Predicting tensile properties of Ti-6Al-4V produced via directed energy deposition

Advanced manufacturing approaches, including additive manufacturing (i.e., “3D printing”) of metallic structures requires a change to qualification strategies. One approach, informed qualification, integrates modeling strategies to make predictions of material characteristics, including the prediction of tensile properties for given chemistries and microstructures. In this work, constitutive equations are developed and presented that can predict the yield strength of additively manufactured Ti-6Al-4V subjected to one of three different heat-treatments: a stress relief anneal in the α+β phase field; a hot isostatic press treatment in the α+β phase field; and a β-anneal. The equations are nominally identical, though different strengthening mechanisms are active according to subtle microstructural differences. To achieve an equation that can predict the yield strength of the material, it is also necessary to include an assessment of dramatic reduction in the tensile strength due to texture (i.e., a “knock-down” effect). This has been experimentally measured, and included in this paper. The resulting predictions of yield strength are generally within 5% of their experimentally measured values

Predicting the tensile properties of additively manufactured Ti-6Al-4V via electron beam deposition

Additively manufactured materials are gaining wide attention owing to the manufacturing benefits as it results in near net shape components. It is well known that the manufacturing processes affects the performance of the components via microstructural features and the mechanical properties. There is an urgent need to understand the processing-structure-property-performance relationship for the materials manufactures via such innovative techniques. Strategies are needed to quantify and modify the mechanical properties. This study assists to design and tailor the process parameters based on the final properties required. Current work predicts the yield strength of additively manufactured Ti-6Al-4V with different post heat treatments. A thermal model predicted by ABAQUS is fed into an implementation of Langmuir equation that predicts the chemistry which is then used in a phenomenological equation predicting the yield strength. The model is confirmed via experiments showing less than 2% deviation from the predicated properties. A statistical model gives design allowables that have an uncertainty of less than 1 ksi

Less favourable climates constrain demographic strategies in plants

Correlative species distribution models are based on the observed relationship between species’ occurrence and macroclimate or other environmental variables. In climates predicted less favourable populations are expected to decline, and in favourable climates they are expected to persist. However, little comparative empirical support exists for a relationship between predicted climate suitability and population performance. We found that the performance of 93 populations of 34 plant species worldwide – as measured by in situ population growth rate, its temporal variation and extinction risk – was not correlated with climate suitability. However, correlations of demographic processes underpinning population performance with climate suitability indicated both resistance and vulnerability pathways of population responses to climate: in less suitable climates, plants experienced greater retrogression (resistance pathway) and greater variability in some demographic rates (vulnerability pathway). While a range of demographic strategies occur within species’ climatic niches, demographic strategies are more constrained in climates predicted to be less suitable

Super-enhancer-based identification of a BATF3/IL-2R-module reveals vulnerabilities in anaplastic large cell lymphoma.

Anaplastic large cell lymphoma (ALCL), an aggressive CD30-positive T-cell lymphoma, comprises systemic anaplastic lymphoma kinase (ALK)-positive, and ALK-negative, primary cutaneous and breast implant-associated ALCL. Prognosis of some ALCL subgroups is still unsatisfactory, and already in second line effective treatment options are lacking. To identify genes defining ALCL cell state and dependencies, we here characterize super-enhancer regions by genome-wide H3K27ac ChIP-seq. In addition to known ALCL key regulators, the AP-1-member BATF3 and IL-2 receptor (IL2R)-components are among the top hits. Specific and high-level IL2R expression in ALCL correlates with BATF3 expression. Confirming a regulatory link, IL-2R-expression decreases following BATF3 knockout, and BATF3 is recruited to IL2R regulatory regions. Functionally, IL-2, IL-15 and Neo-2/15, a hyper-stable IL-2/IL-15 mimic, accelerate ALCL growth and activate STAT1, STAT5 and ERK1/2. In line, strong IL-2Rα-expression in ALCL patients is linked to more aggressive clinical presentation. Finally, an IL-2Rα-targeting antibody-drug conjugate efficiently kills ALCL cells in vitro and in vivo. Our results highlight the importance of the BATF3/IL-2R-module for ALCL biology and identify IL-2Rα-targeting as a promising treatment strategy for ALCL

