Standard Deviation Of Experimental Data Research Articles

Effect of heat transfer on the pressurization, extraction, and depressurization stages of a supercritical CO2 extraction process. 1. Development and validation of the heat transfer model

We modeled and simulated the heat and mass transfer in the depressurization, pressurization, and extraction stages of a supercritical CO2 extraction process. Parameters of a Nusselt correlation for convective wall-to-fluid heat transfer coefficient were best fitted to experimental temperatures during the depressurization of vessels packed with different materials. Heat transfer in the pressurization and extraction stages was simulated predictively using this correlation and compared with literature laboratory-scale, pressurization, and extraction data. In depressurization, simulated temperature, pressure, and vented mass flow profiles agreed reasonably well with experimental values, as the calculated Mean Absolute Percent Error (MAPE) was 1.8% for the temperature. For pressurization, simulated values of final temperatures and pressures fell within a standard deviation of experimental data, estimating a MAPE of 3.9% for temperature and 5.2% for pressure. In the extraction stage, including radial and axial temperature gradients in the mass transfer model reduced the error (about 2%) of simulated cumulative extraction curves against experimental values compared to those obtained when neglecting radial variations in temperature. These results are significant because they prove that heat transfer phenomena may impact industrial more considerably than laboratory-scale processes.

Holes distribution in bilayer graphene

Layer-resolved charge distribution in bilayer graphene is crucial for understanding new physics in van der Waals stacked 2D crystals and related electronics applications. Here, we report the hole distribution in Bernal-stacked and twisted bilayer graphene (AB-BLG and t-BLG) labeled by carbon isotopes prepared by chemical vapor deposition. Raman spectroscopy identifies the isotope components and stacking orientation and further characterizes the hole concentration (nh) by monitoring the shift of ωG and ω2D. This study reveals that, for both AB-BLG and t-BLG, the nh in the top and bottom layers are close, leaving negligible differences smaller than their standard deviation of experimental data. The redshift of ωG in each layer of BLG relative to that of single-layer graphene implies the extra layer reduces the degree of charge exchange at the graphene/dopant interface. Moreover, the hole distribution behavior is rotational-angle independent despite a distinct electronically coupling degree between AB-BLG and t-BLG.

A Small Deformation Thermoporomechanics Finite Element Model and Its Application to Arterial Tissue Fusion

Understanding the impact of thermally and mechanically loading biological tissue to supraphysiological levels is becoming of increasing importance as complex multiphysical tissue-device interactions increase. The ability to conduct accurate, patient specific computer simulations would provide surgeons with valuable insight into the physical processes occurring within the tissue as it is heated or cooled. Several studies have modeled tissue as porous media, yet fully coupled thermoporomechanics (TPM) models are limited. Therefore, this study introduces a small deformation theory of modeling the TPM occurring within biological tissue. Next, the model is used to simulate the mass, momentum, and energy balance occurring within an artery wall when heated by a tissue fusion device and compared to experimental values. Though limited by its small strain assumption, the model predicted final tissue temperature and water content within one standard deviation of experimental data for seven of seven simulations. Additionally, the model showed the ability to predict the final displacement of the tissue to within 15% of experimental results. These results promote potential design of novel medical devices and more accurate simulations allowing for scientists and surgeons to quickly, yet accurately, assess the effects of surgical procedures as well as provide a first step toward a fully coupled large deformation TPM finite element (FE) model.

The contribution of the glenoid labrum to glenohumeral stability under physiological joint loading using finite element analysis

The labrum contributes to passive glenohumeral joint stability. Cadaveric studies have demonstrated that this has position and load dependency, which has not been quantified under physiological loads. This study aims to validate subject-specific finite element (FE) models against in vitro measurements of joint stability and to utilise the FE models to predict joint stability under physiological loads. The predicted stability values were within ± one standard deviation of experimental data and the FE models showed a reduction in stability of 10–15% with high, physiological, loads. The developed regression equations provide the first representation of passive glenohumeral stability and will aid surgical decision-making.

Predicting the elastic response of organic‐rich shale using nanoscale measurements and homogenisation methods

ABSTRACTDetermination of the mechanical response of shales through experimental procedures is a practical challenge due to their heterogeneity and the practical difficulties of retrieving good‐quality core samples. Here, we investigate the possibility of using multi‐scale homogenisation techniques to predict the macroscopic mechanical response of shales based on quantitative mineralogical descriptions. We use the novel PeakForce Quantitative Nanomechanical Mapping technique to generate high‐resolution mechanical images of shales, allowing the response of porous clay, organic matter, and mineral inclusions to be measured at the nanoscale. These observations support some of the assumptions previously made in the use of homogenisation methods to estimate the elastic properties of shale and also earlier estimates of the mechanical properties of organic matter. We evaluate the applicability of homogenisation techniques against measured elastic responses of organic‐rich shales, partly from published data and also from new indentation tests carried out in this work. Comparison of experimental values of the elastic constants of shale samples with those predicted by homogenisation methods showed that almost all predictions were within the standard deviation of experimental data. This suggests that the homogenisation approach is a useful way of estimating the elastic and mechanical properties of shales in situations where conventional rock mechanics test data cannot be measured.

Predictive simulation generates human adaptations during loaded and inclined walking.

Predictive simulation is a powerful approach for analyzing human locomotion. Unlike techniques that track experimental data, predictive simulations synthesize gaits by minimizing a high-level objective such as metabolic energy expenditure while satisfying task requirements like achieving a target velocity. The fidelity of predictive gait simulations has only been systematically evaluated for locomotion data on flat ground. In this study, we construct a predictive simulation framework based on energy minimization and use it to generate normal walking, along with walking with a range of carried loads and up a range of inclines. The simulation is muscle-driven and includes controllers based on muscle force and stretch reflexes and contact state of the legs. We demonstrate how human-like locomotor strategies emerge from adapting the model to a range of environmental changes. Our simulation dynamics not only show good agreement with experimental data for normal walking on flat ground (92% of joint angle trajectories and 78% of joint torque trajectories lie within 1 standard deviation of experimental data), but also reproduce many of the salient changes in joint angles, joint moments, muscle coordination, and metabolic energy expenditure observed in experimental studies of loaded and inclined walking.