Remarkable Alignment Research Articles

Investigation of the influence of initial residual stress and toolpaths on milling deformation of titanium alloy

Titanium alloy structural components are widely used in the aerospace industry due to their excellent physical properties. However, their susceptibility to machining deformation during milling, attributed to the presence of initial residual stress, poses a significant challenge. Therefore, this paper proposes a finite element model for predicting milling deformation in Ti6Al4V titanium alloy structural parts, considering initial residual stress. The methodology involves establishing the initial residual stress field of titanium alloy components based on a mathematical model of annealing heat transfer and a theoretical study of thermal elasto-plastic constitutive relation, with experimental confirmation of model accuracy. Based on the initial residual stress, a finite element model was developed to predict the maximum deformation under different toolpaths. Finally, a comparative analysis with milling experiments validated the proposed models. The experimental results demonstrated a remarkable alignment with the finite element model, showcasing the correctness of the developed models. The maximum deviation in deformation observed was within the range of 0.003 mm–0.011 mm. This study is the first to comprehensively consider the effects of initial residual stress and toolpaths on titanium alloy milling deformation, and to experimentally verify the proposed model’s accuracy and practicality. It provides a new theoretical basis and technical guidelines for titanium alloy milling deformation.

Exploring transitions in finite-size Potts model: comparative analysis using Wang–Landau sampling and parallel tempering

Abstract This research provides a examination of transitions within the various-state Potts model in two-dimensional finite-size lattices. Leveraging the Wang–Landau sampling and parallel tempering, we systematically obtain the density of states, facilitating a comprehensive comparative analysis of the results. The determination of the third-order transitions location are achieved through a meticulous examination of the density of states using microcanonical inflection-point analysis. The remarkable alignment between canonical and microcanonical results for higher-order transition locations affirms the universality of these transitions. Our results further illustrate the universality of the robust and microcanonical inflection-point analysis of Wang–Landau sampling.

Numeričko modeliranje reprofiliranja sljubnica ziđa: analiza konačnih elemenata temeljena na eksperimentalnim istraživanjima

This study investigated the efficacy of joint repointing as a strengthening technique for unreinforced masonry (URM) structures via experimental data combined with advanced numerical modelling. The numerical simulations demonstrated remarkable alignment with the experimental data, validating the efficacy of the proposed modelling approach. The finite element analysis results were consistent with the experimentally observed stress–strain relationships, failure modes, and ultimate capacities of the masonry panels. The calibrated model successfully replicated the enhanced performance of the strengthened specimens, particularly in terms of increased compressive and shear strengths. Although parametric studies were not performed directly in this study, the validated numerical model provides a solid foundation for future investigations. The accurate reproduction of experimental results through finite element modelling facilitates the potential for extensive parametric analyses, which could explore various strengthening configurations and material properties without the need for costly and time-consuming physical experiments—particularly valuable for assessing and optimising retrofitting strategies for existing URM buildings, particularly in seismic-prone regions. This research contributes significantly to the field of structural engineering by demonstrating the potential of simplified micromodelling techniques to capture the intricacies of masonry behaviour at the meso-level.

Influence of carbon dots integrated in Pr3+ doped gahnite nanophosphor for thermal sensing, data fortification and fingerprint visualization analysis through YOLOv8x deep learning embedded model

