Wave Measurements Research Articles

The Effect Of Co2-Brine-Rock Interaction Towards Sand Onset Modeling In Dolomite-Rich Sandstone: A Case Study In Air Benakat Formation, South Sumatera, Indonesia

Carbon Capture Utilization Storage (CCUS) into geological storage (e.g., Enhanced Oil or Gas Recovery) provides a solution to reduce CO­2 emissions. However, it still remains a potential operational problem, such as sand problem phenomena in producer wells. This study observes the phenomenon of sand problems in production wells possibly triggered by CO2-brine-rock interactions on CO2 injection in rich dolomite sandstone reservoir. This research performs several experimental works (i.e., time-lapse dry mass measurements, X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM), and elastic wave measurements) by using CO2-brine-rock batch experimental setup as well as geochemical simulation to observe mineral dissolution, pore structures alteration as well as rock physics alteration due to CO2-brine-rock interactions. We used an outcrop sample of dolomite-rich sandstone from the Air Benakat Formation, South Sumatera, Indonesia. Our experimental and simulation works show that dolomite dissolution (dolomite reduction of ~4% after 14 soaking days), secondary porosity development (11% of visible porosity improvement), as well as rock strength reduction, occur indirectly (shown by elastic wave velocity, i.e. and reduction of ~3.8% and ~4.4%, respectively) due to CO2-brine-rock interactions. Subsequently, the results of elastic wave velocity measurements were then used to modify a considerable sand onset prediction (sand-free envelope) model. The modified model showed that the production well was more prone to sand problems due to CO2-brine-rock interactions. Thus, it is concluded that the sand onset prediction model with considering CO2-brine-rock interactions could help to design a better sand management strategy in producer wells.

Assessment of joint distributions of wave heights and periods

Short-term joint distributions of wave heights and periods provide information about the sea surface that is needed for engineering applications. In recent years much effort has been invested in predicting and validating the (univariate) distributions of wave heights; however, the same cannot be said about the joint probability of wave heights and periods. Comparisons of the joint distribution models with field observations are quite limited in terms of both the duration of the data and the number of locations considered. In addition, the often-contradicting demands for longer sea-state records and stationarity in the datasets have presented researchers with a bit of a conundrum. It is likely that some previous studies that aggregated data from several non-stationary sea states might have yielded improper inferences. The current study attempts a robust assessment of the available theoretical distribution models utilizing an extensive dataset of wave measurements around the UK coast. The results indicate that the Zhang and Guedes Soares (2106) model generally performs the best, and is perhaps a notable improvement over the somewhat bleak outlook laid out for these types of models in earlier years. The results also suggest that the discrepancy between the models and the data arises primarily from the poor ability of the marginal period distributions to capture reality.

Predicting wave run-up on vertical columns based on thermal stereography measurements

Accurate estimation of wave run-up is crucial for the design and safety of marine structures. To facilitate more precise and convenient predictions of wave run-up on vertical columns, including circular and square columns, many empirical formulas have been proposed. However, those derived from wave probe measurements typically underestimate the maximum wave run-up height due to the inability of wire-type wave gauges to closely adhere to the column surface. This study employed the non-contact wave measurement technology based on thermal stereography to measure the wave run-up distributions on vertical columns under regular waves, providing a more accurate measurements of wave run-up closer to the column surface. Utilizing the measurements, a modified formula was proposed to predict the wave run-up on circular columns. Additionally, considering the effects of scattering parameter (kD) and wave steepness (kηmax), a new empirical formula for predicting the wave run-up on square columns was developed based on the velocity stagnation head theory. These formulas were validated using the experimental data from the present study and the literature, demonstrating their ability to provide satisfactory wave run-up predictions. Furthermore, the spatiotemporal wave evolution for circular and square columns were compared. The wave profile in front of the circular cylinder at a half diameter tends to flatten, with water flowing along the cylinder surface to the sides, leading to a significantly lower wave run-up height ratio compared to the square column. This study provides the valuable insights for predicting the wave run-up on vertical columns, contributing to the design and safety assurance of marine structures.

