Developing the concept of linear function: one student’s experiences with dynamic physical models

The current industrial practice in design of the injected pultrusion (IP) process involves costly trial and error procedures, hitherto unavoidable in the absence of established process models. Even for well understood processes, economic design has traditionally used steady-state physical models, separately followed by control system synthesis using simpler dynamic models. This work describes the development of a rigorous model-based design algorithm for the IP process by integration of economics, operability, and environmental considerations. In our previous work, a 3D dynamic physical model of the IP process was experimentally validated on a bench-scale setup. Using this validated model, we can now reduce the time and expenses associated with a purely experimental approach. An understanding of processing economics leads to throughput rate maximization as the desired economic objective. We develop a multiobjective optimization algorithm that maximizes this objective function, using a response surface methodology with iterative meshing to determine optimal equipment specifications (die dimensions, puller ratings) and processing condition parameters (heating zone temperatures, resin injection pressure). Retrofit design of the bench-scale setup promised a tenfold increase in throughput rate. Calculation of theoretical limit on throughput rates from intrinsic resin cure kinetics supported this finding. Various metrics were proposed to evaluate quality of design in a distributed-parameter sense. Sensitivity studies verified that the economic optimum is also robust to a wide range of expected process disturbances. An analysis of process instrumentation revealed the need for additional measurements. We propose resin flow-rate and cutting force measurements for void and cure sensing respectively. This research is a first step to the integration of design and control for a complex multiphase process using a single dynamic physical model. The integration offers several benefits over current design practices, and highlights the potential for increased productivity in polymer composites manufacturing.

The application of endovascular aortic aneurysm repair has expanded over the last decade. However, the long-term performance of stent grafts, in particular durable fixation and sealing to the aortic wall, remains the main concern of this treatment. The sealing and fixation are challenged at every heartbeat due to downward and radial pulsatile forces. Yet knowledge on cardiac-induced dynamics of implanted stent grafts is sparse, as it is not measured in routine clinical follow-up. Such knowledge is particularly relevant to perform fatigue tests, to predict failure in the individual patient and to improve stent graft designs. Using a physical dynamic stent graft model in an anthropomorphic phantom, we have evaluated the performance of our previously proposed segmentation and registration algorithm to detect periodic motion of stent grafts on ECG-gated (3D+t) CT data. Abdominal aortic motion profiles were simulated in two series of Gaussian based patterns with different amplitudes and frequencies. Experiments were performed on a 64-slice CT scanner with a helical scan protocol and retrospective gating. Motion patterns as estimated by our algorithm were compared to motion patterns obtained from optical camera recordings of the physical stent graft model in motion. Absolute errors of the patterns' amplitude were smaller than 0.28 mm. Even the motion pattern with an amplitude of 0.23 mm was measured, although the amplitude of motion was overestimated by the algorithm with 43%. We conclude that the algorithm performs well for measurement of stent graft motion in the mm and sub-mm range. This ultimately is expected to aid in patient-specific risk assessment and improving stent graft designs.

The role of vibrato in the characterization of violin tone will be considered from both a physical acoustics and perceptual viewpoint. Musical examples of individual waveforms from violins of widely different qualities will be used to demonstrate the importance of vibrato and other temporal fluctuations in the recognition of the violin as a specific musical instrument and, by inference, of its perceived tonal quality also. Dynamic physical models will be introduced to describe the waveforms of sounds produced by the bowed string when vibrato is used. The sound produced by an individual instrument will be shown to be critically dependent on both the positions and the Q values of the acoustically important resonances excited, in addition to random noise generated by the bowing action. It will be argued that the temporal fluctuations in the sound of a violin played with vibrato are just as important as the temporal fluctuations associated with the very strong frequency-dependence of the directivity of the violin. Weinreich has emphasized the importance of the latter effect in any realistic reproduction of the sound of a violin.

In recent years, science education has placed increasing importance on learners' mastery of scientific reasoning. This growing emphasis presents a challenge for both developers and users of assessments. We report on our effort around the conceptualization, development, and testing the validity of an assessment of students' ability to reason around physical dynamic models in Earth Science. Building from the research literature on analogical mapping and informed by the current perspectives on learning progressions, we present a three‐tiered construct describing the increasing sophistication of students' analogical reasoning around the correspondences and non‐correspondences between models and the Earth System: at the level of entities (Level 1), configurations in space or relative motion of entities (Level 2), and the mechanism or cause for observed phenomena (Level 3). Grounded in a construct‐centered design approach, we describe our process for developing assessments in order to examine and validate this construct, including how we selected topics and models, designed items, and developed outcome spaces. We present the specific example of one assessment centered on moon phases, which was administered to 164 8th and 9th grade Earth Science students as a pre/postmeasure. Two hundred ninety‐four responses were analyzed using a Rasch modeling approach. Item difficulties and student proficiency scores were calculated and analyzed regarding their relative performance with respect to the three levels of the construct. The analysis results provided initial evidence in support of the construct as conceived, with students displaying a range of analogical reasoning spanning all three construct levels. It also identified problematic items that merit further examination. Overall, the assessment has provided us the opportunity to better describe and frame the cognitive uses of models by students during learning situations in Earth Science. Implications for instruction and future directions for research in this area are discussed. © 2012 Wiley Periodicals, Inc. J Res Sci Teach 49: 713–743, 2012