The remarkable optical properties of carbon dots (CDs) render them highly promising as a versatile group of carbon-based nanomaterials. Integrating hydrothermally synthesized CDs into zinc aluminate doped with Pr3+ ions (ZnAl2O4:Pr3+) nanophosphors (ZAO:Pr3+ NPs) fabricated via the solution combustion (SC) technique holds great potential. The aim of synthesizing these nanocrystals (NCs) is to explore their potential uses in optical thermometry and anti-counterfeiting (AC) measures. The synthesized nanoparticles (NPs) and nanocomposites (NCs) underwent characterization using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and photoluminescence (PL) spectra to verify their phase, morphology, particle size, oxidation state, and chemical composition. When excited at 447 nm, the Pr3+ doped ZAO: NPs exhibited an orange-red emission band at 614 nm. A remarkable enhancement in PL intensity, by a factor of 39.02 folds, is noted upon embedding CDs into the ZAO:Pr3+ NPs (CDs@ ZAO:Pr3+). The enhanced PL intensity can be ascribed to the Förster resonance energy transfer (FRET) mechanism. Even at a temperature of 423 K, the NPs retains 95.4% of its emission intensity compared to that at room temperature, showcasing exceptional thermal stability. The 5 wt% CDs@ZAO:1Pr3+ NCs demonstrate a high colour purity (CP) of 98.3%. Moreover, these NCs hold promise for optical thermometry applications across a broad temperature range spanning from 303 to 463 K. Utilizing the exceptional ZAO:1Pr3+ NPs and 5 wt% CDs@ZAO:1Pr3+ NCs, two representative white light emitting diodes (w-LEDs) have been successfully developed, boasting satisfactory luminous efficacy and colour-rendering index (CRI). This underscores their potential for high-performance w-LED applications. Simultaneously, a highly sensitive, non-contact optical thermometer has been engineered, featuring maximum relative sensitivities of approximately 44.51×10−4K−1 and 75.48×10−4K−1 at the emission intensities corresponding to 673, 693, 712 and 735 nm, respectively. We have developed a simple brush mode technique for creating a variety of patterns using the manufactured AC security ink. The latent fingerprints (LFPs) visualized using 5 wt% CDs@ZAO:1Pr3+ NCs exhibit excellent resolution and contrast, enabling the easy identification of fingerprint characteristics from levels I-III. Employing deep learning utilizing the YOLOv8x algorithm, fluorescence images of the revealed LFPs demonstrate remarkable alignment with standard controls, suggesting a high degree of similarity. In addition, the fabricated white light emitting diode (w-LED) boasts a favorable colour rendering index (Ra=87) alongside Commission International de L′Eclairage (CIE) coordinates (0.617, 0.376). Consequently, the inclusion of 5wt% CDs@ZAO:1Pr3+NPs showcases remarkable luminescent attributes and holds promising prospects across various applications.

Diffusion-Equation-Based Electrical Modeling for High-Power Lithium Titanium Oxide Batteries

Lithium titanium oxide (LTO) batteries offer superior performance compared to graphite-based anodes in terms of rapid charge/discharge capability and chemical stability, making them promising candidates for fast-charging and power-assist vehicle applications. However, commonly used battery models often struggle to accurately describe the current–voltage characteristics of LTO batteries, particularly before the charge/discharge cutoff conditions. In this work, a novel electrical model based on the solid-phase diffusion equation is proposed to capture the unique electrochemical phenomena arising from the diffusion mismatch between the positive and negative electrodes in high-power LTO batteries. The robustness of the proposed model is evaluated under various loading conditions, including constant current and dynamic current tests, and the results are compared against experimental data. The experimental results for LTO batteries exhibit remarkable alignment with the model estimation, demonstrating a maximum voltage error below 3%.

Patriotism in the Political Discourse of the Union State of Belarus and Russia

The article delves into the nuanced challenge of crafting a cohesive unionwide patriotic agenda amidst escalating global tensions fueled, in part, by value conflicts. It scrutinizes the emergence of a patriotic discourse intricately woven into the institutional fabric of the Union State, the Russian Federation, and the Republic of Belarus, primarily steered by top political leadership at the domestic level. The overarching aim is to delineate the enduring themes and prevailing narratives within the political elites' patriotic discourse within the Union State, while exploring its potential conceptualization as a coordinating discourse to further integration objectives and as a countermeasure of "anti-soft power" against external value threats emanating from the collective West. Methodologically, the study draws upon discursive neo-institutionalism, employing qualitative content analysis of speeches delivered by the respective presidents of the two countries as its primary analytical approach.In the conclusions, the paper underscores the remarkable alignment between Russian and Belarusian stances on patriotic issues, particularly concerning their ideological underpinnings. Both underscore the imperative of safeguarding and preserving historical memory and traditional values as the cornerstone of their discourse. However, the analysis also sheds light on the conceptual complexities inherent in articulating sovereignty values by both participating countries. The practical implications underscore the necessity of further solidifying a shared socio-cultural space, harmonizing historical policies within both nations and within the Union State framework, and stimulating a "demand for integration" through the practical implementation of the principal directives outlined in the 2021 package of integration decisions.