In-line detection of salt formation during vitrification using millimeter wave radiometry and interferometry

Vitrification is an internationally significant industrial process used for the treatment and immobilization of hazardous and radioactive waste. For successful silicate melt vitrification, molten salt formation during melter operation must be avoided. As such, proper process controls and continuous monitoring are critical to minimizing melting problems. Several in-situ process technologies for glass melters are well-developed; however, the lack of in-situ surface salt formation detection methods presents a risk to vitrification at the Waste Treatment & Immobilization Plant (WTP) on the US Hanford Site. While proposed previously, millimeter wave (MMW) radiometry and interferometry are demonstrated for the first time for in-line detection of salt formation in simulated nuclear waste glass melts. The experimental radiometer and interferometer setup uses the optical properties of the melt and a dual receiver operating at ∼ 137 GHz to elucidate melting behavior. A series of previously characterized glasses supersaturated with sulfate (Na2SO4), chloride (NaCl), or fluoride (NaF) salts are analyzed using the MMW system. This provides insight into volatile losses, fining, salt formation, salt identity, crystallization, and optical properties of a heterogeneous melt. Relevant terahertz (MMW/THz) optical properties are also compiled. Millimeter wave measurements are evaluated here for the ability to detect phase changes in salt-forming glass melt compositions without opaque body radiometry assumptions. This contribution demonstrates MMW radiometry with interferometry as a useful method for in-situ salt detection, enabling risk reduction in nuclear waste vitrification melters.

A Generalized Ray Formulation For Wave-Optical Light Transport

Ray optics is the foundation of modern path tracing and sampling algorithms for computer graphics; crucially, it allows high-performance implementations based on ray tracing. However, many applications of interest in computer graphics and computational optics demand a more precise understanding of light: as waves. For example, accurately modelling scattering effects like diffraction or interference requires a model that provides the coherence of light waves arriving at surfaces. While recent work in Physical Light Transport [Steinberg et al. 2022; Steinberg and Yan 2021] has introduced such a model, it requires tracing light paths starting from the light sources, which is often less efficient than tracing them from the sensor, and does not allow the use of many effective importance sampling techniques. We introduce a new model for wave optical light transport that is based on the fact that sensors aggregate the measurement of many light waves when capturing an image. This allows us to compactly represent the statistics of light waves in a generalized ray. Generalized rays allow sampling light paths starting from the sensor and applying sophisticated path tracing sampling techniques while still accurately modelling the wave nature of light. Our model is computationally efficient and straightforward to add to an existing path tracer; this offers the prospect of wave optics becoming the foundation of most renderers in the future. Using our model, we show that it is possible to render complex scenes under wave optics with high performance, which has not been possible with any existing method.

Optimization of the method for determining the velocity of surface acoustic waves

The methodological aspects of measuring the velocity of Rayleigh surface waves are considered. The main attention is paid to the method for determining the change in surface wave velocity under the influence of certain factors on the object of study. The main sources of error in determining the change in surface acoustic wave velocity are discussed. The use of a transducer with rigidly connected elements for exciting and recording surface acoustic waves to determine the change in velocity is examined. A distinctive feature of such a transducer is the stable measurement base length, which eliminates the need for its determination during the measurement process. It is shown that the main sources of decreased surface acoustic wave measurement accuracy are the temperature instability of the measuring equipment and the transducer, as well as the instability of the acoustic contact layer between the transducer ele-ments and the object of study. The instability of the acoustic contact is caused by the uncertainty in the distribution of the coupling fluid between the transducer and the specimen during the bonding process, leading to changes in the acoustic signal propagation time. The source of temperature instability is random changes in the ambient temperature. Another source of such instability is the heating of equipment elements due to the release of heat when electrical and acoustic energy pass through them. This is particularly important for the transducer, where electrical energy is converted into acoustic energy, as a significant portion of it is transformed into heat. The magnitude of temperature instability arising from prolonged system operation, as well as the instability caused by the installation of the transducer on the object of study, is experimentally evaluated. The use of a reference sample to compensate for the temperature instability of the measurement system is considered. The possibility of using a measurement scheme with a reference sample to reduce temperature instability and the error caused by the instability of the acoustic contact between the transducer and the object of study is analyzed.

