Gas Load Research Articles

Revisiting the passive biocover system at Klintholm landfill, six years after construction

A biocover system was established at Klintholm landfill in Denmark in 2009 to mitigate methane emissions, and the system exhibited high mitigation efficiency during the first year after implementation. The biocover system was revisited in 2016/2017, and a series of field and laboratory tests were carried out to evaluate functionality about six years after establishment. Three field campaigns were executed in three different barometric pressure conditions, namely increasing, stable and decreasing. Local surface flux measurements and gas concentration profiles in the methane oxidation layer showed that barometric pressure changes had a significant effect on gas emission and methane oxidation. Elevated concentrations of oxygen were observed in the gas distribution layer, and field data showed that significant methane oxidation took place in this location. This finding was verified in laboratory-based methane oxidation incubation tests. Temperatures higher than ambient temperature were observed throughout the methane oxidation layer, with average temperatures ranging between 13 and 27 °C, even in the coldest month of the year. Field measurements showed that total methane emissions from the whole landfill cell were at the same level or lower than measurements performed in 2009/2010 after implementation of the biocover system, and laboratory tests showed methane oxidation potential approximately equal to former tests. In spite of an inhomogeneous distribution of landfill gas load to the methane oxidation layer, the performance of the biocover system had not declined over the 6–7 years since its establishment, even though no maintenance had been carried out in the intervening years.

Comprehensive Energy Demand Response Optimization Dispatch Method Based on Carbon Trading

With the increasingly prominent environmental problems in the world today, the development of an integrated energy system and the introduction of a carbon-trading mechanism have become important means to realize the low carbonization of the energy industry. Based on this, this paper introduces the carbon-trading mechanism into the research on the optimal dispatch of an integrated energy system. The mechanism of integrated energy demand response participating in low-carbon economic dispatch is analyzed. The relationship between carbon emissions and carbon-trading price in carbon-trading mechanism is described. On the basis of considering the commodity attributes of the electricity and gas load and the flexible supply characteristics of the thermal load, an incentive-type comprehensive energy demand response model is established. Finally, aiming at the lowest comprehensive operating cost, a comprehensive energy system model considering the power balance and equipment constraints of the electric–gas–heat system is established, using an improved particle swarm algorithm to solve it. Simulations verify the effectiveness of the proposed method in reducing the carbon emissions and operating costs of integrated energy systems.

Short-Term Power Load Forecasting of Integrated Energy System Based on Attention-CNN-DBILSTM

In view of the fact that the potential high-dimensional features in the historical sequence are difficult to be effectively extracted by traditional power load forecasting methods and the coupling factors of electricity, heat, and gas have not been considered, the correlation of electric heating and gas load is considered in this paper, and a short-term power load forecasting method for integrated energy systems based on Attention-CNN- (Convolutional Neural Network-) DBILSTM (Deep Bidirectional Long-Short-Term Memory) is proposed. First, the correlation between the multiple load influencing factors is considered, and the Pearson coefficient is used to quantitatively calculate the correlation between the multiple loads. Second, a CNN network consisting of a one-dimensional convolutional layer and a pooling layer is established. High-dimensional features reflecting the dynamic changes of the load are extracted, and the proposed feature vector is constructed in the form of time series as the input of the DBILSTM network; the dynamic change law of time series data is modeled and learned. Then, the Attention mechanism is introduced to assign different weights to the hidden state of DBILSTM through the mapping weight and the learning parameter matrix, to reduce the loss of historical information and strengthen the impact of key information, and the Dense layer is used to output the load prediction results. Finally, the influence of the correlation of multiple loads and its influencing factors on the power load forecasting results is analyzed, based on the historical load data of the integrated energy system in a certain area of Northeast China. The simulation results of the calculation example show that the prediction accuracy of the method reaches 97.99%, and the integrated energy system electric, heat, and gas load correlation coefficients as the input parameters of the Attention-CNN-DBILSTM network can reduce the average prediction error by 0.37%∼1.93%. The proposed method has been verified to effectively improve the prediction accuracy by comparison with the prediction model results of CNN-LSTM network, CNN-BILSTM network, and CNN-DBILSTM network.

