On-site Measurements Research Articles

Agricultural limitations to soil carbon sequestration: Plant growth, microbial activity, and carbon stabilization

Soil carbon (C) sequestration is an important process for mitigating climate change while improving soil productivity. At the same time, it presents challenges for nutrient availability and changing agricultural practices. The aim of this study was to survey the challenges and limitations found on pioneering farms testing C sequestration using a Finnish network of farmers testing carbon farming practices. A combination of satellite monitoring, on-site measurements and soil analysis was used to quantify and evaluate soil physical, chemical, and biological quality indicators and plant productivity on 20 farms (40 fields). The indicators were assessed through a conceptual C sequestration model, classifying them into limitations for three stages of plant growth, microbial activity or C stabilization. Based on the results, there are limitations in all three stages: plant growth is constrained by crop choices which limit leaf area and sunlight capture, microbial processing of C is limited by poor soil structure and moisture stress, and C stabilization is limited by waterlogging and sulfur deficiency. These problems were found to be widespread, but not present on all the farms. Bringing all the farms to the levels of the best performing farms could reduce the considerable gap between potential productivity and C sequestration and that achieved in practice.

Lake total suspended matter retrieval by wind speed: A machine learning model trained by time-series satellite imagery

This study aims to develop an affordable and continuous method for monitoring water quality in arid, remote areas with high erosion rates. It presents a hypothesis that establishes a link between the concentration of Total Suspended Matter (TSM) and wind speed, emphasizing its ecological importance in lakes with dry conditions and high erosion rates. Building upon this hypothesis, the study introduces Wind2TSM-Net, a machine learning model that effectively bridges between different regression and neural network algorithms. This model connects on-site wind speed measurements with TSM data obtained through a physically remote sensing approach. It accurately predicts TSM concentration values, overcoming challenges such as cloud interference and reducing reliance on satellite imagery. The model was applied to Iran's Chah-Nimeh Reservoirs (CNRs) as a case study in an arid and remote area. The results revealed a significant correlation between TSM concentration and wind speed measurements, with impressive performance metrics (coefficient of determination (R2) = 0.88, root mean square error (RMSE) = 1.97 g/m3, mean absolute error (MAE) = 1.33). These findings highlight the effectiveness of Wind2TSM-Net in monitoring TSM values in remote and dry regions, particularly during extreme weather conditions when on-site measurements are impractical or cloud cover obstructs satellite observations.

Factors influencing outdoor thermal comfort in a coastal park during the transition seasons in cold regions of China

Coastal outdoor spaces serve as public venues where individuals engage in water-related activities, admire scenic views, embark on tourist excursions, and partake in social gatherings. Enhancing thermal comfort is a crucial prerequisite for increasing the attractiveness of these spaces. This study investigated the outdoor thermal comfort (OTC) in a coastal park called Xinghai Park located in a cold region of China over a period of five days during the spring and autumn seasons. The universal thermal climate index (UTCI) was employed to establish the thermal benchmark. Through on-site measurements and questionnaire surveys, both single-factor and multi-factor analyses were conducted to assess the microclimate and thermal perception in four representative coastal spaces, thereby identifying the thermal benchmark and factors influencing thermal perception in the Coastal Park. The findings indicated that: (1) during the transition seasons, the neutral UTCI (NUTCI) of the Coastal Park was 15.3 °C, with neutral UTCI range (NUTCIR) ranging from 9.3 °C to 21.4 °C, and there were significant variations in the thermal benchmarks among different types of spaces; (2) the primary factors influencing thermal perception during the transition seasons in the Coastal Park were physical factors (Ta, Tg, RH, Va, G), while individual, social, and psychological factors also exerted varying degrees of influence on respondents' thermal perception; (3) there were substantial spatial differences in the factors influencing respondents' thermal perception. The findings of this study provide valuable references for determining thermal environmental design strategies for transitional season coastal outdoor recreational spaces and enhancing the quality of urban life.

