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The nuclear energy development strategy in Russia involves the construction and commissioning of a number of new nuclear power plants, which will lead to an increase in the share of nuclear power plants in the country's energy systems. Based on the information presented in the energy development strategy of Russia for the period until 2035, it is planned to involve nuclear power plants with generation «3+» reactors in regulating the unevenness of daily electrical load schedules. In these circumstances, unloading of the nuclear power plant is inevitable, which is ineffective for a number of reasons. Combining a nuclear power plant with a hydrogen complex makes it possible to achieve the goals set by the government of the Russian Federation, starting from the need to introduce a third-party energy complex that adapts the nuclear power plant to an alternating operating mode without changing the thermal load on the reactor and steam generators. There is a known option for combining a nuclear power plant with a hydrogen complex using piston compressor units, but the introduction of this type of equipment negatively affects the probability of failure-free operation of the hydrogen complex as a whole due to the high failure rate. The new concept of combining a nuclear power station with a hydrogen complex implies the exclusion of gas compressors by organizing excess pressure in a capacitive storage system due to the electrolysis of high-pressure water. In this case, the compressors are replaced with pressure reduction units that meet a higher level of reliability. The main results of the work carried out are a probabilistic assessment of reliability and an analytical comparison of capital investments in the reserve of the hydrogen complex, which allows us to collectively reflect the impact of changes in the number of reserves in terms of the probability of failure-free operation and the economic side of the study. As the assessments performed have shown, a hydrogen complex based on the use of high-pressure water electrolysis has a higher level of reliability, as well as, in the considered pressure range, lower capital costs for reserve. [ABSTRACT FROM AUTHOR]

The sudden surge phenomenon in an axial compressor represents one of the most critical issues that can confront a turbojet engine. This phenomenon primarily arises from the engine ingesting hot exhaust gases from weaponry systems, particularly in military aircraft, potentially leading to engine failure. This study delves into the impact of hot gas ingestion on compressor stability and compares a range of effective methods to prevent surge in such cases which are: (1) air bleed from the compressor, (2) fuel cut-off, (3) gas cooling through water injection at the air inlet. The R29-300 twin-spool turbojet engine was chosen for computational experiments due to the availability of the necessary digital information for mathematical modelling of this engine. It is a two-shaft turbojet engine consisting of a low-pressure compressor (5 stages), a high-pressure compressor (6 stages), an annular combustion chamber, a high-pressure turbine (two stages), and a low-pressure turbine (one stage). The results showed that introducing gases with a heating rate of up to 5000 Kelvin per second causes the low-pressure compressor to exit its stable operating regime and the engine to stall. The effect on the high-pressure compressor was minimal and did not exceed the stability limits, therefore the focus of the procedures was on the low-pressure compressor. The results also showed that both methods 1 and 2 are effective in preventing surge within an acceptable stability range, but they have several drawbacks, including a decrease in engine thrust and efficiency. On the other hand, the water injection method eliminates the root cause of surge by cooling the incoming gases and maintains engine stability. The amount of water required for this process is relatively small and can be carried on aircraft without a significant impact on weight and volume. [ABSTRACT FROM AUTHOR]

Transient gas network simulations can significantly assist in design and operational aspects of gas networks. Models used in these simulations require a detailed framework integrating various models of the network constituents ‐ pipes and compressor stations among others. In this context, the port‐Hamiltonian modelling framework provides an energy‐based modelling approach with a port‐based coupling mechanism. This study investigates developing compressor models in an integrated isothermal port‐Hamiltonian model for gas networks. Four different models of compressors are considered and their inclusion in a larger network model is detailed. A numerical implementation for a simple test case is provided to confirm the validity of the proposed model and to highlight their differences. [ABSTRACT FROM AUTHOR]

