Continuous Variation Research Articles

Residual stress evaluation in innovative layer-level continuous functionally graded materials produced by Powder Bed Fusion-Laser Beam

The main objective of this study is to evaluate residual stresses in AISI 316L and 18Ni Maraging 300 functionally graded materials with continuous variation of composition within a single layer using the contour method. The manufacture of this kind of layer-level continuous functionally graded materials by employing a Powder Bed Fusion-Laser Beam system utilizing a blade/roller-based powder spreading technique has only been recently devised and a proper residual stress analysis is still required. In fact, as the mechanical properties of additively manufactured samples are significantly influenced by the direction of construction, the same holds true for the direction along which the compositional variation is made. Furthermore, in this study, the impact of solution annealing and aging heat treatment, which are necessary for enhancing the mechanical properties of martensitic steel, on residual stresses was explored. Additionally, the effect of adopting material-differentiated process parameters was investigated. The results indicated that each specimen displayed areas of tensile stress concentration on the upper and lower surfaces, balanced by compression in the center. The application of heat treatment led to a decrease in the maximum tensile stress of 8% and provided a uniform and significant stress reduction within the maraging steel. Finally, the implementation of material-specific process parameters for the three composition zones in conjunction with the heat treatment resulted in a reduction in the maximum residual stress of 35% and also a significantly lower residual stress field throughout the specimen.

Topological design of soft substrate acoustic metamaterial for mechanical tuning of sound propagation

The design of tunable acoustic waves is crucial in phononic crystals (PnCs), as acoustic waves exhibit continuous variation across diverse frequency ranges in practical applications. While there have been research efforts on tunable PnCs, existing design strategies predominantly rely on predetermined topology and scatterer shapes based on empirical experience. This reliance poses challenges in ensuring customized and reversible tuning of the bandgap. In this work, we present a customized tunable PnC design model and solution strategy based on soft substrates, which enables reversible tuning of a specific frequency/order bandgap. The designed structure consists of a soft substrate and crystalline columns dispersed in the soft substrate and air. The relative positions of the scatterers in the air are changed by stretching the substrate, thereby realizing the modulation of sound propagation. Since soft materials have both material nonlinearities and complex geometrical variations that are difficult to obtain design sensitivity information, the material-field series expansion topology optimization approach is employed to achieve custom tunable design of the bandgap. The paper presents simulation-based analyses and experimental verification of the customized bandgap opening and closing. The results demonstrate a close alignment between theoretical predictions of propagation curves and experimental findings. This concurrence serves as evidence that the soft-substrate PnC, derived through topology optimization, effectively facilitates the adjustment of bandgaps of arbitrary orders and enables switching between various acoustic functions.

Study on updating finite element model of steel truss structure based on knowledge-enhanced deep reinforcement learning

Accurate assessment of the damage to a structure is the key to structural health monitoring. Among them, one effective means to assess the real-time status of the structure is by establishing a finite element model (FEM) of the structure and updating it synchronously. Previous research mainly updates the FEM of the structure with a certain moment in time without considering the continuous changes of structural parameters over a longer time. In this paper, we propose a FEM updating method for steel truss structure based on knowledge-enhanced deep reinforcement learning, which introduces long short-term memory (LSTM) network based on a deep deterministic policy gradient (DDPG) algorithm and constructs a knowledge-enhanced noise function (NF) module based on parametric analysis. The NF-LSTM-DDPG algorithm can fit a continuous variation of structural parameters. The ablation experiments revealed that the LSTM network and the NF module facilitate the exploration and learning ability of the DDPG algorithm. The NF-LSTM-DDPG algorithm is used in an actual steel truss structure case, and the variation rules of the elastic modulus and support deviations obtained from the solution are consistent with the actual situation. The average relative error of the 34 strain measurement points after updating is 14.147 %, and the relative error is higher than 20 % in only 13 days out of 187 days of continuous monitoring. Five days were selected for the comparative study, and the experimental results show that the relative error of the NF-LSTM-DDPG algorithm is 13.206 %, which is higher than that of the particle swarm optimization algorithm and the simulated annealing algorithm. The change of elastic modulus updated based on the NF-LSTM-DDPG algorithm is more reasonable than other algorithms.

