Physics-based Relationship Research Articles

Evaluation of finite element modeling methods for predicting compression screw failure in a custom pelvic implant.

Introduction: Three-dimensional (3D)-printed custom pelvic implants have become a clinically viable option for patients undergoing pelvic cancer surgery with resection of the hip joint. However, increased clinical utilization has also necessitated improved implant durability, especially with regard to the compression screws used to secure the implant to remaining pelvic bone. This study evaluated six different finite element (FE) screw modeling methods for predicting compression screw pullout and fatigue failure in a custom pelvic implant secured to bone using nine compression screws. Methods: Three modeling methods (tied constraints (TIE), bolt load with constant force (BL-CF), and bolt load with constant length (BL-CL)) generated screw axial forces using functionality built into Abaqus FE software; while the remaining three modeling methods (isotropic pseudo-thermal field (ISO), orthotropic pseudo-thermal field (ORT), and equal-and-opposite force field (FOR)) generated screw axial forces using iterative physics-based relationships that can be implemented in any FE software. The ability of all six modeling methods to match specified screw pretension forces and predict screw pullout and fatigue failure was evaluated using an FE model of a custom pelvic implant with total hip replacement. The applied hip contact forces in the FE model were estimated at two locations in a gait cycle. For each of the nine screws in the custom implant FE model, likelihood of screw pullout failure was predicted using maximum screw axial force, while likelihood of screw fatigue failure was predicted using maximum von Mises stress. Results: The three iterative physics-based modeling methods and the non-iterative Abaqus BL-CL method produced nearly identical predictions for likelihood of screw pullout and fatigue failure, while the other two built-in Abaqus modeling methods yielded vastly different predictions. However, the Abaqus BL-CL method required the least computation time, largely because an iterative process was not needed to induce specified screw pretension forces. Of the three iterative methods, FOR required the fewest iterations and thus the least computation time. Discussion: These findings suggest that the BL-CL screw modeling method is the best option when Abaqus is used for predicting screw pullout and fatigue failure in custom pelvis prostheses, while the iterative physics-based FOR method is the best option if FE software other than Abaqus is used.

Edge and Interface Resistances Create Distinct Trade-Offs When Optimizing the Microstructure of Printed van der Waals Thin-Film Transistors

Inks based on two-dimensional (2D) materials could be used to tune the properties of printed electronics while maintaining compatibility with scalable manufacturing processes. However, a very wide range of performances have been reported in printed thin-film transistors in which the 2D channel material exhibits considerable variation in microstructure. The lack of quantitative physics-based relationships between film microstructure and transistor performance limits the codesign of exfoliation, sorting, and printing processes to inefficient empirical approaches. To rationally guide the development of 2D inks and related processing, we report a gate-dependent resistor network model that establishes distinct microstructure-performance relationships created by near-edge and intersheet resistances in printed van der Waals thin-film transistors. The model is calibrated by analyzing electrical output characteristics of model transistors consisting of overlapping 2D nanosheets with varied thicknesses that are mechanically exfoliated and transferred. Kelvin probe force microscopy analysis on the model transistors leads to the discovery that the nanosheet edges, not the intersheet resistance, limit transport due to their impact on charge carrier depletion and scattering. Our model suggests that when transport in a 2D material network is limited by the near-edge resistance, the optimum nanosheet thickness is dictated by a trade-off between charged impurity screening and gate screening, and the film mobilities are more sensitive to variations in printed nanosheet density. Removal of edge states can enable the realization of higher mobilities with thinner nanosheets due to reduced junction resistances and reduced gate screening. Our analysis of the influence of nanosheet edges on the effective film mobility not only examines the prospects of extant exfoliation methods to achieve the optimum microstructure but also provides important perspectives on processes that are essential to maximizing printed film performance.

Extending a canopy reflectance model for mangroves: A case study in south east queensland, Australia

Mangroves are essential coastal wetland vegetation and their extent and leaf area index (LAI) have been mapped using remotely sensed Earth Observation images. However, the physics-based relationship between biophysical properties of mangroves, tidal height, and their spectral values remains underexplored. In order to quantitatively evaluate the impact of woody material on mangrove spectra from optical imagery, a canopy reflectance model (CRM) was extended to simulate and analyse the reflectance of mangroves. The fractional cover, leaf-to-total area ratio and water depth were included as model parameters, increasing the fidelity of the canopy architecture in the CRM. A mangrove study area in South East Queensland, Australia, was chosen for model parameterisation and verification using field and satellite data. Simulated Sentinel-2 reflectance spectra of the mangrove plots closely matched the observed pixel reflectance spectra, with their coefficient of determination (R2) values higher than 0.98 and root mean square error values lower than 0.01, which was better than the performance of the original CRM omitting the fractional cover and woody material. The inverted plant area index and fractional cover values from the satellite imagery closely matched the field-derived reference values (R2 = 0.78 and 0.97, respectively). Simulation results revealed that a higher proportion of woody material in crowns reduced the canopy reflectance of mangroves in the near infrared region and increased the reflectance in the shortwave infrared region. Moreover, the simulated reflectance of the Sentinel-2 red edge 1 (695–714 nm) was not sensitive to the wood proportion for the examined cases. The modelling framework may be used to evaluate the impact of woody material for estimating mangrove LAI from optical imagery. The model may also be used to quantitatively analyse the mangrove reflectance spectra when including other important factors such as tidal height.