Anomalous Diffusion by Ocean Waves and Eddies

Understanding the dispersion of floating objects and ocean properties at the ocean surface is crucial for various applications, including oil spill management, debris tracking and search and rescue operations. While mesoscale turbulence has been recognized as a primary driver of dispersion, the role of submesoscale processes is poorly understood. This study investigates the largely unexplored mechanism of dispersion by refracted wave fields. In situ observations demonstrate significantly faster and distinct dispersion patterns for objects influenced by wind, waves and currents compared to those solely driven by ocean currents. Numerical simulations of wave fields refracted by ocean eddies corroborate these findings, revealing diffusivities that exceed those of turbulent diffusion at scales up to 10 km during energetic sea states. Our results highlight the importance of ocean waves in dispersing surface material, suggesting that refracted wave fields may play a significant role in submesoscale spreading. As atmospheric forcing at the ocean surface will only strengthen due to anthropogenic contributions, additional research into wave refraction is necessary. This requires concurrent high-resolution measurements of wind, waves and currents to inform the revisions of large-scale coupled models to better include the submesoscale physics.

Geosynthetic-stabilized aggregate: quantitative modulus evaluation via Bender Element

Geosynthetics, mainly geogrids and geotextiles, are commonly used to mechanically stabilize unbound aggregate layers in paved road applications. They provide lateral restraint to aggregates to initially increase the layer modulus during construction and minimize its time-dependent decrease under vehicular traffic loading. Different types of geosynthetics may provide different improvement mechanisms and stiffness enhancement levels. Quantitative evaluation of various stabilization geosynthetics is presented herein to compare modulus improvement trends and help incorporate geosynthetic benefits into state-of-the-art mechanistic-empirical (M-E) pavement design procedures. Five geogrids (three extruded, one woven, and one welded) and two geotextiles (one woven and one nonwoven) were studied with a dense graded aggregate in laboratory triaxial testing. Geosynthetics were placed at specimen mid-height and three pairs of Bender Element (BE) sensors were placed at various heights above the geosynthetic to collect shear waves and quantify the degree of mechanical stabilization during resilient modulus testing. While resilient moduli did not distinguish effectiveness of different geosynthetics, shear wave measurements could clearly show local stiffness increases achieved with geosynthetic inclusions. Meanwhile, trends observed in shear modulus profiles at various distances from the geosynthetic, when compared to that of control specimen, properly established the modulus enhancement level achieved in mechanical stabilization with geosynthetics.

Performance Characteristics of Newly Developed Real-Time Wave Measurement Buoy Using the Variometric Approach

Accurate measurement of ocean wave parameters is critical for applications including ocean modeling, coastal engineering, and disaster management. This article introduces a novel global navigation satellite system (GNSS) drifting buoy for surface wave measurements that addresses the challenges of performing real-time, high-precision measurements and realizing cost-effective large-scale deployment. Unlike traditional approaches, this buoy uses the kinematic extension of the variometric approach for displacement analysis stand-alone engine (Kin-VADASE) velocity measurement method, thus eliminating the need for additional high-precision measurement units and an expensive complement of satellite orbital products. Through testing in the South China Sea and Laoshan Bay, the results showed good consistency in significant wave height and main wave direction between the novel buoy and a Datawell DWR-G4, even under mild wind and wave conditions. However, wave mean period disparities were observed partially because of sampling frequency differences. To validate this idea, we used Joint North Sea Wave Project (Jonswap) spectral waves as input signals, the bias characteristics of the mean periods of the spectral calculations were compared under conditions of identical input signals and gradient-distributed wind speeds. Results showed an average difference of 0.28 s between the sampling frequencies of 1.28 Hz and 5 Hz. The consequence that high-frequency signals have considerable effects on the mean wave period calculations indicates the necessity of the buoy’s high-frequency operation mode. This GNSS drifting buoy offers a cost-effective, globally deployable solution for ocean wave measurement. Its potential for large-scale networked ocean wave observation makes it a valuable oceanic research and monitoring instrument.

