. Full article

A finite element simulation was conducted to analyze the thermal damage caused by a 532nm nanosecond pulsed laser on a CCD detector. A three-dimensional model was developed to study the temperature field variations within the detector. The simulation was centered on the laser-induced temporal progression of thermal damage in the CCD. Results showed that higher laser fluence led to increased heat accumulation, resulting in the expansion of the thermal damage area. Different thermal damage patterns were observed in the light sensor region and the light-shielded region. In the light sensor region, the melting of the silicon substrate expanded more in the transverse direction compared to the longitudinal direction with increasing laser fluence, while damage in the light-shielded region extended from the edges towards the center as laser fluence increased. These distinct damage patterns were attributed to different energy deposition patterns and structural differences between the light sensor region and the light-shielded region. Full article

Lithium niobate (LiNbO₃, LN) is a multifunctional material with broad applicability in photonic and electronic devices. Recent advances in lithium niobate on insulator (LNOI) technology have significantly enhanced the integration density and miniaturization potential of LN-based platforms. Among the various fabrication techniques available, pulsed laser deposition (PLD) presents a cost-effective and versatile alternative to crystalline ion slicing (CIS), particularly advantageous for achieving high doping concentrations. However, a persistent challenge in PLD-grown lithium niobate film is cracking, primarily induced by the substantial thermal stress resulting from the mismatch in thermal expansion coefficients between LN and the substrate. In this study, we implemented a series of process modifications to address the cracking issue and successfully achieved crack-free LN films by introducing a lithium-deficient phase. This approach enabled the successful fabrication of highly Fe³⁺-doped LN films with a high electrical conductivity of 9.95 × 10⁻⁵ S/m while also exhibiting characteristic polarization switching behavior. These results demonstrate that PLD enables the fabrication of highly doped, structurally robust LN films and holds significant potential for the development of advanced electronic and optoelectronic devices. Full article

A new approach is presented to elucidate the phenomena that occur within a porous single-walled carbon nanotubes (SWCNTs) modified glassy carbon electrode (GCE) and that influence the electrochemical behavior of the modified electrode. By employing cyclic voltammetry, reverse pulse voltammetry, and double potential step chronoamperometry, insights into the structural changes in the electrochemical double layer and the mass transport regimes are gained. An analysis of the reduction of the electrochemically generated [Fe(CN)₆]³⁻ shows that the SWCNTs layer can be considered inactive. However, their pronounced influence on the electrochemical signal arises from their capacitive behavior. Furthermore, a novel criterion for distinguishing the mass transport domains is proposed, which allows the estimation of the points at which a change in the mass transport regime occurs. The results also show the role of the porous SWCNTs layer in preventing the expansion of the double layer as well as in the process of ion condensation in the Gouy-Chapman layer. Finally, the counterintuitive and unexpected voltametric behavior, such as the independence of the current peak heights from the ionic strength of the support, the parabolic dependence of the peak potential on the scan rates, and the occurrence of steady-state currents, are discussed. Full article

For the pulsed data streams emitted by multiple signal sources that generate aliasing, traditional density clustering algorithms have the problems of poor clustering effect, heavy reliance on manual experience to set the parameters, and the need to carry out density clustering every time new data are input, resulting in a huge amount of computation. Therefore, an online density clustering algorithm based on the improved golden sine whale optimization is proposed. First, by adding new parameters to the density clustering algorithm, the neighborhood is changed from a single parameter Eps to a joint decision of the parameters Eps and $\theta$, which avoids cross-cluster expansion by more flexibly delimiting the neighborhood range. The improved golden sine whale optimization algorithm is then used to obtain the optimal parameter solution of the DBSCAN algorithm. Finally, the idea of flow clustering is introduced to determine whether a pulse belongs to a valid library, an outlier library, or an inactive library by comparing the distance between the input pulse and each cluster center, effectively reducing the number of pulses required for analysis. The experiment proves that the algorithm improves the sorting accuracy by 57.7% compared to the DBSCAN algorithm and 37.8% compared to the WOA-DBSCAN algorithm. Full article

