Compressive Measurements Research Articles

(Invited) PEM Water Electrolysis Stack Development and Related Characterization Tools

For decades, proton-exchange membrane (PEM) water electrolysis (WE) has been mainly used for oxygen generation in anaerobic environments. Over the past two decades, however, it has been increasingly used for hydrogen generation in the industrial sectors at various scales. The PEMWE technology is also considered a key in the ongoing energy transition, if the process of hydrogen generation by means of WE is linked to renewable energy sources, such as wind, solar, etc.The following key elements enable the operation of a PEM WE plant for hydrogen production: a PEM-based WE stack and the balance of plant. The related system includes, but not limited to such key modules as the water and oxygen management systems, hydrogen gas management system, water input system, safety system, power electronics and electrolysis cell stack power supply, control system, and some other.A WE stack comprises several cells connected in series with electrically conductive bipolar plats and end plates. General design principles for the stack involve reducing efficiency losses, while aiming at lower costs and increase in durability. WE stacks should be designed in such a way, that an even current distribution is maintained, the water feed is optimized, suitable compression ratios are achieved, and preferably high discharge pressure of hydrogen can be enabled. For the stack level, in simple terms, efficiency is benchmarked by the total applied voltage, which includes the Nernst potential, anode and cathode overpotentials, and ohmic overpotentials due to the membrane ionic resistance and interfacial resistance at given current density. Overpotential represents inefficiencies in a cell stack, and some of stack design efforts focus on reducing these overpotential contributions. However, a compromise has to be found between (a) costs reduction challenges (that are often associated with the reduction of PGM-based catalyst loading, attempts to replace Ti as a key material for the bipolar plates, and the less expensive SPE membrane), (b) sufficient durability, (c) performance of the stack, (d) increase in power density of a stack.This talk will focus on the WE stack, and its subcomponents review, as well as characterization methods for both, a single cell and a stack and also challenges of the large-scale stack manufacturing. The key components of the WE stack include ion-conductive solid polyelectrolyte membranes (SPE), anode and cathode catalyst layers (CL), bipolar plates and current collectors/ gas diffusion layers (porous transport layers).In order to gain fundamental understanding of the relationships between electrical loses, degradation of the stack components and strategies to increase power density of the stacks, advanced characterization and modelling tools need to be used. These include, but not limited to electrochemical impedance spectroscopy (EIS), current interrupt (CI), dynamic compression measurements with piezoelectric senor plates, current mapping, gas cross-over analysis, computational fluid dynamics (CFD) simulations modelling, various visualization tools, etc. For example, CFD could assist in understanding and improving fluid flow dynamics in a WE stack as it is a complex challenge that requires a detailed examination of the geometry, channel design, and operating conditions within the stack. As for EIS, the usage of the distribution of relaxation times (DRT) approach would potentially allow to focus on the direct analysis of the data rather focusing on the equivalent circuit development.Approximately 15 years ago the South African Government approved a national program HySA: Hydrogen South Africa, which resulted in the development of the expertise and capacity to conduct research, development, and earlier commercial activities around green hydrogen production by means of water electrolysis. These activities include the development of local IP at the components, stack, and system levels.

Sustainable Alkali Activation: The Role of Water- and Alkali-Treated Sisal Leaf Wastewaters in Solid- Waste-Based Composite Synthesis.

The intricate composition of wastewater impedes the recycling of agricultural and industrial effluents. This study aims to investigate the potential of sisal leaf wastewater (SLW), both water-treated (WTSLW) and alkali-treated (ATSLW), as a substitute for the alkali activator (NaOH solution) in the production of slag-powder- and fly-ash-based composites, with a focus on the effects of WTSLW substitution ratios and sisal leaf soaking durations. Initially, the fresh properties were assessed including electrical conductivity and fluidity. A further analysis was conducted on the influence of both WTSLW and ATSLW on drying shrinkage, density, and mechanical strength, including flexural and compressive measures. Microstructural features were characterized using SEM and CT imaging, while XRD patterns and FTIR spectra were employed to dissect the influence of WTSLW substitution on the composite's products. The results show that incorporating 14 wt% WTSLW into the composite enhances 90-day flexural and compressive strengths by 34.8% and 13.2%, respectively, while WTSLW curtails drying shrinkage. Conversely, ATSLW increases porosity and decreases density. Organic constituents in both WTSLW and ATSLW encapsulated in the alkaline matrix fail to modify the composites' chemical composition. These outcomes underscore the potential for sustainable construction materials through the integrated recycling of plant wastewater and solid by-products.