Counter-rotating wet gas compressor is an ideal equipment for pressurizing natural gas in offshore gas fields. It has a compact structure, a wide range of operating conditions, and a certain liquid tolerance in the process of gas pressurization. However, due to the opposite rotation of the adjacent rotors, and the characteristics of the flow containing liquid, it is also easy to lead to flow separation in its interior and then produce obvious energy dissipation. In this paper, the numerical simulation of the internal flow field of counter-rotating axial-flow compressor under dry and wet conditions is carried out. The entropy production theory based on the second law of thermodynamics is introduced to analyze the energy consumption of the compressor, and the high energy consumption area in the internal flow field of the compressor is accurately located. Then, the energy consumption of this area is evaluated quantitatively and qualitatively. The entropy production and its proportion of each component under different working conditions, the distribution of the entropy production of each rotor along the flow direction, and the radial distribution under the near-stall state are obtained. The calculation results show that the entropy production of upstream rotor and downstream rotor in the total entropy production is 29.19%–31.41% and 59.48%–62.61% under dry gas conditions, respectively. Under wet conditions, the proportions are 28.20%–30.67% and 60.02%–63.33%, respectively. The wet gas droplets can increase the momentum input to the low energy region of 0.7–0.9 relative position of the suction surface of the upstream rotor and improve the flow field in this region. However, it can also exacerbate flow separation in the front middle of the downstream rotor, causing additional energy loss. [ABSTRACT FROM AUTHOR]

The dynamic characteristics of an electromagnetic actuator used in a switching valve are influenced by self-induced effects, resulting in instability in its parameters when subjected to changes in working frequency, load, and other conditions. To quantitatively analyze the impact of variable working conditions, this study establishes an analytical expression for periodic signals through Fourier series expansion. It subsequently solves for transient current, yielding a new model for the response of the electromagnetic actuator under periodic signal excitation. Simulations and analyses are conducted to investigate the variation in action parameters of the electromagnetic actuator in the realm of compressor gas regulation when working conditions, such as rotation speed and load force, are altered. The results indicate that dynamic characteristics of the actuator change within the range of 8% to 35%, significantly affecting the gas regulation efficiency of the compressor. To mitigate this effect, a backstepping adaptive high frequency controller (BAHF) is proposed. Comparative assessments with the backstepping adaptive sliding model controller (BASM) and backstepping adaptive high gain controller (BAHG) reveal that the BAHF exhibits superior overall performance. An experimental platform is constructed to validate both the model's accuracy and the controller's effectiveness. The error between model simulations and experiments does not exceed 7.5%, confirming the accuracy of the model. The proposed BAHF reduces the fluctuation of compression and exhaust phase angles in the compressor by 21.6% and 6.6%, respectively, under variable working conditions. This reduction effectively suppresses the influence of working condition disturbances, yielding positive outcomes. [ABSTRACT FROM AUTHOR]

Faulty compressors must be timely detected to prevent excessive energy consumption, maintenance, and energy costs. Existing diagnostics models lack addressing the energy performance indicators and do not provide effective hybrid machine learning (ML) model for advanced fault diagnosis to prevent compressors from becoming energy hogs. Therefore, this study proposed a novel approach in the form of an energy-based diagnostic model for integrating energy performance indicators to detect the healthy and faulty behavior of the compressor using a hybrid ML model. The time series analysis and Isolation Forest techniques have been used to detect faulty and healthy behavior of centrifugal gas compressor. To obtain more insight and prevent false alarms the hybrid ML model was introduced. The Ridge regression was used as the meta-classifier in the suggested hybrid model, which receives the input from the base classifiers Decision Tree (DT), k-Nearest Neighbors (kNN), and Gradient Boosting (GB) to optimize the performance and accuracy of hybrid model. This study was conducted on a two-stage centrifugal compressor that compresses production gas for export powered by a gas turbine at Malaysia's PETRONAS Angsi oil and gas field. According to the findings, the energy efficiency predicted for the first stage was 84.2% for healthy behavior and 69.7% for faulty behavior, while for the second stage, it was 83.2% for healthy behavior and 68.1% for faulty behavior, indicating high energy efficiency during the healthy operation of a centrifugal compressor in comparison with faulty behavior. The slight difference between the proposed diagnostic model training, testing, and prediction performance accuracy 0.98, 0.97 and 0.99 proposes a model is efficient neither overfitting nor underfitting according to the value of co-efficient of determination (R2). The R2 values for training, testing, and prediction performance accuracy for the GB model were 0.95, 0.93, and 0.94; for kNN, 0.89, 0.87, and 0.86, and for Tree, 0.95, 0.94, and 0.93 respectively. According to the results, the proposed hybrid model performs more eloquently and efficiently than other single models DT, kNN, and GB. This study empowers operators to take critical measures to increase energy efficiency, reduce downtime, and schedule maintenance to improve the reliability of centrifugal gas compressor. [ABSTRACT FROM AUTHOR]