Best practice for motor imagery: a systematic literature review on motor imagery training elements in five different disciplines

<p>Abstract</p> <p>Background</p> <p>The literature suggests a beneficial effect of motor imagery (MI) if combined with physical practice, but detailed descriptions of MI training session (MITS) elements and temporal parameters are lacking. The aim of this review was to identify the characteristics of a successful MITS and compare these for different disciplines, MI session types, task focus, age, gender and MI modification during intervention.</p> <p>Methods</p> <p>An extended systematic literature search using 24 databases was performed for five disciplines: Education, Medicine, Music, Psychology and Sports. References that described an MI intervention that focused on motor skills, performance or strength improvement were included. Information describing 17 MITS elements was extracted based on the PETTLEP (physical, environment, timing, task, learning, emotion, perspective) approach. Seven elements describing the MITS temporal parameters were calculated: study duration, intervention duration, MITS duration, total MITS count, MITS per week, MI trials per MITS and total MI training time.</p> <p>Results</p> <p>Both independent reviewers found 96% congruity, which was tested on a random sample of 20% of all references. After selection, 133 studies reporting 141 MI interventions were included. The locations of the MITS and position of the participants during MI were task-specific. Participants received acoustic detailed MI instructions, which were mostly standardised and live. During MI practice, participants kept their eyes closed. MI training was performed from an internal perspective with a kinaesthetic mode. Changes in MI content, duration and dosage were reported in 31 MI interventions. Familiarisation sessions before the start of the MI intervention were mentioned in 17 reports. MI interventions focused with decreasing relevance on motor-, cognitive- and strength-focused tasks. Average study intervention lasted 34 days, with participants practicing MI on average three times per week for 17 minutes, with 34 MI trials. Average total MI time was 178 minutes including 13 MITS. Reporting rate varied between 25.5% and 95.5%.</p> <p>Conclusions</p> <p>MITS elements of successful interventions were individual, supervised and non-directed sessions, added after physical practice. Successful design characteristics were dominant in the Psychology literature, in interventions focusing on motor and strength-related tasks, in interventions with participants aged 20 to 29 years old, and in MI interventions including participants of both genders. Systematic searching of the MI literature was constrained by the lack of a defined MeSH term.</p

Predicting the tensile properties of additively manufactured Ti-6Al-4V via electron beam deposition

Additively manufactured materials are gaining wide attention owing to the manufacturing benefits as it results in near net shape components. It is well known that the manufacturing processes affects the performance of the components via microstructural features and the mechanical properties. There is an urgent need to understand the processing-structure-property-performance relationship for the materials manufactures via such innovative techniques. Strategies are needed to quantify and modify the mechanical properties. This study assists to design and tailor the process parameters based on the final properties required. Current work predicts the yield strength of additively manufactured Ti-6Al-4V with different post heat treatments. A thermal model predicted by ABAQUS is fed into an implementation of Langmuir equation that predicts the chemistry which is then used in a phenomenological equation predicting the yield strength. The model is confirmed via experiments showing less than 2% deviation from the predicated properties. A statistical model gives design allowables that have an uncertainty of less than 1 ksi

Predicting the tensile properties of additively manufactured Ti-6Al-4V via electron beam deposition

Additively manufactured materials are gaining wide attention owing to the manufacturing benefits as it results in near net shape components. It is well known that the manufacturing processes affects the performance of the components via microstructural features and the mechanical properties. There is an urgent need to understand the processing-structure-property-performance relationship for the materials manufactures via such innovative techniques. Strategies are needed to quantify and modify the mechanical properties. This study assists to design and tailor the process parameters based on the final properties required. Current work predicts the yield strength of additively manufactured Ti-6Al-4V with different post heat treatments. A thermal model predicted by ABAQUS is fed into an implementation of Langmuir equation that predicts the chemistry which is then used in a phenomenological equation predicting the yield strength. The model is confirmed via experiments showing less than 2% deviation from the predicated properties. A statistical model gives design allowables that have an uncertainty of less than 1 ksi