Opposite relationships between soil organic carbon and elevation in the midlands and mountainous areas in Ireland related to different types of peat

Soil organic carbon (SOC) plays an important role in global carbon cycle which is influenced by multiple factors. Elevation, as one of these factors, has a close but complex relationship with SOC concentration. The traditional ‘global’ statistical models cannot capture the spatial variation thus are inefficient in revealing the relationships between SOC and elevation at the local scale. In this study, a ‘local’ model of geographically weighted regression (GWR) was used to explore the complex relationships between SOC and elevation in the topsoil of Ireland based on the dataset from National Soil Database of Ireland. The results indicated SOC and elevation exhibited the spatially continuously varying relationships across the study area. Positive relationships in the mountainous areas suggested SOC concentration increased with the increasing elevation. Negative relationships were observed in the midlands where SOC concentration decreased with the increasing elevation. Such varying relationships between SOC and elevation in Ireland were related to the two different main types of peat: blanket peat and raised peat. These two types of peat have different formation processes, thus are distributed at different elevations. In the mountainous areas, low temperature and high humidity create cool and anoxic environment that mitigates SOC mineralization, promoting the accumulation of blanket peat at a high elevation. In the midlands, the low-lying lakes and wetlands provide anoxic environment where raised peat is developed and located at a low elevation. The findings of the spatially varying relationships between SOC and elevation in Ireland have demonstrated the importance of modelling SOC at the ‘local’ level. Attention is required for soil mapping using a global algorithm and it is recommended that localized algorithms are considered in modelling SOC, taking the feature of continuous variation into consideration.

Identification and characterization of a new species of Taxus — Taxus qinlingensis by multiple taxonomic methods

BackgroundThe taxonomy of Taxus Linn. remains controversial due to its continuous phenotypic variation and unstable topology, thus adversely affecting the formulation of scientific conservation strategies for this genus. Recently, a new ecotype, known as Qinling type, is mainly distributed in the Qinling Mountains and belongs to a monophyletic group. Here, we employed multiple methods including leaf phenotype comparison (leaf shapes and microstructure), DNA barcoding identification (ITS + trnL-trnF + rbcL), and niche analysis to ascertain the taxonomic status of the Qinling type.ResultsMultiple comparisons revealed significant differences in the morphological characters (length, width, and length/width ratio) among the Qinling type and other Taxus species. Leaf anatomical analysis indicated that only the Qinling type and T. cuspidata had no papilla under the midvein or tannins in the epicuticle. Phylogenetic analysis of Taxus indicated that the Qinling type belonged to a monophyletic group. Moreover, the Qinling type had formed a relatively independent niche, it was mainly distributed around the Qinling Mountains, Ta-pa Mountains, and Taihang Mountains, situated at an elevation below 1500 m.ConclusionsFour characters, namely leaf curvature, margin taper, papillation on midvein, and edges were put forward as primary indexes for distinguishing Taxus species. The ecotype Qingling type represented an independent evolutionary lineage and formed a unique ecological niche. Therefore, we suggested that the Qingling type should be treated as a novel species and named it Taxus qinlingensis Y. F. Wen & X. T. Wu, sp. nov.