According to the boundary layer observations of three stations (Garze, Damxung and Qamdu) and relevant earth satellite, radiosonde and surface observations during the intensive observational period (IOP) of the second Tibetan (Qinghai-Xizang) Plateau Experiment of atmospheric science (TIPEX), the land-air physical process and dynamic model on the Tibetan Plateau were comprehensively analyzed in this study. The dynamic characteristics of boundary layer and the rules of turbulent motion on the plateau were illustrated. The characteristics of distributions of wind speed and direction with mutiple-layer structure and deep convective mixed layer on the plateau, the strong buoyancy effect in turbulent motion on the plateau on which the air density is obviously smaller than on the plain, and the Ekman spiral and its dynamic pump effect of the plateau deep boundary layer have been found. The local static distribution of water vapor and the horizontal advection of water vapor in the plateau boundary layer were studied. The abnomal thermodynamic structure on the plateau surface and boundary layer, including the plateau strong radiation phenomenon and strong heating source characteristics of the middle plateau, was also analyzed. The authors synthesized the above dynamic and thermodynamic structures of both surface and boundary layers on the plateau and posed the comprehensive physical model of the turbulence and convective mixture mechanism on the plateau boundary layer. The characteristics of formation, development and movement for convective cloud cluster over the plateau influencing floods in the Yangtze River area of China were studied. The conceptual model of dynamic and thermodynamic structures of turbulent motion and convective plume related to the frequent occurrence of “pop-corn-like” cloud system is given as well.

Dynamic forecasting model of a hybrid photovoltaic/gravity energy storage system for residential applications

Modern Diesel engines with exhaust gas recirculation have achieved a significant progress in intake system, fuel consumption and emissions. So the process became more complex. Therefore, fault detection and diagnosis is difficult to be done and need to be improved. This contribution shows a system of fault detection and diagnosis methods for diesel engines based on physical model and data-driven model. By applying physical dynamic process models, identification with local linear model tree (LOLIMOT), data-driven models and residuals are generated by parity equations. Measured data in fault-free operation is used to build data-driven models. Detectable deflections of these residuals lead to symptoms which are the basis for the detection of faults. In final applications look-up tables can be generated using data-driven models. Experiments with a diesel engine intake system on MATLAB have demonstrated the detection and diagnosis of faults is suitability for application with reasonable calculation effort.

The hot compression of A-100 steel at 850–1150°C and strain rate of 0.01–10 s−1 was tested on a Gleeble-3800 thermal simulation machine to determine the corresponding true stress–strain curve. Based on theoretical calculation, the dislocation density factor was introduced into the Avrami equation and thereby a dynamic recovery physical constitutive relational model based on dislocation density theory was established. Then the hot deformation behaviour of A-100 steel was predicted (correlation coefficient R = 0.9964 with an average absolute relative error AARE = 4.0923%). The structures after hot compression were observed by electron backscattered diffraction and found to be lath-shaped martensite and austenite. With an increase of temperature and deceleration of strain rate, the proportions of large-angle boundaries and substructures increased and the softening mechanism became dominated by dynamic recovery.

A physical model and dynamic simulation models of a solar phase-change heat storage heating system with a plate solar collector, phase-change material (PCM) storage tank, plate heat exchanger, and auxiliary heat sources were established. A control strategy and numerical models for each of seven different operation modes that cover the entire heating season of the system were developed for the first time. The seven proposed operation modes are Mode 1: free cooling; Mode 2: reservation of heat absorbed by the solar collector in the PCM storage tank when there is no heating demand; Mode 3: direct supply of the heating demand by the solar collector; Mode 4: use of the heat absorbed by the solar collector to meet the heating demands, with the excess heat stored in the PCM storage tank; Mode 5: use of heat stored in the PCM storage tank to meet the heating demands, Mode 6: combined use of heat stored in the PCM storage tank and the auxiliary heating sources to meet the heating demands; and Mode 7: exclusive use of the auxiliary heat sources in order to meet the heating demands. Mathematical models were established for each of the above seven operation modes, taking into consideration the effects of the outdoor meteorological parameters and terminal load on the heating system. The real-time parameters for the entire heating season of the system with respect to the different operation modes can be obtained by solving the simulation models, and used as reference for the optimal design and operation of the actual system.