A hybrid deep learning approach by integrating extreme gradient boosting‐long short‐term memory with generalized autoregressive conditional heteroscedasticity family models for natural gas load volatility prediction

AbstractNatural gas load forecasting provides decision‐making support for natural gas dispatch and management, pipeline network construction, pricing, and sustainable energy development. To explain the uncertainty and volatility in natural gas load forecasting, this study predicts the natural gas load volatility. As the natural gas load volatility has the time‐series features, along with long‐term memory, volatility aggregation, asymmetry, and nonnormality, this study proposes a natural gas load volatility prediction model by combining generalized autoregressive conditional heteroscedasticity (GARCH) family models, XGBoost algorithm, and long short‐term memory (LSTM) network. The model first takes the GARCH family models parameters of sliding estimation and meteorological factors as the influencing factors of volatility, and then it screens these influencing factors through the extreme gradient boosting (XGBoost) algorithm. Finally, the selected important features are input into the LSTM network to predict the volatility, and the 90% confidence interval of the volatility is calculated. Compared with a variety of single and combined models, the model proposed in this study has an average reduction of 45.404% in the evaluation index of mean squared error. The experimental results show that the model proposed in this study has a good performance and accuracy in predicting the volatility of natural gas load.

Design and development of a liquid nitrogen cooled test cryopump for application in Steady-state Superconducting Tokamak-1

Cryocoolers and liquid helium cooled sorption cryopumps are widely used for the generation of high and ultra-high vacuum in large size experimental systems. Application areas of the sorption cryopumps using only liquid nitrogen is not explored much. Aiming to that, liquid nitrogen cooled test cryopump is designed, developed and fabricated to confirm the application feasibility on Steady-state Superconducting Tokamak-1 (SST-1) for pumping nitrogen and water vapor. After rough vacuum, base pressure ≤2.0E-7 mbar is achieved in the pumping dome using the cryopump. In addition, the pumping performance tests of the cryopump were carried out as per the AVS recommended method. The system offers pumping speed of ∼3616 l/s for nitrogen gas and 15928 l/s (N2 equivalent) for water vapor using liquid nitrogen only and the temperature on the panels were 80–81 K. Adsorption capacity for nitrogen gas was tested up to 6123 mbar-l and maximum gas load applied was 8.0E-2 mbar-l/s. In this paper, the pump design concept, analysis, pumping speed simulations, selected sorbent application and experimental investigations are discussed systematically.

Optimal Coordinated Control of Multi-Renewable-to-Hydrogen Production System for Hydrogen Fueling Stations

Under the pressure of climate change, the demands for alternative green hydrogen (H₂) production methods have been on the rise to conform to the global trend of transition to a H₂ society. This article proposes a multirenewable-to-hydrogen production method to enhance the green H₂ production efficiency for renewable-dominated hydrogen fueling stations (HFSs). In this method, the aqueous electrolysis of native biomass can be powered by wind and solar generations based on electrochemical effects, and both electrolysis current and temperature are taken into account for facilitating on-site H₂ production and reducing the electricity consumption. Moreover, a capsule network based H₂ demand forecasting model is formulated to estimate the gas load for HFS by extracting the underlying spatial features and temporal dependencies of traffic flows in the transportation network. Furthermore, a hierarchical coordinated control strategy is developed to suppress high fluctuations in electrolysis current caused by volatility of wind and solar outputs based on model predictive control framework. Comparative studies validate the superior performance of the proposed methodology over the power-to-gas scheme on electrolysis efficiency and economic benefits.

Development of mathematical model of tangential regeneration of filter partitions of small-sized dust collecting devices of power plants

The energy development vector is currently aimed at increasing application of renewable fuels. Air pollution is one of the most significant consequences of fuel combustion. The issue is of current importance for small power plants subordinate to the Department of Public Utilities of the Ministry of Defense of the Russian Federation. To solve the problem, it is necessary to both update the existing equipment and to develop fundamentally new gas cleaning equipment that have high cleaning efficiency, reduced hydraulic resistance and smaller size. Thus, these issues determine the relevance of development of mathematical models of filtering equipment operation. To solve the problem, the method of mathematical modeling is used. The model uses the mathematical apparatus of aerohydromechanics using the k- turbulence model. The study of the influence of parameters on the flow of the process has been carried out by numerical methods in the computational fluid dynamics software environment. A mathematical model is proposed that allows us to determine and design pressure and velocity fields in the gap between the filter housing and the filter element at different speeds of the inlet gas flow. It makes possible to quickly assess the degree of clogging of the filter according to the dynamics of pressure changes at the outlet pipe of the filter. The results of the numerical experiment have been confirmed by laboratory studies. The developed mathematical model of the process of tangential regeneration of filter baffles makes it possible to estimate the pressure and velocity fields in the gap that influence on the entrainment of dust particles. Thereby one can predict the efficiency of the filter depending on the specific gas load and the width of the gap. The results of numerical experiments are consistent with the physical concepts of the process. They prove the prospects of the method to create a tangential flow to remove the settled particles of the dispersed phase from the surface of the filter element. The developed model can be used in the engineering practice of designing filters and controlling the filtration process.

