Visual representation and characterization of three-dimensional hydrofracturing cracks within heterogeneous rock through 3D printing and transparent models

The heterogeneity of unconventional reservoir rock tremendously affects its hydrofracturing behavior. A visual representation and accurate characterization of the three-dimensional （3D） growth and distribution of hydrofracturing cracks within heterogeneous rocks is of particular use to the design and implementation of hydrofracturing stimulation of unconventional reservoirs. However, because of the difficulties involved in visually representing and quantitatively characterizing a 3D hydrofracturing crack-network, this issue remains a challenge. In this paper, a novel method is proposed for physically visualizing and quantitatively characterizing the 3D hydrofracturing crack-network distributed through a heterogeneous structure based on a natural glutenite sample. This method incorporates X-ray microfocus computed tomography （μCT）, 3D printing models and hydrofracturing triaxial tests to represent visually the heterogeneous structure, and the 3D crack growth and distribution within a transparent rock model during hydrofracturing. The coupled effects of material heterogeneity and confining geostress on the 3D crack initiation and propagation were analyzed. The results indicate that the breakdown pressure of a heterogeneous rock model is significantly affected by material heterogeneity and confining geostress. The measured breakdown pressures of heterogeneous models are apparently different from those predicted by traditional theories. This study helps to elucidate the quantitative visualization and characterization of the mechanism and influencing factors that determine the hydrofracturing crack initiation and propagation in heterogeneous reservoir rocks.

Simulation of DPM distribution in a long single entry with buoyancy effect

Diesel particulate matter(DPM) is considered carcinogenic after prolonged exposure. With more dieselpowered equipment used in underground mines, miners' exposure to DPM has become an increasing concern. This paper used computational fluid dynamics(CFD) method to study DPM distribution based on an experiment conducted by the Diesel Emissions Evaluation Program(DEEP) in Canada. Twenty-four cases were simulated where the emissions from both truck and load-haul-dumps(LHDs) were examined.Each vehicle was placed in two stream wise locations, and the vehicles were oriented either facing or with the rear end toward the main fresh airflow. A species transport model with buoyancy effect was then used to examine the DPM dispersion pattern. High DPM regions were identified downstream,around, and even upstream of diesel engines. This can provide guidelines for good working practices and selection of diesel emission reduction technologies underground.

Effect of single dead end entry inclination on DPM plume dispersion

Diesel particulate matter(DPM) is a by-product from operating diesel engines. Since diesel powers are one of the major sources of energy for mobile underground mining equipment, the adverse health effects of DPM are of a great concern. This paper used computational fluid dynamics(CFD) method to study the effect of entry inclination on DPM plume distribution in a dead end entry. An upward mining face and a downward mining face were built with a truck and a loader in loading operation close to the face area. A species transport model with incorporated buoyancy effect was used to examine the DPM dispersion pattern for the above steady-state scenarios. High DPM and temperature regions were identified for the two different faces. The model was used to assess the role of auxiliary ventilation in reducing DPM exposures of underground miners working in those entries. In this study, it is suggested to provide local ventilation at least three times of the diesel exhaust rate to be able to lower the average DPM level for the mining upward face. The requirement for local ventilation is much less for the mining downward face. This can provide guidelines for good working practices and selection of diesel emission reduction technologies underground.

圆管-方管混凝土T型节点疲劳性能试验研究

基于热点应力法的管节点疲劳性能研究中,热点应力集中系数和疲劳寿命是描述焊接管结构节点疲劳性能的两个主要因素。对8个支管的圆管主管内填充C50等级混凝土方管节点试件(CT1～CT8)进行热点应力试验以确定其热点应力集中系数(SCF),在此基础上进行疲劳试验以确定其疲劳寿命(N3),将试验结果与具有相同几何尺寸和受力条件的圆管-方管节点试验结果及相关规范进行比较分析。研究表明,支管受轴向荷载下,圆管-方管混凝土节点与对应空钢管节点而言,节点区刚度分布明显改善,前者SCF最大值均小于后者SCF最大值,具有更好的抗疲劳性能;规范中关于空钢管节点疲劳性能的S-N曲线不适用圆管-方管混凝土T型节点的疲劳性能分析。

Digital twin technology for thermal comfort and energy efficiency in buildings:A state-of-the-art and future directions

In recent years,the integration of digital technologies has grown rapidly in the field of thermal comfort and energy efficiency for buildings.The concept of a digital twin,incorporating multiple digital technologies,has gained increasing attention.The literature lacks a review of the digital twin concept in thermal comfort and energy consumption for existing buildings.This paper conducts a review of the current state-of-the-art in digital twin(DT)technology for thermal comfort/energy consumption in buildings.The review employs a scientometric approach and examines various technologies used in creating DTs and a systematic analysis of the methods,technologies,algorithms,and approaches used in digital twin experiments.The results show a growing number of studies in this area,with a focus on thermal comfort monitoring,visualization,tracking,energy management,prediction,and optimization for existing buildings.Furthermore,the prediction of energy consumption using algorithms such as Artificial Neural Networks(ANN),Artificial Intelligence(AI),deep neural networks,and YOLOv4 have been used in buildings.However,the wider adoption of a DT that can facilitate occupants,and thermal sensations,enhance human-centered solutions,and improve energy prediction levels are necessary.There is a need for further international collaboration to expand the studies on digital twins for thermal comfort and energy efficiency.The review highlights the limitations and areas of improvement,such as the limited adoption of sensors for environmental measures,the need for more focus on the subjective perception of occupants,and the need for more comparative studies of algorithms for predicting energy consumption.Further studies can be conducted in areas such as understanding occupant psychological responses/behaviors to comfort in the digital world.This will enhance a more consolidated and robust validation for building performance.