Based on the physical dynamic properties model of the intake system (from the state equation and measurement equation) and the intake system model and the statistical properties assumption of sensor noise, the measured data was mapped to the state space. Then using the state predictor, through the EKF (Extended Kalman Filter) , preprocessing the data from the intake manifold absolute pressure sensor, through the model transformation, unit transformation the sensor's output signal is converted to the state variable describing the amount of intake air, then according to the established state equation of the intake system and the mathematical model of the measuring physical properties, under some criterias for optimal estimation, the optimal estimation was carried out so that the state vector and measurement vector achieve the best fit, to obtain optimal estimates of intake air amount.

Hybrid structures offer a versatile design platform for semiconductor micro‐nano devices, enabling precise modulation of charge transport and energy conversion/storage. However, optimizing the spatial charge response of hybrids via band structure engineering remains challenging for efficient electromagnetic wave (EMW) absorption. Here, a novel synergistic band and multiscale hybrid engineering is proposed to tailor spatial charge relaxation loss of hybrid semiconductor nanocrystal (HSNCs) nanocomposites. The HSNCs exhibit a unique Co[ Fm‐3m ]/TiO 2 [ I41/amd ]/TiO 2 [ P42/mnm ] polycrystalline structure, driven by tunable coordination and electrostatic interactions between metal‐organic frameworks with distinct coordination topologies and MXene nanosheets. The differentiated charge and energy band structure of the nanocrystals in each phase of HSNCs promotes the delocalization of positive and negative charges and the aggregation of space charges at the interface, thereby promoting spatial charge relaxation, which significantly enhances dielectric loss and electromagnetic energy attenuation, as evidenced by a minimum reflection loss of −45.52 dB. Finally, this work elucidates the hybrid structure‐property relationship in semiconductor nanocomposites, establishing a dynamic polarization physical model across multiple scales, including grain boundaries, unit cells, and atoms, offering valuable perspectives for exploring novel EMW absorption materials.

According to nonlinear source-filter theory, as the strength of the coupling between the source and filter increases, typically by a decrease in the vocal tract cross-sectional area, the resultant increase in the inertance of the vocal tract yields an increase in the interactions between acoustic pressures within the vocal tract and the changing glottal airflow and/or the vibratory pattern of the vocal folds as noted in Titze [(2008). J. Acoust. Soc. Am. 123(4), 1902-1915]. The purpose of the current research was to examine the effects of parametric vocal tract constrictions mimicking epilaryngeal tube and lip narrowing on aerodynamic measures in a dynamic self-oscillating physical model of the vocal folds and vocal tract. Multilayered silicone vocal fold models were created based on Murray and Thomson [(2011). J. Visualized Exp. 58, e3498] and Murray and Thomson [(2012). J. Acoust. Soc. Am. 132(5), 3428-3438] and mounted to a simple synthetic trachea and supraglottal vocal tract model. Four constriction cross-sectional areas were examined at two locations (i.e., at the epilarynx and lip regions). Phonation threshold pressure and flow were measured at phonation onset and offset using four M5-CONV vocal fold models. Results indicated that both constriction magnitude and location are relevant factors in determining glottal aerodynamics. In general, a narrow epilarynx tube or lip constriction resulted in the lowest onset pressures and airflows while the no vocal tract condition resulted in the highest onset pressures and airflows.

Hybrid Neural Net, Physical Modeling Applied to a Xylene Splitter

Since the effect of temperature and humidity on the growth of Coprinus Comatus was studied, a dynamic model based on temperature and humidity to simulate the Coprinus Comatus growth is established in this paper. The data used to calculate the model parameters is derived from chamber experiments.The conceptions of the Growth function, thalposis function and humidity sense function are defined creatively. The relationship between the three main growth indices(the stipe diameter, the stipe height and the sporocarp weight) and the growth days is described as linear function, quadratic function and power function respectively. The growth function is established as a matrix on the basis of the three functions. The relationship between the coefficients of the growth function and the humiture is studied. Moreover, the coefficients of the thalposis function and humidity sense function are also studied. The simulation error of the stipe diameter, the stipe height and the sporocarp weight based of the model is existed during the early growth period, and decreasing along with the increasing of the growth days. The simulation error is within the scope of 10% when the Coprinus Comatus is ripe. The dynamical growth rhythm of the Coprinus Comatus is described based on the model. The daily growth of the sporocarp can be forecasted under certain humiture based on the dynamical model which provides the foundation to regulate and control the growth environment in chamber. The model which is more practicability comparatively has the virtue of real-time and dynamic estimation compared to the conventional model.

We describe a computer vision system for observing facial motion by using an optimal estimation optical flow method coupled with geometric, physical and motion-based dynamic models describing the facial structure. Our method produces a reliable parametric representation of the face's independent muscle action groups, as well as an accurate estimate of facial motion. Previous efforts at analysis of facial expression have been based on the facial action coding system (FACS), a representation developed in order to allow human psychologists to code expression from static pictures. To avoid use of this heuristic coding scheme, we have used our computer vision system to probabilistically characterize facial motion and muscle activation in an experimental population, thus deriving a new, more accurate, representation of human facial expressions that we call FACS+. Finally, we show how this method can be used for coding, analysis, interpretation, and recognition of facial expressions.