Statistical sampling method to verify the homogeneity of full-scale cement-solidified radioactive waste

Homogeneity is an important factor for ensuring the structural stability of solidified radioactive waste, and the most effective approach for assessing its homogeneity is by performing compressive strength measurements using the minimum amount of coring specimens. The efficiency of detecting inhomogeneous waste is affected by the coring position and number of coring positions. However, no guidelines exist for coring solidified waste for compressive-strength tests. Therefore, this study compared uniform, random, and quasi-Monte Carlo sampling methods to determine the most effective core position. Further, the effects of different sampling amounts on the detection rate of inhomogeneous solidified waste were observed, and the detection rate of the inhomogeneous waste was obtained by modeling the coring procedure of solidified radioactive waste using MATLAB. Thus, a sampling method and a method for increasing the specimen amount, both of which can efficiently detect inhomogeneous waste during compressive strength tests, were presented in this paper. The results of this study can be applied as background data for developing homogeneity assessment guidelines for solidified radioactive waste.

Anomalous Landau Level Gaps Near Magnetic Transitions in Monolayer WSe2

First-order phase transitions produce abrupt changes to the character of both ground and excited electronic states. Here we conduct electronic compressibility measurements to map the spin phase diagram and Landau level (LL) energies of monolayer WSe2 in a magnetic field. We resolve a sequence of first-order phase transitions between completely spin-polarized LLs and states with LLs of both spins. Unexpectedly, the LL gaps are roughly constant over a wide range of magnetic fields below the transitions, which we show reflects spin-polarized ground states with opposite spin excitations. These transitions also extend into compressible regimes, with a sawtooth boundary between full and partial spin polarization. We link these observations to the important influence of LL filling on the exchange energy beyond a smooth density-dependent contribution. Our results show that WSe2 realizes a unique hierarchy of energy scales where such effects induce reentrant magnetic phase transitions tuned by density and magnetic field. Published by the American Physical Society 2024

Image reconstruction from compressed measurements for ultrasound NDT

In ultrasound NDT, Delay-and-Sum schemes are commonly used to reconstruct images from the measurement data. For single channel pulse-echo measurements, this is called Synthetic Aperture Focusing Technique (SAFT). In a multi-channel setup, SAFT is extended to the Total Focusing Method (TFM), where the focused image is reconstructed from measurements of all transmit-receive combinations, called Full Matrix Capture (FMC). In previous work, we showed that both SAFT and TFM can be cast as a sparse recovery problem that enables enhancing the Delay-and-Sum scheme to a physically motivated forward model that leads to improved image quality. The reconstruction is performed using l1 minimization. Further, this also allows to perform the reconstruction from compressed/subsampled measurements following compressed sensing theory. This subsampling was achieved by only measuring a subset of the frequency coefficients of the signal. In both the single channel and the multi-channel setup the amount of measurement data is thereby significantly reduced. Additionally, for the TFM, we added a spatial subsampling by only considering a subset of transmit and receive pairs, further reducing the measurement data and at the same time also reducing the measurement time. In our previous work, the frequency and spatial dimensions were considered separately for simplicity, using the same compression strategy for all spatial measurements. In this work we consider joint frequency/spatial compression schemes. We show that a joint multidimensional compression strategy where different Fourier subsets are considered for each channel pair leads to a superior reconstruction performance when the compression rate is fixed. Analysis based on an analytical model for a single defect and a real-world example with multiple defects shows that the approach works in practice.

Evaluation of Physical Properties in Carboxymethyl Chitosan Modified Glass Ionomer Cements and the Effect for Dentin Remineralization: SEM/EDX, Compressive Strength, and Ca/P Ratio.

