Search Results (14)

Berthing operation heterogeneity across ship types causes significant uncertainty in assessing port congestion and carbon emissions over comparable timeframes. This study quantifies in-port emission dynamics for four cargo ship types (container, liquid bulk, dry bulk, and general cargo) using an operational phase-specific emission accounting model. We propose a hybrid deep learning model that integrates Two-Dimensional Convolutional Neural Networks (2DCNN) with Squeeze-and-Excitation Attention Mechanisms (SEAM) and Bidirectional Long Short-Term Memory Networks (BiLSTM) layers, optimized via the Triangulation Topology Aggregation Optimizer (TTAO) for hyperparameter tuning. Empirical analysis at Ningbo Zhoushan Port shows that liquid bulk carriers emit 23–41% more than other ship types due to extended auxiliary engine/boiler use during cargo handling. The 2DCNN-SEAM model significantly improves BiLSTM prediction accuracy—reducing Mean Absolute Percentage Error (MAPE) by 18.7% and increasing the R² value to 0.94—by effectively capturing spatiotemporal congestion features. Results confirm that operational congestion is a critical emission multiplier, especially for ships requiring prolonged auxiliary system use during berthing. These insights inform targeted decarbonization strategies for port authorities, prioritizing operational efficiency and energy transition for high-emission ship categories. Full article

Coal mine gangue cementation filling technology has increasingly become an effective and major means of dealing with “coal mining under buildings, railways, and bodies of water” and other complex hard-to-mine coal seams; but also, an important part of a large number of treatments of coal gangue stockpiled on the ground is to realize the green mining of coal mines. Coal mine cement filling often contains gangue particles with particle sizes larger than 15 mm; however, the viscometer and rheometer currently used at home and abroad are unable to accurately measure the rheological parameters of the slurry containing large-particle-sized gangue. In order to accurately measure the rheological parameters of slurry containing large-sized gangue particles combined with the site filling materials, the torque values obtained on the mixing blades at different speeds were generated by the combined action of the slurry between the blade side edge and the mixing drum wall, as well as the slurry between the blade lower edge and the mixing drum bottom. A new type of gangue slurry rheometer was developed. The new type of gangue slurry rheometer mainly included components such as the power system, sensing system, mechanical system, and other auxiliary units. Finally, using Fluent software ANSYS2023 to numerically simulate the fluidity of the slurry under the same conditions, the results obtained after the calculation and the test results showed that the error was within a reasonable range, indicating the correctness of the test principles of the new gangue slurry rheometer and the effectiveness of the instrument. This research offers new insights for accurately measuring the rheological parameters of particles with large sizes. Full article

In order to disintegrate nuclear fuel rods in the grid connection structure, a 10 kW fiber laser was used to cut a stainless steel simulation component with four layers of 3 mm thick plates and 12 mm gaps. The slit width is regarded as an important indicator to evaluate the cutting quality of the four-layer stainless steel plate. The results showed that good laser cutting quality can be successfully achieved under the proper process parameters. The widths of the cut seams of the four layers of grating after cutting were 1.25, 1.65, 1.80, and 1.92 mm. As the auxiliary gas pressure decreased layer by layer, the metal melting pool for the first two plates was mainly destroyed by the auxiliary gas. The cutting quality was good, and the slit area was mainly austenite with the presence of some ferrite. The third- and fourth-layer plates almost had no gas flow to assist blowing off, so the cut surface was an uneven melting pit, the cutting quality was poor, and the cut seam area ferrite content was higher than the upper plate cut seam area. At the same time, due to the lack of airflow cooling of the bottom plate, high laser energy, and long heating time, grain coarsening occurred, while grain deformation and a large number of dislocations existed. It can provide process support and technical guidance for the disintegration of nuclear fuel rods. Full article

