Integrated Experimental, Atomistic, and Microstructurally Based Finite Element Investigation of the Dynamic Compressive Behavior of 2139 Aluminum

The objective of this study was to identify the microstructural mechanisms related to the high strength and ductile behavior of 2139-Al, and how dynamic conditions would affect the overall behavior of this alloy. Three interrelated approaches, which span a spectrum of spatial and temporal scales, were used: (i) The mechanical response was obtained using the split Hopkinson pressure bar, for strain-rates ranging from 1.0×10^(−3) s to 1.0×10^4 s^(−1). (ii) First principles density functional theory calculations were undertaken to characterize the structure of the interface and to better understand the role played by Ag in promoting the formation of the Ω phase for several Ω-Al interface structures. (iii) A specialized microstructurally based finite element analysis and a dislocation-density based multiple-slip formulation that accounts for an explicit crystallographic and morphological representation of Ω and Θ' precipitates and their rational orientation relations were conducted. The predictions from the microstructural finite element model indicated that the precipitates continue to harden and also act as physical barriers that impede the matrix from forming large connected zones of intense plastic strain. As the microstructural FE predictions indicated, and consistent with the experimental observations, the combined effects of Θ' and Ω, acting on different crystallographic orientations, enhance the strength and ductility, and reduce the susceptibility of 2139-Al to shear strain localization due to dynamic compressive loads

The Sandia Fracture Challenge: blind round robin predictions of ductile tearing

Existing and emerging methods in computational mechanics are rarely validated against problems with an unknown outcome. For this reason, Sandia National Laboratories, in partnership with US National Science Foundation and Naval Surface Warfare Center Carderock Division, launched a computational challenge in mid-summer, 2012. Researchers and engineers were invited to predict crack initiation and propagation in a simple but novel geometry fabricated from a common off-the-shelf commercial engineering alloy. The goal of this international Sandia Fracture Challenge was to benchmark the capabilities for the prediction of deformation and damage evolution associated with ductile tearing in structural metals, including physics models, computational methods, and numerical implementations currently available in the computational fracture community. Thirteen teams participated, reporting blind predictions for the outcome of the Challenge. The simulations and experiments were performed independently and kept confidential. The methods for fracture prediction taken by the thirteen teams ranged from very simple engineering calculations to complicated multiscale simulations. The wide variation in modeling results showed a striking lack of consistency across research groups in addressing problems of ductile fracture. While some methods were more successful than others, it is clear that the problem of ductile fracture prediction continues to be challenging. Specific areas of deficiency have been identified through this effort. Also, the effort has underscored the need for additional blind prediction-based assessments

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Derivation of the Orthotropic Nonlinear Elastic Material Law Driven by Low-Cost Data (DDONE)

Orthotropic nonlinear elastic materials are common in nature and widely used by various industries. However, there are only limited constitutive models available in today\u27s commercial software (e.g., ABAQUS, ANSYS, etc.) that adequately describe their mechanical behavior. Moreover, the material parameters in these constitutive models are also difficult to calibrate through low-cost, widely available experimental setups. Therefore, it is paramount to develop new ways to model orthotropic nonlinear elastic materials. In this work, a data-driven orthotropic nonlinear elastic (DDONE) approach is proposed, which builds the constitutive response from stress–strain data sets obtained from three designed uniaxial tensile experiments. The DDONE approach is then embedded into a finite element (FE) analysis framework to solve boundary-value problems (BVPs). Illustrative examples (e.g., structures with an orthotropic nonlinear elastic material) are presented, which agree well with the simulation results based on the reference material model. The DDONE approach generally makes accurate predictions, but it may lose accuracy when certain stress–strain states that appear in the engineering structure depart significantly from those covered in the data sets. Our DDONE approach is thus further strengthened by a mapping function, which is verified by additional numerical examples that demonstrate the effectiveness of our modified approach. Moreover, artificial neural networks (ANNs) are employed to further improve the computational efficiency and stability of the proposed DDONE approach

The sandia fracture challenge: Blind round robin predictions of ductile tearing

Existing and emerging methods in computational mechanics are rarely validated against problems with an unknown outcome. For this reason, Sandia National Laboratories, in partnership with US National Science Foundation and Naval Surface Warfare Center Carderock Division, launched a computational challenge in mid-summer, 2012. Researchers and engineers were invited to predict crack initiation and propagation in a simple but novel geometry fabricated from a common off-the-shelf commercial engineering alloy. The goal of this international Sandia Fracture Challenge was to benchmark the capabilities for the prediction of deformation and damage evolution associated with ductile tearing in structural metals, including physics models, computational methods, and numerical implementations currently available in the computational fracture community. Thirteen teams participated, reporting blind predictions for the outcome of the Challenge. The simulations and experiments were performed independently and kept confidential. The methods for fracture prediction taken by the thirteen teams ranged from very simple engineering calculations to complicated multiscale simulations. The wide variation in modeling results showed a striking lack of consistency across research groups in addressing problems of ductile fracture. While some methods were more successful than others, it is clear that the problem of ductile fracture prediction continues to be challenging. Specific areas of deficiency have been identified through this effort. Also, the effort has underscored the need for additional blind prediction-based assessments