Physics-Based Relationship for Pore Pressure and Vertical Stress Monitoring Using Seismic Velocity Variations

Previous studies examining the relationship between the groundwater table and seismic velocities have been guided by empirical relationships only. Here, we develop a physics-based model relating fluctuations in groundwater table and pore pressure with seismic velocity variations through changes in effective stress. This model justifies the use of seismic velocity variations for monitoring of the pore pressure. Using a subset of the Groningen seismic network, near-surface velocity changes are estimated over a four-year period, using passive image interferometry. The same velocity changes are predicted by applying the newly derived theory to pressure-head recordings. It is demonstrated that the theory provides a close match of the observed seismic velocity changes.

A Bibliometric Analysis of Physics-Based and Data-Driven Hybrid Modeling

Manufacturing evolved substantially over the years and with it the inherent complexity increased well. Currently organizations are transitioning towards smart manufacturing and implementation of industry 4.0 paradigms. Artificial intelligence and machine learning can help organizations of any size on this journey. The physics of manufacturing processes have been extensively studied and documented as relationships and equations. Machine learning algorithms rely on quality data to enable inferences and smart actions. At the intersection of these two methods lies hybrid analytics which captures the knowledge in the defined physics-based relationships and uses data-driven methods to fill the gaps that the physics-based model may have. The goal of this paper is to identify approaches and use cases of hybrid modeling wherein the term hybrid is used to indicate the combination of a physics- or first-principle-based modeling component and a data-driven modeling component. VOSViewer, Voyant Tools, and Microsoft Excel have been used to understand the relationships between various attributes associated with the articles on hybrid modeling. The papers cited the most, the organizations/regions that funded the research in this domain, the contents of recent papers, and what categories and keywords are frequently used are discussed. This work is the basis for an extended literature review to understand in detail the algorithms, use cases, and implementation issues of hybrid analytics. This bibliometric analysis uses the state of the art references and procedures mentioned in the documentation of VOSViewer and Voyant Tools.

Modeling Ti–6Al–4V using crystal plasticity, calibrated with multi-scale experiments, to understand the effect of the orientation and morphology of the α and β phases on time dependent cyclic loading

Classically, crystal plasticity modeling has used a range of constitutive equations, in which the incorporation of additional physics-based relationships typically results in additional model parameters. These additional parameters need to be reliably calibrated, which often necessitates the use of a range of experimental data acquired at multiple length scales. In this work, a crystal plasticity based finite element (CPFE) model for a dual-phase Titanium alloy, Ti–6Al–4V, is developed. The α and β phases of the microstructure are explicitly modeled. The model is calibrated using a systematic optimization routine and experimental data that consist of macroscopic stress-strain curves coupled with lattice strains on different crystallographic planes for the two phases. These experimental data were obtained from in situ high energy X-ray diffraction experiments for multiple material pedigrees, with varying crystallographic orientation distribution and β volume fractions. Depending on the thermomechanical-processing route and the heat treatment used to manufacture the alloy, Ti–6Al–4V can exist in a wide number of microstructural forms, which often results in the α and β phases either having well aligned slip systems (following the Burgers orientation relationship (BOR)) or possessing no alignment of the slip systems across the interphase boundary (not following the BOR). In this study, the fully-calibrated CPFE model is used to gain a comprehensive understanding of the deformation behavior of Ti–6Al–4V, specifically, the effect of microstructures that follow the BOR (or not) on time-dependent cyclic loading (including the effects of dwell hold times).