Incorporating Spatial Autocorrelation into GPP Estimation Using Eigenvector Spatial Filtering

Terrestrial gross primary productivity (GPP) is a critical part of land carbon fluxes. Accurately quantifying GPP in terrestrial ecosystems and understanding its spatiotemporal dynamics are essential for assessing the capability of vegetation to absorb carbon from the atmosphere. Nevertheless, traditional remote sensing estimation models often require complex parameters and data inputs, and they do not account for spatial effects resulting from the distribution of monitoring sites. This can lead to biased parameter estimation and unstable results. To address these challenges, we have raised a spatial autocorrelation light gradient boosting machine model (SA-LGBM) to enhance GPP estimation. SA-LGBM combines reflectance information from remote sensing observations with eigenvector spatial filtering (ESF) methods to create a set of variables that capture continuous spatiotemporal variations in plant functional types and GPP. SA-LGBM demonstrates promising results when compared to existing GPP products. With the inclusion of eigenvectors, we observed an 8.5% increase in R2 and a 20.8% decrease in RMSE. Furthermore, the residuals of the model became more random, reducing the inherent spatial effects within them. In summary, SA-LGBM represents the first attempt to quantify the impact of spatial autocorrelation and addresses the limitations of underestimation present in existing GPP products. Moreover, SA-LGBM exhibits favorable applicability across various vegetation types.

Continuous variation operator configuration for decomposition-based evolutionary multi-objective optimization

There are various multi-objective evolutionary algorithms (MOEAs) for solving multi-objective optimization problems (MOPs), and the significant difference between them lies in the way they generate offspring, which are the so-called variation operators. Since different variation operators have their own characteristics, it is often tedious to select a suitable EA for a given MOP. Even if the optimal operator is assigned, the fixed operator and hyper-parameters make it difficult to balance exploration and exploitation during the evolutionary process. It is imperative to configure variation operators and hyper-parameters automatically during the evolutionary process, which can improve the efficiency of algorithm search. However, numerous configurations only consider operators or discretize hyper-parameters, making it difficult to achieve satisfactory results. In this paper, we formulate the operator configuration as a continuous Markov Decision Process (MDP) and use a suitable Reinforcement Learning (RL) paradigm to realize the online configuration of EAs. To simplify the deployment of MDP, we adopt a decomposition-based framework and use a one-dimensional vector with a combination of weights and objectives as state spaces. In addition, we take the selection of crossover and mutation operators and the fine-tuning of their hyper-parameters as joint action spaces. With an RL technique, we expect to achieve maximum improvement in the performance of offspring on each preference by selecting an action in a given state. We further explore the effectiveness of the proposed methodology on different characteristic MOPs. Experimental results show that our method is more competitive than other configurations and state-of-the-art EAs.

Influence of thickness and strength on plastic instability in tailored steel structures

A mathematical model was intricately devised to explore the influence of continuous variations in thickness and mechanical properties on the performance of tailor rolled blanks (TRB) and tailor rolled tubes (TRT). Through the integration of analytical and numerical techniques, it was discerned that these variations play a pivotal role in modulating stress distribution and strain localization, thereby inducing a spectrum of plastic instability behaviors within the structures. The introduction of an ‘equivalent strength’ metric as a novel means to quantify structural performance shed light on strategic material distribution to enhance durability and mechanical efficiency. Moreover, the insights garnered from this research deepen the understanding of the mechanical responses of tailor-rolled constructs under varying loads, offering valuable perspectives for the development and fabrication of engineered materials with bespoke properties. This study not only contributes to bridging a knowledge gap in the realm of tailored material engineering but also fosters the advancement of design methodologies in the construction of high-performance engineered structures.

Advanced feature extraction for the characterization of impact events on composites using multiresolution wavelet-based simulations

The detection and characterization of impact events on composite structures from the induced wave responses, involves many challenges. Coexisting guided waves of high dispersive nature propagate after impact, entailing continuous time variations in their wavenumber, frequency and group velocity content, which complicate the exact estimation of the time-of-flight and the extraction of impact characteristics. A multiresolution finite wavelet domain computational method, combined with appropriate contact laws, is presented to provide enhanced simulation and characterization capabilities of impact events. An explicit multiresolution time integration scheme involves a coarse solution, followed by finer solutions that are sequentially added to the coarse one, until convergence is achieved. The hierarchical character of the approach makes the impact simulation very fast and accurate. Moreover, due to the filtering properties of Daubechies wavelet functions, each resolution component effectively models and isolates specific wavenumber spectra, providing the capability to separate coexisting wave modes, and to overcome difficulties imposed by the dispersive nature of the resultant guided waves. It is demonstrated that the multiresolution simulation can reveal wave characteristics and time-of-flight features that no other traditional single-resolution method can do, and provides the basis for the development of powerful inverse methods that can localize the impact and characterize the impactor parameters. The method is first applied on impacted composite strips and the structural responses of each resolution component are assessed in order to obtain the desired features for impact location estimation and characterization. Finally, the method is implemented on an impacted composite plate structure and the various wave characteristics simulated by the fine components are presented, evincing the advanced features that the proposed method provides.