Brush seals are extensively used in rotating equipment, such as gas turbines and compressors, providing effective sealing while accommodating radial, axial, and angular movements between components. In this study, the performance of brush seals with and without clearances was predicted through axisymmetric 2D computational fluid dynamic (CFD) simulations using a porous media model. Because the accurate modeling of a brush seal requires the appropriate porosity to be determined and the flow resistance to be calculated, a porosity correction was performed based on the brush seal's geometry and pressure ratio. The corrected porosity was then used to calculate the flow resistance and the leakage flow rate was predicted. Based on the results, the corrected porosity significantly improved the accuracy of the previously unreliable leakage flow rate predictions, regardless of the presence of clearances. For cases with a clearance, the blow-down effect was determined through CFD simulations for the given geometry and was compared with experimental data. The leakage flow rate predictions were highly accurate, with a relative error of less than 5% across a pressure ratio range of 1.5–4. [ABSTRACT FROM AUTHOR]

Ventilation, cooling, heating, and air conditioning (HVAC) systems represent a substantial portion, approximately 40%, of energy consumption in buildings. Among the key components of HVAC/R systems, the compressor, fans, and electrical resistances are major consumers of electricity. In this context, the compressor stands out due to its significant dynamic behaviour, serving as the pivotal element in heat pump operations. However, many manufacturers solely provide empirical data regarding compressor performance, lacking comprehensive models for assessing performance across various operational conditions. This paper addresses the methodology for evaluating mathematical models utilizing experimental compressor data. Through this approach, we aim to bridge the gap between empirical observations and predictive modelling, enabling a more nuanced understanding and optimization of HVAC/R system performance. The proposed model uses interpolation and it takes as input the evaporation and condensation temperatures. It shows an R -- square and adjusted R -- square value of 0.99. By using the experimental data and an open -- source library for interpolation this paper paves the way for a flexible and practical compressor modelling. [ABSTRACT FROM AUTHOR]

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The current research aims at finding a new appropriate way to optimize and reduce water consumption by using various forms of pinch technology in petrochemical complexes due to high rate of water consumption. For this purpose, precise studies were conducted on ethylene plant. In this research, cracked gas compressor (CGC) system was considered to analyze energy and minimize water consumption of heat exchanger network (HEN). Initially, process of the CGC system has been simulated with Aspen HYSYS. Next, Aspen Energy Analyzer software was used to identify cooling water (CW) heat exchangers and economic analysis of HEN. Consequently, composite curves and grand composite curves and other results of HEN simulation were examined. The results of HEN simulation indicate that 91% of cooling loads provided by CW utility is the most widely used fresh water. Despite water circulation system of cooling tower (CT), the rate of water loss is high in this utility. As the design temperature is 40 °C and the minimum approach temperature (ΔTmin) is 10 °C, the new utility pinch point has been estimated 50 °C. In proposed modified case, air coolers were considered before the CW heat exchangers of the CGC system. In this way, air-cooled (AC) utility covers up cooling loads up to 50 °C in the modified unit. Then, the modified unit was compared with main unit. In the modified unit, 78% of cooling loads of the HEN have been covered by AC utility in which this action leads to 86% reduction in energy and water consumption of CW heat exchangers and CT. By reducing the rate of water loss in CT circulation systems, cost of supplying fresh water reduced to the lowest possible which leads to 34% optimization in HEN operating cost in the modified unit. Also in the CGC system, steam turbine is used for supplying power consumption of compressor used to CW steam turbine condenser. This condenser is the most commonly used equipment in terms of water consumption, so that there is 32% more than the total water consumption of the HEN. In the last part of this study, AC steam turbine condenser replaced the CW steam turbine condenser in the modified case. So in this case, the use of AC steam turbine condenser with power consumption (980 kw) leads to 98% reduction in water consumption of the steam turbine condenser. [ABSTRACT FROM AUTHOR]

