Spatial Pressure Distribution Research Articles

Wearable Pressure Sensors Based on MXene/Tissue Papers for Wireless Human Health Monitoring.

Though the widely available, low-cost, and disposable papers have been explored in flexible paper-based pressure sensors, it is still difficult for them to simultaneously achieve ultrahigh sensitivity, low limit and broad range of detection, and high-pressure resolution. Herein, we demonstrate a novel flexible paper-based pressure sensing platform that features the MXene-coated tissue paper (MTP) sandwiched between a polyimide encapsulation layer and a printing paper with interdigital electrodes. After replacing the polyimide with weighing paper in the MTP pressure sensor, the silver interdigital electrodes can be recycled through incineration. The resulting pressure sensor with polyimide or paper encapsulation exhibits a high sensitivity of 509.5 or 344.0 kPa-1, a low limit (∼1 Pa) and a broad range (100 kPa) of detection, and outstanding stability over 10 000 loading/unloading cycles. With ultrahigh sensitivity over a wide pressure range, the flexible pressure sensor can monitor various physiological signals and human movements. Configuring the pressure sensors into an array layout results in a smart artificial electronic skin to recognize the spatial pressure distribution. The flexible pressure sensor can also be integrated with signal processing and wireless communication modules on a face mask as a remote respiration monitoring system to wirelessly detect various respiration conditions and respiratory abnormalities for early self-identification of opioid overdose, pulmonary fibrosis, and other cardiopulmonary diseases.

Intra- and inter-rater reliability of compressed breast thickness, applied force, and pressure distribution in screening mammography

BackgroundEnsuring equivalent and reproducible breast compression between mammographic screening rounds is important for the diagnostic performance of mammography, yet the extent to which screening mammography positioning and compression is reproducible for the individual woman is unknown.PurposeTo investigate the intra- and inter-rater reliability of breast compression in screening mammography.Materials and MethodsEleven breast-healthy women participated in the study. Two experienced radiographers independently positioned and compressed the breasts of each participant in two projections—right craniocaudal and left mediolateral oblique—and at two time points. The spatial pressure distribution on the compressed breast was measured using a pressure sensor matrix. Applied force, compressed breast thickness, force in field of view, contact area, mean pressure, and center of mass (anterio-posterior and mediolateral axes) were measured. The reliabilities of the measures between the time points for each radiographer (intra-rater reliability) and between the radiographers (inter-rater reliability) were analyzed using the intraclass correlation coefficient (ICC).ResultsIntra- and inter-rater reliabilities from both projections demonstrated good to excellent ICCs (≥0.82) for compressed breast thickness, contact area, and anterio-posterior center of mass. The other measures produced ICCs that varied from poor (≤0.42) to excellent (≥0.93) between time points and between radiographers.ConclusionIntra- and inter-rater reliability of breast compression was consistently high for compressed breast thickness, contact area, and anterio-posterior center of mass but low for mediolateral center of mass and applied force. Further research is needed to establish objective and clinically useful parameters for the standardization of breast compression.

Array formation by ultrasound standing waves with solidification of liquid-suspended micro-particles

In the present article, ultrasound technology is proposed using the spatial periodic force distribution of radiation pressure. For applying ultrasound to the solidification of suspended microparticles, the details of a periodicity array of composite materials and its construction methodology are described. Suspended particles of polyethylene and silica with a concentration of less than 1.0 wt. % were used. A periodic arrangement of particles in distilled water using the ultrasound radiation pressure distribution was confirmed. A solidification process from liquid to solid under this periodic arrangement was also observed and was related to temperature. In the case of silica particles, the dendrites in primary ice crystals and their growth conditions were investigated. The ice crystals grew parallel to the periodically arranged particles.

Physics-constrained deep learning for solving seepage equation

With the development of deep learning algorithms, neural networks (NNs) have been widely used in physics, computer science, and other fields. Solving partial differential equations (PDEs) based on NNs is one of the research hotspots. The existing methods can be divided into two categories: one is data-driven method, and the other is physics-constrained method. Physical-constrained method is more popular due to the convenience of constructing NNs and excellent generalization ability. However, the physical-constrained method cannot ensure the solution precision when PDEs are more complex, such as seepage equations with source and sink terms. In this paper, an improved physics-constrained PDE solution method is proposed that incorporates potential features of the PDE in the loss functions. A gradient model is proposed to describe the potential feature based on spatial pressure distribution, which can be used as the additional signpost to guide NNs to approximate PDEs. The gradient models are described as special neurons that are added into the hidden layer of the NN. Based on the new ideas, the seepage equation is well solved without using any exact solutions. The effectiveness of the proposed method is verified by numerical simulation results based on PEBI grid. • An improved PDE solution method is proposed based on physics-constrained neural network. • A gradient model is proposed based on spatial distribution features to help signpost neural network (SNN) converge. • SNNs reduces the network parameters required to achieve the local minimum and improves the solution accuracy.

