Development and Validation of Scale-resolving Computational Models Relevant to IC-engine Flow Configurations

Turbulent swirling and tumbling flow currents are dominating phenomena in the internal combustion engine systems. These occurrences have great influence on the quality of fuel-air mixture and combustion. Concerning the employment of the CFD (Computation Fluid Dynamics) methods for relevant flow simulations, the LES (Large Eddy Simulation) method is becoming more and more the computational tool in the field of engine design and optimization, thanks to its predictive capability to better estimate the rotational characteristics and cycle-to-cycle variations. This method com- pensates the disadvantages of classical RANS (Reynolds Averaging Navier- Stokes) models of turbulence by resolving the instantaneous flow structures. However, it is accompanied by uncertainties concerning the required mesh resolution. The hybrid eddy-resolving methods, which gain increased popularity in the CFD community, are conceptualized to combine the advantageous characteristics of RANS and LES. This leads to an advanced modeling strategy for complex flow configurations at higher Reynolds numbers. On one hand, the large flow structure is captured in accordance with the applied grid spacing; furthermore, the small structures are computed by an appropriately modified RANS model of turbulence. In the present work, an eddy-resolving model, denoted as ”Very Large Eddy Simulation” (VLES) according to Speziale (1998), is formulated and validated. The validations are preliminary carried out by computing some important generic configurations as decay of homogeneous isotropic turbulence (Tavoularis et al. (1997); underlying the basic turbulence law concerning its natural decay), plane channel flow (Moser et al. (1999); most important representative of wall-bounded flow configurations for studying the near-wall turbulence) and flow over a periodical arrangement of two-dimensional hills (Temmermann et al. (2003); separation at a curved continuous surface) to check the model’s predictive capabilities. Furthermore, a real three-dimensional swirling flow in a vortex tube with different shapes of outlet orifices (investigated experimentally by Grundmann et al.,2012) and a generic piston-cylinder assembly focusing on the compression of a tumbling vortex generated during the intake phase (experiment by Borèe et al., 2001) were computed to examine whether the relevant flow properties can be correctly captured computationally. Finally, an industrial engine system (not accounting for the spray and combustion) for which the experimental reference is provided by Baum et al. (2013) is considered for the final validation to see the suitability of the turbulence models formulated presently for the application in internal combustion engines. Compared to both the Partially Averaged Navier-Stokes (PANS) and RANS methods (the four-equation k-ζ-f model of Hanjalić et al., 2004, was used as the RANS constituent in the present hybrid scheme; in addition the pure LES and RANS computations, the latter employing the same model as the PANS and VLES, have been performed), the present eddy-resolving model exhibits better reproduction of the corresponding reference data. The VLES, which suppresses the modeled turbulent properties to the level of subgrid-scale explicitly by appropriately modifying the turbulent viscosity model, is especially capable of triggering the fluctuation in the entire flow region, whereas PANS shows a too diffusive representation. These features enable the calculation to preserve the LES operating mode in the configurations where the employment of a RANS model is not satisfactory. Furthermore, the VLES method utilizes the currently computed (instantaneous) values without having to extract the averaged properties. This also avoids the problem the PANS method has in the time-dependent calculation of flows with moving boundaries

Mycobacterium tuberculosis and M. bovis infection in Feedlot Deer (Cervus unicolor swinhoei and C. nippon taiouanus) in Taiwan

Background/purposeMycobacterium bovis frequently infects wild and farm deer species with tuberculosis. This study investigated mycobacterial infection in two native deer species Cervus unicolor swinhoei (Formosan Sambar, Sambar) and C. nippon taiouanus (Formasan Sika, Sika).MethodsBased on different sampling sources of 19 intradermal tuberculin test (ITT) Sambar, mycobacterial infection and/or species were detected by acid-fast stain, duplex polymerase chain reaction (PCR) and multiplex nested PCR (mnPCR) methods, traditional mycobacterial culture and gross lesion. Blood samples of 167 Sambar deer and 147 Sika deer were then tested by duplex PCR and mnPCR methods to investigate the prevalence of mycobacterial infection. Sequence variations of these mycobacterial species were analyzed as well.ResultsDuplex PCR and mnPCR assays could differentiate between MTBC (M. bovis and M. tuberculosis) and M. avium, as well as between M. bovis and M. tuberculosis, respectively. These PCR methods showed a higher detection rate than traditional culture and matched the gross lesions examined in 19 ITT-examined Sambar. Therefore, the mycobacterial infection in blood samples of 314 deer samples was detected using these PCR methods. Duplex PCR and mnPCR showed an identical prevalence of 16.1% in Sambar and 8.2% in Sika and a significant difference in prevalence between these two deer species. M. bovis and M. tuberculosis were the species detected in feedlot Sambar and Sika. M. tuberculosis was found only and first in Sambar fed in central Taiwan. Sequence analysis revealed diverse genetic variations in M. bovis and M. tuberculosis associated with deer subspecies.ConclusionMultiplex PCR methods were established, and M. bovis and M. tuberculosis were identified in feedlot deer in Taiwan. Sequence variations indicated diverse sources of both mycobacterial species

EFFECT OF DIFFERENT TIBIA ANGLES TO LOADING OF KNEE DURING SPLIT SQUAT

The aim of this study was to investigate the difference of knee joint force and moment during split squats of different front tibia angles. Twelve healthy male college students performed six repetitions of four different split squat types with a standard additional load of 25% BW added using a barbell. Using 10 camera 3D motion capture system and a force plate to collect data. The peak force and moment of knee flexion (sagittal plane) were calculated by using self-designed MATLAB programs. One-way ANOVA test was undertaken using SPSS 20.0 statistical software. The analysis results of the study indicated that all kinetic parameters of the four types split squats were achieved high significant differences (p less than .000). A better understanding of different loading in specific joints and correct exercise execution during training will help protecting practitioners from sport injury

