Compressive Measurements Research Articles

The Landscape of Compressibility Measures for Two-Dimensional Data

The Landscape of Compressibility Measures for Two-Dimensional Data

Coil-shaped Optical Fiber Sensor for Compression Measurements

This study investigated the effectiveness of a coil-shaped optical fiber interferometric sensor, with a diameter of 13 mm, for measuring compression. The sensor’s design utilizes the principles of interferometry to create a pattern that changes with applied pressure. This configuration significantly amplifies the sensor’s sensitivity to compression due to the extended optical path length within the compact form factor. The experimental results demonstrated that even small compressive forces caused detectable alterations in the interference pattern, allowing for precise quantification of pressure changes. The 13 mm diameter proved to be particularly advantageous, providing a balance between sensitivity and practical integration into various systems, from structural health monitoring to biomedical devices. This study also highlights the sensor’s robustness against electromagnetic interference and environmental variations, attributing this to the intrinsic properties of optical fiber. Overall, the findings suggest that coil-shaped optical fiber interferometric sensors are highly effective for accurate and reliable compression sensing, with potential for broad application across multiple industries.

Quantifying uncertainty in analysis of shockless dynamic compression experiments on platinum. I. Inverse Lagrangian analysis

Absolute measurements of solid-material compressibility by magnetically driven shockless dynamic compression experiments to multi-megabar pressures have the potential to greatly improve the accuracy and precision of pressure calibration standards for use in diamond anvil cell experiments. To this end, we apply characteristics-based inverse Lagrangian analysis (ILA) to 11 sets of ramp-compression data on pure platinum (Pt) metal and then reduce the resulting weighted-mean stress–strain curve to the principal isentrope and room-temperature isotherm using simple models for yield stress and Grüneisen parameter. We introduce several improvements to methods for ILA and quasi-isentrope reduction, the latter including calculation of corrections in wave speed instead of stress and pressure to render results largely independent of initial yield stress while enforcing thermodynamic consistency near zero pressure. More importantly, we quantify in detail the propagation of experimental uncertainty through ILA and model uncertainty through quasi-isentrope reduction, considering all potential sources of error except the electrode and window material models used in ILA. Compared to previous approaches, we find larger uncertainty in longitudinal stress. Monte Carlo analysis demonstrates that uncertainty in the yield-stress model constitutes by far the largest contribution to uncertainty in quasi-isentrope reduction corrections. We present a new room-temperature isotherm for Pt up to 444 GPa, with 1-sigma uncertainty at that pressure of just under ±1.2%; the latter is about a factor of three smaller than uncertainty previously reported for multi-megabar ramp-compression experiments on Pt. The result is well represented by a Vinet-form compression curve with (isothermal) bulk modulus K0=270.3±3.8 GPa, pressure derivative K0′=5.66±0.10, and correlation coefficient RK0,K0′=−0.843.

A likelihood based method for compressive signal recovery under Gaussian and saturation noise

Practical sensing systems have a limited dynamic range, which gives rise to saturation noise in signal acquisition if the signal attains values outside this range at certain locations. Despite rapid advances in compressed sensing theory and systems over the years, the effect of saturation on compressed sensing measurements, especially in the presence of additive Gaussian noise, has often been overlooked in many existing approaches. Some methods for compressive recovery under saturation noise simply discard saturated measurements, while others impose some ad hoc hard constraints to ensure consistency with the known saturation threshold. In this paper, we propose a novel maximum likelihood based estimator for compressive reconstruction in the presence of both Gaussian and saturation noise. Our proposed method ensures probabilistic consistency between the estimated signal and the saturated measurements and helps account for both the saturation effect and the potentially unbounded Gaussian noise in the measurements. We also derive upper bounds on the reconstruction error for our estimator, and argue that they follow intuitive trends. We analyze an important curvature term in these bounds, and show that it is superior to methods such as saturation rejection, indicating better stability and robustness. Furthermore, we present extensive simulation results to demonstrate the effectiveness of our method over several other existing methods in reconstructing synthetic signals and images from compressive measurements with saturation and Gaussian noise. We also show simulation results in audio signal de-clipping.

Effect of brick powders of various purities on hydration and compressive strength of Portland cement

AbstractThe availability of common supplementary cementitious materials (SCMs), as slags and fly ashes, is expected to reduce in the future. Among potential new SCMs, brick powders (BPs) have gained considerable attention. To study the effect of BPs as potential SCMs three BPs of different contamination were used for the experiments. The investigations included the R3 test as well as isothermal heat flow calorimetry and compressive strength measurements up to 91 days. In all tests, fly ash (FA) and limestone powder (LS) were used as a comparison. The reactivities determined in the R3 test could be explained by examining the chemical, mineralogical and physical properties of the BPs. Based on their reactivity in the R3 test, the BPs could be classified as pozzolanic, less reactive SCMs, with BPN showing the highest reactivity among the BPs. The results of the compressive strengths and the heat flow calorimetry confirm the reactivities determined in the R3 test. Based on the obtained results, BPN shows the highest potential for application as an SCM.