Investigation of Polycyclic Aromatic Hydrocarbons (PAHs) Uptake by Cucurbita pepo under Exhaust Gas Loading

It was aimed to compare the uptake of PAHs (Polycyclic aromatic hydrocarbon) by Cucurbita pepo fruits exposed to exhaust gas or not in a greenhouse chamber. Cucurbita pepo vegetable was grown in two greenhouses, which were formed as control group and experimental group. The experimental group greenhouse was regularly exposed to exhaust gas for a certain period, no intervention was made to the control group. PAHs were measured in grown Cucurbita pepo samples and indoor air of greenhouse by passive air sampler (PAS). The average ∑16PAH concentration in Cucurbita pepo in the experimental group (exposed to exhaust gas) was 191.5 ng/g, compared with 124.8 ng/g in the control group (not exposed). The nearness of the vegetable to exhaust gas source were effective on the PAH levels. A significantly positive relationship (p < 0.05) was observed in PAH concentration between Cucurbita pepo and indoor air. It was found that PAH levels measured in the Cucurbita pepo vegetable were increased in proportion to PAH exposure, but this amount tended to decrease in the Cucurbita pepo growing sufficiently. Benzo(a)pyrene had the highest toxic equivalence value in health risk assessment calculations. A negative effect of excess foliation on plant growth rather than fruit production was observed under exhaust gas exposure.

Pilot Quality-Assurance Study of a Third-Generation Batch-Mode Clinical-Scale Automated Xenon-129 Hyperpolarizer.

We present a pilot quality assurance (QA) study of a clinical-scale, automated, third-generation (GEN-3) 129Xe hyperpolarizer employing batch-mode spin-exchange optical pumping (SEOP) with high-Xe densities (50% natural abundance Xe and 50% N2 in ~2.6 atm total pressure sourced from Nova Gas Technologies) and rapid temperature ramping enabled by an aluminum heating jacket surrounding the 0.5 L SEOP cell. 129Xe hyperpolarization was performed over the course of 700 gas loading cycles of the SEOP cell, simulating long-term hyperpolarized contrast agent production in a clinical lung imaging setting. High levels of 129Xe polarization (avg. %PXe = 51.0% with standard deviation σPXe = 3.0%) were recorded with fast 129Xe polarization build-up time constants (avg. Tb = 25.1 min with standard deviation σTb = 3.1 min) across the first 500 SEOP cell refills, using moderate temperatures of 75 °C. These results demonstrate a more than 2-fold increase in build-up rate relative to previously demonstrated results in a comparable QA study on a second-generation (GEN-2) 129Xe hyperpolarizer device, with only a minor reduction in maximum achievable %PXe and with greater consistency over a larger number of SEOP cell refill processes at a similar polarization lifetime duration (avg. T1 = 82.4 min, standard deviation σT1 = 10.8 min). Additionally, the effects of varying SEOP jacket temperatures, distribution of Rb metal, and preparation and operation of the fluid path are quantified in the context of device installation, performance optimization and maintenance to consistently produce high 129Xe polarization values, build-up rates (Tb as low as 6 min) and lifetimes over the course of a typical high-throughput 129Xe polarization SEOP cell life cycle. The results presented further demonstrate the significant potential for hyperpolarized 129Xe contrast agent in imaging and bio-sensing applications on a clinical scale.

An Improved Model for the Prediction of Liquid Loading in gas Wells using Firefly and Particle Swarm Optimization Algorithms

Liquid loading is an undesired phenomenon in gas wells that occurs when producing wells attain a flow rate below which liquid will not be able to flow to the surface. The inability of the energy from the gas to transport the liquid to the surface causes back flow and eventual accumulation of liquid at the wellbore. This is characterised by intermittent flow, which, if left unchecked, can eventually kill the well. An effective and reliable predictive method must therefore, be employed. In this study, improved models based on data set from condensate/water in a gas well were developed by applying firefly (FA) and particle swarm optimisation (PSO) algorithms. The results showed that the model developed out perform many of the existing models. The models predicted liquid loading in gas well at 86% level of accuracy compared to the 81% highest possible from published models. Although, the FA and PSO models predicted liquid loading at higher accuracy compared with Turner and Coleman models for higher wellhead pressure systems, the Coleman model appeared to perform better in the prediction of critical gas rate for low-pressure systems. However, the developed model can significantly improve the prediction of liquid loading in gas wells at a higher reliability and accuracy levels. Thus, the proposed models can be a veritable tool for accurately predicting liquid loading in gas wells.