The development height of a water-flowing fractured zone is the key parameter to consider when carrying out mining under water pressure and coal mining with water conservation. In this paper, Jurassic coal seam 3-1 in the Menkeqing Coal Mine was taken as the research target, and a three-dimensional mining geological model was established by using FLAC^3D to study the deformation and failure rules of overburden. Three roof boreholes were drilled in the auxiliary transportation roadway of adjacent working faces for dynamic monitoring by the resistivity method, which can better observe the whole process from failure to stability of the overburden. The results show that due to the complex sedimentary environment and large buried depth of coal seams in western China, there is a large deviation between the calculation results of the empirical formula of the fractured zone height under the “Regulations of buildings, water, railway and main well lane leaving coal pillar and press coal mining” (three regulations) and the simulation and on-site measurement. Based on the comprehensive analysis, the influence range of mining advance abutment pressure is approximately 60 m. The height of the water-flowing fractured zone is approximately 106 m, and it is located at the interface between sandy mudstone and mudstone. The height of the caving zone is approximately 22 m, and it is located at the interface between fine sandstone and medium sandstone. The ratio of the fractured height and coal seam thickness (R_f) reached 24.4, which was basically consistent with the test result of the adjacent Yushenfu mining area (which was 26 on average). There is no obvious change in the development height of the caving zone and water-flowing fracture zone from the working face to the drilling borehole position of more than 120 m, which reflects that the height of the overburden failure zone is related to the control of lithological combination. Full article

This document introduces a novel equivalent algorithm for forecasting gas content within deep coal seams, which is subject to constraints stemming from the advancements and precision achieved in well and roadway engineering endeavors. This algorithm meticulously acknowledges that coal seam gas content comprises three fundamental components: the inherent gas emission rate of the equivalent stratum, the residual gas content retained within the coal seam itself, and the influence imparted by the gas content within the coal seam. Furthermore, the approach thoroughly considers variations in the level of porosity development within the coal seam and its surrounding rock formations, as well as the occurrence of gas within these structures. The equivalent layer is classified into two distinct groups: the sandstone zone and the clay zone. The sandstone zone utilizes pertinent parameters pertaining to fine sandstone, whereas the clay zone distinguishes between clay rock and thick mudstone. The influencing factor considerations solely encompass natural elements, such as the coal seam’s occurrence and geological structure. The residual gas content employs either existing measured parameters or acknowledged experimental parameters specific to the coal seam. Based on this predictive approach, an intelligent auxiliary software (V1.0) for mine gas forecasting was devised. The software calculates the gas content of deep coal seams within the mine at intervals of 100 m × 100 m, subsequently fitting the contour lines of gas content across the entire area. The gas content predictions derived from this equivalent algorithm demonstrate robust adaptability to variations in gas content caused by construction activities, and the prediction results exhibit an acceptable level of error on-site. Notably, the prediction process is not constrained by the progress of tunnel engineering, ensuring that the prediction outcomes can accurately represent the distribution characteristics of deep coal seam gas content. After a year of application, the prediction results have consistently met on-site requirements, providing a scientific foundation for the implementation of effective gas prevention and control measures in the mining area. Furthermore, this approach can effectively guide the formulation of medium- and long-term gas prevention and control plans for mines. Full article

The paper presents the application of MTM, RAV and ZAK methods in the determination of working methods and time norms for the technological process of sewing. The technological operation of sewing the back sleeve seam on a men’s jacket is used for the study. The paper presents the designed workplace in a real production process. In addition, the appropriate working method and the time norm are determined using the MTM (Method Time Measurement), RAV (determination of sewing time for straight seams) and ZAK (determination of sewing time for curved seams) methods. The aim of the study was to combine the methods for determining different types of time (manual, machine-hand and machine) for performing technological operations and precisely calculate the time norms. For the described methods of determining the production time, computer programs were developed that speed up the calculation of the time norm. If the working method is defined in advance and the characteristics of the sewing machine are known, the time norm for each technological operation can be determined in advance. Based on these calculations, it is possible to determine the total time for the production of clothing in advance and thus to plan and schedule the production process and plan the delivery dates to customers. The results show that the technical equipment of the sewing machine and the working method have an influence on the structure of the technological sewing process. By choosing an appropriate working method, the workload and fatigue of the workers is reduced, as an appropriate number of auxiliary hand sub-operations are used. In this way, the appropriate time required to perform the technological operation is achieved. Full article