A computational Finite Element Study for Optimizing the Biomedical Strength of MWCNT Reinforced Polymer Nanocomposites

Multi-walled carbon nanotubes (MWCNTs) are highly regarded for reinforcing polymeric nano biocomposites, like polymethylmethacrylate (PMMA), owing to their versatility across various biological applications such as such as dental crowns, artificial teeth and dentures. In this study micromechanical models were meticulously developed to evaluate PMMA matrices fortified with MWCNTs at varying weight percentages (0.1%, 0.5%, and 1.0%). The assessment was conducted using Finite Element Analysis (FEA) facilitated by ANSYS 2022 (Ansys, Inc., USA). Notably, the investigation focused on validating the tensile strength against experimental data, revealing the peak tensile strength at 0.5 wt% MWCNT. Moreover, models featuring isotropic filler orientations demonstrated remarkable alignment with experimental outcomes. Furthermore, the study delved into exploring the influence of diverse MWCNT filler diameters (ranging from 10 to 35 nm) on the tensile strength, indicating a direct correlation with increasing diameter. However, it was observed that the larger diameters tended to correlate with decreased compressive and flexural strength. These comprehensive findings underscore the promising potential of MWCNT reinforced PMMA nanocomposites in advancing biomedical research, where enhanced mechanical properties play a pivotal role.

Exceptional Alignment in a Donor–Acceptor Conjugated Polymer via a Previously Unobserved Liquid Crystal Mesophase

AbstractOrienting polymer semiconductors is desirable to optimize device characteristics, provide insight into microstructure, and magnify subtle phase behavior. Here, a combination of uniaxial strain and subsequent heating of the donor–acceptor (DA) polymer PBnDT‐FTAZ is discovered to lead to exceptional optical dichroic ratios of up to 38 (and close to 50 near the polymer's absorption edge). This alignment is achieved due to the existence of a previously undetected thermotropic liquid crystal (LC) mesophase. The LC transition, not discernable through calorimetry, is uncovered through a combination of in situ UV–vis spectroscopy, X‐ray scattering, and dynamic mechanical analysis (DMA). Comparing PBnDT‐FTAZ to the non‐fluorinated PBnDT‐HTAZ and the homo polymer PBnDT, all of which show similar thermal transitions, reveals that exceptional alignment is only found in PBnDT‐FTAZ. This is attributed to the PBnDT‐FTAZ film having two distinct liquid crystal populations, and the polymer templating to a highly aligned, high‐clearing temperature population when heated. The DMA thermal relaxation behavior observed here is also seen in other DA conjugated polymers suggesting that such thermotropic LC mesophases may be common in these materials. These findings demonstrate a polymer semiconductor with remarkable alignment and uncover phase behavior with broad implications for process‐structure‐property relationships in polymer semiconductors.

Data-driven RANS closures for improving mean field calculation of separated flows

Reynolds-averaged Navier-Stokes (RANS) simulations have found widespread use in engineering applications, yet their accuracy is compromised, especially in complex flows, due to imprecise closure term estimations. Machine learning advancements have opened new avenues for turbulence modeling by extracting features from high-fidelity data to correct RANS closure terms. This method entails establishing a mapping relationship between the mean flow field and the closure term through a designated algorithm. In this study, the k-ω SST model serves as the correction template. Leveraging a neural network algorithm, we enhance the predictive precision in separated flows by forecasting the desired learning target. We formulate linear terms by approximating the high-fidelity closure (from Direct Numerical Simulation) based on the Boussinesq assumption, while residual errors (referred to as nonlinear terms) are introduced into the momentum equation via an appropriate scaling factor. Utilizing data from periodic hills flows encompassing diverse geometries, we train two neural networks, each possessing comparable structures, to predict the linear and nonlinear terms. These networks incorporate features from the minimal integrity basis and mean flow. Through generalization performance tests, the proposed data-driven model demonstrates effective closure term predictions, mitigating significant overfitting concerns. Furthermore, the propagation of the predicted closure term to the mean velocity field exhibits remarkable alignment with the high-fidelity data, thus affirming the validity of the current framework. In contrast to prior studies, we notably trim down the total count of input features to 12, thereby simplifying the task for neural networks and broadening its applications to more intricate scenarios involving separated flows.