Development on risk assessment model of urban ventilation based on COVID-19 pollution——A case study of an innovation base in Chongqing

Numbers of constructions have emerged due to the continuous urbanization process and the diversity of building clusters. Meanwhile, frequent global epidemics, such as COVID-19, have raised higher requirements for efficient urban ventilation. Traditional building design is insufficient to quantitatively consider the rationality of urban ventilation and corresponding risk assessments. This study carries out urban safety ventilation research and provides risk assessment models by using simulation and mathematical induction based on on-site measurement data, to realize accurate evaluation of disturbance of building clusters in urban environment, taking an Innovation Base in Chongqing as an example. The Amplification Coefficients on Urban Disturbance (ACUD) of the Innovation Base are respectively σ1 = 0.047 representing safe evacuation distance for ventilation of new buildings downstream, σ2 = 0.403 representing origin airflow disturbance retreat of new buildings, σ3 = 1.261 representing the control range of skyline design, and σ4 = 4.381 representing urban canopy ventilation boundary. The Comprehensive Risk Coefficient (CRC) of the Innovation Base in the horizontal & vertical direction of CRCh = 17.88 and CRCv = 102.97 is obtained indicating the infection risk of residents in the vertical direction is 5.76 times greater than that in the horizontal direction. The Comprehensive Pollution Disturbance (CPD) is 1.70692*10−19 kg/m3 which can be regarded as the quantitative risk assessment index of the Innovation Base under large public health safety events. This study contributes to effective support of architectural and urban design facing safe ventilation, providing theoretical support for the risk assessments, the resident control and anti-epidemic policies for both governments and residents during the worldwide epidemic situation.

Modelling and onsite testing on dynamic thermal responses of built environment in passive solar rooms on Tibetan plateau

It of great importance in assessing built thermal environment level and evaluating corresponding indoor air conditioning demand for energy conservation in construction sectors. Nevertheless, because of the unique meteorological features in plateau area, classical building performance simulation approach contributes to thermal performance evaluation errors since most design codes or standards relies on low attitude regions. In this paper, a modified and improved dynamic thermal design model is put forward for built environment and energy consumption estimation for passive buildings for plateau buildings. Moreover, the simplified experiment is set up to monitor dynamic thermal responses for modelling building. The testing validation illustrate that the onsite measurement accuracy level is quite acceptable for engineering applications with less than 30% relative change range coefficient. Besides, the experiment data demonstrates that window-to-wall ratios, architectural orientation, thermal insulation coefficients, have substantial impacts for solar heat gains in plateau buildings. The study renders building design guidance for energy conservation in high altitude plateau areas.

A high-precision transient state prediction framework for ageing hydropower systems: Refined model, two-stage parameter identification and impact analysis

Ageing has adverse effects on the hydraulic-mechanical characteristics of hydropower systems (HPSs). It leads to parameter uncertainty both in the hydropower generating units (HGUs) and pipeline systems, further resulting in more severe transient conditions. Existing studies on transient state prediction of HPSs mostly do not consider the parameter uncertainty caused by HPS ageing, especially in the hydro-turbine model. This omission significantly reduces the accuracy. Therefore, a novel framework is proposed to achieve a high-precision transient state prediction of ageing HPSs. The framework includes: a refined HPS model to consider the uncertain ageing of HPSs through its uncertain parameters; a two-stage parameter identification strategy to enhance the prediction accuracy iteratively; and a parameter impact analysis which quantifies the contribution of identifying parameters to the precision improvement. Note that a comprehensive hydro-turbine model with six uncertain parameters is proposed to account for both the hydraulic-mechanical characteristic and uncertain ageing, and a fuzzy analytic hierarchy process is applied to quantify the precision. Comparative studies with on-site measurement show that: (1) The proposed framework demonstrates a 13.24% improvement in prediction performance compared to existing methods; (2) The parameters associated with HGU (especially those related to the hydro-turbine model) contribute significantly more to prediction precision, surpassing those related to the pipeline by an average factor of 9.27; (3) The contribution ranking of HGU parameters to the precision improvement is GD2＞ kf＞ μQ0＞kyd＞kq ＞kn ＞ηc. Overall, this study effectively improves the transient state prediction for ageing HPSs considering the uncertain parameters related to HGU and pipeline systems.

