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By using small reference samples, the calculation method of confidence value and prediction method of confidence interval for multi-input system are investigated. The purpose of this paper is to offer effective assessing methods of confidence value and confidence interval for the simulation models used in establishing guidance and control systems.

In this paper, first, an improved cluster estimation method is proposed to guide the selection of the small reference samples. Then, based on analytic hierarchy process method, the new calculation method of the weight of each reference sample is derived. By using the grey relation analysis method, new calculation methods of the correlation coefficient and confidence value are presented. Moreover, the confidence interval of the sample awaiting assessment is defined. A new prediction method is derived to obtain the confidence interval of the sample awaiting assessment which has no reference sample. Subsequently, by using the prediction method and original small reference samples, Bootstrap resampling method is used to obtain more correlation coefficients for the sample to reduce the probability of abandoning the true.

The grey relational analysis is used in assessing the confidence value and interval prediction. The numerical simulations are presented to demonstrate the effectiveness of the theoretical results.

Based on the selected small reference samples, new calculation methods of the correlation coefficient and confidence value are presented to assess the confidence value of model awaiting assessment. The calculation methods of maximum confidence interval, expected confidence interval and other required confidence intervals are presented, which can be used in assessing the validities of controller and guidance system obtained from the model awaiting assessment.

The low-temperature sintering of silica glass combined with additive manufacturing (AM) technology has brought a revolutionary change in glass manufacturing. This study aims to carry out in an attempt to achieve precious manufacturing of silicate glassy matrix through the method of slurry extrusion.

A low-cost slurry extrusion modelling technology is used to extrude silicate glassy matrix inks, composed of silicate glass powder with different amounts of additives. Extrudability of the inks, their printability window and the featuring curves of silicate glassy matrix are investigated. In addition, the properties of the low-temperature sintering green part as a functional part are explored and evaluated from morphology, hardness and colour.

The results showed that the particle size was mainly distributed from 1.4 µm to 5.3 µm, showing better slurry stability and print continuity. The parameters were set to 8 mm/s, 80% and 0.4 mm, respectively, to achieve better forming of three-dimensional (3D) samples. Besides, the organic binder removal step was concentrated on 200°C–300°C and 590°C–650°C was the fusion bonding temperature of the powder. The hardness values of 10 test samples ranged from 588 HL to 613 HL, which met the requirements of hard stones with super-strong mechanical strength. In addition, the mutual penetration of elements caused by temperature changes may lead to a colourful appearance.

The custom continuous AM technology enables the fabrication of a glass matrix with 3D structural features. The precise positioning technology of the glass matrix is expected to be applied more widely in functional parts.

Traditional simulation research of geological and similar engineering models, such as landslides or other natural disaster scenarios, usually focuses on the change of stress and the state of the model before and after destruction. However, the transition of the inner change is usually invisible. To optimize and make models more intelligent, this paper aims to propose a perceptible design to detect the internal temperature change transformed by other energy versions like stress or torsion.

In this paper, micron diamond particles were embedded in 3D printed geopolymers as a potential thermal sensor material to detect the inner heat change. The authors use synthetic micron diamond powder to reinforced the anti-corrosion properties and thermal conductivity of geopolymer and apply this novel geopolymer slurry in the direct ink writing (DIW) technique.

As a result, the addition of micron diamond powder can greatly influence the rheology of geopolymer slurry and make the geopolymer slurry extrudable and suitable for DIW by reducing the slope of the viscosity of this inorganic colloid. The heat transfer coefficient of the micron diamond (15 Wt.%)/geopolymer was 50% higher than the pure geopolymer, which could be detected by the infrared thermal imager. Besides, the addition of diamond particles also increased the porous rates of geopolymer.

In conclusion, DIW slurry deposition of micron diamond-embedded geopolymer (MDG) composites could be used to manufacture the multi-functional geological model for thermal imaging and defect detection, which need the characteristic of lightweight, isolation, heat transfer and wave absorption.

The purpose of this paper is to reduce the drag loss and study the effects of operating conditions and groove parameters such as flow rate and temperature of automatic transmission fluid, clearance between plates, groove depth and groove ratio on the drag torque of a wet clutch for vehicles, parametric analysis of the drag torque model of wet multi-plate friction clutch with groove consideration.

Both experimental and numerical research was carried out in this work. Parametric groove models, full film lubrication flow model and pressure distribution model are established to investigate the effects of the grooves on drag torque of a wet clutch. Multigrid method is used to simplify the solution.

In this paper, a drag torque model of a wet multi-plate friction clutch based on the basic theory of viscous fluid dynamics is examined through experimental and numerical methods that take grooves into account, and the change trend of drag torque with operating conditions and groove parameters is analyzed.

Multigrid method is used to solve the governing equations, which simplifies the solution process because of the restrictions and interpolation operations between the adjacent layers of coarser and fine grids. These works provide insight into the effect regularity of operating conditions and groove parameters on drag torque of a wet multi-plate friction clutch. Furthermore, variable test conditions and sufficient experimental data are the main functions in the experimental research.

The tender documents, an essential data source for internet-based logistics tendering platforms, incorporate massive fine-grained data, ranging from information on tenderee, shipping location and shipping items. Automated information extraction in this area is, however, under-researched, making the extraction process a time- and effort-consuming one. For Chinese logistics tender entities, in particular, existing named entity recognition (NER) solutions are mostly unsuitable as they involve domain-specific terminologies and possess different semantic features.

To tackle this problem, a novel lattice long short-term memory (LSTM) model, combining a variant contextual feature representation and a conditional random field (CRF) layer, is proposed in this paper for identifying valuable entities from logistic tender documents. Instead of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid error segmentation.

The proposed model is then verified by the Chinese logistic tender named entity corpus. Moreover, the results suggest that the proposed model excels in the logistics tender corpus over other mainstream NER models. The proposed model underpins the automatic extraction of logistics tender information, enabling logistic companies to perceive the ever-changing market trends and make far-sighted logistic decisions.

(1) A practical model for logistic tender NER is proposed in the manuscript. By employing and fine-tuning BERT into the downstream task with a small amount of data, the experiment results show that the model has a better performance than other existing models. This is the first study, to the best of the authors' knowledge, to extract named entities from Chinese logistic tender documents. (2) A real logistic tender corpus for practical use is constructed and a program of the model for online-processing real logistic tender documents is developed in this work. The authors believe that the model will facilitate logistic companies in converting unstructured documents to structured data and further perceive the ever-changing market trends to make far-sighted logistic decisions.

The study aims to explore the composition and microstructure of clay functionally graded materials under the process of double-gradient direct ink writing (DIW).

The investigation focused specifically on the pore characteristics of barite-kaolin clay composite after three-dimensional (3D) printing and sintering as well as its bionic application in geophysical model.

The model with pore and material variations brought about spatial and nonlinear mechanical properties. Moreover, the vertical gradient and connected pores in the upper kaolin part simulated the natural phenomenon of the landslide model (take Chinese Majiagou landslides as an example). Both the thermal debinding behavior and the kaolin powder particles characteristics [large pore volume (0.019 cm³g^–1) and pore size (29.20 nm)] were attributed to the interconnection channels.

Hence, the macroscopic and microscopic pores achieved by dual-gradient DIW process make it possible to control the permeability and details of properties, precisely in the geological model.