Perpendicular-To-Grain Rheological Behavior of Loblolly Pine in Press Drying

To predict the thickness loss of loblolly pine lumber during press drying, a model was developed to describe the perpendicular-to-grain rheological behavior as a function of pressure, temperature, and drying time. The strain-time curve was divided into four parts—initial elastic deformation, viscoelastic deformation, final elastic springback, and time-dependent springback—according to the characteristic responses of these behaviors to pressure, temperature, and drying time. The model was fitted to experimental data by nonlinear regression. Good agreement was obtained between the predicted and experimental thickness loss during press drying

Effect of Juvenile Wood and Choice of Parametric Property Distributions on Reliability-Based Beam Design

A comparison is made of the effect of choice of the SB distribution, Weibull distribution, or log-normal distribution on reliability-based design of a 2 x 4 southern pine beam, No. 2 grade. The SB distribution provided most flexibility in describing the lumber properties.The presence of juvenile wood in lumber may affect the distributional characterization of lumber properties and in turn affect reliability-based design results. This study shows that juvenile wood had a significant effect on the reliability-based design results when stiffness was the limiting state. Unless juvenile wood lumber is separated from mature wood lumber in the grading process, a considerable loss in efficiency in utilizing lumber from fast-grown trees will occur where stiffness is critical

A Numerical Model for Heat Transfer and Moisture Evaporation Processes in Hot-Press Drying—An Integral Approach

A numerical model, which was based on the energy principle that the rate of water evaporation from the interface (or wet line) at a given time during hot-press drying was controlled by the rate of heat energy reaching the interface at that time, has been developed. The model treated the drying as a process in which the retreat of the interface and free water flow to the interface occur simultaneously. After all parameters were determined according to the available literature and experiments, the numerical model worked well in predicting the drying curves from process and material variables. The model, which has a sound theoretical base but is numerically simple, has a good potential to be expanded for general high temperature drying and to be adopted in a production line to presort the lumber for good drying practice

Discrete Spectrum cover Signal Waveform Design and Generation Method

Radio Frequency-screen is one of the earliest radar active antijamming measures. It achieves antijamming by transmitting cover pulses of different frequencies before the radar pulse signal to induce enemy jammers. As the demand for antijamming measures has become increasingly urgent in recent years, Radio Frequency-screen technology has been further developed. The most representative is the use of discontinuous spectrum signals as a cover signal. However, energy utilization for sending the cover signal can be improved further. To address this problem, this paper proposes a discrete spectrum cover signal based on the discontinuous spectrum cover signal and establishes the waveform design function under the joint constraint of constant modulus and spectral amplitude. The cover signal with discrete spectrum and energy aggregation is generated using the Alternating Direction Method of Multipliers (ADMM) and spectrum shaping algorithm solution. The simulation results show that the discrete spectrum cover signal has a higher spectral amplitude of approximately 5～12 dB than the discontinuous-spectrum cover signal for the same energy and bandwidth. Moreover, the discrete spectrum cover signal can cover a larger spectral range with the same energy and close spectral amplitude, realizing a better antijamming cover effect

Experimental Investigation on a Novel Necking Heat Pipe with Double-End Heating for Thermal Management of the Overload Operation

This work proposed a novel necking heat pipe with double-end heating for thermal management of the overload operation. The addition of another heat load was adopted to obtain a higher threshold critical power for the heat pipe system. The thermal performance of thermal switch heat pipe (TSHP) and traditional grooved heat pipe (TGHP) was investigated experimentally, including the threshold critical power, starting characteristic, recovery characteristic, surface temperature distribution, thermal resistance, etc. The optimized TSHP exhibited a larger threshold critical power range with low additional heat load input (from 55 W to 65 W, almost 20% increase), low starting additional heat load input (2 W), good recovery characteristic (less than 150 s from 75 °C to normal after overload), and low thermal resistance with additional heat load input (less than 0.13 °C/W). These results indicate that the optimized TSHP can offer great potential for the overload operation situation with the additional heat load. Such a novel necking heat pipe with double-end heating can be utilized in heat pipe systems to obtain different thermal performances for complicated working situations, especially for the overload operation situation

JKT: A joint graph convolutional network based Deep Knowledge Tracing

Knowledge Tracing (KT) aims to trace the student\u27s state of evolutionary mastery for a particular knowledge or concept based on the student\u27s historical learning interactions with the corresponding exercises. Taking the “exercise-to-concept” relationships as input, several existing methods have been developed to trace and model students’ mastery states. However, these studies face two major shortcomings in KT: 1) they only consider “exercise-to-concept” relationships; 2) the multi-hot embeddings lack interpretability. In order to address the above issues, we propose a Joint graph convolutional network based deep Knowledge Tracing (JKT) framework to model the multi-dimensional relationships of “exercise-to-exercise”, and “concept-to-concept” into graph and fuse them with “exercise-to-concept” relationships. In JKT, it is not only possible to establish connections between exercises under cross-concepts, but also to help capture high-level semantic information and increase the model\u27s interpretability. In addition, sufficient experiments conducted on four real-world datasets have demonstrated that JKT performs better than the other baseline models. We further illustrate a case study to demonstrate its interpretability for learning analysi