Simple Physical Model Research Articles

On the robust experimental multi-degree-of-freedom identification of bolted joints using frequency-based substructuring

Modeling joint dynamics is the bottleneck for precise predictive models of machines. Bolted joints are especially relevant due to their common use in mechanical engineering. Stiffness and damping properties of bolted joints are highly influenced by contact parameters (geometry, surface treatment, preload, …). For high amplitude vibrations, when non-appropriate joint closure is present, even frictional effects can play a role.Substructuring techniques offer a lean solution for isolating dynamical or quasi-static components of joint dynamics. It may be used for an identification of linearized contact parameters for multiple degrees of freedom (dofs). The main limitation of the method is finding a robust workflow to guarantee a proper controllability and observability of the desired joint dynamics, as well as dealing with disturbance/noise in the measurements.In this contribution a robust procedure for the identification of a bolted joint using frequency-based substructuring is presented for a contact in an experimental scenario. The dynamics of the joint are isolated from the assembled system using different substructuring techniques treating the joint as a quasi-static or dynamic component. A simple physical model of the joint is parametrized from the experimental joint dynamics. A validation of the methodology is given by using the identified joint parameters on a modified assembled system.

Increasing Volumetric Capacity Diminishes Rate Performance in Li-Ion Battery Electrodes

Combining high-capacity electrodes with good rate performance is essential for maximising both energy and power density in Li-ion batteries. While much effort has been dedicated to increasing both capacity and rate performance, little consideration has been made as to how an increase in specific or volumetric capacity might directly affect rate performance. Here, we quantitatively examine the relationship between the volumetric capacity of Li-storing electrodes and their rate performance using graphite/boron-nitride composite electrodes with a range of compositions as a model system. The rate performance of these cells is evaluated by fitting capacity vs rate curves to a semi-empirical equation and extracting a characteristic charge/discharge time. As graphite content and so electrode capacity are increased, we observe a linear, threefold increase of this characteristic time, representing a significant degradation in rate performance. This shows that capacity and rate performance are anti-correlated, an observation is consistent with the predictions of a simple physical model which shows this effect to be associated with the RC charging time of the electrode. Using no adjustable parameters, we find excellent agreement between the model and our experimental data.

A simultaneous Eigen valued expression to model the three coupled electronic states with triply and doubly degenerate seams together I

AbstractThe accurate modeling of triply and doubly degenerate seam together while computing the coupled multiple potential energy surfaces globally remains a challenging task due to the unavailability of a suitable model function taking care of this aspect. In this paper, we present such a function capable of predicting many‐fold electronic degeneracies simultaneously as well as the features found away from the vicinity of such degeneracies if present in the coupled surfaces disregarding the symmetry requirements. The basis of the proposed model comes from the analytical diagonalization of a real valued diagonally symmetric diabatic matrix and thus, the resulting three symbolic Eigen valued functions form the basis of model to be used in this work. From the analytical model, an attempt was made to provide an analytical expression for the adiabatic‐diabatic transformation angle. Few applications were considered starting from the simple physical model systems to actual realistic molecule illustrating how the present model function are being applied to them to show the presence of degeneracies among the three electronic states.

Physics-Informed Guided Disentanglement Ingenerativenetworks.

Image-to-image translation (i2i) networks suffer from entanglement effects in presence of physics-related phenomena in target domain (such as occlusions, fog, etc), lowering altogether the translation quality, controllability and variability. In this paper, we propose a general framework to disentangle visual traits in target images. Primarily, we build upon collection of simple physics models, guiding the disentanglement with a physical model that renders some of the target traits, and learning the remaining ones. Because physics allows explicit and interpretable outputs, our physical models (optimally regressed on target) allows generating unseen scenarios in a controllable manner. Secondarily, we show the versatility of our framework to neural-guided disentanglement where a generative network is used in place of a physical model in case the latter is not directly accessible. Altogether, we introduce three strategies of disentanglement being guided from either a fully differentiable physics model, a (partially) non-differentiable physics model, or a neural network. The results show our disentanglement strategies dramatically increase performances qualitatively and quantitatively in several challenging scenarios for image translation.