Hartley Transform Signal Compression and Fast Power Quality Measurements for Smart Grid Application

Hartley Transform Signal Compression and Fast Power Quality Measurements for Smart Grid Application

A Tensor-Based Online RPCA Model for Compressive Background Subtraction.

Background subtraction of videos has been a fundamental research topic in computer vision in the past decades. To alleviate the computation burden and enhance the efficiency, background subtraction from online compressive measurements has recently attracted much attention. However, current methods still have limitations. First, they are all based on matrix modeling, which breaks the spatial structure within video frames. Second, they generally ignore the complex disturbance within the background, which reduces the efficiency of the low-rank assumption. To alleviate this issue, we propose a tensor-based online compressive video reconstruction and background subtraction method, abbreviated as NIOTenRPCA, by explicitly modeling the background disturbance in different frames as nonidentical but correlated noise. By virtue of such sophisticated modeling, the proposed method can well adapt to complex video scenes and, thus, perform more robustly. Extensive experiments on a series of real-world video datasets have demonstrated the effectiveness of the proposed method compared with the existing state of the arts. The code of our method is released on the website: https://github.com/crystalzina/NIOTenRPCA.

A temporal Convolutional Network for EMG compressed sensing reconstruction

Electromyography (EMG) plays a vital role in detecting medical abnormalities and analyzing the biomechanics of human or animal movements. However, long-term EMG signal monitoring will increase the bandwidth requirements and transmission system burden. Compressed sensing (CS) is attractive for resource-limited EMG signal monitoring. However, traditional CS reconstruction algorithms require prior knowledge of the signal, and the reconstruction process is inefficient. To solve this problem, this paper proposed a reconstruction algorithm based on deep learning, which combines the Temporal Convolutional Network (TCN) and the fully connected layer to learn the mapping relationship between the compressed measurement value and the original signal, and it has been verified in the Ninapro database. The results show that, for the same subject, compared with the traditional reconstruction algorithms orthogonal matching pursuit (OMP), basis pursuit (BP), and Modified Compressive Sampling Matching Pursuit (MCo), the reconstruction quality and efficiency of the proposed method is significantly improved under various compression ratios (CR).

FAST Low-Energy Beamline Studies: Toward High-Peak 5D Brightness Beams for FAST-GREENS

The FAST beamline is the injector for the planned Gamma-Ray Electron ENhanced Source (GREENS) program, which aims to achieve the demonstration and first application of a high-efficiency, high-average-power free-electron laser at 515 nm. FAST-GREENS requires high 5D peak brightness; transverse normalized projected emittances of 3 mm-mrad and a peak current of 600 A are the minimum beam requirements for the FEL to reach the 10% efficiency goal. In this work, studies of the low-energy section of the FAST beamline are presented toward these ends, including preliminary measurements of beam compression and beam emittance. An effort toward developing a high-fidelity simulation model that could be later optimized for FAST-GREENS is presented.

BIOMECHANICS OF FACET JOINTS: SYNCHRONIZED SPATIO-TEMPORAL AND MECHANICAL ANALYSIS

AbstractObjectivesWhile spinal fusion is known to be associated with adjacent disc degeneration, little is known on the role of the facet joints in the process, and whether their altered biomechanics following fusion plays a role in further spinal degeneration. This work aimed to develop a model and method to sequentially measure the effects of spinal fusion on lumbar facet joints through synchronisation of both motion analysis, pressure mapping and mechanical analysis.MethodsParallel measurements of mature ovine lumbar facet joints (∼8yr old, n=3) were carried out using synchronised load and displacement measurements, motion capture during loading and pressure mapping of the joint spaces during loading. Functional units were prepared and cemented in PMMA endcaps. Displacement-controlled compression measurements were carried out using a materials testing machine (3365, Instron, USA) at 1 mm/min up to 950 N with the samples in a neutral position, while motion capture of the facet joints during compression was carried out using orthogonal HD webcams (Logitech, Switzerland) to measure the displacement of key facet joint features. The pressure mapping of load transfer during displacement was carried out using a flexible pressure sensor (6900 series, Tekscan, USA). Each sample was imaged at an isotropic resolution of 82 microns using a μCT scanner (XtremeCT, Scanco, Switzerland) to quantify the curvature within the facet joints.ResultsRelative facet joint displacement under load, in a neutral position, showed more displacement (2.36 ±1.68 mm) compared to the cross-head when under compression (2.06 ±1.19 mm). Motion capture indicated the relative displacement of the facet joints was more posterior with some lateral motion. For five of the six facet joints, pressure measurement was possible only on 24±7 % of the surface due to the large change in curvature. Partially measured loads through the facets was 10.5 ±1.1 N.ConclusionsThe relative displacement of the lumbar facet joints compared to the crosshead displacement was consistent with previous studies of cervical facet joints, despite the differences in anatomical geometry between cervical and lumbar joints. The difficulties in accurately measuring the load transfer through the facet joints was due to the age of the tissue and the degree of curvature of the facet joints. Synchronisation of the biomechanical data will provide a setup to assess the effect of interventions such as spinal fusion, with curvature-related issues unlikely to occur in human spines.Declaration of Interest(a) fully declare any financial or other potential conflict of interest

