A study of grain rotations and void nucleation in aluminum triple junctions using molecular dynamics and crystal plasticity

This study focuses on molecular dynamics (MD) simulations, coupled with a discrete mathematical framework, and crystal plasticity (CP) simulations to investigate micro void nucleation and the plastic spin. The origin and historical use of the plastic spin are discussed with particular attention to quantifying the plastic spin at the atomistic scale. Two types of MD simulations are employed: (a) aluminum single crystals undergoing simple shear and (b) aluminum triple junctions (TJ) with varying grain orientations and textures undergoing uniaxial tension. The high-angle grain boundary simulations nucleate micro voids at or around the TJ and the determinant of the deformation gradient shows the ability to predict such events. Crystal plasticity simulations are used to explore the stress-state of the aluminum TJ from uniaxial tension at a higher length scale with results indicating a direct correlation between CP stress-states and the location of micro void nucleation in the MD simulations

Hay Making Weather in Kentucky: How to Get Good Information

The UK Agricultural Weather Center, housed within the Department of Biosystems and Agricultural Engineering, was developed in 1978. As part of the Cooperative Extension Service, the goal of the Ag Weather Center is to minimize weather and climate related surprise for Kentucky residents and their agricultural needs, ultimately for profitable and sustainable production. In doing so, numerous tools and models have been developed throughout the years to further help farmers and producers in management and production related decisions

Mindfulness training applied to addiction therapy: insights into the neural mechanisms of positive behavioral change

Dual-process models from neuroscience suggest that addiction is driven by dysregulated interactions between bottom-up neural processes underpinning reward learning and top-down neural functions subserving executive function. Over time, drug use causes atrophy in prefrontally mediated cognitive control networks and hijacks striatal circuits devoted to processing natural rewards in service of compulsive seeking of drug-related reward. In essence, mindfulness-based interventions (MBIs) can be conceptualized as mental training programs for exercising, strengthening, and remediating these functional brain networks. This review describes how MBIs may remediate addiction by regulating frontostriatal circuits, thereby restoring an adaptive balance between these top-down and bottom-up processes. Empirical evidence is presented suggesting that MBIs facilitate cognitive control over drug-related automaticity, attentional bias, and drug cue reactivity, while enhancing responsiveness to natural rewards. Findings from the literature are incorporated into an integrative account of the neural mechanisms of mindfulness-based therapies for effecting positive behavior change in the context of addiction recovery. Implications of our theoretical framework are presented with respect to how these insights can inform the addiction therapy process.National Institute of Health (NIH) award to ELG (R34DA037005

Sedimentology and isotope geochemistry of transitional evaporitic environments within arid continental settings : from erg to saline lakes

This research was supported by grants to RPP from the AAPG (Gustavus E. Archie Memorial Grant) and by the European Union’s Horizon 2020 research and innovation programme (Grant 678812 to M.W.C.).Arid continental basins typically contain a spectrum of coeval environments that coexist and interact from proximal to distal. Within the distal portion, aeolian ergs often border playa, or perennial, desert lakes, fed by fluvial incursions or elevated groundwaters. Evaporites are common features in these dryland, siliciclastic dominant settings. However, sedimentary controls upon evaporite deposition are not widely understood, especially within transitional zones between coeval clastic environments that are dominantly controlled by larger scale allocyclic processes, such as climate. The sulphur (δ34S) and oxygen (δ18O, Δ17O) isotope systematics of evaporites can reveal cryptic aspects of sedimentary cycling and sulphate sources in dryland settings. However, due to the lack of sedimentological understanding of evaporitic systems, isotopic data can be easily misinterpreted. This work presents detailed sedimentological and petrographic observations, coupled with δ34S, δ18O and Δ17O data, for the early Permian Cedar Mesa Sandstone Formation (western USA). Depositional models for mixed evaporitic / clastic sedimentation, which occurs either in erg-marginal or lacustrine-marginal settings, are presented to detail the sedimentary interactions present in terms of climate variations that control them. Sedimentological and petrographical analysis of the evaporites within the Cedar Mesa Sandstone Formation reveal a continental depositional environment and two end member depositional models have been developed: erg-margin and lake-margin. The δ34S values of gypsum deposits within the Cedar Mesa Sandstone Formation are consistent with late Carboniferous to early Permian marine settings. However, a marine interpretation is inconsistent with sedimentological and petrographic evidence. Consequently, δ34S, δ18O and Δ17O values are probably recycled and do not reflect ocean-atmosphere values at the time of evaporite precipitation. They are most likely derived from the weathering of older marine evaporites in the hinterland. Thus, the results demonstrate the need for a combination of both sedimentological and geochemical analysis of evaporitic systems to better understand their depositional setting and conditions.PostprintPeer reviewe