Spatiotemporal sensitivity of thermal stress for monitoring canopy hydrological stress in near real-time

Monitoring drought in real-time using minimal field data is a challenge for ecosystem management and conservation. Most methods require extensive data collection and in-situ calibration and accuracy is difficult to evaluate. Here, we demonstrated how the space-borne canopy “thermal stress”, defined as surface-air temperature difference, provides a reliable surrogate for drought-induced water stress in vegetation. Using physics-based relationships that accommodate uncertainties, we showed how changes in canopy water flux from ground-based measurements relate to both the surface energy balance and remotely-sensed thermal stress. Field measurements of evapotranspiration in the southeastern and northwestern US verify this approach based on sensitivity of evapotranspiration to thermal stress in a large range of atmospheric and climate conditions. We found that a 1 °C change in the thermal stress is comparable to 1–1.2 mm day−1 of evapotranspiration, depending on site and climate conditions. We quantified temporal and spatial sensitivity of evapotranspiration to the thermal stress and showed that it has the strongest relationship with evapotranspiration during warm and dry seasons, when monitoring drought is essential. Using only air and surface temperatures, we predicted the inter-annual anomaly in thermal stress across the contiguous United States over the course of 15 years and compared it with conventional drought indices. Among drought metrics that were considered in this study, the thermal stress had the highest correlation values. Our sensitivity results demonstrated that the thermal stress is a particularly strong indicator of water-use in warm seasons and regions. This simple metric can be used at varying time-scales to monitor surface evapotranspiration and drought in large spatial extents in near real-time.

Towards a physics-based relationship for crack growth under different loading modes

In an attempt to understand quasi-static delamination growth under mixed mode loading conditions from a physics-based perspective, this work first evaluated cracking in isotropic materials. The critical Strain Energy Density (SED) approach is adopted, because physically the onset of crack growth is expected to occur when the energy available near the crack tip reaches a critical value.The main hypothesis of the present paper is that the critical SED for onset of crack growth is constant for a given material, and independent of the loading mode. The relationship derived from this hypothesis therefore relates the physical onset of crack growth and the angle at which that occurs for any opening mode through the SED.To test this hypothesis, results from literature were taken and shear fracture tests on foam specimens were performed, which both were compared with the derived relationship. The excellent correlation demonstrated the validity of the physics-based relationship, which explains the observed differences between mode I and mode II fracture toughnesses and illustrates why concepts like the Stress Intensity Factor (SIF) alone are insufficient to explain the observations. The developed relationship allows to derive the mode II fracture toughness from mode I fracture toughness tests and the material’s mechanical properties.

Analysis of Electrothermal and Impact-Ionization Effects in Bipolar Cascode Amplifiers

This paper is aimed at the analysis of the influence of electrothermal and impact-ionization effects on the dc behavior of bipolar cascode amplifiers. A simple physics-based relationship is derived to predict the limit of the safe operating area in the output diagram. Experiments and circuit simulations are performed on amplifiers in GaAs and SiGe technologies to examine and explain the distortion in the dc ${I}$ – ${V}$ curves induced by these positive-feedback mechanisms, as well as to predict the temperatures of the individual devices.

Multifinger MOSFETs’ Optimization Considering Stress and INWE in Static CMOS Circuits

Strain engineering and inverse narrow width effect (INWE) are among the main causes of layout-dependent variations in narrow width devices. Transistor sizing and layout without considering these effects at a prelayout stage may result in suboptimal design and design/layout iterations. In this paper, we model the channel stress variations in multifinger gate structure (MFGS) empirically using 3-D technology computer aided design simulations. Thereafter, we use these stress models along with a model for INWE to establish a physics-based relationship between effective drive current and number of fingers in MFGS. We also design single-stage combinational standard cells and predict the values of their logical effort using our approach. The performance of the standard cells using our approach improves significantly compared with the conventional approach. Inverter chains (buffers) are representative and extensively used multistage circuits. Using our model of effective drive current, we propose a methodology to optimize the buffer designed and layout to maximize performance in stress-enabled technologies. We observe that the proposed methodology results in a significant reduction in power dissipation up to 35% and reduction in silicon area up to 43% as compared with the existing methodologies.

An experimental and modeling assessment of the HCFC-R123 refrigerant capabilities for lubricating rolling EHD circular contacts

This work aims at investigating the capabilities of the hydrochlorofluorocarbon (HCFC)-R123 refrigerant for lubricating rolling elastohydrodynamic circular contacts. The viscosity pressure and temperature dependence of this fluid, used in oil-free compressors, are first studied in its liquid phase. Complementary data like density variations are taken from the thermo-physics literature. Besides, film thickness measurements using a ball-on-disk tribometer equipped with an interferometry facility have been performed under pure rolling conditions. For the same operating conditions, film thickness is then predicted from a numerical elastohydrodynamic model in which the viscosity and density dependencies with pressure and temperature are described using physics-based relationships, allowing a quantitative approach. The results obtained from the full numerical model, from the analytical elastohydrodynamic film-thickness expressions, and from the experiments show an acceptable agreement. They clearly reveal that indeed refrigerants can build up a reasonable film thickness for lubricating elastohydrodynamic rolling point contacts.