Measuring nearshore waves at break point in 4D with Stereo-GoPro photogrammetry: A field comparison with multi-beam LiDAR and pressure sensors

Measuring nearshore waves remains technically challenging despite wave properties are being used in a variety of applications. With the promise of high-resolution and remotely-sensed measurements of water surfaces in four dimensions (spatially and temporally), stereo-photogrammetry applied to video imagery has grown as a viable solution over the last ten years. However, past deployments have essentially used costly cameras and optics, requiring fixed deployment platforms and hindering the applicability of the method in the field.Focusing on close-range measurements of nearshore waves at break point, this paper presents a detailed evaluation of a field-oriented and cost-effective stereo-video system composed of two GoProTM(Hero 7) cameras capable of collecting 12-megapixel imagery at 24 frames per second. The so-called ‘Stereo-GoPro’ system was deployed in the surf zone during energetic conditions at a macrotidal field site using a custom-assembled mobile tower. Deployed concurrently with stereo-video, a 16-beam LiDAR (Light Detection and Ranging) and two pressure sensors provided independent data to assess stereo-GoPro performance. All three methods were compared with respect to the evolution of the free-surface elevation over 25 min of recording at high tide and the wave parameters derived from spectral analysis. We show that stereo-GoPro allows producing digital elevation models (DEMs) of the water surface over large areas (250 m2) at high spatial resolution (0.2 m grid size), which was unsurpassed by the LiDAR. From instrument inter-comparisons at the location of the pressure transducers, free-surface elevation root-mean square errors of 0.11 m and 0.18 m were obtained respectively for LiDAR and stereo-GoPro. This translated into a maximum relative error of 3.9% and 12.5% on spectral wave parameters for LiDAR and stereo-GoPro, respectively. Optical distortion in imagery, which could not be completely corrected with calibration, was the main source of error. Whilst stereo-video processing workflow remains complex, cost-effective stereo-photogrammetry already opens new opportunities for deriving wave parameters in coastal regions, as well as for various other practical applications. Further tests should try to address specifically challenges associated to variable ambient conditions and acquisition configurations, affecting measurement performance, to guarantee a larger uptake of the technique.

A Novel Sea State Classification Scheme of the Global CFOSAT Wind and Wave Observations

AbstractOcean waves are essential elements across the air‐sea interface, regulating momentum and energy transfer. The mixture of wind sea and ocean swell coupled with surface winds results in diverse sea state conditions that modify the local air‐sea interaction. Previous classifications of wind waves and swells are mostly binary that are insufficient to represent the complexity of sea states. In this study, we utilize wind and wave measurements from the China‐France Oceanography Satellite (CFOSAT) to construct an observational wind‐wave ensemble. Four key parameters: wind speed, significant wave height, inverse wave age, and spectral width are selected out of six variables based on their correlations. Employing the unsupervised learning of k‐means clustering, global sea states are categorized into six distinct classes. These classes, characterized by unique centroids and separated in the feature space, represent specific wind regimes and degrees of wave development. Global occurrence highlights that each sea state is region‐specific, bridging the spatial gap of swell and wind sea dominated areas, respectively. This new grouping scheme complements the traditional wind sea and/or swell classification by resolving the diversity of wave regimes. The six‐class classification enables us to identify transitional states and hybrid conditions that may have been overlooked in the binary classification scheme, which shall help investigate the impact of ocean waves on the air‐sea interaction under varying sea states.