Facing challenges of low efficiency and severe wear in deep hard formations with conventional drilling bits, this study investigates the synergistic rock-breaking technology combining a pulsed CO₂ laser with mechanical bits. The background highlights the need for novel methods to enhance drilling speed in high-strength, abrasive strata where traditional bits struggle. The theoretical analysis explores the thermo-mechanical coupling mechanism, where pulsed laser irradiation rapidly heats the rock surface, inducing thermal stress cracks, micro-spallation, and strength reduction through mechanisms like mineral thermal expansion mismatch and pore fluid vaporization. This pre-damage layer facilitates subsequent mechanical fragmentation. The research employs finite element numerical simulations (using COMSOL Multiphysics with an HJC constitutive model and damage evolution criteria) to model the coupled laser–mechanical–rock interaction, capturing temperature fields, stress distribution, crack propagation, and assessing efficiency. The results demonstrate that laser pre-conditioning significantly achieves 90–120% higher penetration rates compared to mechanical-only drilling. The dominant spallation mechanism proves energy-efficient. Conclusions affirm the feasibility and significant potential of CO₂ laser-assisted drilling for deep formations, contingent on optimized laser parameters, composite bit design (incorporating laser transmission, multi-head layout, and environmental protection), and addressing challenges, like high in-situ stress and drilling fluid interference through techniques like gas drilling. Future work should focus on high-power laser downhole transmission, adaptive control, and rigorous field validation. Full article

Achieving high efficiency and quality in millisecond pulsed laser drilling of metallic through-holes is contingent on precise process control. This study introduces a penetration detection-based method to determine the pulse count threshold, effectively overcoming the limitations of conventional approaches. We systematically investigated the effects of pulse energy, defocus, and beam expansion ratio on the drilling of 3 mm thick 304 stainless steel and TC4 titanium alloy. The experiments revealed that for stainless steel 304, the minimum taper angle was achieved at a pulse energy of 2.2 J, a defocus amount of −0.5 mm, and a beam expansion ratio of 2.5. Additionally, relatively high drilling efficiency was observed when the pulse energy ranged from 2.6 to 2.8 J, the defocus amount was −1 to 0 mm, and the beam expansion ratio was 3 to 4. For titanium alloy TC4, the minimum taper angle was achieved at a pulse energy of 2.6 J, a defocus amount of −0.5 mm, and a beam expansion ratio of 3.5. High drilling efficiency was recorded when the pulse energy was 2.8 J, the defocus amount was −0.5 mm, and the beam expansion ratio ranged from 2.5 to 3. When stainless steel 304 and titanium alloy TC4 were processed using the same laser parameters, the drilling efficiency of stainless steel 304 was higher than that of titanium alloy TC4 under the same conditions. This work provides a practical process control strategy and a valuable parameter database for high-quality, efficient laser drilling of these industrially important metals. Full article

The shallow water equations (SWEs) model fluid flow in rivers, coasts, and tsunamis. Their nonlinearity challenges analytical solutions. We present a numerical algorithm combining the finite integration method with Chebyshev polynomial expansion (FIM-CPE) to solve one- and two-dimensional SWEs. The method transforms partial differential equations into integral equations, approximates spatial terms via Chebyshev polynomials, and uses forward differences for time discretization. Validated on stationary lakes, dam breaks, and Gaussian pulses, the scheme achieved errors below ${10}^{-12}$ for water height and velocity, while conserving mass with volume deviations under ${10}^{-5}$. Comparisons showed superior shock-capturing versus finite difference methods. For two-dimensional cases, it accurately resolved wave interactions over complex topographies. Though limited to wet beds and small-scale two-dimensional problems, the method provides a robust simulation tool. Full article

As global demand for rare earth elements (REEs) increases, maintaining the production and supply chain is critical. Technologies capable of being used in the field and in situ in the subsurface for rapid REE detection and quantification facilitates the efficient mining of known resources and exploration of new and unconventional resources. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for rapid elemental analysis both in the laboratory and in the field. Multiple articles have been published evaluating LIBS for detection and quantification of REEs; however, REEs in their natural deposits have not been adequately studied. In this work, detection and quantification of two REEs, La and Nd, have been studied in both synthetic and natural mineral matrices at concentrations relevant to REE extraction. Measurements were performed on REE-containing rock and coal samples (natural and synthetic) utilizing different LIBS instruments and techniques, specifically a commercial benchtop instrument, a custom benchtop instrument (single- and double-pulse modes), and a custom LIBS probe currently being developed for in situ, subsurface, borehole wall detection and quantification of REEs. Plasma expansion, emission intensity, detection limits, and double-pulse signal enhancement were studied. The limits of detection (LOD) were found to be 10/14 ppm for La and 15/25 ppm for Nd in simulated coal/rock matrices in single-pulse mode. Signal enhancement of 3.5 to 6-fold was obtained with double-pulse mode as compared to single-pulse operation. Full article

