Design and Analysis of Honeycomb Structures with Advanced Cell Walls

Honeycomb structures are widely used in engineering applications. This work consists of three parts, in which three modified honeycombs are designed and analyzed. The objectives are to obtain honeycomb structures with improved specific stiffness and specific buckling resistance while considering the manufacturing feasibility. The objective of the first part is to develop analytical models for general case honeycombs with non-linear cell walls. Using spline curve functions, the model can describe a wide range of 2-D periodic structures with nonlinear cell walls. The derived analytical model is verified by comparing model predictions with other existing models, finite element analysis (FEA) and experimental results. Parametric studies are conducted by analytical calculation and finite element modeling to investigate the influences of the spline waviness on the homogenized properties. It is found that, comparing to straight cell walls, spline cell walls have increased out-of-plane buckling resistance per unit weight, and the extent of such improvement depends on the distribution of the spline’s curvature. The second part of this research proposes a honeycomb with laminated composite cell walls, which offer a wide selection of constituent materials and improved specific stiffness. Analytical homogenization is established and verified by FEA comparing the mechanical responses of a full-detailed honeycomb and a solid cuboid assigned with the calculated homogenization properties. The results show that the analytical model is accurate at a small computational cost. Parametric studies reveal nonlinear relationships between the ply thickness and the effective properties, based on which suggestions are made for property optimizations. The third part studies honeycomb structures with perforated cell walls. The homogenized properties of this new honeycomb are analytically modeled and investigated by finite element modeling. It is found that comparing to conventional honeycombs, honeycombs with perforated cell walls demonstrate enhanced in-plane stiffness, out-of-plane bending rigidity, out-of-plane compressive buckling stress, approximately the same out-of-plane shear buckling strength, and reduced out-of-plane stiffness. For the future design, empirical formulas, based on finite element results and expressed as functions of the perforation size, are derived for the mechanical properties and verified by mechanical tests conducted on a series of 3D printed perforated honeycomb specimens

Virasoro and Kac-Moody algebra in generic tensor network representations of 2d critical lattice partition functions

In this paper, we propose a general implementation of the Virasoro generators and Kac-Moody currents in generic tensor network representations of 2-dimensional critical lattice models. Our proposal works even when a quantum Hamiltonian of the lattice model is not available, which is the case in many numerical computations involving numerical blockings. We tested our proposal on the 2d Ising model, and also the dimer model, which works to high accuracy even with a fairly small system size. Our method makes use of eigenstates of a small cylinder to generate descendant states in a larger cylinder, suggesting some intricate algebraic relations between lattice of different sizes.Comment: 5+11 pages, 5+4 figure

Virasoro Generators in the Fibonacci Model Tensor Network -- Tackling Finite Size Effects

In this paper, we extend the method implementing Virasoro operators in a tensor network we proposed in arXiv:2205.04500 and test it on the Fibonacci model, which is known to suffer from far more finite size effects. To pick up the "seed" state that would flow to the stress tensor in the thermodynamic limit, we make use of the topological idempotent that projects the transfer matrix to the trivial sector. Combined with an optimization method, the seed state can be identified. We demonstrate that the descendant states in the Fibonacci model can be correctly generated with this approximate stress tensor, giving further evidence that the method applies more generally.Comment: 7+7 pages, 3+5 figure

Development of a Non-invasive Deep Brain Stimulator With Precise Positioning and Real-Time Monitoring of Bioimpedance