Underwater Image Enhancement Method Based on Improved GAN and Physical Model

Underwater vision technology is of great significance in marine investigation. However, the complex underwater environment leads to some problems, such as color deviation and high noise. Therefore, underwater image enhancement has been a focus of the research community. In this paper, a new underwater image enhancement method is proposed based on a generative adversarial network (GAN). We embedded the channel attention mechanism into U-Net to improve the feature utilization performance of the network and used the generator to estimate the parameters of the simplified underwater physical model. At the same time, the adversarial loss, the perceptual loss, and the global loss were fused to train the model. The effectiveness of the proposed method was verified by using four image evaluation metrics on two publicly available underwater image datasets. In addition, we compared the proposed method with some advanced underwater image enhancement algorithms under the same experimental conditions. The experimental results showed that the proposed method demonstrated superiority in terms of image color correction and image noise suppression. In addition, the proposed method was competitive in real-time processing speed.

Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS

Abstract. In remote sensing applications, clouds are generally characterized by two properties: cloud optical thickness (COT) and effective radius of water–ice particles (Reff), as well as additionally by geometric properties when specific information is available. Most of the current operational passive remote sensing algorithms use a mono-angular bispectral method to retrieve COT and Reff. They are based on pre-computed lookup tables while assuming a homogeneous plane-parallel cloud layer. In this work, we use the formalism of the optimal estimation method, applied to airborne near-infrared high-resolution multi-angular measurements, to retrieve COT and Reff as well as the corresponding uncertainties related to the measurement errors, the non-retrieved parameters, and the cloud model assumptions. The measurements used were acquired by the airborne radiometer OSIRIS (Observing System Including PolaRization in the Solar Infrared Spectrum), developed by the Laboratoire d'Optique Atmosphérique. It provides multi-angular measurements at a resolution of tens of meters, which is very suitable for refining our knowledge of cloud properties and their high spatial variability. OSIRIS is based on the POLDER (POlarization and Directionality of the Earth's Reflectances) concept as a prototype of the future 3MI (Multi-viewing Multi-channel Multi-polarization Imager) planned to be launched on the EUMETSAT-ESA MetOp-SG platform in 2024. The approach used allows the exploitation of all the angular information available for each pixel to overcome the radiance angular effects. More consistent cloud properties with lower uncertainty compared to operational mono-directional retrieval methods (traditional bispectral method) are then obtained. The framework of the optimal estimation method also provides the possibility to estimate uncertainties of different sources. Three types of errors were evaluated: (1) errors related to measurement uncertainties, which reach 6 % and 12 % for COT and Reff, respectively, (2) errors related to an incorrect estimation of the ancillary data that remain below 0.5 %, and (3) errors related to the simplified cloud physical model assuming independent pixel approximation. We show that not considering the in-cloud heterogeneous vertical profiles and the 3D radiative transfer effects leads to an average uncertainty of 5 % and 4 % for COT and 13 % and 9 % for Reff.

Strong signature of one-loop self-energy in polarization resolved nonlinear Compton scattering

The polarization dynamics of electrons including multiple nonlinear Compton scattering during the interaction of a circularly polarized ultraintense laser pulse with a counterpropagating ultrarelativistic electron beam is investigated. While electron polarization emerges mostly due to spin-flips at photon emissions, there is a nonradiative contribution to the polarization which stems from the one-loop QED radiative corrections to the self-energy, which admits of a simple physical model. We put forward a method to single out the nonradiative contribution to the polarization, employing the reflection regime of the interaction when the radiation reaction is significant. The polarization of electrons that penetrate in the forward direction through a colliding laser is shown to be dominated by the loop effect, while the reflected electrons are mostly polarized by spin-flips at photon emissions. We confirm this effect by quantum Monte Carlo simulations considering the helicity transfer from the laser field to the electrons, taking into account the opposite sign of the polarizations induced by the nonradiative loop effect and radiative spin-flip. Our Monte Carlo simulations show a polarization signal as high as $\ensuremath{\gtrsim}10%$ from the nonradiative effect, amenable for experimental detection with current technology.