Numerical simulation of the dust pollution characteristics and the optimal dustproof air volume in coal washing plant screening workshop

Dust pollution generated during the working process of a screening workshop in a coal washing plant seriously threatens the occupational health of workers. To improve the working environment for workers, we investigated the effects of various airflow parameters on the diffusion of dust particles and pollutants. We established a proportional model of the screening workshop and conducted spatiotemporal analysis of the evolution laws of airflow and particulate matter. We used numerical simulation and on-site measurements to obtain the optimal dust removal air flow rate in a coal washing plant workshop. When the air flow rate is between 360 and 1260 m³/min, the overall dust concentration in the workshop and the average dust mass concentration in the breathing zone decrease significantly as the air flow rate increases. However, if the air flow rate is too high, this can cause re-entrainment of dust, which will pollute the operation area again. The optimum dust removal airflow for the inlet air was 1260 m³/min. This air flow rate decreases the dust at the height of the breathing zone in the working area, and the dust concentration at the sidewalk in the working area decreases by 58.82%. This air flow rate can act as a reference value for workshop ventilation design to provide a clean and safe production environment for coal miners. Our methodology and results are of value the formulation and development of effective dust control and clean production technologies.

A bacterial biosensor based on gold nanoparticles functionalized by a hydrophobin-chimera and combined with machine learning for user-friendly detection

A chimeric protein, in which a cationic antimicrobial peptide was fused to the adhesive self-assembling moiety of a fungal class I hydrophobin, was produced and used to easily functionalize gold nanoparticles (f-AuNPs). f-AuNPs are able to bind Escherichia coli and Staphylococcus epidermidis bacteria, tested as model organisms. A reverse colorimetric assay was then set up based on the induced aggregation of the free f-AuNPs. This leads to changes in optical properties of the solution, visible even by naked eyes. This approach allows detection of 10 CFU mL−1 of E. coli within 15 min and can be applicable to detect bacterial contamination in real matrices. Notably, the colorimetric variation was combined to machine-learning methodologies inferring data from photos of the colored solutions, acquired by smartphones. This fast, highly practical and flexible system, would enable on-site measurements and, therefore, help to prevent significant contaminations.

Characteristics of resistivity variation in deep granite and in-situ detection applications

During the construction of deep vertical shafts, water inrush and flooding accidents are prone to occur, which seriously affect construction safety. Accurately determining the groundwater conditions is a prerequisite for effectively controlling water hazards and conducting risk management. In order to ensure the accuracy of the resistivity method in deep vertical well water exploration construction, a combination of indoor rock physics, mechanical testing, and on-site engineering measurements was used to analyze the influencing factors of granite resistivity. The corresponding relationship between resistivity and formation integrity was revealed, and water exploration experiments were conducted in the working face of deep underground mines. The results show that: (1) Rock resistivity is influenced by metallic minerals, saturation, temperature, ion content of fracture water, and joints. Regarding deep subsurface detection issues, the main factors affecting the detection results are water content and rock integrity. (2) During the loading process, rock resistivity exhibits significant stage response characteristics, which are closely related to rock integrity and damage accumulation. (3) A degradation model for aquifer zoning based on resistivity benchmark line was established. When the formation resistivity is higher than the benchmark line, it indicates a well-integrated formation with low water content. (4) Resistivity cloud maps and zoning degradation models can be used to visually determine and evaluate the occurrence status of formations and the effectiveness of grouting.