A low-frequency pure metal metamaterial absorber with continuously tunable stiffness

To address the incompatibility between high environmental adaptability and deep subwavelength characteristics in conventional local resonance metamaterials, and overcome the deficiencies in the stability of existing active control techniques for band gaps, this paper proposes a design method of pure metal vibration damping metamaterial with continuously tunable stiffness for wideband elastic wave absorption. We design a dual-helix narrow-slit pure metal metamaterial unit, which possesses the triple advantage of high spatial compactness, low stiffness characteristics, and high structural stability, enabling the opening of elastic flexural band gaps in the low-frequency range. Similar to the principle of a sliding rheostat, the introduction of continuously sliding plug-ins into the helical slits enables the continuous variation of the stiffness of the metamaterial unit, achieving a continuously tunable band gap effect. This successfully extends the effective band gap by more than ten times. The experimental results indicate that this metamaterial unit can be used as an additional vibration absorber to absorb the low-frequency vibration energy effectively. Furthermore, it advances the metamaterial absorbers from a purely passive narrowband design to a wideband tunable one. The pure metal double-helix metamaterials retain the subwavelength properties of metamaterials and are suitable for deployment in harsh environments. Simultaneously, by adjusting its stiffness, it substantially broadens the effective band gap range, presenting promising potential applications in various mechanical equipment operating under adverse conditions.

Comparative Study on PSD and HHT Techniques for Condition Assessment of Steel Truss Bridge Using Acceleration Data

Bridge structures deteriorate over time due to factors like corrosion, fatigue, aging of materials, and unexpected natural or accidental events. Consequently, the vibrations measured in these structures exhibit time-varying and non-stationary characteristics. Additionally, non-linearities are inherent in these structures due to material behavior, boundary condition changes, and joints or connections. Analysis of non-linear and non-stationary structural vibration data is necessary to extract information on the condition of the bridge. Most methods assessing bridge conditions from acceleration responses rely on the Power Spectral Density (PSD) which is based on the Fourier Transform. However, the accuracy of the Fourier transforms for non-linear and non-stationary signals limits its application potential. The Hilbert–Huang Transform (HHT) has emerged as an alternative for handling these non-stationary signals due to its time-frequency-energy representation. This study provides a comparative study of both techniques by utilizing the data obtained from continuously monitored Pamban Bridge. This steel truss bridge was fitted with accelerometers to record bidirectional acceleration time histories at twenty bottom node points on the bridge. This study examines the continuous variations in the frequency component by both methods for 136 days. A linear best-fit trendline is obtained for the frequency parameters at different sensor positions. The slope and intercept values of this linear best fit trendline is further studied. The HHT showcases various evolving dominant frequency components over time in contrast to the PSD representation. The frequency spectrum from the HHT displays less variation over time at each sensor position compared to the predominant peak value derived from the PSD of the acceleration signal. The spatial variability in the predominant frequency obtained from HHT is also less than the PSD. Therefore, the ability of HHT to discriminate damages needs further investigations.