Measurements of stresses in β‐(Y,Yb)2Si2O7 environmental barrier coating layers using Raman spectroscopy

AbstractResidual stress measurements in environmental barrier coatings (EBCs) can help in understanding coating durability and potential damage mechanisms. We demonstrate the capability of Raman spectroscopy to measure average residual stresses in two different β‐RE2Si2O7 (RE = rare earth or Y3+, denoted as REDS) EBCs with a nominal (Yb,Y)2Si2O7 composition, focusing on macroscopic residual stresses acting at macroscopic length scales. Uniaxial compression measurements of dense β‐(Yb,Y)2Si2O7 ceramics are used for calibration curves for applied stress versus Raman peak shift. We use these calibration curves to evaluate the macroscopic thermoelastic residual stress in the (Yb,Y)2Si2O7 layers from coefficient of thermal expansion (CTE) mismatch of two different (Yb,Y)2Si2O7‐based EBCs on SiC‐based substrates. Microscopic stress contributions to Raman peak shifts are subtracted using reference free‐standing coatings and analytic estimates for inclusion stresses when (Yb,Y)2Si2O7 coatings have a high, variable volume fraction of (Yb,Y)2SiO5. The macroscopic thermal residual stress in these (Yb,Y)2Si2O7 EBCs is compressive, as expected from the smaller CTE of β‐REDS versus SiC. These thermal residual stresses can vary between different YbYDS EBC coatings by more than a factor of three with a measured layer residual stress of approximately –180 MPa (compressive) for a high modulus, low CTE coating, and our measured values generally agree with calculated estimates.

Properties of red mud blended magnesium phosphate cements: Workability and microstructure evolution

Alumina and iron oxide which constitute significant components of red mud can participate in the hydration reaction with phosphate. This paper partially replaced magnesia with red mud in the preparation of magnesium phosphate cement (MPC) and investigated the effects of red mud substitution on the performance of fresh and hardened properties of the MPC. The fresh properties of MPC were analyzed by measuring the setting time, fluidity, early hydration heat release and rheological properties, while the hardened mechanical properties were characterized by compressive strength measurement. The phase composition and micro-morphology were examined by XRD, SEM, EDS, and TG-DTA. The experimental results demonstrated that the incorporation of red mud prolonged the setting time, and postponed the occurrence of the peak temperature, and reduced the hydration reaction intensity. Regarding to the rheological properties, an increase in the dynamic yield stress was followed by a decline with gradually addition of red mud. Conversely, the plastic viscosity increased consistently. Concerning hardened properties, adding appropriate amount of red mud powders to MPC can significantly improve the compressive strength of hardened MPC mortars. The samples containing 15 % red mud yield the highest compressive strength, especially in the early strength, it was even more pronouncedly improved by 14.8 % comparing to the controlled samples at 3 h. Furthermore, detailed information about the modification effects of red mud on the MPC microstructure has been studied. The density of the MPC matrix was improved, microcracks and gaps appeared less, and some new hydrates could be determined, which is responsible for the improvement of the MPC’s mechanical properties.

