Search Results (235)

In this article, we present LaserCAD, an open-source, script-based software toolkit for the design and visualization of optical setups based on parametric ray tracing. Unlike conventional commercial tools, which focus on complex lens optimization and offer dense GUIs with extensive parameters, LaserCAD is tailored for fast, intuitive modeling of laser beam paths and opto-mechanical assemblies with minimal setup overhead. Written in Python, it allows users to describe optical systems in a language close to geometrical optics, using simple commands with sensible defaults for most parameters. Optical elements can be automatically positioned including the required mounts. As a graphical backend, FreeCAD renders 3D models of all components for interactive visualization and post-processing. LaserCAD supports integration with other simulation tools and can automate the creation of alignment aids for 3D printing. This makes it especially suitable for rapid prototyping and lab-ready designs. Full article

This study presents a novel structural framing solution designed to improve seismic energy dissipation and limit displacements, aiming to serve as an effective alternative to traditional precast systems employing pendulum-based isolation. While pendulum mechanisms mitigate seismic forces by decoupling the superstructure from ground motion, they are typically characterized by high implementation costs, mechanical complexity, and post-event maintenance challenges. In contrast, the proposed approach integrates seismic performance enhancements within the structural frame itself, removing the dependency on external isolation components. The system leverages a combination of pinned and semi-rigid beam-to-column joints that are tailored for use within dry precast construction technologies. These connection types not only support rapid and labor-efficient assembly but also, when properly detailed, offer robust hysteretic behavior and deformation control under dynamic loading. The research includes both experimental testing and numerical simulations focused on the cyclic response of these connections, enabling a comprehensive understanding of their role in dissipating energy and delaying damage progression. Recognizing the industry’s frequent emphasis on construction speed and upfront cost-efficiency, often at the cost of long-term reparability, this work introduces an alternative framework that emphasizes resilience without compromising construction practicality. The resulting system demonstrates improved post-earthquake functionality and reduced downtime, making it a promising and economically viable option for seismic applications in precast construction. This advancement supports current trends toward performance-based design and enhances the structural reliability of dry-assembled systems in seismic regions. Full article

The material point method (MPM) has shown significant potential for simulating problems involving large deformations. However, many implicit MPM formulations based on the traditional Updated Lagrangian (UL) scheme still face challenges in terms of computational stability. In this study, we propose a novel Lagrangian equilibrium formulation for an implicit MPM that is tailored to large-deformation problems. (1) The previously converged state is utilized to simplify stiffness matrix computations, thereby improving the stability of the algorithm. (2) The framework supports a variety of high-order interpolation functions, which effectively mitigate numerical artifacts such as cell-crossing errors. (3) The B-bar technique is further incorporated to suppress spurious stress oscillations in the incompressible limit. The proposed method is validated through two classical benchmark tests, the simple shear of a single element and the cantilever beam problem, by comparing the simulation results with analytical solutions and alternative numerical approaches. Finally, its capability is demonstrated in slope stability and strip footing analyses, confirming the superior accuracy, stability, and robustness of the method for large-deformation elastoplastic problems. Full article

Key detection performance metrics, particularly resolution, are largely determined by the design parameters of ultrasonic arrays. The structural design of the transducer strongly influences critical indicators, including side lobe levels, beam directivity, and focal spot size. To improve parameter selection, this study proposes a multi-objective optimization strategy specifically tailored for cylindrical surface ultrasonic transducers. The geometric parameters of the array and the variables influencing resolution performance are mapped in a nonlinear manner. The NSGA-II algorithm is employed to perform extremum seeking optimization on a trained BPNN, generating a Pareto-optimal solution set by specifying main-lobe width, side-lobe intensity, and sound-pressure uniformity as optimization objectives. For validation, the geometric configurations derived from this solution set are applied in acoustic field simulations. Simulation results demonstrate that the dynamic aperture exhibits clear regularity when the array settings meet millimeter-level resolution requirements. These findings support real-world engineering applications and provide valuable insights for enhancing the geometric design of cylindrical ultrasonic arrays. Full article