Spatial patterns of exposure to sediment-laden flows on an experimental alluvial fan

Sediment-laden flows with significant amounts of large wood can impact alluvial fans and seriously damage infrastructure and property which makes a profound knowledge of exposure an essential requisite for risk mitigation. To investigate its spatial variability, we executed experiments on a simplified physical model and assessed the observed spatial process and exposure patterns by quantifying synthetic indexes and geostatistically analysing spatial probabilities. We systematically varied the loading conditions, i.e. total flow volume, solid fraction and the tank opening controlling water release, and repeated each experimental configuration eight times. Two alluvial fan layouts were considered, one equipped with a guiding channel and a bridge and one with a guiding channel only. First, we tested the hypothesis, that water released though the fully opened tank outflow valve induces a sediment-laden flow which is associated with higher exposure and lower spatial uncertainty of exposure if compared to flows generated by a half-opened tank outflow valve. Second, we tested whether a higher flow volume is associated with higher exposure on the alluvial fan and with lower spatial uncertainty. It turned out that neither of the aforementioned hypotheses is verified for the whole set of tested flow conditions. The first hypothesis is rejected in the majority of the considered conditions. The second hypothesis is prevailingly corroborated when the exposed areas due to both sediment and water were considered. Instead, when only the areas of sediment deposition are considered, this hypothesis is prevailingly corroborated on the alluvial fan featuring the presence of the bridge. We provided exposure probability maps for all experimental conditions and presented the variability of exposure by standard deviation ellipses. Although solely indicative for the adopted alluvial fan layouts, a variation of the loading parameters led to remarkable changes in the patterns of exposure probability and the parameters of the standard deviation ellipses. Our results urge decision makers to fully acknowledge the potential variability of geomorphic responses on alluvial fans in their risk management practices as to avoid underestimating the impacts for the built environment.

Optimization of Nanofluid Flow and Temperature Uniformity in the Spectral Beam Splitting Module of PV/T System

The mass fraction of 0.01 wt% ZnO nanofluid was prepared via the two-step method. The measurement verifies that ZnO nanofluids have better transmission characteristics in the frequency division window range of 400–1200 nm. At the same time, it has good absorption characteristics in ultraviolet and near-infrared bands, which meets the application conditions of the spectral beam-splitting module of the PV/T system. A spectral beam-splitting module of the PV/T system was designed. The simplified physical model was established in ANSYS 14.0. The flow field and convective heat transfer were simulated for different arrangements of the interlayer inlet to obtain a more ideal and uniform temperature distribution to improve the system’s comprehensive efficiency. The results show that the fluid flow in the interlayer under case II is more uniform, and the temperature field distribution is better than other arrangements. Hence, this work could provide a reference for optimising nanofluid flow within a spectral beam-splitting module.

Stress sensitivity of elastic moduli in high-porosity cemented sandstone — Heuristic models and experimental data

Quantitative description of the reservoir rock stress sensitivity is critical for seismic modeling and interpretation. Laboratory studies have indicated that the wave velocity of high porosity cemented sandstone is asymmetrically much more sensitive to stress unloading than stress loading. However, there is a lack of a simple rock physics model that is capable of describing the asymmetric stress sensitivity of reservoir rock. A new rock physics model is developed by extending an existing rock physics model based on contact theory combined with elastic bounds. The new model relates the stress softening of rock to cement cracking and crumbling induced by stress release. The diluting factor is introduced to describe the weakening of effective cement and analyze the increase of stress sensitivity when the stress is gradually removed. The combination of the new model and its base model forms a rock physics modeling workflow that can accurately describe the evolution of velocities measured in samples undergoing stress loading and unloading. The model performance is compared with samples representing synthetic weakly cemented glass bead pack and sandstone manufactured with different cements at different forming stress levels. The modeling results are in accordance with the measured stress sensitivities of wave velocities. The sequential model calibration using a simple constraint optimization approach yields important calibration parameters that are indicative of the elastic stress sensitivity and damage behavior in the studied rocks. The model can be particularly interesting for time-lapse monitoring of fluid injection and seismic interpretation of overpressured reservoir rock.