Evolution of Arctic Ocean surface circulation from 1958 to 2017

Arctic Ocean surface circulation plays an important role in the global ocean circulation system. In recent years, its position and velocity have been changing constantly, attracting increasing attention. The cause of this change, however, is still a matter of disagreement. In this paper, we use empirical orthogonal function analysis (EOF) to analyze the spatial and temporal distributions of sea level pressure (SLP), sea surface height (SSH) and sea surface temperature (SST) in the Arctic Ocean. We use the wavelet transform to obtain the periodic variation law governing Arctic Ocean surface circulation as well as to explore the relationship between the Arctic Oscillation (AO) and Arctic Ocean surface circulation. Our results show that the SSH of the Arctic Ocean exhibit a periodic variation with AO, in particular the sudden change seen from 1987 to 1992 coinciding with the trend of the AO index for the same period. When the AO index is positive, the Beaufort Gyre (BG) weakens and the source of transpolar drift (TPD) moves eastward, to the East Siberian Sea; when the AO index is negative, the BG accelerates and expands and the source of TPD moves to the New Siberian Islands. As a result, the direction and amplitude of the circulation change.

Full-Textile Human Motion Detection Systems Integrated by Facile Weaving with Hierarchical Core-Shell Piezoresistive Yarns.

The tremendous progress of the wearable intelligent system has brought an urgent demand for flexible pressure sensors, especially for those possessing high sensing performances, simple manufacture technology, and efficient integration. In this work, hierarchical core-shell piezoresistive yarns (HCPYs), which contain internal silver-plated nylon electrodes and surface microporous structured carbon nanotubes (CNTs)/thermoplastic polyurethane (TPU) sensing layer, are designed and manufactured via facile wet-spinning accompanied by a water vapor coagulating bath. The obtained HCPY can either be inserted into traditional textiles to assemble a single-pressure sensor, or be woven into a textile-based flexible pressure sensors array with expected size and resolution, without compromising their comfort, breathability, and three-dimensional (3D) conformability. Simultaneously, to further enhance the sensing performance, the surface microporous structures of HCPYs are optimized by altering the treatment humidity and exposure time during the process of water vapor-induced phase separation. The wearable pressure sensors assembled by the optimal HCPY achieved a high sensitivity up to 84.5 N-1, a good durability over 5000-cycle tests, a fast response time of 2.1 ms, and a recovery time of 2.4 ms. Moreover, the wearable pressure sensors have been successfully used to monitor physical signals and human motions. The textile-based flexible pressure sensors array has also been seamlessly integrated with sportswear to detect movements of the elbow joint and map spatial pressure distribution, which makes HCPY a promising candidate for constructing next-generation wearable electronics.

Flexible Ti3C2Tx MXene/PANI/Bacterial Cellulose Aerogel for e-Skins and Gas Sensing.

Flexible pressure sensors made of carbon materials have been used in electronic skins (e-skins), whose performance can be enhanced if composite sensing materials are used. Herein, an MXene/polyaniline/bacterial cellulose (MXene/PANI/BC) aerogel sensor has been fabricated through the self-assembly process between the MXene and one-dimensional active material. Combined with fewer-layer or single-layer MXenes, the as-fabricated aerogel could be used as the active layer of the pressure sensor, monitoring tiny motion signals of finger bending, wrist bending, and pulse beating. Bluetooth wireless transmission could also be realized to monitor the real-time spatial pressure distributions on the mobile phone, making the aerogel-based sensor an ideal candidate in e-skins. Meanwhile, the aerogel-based sensor is sensitive toward NH3 due to the unique three-dimensional (3D) structure of the aerogel and the abundant terminal groups (such as -O, -OH, and -F) of the MXene in the system that ensure efficient electronic transfer for the sensing process and create active sites for the absorption with the target gas. This work offers a versatile platform to develop MXenes to fabricate 3D composite aerogels for high-performance flexible multiple sensors.