The aim of this article was to evaluate the effects of modifying glass ionomer cement (GIC) with carboxymethyl chitosan (CMC) on surface morphology and remineralization outcomes by examining dentin morphology and calcium ion composition changes. Thirty holes in a cylindrical acrylic mold were filled with three groups of restorative materials: GIC, GIC modified with CMC (GIC-CMC) 5%, and GIC-CMC10%. The surface morphology of each group's materials was observed using scanning electron microscopy (SEM). The compressive strength measurement was performed using a universal testing machine. The dentin remineralization process was performed by applying GIC, GIC-CMC5%, and GIC-CMC10% materials for 14 days on demineralized dentin cavities treated with 17% ethylenediamine tetraacetic acid (EDTA) for 7 days. A morphological evaluation was conducted using SEM. The calcium ion composition and calcium-to-phosphorous (Ca/P) ratio were examined using an energy-dispersive X-ray (EDX). The Kruskal-Wallis and post-hoc Mann-Whitney U tests were performed to compare all four groups of calcium ions (p < 0.05). The modification of GIC with CMC affected the morphological changes in the materials in the form of reduced porosity and increased fractures. A significant difference was found in compressive strength between the GIC-CMC modification materials of GIC-CMC5% and GIC-CMC10% and the GIC control group. The dentin tubule morphology and surface changes were observed after applying GIC, GIC-CMC5%, and GIC-CMC10% materials for 14 days, as evaluated by SEM. The EDX examination showed an increase in calcium ion content and hydroxyapatite formation (Ca/P ratio) after applying the GIC-CMC10% material. The surface porosity of the GIC modification material with the addition of CMC tended to decrease. However, an increase in cracked surfaces that widened, along with the rise in CMC percentage, was found. This modification also reduced the compressive strength of the materials, with the lowest average yield at 10% CMC addition. Therefore, the modification of GIC with CMC affects changes in morphology, calcium ion composition, and Ca/P ratio in demineralized dentin.

Artificial intelligence-based evaluation of carotid artery compressibility via point-of-care ultrasound in determining the return of spontaneous circulation during cardiopulmonary resuscitation

AimThis study introduces RealCAC-Net, an artificial intelligence (AI) system, to quantify carotid artery compressibility (CAC) and determine the return of spontaneous circulation (ROSC) during cardiopulmonary resuscitation. MethodsA prospective study based on data from a South Korean emergency department from 2022 to 2023 investigated carotid artery compressibility in adult patients with cardiac arrest using a novel AI model, RealCAC-Net. The data comprised 11,958 training images from 161 cases and 15,080 test images from 134 cases. RealCAC-Net processes images in three steps: TransUNet-based segmentation, the carotid artery compressibility measurement algorithm for improved segmentation and CAC calculation, and CAC-based classification from 0 (indicating a circular shape) to 1 (indicating high compression). The accuracy of the ROSC classification model was tested using metrics such as the dice similarity coefficient, intersection-over-union, precision, recall, and F1 score. ResultsRealCAC-Net, which applied the carotid artery compressibility measurement algorithm, performed better than the baseline model in cross-validation, with an average dice similarity coefficient of 0.90, an intersection-over-union of 0.84, and a classification accuracy of 0.96. The test set achieved a classification accuracy of 0.96 and an F1 score of 0.97, demonstrating its efficacy in accurately identifying ROSC in cardiac arrest situations. ConclusionsRealCAC-Net enabled precise CAC quantification for ROSC determination during cardiopulmonary resuscitation. Future research should integrate this AI-enhanced ultrasound approach to revolutionize emergency care.