The scroll compressor is a kind of positive-displacement compressor applied in refrigeration systems, heat pump systems, and air conditioner systems. Using the spring smoothing method and considering the heat transfer, the numerical simulation model of the scroll compressor is established under standard working conditions. The results show that the CFD model is well validated by the experiment result. The compressor performance and the working process are analyzed. The pre-compression and the over-compression phenomenon are also studied. Moreover, the temperature distribution and velocity distribution of gas flow in the compressor are illustrated. The result shows that the pre-compression can improve the performance of the scroll compressor and the optimization of the suction channel geometry can provide a smoother suction process. Under the combined effect of the pre-compression and heat transfer, the refrigerating capacity is increased by approximately 0.54 kW and the volume efficiency is increased by approximately 2.2%. The additional power loss due to over-compression is 47.6615 W, and the setting of over-compression discharges can reduce the pressure and power loss. This study is helpful to the performance prediction and the structural optimization of the scroll compressor. [ABSTRACT FROM AUTHOR]

For a gas undergoing a compression process, it is more appropriate to think of either isentropic or polytropic efficiency as process-defining parameters indicating that a given end state of compression has been achieved, rather than a measure of effectiveness of conversion of one form of energy into another. The polytropic efficiency, as defined in ASME PTC-10 standard for compressor field trials and acceptance tests, actually involves the comparison of two distinct compression processes, neither of which are actually connected to the performance of the compressors producing them. Consequently, it is not rational to compare the ASME PTC-10 polytropic efficiency of a compressor designed to compress a gas predominantly adiabatically with that for a compressor designed to compress a gas predominantly isothermally. A framework correcting this situation is set out and is illustrated with several numerical examples. Suggestions for maintaining backward compatibility with ASME PTC-10 are also put forward. [ABSTRACT FROM AUTHOR]

• The thermal-fluid-structure coupling method is proposed in this study. • Thermal deformation of the structure is considered in the proposed model. • The effect of low temperature on the compressor efficiency is analyzed. • The effect of the rotor deformation on the compressor performance is studied. • The effect of operating conditions on the compressor efficiency is investigated. The boil-off gas (BOG) twin-screw compressors are widely used in the transportation of liquefied natural gas. A thermal-fluid-structure (TFS) simulation model of the screw compressor is established based on the conjugated heat transfer and weak fluid-structure coupling method. The thermal deformation of the structure at a steady state is considered in the CFD simulation to improve the calculation accuracy. The accuracy of the calculation results was verified by the experiment on a high-speed oil-free twin-screw air compressor. The thermal performance and the compressor efficiencies at different operating conditions were obtained by simulations. It was found that the volumetric efficiency increased from 67 to 78 % while the isentropic efficiency increased from 64 to 75 % with increasing the suction temperature. The volumetric efficiency reduced from 76 to 71 % with increasing the discharge pressure while the isentropic efficiency reached the maximum value of 70 % when the discharge pressure was equal to the end-of-compression pressure. Besides, when the rotational speed was lower than 6000 rpm, increasing the rotational speed had a significantly positive effect on the compressor efficiencies. The volumetric efficiency increased slowly when the speed raised from 6000 to 10,000 rpm. The isentropic efficiency reached a maximum of 73 % at the speed of 8000 rpm, which decreased to 72 % at 10,000 rpm. [ABSTRACT FROM AUTHOR]

This paper presents a multidisciplinary design methodology for a single-stage radial compressor of a small-scale gas turbine jet engine. The entire engine, producing more than 600 N thrust with an engine diameter of less than 30 cm, will be manufactured by additive manufacturing (AM) in a single piece. Therefore, it is crucial to pinpoint the design limitations that may arise due to the AM methods. The preliminary design calculations are carried out in the Von Karman Institute for Fluid Dynamics (VKI's) in-house centrifugal compressor off-design (CCOD) code. The detailed design and optimization studies coupled with computational fluid dynamics (CFD) simulations are performed to improve the aerodynamic performance of the radial compressor by using the sequential quadratic programming (SQP) method with an Adjoint solver in the VKI's in-house computer aided design and optimization (CADO) tool. In the final design, a large increase in thrust is obtained and the manufacturing constraints are satisfied. [ABSTRACT FROM AUTHOR]