Large-aperture experimental characterization of the acoustic field generated by a hovering unmanned aerial vehicle.

Unmanned aerial vehicles, specifically quadrotor drones, are increasingly commonplace in community and workplace settings and are often used for photography, cinematography, and small parcel transport. The presence of these flying robotic systems has a substantial impact on the surrounding environment. To better understand the ergonomic impacts of quadrotor drones, a quantitative description of their acoustic signature is needed. While previous efforts have presented detailed acoustic characterizations, there is a distinct lack of high spatial-fidelity investigations of the acoustic field of a quadrotor hovering under its own power. This work presents an experimental quantification of the spatial acoustic pressure distribution in the near-field of a live hovering unmanned aerial vehicle. A large-aperture scanning microphone array was constructed to measure sound pressure level at a total of 1728 points over a 2 m × 3 m × 1.5 m volume. A physics-infused machine learning model was fit to the data to better visualize and understand the experimental results. The experimental data and modeling presented in this work are intended to inform future design of experiments for quadrotor drone acoustics, provide quantitative information on the acoustic near-field signature, and demonstrate the utility of optical motion tracking coupled with a custom microphone array for characterization of live acoustic sources.

3D models of the dynamics of cancer cells under external pressure.

Skin cancer is one of the most frequent cancers worldwide. Recently, it has been shown that the tumor proliferation rate in skin and its dynamics can be changed by an osmotic pressure. However, these findings are rather unstructured. A weak pressure can slow down the tumor growth, while a very high pressure can, on the contrary, lead to accelerated growth and metastases. The magnitude and spatial distribution of osmotic pressures in tumors at present cannot be measured experimentally. Therefore, it is of particular interest to find appropriate models that would simulate the effects of additional osmotic pressures in skin and assess the features of its implementation. In this paper, we suggest an improved model based on the principles of the conventional hydrodynamic model for macrophase separations, which allows one to include not only the properties of healthy and cancer cells but also the microenvironment. We study and analyze the proliferation of cancer cells in 3D models of the epidermal layer of skin under an osmotic pressure. There are two suggested 3D models that are based on the same principles: (1) cellular cubic lattice and (2) cell spheroid. This allows expanding the application of the model depending on a given task. Here, we are focused on the study of melanoma at an early stage when there are not many cancer cells. Additional compressive and expansive pressures are added to the central part of the system. Both systems demonstrate similar results in slowing down the rate of tumor growth with a small pressure.

Pressure reconstruction of a planar turbulent flow field within a multiply-connected domain with arbitrary boundary shapes

Over the past two decades, it has been demonstrated that the instantaneous spatial pressure distribution in a turbulent flow field can be reconstructed from the pressure gradient field non-intrusively measured by Particle Image Velocimetry (PIV). Representative pressure reconstruction methods include the omnidirectional integration (Liu and Katz, 2006; Liu et al., 2016; Liu and Moreto, 2020), the Poisson equation approach (Violato et al., 2011; De Kat and Van Oudheusden, 2012), the least-square method (Jeon et al., 2015), and most recently, the adjoint-based sequential data assimilation method, which also essentially utilizes the Poisson equation to reconstruct the pressure(He et al., 2020). Most of these previous pressure reconstruction examples, however, were applied to simply-connected domains (Gluzman et al., 2017) only. None of these previous studies have discussed how to apply the pressure reconstruction procedures to a multiply-connected domain (Gluzman et al., 2017). To fill in this gap, this paper presents a detailed report for the first time documenting the implementation procedures and validation results for pressure reconstruction of a planar turbulent flow field within a multiply-connected domain that has arbitrary inner and outer boundary shapes. The pressure reconstruction algorithm used in the current study is the rotating parallelray omni-directional integration algorithm, which, as demonstrated in reference (Liu and Moreto, 2020) based on simply-connected flow domains, offers high-level of accuracy in the reconstructed pressure. While preserving the nature and advantage of the parallel ray omni-directional pressure reconstruction at places with flow data, the new implementation of the algorithm is capable of processing an arbitrary number of inner void areas with arbitrary boundary shapes. Validation of the multiply-connected domain pressure reconstruction code is conducted using the DNS (Direct Numerical Simulation) isotropic turbulence field available at the Johns Hopkins Turbulence Databases, with 1000 statistically independent pressure gradient field realizations embedded with random noise used to gauge the code performance. For further validation, the code is also applied for pressure reconstruction from the DNS pressure gradient in the ambient flow field of a shock-induced non-spherical bubble collapse in water (Johnsen and Colonius, 2009). The successful implementation of the parallel ray pressure reconstruction method to multiply-connected domains paves the way for a variety of important applications including, for example, experimental characterization of pressure field changes during the process of cavitation bubble inception, growth and collapse, non-intrusive unsteady aerodynamic force assessment for an arbitrary body shape immersed in flows, and multi-phase flow investigations, etc. In particular, as an immediate follow-up effort, the parallel ray pressure code will be used for the instantaneous pressure distribution reconstruction of the turbulent flow surrounding cavitation inception bubbles occurring on top of a cavity trailing corner based on high-speed PIV measurements.