Predictive modeling of residual stress in minimum quantity lubrication machining

Residual stress is one of the critical characteristics for assessing the surface integrity of machined components as it poses a strong bearing on the service quality, functionality, and life of the machined components. The machined-in residual stresses can be affected by cutting parameters, tool geometry, material properties, and lubrication conditions. A physics-based relationship between residual stresses and processing conditions could support process planning in achieving desirable part quality and functionality. This paper presents an analytical model that predicts the residual stresses in machining under minimum quantity lubrication (MQL) condition as functions of cutting parameters, tool geometry, material properties as well as MQL application parameters. Both the lubrication and cooling effects caused by MQL air–oil mixture contribute to changes in friction due to boundary lubrication as well as changes in the thermal stress due to heat loss. The cutting force and cutting temperature are coupled into a thermal–mechanical model which incorporates the kinematic hardening and strain compatibility to predict the resulting residual stress under lubricated conditions. The residual stress prediction model is verified for orthogonal tube facing of TC4 alloy. The predicted residual stresses captured the measured results well in terms of the trend and magnitude.

Preliminary Modeling and Analysis of a Horizontal Pressure Differential Wave Energy Converter

Wave energy converters (WECs) have been proposed that take advantage of spatially varying pressure differentials (PDs) in a wave field to drive a fluid flow. In order to accurately assess the pressure forcing on PD devices, physics-based relationships between major device parameters and device performance need to be determined. Herein, a transfer function is developed that relates horizontally oriented PD device configurations and wave conditions to the amount of pressure forcing available to the device. Investigation of the transfer function confirms intuitive expectation but also yields surprising results. The transfer function can be applied to a wave spectrum to create a pressure resource spectrum. By manipulating the device length and orientation, an optimal configuration can be found that maximizes the total harnessable pressure resource for a given wave condition or a wave climate. Optimal device lengths for directional seas are longer than those for nondirectional seas, and a wide range of suboptimal configurations yields a reasonable pressure resource. The pressure resource transfer function is a fundamental tool for understanding how horizontal PD WECs work and designing an optimal device.

Simple Semi-Analytic Model for Optimized Interplanetary Low-Thrust Trajectories Using Solar Electric Propulsion

This paper describes a simple semi-analytic model for mass-optimized interplanetary solar electric low-thrust trajectories. A description is given of a model that accurately and quickly determines the performance of circular-coplanar low-thrust transfers with a series of simple empirical and physics-based relationships that can be implemented easily in a spreadsheet. The model takes flight time, departure and arrival velocity, initial power, initial mass, and propulsion-system efficiency as inputs and produces the optimum specific impulse, , final mass, and burn time that correspond to the mass-optimum trajectory as outputs. The development methodology is described, governing variables and fundamental relationships are identified, and a model is presented that efficiently calculates these parameters for a wide range of low-thrust trajectories. Models are presented for Earth-Jupiter/Trojan asteroid, Earth-Mars, Mars-Earth, Earth-Venus, and Earth-Main-Belt asteroid transfers using solar electric propulsion. The results show good agreement for estimates of both delivered mass () and optimum specific impulse (). This model is well suited to classroom instruction, concurrent engineering, and the initial development of new mission concepts.

Bounding of near-fault ground motion based on radiated seismic energy with a consideration of fault frictional mechanisms

The energy radiated as seismic waves strongly depends on the fault rupture process associated with rupture speed and dynamic frictional mechanisms involved in the fault slip motion. Following McGarr and Fletcher approach, we derived a physics-based relationship of the weighted average fault slip velocity vs apparent stress, rupture speed and static stress drop based on a dynamic circular fault model. The resultant function can be approximately used to bound near-fault ground motion and seismic energy associated with near-fault coseismic deformation. Fault frictional overshoot and undershoot mechanisms governed by a simple slip-weakening constitutive relation are included in our consideration by using dynamic rupture models named as M- and D-models and proposed by Madariaga (1976) and Boatwright. We applied the above function to the 2008 great Wenchuan earthquake and the 1999 Jiji (Chi-Chi) earthquake to infer the near-fault ground motion called slip weighted average particle velocity and obtained that such model-dependent prediction of weighted average ground velocities is consistent to the results derived from the near-fault strong motion observations. Moreover, we compared our results with the results by McGarr and Fletcher approach, and we found that the values of the weighted average particle velocities we obtained for these two earthquakes are generally smaller and closer to the values by direct integration of strong motion recordings of the near-fault particle velocity waveform data. In other words, if this result comes to be true, it would be a straightforward way used to constrain the near-fault ground motion or to estimate source parameters such as rupture speed, static and dynamic stress drops.

Sound velocities, elastic constants: Temperature dependence

I describe a simple physics-based relationship for describing and predicting the temperature dependence of solid-state sound velocities and elastic constants. Originating in an Einstein-oscillator model, the relationship applies to essentially all solid types: successful uses range from monocrystal diamond, various elemental polycrystals, through multiphase steels, to epoxy-matrix composites.