An Effective Water Depth Correction for Pressure-Based Wave Statistics on Rough Bathymetry

Abstract Near-bottom pressure sensors are widely used to measure surface gravity waves. Pressure spectra are usually converted to sea surface elevation spectra with a linear-theory transfer function assuming constant depth. This methodology has been validated over smooth sandy beaches but not over complex bathymetry of coral or rocky environments. Bottom-mounted pressure sensors collocated with wave buoys in 10–13-m water depth from a 5-week rocky shoreline experiment are used to quantify the error of pressure-based surface gravity wave statistics and develop correction methods. The rough bathymetry has O(1) m vertical variability on O(1–10) m horizontal scales, much shorter than the 90–40-m wavelength of sea band (0.1–0.2 Hz). For sensor stability, pressure sensors were deployed by divers in bathymetric lows. When using the local depth measured by the pressure sensor, significant wave height squared overestimates the direct wave buoy measurements (up to 21%) in the sea band. An effective depth hypothesis is proposed where a spatially averaged water depth provides more accurate wave height statistics than the local depth at the pressure sensor. An optimal depth correction, estimated by minimizing the wave height error, varies from 0.1 to 1.6 m. A bathymetry averaging scale of 13 m is found by minimizing the median bathymetry deviation relative to the optimal. The optimal and averaged bathymetry depth corrections are similar across locations and, using linear theory, significantly reduce wave statistical errors. Therefore, pressure-based wave measurements require a correction that depends on the spatially averaged bathymetry around the instrument. The larger errors when using the local depth suggest that approximately linear surface waves are not strongly modified by abrupt depth changes over O(1) m horizontal scales. Significance Statement The measurement of surface waves by bottom-mounted pressure sensors relies on wave theory formally derived for constant depth. We show that the constant depth assumption leads to systematic errors in wave statistics from observations over a rough, rocky bottom. By considering a spatially averaged bathymetry instead of the local water depth at the pressure sensor, the accuracy of wave energy density is improved, and upper-bound biases decay from 20% to 10%.

Influence of Ocean Currents on Wave Modeling and Satellite Observations: Insights From the One Ocean Expedition

AbstractThis study investigates the influence of ocean currents on wave modeling and satellite observations using in situ wave measurements from the One Ocean Expedition 2021–2023. In January 2023, six OpenMetBuoy drifters were deployed in the Agulhas Current region. Their high immersion ratio minimized wind effects, allowing them to follow the current and return to the Indian Ocean by the Agulhas retroflection, collecting data for about 2 months. Comparing surface current velocities from both the Mercator model and Globcurrent product with drifter data reveals underestimation for velocities over with Mercator showing greater variability. Significant wave height and Stokes drift parameters from MFWAM and ERA5 were also evaluated against drifters. Both models tend to overestimate Stokes drift more noticeable in ERA5, indicating sensitivity to wind seas. For significant wave height, both models agree well with drifter measurements with correlations of 0.90 for MFWAM and 0.83 for ERA5. However, ERA5's lack of surface current data combined with its coarse resolution (0.5) lead to underestimation of wave heights exceeding 2.5 m. MFWAM products including and excluding currents exhibit root mean square errors of 0.39 and 0.45 m, respectively, when compared to drifter measurements. This confirms that neglecting currents introduces additional errors particularly in areas with sharp current gradients. Analyzing MFWAM wave spectra, including and excluding currents, reveals wave energy transfer attributed to wave‐current interactions. The spatial extent of these interactions is captured by satellite altimeters, revealing wave modulations with considerable wave height variations when waves cross eddies and the current core.