A permeability model for coal based on elastic and plastic deformation conditions under the interaction of hydro-mechanical effects

In engineering activities involving the mining of coal resources, gas is the main factor for causing coal and gas explosions accidents, with permeability being an important parameter in estimating gas emissions. With the steady development of the mining face, stress in front of the work face has evidently changed, that has resulted in coal damage under mining disturbance. In the underground environment, coal is in a complex environment where water, gas and external loads combine with each other, leading to changes in permeability that are often extremely complex, with effective stress being the dominant factor to changes in permeability. Therefore, coal permeability change related to damage-induced effects under different water contents should be further studied. In this study, first, the influence of water, gas adsorption and effective stress on coal fracture permeability change were considered. Further, damage variables were introduced to combine mechanical damage with water weakening damage. By quantifying changes in matrix sizes with new fracture generations, the plastic deformation in fractures was estimated. Based on a cubic model, a damaged-induced permeability model under the interaction of hydro-mechanical effects was established. From this, a triaxial seepage experiment involving the whole stress-strain process, including effective stress changes of water-bearing coal, was conducted to compare with, and to verify the results against an established model. The experimental results revealed that changes in axial strain and permeability was “S” shaped during the whole stress-strain process. In addition, during the whole stress-strain and effective stress changes process, the permeability model corresponded well with the experimental results. This demonstrated that the model could not only predict permeability change under elastic deformation, but could also describe permeability changes under plastic deformation during the damage stage. The purpose of this study was to provide a new method for predicting the permeability evolution law relating to coal mining and gas extraction.

Dynamic modeling and predictive control of boil-off gas generation during LNG loading

During liquefied natural gas (LNG) loading, excessive boil-off gas (BOG) is generated due to the temperature difference between the LNG and a tank at room temperature. While one way to deal with this challenge is to gradually reduce the tank temperature via an LNG, this cool-down process may also produce excessive BOG, if not properly handled, leading to a sudden pressure change inside the tank. To this end, a model predictive control (MPC) system was formulated in this work to simultaneously regulate the pressure and temperature of the tank by manipulating the vapor outlet flow rate and the amount of LNG spray injected during the cool-down process. Specifically, a high-fidelity model of cool-down process was developed and simplified to a reduced-order model (ROM). Then, the ROM was incorporated into the developed MPC scheme which successfully computed an input profile to drive the pressure and tank temperature to target values.

Spatio-temporal 1D gas–liquid model for biological methanation in lab scale and industrial bubble column

Numerical simulation of biological methanation in bubble column reactors is challenging due to strong coupling between hydrodynamics, mass transfer and bioreaction. A satisfactory prediction of the mass transfer coefficient and the gas solubility is crucial to couple hydrodynamics and biokinetics. A comprehensive 1D multispecies multiple-way coupled gas–liquid model is developed. The hydrodynamics of the model is validated using experimental gas loading data at very low gas holdup. The local mass transfer is validated using literature data on CO2 mass transfer in the large-scale. The local gas holdup and interfacial CO2 mass transfer flux are correctly described thanks to a two-way coupling between hydrodynamics and mass transfer, including changes in bubble diameter and pressure effects. When a mixture of H2, CO2 and CH4 is used, highly non-linear mass transfer profiles due to differences in solubilities are observed. An original flux-based metabolic model is proposed to simulate an industrial biological methanation process. This allows smooth transition between biologically and physically controlled regimes as the culture reaches a steady-state. The comprehensive model enlightens that the biological methanation performances are governed by the H2 mass transfer limitation balanced by growth in the transient state and biological maintenance in the steady-state.