Wideband Millimeter-Wave Perforated Cylindrical Dielectric Resonator Antenna Configuration

This article delves into the capabilities of 3D-printed millimeter-wave (mmWave) layered cylindrical dielectric resonator antennas (CDRAs). The proposed design yielded promising results, boasting a remarkable 53% impedance bandwidth spanning the frequency spectrum from 18 to 34 GHz. Furthermore, the axial ratio (AR) bandwidth achieved an impressive 17%, coupled with a maximum gain of 13.3 dBic. These notable results underscore the efficacy of the proposed design, positioning it as a viable solution for applications in Beyond 5G (B5G). A novel assembly technique was also investigated, employing additive manufacturing to seamlessly merge two layers with distinct dielectric constants into a singular layer. This innovative approach systematically eliminates the potential for air gaps between layers, enhancing the antenna’s overall performance. This approach exhibited potential, particularly in the performance of a millimeter-wave circularly polarized (CP) cylindrical DRA featuring a perforated coating layer. The synergy between measurements and simulations demonstrates a remarkable alignment, providing robust validation of the effectiveness of the proposed design.

Experimental and numerical investigation of porous bleed control for supersonic/subsonic flows, and shock-wave/boundary-layer interactions

This paper presents a comprehensive experimental and numerical investigation into the control of boundary layers using porous bleed systems. The study focuses on both supersonic and subsonic flow regimes, as well as on the control of shock-wave/boundary-layer interactions. By simplifying this complex problem into two separate scenarios, the research establishes the necessity of individually characterizing bleed systems for both supersonic and subsonic flow regimes due to variations in the flow topology within the bleed holes. In supersonic conditions, a strong agreement between experimental and numerical results validates the effectiveness of porous bleed in controlling boundary layers. Notably, three-dimensional effects are experimentally demonstrated, and variations of the boundary-layer profiles along the span are the first time experimentally proven. The study extends its scope to subsonic flows, revealing that while boundary-layer bleeding enhances flow momentum near the wall, mass removal induces a decrease in momentum in the outer boundary layer and external flow. The research also explores shock-wave/boundary-layer interaction control, achieving a remarkable alignment between simulations and experiments. The findings endorse the use of Reynolds-Averaged Navier-Stokes simulations for studying porous bleed systems in various flow conditions, providing valuable insights to enhance bleed models, especially in the context of shock-wave/boundary-layer interaction control.

Enhanced earth pressure determination with negative wall-soil friction using soft computing

Estimating active earth pressure in cohesionless backfill behind rigid retaining walls has been significantly improved through the application of cutting-edge soft computing techniques in this paper. This study delves into the intricate interplay of negative wall-soil friction with load transfer mechanisms, underpinned by a comprehensive dataset obtained from a conservative solution that leverages statically admissible stress fields. Utilizing a Bayesian regularization backpropagation neural network, we construct an explicit function for active earth pressure estimation, ensuring the model's reliability through its remarkable alignment with measured values. Furthermore, feature importance analysis and advanced mathematical modeling enrich the study, providing a practical tool for retaining wall design and analysis. This tool is adept at addressing complex scenarios, including those involving negative wall-soil friction, thereby advancing the state-of-the-art in geotechnical engineering.

Dynamics of anisotropic colloidal systems: What to choose, DLS, DDM or XPCS?

Investigation of the dynamics of colloids in bulk can be hindered by issues such as multiple scattering and sample opacity. These challenges are exacerbated when dealing with inorganic materials. In this study, we employed a model system of Akaganeite colloidal rods to assess three leading dynamics measurement techniques: 3D-(depolarized) dynamic light scattering (3D-(D)DLS), polarized-differential dynamic microscopy (P-DDM), and x-ray photon correlation spectroscopy (XPCS). Our analysis revealed that the translational and rotational diffusion coefficients captured by these methods show a remarkable alignment. Additionally, by examining the q-ranges and maximum volume fractions for each approach, we offer insights into the best technique for investigating the dynamics of anisotropic systems at the colloidal scale.