Validating the effect of fuel moisture content by a multivalued operator in a simplified physical fire spread model

Validating the effect of fuel moisture content by a multivalued operator in a simplified physical fire spread model

Thermally Switchable Nanogate Based on Polymer Phase Transition.

Mimicking and extending the gating properties of biological pores is of paramount interest for the fabrication of membranes that could be used in filtration or drug processing. Here, we build a selective and switchable nanopore for macromolecular cargo transport. Our approach exploits polymer graftings within artificial nanopores to control the translocation of biomolecules. To measure transport at the scale of individual biomolecules, we use fluorescence microscopy with a zero-mode waveguide set up. We show that grafting polymers that exhibit a lower critical solution temperature creates a toggle switch between an open and closed state of the nanopore depending on the temperature. We demonstrate tight control over the transport of DNA and viral capsids with a sharp transition (∼1 °C) and present a simple physical model that predicts key features of this transition. Our approach provides the potential for controllable and responsive nanopores in a range of applications.

Thermomechanical Modeling of Aircraft Tire–Runway Contact for Transient Maneuvers

ABSTRACT The aircraft tire is the link between the aircraft and the runway and transmits forces and moments within the contact area. During ground maneuvers, the tire is exposed to a wide range of operating conditions. The tires support the weight of the aircraft, they ensure safe rolling during taxiing, and they transfer the required forces to the runway during takeoff and landing. Temperature development during these maneuvers is of great importance because temperature can affect both material stiffness and friction behavior as well as wear characteristics. Heat is generated inside the tire due to energy dissipation caused by the cyclic loading of the tire during rolling. In addition, heat is generated due to friction in the tire–runway contact. Experimental measurements of the temperature distribution in the entire tire are not yet possible. The tire temperatures can only be determined at selected critical spots. Simulation models can help to obtain a better understanding of the overall tire temperature distribution during transient maneuvers. In this work, the transient thermomechanical processes of a rolling aircraft tire, e.g., directly following the touchdown process or during taxiing, are modeled based on a simple physical tire model. An extended brush model is used to simulate the contact forces. The tire temperature is determined via the transient heat conduction equation in radial and circumferential directions. The mechanical and thermal models are coupled via the coefficient of friction and the sliding velocities in contact. The free model parameters are parameterized using experimental data, and the overall model is validated by measurements on the whole tire. The validated thermomechanical tire model is used for simulations or the analysis of different driving maneuvers to get a better understanding of the temperature development in the aircraft tire.

Snowmelt detection in Greenland ice sheet based on AMSR2 89GHz

The snowmelt on the surface of the Greenland ice sheet can show the climate change in the Arctic. In order to obtain high spatial resolution and high precision results for snowmelt detection on the polar ice sheet surface, a method of snowmelt detection based on an Advanced Microwave Scanning Radiometer-2 (AMSR-2) 89GHz channel is presented. Firstly, the stable relationship between the polarization ratio of 89GHz data and 36GHz data under clear and cloudless weather conditions is used to screen out the 89GHz data that is not affected by external factors such as clouds and water vapor. Then, the Nobuyuki Otsu (Otsu) method is used to obtain the freeze-thaw threshold, and the snowmelt detection results of the ice sheet surface are obtained from the unaffected data by cloud conditions. The areas affected by cloud cover are replaced by the snowmelt detection results of the ice sheet surface from the gradient ratio (GR) model based on 19GHz and 37GHz horizontal polarization data. Finally, we get the snowmelt detection results of the Greenland ice sheet surface. To verify the feasibility and rationality of the proposed method, the results are compared with those of the cross-polarized gradient ratio algorithm (XPGR) and the simple physical model algorithm. The snowmelt area obtained by our method is between the XPGR and the simple physical model, and the snowmelt trend of our method and the simple physical model algorithm is closer. Then the results of the three algorithms are compared and analyzed with the temperature data from the automatic weather stations showing that the results obtained by our method are closer to the measurement data.