Background/Objectives: Full-spine radiography is frequently performed from childhood to adulthood, raising concerns about radiation-induced breast cancer risk. To assess such probabilistic risks as cancer, accurate estimation of equivalent and effective organ doses is essential. The purpose of this study is to investigate X-ray imaging conditions for radiation reduction based on breast organ dose and to evaluate the accuracy of simulation software for dose calculation. Methods: Breast organ doses from full-spine radiography were calculated using the Monte Carlo-based dose calculation software PCXMC. Breast organ doses were estimated under various technical conditions of full-spine radiography (tube voltage, distance, grid presence, and beam projection). Dose reduction methods were explored, and variations in dose and error due to phantom characteristics and photon history number were evaluated. Results: Among the X-ray conditions, the greatest radiation reduction effect was achieved by changing the imaging direction. Changing from the anteroposterior to posteroanterior direction reduced doses by approximately 76.7% to 89.1% (127.8–326.7 μGy) in children and 80.4% to 91.1% (411.3–911.1 μGy) in adults. In addition, the study highlighted how phantom characteristics and the number of photon histories influence estimated doses and calculation error, with approximately 2 × 10⁶ photon histories recommended to achieve a standard error ≤ 2%. Conclusions: Modifying radiographic conditions is effective for reducing breast radiation exposure in patients with scoliosis. Furthermore, to ensure the accuracy of dose calculation software, the number of photon histories must be adjusted under certain conditions and used while verifying the standard error. This study demonstrates how technical modifications, projection selection, and phantom characteristics influence breast radiation exposure, thereby supporting the need for patient-tailored imaging strategies that minimize radiation risk while maintaining diagnostic validity. The findings may be useful in informing radiographic protocols and the development of safer imaging guidelines for both pediatric and adult patients undergoing spinal examinations. Full article

Measurement technology employing optical interference phenomena such as a fringe pattern or frequency shift has been evolving for more than a century. Systems are being designed better, and their components are being built better. However, the major components themselves hardly change. Most modern interferometers rely on the same conventional set of components to separate the electromagnetic field into multiple beams, such as plate optics and beam splitters. This naturally limits the design scope and thus the potential applicability and performance. However, recent investigations suggest that incorporating novel, higher-dimensional linear optical splitters in interferometer design can lead to several improvements. In this work, we review the underlying theory of these novel optical scatterers and some demonstrated configurations with enhanced resolution. The basic principles of optical interference and optical phase sensing are discussed in tandem. Emphasis is placed on both familiar and unfamiliar scatterers, such as the maximally symmetric Grover multiport, whose actions are left unchanged by certain gauge transformations. These higher-dimensional, gauge-invariant multiports embody a new class of building blocks that can tailor optical interference to metrology in unconventional ways. Full article

The present paper reports the comparison of the ship motions and added resistance assessment using high fidelity RANSE simulations in virtual towing tank LincoSim, using 2D strip theory as implemented in ShipX v4.4.0 and 3D BEM potential flow software Hydrostar v8.2.1. All calculations are performed for a medium-sized RoPax ferry of Levante Ferries fleet, which operates daily routes in the Ionian Sea. Calculations by ShipX are performed in frequency domain (using strip-theory and direct pressure integration) and in time domain. The high-fidelity RANSE seakeeping modeling is based on the open-source CFD code OpenFOAM v12 using a standardized framework, tailored to take advantage of HPC facilities and based on a forcing zone formulation. The CFD simulations are performed for six wave periods in head and beam seas at the constant wave height of 3 m. Comparison of the obtained results shows that potential-flow methods are very efficient and reliable tools, suitable for the massive calculations in the first stages of the project. High-fidelity RANSE modeling seems to be more suited for selected cases such as analysis of roll and added resistance in beam waves. Full article

Precast concrete frames integrating ultra-high-performance concrete (UHPC) beams and high-strength concrete (HSC) columns offer exceptional seismic resilience and construction efficiency. However, a performance-based seismic design methodology tailored for this hybrid structural system remains underdeveloped. This study aims to develop and validate a direct displacement-based design (DDBD) procedure specifically for precast UHPC-HSC frames. A novel six-tier performance classification scheme (from no damage to severe damage) was established, with quantitative limit values of interstory drift ratio proposed based on experimental data and code calibration. The DDBD methodology incorporates determining the target displacement profile, converting the multi-degree-of-freedom system to an equivalent single-degree-of-freedom system, and utilizing a displacement response spectrum. A ten-story case study frame was designed using this procedure and rigorously evaluated through pushover analysis. The results demonstrate that the designed frame consistently met the predefined performance objectives under various seismic intensity levels, confirming the effectiveness and reliability of the proposed DDBD method. This work contributes a performance oriented seismic design framework that enhances the applicability and reliability of UHPC-HSC structures in earthquake regions, offering both theoretical insight and procedural guidance for engineering practice. Full article