Modeling of thermodynamic processes in internal combustion engine cylinder during cranking in compression measurement tests

The thermodynamics of in-cylinder processes of the internal combustion engine in cranking mode when measuring compression were examined. Analysis of various theoretical models and comparison of known data showed that the problems of constructing mathematical models of the engine operating cycle remain unresolved. The vast majority of practical data and recommendations for measuring cylinder compression are based on empirical knowledge, numerous experiments and tests. In accordance with this, there is a need for computational models of the compression measurement process and their theoretical justification. To solve the identified problems, a mathematical model of the thermodynamic processes in the cylinder was developed. Unlike existing ones, the model describes the processes in the cylinder step by step, taking into account the real nature of the intake-exhaust processes, air leakage through the interfaces of parts and heat exchange with the walls. Using modeling, the main patterns of changes in compression depending on the modes, the nature of damage to the associated parts of the valve mechanism and cylinder-piston group, the amount of leakage and engine temperature were found. Based on the results of the study, the properties of the model which make its use effective in diagnosing and monitoring the technical condition of engines in operation were concluded.

Gypsum-Enhanced Red Mud Composites: A Study on Strength, Durability, and Leaching Characteristics

The strong alkalinity of red mud and the heavy metals it contains pose a serious threat to the environment. This study investigated the possibility of applying red mud as a solid waste material in road construction to mitigate the problem of red mud accumulation. Red mud was modified using titanium gypsum and phosphogypsum as curing agents. The effects of varying gypsum types and mixing ratios on the mechanical properties and heavy metal leaching of the resulting red mud-based materials were assessed using percussion tests, unconfined compressive strength measurements, scanning electron microscopy (SEM), and continuous heavy metal leaching tests. The results showed that the optimal moisture content for titanium gypsum–cement-stabilized red mud (RTC) exceeds that of phosphogypsum–cement-stabilized red mud (RPC), with RTC exhibiting a lower maximum dry density compared to RPC. When the gypsum admixture was within 10%, the strength of the RPC was higher than that of the RTC at the same and curing time. The reticulation in RPC-10 was denser. The cumulative heavy metal releases from both RTC and RPC were within the permissible limits for Class III groundwater discharge standards. Based on the comprehensive test results, RPC is identified as the superior modified red mud material, with an optimal mix ratio of red mud/phosphogypsum/cement of 87:5:8.

Determining peat's vertical hydraulic diffusivity and hydraulic conductivity from naturally occurring hydraulic pressure fluctuations measured at various depths

AbstractThis study presents a method that could be used to assess the in‐situ saturated vertical hydraulic conductivity of deeper and more decomposed peat layers. Deeper peat layers may exhibit very low permeability comparable to clayey sediments, where measurements and sediment sample collection are very difficult. More traditional measurement methods, such as slug‐tests and permeameter tests, have proven difficult to carry out in these conditions, necessitating an alternative method. For surpassing these possible constraints, this paper introduces a field method to quantify vertical hydraulic diffusivity, capitalizing on naturally occurring hydraulic pressure fluctuations measured with buried pressure sensors. The determined diffusivity values are used to calculate vertical hydraulic conductivity of peat using separately measured compressibility and specific storage values. Our research demonstrates the feasibility of using this method to evaluate vertical hydraulic diffusivity in lower peat layers. Calculated diffusivity values, combined with peat compressibility measurements, yield reasonable estimates of vertical hydraulic conductivity for dense fen peat comparable with more widely used in‐situ and laboratory methods. It also shows potential for vertical hydraulic characteristics parametrization in the upper less decomposed and compacted peat layers; however, further research is needed to understand the method's limitations in such conditions. Our approach provides a potential method for measuring in‐situ vertical hydraulic properties of less accessible peat layers, often overlooked, while also providing a way to surpass the scale‐dependency constraints inherent in peatlands' heterogeneous structure. Such information is necessary when studying the hydraulic interactions between groundwater aquifers and peatlands.

A platform for planar dynamic compression of crystalline hydrogen toward the terapascal regime

We describe a method for laser-driven planar compression of crystalline hydrogen that starts with a sample of solid para-hydrogen (even-valued rotational quantum number j) having an entropy of 0.06 kB/molecule at 10 K and 2 atm, with Boltzmann constant kB. Starting with this low-entropy state, the sample is compressed using a small initial shock (&amp;lt;0.2 GPa), followed by a pressure ramp that approaches isentropic loading as the sample is taken to hundreds of GPa. Planar loading allows for quantitative compression measurements; the objective of our low-entropy compression is to keep the sample cold enough to characterize crystalline hydrogen toward the terapascal range.