A reduced-order modeling of a tubular solar reactor for long duration thermochemical energy storage

The storage of solar energy in a solid form, referred to as a “solar fuel”, can be achieved through a process known as endothermic solar thermochemistry. This process transforms the absorbed solar energy into a stable and retrievable form that can be stored for extended periods of time. This paper presents a low–order heat transfer model of a counter–current tubular falling bed reactor designed to produce thermally reduced magnesium manganese oxide pellets for long duration thermochemical energy storage. The energy required for the endothermic reduction was supplied by concentrated solar energy or renewable electricity via indirect heating of the gas and solid reactants flowing in a ceramic tube. The counter-current gas flow enhances the mixing of the solid particles with the heat recuperation zone, allowing the gas and particles to enter and exit the tubular reactor close to room temperature. The reactor was vertically oriented and was heated circumferentially by an adjustable level heat flux along a finite segment of its length. The temperature distribution of the reactor in response to transient changes along the tube was modeled by considering conduction, convection, and radiation heat transfer. Governing equations for the heat transfer model were solved by discretizing the reactor tube into a finite number of control volumes and using an energy balance for the heat exchange between the reactor wall, gas, and particles within the control volume. The energy absorbed during this endothermic reaction was modeled numerically by fitting the data of the chemical conversion rate with the corresponding temperature of particles in the heating zone. The numerical model has been experimentally validated using a reactor prototype made of a 121.92 cm alumina tube heated by a 7 kW electric tube–furnace. The alumina tube receives magnesium manganese oxide pellets of 3.66 ± 0.516 mm in diameter from the top, and a counter–current gas flow from the bottom. The reactor wall temperature was monitored by six thermocouples installed along the reactor tube length. The experimental procedure was numerically simulated, and the temperature variation along the reactor tube was compared with a matrix of experimental runs for a range of particles mass flowrates (0.75–1.25 g/s) and corresponding gas flowrates (36–65 SLPM). The reactor system was heated gradually from room temperature to a steady state temperature of 1673 K, and then cooled down to room temperature. The heating and cooling processes were simulated, and the numerical and experimental results were compared throughout processes. The numerical model showed similar trends to the experimental results, with an error of 0.69 to 7.9 % for the particle inlet and 0.7 to 7.9 % for the gas inlet during steady-state operation. The proposed numerical model can be implemented as a simplified physical model to design a feedback control system to regulate reactor temperature.

A Markov chain Monte Carlo analysis of carbon-phenolic ablation through a lumped physical model

Payloads and other rocket components use Thermal Protection Systems (TPS) to avoid the effects of high heat fluxes generated by aerodynamic heating or propellant burning. The most used type of TPS is the ablative thermal shield, employing polymeric composite ablators. Ablative and thermophysical properties of such materials must be known for TPS design. These properties are often difficult to access experimentally, and vary according to the manufacturing process, ratio between reinforcement and matrix and the fiber direction in the case of composites, and other process variables. Inverse solution methods were initially applied in computational models to solve the heat transfer problems in space vehicles. This work proposes an inverse methodology, using the Markov chain Monte Carlo (MCMC) method, to determine the ablative properties of carbon-phenolic materials manufactured by biased tape wrapping, starting from arc-jet ablation results of samples of this material. A simplified but robust lumped physical model is used to represent the direct problem. The obtained values of these properties were used in the direct problem in a more refined mesh, and the simulation was compared to the experiments. Good agreement between numerical and experimental data was obtained, allowing the use of this methodology in estimation of ablation properties.

Risk of Interprosthetic Femur Fracture Is Associated with Implant Spacing-A Biomechanical Study.