Gellan gum (Gellan), a versatile polysaccharide applied in gel formation and prebiotic formulations, is often processed to tailor its molecular properties. Previous studies employed gamma irradiation and chemical hydrolysis, though without addressing systematic scaling behavior. This study investigates the structural and conformational modifications of Gellan in dilute aqueous salt solutions using a safer and eco-friendly approach: atmospheric low-dose electron beam (e-beam) degradation coupled with viscosity analysis. Native and E-beam-treated Gellan samples (0.05 g/cm³ in 0.1 M KCl) were examined by relative viscosity at varying temperatures, with intrinsic viscosity and molar mass determined via Solomon–Ciuta and Mark–Houwink relations. Molar mass degradation followed first-order kinetics, yielding rate constants and degradation lifetimes. Structural parameters, including radius of gyration and second virial coefficient, produced scaling coefficients of 0.62 and 0.15, consistent with perturbed coil conformations in a good solvent. The shape factor confirmed preservation of an ideal random coil structure despite irradiation. Conformational flexibility was further analyzed using theoretical models. Transition state theory (TST) revealed that e-beam radiation lowered molar mass and activation energy but raised activation entropy, implying reduced flexibility alongside enhanced solvent interactions. The freely rotating chain (FRC) model estimated end-to-end distance (R_θ) and characteristic ratio (C_∞), while the worm-like chain (WLC) model quantified persistence length (l_p). Results indicated decreased R_θ, increased l_p, and largely unchanged C_∞, suggesting diminished chain flexibility without significant deviation from ideal coil behavior. Overall, this work provides new insights into Gellan’s scaling laws and flexibility under aerobic low-dose E-beam irradiation, with relevance for bioactive polysaccharide applications. Full article

This paper presents the design and experimental evaluation of a compact microstrip patch antenna and a 4 × 4 phased antenna array system tailored for Wi-Fi 6E applications, U-NII-5 band. A single inset-fed microstrip patch antenna was first optimized through full-wave simulations, achieving a resonant frequency of 5.96 GHz with a measured return loss of −17.5 dB and stable broadside radiation. Building on this element, a corporate-fed 4 × 4 array was implemented on an FR4 substrate, incorporating stepped-impedance transmission lines and λ/4 transformers to ensure equal power division and impedance matching across all ports. A 4-bit digital phase shifter, controlled by an ATmega328p microcontroller, was integrated to enable electronic beam steering. Simulated results demonstrated accurate beam control within ±28°, with directional gains above 13 dBi and minimal degradation compared to the broadside case. Over-the-air measurements validated these findings, showing main lobe steering at 0°, ±15°, +33° and −30° with peak gains between 7.8 and 11.5 dBi. The proposed design demonstrates a cost-effective and practical solution for Wi-Fi 6E phased array antennas, offering enhanced beamforming, improved spatial coverage, and reliable performance in next-generation wireless networks. Full article

In this work, we propose a knowledge-aware approach for Arabic automatic question generation (QG) that leverages the multilingual T5 (mT5) transformer augmented with a pre-trained Arabic question-answering model to address challenges posed by Arabic’s morphological richness and limited QG resources. Our system generates both subjective questions and multiple-choice questions (MCQs) with contextually relevant distractors through a dual-model pipeline that tailors the decoding strategy to each subtask: the question generator employs beam search to maximize semantic fidelity and lexical precision, while the distractor generator uses top-k sampling to enhance diversity and contextual plausibility. The QG model is fine-tuned on Arabic SQuAD, and the distractor model is trained on a curated combination of ARCD and Qudrat. Experimental results show that beam search significantly outperforms top-k sampling for fact-based question generation, achieving a BLEU-4 score of 27.49 and a METEOR score of 25.18, surpassing fine-tuned AraT5 and translated English–Arabic baselines. In contrast, top-k sampling is more effective for distractor generation, yielding higher BLEU scores and producing distractors that are more diverse yet remain pedagogically valid, with a BLEU-1 score of 20.28 establishing a strong baseline in the absence of prior Arabic benchmarks. Human evaluation further confirms the quality of the generated questions. This work advances Arabic QG by providing a scalable, knowledge-aware solution with applications in educational technology, while demonstrating the critical role of task-specific decoding strategies and setting a foundation for future research in automated assessment. Full article

Spot melting is an emerging alternative to traditional line melting in electron beam powder bed fusion, dividing a layer into thousands of individual spots. This method allows for an almost infinite number of spot arrangements and spot melting sequences to tailor material and part properties. To enhance the productivity of spot melting, the number of spots can be reduced by increasing the beam diameter. However, this results in rough surfaces due to the staircase effect. The classical approach to counteract these effects is to melt a contour that surrounds the infill area. Creating effective contours is challenging because the melted area ought to cover the artifacts from the staircase effect and avoid porosity in the transition area between the infill and contour, all while minimizing additional energy and melt time. In this work, we propose an algorithm for generating a spot melting sequence for contour lines surrounding the infill area. Additionally, we compare three different approaches for combining the spot melting of infill and contour areas, each utilizing a combination of large infill spots and small contour spots. The quality of the contours is evaluated based on optical inspection as well as the porosity between infill and contour using electron optical images, balanced against the additional energy input. The most suitable approach is used to build a complex brake caliper. Full article