Incorporating Copper and Carbon Nanotube Nanoparticles into Phase Change Materials for Enhanced Thermal Management in Batteries

The primary objective of this study was to explore the impact of integrating nano-additives on heat transfer enhancement within an LHTES (Latent Heat Thermal Energy Storage) system. Our findings revealed that introducing a minimal amount of nano-materials (less than 5.0 vol%) into the Phase Change Material (PCM) led to a remarkable alignment between experimental correlations and mixture models. Furthermore, employing the mixing model allowed for the accurate prediction of outcomes. In the current context of scientific research, there is a strong endorsement for the widespread adoption of Electric Vehicles (EVs) as a sustainable alternative to Internal Combustion Engines (ICEs), crucial for advancing decarbonization and mitigating climate-related crises. Lithium-ion batteries are the predominant choice for EVs and various electrical devices. However, the operational challenges posed by high temperatures, impacting their lifespan, charge/discharge cycles, and the risk of thermal runaway, necessitate effective thermal management systems. Given this background, our study focuses on simulating the heat dissipation of a single cylindrical Li-ion battery cell employing a Nano-enhanced Phase Change Material (NePCM)-based cooling system. We also introduce a novel fin design in this work. Through comprehensive analysis, we examine the performance of battery modules utilizing PCM and NePCM at different discharge rates, both with and without the newly proposed fin design. Our research demonstrates that the incorporation of fins and nanoparticles into PCM significantly enhances heat transfer and reduces the charging time compared to the base PCM. Notably, carbon-based nanoparticles outshine their metal-based counterparts in terms of melting rate and maintaining a uniform temperature profile within the battery.

The Role of Evaluation Theory and Practice in Narrowing the Research-to-Practice Gap

The research-to-practice gap describes the well-documented phenomena of researchers and practitioners working in silos, embedded in vastly different contexts. This “cultural divide” has several causes, including ineffective collaboration, inadequate understanding of context, and insufficient dissemination and translation of research. Evaluation theory and practice have been largely absent from discussions about solving the research-to-practice gap, despite remarkable alignment between these efforts and the core principles and goals of evaluation. In this article, we describe why the research-to-practice gap exists, current models and frameworks to address the gap, and how evaluation aligns with, and extends, efforts to create a bi-directional bridge between research and practice. This article is a call-to-action for professional evaluators who are poised to narrow this gap given that they work at the intersection of research and practice. Through authentic collaboration, researchers, practitioners, and evaluators can leverage our collective strength to address the pressing challenges faced by our communities.

Advancing circular economy in industrial chemistry and environmental engineering: Principles, alignment with United Nations sustainable development goals, and pathways to implementation

This groundbreaking review explores the crucial role of the circular economy in industrial chemistry and environmental engineering. It surpasses a mere examination of principles and methods, delving into the profound significance and urgency of this transformative shift. By analyzing key elements such as resource efficiency, waste valorization, sustainable product design, industrial symbiosis, and policy integration, the study highlights the power of collaboration, technological advancements, and extensive literature research. It reveals the remarkable alignment between the circular economy and the Sustainable Development Goals (SDGs), emphasizing how circular practices promote resource efficiency, waste reduction, and sustainable production and consumption patterns, thus driving progress across multiple SDGs. With a specific focus on responsible consumption and production, clean energy, innovative industrial practices, climate action, ecosystem protection, water resource management, job creation, economic growth, sustainable urbanization, and collaboration, the review provides a comprehensive roadmap for adopting circularity. Its practical recommendations cover sustainable material selection, resource efficiency, closing loop, digitalization, and robust policy support. In addition, it emphasizes the paramount importance of collaboration, stakeholder engagement, education, capacity building, circular supply chain management, and effective policy frameworks in spearheading circular economy initiatives. Drawing inspiration from diverse circular economy models and compelling case studies in industrial chemistry, the study highlights the integration of environmental, social, and governance (ESG) factors, ensuring both sustainability and positive societal impact. This comprehensive review serves as a guiding light, demonstrating the immense potential of the circular economy in driving sustainable development. It offers actionable guidance for implementing circular practices, empowering professionals to make tangible contributions to a more sustainable future. Additionally, it serves as a foundational piece, fueling the advancement of knowledge, inspiring further research, and propelling remarkable progress in the ever-evolving fields of industrial chemistry and environmental engineering.