The aim of the present study is to investigate the influence of Nickel–Hexagonal Boron Nitride (Ni-hBN) nanocomposite coatings, deposited using the pulse reverse current electrodeposition technique. This experimental study focuses on assessing the tribological and corrosion properties of the produced coatings on the SS304 substrate. The microhardness of the as-deposited (AD) sample and heat-treated (HT) sample were 49% and 83.8% higher compared to the control sample. The HT sample exhibited a grain size which was approximately 9.7% larger than the AD sample owing to the expansion–contraction mechanism of grains during heat treatment and sudden quenching. Surface roughness reduced after coating, where the Ni-hBN-coated sample measured a roughness of 0.43 µm compared to 0.48 µm for the bare surface. The average coefficient of friction for the AD sample was 42.4% lower than the bare surface owing to the self-lubricating properties of nano hBN. In particular, the corrosion rate of the AD sample was found to be 0.062 mm/year, which was lower than values reported in other studies. As such, findings from the present study can be particularly beneficial for applications in the automotive and aerospace industries, where enhanced wear resistance, reduced friction, and superior corrosion protection are critical for components such as engine parts, gears, bearings and shafts. Full article

This paper consists of various kinds of wave solitons to the mathematical model known as the truncated M-fractional FitzHugh–Nagumo model. This model explains the transmission of the electromechanical pulses in nerves. Through the application of the modified extended tanh function technique and the modified $(G^{\prime }/G^2)$-expansion technique, we are able to achieve the series of exact solitons. The results differ from the current solutions because of the fractional derivative. These solutions could be helpful in the telecommunication and bioscience domains. Contour plots, in two and three dimensions, are used to describe the results. Stability analysis is used to check the stability of the obtained solutions. Moreover, the stationary solutions of the focusing equation are studied through modulation instability. Future research on the focused model in question will benefit from the findings. The techniques used are simple and effective. Full article

Repetitively pulsed (RP) laser propulsion is regarded as an alternative to chemical rockets for space launches, potentially offering remarkable cost reductions. Understanding the physics of laser-supported detonation (LSD) is important for designing a high-performance propulsion system. Experimentally observed LSD propagation velocities are reportedly lower than the Chapman–Jouguet (C-J) velocity; hence, a previous study that examined two-dimensional expansion behind the LSD to perform Hugoniot analysis using computational fluid dynamics (CFD) simulation resulted in strong detonation solution. In the present study, the effects of varying the relationship between heating and propagation velocity are investigated using CFD simulations. The findings indicate that a weak detonation solution was obtained with more realistic input of heating rate distribution and the pressure behind the LSD wave was lower than that in C-J detonation by a factor of three. The input LSD propagation velocity was changed by ±30% in the CFD simulation to examine the case of faster propagation in helium and slower propagation in argon and even so, a weak detonation mode was maintained. However, the input relaxation distance from the electron temperature to heavy particle temperature that is shorter in a light gas such as helium can produce a solution of C-J or strong detonation. Full article

The development of thermoelectric modules based on skutterudite materials requires stable, low-resistance interfaces between segments operating at different temperature ranges. This study investigates the microstructure, thermoelectric performance, and thermal stability of the following two joints: In_0.4Co₄Sb₁₂/Co₄Sb_10.8Te_0.6Se_0.6 (n-type) and CeFe₃Co_0.5Ni_0.5Sb₁₂/In_0.25Co₃FeSb₁₂ (p-type), fabricated by pulse plasma sintering (PPS). Scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) analyses confirmed the formation of well-bonded interfaces without pores or cracks. Aging at 773 K for 168 h did not result in morphological or chemical degradation, and phase composition remained unchanged according to X-ray diffraction (XRD). Surface Seebeck coefficient mapping and contact resistance measurements showed negligible changes after annealing, confirming electrical stability. To provide context for potential applications, theoretical energy conversion efficiencies were estimated based on measured thermoelectric properties, yielding 13.2% and 10.1% for the n- and p-type segmented legs, respectively. Additionally, measured coefficients of thermal expansion (CTE) indicated low mismatch between jointed materials, supporting good mechanical compatibility. The results demonstrate that the selected material combinations are thermally, chemically, and electrically stable and can be effectively used in segmented thermoelectric legs for intermediate-temperature applications. Full article