Mechanical Behavior of Secondary Lining in Super Large-Span Tunnels Considering Temperature Effects

Temperature stress has a significant impact on the structural stress of (super) large-span tunnel lining, which can easily lead to structural fatigue damage and premature cracking. With the increasing scale and quantity of super large-span tunnels, the issue of temperature stress in secondary lining has attracted widespread attention. Previous studies have paid little attention to the influence of temperature stress on the structural internal forces of ordinary small–medium-span tunnels, but this influence cannot be ignored for super large-span tunnels. We take the Letuan Tunnel (a double-hole eight-lane tunnel) of the Binzhou-Laiwu expressway renovation and expansion project in Shandong Province as a case study and analyze the mechanical response of the secondary lining through on-site measurement. Moreover, a numerical simulation was conducted to evaluate the effects of self-weight and temperature stress on the secondary lining of the case tunnel. The results indicate that: the stress of the secondary lining concrete and steel bars is greatly affected by seasonal temperature changes. The compressive stress of the concrete and steel bars is significantly greater in summer than in winter, and the tensile stress is greater in winter than in summer. Furthermore, multiple measurement points have shown a phenomenon of transition between tensile and compressive stress states. The stress of concrete and steel bars fluctuates periodically with a sine function over time, with a fluctuation period of one year. The structural stress increases with the increase of summer temperature and decreases with the decrease of winter temperature. The fluctuation amplitude of stress in the inner side of the lining concrete and steel bars is greater than that on the outer side. Among them, the stress amplitudes of the inner and outer sides of the concrete are between 0.77–1.75 MPa and 0.44–1.07 MPa, respectively, and the stress amplitudes of the inner and outer steel bars are between 5–31 MPa and 7–13 MPa, respectively. The safety factors in summer are lower than those in winter. The minimum safety factors for secondary lining in summer and winter are 3.4 and 4.6, respectively, which can meet the safety requirements for service. The average axial forces of the secondary lining under the coupling effects of self-weight and temperature in winter and summer are 528 MPa and 563 MPa, respectively, which are significantly greater than the combined axial forces under their individual effects. The bending moment distribution of the secondary lining at the tunnel vault, inverted arch, wall spring and other positions under the coupling effect of self-weight and temperature is different from or even opposite to the bending moment superposition result under the two individual actions. The achieved results reveal that the influence of temperature stress on the service performance of the lining structure cannot be ignored, and the research results can provide useful reference for similar tunnels and related studies.

Data-augmented landslide displacement prediction using generative adversarial network

Landslides are destructive natural disasters that cause catastrophic damage and loss of life worldwide. Accurately predicting landslide displacement enables effective early warning and risk management. However, the limited availability of on-site measurement data has been a substantial obstacle in developing data-driven models, such as state-of-the-art machine learning (ML) models. To address these challenges, this study proposes a data augmentation framework that uses generative adversarial networks (GANs), a recent advance in generative artificial intelligence (AI), to improve the accuracy of landslide displacement prediction. The framework provides effective data augmentation to enhance limited datasets. A recurrent GAN model, RGAN-LS, is proposed, specifically designed to generate realistic synthetic multivariate time series that mimics the characteristics of real landslide on-site measurement data. A customized moment-matching loss is incorporated in addition to the adversarial loss in GAN during the training of RGAN-LS to capture the temporal dynamics and correlations in real time series data. Then, the synthetic data generated by RGAN-LS is used to enhance the training of long short-term memory (LSTM) networks and particle swarm optimization-support vector machine (PSO-SVM) models for landslide displacement prediction tasks. Results on two landslides in the Three Gorges Reservoir (TGR) region show a significant improvement in LSTM model prediction performance when trained on augmented data. For instance, in the case of the Baishuihe landslide, the average root mean square error (RMSE) increases by 16.11%, and the mean absolute error (MAE) by 17.59%. More importantly, the model's responsiveness during mutational stages is enhanced for early warning purposes. However, the results have shown that the static PSO-SVM model only sees marginal gains compared to recurrent models such as LSTM. Further analysis indicates that an optimal synthetic-to-real data ratio (50% on the illustration cases) maximizes the improvements. This also demonstrates the robustness and effectiveness of supplementing training data for dynamic models to obtain better results. By using the powerful generative AI approach, RGAN-LS can generate high-fidelity synthetic landslide data. This is critical for improving the performance of advanced ML models in predicting landslide displacement, particularly when there are limited training data. Additionally, this approach has the potential to expand the use of generative AI in geohazard risk management and other research areas.