Changes in physical activity and sedentary behavior during COVID-19 pandemic restrictions in Germany

Abstract Background During the COVID-19 pandemic’s first wave, mobility restrictions and protective measures have impacted both public and private life. In Germany, the population was advised to stay home except for work, outdoor sport activities, and essential shopping. This study aims to evaluate how these measures affected physical activity and sedentary behavior, focusing on identifying the groups most affected. Methods In April and May 2020, we distributed a COVID-19-specific questionnaire to participants of the German National Cohort (NAKO). The questionnaire was specifically designed to assess changes in physical activity and sedentary behavior compared to pre-restriction levels, along with data on anxiety and depressive symptoms. Results Around 26 % of the 152,421 respondents reported increased sedentary time, and about 38 % reported reduced participation in sport activities compared to pre-restriction levels. Over one-third of those who previously met the WHO’s physical activity recommendation could not maintain it during the restrictions. There was also a notable decline in active transportation (M = - 0.12; 95% CI: -.126; -.117), whereas participants spent more time on recreational physical activities (M = 0.12; 95% CI: .117; .126). Based on multivariable linear and log-binomial regression models, we found that younger people were more affected by the restrictions than older adults. Factors such as transitioning to remote work, self-rated health, and depressive symptoms strongly correlated with changes in all physical activity domains, including sedentary behavior and adherence to physical activity guidelines. Conclusions The shift towards inactivity or low-intensity activities during the nationwide restrictions poses potential long-term health risks, highlighting the urgent need for public health policies to address the negative impact of COVID-19 restrictions on physical activity and sedentary behavior.

A third kind of episodic memory: Context familiarity is distinct from item familiarity and recollection.

Memory for past events is widely believed to operate through two different processes: one called 'recollection' when retrieving confident, specific details of a memory, and another called 'familiarity' when only having an unsure but conscious awareness that an item was experienced before. When people successfully retrieve details such as the source or context of a prior event, it has been assumed to reflect recollection. We demonstrate that familiarity of context is functionally distinct from familiarity of items and recollection and offer a new, tri-component model of memory. The three memory responses were differentiated across multiple behavioral and brain wave measures. What has traditionally been thought to be two kinds of memory processes are actually three, becoming evident when using sensitive enough multi-measures. Results are independently replicated across studies from different labs. These data reveal that context familiarity is a third process of human episodic memory.

Soil moisture estimation in the unsaturated zone using surface wave measurements and hybrid modeling framework

Abstract Soil moisture plays a critical role in influencing various facets of ecosystem dynamics. The preference for measuring soil moisture without physical intrusion has been desirable for precise assessments while minimizing disruptions to soil structural, hydraulic, and biological characteristics. In this study, we explored the potential of surface elastic waves as a proxy to estimate soil moisture profiles to a depth of 1.05 m at intervals of 0.1 m. We conducted a multichannel analysis of surface waves (MASW) survey and measured soil moisture at depths of 0.15 m and 0.35 m. To address the limited availability of soil moisture measurements, we developed a mechanistic soil moisture model as a substitute for measured soil moisture profiles. Our results showed that as soil moisture increased, the propagation of surface waves became more pronounced due to reduced frictional resistance. However, it was not straightforward to link measured surface wave responses and subsurface soil moisture profile. To address these challenges, we developed a convolutional neural network (CNN) with the inputs of the frequency-velocity and frequency-wavenumber images obtained from the measured surface waves. We found that the integration of MASW and CNN proved effective in estimating soil moisture profiles to a depth of 1.05 m at intervals of 0.1 m without causing disturbances to the soil (MAE = 0.0035 m3 m−3). This study suggested that the combined use of surface waves and CNN hold promise in measuring soil moisture profiles without physical disruptions. As such, the proposed approach could serve as a viable alternative to noninvasive soil moisture sensors.

Targeting the high frequency tail of wave spectra for energy harvesting in marine sensor networks

While the conventional philosophy of wave energy conversion is to target the large amounts of power in the peak of the input wave spectrum, this study proposes that for the application of powering marine sensor networks (MSNs), it is advantageous to target the high frequency tail of the wave spectrum. This strategy is predicated on two primary advantages: the spatial and temporal persistence of the wave energy resource in the high-frequency region and its compatibility with the resonance characteristics of smaller MSN devices. To identify the optimal frequency range for energy harvesting, we conducted a detailed analysis of wave spectra across multiple coastal locations. This involved calculating and comparing the power spectra at different frequencies, using data from long-term wave measurements. The high-frequency tail was defined by determining the frequency above which the energy content showed consistent temporal and spatial stability across all study sites. The quantification of available power was achieved by integrating the wave power spectrum over the identified frequency range. Our case study, focusing on the coast of Queensland, Australia, reveals that frequencies above 2.5 rad/s consistently offer a stable and persistent energy resource. The available power in this range is quantified, totalling an average of 60 W/m, with additional analysis provided within narrower sub-bandwidths to address the inherent narrow-bandedness of wave energy harvesters. This research provides critical insights for the design of efficient wave energy harvesters tailored to the needs of diverse marine environments.