Ipsilateral revision surgeries of total hip or knee arthroplasties due to periprosthetic fractures or implant loosening are becoming more frequent in aging populations. Implants in revision arthroplasty usually require long anchoring stems. Depending on the residual distance between two adjacent knee and hip implants, we assume that the risk of interprosthetic fractures increases with a reduction in the interprosthetic distance. The aim of the current study was to investigate the maximum strain within the femoral shaft between two ipsilateral implants tips. A simplified physical model consisting of synthetic bone tubes and metallic implant cylinders was constructed and the surface strains were measured using digital image correlation. The strain distribution on the femoral shaft was analyzed in 3-point- and 4-point-bending scenarios. The physical model was transferred to a finite element model to parametrically investigate the effects of the interprosthetic distance and the cortical thickness on maximum strain. Strain patterns for all parametric combinations were compared to the reference strain pattern of the bone without implants. The presence of an implant reduced principal strain values but resulted in distinct strain peaks at the locations of the implant tips. A reduced interprosthetic distance and thinner cortices resulted in strain peaks of up to 180% compared to the reference. At low cortical thicknesses, the strain peaks increased exponentially with a decrease in the interprosthetic distance. An increasing cortical thickness reduced the peak strains at the implant tips. A minimum interprosthetic distance of 10 mm seems to be crucial to avoid the accumulation of strain peaks caused by ipsilateral implant tips. Interprosthetic fracture management is more important in patients with reduced bone quality.

Post-shock turbulence recovery in oblique-shock/turbulent boundary layer interaction flows

The oblique shock impinging on the supersonic turbulent boundary layer leads to a mixing layer and the emergence of large-scale coherent structures within the interaction zone which leave significant velocity defect and turbulence amplification downstream. In the present study, we investigate the turbulence recovery in the post-shock region by exploiting direct numerical simulation data of the oblique-shock/turbulent boundary layer interaction flow at the incoming Mach number of $2.28$ and the shock angle of $33.2^\circ$ , with special attention paid to the contribution of the mixing layer and large-scale structures to flow dynamics. For that purpose, we propose to split the mean velocity, Reynolds stresses and spanwise spectra into a canonical portion that is constructed according to the statistics of canonical turbulent boundary layers, and a mixing-layer-induced portion. We found that the hidden mixing layer grows with the boundary layer thickness and that the induced mean shear and Reynolds stresses decay at different rates. The mean velocity recovers to the canonical profiles at a distance of 13 boundary layer thicknesses downstream where the mixing-layer-induced mean shear ceases to have strong impacts. The recovery of Reynolds stresses requires 10 boundary layer thicknesses in the near-wall region but a much longer streamwise extent in the outer region due to the slow decay of large-scale motions. These large-scale motions superpose on the near-wall turbulence, intensifying the turbulent fluctuations, yet having a trivial impact on the skin friction, for the contribution of the mixing-layer-induced mean shear and Reynolds shear stress are balanced by the advection term. We further establish a simple physical model capable of approximately predicting the streamwise evolution of mixing-layer-induced mean shear and turbulent kinetic energy. This model suggests that the complete recovery of turbulence in the outer region requires a streamwise extent of approximately 50 boundary layer thicknesses.

Simple physical model with empirical formulas for solid-state sintering of CaCO3 for estimation of porosity

The porosity after solid-state sintering is theoretically estimated by using a simple physical model with empirical formulas as a function of applied pressure and initial particle size. The comparison with the experimental data has revealed that tight aggregation of CaCO3 nanoparticles strongly increases porosity in solid-state sintering compared to that predicted for isolated nanoparticles.

Self-Thermal Insulation of Containers by the Precipitation and Formation of a Gas Film at the Walls for Thermal Energy Storage

AbstractIn this study, consideration is given to a novel idea for thermal storage enhancement by the passive thermal self-insulation of the inside walls of containers when they are deliberately coated by nucleation sites and the working fluid is supersaturated with a certain gas. Here, it is proposed that a gas film blanketing the inside surfaces of the container may be promoted by previously supersaturating the working fluid in which the heat is to be stored (e.g, molten salts, water, etc) and covering the surface with nucleation sites. The last achievements in micro/nano surface modification allow the control in number and roughness of the surface with nucleation sites near to its critical radius for nucleation which translates into a vigorous gas precipitation even working at relatively low supersaturation rates. Utilizing a simplified geometrical and physical model, an expression for the average thickness of the film gas and the heat transfer coefficient was derived.