Novel eco-friendly spectrophotometric determination of lercanidipine hydrochloride in tablets using methyl red

The aim of the work was to develop a simple, eco-friendly, quick, affordable and alternative spectrophotometric procedure that uses the azodye methyl red (MR) for the determination of lercanidipine in its dosage form considering the “green” chemistry principles. Materials and methods. Analytical equipment: Shimadzu UV-1800 double beam UV-visible spectrophotometer (Japan) with included UV-Probe 2.70 software, RAD WAG AS 200/C precise analytical balance (Poland), Elmasonic EASY 40H ultrasonic bath. Lercanidipine hydrochloride (purity 99 %) was purchased from Jiyan Chemicals (India). Lercanidipine tablets 10 mg and 20 mg were used in our experiments. Results and discussion. To determine the amount of lercanidipine in tablets, a spectrophotometric method has been developed. To select the best dye for the method development, we tested a variety of dyes, including MR, bromocresol purple, bromophenol blue, cresol red, bromocresol green and bromothymol blue. We selected MR as the reagent based on the experimental studies' outcomes, and the solvent was an acetonitrile and ethanol mixture with a ratio of 95 to 5. The optimal parameters were determined for the quantitation of lercanidipine in tablets utilizing MR with 5×10-5 mol/L of dye concentration, 0.5 ml of MR solution, at a temperature of 25 °C without heating; detection wavelength was 498 nm and reaction time of 5 min. By using the molar ratios (saturation) method and Job's (continuous variations) approach, the stoichiometric coefficients of reacting components involving lercanidipine and dye were established to be 1:1. The proposed spectrophotometric procedure was linear within the concentration ranging from 6.48 – 32.41 μg/mL. Using the least squares method, a regression equation was generated: y = 0.0208x – 0.0318. The correlation coefficient was higher than 0.999, indicating that the analytical procedures' linearity is acceptable; the limit of detection and limit of quantitation were 1.19 μg/mL and 3.62 μg/mL, respectively. The robustness, accuracy and precision of the study results fell within acceptable limits. The proposed method was successfully applied to determine the content of lercanidipine in its tablet dosage forms. The analysis of the method's "greenness" using AGREE and GAPI tools yielded excellent results. Conclusions. The method that has been developed can serve as an alternative approach for the routine control of lercanidipine content in its tablets

MATN1 gene variant (rs1065755) and malocclusion risk: Evidence from Romanian population analysis

Malocclusion, characterized by its diverse phenotypic expression, significantly impacts patients’ quality of life. Over recent years, extensive attention has been directed towards the genetic basis of this condition, particularly focusing on various polymorphisms of the MATN1 gene. Among these, the rs1065755 polymorphism has emerged as particularly relevant, associated with an elevated risk of mandibular prognathism. In this study, employing DNA sequencing, we investigated the extent of association between the rs1065755 SNP and malocclusion risk within the Romanian population. Our approach concentrated on assessing continuous phenotypic variation through four cephalometric measurements, aiming for a comprehensive understanding beyond categorical phenotypes. The findings shed light on the relationship between the MATN1 rs1065755 SNP and the investigated dentofacial disorder, revealing a positive association between TT homozygous individuals and Class II skeletal malocclusion. However, further investigations employing larger sample sizes are necessary to validate these findings conclusively. Keywords: malocclusion, MATN1, rs1065755, cephalometric measurements.

KCC theory for a type of nonlinear damped SD oscillators

Smooth and discontinuous (SD) oscillators are the nonlinear models that will exhibit SD dynamics due to continuous variation of the smooth parameter. Kosambi–Cartan–Chern (KCC) theory is a differential geometric theory that describes the deviations from the entire trajectory of the variational equation to the nearby trajectory. This paper presents a completely new dynamical analysis of a type of SD oscillators with nonlinear damping based on the KCC theory. First, the paper gives five KCC geometrical invariants of SD oscillators in the smooth and non-smooth cases, respectively. The results show that the geometric quantities in the non-smooth case cannot be derived directly from the geometric quantities in the smooth case. Second, from these geometric quantities, KCC stability of SD oscillators trajectory at any point except [Formula: see text] is analyzed. Lastly, numerical results show that in some regions that deviate from the equilibrium point of system, the system will exhibit complex and variable dynamical behavior due to small changes in parameters. This paper shows that the KCC theory is also a useful tool in the dynamical analysis of non-smooth systems.