Joint-learning-based coded aperture compressive temporal imaging

Coded aperture compressive temporal imaging (CACTI) is a recently developed imaging technique based on the theory of compressed sensing. It uses an optical imaging system to sample a high-speed dynamic scene (a set of consecutive video frames), integrates the sampled data in time according to masks (sensing matrix), and thus obtains compressive measurements. Considerable effort has been devoted to the sampling strategy and the ill-posed inverse process of reconstructing a three-dimensional (3D) high-speed dynamic scene from two-dimensional (2D) compressive measurements. The importance of the reconstruction algorithm and the optimization mask is evident. In this paper, a flexible, efficient, and superior quality Landweber iterative method is proposed for video reconstruction through jointly learning the optimal binary mask strategy, relaxation strategy, and regularization strategy. To solve the sparse representation problem in iteration, multiple denoisers are introduced to obtain more regularization prior information. By combining the mathematical structure of the Landweber iterative reconstruction method with deep learning, the challenging parameter selection procedure is successfully tackled. Extensive experimental results demonstrate the superiority of the proposed method.

Adaptive Joint Carrier and DOA Estimations of FHSS Signals Based on Knowledge-Enhanced Compressed Measurements and Deep Learning.

As one of the most widely used spread spectrum techniques, the frequency-hopping spread spectrum (FHSS) has been widely adopted in both civilian and military secure communications. In this technique, the carrier frequency of the signal hops pseudo-randomly over a large range, compared to the baseband. To capture an FHSS signal, conventional non-cooperative receivers without knowledge of the carrier have to operate at a high sampling rate covering the entire FHSS hopping range, according to the Nyquist sampling theorem. In this paper, we propose an adaptive compressed method for joint carrier and direction of arrival (DOA) estimations of FHSS signals, enabling subsequent non-cooperative processing. The compressed measurement kernels (i.e., non-zero entries in the sensing matrix) have been adaptively designed based on the posterior knowledge of the signal and task-specific information optimization. Moreover, a deep neural network has been designed to ensure the efficiency of the measurement kernel design process. Finally, the signal carrier and DOA are estimated based on the measurement data. Through simulations, the performance of the adaptively designed measurement kernels is proved to be improved over the random measurement kernels. In addition, the proposed method is shown to outperform the compressed methods in the literature.

Mathematical and experimental insights into acid-resistant enhancements: Graphene plates' influence on rubber-incorporated cementitious materials

To mitigate the strength loss of rubberised cementitious materials, either concrete or mortar, graphene plates were incorporated. Limited studies have highlighted significant strength enhancement in rubberised cementitious materials incorporating graphene plates under non-acidic conditions. However, a notable gap persists in their performance when exposed to harsh conditions, particularly those induced by acid attack. Therefore, this study aimed to assess the inclusion of graphene plates, alongside Arabic gum as a surfactant for graphene dispersion, on the acid resistance of rubberised mortar exposed to sulphuric acid (H2SO4). One purpose of this study was to experimentally examine their behaviour through visual inspection, compressive strength measurement, and weight loss analysis. The second purpose was to utilise response surface methodology for prediction, optimisation, and developing two quadratic equations for further exploration. The results exhibit a strong alignment between equations and experimental data, with a coefficient of variation below 2.8 % and an impressive R-squared value of 0.99, confirming their reliability and accuracy. Additionally, the proposed mortar incorporating graphene plates and rubber demonstrates superior resistance to acid attacks. Even with up to an 18 % increase in rubber content, it shows reduced strength and weight losses of 47.1 % and 25.2 % after 40 days, respectively, compared to the control mixture's losses of 62.1 % and 33.6 %. It can be concluded that the remarkable results obtained for graphene-based rubberised cementitious material hold promise for real-world applications, particularly where resistance to energy absorption and penetration by aggressive agents is required such concrete pavement.

Mechanical imbalance between normal and transformed cells drives epithelial homeostasis through cell competition.