МАТЕМАТИЧЕСКАЯ МОДЕЛЬ ГИДРОДИНАМИКИ КАСПИЙСКОГО МОРЯ С УЧЕТОМ ЛЬДА НА ЕГО ПОВЕРХНОСТИ

This article is devoted to the development and research of a mathematical model of water fluid dynamics with variable depth. This model describes the water flow movement, the thermodynamics of ice formation and melting, considers the Coriolis force, horizontal and vertical turbulence of the water environment, the complex geometry of the coastline and bottom, friction on the bottom and wind currents, evaporation, wind speed, and atmospheric density, and the deviation of the pressure field value from the hydrostatic approximation. The article describes the influence of the spatial distribution of temperature, salinity, ionic composition, and hydrostatic pressure on the processes of ice cover formation. The Caspian Sea-was chosen as the object of the simulation. The changes in the temperature and salinity distributions measured by the electrical conductivity of the water, considering the ionic composition of the Caspian Sea waters over a long-term period, are used as input data. Modeling the movement of water flow will allow you to respond to man-made threats in an accelerated time mode. The models of hydrodynamics presented in this paper can be adapted for other reservoirs using the appropriate geoinformation systems.

ЧИСЛЕННОЕ МОДЕЛИРОВАНИЕ ПРОЦЕССА РАЗЛОЖЕНИЯ ГАЗОГИДРАТА В ПОРИСТОЙ СРЕДЕ, ВЫЗВАННОГО СВЕРХВЫСОКОЧАСТОТНЫМ ЭЛЕКТРОМАГНИТНЫМ НАГРЕВОМ

Numerical studies are performed with the two-dimensional axisymmetric model of gas hydrate decomposition in porous media under the action of microwave heating. The system of equations describing the above process includes the mass balance equations of gas, water and hydrate phases, the energy balance equation, generalized Darcy’s law for water and gas, and the Kim–Bishnoi kinetics equation for hydrate decomposition reaction. The system of equations resolves itself into four differential equations relative to temperature, pressure, volume hydrate, water, and gas saturation with appropriate boundary and initial conditions. Simulation of gas hydrate decomposition in porous media under the action of microwave heating is carried out by finite element method. Physical parameters characteristic of a typical hydrate reservoir are used in the modeling. The reservoir was heated for ten days. Spatial and temporal distribution of temperature, pressure, hydrate, water, and gas saturation were obtained. The mass of gas evolved during hydrate dissociation was determined. The calculation of the energy efficiency of electromagnetic heating was carried out. These results are quite usable from a practical standpoint, and the electromagnetic heating method is technically achievable and competitive.

Pump-probe X-ray holographic imaging of laser-induced cavitation bubbles with femtosecond FEL pulses

Cavitation bubbles can be seeded from a plasma following optical breakdown, by focusing an intense laser in water. The fast dynamics are associated with extreme states of gas and liquid, especially in the nascent state. This offers a unique setting to probe water and water vapor far-from equilibrium. However, current optical techniques cannot quantify these early states due to contrast and resolution limitations. X-ray holography with single X-ray free-electron laser pulses has now enabled a quasi-instantaneous high resolution structural probe with contrast proportional to the electron density of the object. In this work, we demonstrate cone-beam holographic flash imaging of laser-induced cavitation bubbles in water with nanofocused X-ray free-electron laser pulses. We quantify the spatial and temporal pressure distribution of the shockwave surrounding the expanding cavitation bubble at time delays shortly after seeding and compare the results to numerical simulations.