Thermal Stress Analysis for Functionally Graded Plates with Modulus Gradation, Part II

BackgroundThe gradation of thermal expansion coefficient was analyzed in the earlier study. The analytical formulation derived here, which is quite different, should be validated to understand the thermal stress distribution in a laminated composite and functionally graded material. Besides this solution, a validated numerical model can also be used to optimize the material gradation of plates in terms of sustainability.ObjectiveTo validate the analytical formulation derived here, an experimental model is presented to understand the thermal stress concentration for functionally graded and laminated composite plates. A numerical model is also validated to extend to understand the effects of the number of layers, the thickness of a layer, the gradation function, the ratio of elastic moduli, and the coating.MethodsThe experimental problems in the production of the experimental models with layers of different elastic moduli are discussed here. In the experimental analysis, a three-dimensional photoelastic stress analysis of two- and four-layer composite plate was used to mechanically model the thermal expansion. The analytical solution for the thermal stress in a free plate was derived by the strain suppression method based on the principle of superposition. The numerical models were analyzed using finite element software. The step variation in the experiment was used as a reference point for a continuous or multi-layer (> 2) step variation of material coefficients in the models.ResultsThe variation of stress concentration is shown for various cases of laminated and continuous gradations of elastic modulus. The four-layer experimental model provides the difference in thermal stress distribution as a result of a layered coating. The validated analytical and numerical models provide reasonable results. An empirical formula to optimize the material gradation in terms of elastic modulus is derived.ConclusionsThe experimental model can be used to analyze thermal stress in functionally graded materials. The gradations of the material in the plate or the coating of the plates can be optimized by the validated analytical and numerical models. The empirical formula can be used to determine the elastic modulus of the coating to minimize the stress concentration.

Multilayer-laminated optically transparent 300-GHz-band transmissive beamforming metasurface for wireless communication

A 300-GHz-band transmission-type multilayer metasurface beamformer based on a Jerusalem cross geometry is presented. A metamaterial cell with a continuous 2π phase variation for the radius change was designed and used in the fabrication of a reference device and three types of beamforming devices. The beamforming metasurface devices achieved steering angles of θ = 18°, θ = 30°, and θ = 38°, which were in good agreement with simulated results. A broadband operation in a 40 GHz band, from 280 GHz to 320 GHz was evaluated, showing only minor frequency dependence of the beamforming angles. The design and fabrication methodology can be applied to various types of metasurface devices, such as circular and fan lenses, beamformers, polarization switches, and so on for millimeter-wave frequency bands that are considered to be used in future 6 G wireless network systems.

Ferroelectric Order Evolution in Freestanding PbTiO3 Films Monitored by Optical Second Harmonic Generation.

The demand for low-dimensional ferroelectric devices is steadily increasing, however, the thick substrates in epitaxial films impede further size miniaturization. Freestanding films offer a potential solution by eliminating substrate constraints. Nevertheless, it remains an ongoing challenge to improve the stability in thin and fragile freestanding films under strain and temperature. In this work, the structure and ferroelectric order of freestanding PbTiO3 (PTO) films are investigated under continuous variation of the strain and temperature using nondestructive optical second harmonic generation (SHG) technique. The findings reveal that there are both out-of-plane and in-plane domains with polarization along out-of-plane and in-plane directions in the orthorhombic-like freestanding PTO films, respectively. In contrast, only out-of-plane domains are observed in the tetragonal epitaxial PTO films. Remarkably, the ferroelectricity of freestanding PTO films is strengthened under small uniaxial tensile strain from 0% up to 1.66% and well-maintained under larger biaxial tensile strain up to 2.76% along the [100] direction and up to 4.46% along the [010] direction. Moreover, a high Curie temperature of 630K is identified in 50nm thick freestanding PTO films by wide-temperature-range SHG. These findings provide valuable understanding for the development of the next-generation electronic nanodevices with flexibility and thermostability.