Effect of an inclined magnetic field on unsteady mixed convective stagnation point flow over a permeable stretching sheet with radiative heat transfer

In this study, we analyzed the time-dependent, 2D, inclined magnetohydrodynamics mixed convection stagnating point flow of nanoparticle toward a permeable stretchable surface with radiative heat effect. Four different types of water-based nanomaterials, namely titanium dioxide copper aluminum oxide and copper oxide are analyzed in this investigation. Numerous engineering disciplines, including energy systems, material processing, thermal management, and environmental engineering, can benefit greatly from research in mixed convection, MHD, and nanofluids. The boundary layer representations of the dominating partial differential equations PDEs are converted into strong nonlinear ordinary differential equations ODEs utilizing similarities approach. The ODEs are computed numerically employing 4th order Runge–Kutta methodology-based shooting scheme. Few special situations, a remarkable alignment is determined between the present study and the outcomes obtained in the existing research. The impact of numerous pertinent variables on the prominent quantities such as velocity, temperature and concentration distributions, drag friction coefficient and heat transport are demonstrated graphically. It is noticed that the velocity and thermal curve decrease as the nanoparticle volume friction factor increases. Moreover, it is analyzed that higher values of nanoparticle concentration diminishes the velocity and temperature distributions.

Study on Sublimation Drying of Carrot and Simulation by Using Cellular Automata

Vacuum freeze-dried products exhibit properties characteristic of porous media, rendering them superior in both drying and rehydration capabilities. However, the process of sublimation drying is constrained by its substantial time and energy costs. To comprehensively grasp its technological process and identify the optimal process parameters, the cellular automata method was employed for sublimation process simulation. Carrot slices, measuring 10 mm in thickness and 40 mm in radius, were selected for both simulation and experimentation. The sublimation process was characterized using a two-dimensional heat and mass transfer equation, inclusive of a dusty gas model. Additionally, a cellular automaton model was applied to simulate the mass transfer process, temperature, and moisture content changes in the sublimation drying stage. Then, the accuracy of the model was verified through experimentation. There was a remarkable alignment between simulation and experimental outcomes, with determination coefficients R2 of 99.4% for moisture content and 97.6% for temperature variations.

Dynamic modeling and ride comfort evaluation of railway vehicle under random track irregularities: A case study of a Linke-Hofmann-Busch coach

The ride comfort of passengers is an important parameter for evaluating the performance of railway vehicles. Many standards/ models, such as quarter car, half car, and full car, have been proposed to evaluate the human comfort of railway vehicles. However, a full-scale coupled railway vehicle model is rarely considered for calculating ride comfort. Therefore, this paper proposes a twenty-seven-degree-of-freedom (27-DOF) coupled dynamic model of railway vehicles integrated with wheel-rail contact forces. The developed model is solved using the two-dimensional (2-D) state space method, and the effects of different track irregularities on human comfort are evaluated. The outputs are described in terms of three-dimensional (3-D) Power Spectral Densities (PSDs) under three types of random track irregularities: vertical profile, lateral alignment, and cross-level. Furthermore, Sperling's method is used to evaluate the human comfort index. For the case study, a Linke-Hofmann-Busch coach (LHB) based model has been employed, and the results are validated with the experimental data of ride comfort reported by the Research Design and Standard Organization (RDSO). The simulated results of the proposed model demonstrate a remarkable alignment with the experimental data, exhibiting a small error ranging from 2.36 % to 8.81 % for vertical motion and 5.84 % to 8.30 % for lateral motion, respectively. Such promising results offer valuable insight for the design of future coaches, ensuring enhanced ride comfort even at high speeds.

Public use and public funding of science.

Knowledge of how science is consumed in public domains is essential for understanding the role of science in human society. Here we examine public use and public funding of science by linking tens of millions of scientific publications from all scientific fields to their upstream funding support and downstream public uses across three public domains-government documents, news media and marketplace invention. We find that different public domains draw from various scientific fields in specialized ways, showing diverse patterns of use. Yet, amidst these differences, we find two important forms of alignment. First, we find universal alignment between what the public consumes and what is highly impactful within science. Second, a field's public funding is strikingly aligned with the field's collective public use. Overall, public uses of science present a rich landscape of specialized consumption, yet, collectively, science and society interface with remarkable alignment between scientific use, public use and funding.