A novel drying system – simultaneous use of ohmic heating with convectional air drying: System design and detailed examination using CFD

This paper introduces a novel drying system called ohmic assisted drying (OAD) – the simultaneous combination of ohmic heating and convectional air drying. The OAD system improved the drying characteristics of potato slices. Depending on the process conditions, drying time was shortened by 20–60% by OAD compared to conventional air-drying system. The level of applied voltage and air temperature were effective on drying time reduction. To achieve a better understanding of the changes in potato slices during OAD, a 3D mechanistic model was developed and validated with experimental moisture and temperature results. The model involves coupled heat, mass, momentum transfer as well as heat generation due to electrical current through the porous media. A non-conjugate, macroscopic, non-equilibrium modelling approach helps to define OAD process. Drying material (potato) consists of solid matrix, water, and gas phases, where pressure-driven flow, binary diffusion and phase change in drying volume were considered. The model predicts the spatial distribution of temperature, moisture, and pressure in the drying material. The prediction performance of the model is satisfactory especially in terms of moisture content since the standard error of estimate changes between 0.05 and 0.23. A deeper understanding is presented about the mechanisms of OAD highlighting strengths and weaknesses of the model and the drying system.

Numerical simulation of boiling liquid outflows process

  Computational algorithm was developed based on the well-known ANSYS Fluent  software package for studying unsteady wave outflow of a saturated liquid from high-pressure pipelines during emergency depressurization. The unsteady processes of the outflow of liquid, boiling as a result of depressurization of high-pressure vessels, have been investigated. The system of equations for the conservation of mass, momentum, and energy in a two-dimensional coordinate system is used in order to create mathematical model this process. The system of equations for the conservation of mass, momentum, and energy in a two-dimensional coordinate system is used to describe the initial stage of the unsteady outflow process. The features of the formation of jets of boiling liquid at various equilibrium initial states of water in a high-pressure vessel under conditions close to the experiments carried out by the authors [10] have been studied. The spatial distributions of pressure, temperature and velocity of the forming jet are obtained. Numerical results have shown that, over time, the character of the velocity distribution acquires a conical shape. With an increase in the initial temperature and pressure, this distribution is preserved, and the opening angle increases. The results are in qualitative agreement with the experimental data. &nbsp

Near-field spatial and temporal blast pressure distributions from non-spherical charges: Horizontally-aligned cylinders

Research into the characterisation of blast loading on structures following the detonation of a high explosive commonly assumes that the charge is spherical. This has the advantage of simplifying experimental, analytical and computational studies. In practice, however, designers of protective structures must often consider explosive threats which have other geometric forms, which has significant influence on the loading imparted to structures very close to the explosion source. Hitherto, there has been little definitive experimental investigation of the ‘near-field’ blast load parameters from non-spherical explosive charges and studies that have been conducted are usually confined to measurement of the total impulse imparted to a target. Currently, a detailed understanding of the development of loading on a target, necessary to fully inform the design process and appraise the efficacy of predictions from computational models, is lacking. This article, the first part of a wider investigation into these geometrical effects, details work conducted to address this deficiency. Results are presented from an experimental study of loading from detonations of cylindrical charges, set with the longitudinal axis parallel to an effectively rigid target, instrumented to facilitate the capture of the spatial and temporal evolution of the loading at different radial and angular offsets from the charge. These results are compared against loads from spherical charges and the effect of charge shape is identified. Significant differences are observed in the mechanisms and magnitude of loading from cylindrical and spherical charges, which is confirmed through the use of numerical analysis. The overall study provides insights which will assist the future design of effective protection systems.

All-Fabric Ultrathin Capacitive Sensor with High Pressure Sensitivity and Broad Detection Range for Electronic Skin.

Flexible pressure sensors have emerged as an indispensable part of wearable devices due to their application in physiological activity monitoring. To realize long-term on-body service, they are increasingly required for properties of conformability, air permeability, and durability. However, the enhancement of sensitivity remains a challenge for ultrathin capacitive sensors, particularly in the low-pressure region. Here, we introduced a highly sensitive and ultrathin capacitive pressure sensor based on a breathable all-fabric network with a micropatterned nanofiber dielectric layer, an all-fabric capacitive sensor (AFCS). This all-fabric network endows a series of exceptional performances, such as high sensitivity (8.31 kPa-1 under 1 kPa), ultralow detection limit (0.5 Pa), wide detection range (0.5 Pa to 80 kPa), and excellent robustness (10 000 dynamic cycles). Besides, the all-fabric structure provides other properties for the AFCS, e.g., high skin conformability, super thinness (dozens of micrometers), and exceptional air permeability. Our AFCS shows promising potential in breathing track, muscle activity detection, fingertip pressure monitoring, and spatial pressure distribution, paving way for comfortable skinlike epidermal electronics.