Defining the calibration process for building thermal performance simulation during the warm season: a case study of a single-family log house

ABSTRACT The study aimed to develop a holistic, evidence-based calibration strategy and define a hybrid step-by-step methodology for building thermal simulations during the warm season. The methodology was demonstrated using the thermal performance of a naturally ventilated single-family log house in a temperate climate. The calibration process was supported by on-site measurements of indoor thermal conditions and occupant behavioural reports between April and July. Hybrid calibration methodology combines statistical indicators, such as NMBE, CV(RMSE), and R 2, and a graphical evaluation of the deviation between the simulated and measured values. After 28 proposed calibration steps, a final calibrated model predicted the actual thermal response of the log house with an accuracy of ±1°C at 71.6% or ±2°C at 98.4% of the considered time. The results showed that occupant-related information, material properties and infiltration rates are crucial to improving the reliability of building thermal models. Moreover, in the calibration process of log houses, appropriate determination of building envelope materials’ thermal conductivity, wood's solar absorptivity, and airtightness showed high importance. The study highlights the importance of calibration for reliable building thermal models, specifically in overheating prevention simulations.

Case study: Computer modeling the noise produced by a future food court radiated to nearby existing offices

Lately, there’s an increase in the co-existence of spaces of different usage with acoustical challenge. Throughout 2016 to 2018, the 2nd floor of the Complexe Les Ailes, in Montreal, underwent a fit-out to become a food court. At its center, there is an elliptical atrium where all levels are can be viewed. There are existing offices above the food court separated by a glass pane. The purpose of this study was to evaluate the noise generated by human activities in the future food court to the adjacent offices and recommend noise control elements if needed. Multiple sound samples were taken at existing food courts to quantify the sound level. Simulations were done with ODEON, a room acoustic software, to evaluate the sound level produced by different activities. On-site measurements were conducted to calibrate the existing conditions with the 3D ODEON model. Finally, noise reduction tests were undertaken to determine the sound levels that would be radiated in the offices by the activities in the food court. To reduce noise disturbance in the offices, acoustical treatment under the ceiling of the food court was recommended and the 3rd and 4th floor glass panes composition would have to be improved.

Mechanical behaviors of segmental lining of shield tunnels: A comparison between stagger-jointed and cross-jointed assembly type

The assembly type of segmental linings has a great impact on mechanical behaviors and failure mechanism of the linings. In this paper, a sophisticated 3D FEM model for segmental linings with different assembly types (single ring, three rings cross-jointed and stagger-jointed) was established to investigate the mechanical behaviors and failure mechanism of the linings under loading condition, with particular focus on the structural effect of the staggered-jointed linings. The effectiveness of the numerical model was verified by the data from the on-site measurements. The results show that the segmental linings turn into horizontal ellipse under the overloading condition. For the stagger-jointed linings, the initial cracks are emerged on the segment body and some oblique cracks and circumferential cracks are generated due to the interaction among rings. The failure process of the stagger-jointed linings was illustrated by the damaged plasticity point which are mainly staggered distributed on segment body and the time sequence of the points reaching certain structural performance state are progressive and discrete. The stagger effect is captured on the internal force of stagger-jointed linings and the major reasons causing the bending moment transmission are analyzed. Above analysis will contribute to the structural safety evaluation of the tunnels.

Classroom architectural design evolution: Acoustic evaluation of public-school classrooms in Malaysia

Education transformation greatly emphasises curriculum modification to produce impactful future generations and yet often disregards the impact of classroom design in achieving desired education outcomes. The prioritisation of optimal acoustic quality in classroom design is crucial due to the inherent reliance on auditory abilities in the process of teaching and learning. Therefore, a comprehensive acoustic standard guideline for classrooms, ANSI Standard 12.60, was launched in 2002 and adopted for school classrooms in the USA. However, the scenario might be different in Malaysia, as there is no acoustic standard guideline established. Therefore, this study seeks to identify the actual acoustic conditions of classrooms that were constructed in the post-independence era. On-site acoustic measurements were performed to evaluate significant acoustic parameters, including reverberation time (RT), background noise level (BNL), speech transmission index (STI), and sound pressure level (SPL). The findings revealed that the RT for both classrooms was within the recommended value, while the BNL and STI of both classrooms failed to comply with the established recommended guidelines. In a similar vein, these findings translate the degree of awareness among the education institutions and construction sector of the importance of classroom acoustics in providing a better learning experience among students.