Evaluating the strength properties of standing trees through fractometry

In recent years, significant advancements in non-destructive testing (NDT) methodologies have emerged, with applications spanning various domains, including structural wood quality assessment and planted tree characteristic evaluation. Within the context of planted trees, a range of non-destructive and semi-destructive techniques have been developed to assess the extent of degradation in tree trunks. In this study, various mechanical characteristics of brutian pine (Pinus brutia Ten.) trees near the Ertokuş Madrasah in the Atabey district of the province of Isparta are examined. Beside their historical significance, these trees are notable for the potential risk they present in terms of leaning towards the madrasah facade and the risk of falling over. To achieve the goals of research, the resistance characteristics of incremental cores were systematically determined by using a thermal imaging camera in conjunction with a portable, non-destructive testing device called a Fractometer. Totally 15 incremental auger specimens were obtained by extracting three increment core samples, each with a thickness of 5 mm, from the trunks of five distinct trees, all at a consistent height of 1.3 meters above ground level. Bending and compressive strength measurements were recorded at intervals of 6 mm from the core to the outermost layer. Furthermore, the moisture content of the incremental cores was assessed using thermal imaging technology. Following an analysis of the collected data, it was concluded that the mechanical properties of the investigated brutian pine trees within an acceptable range.

Automated operational modal analysis for civil engineering structures with compressed measurements

Introducing compressive sensing (CS) to modal analysis enables modal identification approaches to process compressed measurements, which enhances the efficiency in both data transmission and analysis for long-term monitoring of civil engineering structures. Nevertheless, the existing methods normally require users’ judgment in mode selection, and thus they cannot realize automated modal analysis. To bridge this gap, this study proposes an automated CS-based operational modal analysis (OMA) method, namely Automated Sparse Decomposition (ASD). A mode selection strategy is proposed to gradually eliminate noise and false modes and thus realize automated modal identification based on compressed measurements. A search strategy with both extensive and intensive search stages is proposed to realize higher frequency search resolution with low computational costs. Additionally, an automated mode shape identification process is designed to enhance accuracy. To demonstrate the effectiveness of the proposed method, experimental data on an offshore wind turbine model and real-world monitoring data from an in-service cable-stayed bridge are analyzed. The results show that the identification accuracy of the proposed ASD is comparable to state-of-art CS-based methods. Due to its superior performance in both efficiency and accuracy, the proposed method has the potential to become a promising online modal analysis tool.

Characteristics and Influence Factors of Natural Desorption in Coal Bodies from Fukang Mining Area, Xinjiang, China.

Coal body desorption characteristics are one of the key factors that influence the development of coalbed methane (CBM). In this study, 91 coal core samples from 11 CBM wells in the Fukang mining area were collected from Xinjiang, China, and the coal quality, high-pressure mercury compression, gas content, and natural desorption characteristics measurements were launched. With the detailed analyses of the differences in cumulative desorption volume, desorption ratio, and on-site average desorption rate for the coal samples with different body structures and macrolithotypes, the influence of the maximum reflectance of vitrinite, microscopic coal rock composition, and coal quality and pore characteristics on CBM desorption characteristics were discussed. The results showed that the cumulative desorption volume, desorption ratio, and desorption rate of cataclastic structure-bright coal are higher than those of primary structure-semibright coal. With the increase of RO,max and vitrinite content, the adsorption capacity of coal increases, and the increased methane concentration difference during desorption leads to an increase in cumulative desorption volume and on-site average desorption rate. The higher contents of moisture and ash yield would occupy the adsorption sites and hinder gas diffusion, which would decrease the desorption of coalbed methane. The greater porosity/pore volume ratio of medium and large pores can enhance the connectivity of pores, which increases the desorption ratio and the average desorption rate, while the higher micropore porosity/pore volume ratio can increase the gas adsorption space and the cumulative desorption volume. The pore characteristics have the most significant effect on the cumulative desorption volume and desorption ratio. The results of the study can help guide coal mine gas management and CBM development from middle-and low-rank coal reservoirs in Xinjiang.

Flexible deterministic compressive measurement matrix based on two finite fields

Flexible deterministic compressive measurement matrix based on two finite fields

Predicting Swell in Clay-Sand Mixtures Used in Liners

A method to predict the swellability of clay-sand mixtures is proposed. This model is a modified form of the Studds (1997) prediction model for clay-sand mixtures. The new proposed model uses the laboratory fall cone penetration technique to produce a characterization chart. This chart presents slope levels that can be used to obtain an equation for the final clay void ratio versus the vertical effective stress for clays. The porosity of the clay-sand mixtures was worked out based on a correction factor obtained from compression and porosity measurements in the laboratory. The porosity of the mixture was merged into the clay profile equation to compute the final clay void ratio at a specified stress level, which made it possible to predict the swelling behavior for different and variable stress levels. The swellability slope was obtained using fall cone tests conducted on the fine portion. Mixtures of kaolinite and bentonite were introduced to represent soils with different swell potentials. The fall cone measurements of a few points can be used to establish the swellability relationships for natural clay. Merging fall cone points with the swellability slope chart can define the profile of the vertical effective stress versus the clay void ratio.