Methods by which to achieve non-invasive deep brain stimulation via temporally interfering with electric fields have been proposed, but the precision of the positioning of the stimulation and the reliability and stability of the outputs require improvement. In this study, a temporally interfering electrical stimulator was developed based on a neuromodulation technique using the interference modulation waveform produced by several high-frequency electrical stimuli to treat neurodegenerative diseases. The device and auxiliary software constitute a non-invasive neuromodulation system. The technical problems related to the multichannel high-precision output of the device were solved by an analog phase accumulator and a special driving circuit to reduce crosstalk. The function of measuring bioimpedance in real time was integrated into the stimulator to improve effectiveness. Finite element simulation and phantom measurements were performed to find the functional relations among the target coordinates, current ratio, and electrode position in the simplified model. Then, an appropriate approach was proposed to find electrode configurations for desired target locations in a detailed and realistic mouse model. A mouse validation experiment was carried out under the guidance of a simulation, and the reliability and positioning accuracy of temporally interfering electric stimulators were verified. Stimulator improvement and precision positioning solutions promise opportunities for further studies of temporally interfering electrical stimulation

Enhancing Working Memory Based on Mismatch Negativity Neurofeedback in Subjective Cognitive Decline Patients: A Preliminary Study

Mismatch negativity (MMN) is suitable for studies of preattentive auditory discriminability and the auditory memory trace. Subjective cognitive decline (SCD) is an ideal target for early therapeutic intervention because SCD occurs at preclinical stages many years before the onset of Alzheimer's disease (AD). According to a novel lifespan-based model of dementia risk, hearing loss is considered the greatest potentially modifiable risk factor of dementia among nine health and lifestyle factors, and hearing impairment is associated with cognitive decline. Therefore, we propose a neurofeedback training based on MMN, which is an objective index of auditory discriminability, to regulate sensory ability and memory as a non-pharmacological intervention (NPI) in SCD patients. Seventeen subjects meeting the standardized clinical evaluations for SCD received neurofeedback training. The auditory frequency discrimination test, the visual digital N-back (1-, 2-, and 3-back), auditory digital N-back (1-, 2-, and 3-back), and auditory tone N-back (1-, 2-, and 3-back) tasks were used pre- and post-training in all SCD patients. The intervention schedule comprised five 60-min training sessions over 2 weeks. The results indicate that the subjects who received neurofeedback training had successfully improved the amplitude of MMN at the parietal electrode (Pz). A slight decrease in the threshold of auditory frequency discrimination was observed after neurofeedback training. Notably, after neurofeedback training, the working memory (WM) performance was significantly enhanced in the auditory tone 3-back test. Moreover, improvements in the accuracy of all WM tests relative to the baseline were observed, although the changes were not significant. To the best of our knowledge, our preliminary study is the first to investigate the effects of MMN neurofeedback training on WM in SCD patients, and our results suggest that MMN neurofeedback may represent an effective treatment for intervention in SCD patients and the elderly with aging memory decline

Association between triglyceride glucose-body mass index and heart failure in subjects with diabetes mellitus or prediabetes mellitus: a cross-sectional study

BackgroundThe triglyceride glucose-body mass index (TyG-BMI) is a surrogate indicator of insulin resistance. However, the association of TyG-BMI with heart failure (HF) in individuals with diabetes mellitus or prediabetes mellitus is unknown.MethodsThis study included 7,472 participants aged 20–80 years old with prediabetes or diabetes from the National Health and Nutrition Examination Survey (2007–2018). The TyG-BMI was calculated as Ln [triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI, and individuals were categorized into tertiles based on TyG-BMI levels. The relationship of TyG-BMI with HF was analyzed using multiple logistic regression models. Subgroup analyses were stratified by gender, age, hypertension, and diabetes mellitus status.ResultsThis cross-sectional study had 7,472 participants (weighted n = 111,808,357), including 329 HF participants. Participants with a high TyG-BMI were prone to HF. The highest tertile group with a fully adjusted model was more likely to have HF compared to the lowest tertile group (odds ratio [OR], 2.645; 95% CI, 1.529–4.576). Restricted cubic spline analysis showed a significant dose-response relationship between TyG-BMI and HF (P < 0.001). In subgroup analyses, similar results were seen in terms of age (≥50 years old), gender, hypertension, and diabetes mellitus status.ConclusionA high TyG-BMI is significantly associated with HF risk in participants with diabetes mellitus or prediabetes mellitus