A roadmap towards quantitative cumulative impact assessments: Every step of the way

Currently most Cumulative Impacts Assessments (CIAs) are risk-based approaches that assess the potential impact of human activities and their pressures on the ecosystem thereby compromising the achievement of policy objectives. While some of these CIAs apply actual data (usually spatial distributions) they often have to rely on categorical scores based on expert judgement if they actually assess impact which is often expressed as a relative measure that is difficult to interpret in absolute terms. Here we present a first step-wise approach to conduct a fully quantitative CIA based on the selection and subsequent application of the best information available. This approach systematically disentangles risk into its exposure and effect components that can be quantified using known ecological information, e.g. spatial distribution of pressures or species, pressure-state relationships and population dynamics models with appropriate parametrisation, resulting in well-defined assessment endpoints that are meaningful and can be easily communicated to the recipients of advice. This approach requires that underlying assumptions and methodological considerations are made explicit and translated into a measure of confidence. This transparency helps to identify the possible data-handling or methodological decisions and shows the resulting improvement through its confidence assessment of the applied information and hence the resulting accuracy of the CIA.To illustrate this approach, we applied it in a North Sea CIA focussing on two sectors, i.e. fisheries and offshore windfarms, and how they impact the ecosystem and its components, i.e. seabirds, seabed habitats and marine mammals through various pressures. The results provide a “proof of concept” for this generic approach as well as rigorous definitions of several of the concepts often used as part of risk-based approaches, e.g. exposure, sensitivity, vulnerability, and how these can be estimated using actual data. As such this widens the scope for increasingly more quantitative CIAs using the best information available.

Synergy of Porous Structure and Microstructure in Piezoresistive Material for High-Performance and Flexible Pressure Sensors

A porous and microstructure piezoresistive material composed of polydimethylsiloxane (PDMS) and multiwalled carbon nanotubes (MWCNTs) was designed and prepared for a flexible and highly sensitive pressure sensor over a wide detection range. The microstructure was patterned on the surface of the partially cured PDMS/MWCNTs/NaCl mixture by imprinting a nonwoven fabric. After curing and dissolving the NaCl powders, the porous and surface microstructure PDMS/MWCNT film was obtained. Two PDMS/MWCNT films were stacked together and sandwiched between two copper foil electrodes, in which the two microstructure surfaces were in contact with the electrodes. Due to the synergistic effects of the combination of the porous structure and surface microstructure, the flexible sensor had highly sensitive response over a wide pressure range from 1 Pa to 100 kPa. Under the small pressure, the high sensitivity was achieved by the change in contact areas between the electrodes and the surface microstructures; at high pressure up to 100 kPa, the sensor retained its high sensitivity because of the porous structure of the piezoresistive PDMS/MWCNT material. Additionally, the sensor had fast response speed and good durability. The piezoresistive pressure sensors based on the porous and microstructure PDMS/MWCNTs were demonstrated in detection of sound, monitoring of human activities, and array mapping of the spatial pressure distribution.

Radiation force fields formed by a standing surface acoustic wave in a viscous liquid layer lying on an elastic half-space

The field of a surface acoustic wave in the system “viscous fluid layer—elastic substrate” is calculated taking into account the shear components in the fluid. On the basis of the dispersion equation, the velocity and attenuation of the surface wave are calculated. It is shown that for low-viscosity liquids the change in velocity is insignificant, but the shear components make the main contribution to the attenuation of the wave. The radiation pressure corresponding to a standing surface wave in a viscous fluid and acting on an element of its volume due to the nonlinearity of the equation of motion is calculated. It is shown that taking viscosity into account changes the spatial distribution of radiation pressure. In the presence of suspended particles in the liquid form, the attenuation of the wave causes an additional tendency to collect these particles in the center of the system. The shear components have significant radiation pressure gradients near the interface. They play a decisive role in the formation of ordered ensembles of particles at the last stage of the self-organization process. [The study was supported by the Russian Foundation for Basic Research under Project No. 20-02-00493-a.]