Improving the Properties of Saline Soil Using a Deep Soil Mixing Technique

Saline soils belong to the category of problematic soils with high compressibility and weak shear strength when exposed to water. Water dissolves the salts in soils which are the primary cementing agents. Therefore, stabilization methods that provide sustainable cementing substances are employed in this study using deep soil mixing techniques to enhance the properties of saline soil. In this regard, a laboratory-scaled deep soil mixing procedure was developed to treat the soil in a way similar to the field methods. A binder, consisting of marble powder and cement, was employed to treat the soil. This study aimed to select the most efficient binder mix design in terms of optimum marble powder/cement ratio and optimum water/binder ratio. Unconfined compressive strength, durability, density measurements and ultrasonic velocity pulse tests were conducted on the treated soil. To determine the treatment efficacy, microstructure analysis of the treated samples was conducted. The 80C20MP and 70C30MP samples exhibit a dense soil structure with minimal voids, and their microstructure is denser than the other treated specimens. Additionally, the EDX analysis shows increased calcium percentages with up to 30% MP replacement, aligning well with the microstructure analysis and the UCS values. The results indicate that the economical and eco-friendly binder mix consisted of (70% to 80%) cement and (20% to 30%) marble powder with water/binder ratio in the range of 1.1 to 1.3. This mix contributed greatly to the improvement in soil strength and integrated columns.

In-situ micro-CT scanning and compressive strength assessment of diammonium hydrogen phosphate (DAP) treated chalk

The occurrence of wellbore mechanical failure is a consequence of the interaction among factors such as in situ stress, rock strength, and engineering procedures. The process of hydrocarbons production, causing reduction of pore pressure, alters the effective stresses in the vicinity of a borehole, leading to borehole instability issues. Estimating the rocks’ elastic modulus and compressive strength is essential to comprehend the rock matrix’s mechanical response during drilling and production operations. This study aimed to assess the practicality of Diammonium Hydrogen Phosphate (DAP) application as a chemical for strengthening chalk in hydrocarbon reservoirs, to make it resistant to high stresses and failure during drilling and production. The mechanical and physical properties of Austin chalk rock samples treated with DAP under mimicked reservoir conditions were studied. The results showed that DAP is a highly effective carbonate rock consolidating agent that improves the mechanical strength of the chalk. Compressive test measurements conducted on rocks treated at two different temperatures (ambient and 50 °C) showed that DAP effectively strengthened the rock matrix, resulting in an increase in its compressive strength (22–24%) and elastic modulus (up to 115%) compared to the untreated sample. The favorable outcomes of this research suggest that the DAP solution holds promise as a consolidation agent in hydrocarbon reservoirs. This contributes to the advancement of knowledge regarding effective strategies for mitigating mechanical failures of the wellbore during drilling and production.

Is the type and/or co-existence of degenerative spinal pathology associated with the occurrence of degenerative cervical myelopathy? A single centre retrospective analysis of individuals with MRI defined cervical cord compression

BackgroundDegenerative cervical myelopathy (DCM) arises from spinal degenerative changes injuring the cervical spinal cord. Most cord compression is incidental, referred to as asymptomatic spinal cord compression (ASCC). How and why ASCC differs from DCM is poorly understood. In this paper, we study a local cohort to identify specific types and groups of degenerative pathology more likely associated with DCM than ASCC. MethodsThis study was a retrospective cohort analysis (IRB Approval ID: PRN10455). The frequency of degenerative findings between those with ASCC and DCM patients were compared using network analysis, hierarchical clustering, and comparison to existing literature to identify potential subgroups in a local cohort (N = 155) with MRI-defined cervical spinal cord compression. Quantitative measures of spinal cord compression (MSCC and MCC) were used to confirm their relevance. ResultsELF (8.7 %, 95 % CI 3.8–13.6 % vs 35.7 %, 95 % CI 27.4–44.0 %) Congenital Stenosis (3.9 %, 95 % CI 0.6–7.3 % vs 25.0 %, 95 % CI 17.5–32.5 %), and OPLL (0.0 %, 95 % CI 0.0–0.0 % vs 3.6 %, 95 % CI 0.3–6.8 %) were more likely in patients with DCM. Comparative network analysis indicated loss of lordosis was associated with ASCC, whilst ELF with DCM. Hierarchical Cluster Analysis indicated four sub-groups: multi-level disc disease with ELF, single-level disc disease without loss of lordosis and OPLL with DCM, and single-level disc disease with loss of lordosis with ASCC. Quantitative measures of cord compression were higher in groups associated with DCM, but similar in patients with single-level disc disease and loss of lordosis. ConclusionsThis study identified four subgroups based on degenerative pathology requiring further investigation.