During the gob-side entry driving of the Jurassic coal seam in Western China, ejection disasters occur under the influence of roof drainage, which rarely appear in the eastern mining area. To address this problem, a method combining theoretical analysis, numerical simulation, and field monitoring was used to study the disaster induced by head-on ejection during speedy driving under the influence of roof drainage in the context of gob-side entry driving of the 2202 auxiliary haulage roadway in a mine. A calculation model for the critical energy conditions for disasters induced by head-on ejection was established. The relationships between the driving velocity and the dynamic and static loads on the driving face and the disasters induced by ejection were clarified under the influence of roof drainage. The results indicate that the energy threshold for ejection-induced disaster is 12.23 kJ, and the elastic energy of the driving face induced only by static load fails to reach the energy threshold. When the driving velocity exceeds 5 m/d, microseismic activity in front of the driving face increases in a stepwise manner, and the influence of dynamic load intensifies. The superposition of accumulated elastic energy induced by static load and the energy transmitted by microearthquake to the driving face exceeds the energy threshold, resulting in the risk of ejection-induced disaster. Based on this, measures such as microseismic monitoring in front of the driving face, advanced pulverized coal monitoring, driving speed adjustment, and advanced pressure relief of large-diameter boreholes are adopted to ensure safe driving. Full article

In this paper, a module-combined stator is proposed, which is used for large and ultra-low-speed permanent magnet synchronous motors, and the influence of stator core seams on the no-load performance is studied. A method is proposed to weaken the negative influence of stator iron core seams on the no-load performance of permanent magnet synchronous motors. Firstly, the magnetic circuit model of the motor considering the stator iron core seams was deduced theoretically, and the selection principle of stator core seam number was given a description. The influence of different seam parameters on the no-load performance and the influence of different pole-slot fits and the number of parallel branches on the no-load performance are analyzed. The proposed structure of the stator iron core, which can weaken the influence of stator iron core seams on the no-load performance of the motor, is proposed. Using analysis and simulation experiments, the effectiveness of the proposed stator iron core structures in weakening the negative influence of the stator iron core seams on the no-load performance was verified. Full article

Vision-based welding seam tracking is an important and unique branch of welding automation. Active vision seam tracking systems achieve accurate feature extraction by using an auxiliary light source, but this will introduce extra costs and the real-time performance will be affected. In contrast, passive vision systems achieve better real-time performance and their structure is relatively simple. This paper proposes a passive vision welding seam tracking system in Plasma Arc Welding (PAW) based on semantic segmentation. The BiseNetV2 network is adopted in this paper and online hard example mining (OHEM) is used to improve the segmentation effect. This network structure is a lightweight structure allowing effective image feature extraction. According to the segmentation results, the offset between the welding seam and the welding torch can be calculated. The results of the experiments show that the proposed method can achieve 57 FPS and the average error of the offset calculation is within 0.07 mm, meaning it can be used for real-time seam tracking. Full article

An overlap auxiliary ventilation system is very often used for driving roadways in methane-rich coal seams. An overlap zone between the outlets of the forcing duct ends with a whirl flow air-duct (WFAD) and the exhaust duct ends with a dust scrubber that is created by applying the overlap system. This study examines the distribution of methane concentrations at various distances in the overlap zone. Maintaining a long overlap zone could increase the advance of the face. Therefore, the impact of overlap zone length on the methane concentration distribution, in and beyond the overlap zone, is investigated. The evaluation of methane concentrations is performed utilizing a well-established computational fluid dynamics (CFD) approach. The mathematical model of methane emissions into the roadway is adopted. Moreover, the CFD model is validated. A vortex of the return air, caused by the free airstream flowing out of the dust scrubber, is found. This air vortex is responsible for higher methane concentrations at the end of the overlap zone. Therefore, the conclusion can be drawn that maintaining the length of the overlap zone at 5 m to 10 m should be done to control permissible methane concentrations. Full article