Development of a Continuous Photo-catalytic/Ozonation System: Application on Amido Black Removal from Water

ABSTRACT A continuous system for photo-catalytic/ozonation was designed at laboratory scale and evaluated for water treatment using Amido Black 10B dye (AB) as a pollutant model. The effect of single ozonation (O3), photolytic ozonation (UV/O3) and combined photocatalytic/ozonation treatment (UV/O3/TiO2) were investigated. TiO2 nanocatalysts films were coated on stainless steel grids (AISI 304) by Atomic Layer Deposition technique (ALD) at 350 °C. An experimental hydrodynamic study of the designed reactor was conducted based on dry and total pressure drop. Three flow regimes were observed by increasing the total pressure drop against gas load factor (Fs). Depollution experiments conducted on the developed reactor showed that reaction rates and efficiency of studied processes were dependent on the studied operational parameters (initial dye concentration, ozone dose, pH). The maximum AB dye ([AB]0 = 100 mg. L−1) conversion efficiency, using the designed (UV/O3/TiO2) system, was about 40.3% of initial TOC and 100% AB color removal was achieved within 10 min at an optimal ozone dose of 132 mg. L−1. A significant improvement in AB removal using UV/TiO2/O3 process (koverall = 0.056 min−1, 40.3%) compared to O3 alone (koverall = 0.032 min−1, 26.87). Results shows also that the addition of tert-butanol (TB), as radical scavenger ([TB] = 0.2 M and 0.4 M), greatly affects the reaction mechanisms of a photocatalytic ozonation process within 5 min of reaction, by decreasing the Amido Black conversion from 99.67% ([TB] = 0 M) to 74.63% and 31.35%, respectively, in presence of 0.2 M and 0.4 M of tert-butanol. The remarkable decrease in AB removal rate observed in the presence of a radical scavenger expresses that there was an obvious enhancement of hydroxyl radical OH• generation due to the synergetic effect between ozone and photocatalytic processes.

Robust Pricing of Energy and Ancillary Services in Combined Electricity and Natural Gas Markets

Rapid growth of gas-fired generators strengthens the interdependency of electricity and natural gas markets. To meet the uncertainty challenge, a robust day-ahead market clearing framework for the integrated electricity and natural gas system (IEGS) is presented. First, a robust security-constrained unit commitment (SCUC) model is built considering the joint dispatch of ancillary services. Regulation-up/down reserve is scheduled to balance electrical load/wind power uncertainties, spinning reserve is to manage N-1 generator outage, and natural gas reserve is to withstand gas load uncertainty and provide fuel for gas-fired electrical reserve. The SCUC model is a two-stage mixed-integer nonlinear optimization problem so that a sequential linear approximation-based Column & Constraint Generation (SLA-based C&CG) algorithm is proposed. Then, according to SCUC solutions, an economic dispatch model is derived to obtain market clearing and pricing results. Based on locational marginal pricing, novel definitions of electrical energy, natural gas and multiple ancillary service prices are proposed, which can reflect network limits and uncertainty effects. Numerical cases on two test IEGSs and a provincial-level IEGS demonstrate the high accuracy of proposed SLA-based C&CG algorithm and the impact of uncertainties on market clearing.

Results of experimental studies of cold running-in of a diesel engine D-240 with increased load-rate modes

Currently used diesel engine running-in methods are based mainly on typical technologies with the use of serial running-in and braking stands, which have limited speed and capacity for cold and hot running-in at idle and under load of all types of modern diesel engines, available in agricultural enterprises. In addition, typical running-in technologies have a number of technological, economic and environmental drawbacks. Taking into account high cost of up-to-date running-in equipment and low level of equipment of enterprises with serial running-in equipment, including those with long service life, the modernization of existing equipment is the urgent task, as well as the development of new technologies and means for their realization. The technology of cold running-in of diesels with increased load-rate modes using modernized running-in-brake stands and the developed system for increasing gas loads is proposed. The results of experimental studies show the possibility of creating higher load-rate modes during cold running-in of diesels and allow improving the typical technologies of running-in of diesels and means for their implementation.

Electricity‐heat‐gas integrated demand response dependency assessment based on BOXCOX‐Pair Copula model

With the continuous development of Regional Integrated Energy System (RIES), demand response (DR) is composed of diversified loads including electric load, heat load and gas load. Their cross-dependencies reflecting the nonlinear coupling complementary relationship between each load type are one of the key factors to improve multi-energy flow optimisation modelling and utilisation efficiency on the demand side. Accordingly, this paper proposes a DR dependency assessment method considering electricity-heat-gas loads based on the BOXCOX-Pair Copula model. BOXCOX transformation is introduced to convert various probability distribution statistics of electricity-heat-gas loads into Gaussian distributed variables. C-vine Pair Copula is used to characterise an ensemble-of-trees of high-dimensional dependency structure among multi-energy demand modalities. Then the combined model of BOXCOX transformation and C-vine Pair Copula can be employed to determine the complex coupling dependency among electricity-heat-gas loads according to different DR statistics. Some metrics between the original empirical distribution and BOXCOX-Pair Copula distribution are introduced to assess the dependency evaluation precision of the proposed model. Finally, the novel dependency assessment model is numerically tested utilising the electricity load, heat load and gas load data sequences in a real RIES. The results illustrate that the cross-dependency of electricity-heat-gas integrated DR based on the BOXCOX-C-vine copula model is closer to that of actual sample data, which verify the effectiveness and superiority of the proposed approach.

