Factors Affecting Thermal Shrinkage of Mouthguard Sheet during Thermoforming: Model Shape and Sheet Material Thickness

The effectiveness and safety of the mouthguard depend on the sheet material thickness. The thickness of the thermoformed mouthguard is affected by the model undercut and the thermal shrinkage that occurs when the extruded-molded sheet is reheated. The aim of this study was to clarify the influence of the undercut amount of the model and the thickness of the sheet material on the thermal shrinkage of the extruded sheet. The mouthguard sheet used ethylene-vinyl acetate resin with a thickness of 4.0 mm (4M) and 3.0 mm (3M) and was manufactured by extrusion molding. The working models were three hard gypsum models with the undercut amount on the labial side trimmed to 0? (U0), 10? (U10), and 20? (U20). Mouthguard thickness after vacuum formation was compared between the conditions formed so that the extrusion direction was vertical (condition V) or parallel (condition P) to the model midline. Differences in the reduction rate of the mouthguard thicknesses of the labial and buccal side depending on the sheet extrusion direction, model angle, and sheet material thickness were analyzed by three-way ANOVA and Bonferroni method. The reduction rate of the thickness in condition P was significantly greater than in condition V under all conditions except U0-4M on the labial side and U0-4M and U10-4M on the buccal side. In all models, the reduction rate of the thicknesses was significantly greater in 3M than in 4M in the same extrusion direction. In both 4M and 3M, the reduction rate of the thicknesses tended to increase as the amount of undercut increased in each extrusion direction. This study suggested that a model with a large amount of undercut on the labial side or a thin sheet had a significant effect on the thermal shrinkage of the mouthguard sheet during thermoforming, which leads to the thinning of the mouthguard.

Electron Shape Calculated for the Dual-Charge Dual-Mass Model

A model for the internal structure of the electron using classical physics equations has been previously published by the author. The model employs both positive and negative charges and positive and negative masses. The internal attributes of the electron structure were calculated for both ring and spherical shapes. Further examination of the model reveals an instability for the ring shape. The spherical shape appears to be stable, but relies on tensile or compressive forces of the electron material for stability. The model is modified in this document to eliminate the dependency on material forces. Uniform stability is provided solely by balancing electrical and centrifugal forces. This stability is achieved by slightly elongating the sphere along the spin axis to create a prolate ellipsoid. The semi-major axis of the ellipsoid is the spin axis of the electron, and is calculated to be 1.20% longer than the semi-minor axis, which is the radius of the equator. Although the shape deviates slightly from a perfect sphere, the electric dipole moment is zero. In the author’s previously published document, the attributes of the internal components of the electron, such as charge and mass, were calculated and expressed as ratios to the classically measured values for the composite electron. It is interesting to note that all of these ratios are nearly the same as the inverse of the Fine Structure Constant, with differences of less than 15%. The electron model assumed that the outer surface charge was fixed and uniform. By allowing the charge to be mobile and the shape to have a particular ellipticity, it is shown that the calculated charge and mass ratios for the model can be exactly equal to the Fine Structure Constant and the Constant plus one. The electron radius predicted by the model is 15% greater than the Classical Electron Radius.

基于MDL Shape Model及EFD的行人轮廓2D＋time表示

针对智能监控的行人轮廓特征提取,先利用MDL shape model得到紧致但能充分表征轮廓几何特征标志点之间的对应关系,再利用椭圆傅里叶分解把行人轮廓表示为一系列不同频率下椭圆傅里叶系数组成的向量,最后得到行人2D+time轮廓的描述向量。实验结果表明,此方法不但可以在几何上直观地表示行人轮廓,而且大大降低了轮廓向量的维数。

2-D IMAGE-BASED VOLUMETRIC MODELING FOR PARTICLE OF RANDOM SHAPE

In this paper, an approach to predicting randomly-shaped particle volume based on its two-Dimensional (2-D) digital image is explored. Conversion of gray-scale image of the particles to its binary coun-terpart is first performed using backlighting technique. The silhouette of particle is thus obtained, and conse-quently, informative features such as particle area, centroid and shape-related descriptors are collected. Several dimensionless parameters are defined, and used as regressor variables in a multiple linear regression model to predict particle volume. Regressor coefficients are found by fitting to a randomly selected sample of 501 parti-cles ranging in size from 4.75mm to 25mm. The model testing experiment is conducted against a different ag-gregate sample of the similar statistical properties, the errors of the model-predicted volume of the batch is within ±2%.

