Crack Length Effect on the Fracture Behavior of Single-Crystals and Bi-Crystals of Aluminum

Molecular dynamics simulations of cracked nanocrystals of aluminum were performed in order to investigate the crack length and grain boundary effects. Atomistic models of single-crystals and bi-crystals were built considering 11 different crack lengths. Novel approaches based on fracture mechanics concepts were proposed to predict the crack length effect on single-crystals and bi-crystals. The results showed that the effect of the grain boundary on the fracture resistance was beneficial increasing the fracture toughness almost four times for bi-crystals.

Finsler differential geometry in continuum mechanics: Fundamental concepts, history, and renewed application to ferromagnetic solids

Finsler differential geometry enables enriched mathematical and physical descriptions of the mechanics of materials with microstructure. The first propositions for Finsler geometry in solid mechanics emerged some six decades ago. Ideas set forth in these early works are reviewed, along with subsequent literature culminating in contemporary theories of Finsler-geometric continuum mechanics. Concepts unique to generalized Finsler spaces, in the context of continuum mechanical applications, are highlighted. Capabilities afforded by physical models in generalized Finsler spaces are contrasted with those of standard approaches in affinely connected spaces. Theory and several examples of reduced dimensionality are reported for boundary value problems of fracture and phase transformations, showing how simultaneously novel, physical, and pragmatic model predictions can be obtained from Finsler-type continuum field theory. Lastly, the modern theory is newly applied to describe nonlinear elastic ferromagnetic solids in the magnetically saturated state. A variational approach is used to derive Euler–Lagrange equations for macroscopic and microscopic, i.e., respective electromechanical and electronic continuum, equilibrium states. For a representative generalized Finsler metric depending on material symmetry, augmented conservation laws of macroscopic momentum and electronic spin angular momentum naturally emerge.

Lessons Learned from a Human-Centered Design of an Immersive Exergame for People with Dementia

Cognitive-physical exercises can reduce the progression of dementia. However, traditional methods often induce problems (e.g., lack of motivation), whereas the success of recent virtual reality (VR) exergames such as Beat Saber may provide a playful, motivational, and immersive alternative. Yet, until now, it remains unclear which game mechanics, concepts, and designs work best for people with dementia, and how to implement exergames for and with this user group. In this paper, we adapted a human-centered design approach to address the specifics of developing VR exergames for people with dementia. This includes semi-structured interviews with stakeholders and contextual inquiries to better analyze the user requirements. Based on our analysis, we present Memory Journalist VR - a novel VR exergame specifically designed for people with dementia in a participatory design process. We report the qualitative evaluation based on the feedback gathered in five focus group sessions. Finally, we discuss the lessons learned, which provide important insights for the design of future VR exergames for people with dementia: (i) creating social gaming activities with a focus on shared aspects, (ii) support of an inverse game flow channel addressing decline and variance in cognitive-physical abilities, and (iii) ensuring a safe VR exergame experience.

Hybrid Computational Model to Assist in the Location of Victims Buried in the Tragedy of Brumadinho

This paper presents a hybrid computational model based on regression techniques, machine learning and physicomathematical algorithms developed for assistance in locating victims in the Brumadinho tragedy in 2019. The physicomathematical model, which provided results to help search teams, is based on integral and vector calculus, and fluid mechanics concepts. In addition, from data provided by the physicomathematical algorithm, two hybrid model were developed. One of them uses regression statistical and the other one uses support vector regression which is a type of machine learning. With good prospects of the advances in research, it is expected in future work, a more accurate model that can be used in other possible situations of dam-break. Moreover the model can be applied to situations involving computational fluid dynamics in general

Application of Damage Mechanics and Polynomial Chaos Expansion for Lifetime Prediction of High-Temperature Components Under Creep-Fatigue Loading

Several (accumulative) lifetime models were developed to assess the lifetime consumption of high-temperature components of steam and gas turbine power plants during flexible operation modes. These accumulative methods have several drawbacks, e.g. that measured loading profiles cannot be used within accumulative lifetime methods without manual corrections, and cannot be combined directly to sophisticated probabilistic methods. Although these methods are widely accepted and used for years, the accumulative lifetime prediction procedures need improvement regarding the lifetime consumption of thermal power plants during flexible operation modes. Furthermore, previous investigations show that the main influencing factor from the materials perspective, the critical damage threshold, cannot be statistically estimated from typical creep-fatigue experiments due to massive experimental effort and a low amount of available data. This paper seeks to investigate simple damage mechanics concepts applied to high-temperature components under creep-fatigue loading to demonstrate that these methods can overcome some drawbacks and use improvement potentials of traditional accumulative lifetime methods. Furthermore, damage mechanics models do not provide any reliability information, and the assessment of the resultant lifetime prediction is nearly impossible. At this point, probabilistic methods are used to quantify the missing information concerning failure probabilities and sensitivities and thus, the combination of both provides rigorous information for engineering judgment. Nearly 50 low cycle fatigue experiments of a high chromium cast steel, including dwell times and service-type cycles, are used to investigate the model properties of a simple damage evolution equation using the strain equivalence hypothesis. Furthermore, different temperatures from 300 °C to 625 °C and different strain ranges from 0.35% to 2% were applied during the experiments. The determination of the specimen stiffness allows a quantification of the damage evolution during the experiment. The model parameters are determined by Nelder-Mead optimization procedure, and the dependencies of the model parameters concerning to different temperatures and strain ranges are investigated. In this paper, polynomial chaos expansion (PCE) is used for uncertainty propagation of the model uncertainties while using non-intrusive methods (regression techniques). In a further post-processing step, the computed PCE coefficients of the damage variable are used to determine the probability of failure as a function of cycles and evolution of the probability density function (pdf). Except for the selected damage mechanics model which is considered simple, the advantages of using damage mechanics concepts combined with sophisticated probabilistic methods are presented in this paper.