Mindfulness meditation in the treatment of substance use disorders and preventing future relapse: neurocognitive mechanisms and clinical implications

Substance use disorders (SUDs) are a pervasive public health problem with deleterious consequences for individuals, families, and society. Furthermore, SUD intervention is complicated by the continuous possibility of relapse. Despite decades of research, SUD relapse rates remain high, underscoring the need for more effective treatments. Scientific findings indicate that SUDs are driven by dysregulation of neural processes underlying reward learning and executive functioning. Emerging evidence suggests that mindfulness training can target these neurocognitive mechanisms to produce significant therapeutic effects on SUDs and prevent relapse. The purpose of this manuscript is to review the cognitive, affective, and neural mechanisms underlying the effects of mindfulness-based interventions (MBIs) on SUDs. We discuss the etiology of addiction and neurocognitive processes related to the development and maintenance of SUDs. We then explore evidence supporting use of MBIs for intervening in SUDs and preventing relapse. Finally, we provide clinical recommendations about how these therapeutic mechanisms might be applied to intervening in SUDs and preventing relapse.National Institute of Health (NIH) award to ELG (R01DA042033

Phase-field-lattice Boltzmann method for dendritic growth with melt flow and thermosolutal convection–diffusion

We propose a new phase-field model formulated within the system of lattice Boltzmann (LB) equation for simulating solidification and dendritic growth with fully coupled melt flow and thermosolutal convection–diffusion. With the evolution of the phase field and the transport phenomena all modeled and integrated within the same LB framework, this method preserves and combines the intrinsic advantages of the phase-field method (PFM) and the lattice Boltzmann method (LBM). Particularly, the present PFM/LBM model has several improved features compared to the existing phase-field models including: (1) a novel multiple-relaxation-time (MRT) LB scheme for the phase-field evolution is proposed to effectively model solidification coupled with melt flow and thermosolutal convection–diffusion with improved numerical stability and accuracy, (2) convenient diffuse interface treatments are implemented for the melt flow and thermosolutal transport which can be applied to the entire domain without tracking the interface, and (3) the evolution of the phase field, flow, concentration, and temperature fields on the level of microscopic distribution functions in the LB schemes is decoupled with a multiple-time-scaling strategy (despite their full physical coupling), thus solidification at high Lewis numbers (ratios of the liquid thermal to solutal diffusivities) can be conveniently modeled. The applicability and accuracy of the present PFM/LBM model are verified with four numerical tests including isothermal, iso-solutal and thermosolutal convection–diffusion problems, where excellent agreement in terms of phase-field and thermosolutal distributions and dendritic tip growth velocity and radius with those reported in the literature is demonstrated. The proposed PFM/LBM model can be an attractive and powerful tool for large-scale dendritic growth simulations given the high scalability of the LBM

Effects Due to Variations in Thermal Properties of Maraging Steel for Finite Element Modeling of the WAAM Process