High-entropy alloys (HEAs) have shown great promise for applications in extreme service environments due to their exceptional mechanical properties and thermal stability. However, traditional alloy design often struggles to balance multiple properties such as strength and ductility. Constructing heterogeneous microstructures has emerged as an effective strategy to overcome this challenge. With the rapid advancement of additive manufacturing (AM) technologies, their unique ability to fabricate complex, spatially controlled, and non-equilibrium microstructures offers unprecedented opportunities for tailoring heterostructures in HEAs with high precision. This review highlights recent progress in utilizing AM to engineer heterogeneous microstructures in high-performance HEAs. It systematically examines the multiscale heterogeneities induced by the thermal cycling effects inherent to AM techniques such as selective laser melting (SLM) and electron beam melting (EBM). The review further discusses the critical role of these heterostructures in enhancing the synergy between strength and ductility, as well as improving work-hardening behavior. AM enables the design-driven fabrication of tailored microstructures, signaling a shift from traditional “performance-driven” alloy design paradigms toward a new model centered on “microstructural control”. In summary, additive manufacturing provides an ideal platform for constructing heterogeneous HEAs and holds significant promise for advancing high-performance alloy systems. Its integration into alloy design represents both a valuable theoretical framework and a practical pathway for developing next-generation structural materials with multiple performance attributes. Full article

The geometry and quality of a weld seam are critical factors in laser beam welding, influencing mechanical performance and structural integrity. Dynamically modulated laser beams provide a precise means of tailoring energy input in high-power laser welding processes. This study investigates the influence of beam shape and modulated frequency on weld seam geometry, penetration depth, and capillary behaviour using a coherent beam combining (CBC) laser system from Civan Lasers. Three beam intensity distributions—single point, line–point–line (LPL), and boomerang—were applied across a modulation frequency range of 1, 10, and 100 kHz during the welding of duplex and austenitic stainless steels. High-speed imaging captured real-time capillary dynamics, and the data were analysed to assess capillary stability, measure capillary diameter, and determine the capillary front angle as a function of frequency and beam shape. Transverse cross-sections of the welds were prepared to evaluate seam geometry and microstructure. The results show that beam shape significantly affects energy distribution and weld profile, while modulation frequency critically influences capillary behaviour and penetration characteristics. These findings highlight the critical role of dynamic beam shaping and frequency modulation in optimizing laser welding processes for material-specific performance, offering a versatile platform for advancing precision manufacturing using CBC technology. Full article

In the rapidly evolving landscape of digital marketing and electronic commerce, short-form content—particularly on platforms like Twitter (now X)—has become pivotal for real-time branding, community engagement, and product promotion. The rise of Non-Fungible Tokens (NFTs) and Web3 ecosystems further underscores the need for domain-specific, engagement-oriented social media content. However, automating the generation of such content while balancing linguistic quality, semantic relevance, and audience engagement remains a substantial challenge. To address this, we propose RL-TweetGen, a socio-technical framework that integrates instruction-tuned large language models (LLMs) with reinforcement learning (RL) to generate concise, impactful, and engagement-optimized tweets. The framework incorporates a structured pipeline comprising domain-specific data curation, semantic classification, and intent-aware prompt engineering, and leverages Parameter-Efficient Fine-Tuning (PEFT) with LoRA for scalable model adaptation. We fine-tuned and evaluated three LLMs—LLaMA-3.1-8B, Mistral-7B Instruct, and DeepSeek 7B Chat—guided by a hybrid reward function that blends XGBoost-predicted engagement scores with expert-in-the-loop feedback. To enhance lexical diversity and contextual alignment, we implemented advanced decoding strategies, including Tailored Beam Search, Enhanced Top-p Sampling, and Contextual Temperature Scaling. A case study focused on NFT-related tweet generation demonstrated the practical effectiveness of RL-TweetGen. Experimental results showed that Mistral-7B achieved the highest lexical fluency (BLEU: 0.2285), LLaMA-3.1 exhibited superior semantic precision (BERT-F1: 0.8155), while DeepSeek 7B provided balanced performance. Overall, RL-TweetGen presents a scalable and adaptive solution for marketers, content strategists, and Web3 platforms seeking to automate and optimize social media engagement. The framework advances the role of generative AI in digital commerce by aligning content generation with platform dynamics, user preferences, and marketing goals. Full article