Background/Objectives: This research presents a novel analytical method for breast tumor characterization and tissue classification by leveraging intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) combined with hyperspectral imaging techniques and deep learning. Traditionally, dynamic contrast-enhanced MRI (DCE-MRI) is employed for breast tumor diagnosis, but it involves gadolinium-based contrast agents, which carry potential health risks. IVIM imaging extends conventional diffusion-weighted imaging (DWI) by explicitly separating the signal decay into components representing true molecular diffusion ($D$) and microcirculation of capillary blood (pseudo-diffusion or $D*$). This separation allows for a more comprehensive, non-invasive assessment of tissue characteristics without the need for contrast agents, thereby offering a safer alternative for breast cancer diagnosis. The primary purpose of this study was to evaluate different methods for breast tumor characterization using IVIM-DWI data treated as hyperspectral image stacks. Dice similarity coefficients and Jaccard indices were specifically used to evaluate the spatial segmentation accuracy of tumor boundaries, confirmed by experienced physicians on dynamic contrast-enhanced MRI (DCE-MRI), emphasizing detailed tumor characterization rather than binary diagnosis of cancer. Methods: The data source for this study consisted of breast MRI scans obtained from 22 patients diagnosed with mass-type breast cancer, resulting in 22 distinct mass tumor cases analyzed. MR images were acquired using a 3T MRI system (Discovery MR750 3.0 Tesla, GE Healthcare, Chicago, IL, USA) with axial IVIM sequences and a bipolar pulsed gradient spin echo sequence. Multiple b-values ranging from 0 to 2500 s/mm² were utilized, specifically thirteen original b-values (0, 15, 30, 45, 60, 100, 200, 400, 600, 1000, 1500, 2000, and 2500 s/mm²), with the last four b-value images replicated once for a total of 17 bands used in the analysis. The methodology involved several steps: acquisition of multi-b-value IVIM-DWI images, image pre-processing, including correction for motion and intensity inhomogeneity, treating the multi-b-value data as hyperspectral image stacks, applying hyperspectral techniques like band expansion, and evaluating three tumor detection methods: kernel-based constrained energy minimization (KCEM), iterative KCEM (I-KCEM), and deep neural networks (DNNs). The comparisons were assessed by evaluating the similarity of the detection results from each method to ground truth tumor areas, which were manually drawn on DCE-MRI images and confirmed by experienced physicians. Similarity was quantitatively measured using the Dice similarity coefficient and the Jaccard index. Additionally, the performance of the detectors was evaluated using 3D-ROC analysis and its derived criteria (AUC_OD, AUC_TD, AUC_BS, AUC_TD−BS, AUC_ODP, AUC_SNPR). Results: The findings objectively demonstrated that the DNN method achieved superior performance in breast tumor detection compared to KCEM and I-KCEM. Specifically, the DNN yielded a Dice similarity coefficient of 86.56% and a Jaccard index of 76.30%, whereas KCEM achieved 78.49% (Dice) and 64.60% (Jaccard), and I-KCEM achieved 78.55% (Dice) and 61.37% (Jaccard). Evaluation using 3D-ROC analysis also indicated that the DNN was the best detector based on metrics like target detection rate and overall effectiveness. The DNN model further exhibited the capability to identify tumor heterogeneity, differentiating high- and low-cellularity regions. Quantitative parameters, including apparent diffusion coefficient ($ADC$), pure diffusion coefficient ($D$), pseudo-diffusion coefficient ($D*$), and perfusion fraction ($PF$), were calculated and analyzed, providing insights into the diffusion characteristics of different breast tissues. Analysis of signal intensity decay curves generated from these parameters further illustrated distinct diffusion patterns and confirmed that high cellularity tumor regions showed greater water molecule confinement compared to low cellularity regions. Conclusions: This study highlights the potential of combining IVIM-DWI, hyperspectral imaging techniques, and deep learning as a robust, safe, and effective non-invasive diagnostic tool for breast cancer, offering a valuable alternative to contrast-enhanced methods by providing detailed information about tissue microstructure and heterogeneity without the need for contrast agents. Full article