Finite element (FE) thermal simulations of the wire arc additive manufacturing (WAAM) process have been widely used to predict the temperature history of as-built parts. Temperature-dependent thermal properties like density, conductivity, specific heat, and latent heat are required to accurately simulate the solidus to liquidus transition seen in the heat affected zone. Current research has shown that thermal properties measured experimentally or simulated using material database software can be used for thermal modeling; however, there has been no direct comparison shown to determine which is most appropriate for WAAM modeling. The focus of this research is to compare the temperature variation of the FE thermal simulations with experimentally measured and computer-generated properties for M250 grade maraging steel. The thermal history for thin wall builds are compared with differing temperature-dependent thermal properties to examine the relationship between thermal properties and history. It was shown that constant values at room temperature result in an increased thermal response for WAAM thermal simulations and linearized properties decreased the temperature when both were compared with the experimental thermal property inputs. Further work needs to be performed before determining the most appropriate source for thermal properties (wrought, wire, as-built, or material database), but it can be concluded that the form of material does affect the thermal response for maraging grade 250 steel.Mechanical Engineerin

Exploration of forward and inverse protocols for property optimization of Ti-6Al-4V

The modeling and simulation of advanced engineering materials undergoing mechanical loading requires accurate treatment of relevant microstructure features, such as grain size and crystallographic texture, to determine the heterogeneous response to deformation. However, many models constructed for this purpose are not being fully realized in their predictive capability. Additionally, physics-based models can be combined with bottom-up deductive mappings and top-down inductive decision paths to increase their utility in materials selection and optimization. However, connecting these types of models or algorithms with experiments, rapid inverse property/response estimates, and design decision-making via integrated workflows has yet to become well-established for materials design and/or development. One material system primed for this type of concurrent advancement is alpha+beta titanium alloys, because its resultant microstructure and mechanical properties are highly dependent on material processing and composition. This dissertation seeks to advance a materials design process for fatigue resistance, strength, and elastic stiffness of Ti-6Al-4V through the advancement of various computational tools, as well as the integration of simulation-based tools and high-throughput experimental datasets. The microstructure-sensitive crystal plasticity finite element method (CPFEM) is utilized to explicitly account for the grain structure and crystallographic texture of Ti-6Al-4V. To improve the predictive capability of the CPFEM model, high throughput spherical indentation experimental datasets are used for model calibration because of their ability to extract elastic and plastic individual phase and grain properties from multiphase materials such as titanium alloys. The CPFEM can be used to capture the microstructure heterogeneity on fatigue crack driving forces, but these types of simulations are computationally expensive. Instead, an explicit integration of the relevant constitutive relations in the CPFEM model are combined with the materials knowledge system (MKS) approach for generating spatially local results of polycrystalline materials. These bottom-up simulation methods provide macroscopic properties from microstructure-level model inputs. For materials design, it is important to determine the inverse -- microstructure-level information from the macroscopic response -- which is referred to as top-down modeling. The Inductive Design Exploration Method (IDEM) offers a systematic approach to combining bottom-up simulations with top-down inductive design search. In this dissertation, a generalized framework of the IDEM is implemented to assess multi-objective design scenarios specific to the microstructure-sensitive datasets generated in this work.Th e general approach presented in this dissertation integrates CPFEM simulations with experimental spherical indentation for model refinement and also combines CPFEM with the MKS for computational-efficient generation of local quantities. These advancements are the basis for accelerated decision-support for materials design exploration when merged with the IDEM. Although performed with alpha+beta titanium, individual elements of the framework can be applied to a variety of engineering alloys for tasks such as extraction of model parameters from spherical indentation experiments, coupling MKS with crystal plasticity constitutive relations, and performing a top-down inductive design search with polycrystalline datasets.Ph.D

Low-speed instrumented drill press for bone screw insertion

Screw insertion torque is a widely used/effective method for quantifying fixation strength in orthopedic implant research for different screw geometries, implantation sites, and loads. This work reports the construction of an open-source instrumented benchtop screw insertion device for a total cost of $7545 ($492 + $7053 for equipped sensors), as well as validation of the device and an example use-application. The insertion device is capable of recording the axial load, rotational speed, and applied torque throughout the screw insertion process at 10 samples per second, as demonstrated in the validation test. For this combination of bone analog (20 PCF Sawbones©), screw, and loading, the resolution of the torque sensor was 25% of the maximum measured torque; a different model torque sensor would be required to meet ASTM F543-17, which specifies a resolution of 10% of the maximum torque. This system is optimized for fastener insertion at speeds of 120 rpm or less and axial loading up to 50 N