Incorporating shape constraints in generalized additive modelling of the height-diameter relationship for Norway spruce

Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height （dbh） can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter （h-d） models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods： We develop unconstrained generalized additive models （GAM） and shape constrained generalized additive models （SCAM） for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results： Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand, The definition of constraints leads only to marginal or minor decline in the model statistics like AIC An observed structured spatial trend in tree height is modelled via 2-dimensional surface fitting. Conclusions： We demonstrate that the SCAM approach allows optimal regression modelling flexibility similar to the standard GAM but with the additional possibility of defining specific constraints for the model effects. The longitudinal character of the model allows for tree height imputation for the current status of forests but also for future tree height prediction.

Detecting winter canola(Brassica napus) phenological stages using an improved shape-model method based on time-series UAV spectral data

Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on the flowering stage, using its apparent structure features and colors. Additional phenological stages have been largely overlooked. The objective of this study was to improve a shape-model method(SMM) for extracting winter canola phenological stages from time-series top-of-canopy reflectance images collected by an unmanned aerial vehicle(UAV). The transformation equation of the SMM was refined to account for the multi-peak features of the temporal dynamics of three vegetation indices(VIs)(NDVI, EVI, and CI). An experiment with various seeding scenarios was conducted, including four different seeding dates and three seeding densities. Three mathematical functions: asymmetric Gaussian function(AGF), Fourier function, and double logistic function, were employed to fit timeseries vegetation indices to extract information about phenological stages. The refined SMM effectively estimated the phenological stages of canola, with a minimum root mean square error(RMSE) of 3.7 days for all phenological stages. The AGF function provided the best fitting performance, as it captured multiple peaks in the growth dynamics characteristics for all seeding date scenarios using four scaling parameters. For the three selected VIs, CIred-edgeachieved the greatest accuracy in estimating the phenological stage dates. This study demonstrates the high potential of the refined SMM for estimating winter canola phenology.

Modeling of the Shape Forming of Composite Roll

A shape modeling of spray formed composite roll, which is utilized to predict the shape and dimension of roll during spray forming process, is developed in this paper. The influences of the principal spray forming parameters, such as the spatial distribution of melt mass flux, spray distance, rotating and translating speeds of substrate bar etc. , on the geometry and dimension of spray formed product were investigated.

Roll System and Stock's Multi-parameter Coupling Dynamic Modeling Based on the Shape Control of Steel Strip

The existence of rolling deformation area in the rolling mill system is the main characteristic which dis- tinguishes the other machinery. In order to analyze the dynamic property of roll system＇s flexural deformation, it is necessary to consider the transverse periodic movement of stock in the rolling deformation area which is caused by the flexural deformation movement of roll system simul- taneously. Therefore, the displacement field of roll system and flow of metal in the deformation area is described by kinematic analysis in the dynamic system. Through intro- ducing the lateral displacement function of metal in the deformation area, the dynamic variation of per unit width rolling force can be determined at the same time. Then the coupling law caused by the co-effect of rigid movement and flexural deformation of the system structural elements is determined. Furthermore, a multi-parameter coupling dynamic model of the roll system and stock is established by the principle of virtual work. More explicitly, the cou- pled motion modal analysis was made for the roll system. Meanwhile, the analytical solutions for the flexural defor- mation movement＇s mode shape functions of rolls are discussed. In addition, the dynamic characteristic of the lateral flow of metal in the rolling deformation area has been analyzed at the same time. The establishment ofdynamic lateral displacement function of metal in the deformation area makes the foundation for analyzing the coupling law between roll system and rolling deformation area, and provides a theoretical basis for the realization of the dynamic shape control of steel strip.