Cell competition in epithelial tissue eliminates transformed cells expressing activated oncoproteins to maintain epithelial homeostasis. Although the process is now understood to be of mechanochemical origin, direct mechanical characterization and associated biochemical underpinnings are lacking. Here, we employ tissue-scale stress and compressibility measurements and theoretical modeling to unveil a mechanical imbalance between normal and transformed cells, which drives cell competition. In the mouse intestinal epithelium and epithelial monolayer, transformed cells get compacted during competition. Stress microscopy reveals an emergent compressive stress at the transformed loci leading to this compaction. A cell-based self-propelled Voronoi model predicts that this compressive stress originates from a difference in the collective compressibility of the competing populations. A new collective compressibility measurement technique named gel compression microscopy then elucidates a two-fold higher compressibility of the transformed population than the normal population. Mechanistically, weakened cell-cell adhesions due to reduced junctional abundance of E-cadherin in the transformed cells render them collectively more compressible than normal cells. Taken together, our findings unveil a mechanical basis for epithelial homeostasis against oncogenic transformations with implications in epithelial defense against cancer.

Human cytochrome C natural variants: Studying the membrane binding properties of G41S and Y48H by fluorescence energy transfer and molecular dynamics

Cytochrome C (cyt C), the protein involved in oxidative phosphorylation, plays several other crucial roles necessary for both cell life and death. Studying natural variants of cyt C offers the possibility to better characterize the structure-to-function relationship that modulates the different activities of this protein. Naturally mutations in human cyt C (G41S and Y48H) occur in the protein central Ω-loop and cause thrombocytopenia 4. In this study, we have investigated the binding of such variants and of wild type (wt) cyt C to synthetic cardiolipin-containing vesicles. The mutants have a lower propensity in membrane binding, displaying higher dissociation constants with respect to the wt protein. Compressibility measurements reveal that both variants are more flexible than the wt, suggesting that the native central Ω-loop is important for the interaction with membranes. Such hypothesis is supported by molecular dynamics simulations. A minimal distance analysis indicates that in the presence of cardiolipin the central Ω-loop of the mutants is no more in contact with the membrane, as it happens instead in the case of wt cyt C. Such finding might provide a hint for the reduced membrane binding capacity of the variants and their enhanced peroxidase activity in vivo.

Compaction behaviours of 17-4 PH, 316L, and 1.4551 stainless-steel powders during cold pressing

Despite numerous recent technological developments, conventional powder metallurgy (CPM) remains the most commonly applied technique for fabricating stainless-steel products. However, the compressibility of stainless-steel powders is still a critical issue. Martensitic stainless-steel powders (i.e., 17-4 PH) are significantly harder than austenitic stainless-steel powders (i.e., 316L and 1.4551). Herein, three different stainless-steel (DSS) powders (i.e., 17-4 PH, 316L, and 1.4551) were investigated using a high cold pressing pressure (i.e., 1.6 GPa) and a relatively low sintering temperature of 1200 °C during CPM. Dimensional and Archimedes density measurements, volume and radial shrinkage calculations, optical and scanning electron microscopy analyses, and compressive strength measurements were conducted to investigate the physical and mechanical properties. Using 1.6 GPa resulted in a 10 % and 6 % increase in the relative green density of the 17-4 PH and 316L samples, compared with the reported literature. For the first time, relative sintering densities of approximately 97 % and 99 % were obtained for 316L and 1.4551 at a sintering temperature of 1200 °C, respectively. Despite the insufficient sintering process, the relative density of the 17-4 PH sample increased by 2 % compared with the literature values reported for higher sintering temperatures. The shrinkage ratios were much lower than those reported in the literature. Furthermore, the present 316L samples achieved 90 % of the compressive yield strength observed in cast 316L, a 25 % increase compared with that previously reported in the literature. This study extends the CPM procedure for enhancing green densities, employing low sintering temperatures, and reducing the shrinkage values of stainless-steel powders with differing hardness.