A Recurrent Neural Networks (RNN) based attention model has been used in code-switching speech recognition (CSSR). However, due to the sequential computation constraint of RNN, there are stronger short-range dependencies and weaker long-range dependencies, which makes it hard to immediately switch languages in CSSR. Firstly, to deal with this problem, we introduce the CTC-Transformer, relying entirely on a self-attention mechanism to draw global dependencies and adopting connectionist temporal classification (CTC) as an auxiliary task for better convergence. Secondly, we proposed two multi-task learning recipes, where a language identification (LID) auxiliary task is learned in addition to the CTC-Transformer automatic speech recognition (ASR) task. Thirdly, we study a decoding strategy to combine the LID into an ASR task. Experiments on the SEAME corpus demonstrate the effects of the proposed methods, achieving a mixed error rate (MER) of $30.95\%$. It obtains up to $19.35\%$ relative MER reduction compared to the baseline RNN-based CTC-Attention system, and $8.86\%$ relative MER reduction compared to the baseline CTC-Transformer system. Full article

The estimation of fuel characteristics and spatial variability in multi-seam coal deposits is of great significance for the optimal mine planning and exploitation, as well as for the optimization of the corresponding power plants operation. It is mainly based on the quality properties of the coal (i.e., Lower Calorific Value (LCV), ash content, CO₂, and moisture). Even though critical, these properties are not always measured in practice for all available borehole samples, or, they are generally estimated by using non-parametric statistics. Therefore, spatial modeling of LCV can become problematic due to the limited number of data. Thus, the use of other available correlated attributes might be helpful. In this research, techniques of multivariate geostatistics were used to estimate and evaluate the spatial distribution of quality properties in a multi-seam coal deposit, with special reference to the LCV. More specifically, kriging, cokriging, and Principal Component Analysis (PCA) techniques were tested in a case study as estimators of the LCV, using an extensive set of borehole data from the South Field lignite mine in Ptolemais, Greece. The research outcomes show that the application of kriging with two PCA factors and the use of inverse transform result in the best LCV estimates. Moreover, cokriging with two auxiliary variables gives more accurate values for a LCV estimate, in relation to the kriging technique. The research outcomes could be considered significant for the coal mining industry, since the use of correlated quality attributes for the estimation of LCV may contribute to a reduction of the estimation uncertainty at no additional drilling cost. Full article

The accidents caused by roof pressure seriously restrict the improvement of mines and threaten production safety. At present, most coal mine pressure forecasting methods still rely on expert experience and engineering analogies. Artificial neural network prediction technology has been widely used in coal mines. This new approach can predict the surface pressure on the roof, which is of great significance in coal mine production safety. In this paper, the mining pressure mechanism of coal seam roofs is summarized and studied, and 60 sets of initial pressure data from multiple working surfaces in the Datong mining area are collected for gray correlation analysis. Finally, 12 parameters are selected as the input parameters of the model. Suitable back propagation (BP) and GA(genetic algorithm)-BP initial roof pressure prediction models are established for the Datong mining area and trained with MATLAB programming. By comparing the training results, we found that the optimized GA-BP model has a larger determination coefficient, smaller error, and greater stability. The research shows that the prediction method based on the GA-BP neural network model is relatively reliable and has broad engineering application prospects as an auxiliary decision-making tool for coal mine production safety. Full article

Automatic joint detection is of vital importance for the teaching of robots before welding and the seam tracking during welding. For narrow butt joints, the traditional structured light method may be ineffective, and many existing detection methods designed for narrow butt joints can only detect their 2D position. However, for butt joints with narrow gaps and 3D trajectories, their 3D position and orientation of the workpiece surface are required. In this paper, a vision based detection method for narrow butt joints is proposed. A crosshair laser is projected onto the workpiece surface and an auxiliary light source is used to illuminate the workpiece surface continuously. Then, images with an appropriate grayscale distribution are grabbed with the auto exposure function of the camera. The 3D position of the joint and the normal vector of the workpiece surface are calculated by the combination of the 2D and 3D information in the images. In addition, the detection method is applied in a robotic seam tracking system for GTAW (gas tungsten arc welding). Different filtering methods are used to smooth the detection results, and compared with the moving average method, the Kalman filter can reduce the dithering of the robot and improve the tracking accuracy significantly. Full article