Composite materials in aircraft engine blades

The article investigates the strength of the propeller blades made of a multilayer composite material, subjected to centrifugal and gas loads with various combinations of fiberglass and carbon fiber and orientation of the material base. The finite element method is used as a research method. A propeller blade used in turbines of jet engines and compressors, made of composite materials, is considered as a naturally twisted rod, provided that the hypothesis of flat sections across the thickness of a multilayer composite package is valid under conditions of rigid contact at the boundary of layers. The propfan blade model is modeled by four-node finite elements of natural curvature with forty-eight degrees of freedom, taking into account the compression of the normal. The applied method for calculating the strength makes it possible to assess the strength of an arbitrarily reinforced blade in sections and layer by layer. The blades of hydrodynamic engines of the first and second stages were considered under the action of centrifugal and gas loads. The stress was determined at 17 points of 21 cross-sections in layers. As a result of the study, the strength parameters of the blades with different ratios of the dissimilar materials of the layers of the multilayer composite material were obtained. Conclusions are drawn, based on the fact that the blades made of composite material have significant advantages in terms of strength and weight characteristics compared to blades made of materials traditionally used in technology in the manufacture of propfans.

Circular economy in the brewing chain

The main aim of this review was to check for the applicability of the concept of circular economy to brewing chain. By analyzing the beer brewing process, it was possible to identify the main brewery wastes formed and packaging materials used as well as their range of composition and yields. In order to reduce the contribution of packaging material to the carbon footprint of beer, it would be necessary to replace one-way containers used nowadays with lighter, reusable, or recycled ones. Even if the contribution of beer consumption phase was taken into account, there was no definitive solution about the less environmentally impacting beer packaging format. The direct management of polyethylene terephthalate (PET) packaging for liquid foodstuffs could make available 100% recycled PET flakes to be reconverted into food-grade bottles with minimum downcycling to other non-food usage. The countless potential uses of brewery wastes in nutritional and biotechnological fields were tested in laboratory by disregarding any cost–benefit or market analysis. This was mainly because the estimated market price of dried brewer’s spent grain (BSG) resulted to be about 450% higher than that of conventional lignocellulose residues. All the alternative uses hailed in the literature appeared to be more useful for publishing articles than for defining any economically feasible reusing procedure for all brewery wastes. Owing to their high moisture content, such wastes are so perishable as to prevent their safe usage in the human food chain. Currently, their use as-is in animal feeding is the disposal method not only economically feasible but also able to reduce the greenhouse gas load of beer packed in glass bottles (GB) by about one-third of that associated with packaging materials. Not by chance, it is practiced by most industrial and craft breweries.

Experimental investigations of direct measurement of borehole wall pressure under decoupling charge

Decoupling charge is quite widely applied in smooth blasting, pre-splitting blasting, and bench blasting. The borehole wall pressure (BWP) is an indispensable condition for analyzing blasting action as it is the main initial parameter that determines the stress wave generated in the rock. In this study, a full-scale concrete model (4.0 m in length × 3.0 m in width × 1.6 m in height) with two boreholes was utilized to directly measure the BWP under decoupling charging. PVDF (polyvinylidene fluoride) gauges were employed as pressure-sensing devices to develop a technique for direct measuring high dynamic pressure due to its superior characteristics. The values of measured peak pressures of the borehole wall ranged from 1461 to 205 MPa within 0.1–1.1 m from the explosive charge end along the borehole axis. BWP of decoupling charge are responses to air shock wave loading and explosion gas loading, in which the responses near the explosive charge are the results of air shock wave and explosion gas working together, while the responses far from the charge are merely loaded by the air shock wave. The strain rates varied from 2.12 to 0.73 s−1 for the test range, which has confirmed that decoupling blast loading is a quasi-dynamic process. By fitting the experimental data, it is found that the peak value of BWP along the borehole axisdecreases as a power function with the increase of the distance from the explosive. The findings may be of great significance to mechanism analysis of rock blasting, scientific design of blasting schemes, and numerical simulation of rock blasting.