An interpretable and flexible fusion prior to boost hyperspectral imaging reconstruction

Hyperspectral image (HSI) reconstruction from the compressed measurement captured by the coded aperture snapshot spectral imager system remains a hot topic. Recently, deep-learning-based methods for HSI reconstruction have become the mainstream due to their high performance and efficiency in the testing inference. However, these learning methods do not fully utilize the abundant spectral information with proper physical spectral priors, resulting in complex architectures and unsatisfactory reconstruction performance. In this paper, we claim that the spectral low-rank property can still help these learning methods and propose a hyperspectral fusion theory, which demonstrates that full HSIs are mathematically equivalent to the closed-form combination of subspace images, mask, and measurements. Based on the above fusion theory, we propose the subspace distillation prior (SP) to efficiently cooperate with existing learning models to enhance the exploration of the spectral low-rank property. In detail, the SP can directly improve the testing inference of existing models (SP1, Section 4.1). Furthermore, SP can also be cooperated with exiting networks to formulate a new framework, which regularizes the existing models to learn the subspace images, and help to reconstruct the full HSIs from subspace images, mask, and measurements (SP2, Section 4.2). We choose six existing representative models for the HSI reconstruction experiments and find that SP1 and SP2 can, respectively, achieve improvements of 0.08 dB∼0.76 dB and 0.36 dB∼1.76 dB on the simulated datasets, demonstrating the advantage of the proposed hyperspectral fusion theory. The source code is available at https://github.com/prowDIY.

Research on compressive strength and thermal conductivity of lightweight phosphogypsum-based composite cementitious materials

Investigation of the mechanical and thermal properties of lightweight phosphogypsum-based cementitious materials can enhance the utilization rate of phosphogypsum-based composites and reduce building energy consumption. In this study, various amounts of hollow glass microspheres (HGMs) are incorporated into phosphogypsum-based composite cementitious materials to investigate their effects on mechanical and thermal insulation properties. Subsequently, comparisons are made between lightweight phosphogypsum-based composite cementitious materials produced by foaming and those with added HGMs. The research findings indicate that HGMs significantly mitigate the loss of compressive strength and notably reduce thermal conductivity, aligning with the development needs of lightweight and high-strength construction materials. Specifically, at a 20 % HGM dosage, the specimen exhibits a thermal conductivity of 0.2512 W·m−1·K−1, marking a 46.0 % decrease compared to specimens without HGMs. Additionally, the compressive strength measures at 25.45 MPa, reflecting a 36.4 % decline relative to specimens without HGMs. However, because of the uncontrolled pore structure and size in lightweight phosphogypsum-based composite cementitious materials produced by direct foaming, the decrease in compressive strength of foamed materials is greater than that of materials with added HGMs when the reduction in the coefficient of thermal conductivity is the same. Moreover, the compressive strength of phosphogypsum-based composite cementitious materials made with HGMs decreases more than that made with the addition of HGMs. This can be attributed to the uniform particle size of HGMs, contributing to a singular and complete pore structure within the phosphogypsum-based cementitious materials, thereby optimizing their performance.

Enhancing data sparsity in spectral signals using wavelet decomposition for improved compression and storage efficiency

Wavelet decomposition (WD) is integrated into the Compressive Sensing (CS) model to enhance data sparsity. This approach aims to ensure efficiency and quality in the received data after compression and reconstruction processes. The proposed WD-CS model is developed for reflected spectra signals from Fiber Bragg Gratings-based extensometers, which were subjected to induced deflections simulating the underground soil movement. WD decomposes the input signal before compressive measurement, followed by transferring and storing the compressed data in the cloud. The spectral data were reconstructed using Orthogonal Matching Pursuit (OMP) followed by wavelet reconstruction. The impact of wavelet decomposition on the quality of compression and reconstruction is assessed and compared against that of the standard CS model. The findings indicate that the WD-CS model can improve data sparsity by a factor of three and compressibility by a factor of ten without degenerating the reconstructed data quality. The error in the Bragg wavelength shift of the reconstructed spectra is minimal extracted using Pseudo-high Resolution Interrogation (PHRI) method. The proposed WD-CS model is useful in improving data compression for FBG spectra as well as storage efficiency, which make it potentially applicable in FBG-based sensor networks for long-term structural health monitoring applications.