Longitudinal height-diameter curves for Norway spruce, Scots pine and silver birch in Norway based on shape constraint additive regression models

Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pendula Roth） in Norwa are presented. The Norwegian National Forest Inventory （NFI） is used as data base for estimating the model parameters. The derived models are developed to enable spatially explicit and site sensitive tree height imputatio in forest inventories as well as future tree height predictions in growth and yield scenario simulations. Methods： Generalized additive mixed models （gamm） are employed to detect and quantify potentially non-linear effects of predictor variables. In doing so the quadratic mean diameter serves as longitudinal covariate since stand ag as measured in the NFI, shows only a weak correlation with a stands developmental status in Norwegian forests. Additionally the models can be locally calibrated by predicting random effects if measured height-diameter pairs are available. Based on the model selection of non-constraint models, shape constraint additive models （scare） were fit tc incorporate expert knowledge and intrinsic relationships by enforcing certain effect patterns like monotonicity. Results： Model comparisons demonstrate that the shape constraints lead to only marginal differences in statistical characteristics but ensure reasonable model predictions. Under constant constraints the developed models predict increasing tree heights with decreasing altitude, increasing soil depth and increasing competition pressure of a tree. / two-dimensional spatially structured effect of UTM-coordinates accounts for the potential effects of large scale spatial correlated covariates, which were not at our disposal. The main result of modelling the spatially structured effect is lower tree height prediction for coastal sites and with increasing latitude. The quadratic mean diameter affects both the level and the slope of the height-diameter curve and both effects are positive. Conclusions： In this investigation it is assumed that model effects in additive modelling of height-diameter curves which are unfeasible and too wiggly from an expert point of view are a result of quantitatively or qualitatively limited data bases. However, this problem can be regarded not to be specific to our investigation but more general since growth and yield data that are balanced over the whole data range with respect to all combinations of predictor variables are exceptional cases. Hence, scare may provide methodological improvements in several applications by combining the flexibility of additive models with expert knowledge.

Improved shape hardening function for bounding surface model for cohesive soils

A shape hardening function is developed that improves the predictive capabilities of the generalized bounding surface model for cohesive soils, especially when applied to overconsolidated specimens. This improvement is realized without any changes to the simple elliptical shape of the bounding surface, and actually reduces the number of parameters associated with the model by one.

Flow field simulation and establishment for mathematical models of flow area of spool valve with sloping U-shape notch machined by different methods

Precise function expression of the flow area for the sloping U-shape notch orifice versus the spool stroke was derived.The computational fluid dynamics was used to analyze the flow features of the sloping U-shape notch on the spool,such as mass flow rates,flow coefficients,efflux angles and steady state flow forces under different operating conditions.At last,the reliability of the mathematical model of the flow area for the sloping U-shape notch orifice on the spool was demonstrated by the comparison between the orifice area curve derived and the corresponding experimental data provided by the test.It is presented that the bottom arc of sloping U-shape notch(ABU) should not be omitted when it is required to accurately calculate the orifice area of ABU.Although the theoretical flow area of plain bottom sloping U-shape notch(PBU) is larger than that of ABU at the same opening,the simulated mass flow and experimental flow area of ABU are both larger than these of PBU at the same opening,while the simulated flow force of PBU is larger than that of ABU at the same opening.Therefore,it should be prior to adapt the ABU when designing the spool with proportional character.

Incorporating S-shaped testing-effort functions into NHPP software reliability model with imperfect debugging

Testing-effort（TE） and imperfect debugging（ID） in the reliability modeling process may further improve the fitting and prediction results of software reliability growth models（SRGMs）. For describing the S-shaped varying trend of TE increasing rate more accurately, first, two S-shaped testing-effort functions（TEFs）, i.e.,delayed S-shaped TEF（DS-TEF） and inflected S-shaped TEF（IS-TEF）, are proposed. Then these two TEFs are incorporated into various types（exponential-type, delayed S-shaped and inflected S-shaped） of non-homogeneous Poisson process（NHPP）SRGMs with two forms of ID respectively for obtaining a series of new NHPP SRGMs which consider S-shaped TEFs as well as ID. Finally these new SRGMs and several comparison NHPP SRGMs are applied into four real failure data-sets respectively for investigating the fitting and prediction power of these new SRGMs.The experimental results show that：（i） the proposed IS-TEF is more suitable and flexible for describing the consumption of TE than the previous TEFs;（ii） incorporating TEFs into the inflected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S-shaped NHPP SRGMs;（iii） the inflected S-shaped NHPP SRGM considering both IS-TEF and ID yields the most accurate fitting and prediction results than the other comparison NHPP SRGMs.