An Investigation of the Energy-Saving Optimization Design of the Enclosure Structure in High-Altitude Office Buildings

Concerning the double carbon national strategy, the energy-saving renovation of old buildings has become one of the most important tasks of energy conservation and emission reduction in construction in China. There are many problems, such as high energy consumption, thermal environment, and poor thermal comfort. Taking Lhasa as an example, this study adopts field research, questionnaire interviews, on-site measurements, numerical simulations, and other methods to propose suitable energy-saving potential excavation points and thermal optimization strategies for office building envelopes in Lhasa through software simulation. Additionally, typical office buildings are selected to carry out the energy-saving renovation of envelopes with the goal of improving indoor thermal comfort to validate the feasibility of the energy-saving renovation strategies. The results show the following: (1) The measured and predicted thermal neutral temperatures of the office population in Lhasa are 16.5 °C and 18.9 °C, respectively. The 90% acceptable temperature range is from 16.10 °C to 21.77 °C, and the occupants of the office buildings in Lhasa have a higher tolerance for cold than predicted. (2) The passive measures adapted to Lhasa are prioritized in the order of passive solar energy, high-heat-capacity materials, and nighttime ventilation. (3) Through the optimization of the enclosure structure of existing office buildings, the improvement of the heat storage capacity of the outer enclosure structure, and the increase in the window opening area to increase natural ventilation, the indoor thermal comfort of the renovated buildings is effectively improved.

Measurement Errors When Measuring Temperature in the Sun.

In the validation of microclimate simulation software, the comparison of simulation results with on-site measurements is a common practice. To ensure reliable validation, it is crucial to utilize high-quality temperature sensors with a deviation smaller than the average absolute error of the simulation software. However, previous validation campaigns have identified significant absolute errors, particularly during periods of high solar radiation, possibly attributed to the use of non-ventilated radiation shields. This study addresses the issue by introducing a ventilated radiation shield created through 3D printing, aiming to enhance the accuracy of measurements on cloudless summer days with intense solar radiation. The investigation employs two pairs of sensors, each comprising one sensor with a ventilated and one with a non-ventilated radiation shield, placed on a south-oriented facade with two distinct albedos. Results from the measurement campaign indicate that the air temperature measured by the non-ventilated sensor is elevated by up to 2.8 °C at high albedo and up to 1.9 °C at a low albedo facade, compared to measurements with the ventilated radiation shield. An in-depth analysis of means, standard deviations, and 95% fractiles highlights the strong dependency of the non-ventilated sensor error on wind velocity. This research underscores the importance of employing ventilated radiation shields for accurate microclimate measurements, particularly in scenarios involving high solar radiation, contributing valuable insights for researchers and practitioners engaged in microclimate simulation validation processes.