In-situ formation of hydrophobic deep eutectic solvents to separate lactic acid: Lactam as hydrogen bond acceptor and lactic acid as hydrogen bond donor

Lactic acid (LA) is a typical high added-value chemical and platform molecule derived from renewable biomass. To realize high efficiency and green separation of LA is of both scientific and practical significance. In this work, we proposed a novel mechanism of in-situ formation of hydrophobic deep eutectic solvents (HDES) to couple the separation of LA and synthesis of HDES. Due to the high solubility of LA as hydrogen bond donor in water, three hydrophobic lactams (N-Octyl-2-pyrrolidone (NOP), N-Dodecyl-2-pyrrolidone (NDP) and 2-Octyl-4-isothiazolin-3-one (OIT)) were optioned as hydrogen bond acceptors. The effect of lactam molecular structure on separation efficiency was discussed and compared in detail. The compositions of HDES forming in-situ were found to be 1.50 for NOP and NDP to LA while 1.20 for OIT to LA using experiments of slope method and continuous variations method. The key evidence of formation of HDES was confirmed by FT-IR, frontier molecular orbital analysis and interaction region indicator analysis. The multistage counter-current extraction experiment results showed the in-situ formation of HDESs can transfer 99% of LA from fermentation broth to the HDES, and LA was separated completely from the impurities. This work provided a new perspective on lactic acid separation and its potential industrial applications.

Real-time adaptive scheduling optimization for inter-satellite contact window resources in dynamic satellite networks

Real-time scheduling of contact window resources is a fundamental technology for the future construction of Space–Terrestrial Integrated Networks (STIN). The spatio-temporal dynamics of satellite networks result in continuous variations in satellite relative positions and inter-satellite visibility window resource status. Furthermore, frequent changes in task priority make real-time resource scheduling extremely challenging. Centralized online scheduling methods often lead to a significant amount of waiting time, while distributed online scheduling methods struggle to adapt to the high dynamics of satellite networks. Therefore, the real-time scheduling technology for contact window resources in satellite networks is still in the exploration phase. We propose an inter-satellite online resource allocation method to solve the latency issue caused by the seizure of contact window resources. First, we determine the shortest and maximum flow paths set in the satellite network according to task requirements and construct them as the core network. Then, we comprehensively analyze the supply and demand situation of the task and the core network at a specific moment and verify the reliability of our minimum cost flow-solving method based on the core network. Moreover, we consider factors such as changes in task priority and edge modifications and validate the correctness of our method to update the minimum cost flow at the next moment based on local network changes. Finally, through extensive comparative simulations, we evaluate the absolute advantage of our inter-satellite online scheduling method and validate a significant improvement in task scheduling timeliness.

Multi-factor thermal analysis of phase change material integrated roofing elements

In the present study, the PCM layer is integrated into the roof, analyzed, and compared for its thermal behaviour in terms of Indoor Air Temperature Reduction (IATR), Thermal Load Levelling (TLL), and Lag Time (LT) to determine the ideal position, thickness, and type of PCM. The observations from the experimental analysis were validated using COMSOL Multiphysics v6.0 with available literature. The results showed that PCM-integrated roofs reduced the interior temperature by around 30%. Furthermore, the fluctuations in the interior temperatures were reduced to 6.1% with PCM integration within the roof. A lag time of 5–8.25 h was observed for the PCM roofs. The study also found that the material properties impact the overall thermal behaviour of the PCM-integrated roofs. These properties were further explored using continuous cyclic thermal loading and variation of latent heat over a period of four days for three climatic zones in India. Abbreviations: PCM: Phase Change Material; CC: Conventional Concrete; AAC: Autoclaved Aerated Cement; TMY: Typical Meteorological Years; epw file: Energy Plus Weather File; mPCM: Microencapsulated Phase Change Material; PTC: Positive Temperature Coefficient; DHT: Digital Temperature And Humidity; IATR: Indoor Air Temperature Reduction (%); TLL: Thermal Load Levelling (%); LT: Lag Time (hours)