EFFECTS OF PLYOMTRIC TRAIN lNG ON MUSCLE FATIGUE AND MAXIMAL RATE OF FORCE DEVELOPMENT OF LOWER-LIMB

The purpose of this study was to examine the effects of ploymetric training on muscle fatigue and maximal rate of force development in volleyball players. Ten college volleyball players volunteered to participate in this study and underwent a 6-week plyometric training. The BTS free EMG and force-plate were used to evaluate the median frequency (MDF) of the rectus femoris (RF), anterior tibialis (AT), lateral gastrocnemius (LG), biceps femoris (BF) and maximum rate of force development (mRFD). The results revealed that the plyometric training significantly improves the MDF of RF and AT and mRFD. This study demonstrated hat by using plyometric training could facilitate the mRFD and postpone muscle fatigue for trained volleyball players

THE ACUTE EFFECT OF WHOLE BODY VIBRATION TRAINING ON AGILITY, SPEED AND POWER IN MALE VOLLEYBALL PLAYERS

The purpose of this study was to examine the acute effect of whole body vibration training on agility, speed and power in male volleyball players. Ten college volleyball players volunteered to participate in this study. The vibration training (VT) consisted of 60% with 28 Hz frequencies and 1Omm amplitudes. Counter movement jump (CMJ), blocking agility test (BAT), agility test (AT) and 10 meters sprinting (1 OMS) were performed at pre-test and post-test (60s rest). The peak force (PF). mean force (MF), maximum rate of force development (mRFD) and relative net impulse (RNI) from the CMJs were computed. A repeated measures ANOVA was applied to obtain the variables. The present study indicated that the WBV significantly improves the MF, mRFD and BAT parameters of CMJ and BAT performances excluding the PF. Speed and agility does not seem to be enhanced by VT

Paxillin facilitates timely neurite initiation on soft-substrate environments by interacting with the endocytic machinery.

Neurite initiation is the first step in neuronal development and occurs spontaneously in soft tissue environments. Although the mechanisms regulating the morphology of migratory cells on rigid substrates in cell culture are widely known, how soft environments modulate neurite initiation remains elusive. Using hydrogel cultures, pharmacologic inhibition, and genetic approaches, we reveal that paxillin-linked endocytosis and adhesion are components of a bistable switch controlling neurite initiation in a substrate modulus-dependent manner. On soft substrates, most paxillin binds to endocytic factors and facilitates vesicle invagination, elevating neuritogenic Rac1 activity and expression of genes encoding the endocytic machinery. By contrast, on rigid substrates, cells develop extensive adhesions, increase RhoA activity and sequester paxillin from the endocytic machinery, thereby delaying neurite initiation. Our results highlight paxillin as a core molecule in substrate modulus-controlled morphogenesis and define a mechanism whereby neuronal cells respond to environments exhibiting varying mechanical properties

VI-Band Follow-Up Observations of Ultra-Long-Period Cepheid Candidates in M31

The ultra-long period Cepheids (ULPCs) are classical Cepheids with pulsation periods exceeding $\approx 80$ days. The intrinsic brightness of ULPCs are ~1 to ~3 mag brighter than their shorter period counterparts. This makes them attractive in future distance scale work to derive distances beyond the limit set by the shorter period Cepheids. We have initiated a program to search for ULPCs in M31, using the single-band data taken from the Palomar Transient Factory, and identified eight possible candidates. In this work, we presented the VI-band follow-up observations of these eight candidates. Based on our VI-band light curves of these candidates and their locations in the color-magnitude diagram and the Period-Wesenheit diagram, we verify two candidates as being truly ULPCs. The six other candidates are most likely other kinds of long-period variables. With the two confirmed M31 ULPCs, we tested the applicability of ULPCs in distance scale work by deriving the distance modulus of M31. It was found to be $\mu_{M31,ULPC}=24.30\pm0.76$ mag. The large error in the derived distance modulus, together with the large intrinsic dispersion of the Period-Wesenheit (PW) relation and the small number of ULPCs in a given host galaxy, means that the question of the suitability of ULPCs as standard candles is still open. Further work is needed to enlarge the sample of calibrating ULPCs and reduce the intrinsic dispersion of the PW relation before re-considering ULPCs as suitable distance indicators.Comment: 13 pages, with 14 Figures and 4 Tables (one online table). AJ accepte

A moment kernel machine for clinical data mining to inform medical decision making

Machine learning-aided medical decision making presents three major challenges: achieving model parsimony, ensuring credible predictions, and providing real-time recommendations with high computational efficiency. In this paper, we formulate medical decision making as a classification problem and develop a moment kernel machine (MKM) to tackle these challenges. The main idea of our approach is to treat the clinical data of each patient as a probability distribution and leverage moment representations of these distributions to build the MKM, which transforms the high-dimensional clinical data to low-dimensional representations while retaining essential information. We then apply this machine to various pre-surgical clinical datasets to predict surgical outcomes and inform medical decision making, which requires significantly less computational power and time for classification while yielding favorable performance compared to existing methods. Moreover, we utilize synthetic datasets to demonstrate that the developed moment-based data mining framework is robust to noise and missing data, and achieves model parsimony giving an efficient way to generate satisfactory predictions to aid personalized medical decision making