3D Anisotropic Magnetoresistance sensor for steel health monitoring

Electromagnetic sensors are widely used for safety and maintenance inspection purposes of ferromagnetic materials used in aerospace, construction and transport industry. In this paper, a portable device based on an Anisotropic Magnetoresistance (AMR) sensor for steel health monitoring is presented. The principle of operation of this device is the detection of magnetic anomalies of ferromagnetic materials, such as steel, due to stresses, corrosion, or other kind of defections. For this purpose, a cost-effective, low-consumption and high-sensitivity device has been developed, consisting of a sensor, a magnetic yoke and a microcontroller. The AMR sensor, is placed above the material under test, giving the ability of contactless measurement of the magnetic flux density on 3 axes. Additionally, a yoke, consisting of two iron poles and a permanent magnet between them, is used in this implementation, in order to create a closed magnetic circuit with the steel sample, enhancing the measurements. Then, a microcontroller with the appropriate electronic components receives the acquired data, enabling their real-time analysis and visualization of the measurements through a personal computer, smartphone, etc. Moreover, a 3D-printed enclosure has been designed and constructed, which both protects the sensor and maintains the desired position and alignment with the samples. The device can be portable due to an integrated Li-Po battery and its Wi-Fi capabilities. It can be used to determine the location of the defective spots or zones of the material under inspection, facilitating its treatment through rehabilitation methods that can be applied on the affected area. Both single-point and scanning mode monitoring are possible, making it suitable for many testing scenarios. Furthermore, its ease of use and portability render it accessible to a wide range of users, and appropriate for on-site measurements. The initial measurements using the device on test samples, demonstrate its reliability and accuracy in steel health monitoring.

Research on factors affecting the spread of dust pollution in conveyor belt workshop and research on wet dust reduction technology.

At this stage, there are many dust-hazardous industries, and occupational pneumoconiosis has a high incidence for a long time. To solve the dust pollution problem in coal processing plant workshops, the dust particle field and liquid droplet particle field were numerically simulated using computational fluid dynamics (CFD), and the influences of the induced airflow and corridor wind speed on the internal airflow field of the workshop were investigated to derive the dust pollution mechanism in the coal plant workshop under the change in the wind flow field. In this study, it was shown that the wind flow rate in the coal processing plant workshop is mainly affected by the corridor wind speed, and the higher the corridor wind speed is, the higher the wind flow rate. The induced airflow mainly affected the direction of the wind flow field in the workshop. According to the conclusions obtained from the simulations, a spray dust reduction system was designed for the coal processing plant workshop and applied in the Huangyuchuan coal processing plant. On-site measurement revealed that the dust reduction effect inside the coal processing plant workshop is obvious, and the overall dust reduction efficiency in the workshop reaches more than 94%, which meets the requirements of environmentally sustainable development and clean production.

Characterization of spatiotemporal distribution of gas in the goaf of W-type ventilated working face

In order to solve the problem of gas over limit near the return air trough of W-type ventilated working face, a method combining numerical simulation and on-site measurement was used to study the spatial and temporal distribution characteristics of gas in the goaf under the W-type ventilated mode, and the reliability of the model was verified. Delineate the gas-rich area and suitable pumping area in the goaf, by analyzing the pumping of the top plate high-level directional borehole in the area, optimize the best layout of the top plate high-level directional borehole. The results show: The gas concentration in the goaf gradually increases from shallow to deep in the direction, and increases rapidly in the range of 0–75 m; in the direction of inclination, it is approximately symmetrically distributed along the axis of the return air trough, and gradually decreases toward the air inlets on both sides. The gas concentration in the middle area of the working face is higher than 0.85%; in the vertical direction, the further away from the coal seam roof, the higher the gas concentration, but the growth rate decreases, and the range of high gas concentration gradually expands. The gas concentration of the goaf reflected by the changes in the concentration of the working face has gradually increased in the early stages of mining. and then changes periodically with the cycle of roof pressure in the later stage. There is a strong correlation between the amount of gas emission the goaf and the mining speed of the working face. The regularity of the simulation result is the same as the regularity of the measured results, and the absolute value of the relative error is within 10%, that the concentration of extraction from high-level directional borehole increases with the height of the arrangement, mixed and pure volume decreases with the height of the arrangement. Comparison of the average mixed volume, concentration, pure volume and total extraction volume of each high-level directional borehole, it can be seen that the average pure volume from 3#holes is 3.9 times higher than that from 1#holes, and the total extraction volume accounts for 29% of the total extraction volume from the drill site, it is obtained that the best layout of the high-level directional boreholes of the 3203 working face is between 25 and 35 m above the top board. During the high-level drilling period, the gas concentration in the return air trough was between 0.42% and 0.75%, which effectively prevented the occurrence of gas over limit accidents.