Magnetospheric Line Radiation: Temporal Modulation Corresponding to a Bouncing Wave

AbstractMagnetospheric line radiation (MLR) is a peculiar type of whistler‐mode emissions formed by several similarly spaced spectral lines, whose frequencies may vary with time. These emissions typically occur at frequencies between about 1 and 8 kHz and are observed in both ground‐based and satellite measurements. However, their origin and source locations are not yet understood, as their detection by spacecraft instruments is challenging due to the limited frequency resolution of onboard wave measurements. We use high‐resolution multicomponent wave data obtained by the Van Allen Probes to demonstrate that, in addition to the frequency modulation, MLR events possess a temporal modulation with periods on the order of seconds, which may be related to the wave bouncing between hemispheres. Observed modulation periods are used to estimate a tentative source L‐shell. The modulation periods are shorter for events with larger frequency spacing, and the estimated source L‐shells correlate with model plasmapause locations.

Kalman-based estimation of loading conditions from ultrasonic guided wave measurements

Abstract Ultrasonic guided wave-based structural health monitoring (SHM) of structures can be perturbed by environmental and operations conditions (EOCs) that alter wave propagation. In this work, we present an estimation procedure to reconstruct an EOC-free baseline of the structure from the only available Ultrasonic guided wave measurements. This procedure could typically be used as a prior step to increase the robustness of a more general ultrasonic imaging algorithm or SHM process dedicated to flaw detection. Our approach is model-based, i.e. we use a precise modeling of the wave propagation altered by structure loading conditions. This model is coupled with the acquired data through a data assimilation procedure to estimate the deformation caused by the unknown loading conditions. From a methodological point of view, our approach is original since we have proposed an iterated reduced-order unscented Kalman strategy, which we justify as an alternative to a Levenberg–Marquardt strategy for minimizing the non quadratic least-squares estimation criteria. Therefore, from a data assimilation perspective, we provide a quasi-sequential strategy that can valuably replace more classical variational approaches. Indeed, our resulting algorithm proves to be computationally very effective, allowing us to successfully apply our strategy to realistic 3D industrial SHM configurations.

Joint measurement of cosmic-ray muons and seismic waves at laboratory scale

SUMMARY Current geophysical exploration methods face challenges in accurately determining gas saturation levels and elastic constants with adequate spatial resolution. Seismic wave velocity is a critical physical property in these techniques, but it introduces uncertainties because of its composite nature involving density and two elastic constants (e.g. bulk and shear modulus), which exhibit a trade-off relationship. We propose a novel approach that integrates cosmic-ray muon detection with seismic exploration to independently resolve P- and S-wave velocities into their constituent elastic constants and densities. First, we utilized a fluid substitution approach based on Gassmann's model to illustrate the benefits of incorporating density information in predicting gas saturation levels in pores. This supports the advantage of decomposing seismic wave velocity into density and two elastic constants. Second, to validate the applicability and performance of the proposed method, which involves separating seismic wave velocity into density and two types of elastic constants, muon and ultrasonic data were collected in laboratory experiments on two different targets: an acrylic block and an aluminium block. Upon muon observation, a relationship is established to convert muon flux into density length, considering the characteristics of the building housing the laboratory and the direction of muon arrival at specific positions within the building. Although there is potential for enhancing the accuracy of the derived physical properties such as density, bulk modulus, and shear modulus, the feasibility of this method has been successfully demonstrated at the laboratory scale.