ANN Based Predictive Modelling of Weld Shape and Dimensions in Laser Welding of Galvanized Steel in Butt Joint Configurations

The quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser welding. Accurate and efficient model to perform non-destructive quality estimation is an essential part of this assessment. This paper presents a structured and comprehensive approach developed to design an effective artificial neural network based model for weld bead geometry prediction and control in laser welding of galvanized steel in butt joint configurations. The proposed approach examines laser welding parameters and conditions known to have an influence on geometric characteristics of the welds and builds a weld quality prediction model step by step. The modelling procedure begins by examining, through structured experimental investigations and exhaustive 3D modelling and simulation efforts, the direct and the interaction effects of laser welding parameters such as laser power, welding speed, fibre diameter and gap, on the weld bead geometry (i.e. depth of penetration and bead width). Using these results and various statistical tools, various neural network based prediction models are developed and evaluated. The results demonstrate that the proposed approach can effectively lead to a consistent model able to accurately and reliably provide an appropriate prediction of weld bead geometry under variable welding conditions.

Modeling the keyhole shape and dimension in plasma arc welding

It is of great significance to model the keyhole shape and dimensions to optimize the plasma arc welding process parameters. In this study, through employing a combined volumetric heat source mode, the weld pool in keyhole plasma arc welding is determined firstly, and then the dynamic force-balance condition on the interface between the plasma jet and the molten metal is dealt with in describing the keyhole formation inside the weld pool. The effects of welding current on the shape and size of keyhole are numerically analyzed. The sharp transformation from a partial keyhole to a full-penetration keyhole is quantitatively demonstrated.

A macroscopic multi-mechanism based constitutive model for the thermo-mechanical cyclic degeneration of shape memory effect of NiTi shape memory alloy

A macroscopic based multi-mechanism constitutive model is constructed in the framework of irreversible thermodynamics to describe the degeneration of shape memory effect occurring in the thermo-mechanical cyclic deformation of NiTi shape memory alloys (SMAs). Three phases, austenite A, twinned martensite and detwinned martensite , as well as the phase transitions occurring between each pair of phases (, , , , and are considered in the proposed model. Meanwhile, two kinds of inelastic deformation mechanisms, martensite transformation-induced plasticity and reorientation-induced plasticity, are used to explain the degeneration of shape memory effects of NiTi SMAs. The evolution equations of internal variables are proposed by attributing the degeneration of shape memory effect to the interaction between the three phases (A, , and and plastic deformation. Finally, the capability of the proposed model is verified by comparing the predictions with the experimental results of NiTi SMAs. It is shown that the degeneration of shape memory effect and its dependence on the loading level can be reasonably described by the proposed model.

Pipe Shape Solution of Faddeev Model

利用 Faddeev 模型等价于的结果我苏(2 ) Skyrme 模型的声音的部门酒吧那里的数字电流到处消失，包括 Faddeev 模型的旋涡答案的一些准确答案被讨论。答案被第一个 Chern 数字分类。当 Chern 数字等于 2 时，新 multisoliton 答案被获得，答案的精力密度的管子形状分发被发现。

DEFICIENT INFORMATION MODELING OF MECHANICAL PRODUCTS FOR CONCEPTUAL SHAPE DESIGN

In allusion to the deficient feature of product information in conceptualdesign, a framework of deficient information modeling for conceptual shape design is put forward,which includes qualitative shape modeling (a qualitative solid model), uncertain shape modeling (anuncertain relation model) and imprecise shape modeling (an imprecise region model). In theframework, the qualitative solid model is the core, which represents qualitatively (using symbols)the conceptual shapes of mechanical products. The uncertain relation model regarding domainrelations as objects and the imprecise region model regarding domains as objects are used to dealwith the uncertain and imprecise issues respectively, which arise from qualitative shape modeling orexist in product information itself.