The article discusses a solution to the relevant task of analyzing and designing modular buildings made of blocks to be used in industrial and civil engineering. A block that represents a container is a combination of plate and beam systems. The criteria for its failure include both the strength of the individual elements and the loss of stability in a corrugated web. Methods of engineering analysis are hardly applicable to this system. Numerical analysis based on the finite element method is time-consuming, and this fact limits the number of design options for modular buildings made of blocks. Adjustable machine learning models are proposed as a solution to these problems. Decision trees are made and clustered into a single ensemble depending on the values of the design parameters. Key parameters determining the structures of decision trees include design steel resistance values, types of loads and the number of loadings, and ranges of rolled sheet thickness values. An ensemble of such models is used to take into account the nonlinear strain of elements. Piecewise approximation of the dependencies between components of the stress–strain state is used for this purpose. Linear regression equations are subjected to feature binarization to improve the efficiency of nonlinearity projections. The identification of weight coefficients without laborious search optimization methods is a distinguishing characteristic of the proposed models of steel blocks for modular buildings. A modular building block is used to illustrate the effectiveness of the proposed models. Its purpose is to accommodate a gas compressor of a gas turbine power plant. These machine learning models can accurately spot the stress–strain state for different design parameters, in particular for different corrugated web thickness values. As a result, ensemble models predict the stress–strain state with the coefficient of determination equaling 0.88–0.92. [ABSTRACT FROM AUTHOR]

A dry gas seal (DGS) is one of the key basic components of natural gas transmission pipeline compressors, and the sealing performance of a DGS dealing with complex multi-component pipeline natural gas is different from that dealing with conventional nitrogen medium. In this paper, a spiral groove DGS of the compressor in natural gas transmission pipeline systems is taken as the research object. The thermal hydrodynamic lubrication model of the DGS is established considering turbulence effect and choking effect. Based on the finite difference method, the temperature and pressure distributions and the steady-state performance of the DGS are obtained by simulating. The influence of unitary impurity compositions such as light hydrocarbon, heavy hydrocarbon, non-hydrocarbon, and their contents on the steady-state performance of the DGS is analyzed. The steady-state performance of the DGS dealing with multi-impurity natural gas such as in the West-East gas transmission is investigated under different operating conditions. The results show that turbulence had a significant effect on the DGS, while choking had a weak effect. Increasing the content of light hydrocarbon such as C2H6 and heavy hydrocarbon such as C5H10 resulted in an increase in the gas film stiffness, leakage rate, and the temperature difference between the inlet and outlet, while non-hydrocarbon, such as N2, reduced the temperature difference between the inlet and outlet. The greatest impact on seal performance was produced by the heavy hydrocarbon, followed by the light hydrocarbon, and the least was produced by the non-hydrocarbon. [ABSTRACT FROM AUTHOR]

Accurate and comprehensive quantification of oil and gas methane emissions is pivotal in informing effective methane mitigation policies, while also supporting the assessment and tracking of progress towards emissions reduction targets set by governments and industry. While national bottom-up source-level inventories are useful for understanding the sources of methane emissions, they are often unrepresentative across spatial scales, and their reliance on generic emission factors produces underestimations when compared with measurement-based inventories. Here, we compile and analyze previously reported ground-based facility-level methane emissions measurements in the major US oil and gas producing basins and develop representative methane emission profiles for key facility categories in the US oil and gas supply chain, including well sites, natural gas compressor stations, processing plants, crude oil refineries, and pipelines. We then integrate these emissions data with comprehensive spatial data on national oil and gas activity to estimate each facility's mean total methane emissions and uncertainties, from which we develop a mean estimate of national methane emissions, resolved at 0.1° × 0.1° spatial scales (~10 km × 10 km). From this measurement-based methane emissions inventory (EI-ME), we estimate total US national oil/gas methane emissions of 15.7 Tg (95 % confidence interval of 14–18 Tg) in 2021 which is 2.5 times greater than the EPA Greenhouse Gas Inventory. Our estimate represents a mean gas production-normalized methane loss rate of 2.6 %, consistent with recent satellite-based estimates. We find significant variability in both the magnitude and spatial distribution of basin-level methane emissions, ranging from <1 % methane loss rates in the gas-dominant Appalachian and Haynesville regions to >3–6 % in oil-dominant basins, including the Permian, Bakken, and the Uinta. Additionally, we present and compare novel comprehensive wide-area airborne remote sensing data and results of total area methane emissions and the relative contributions of diffuse and concentrated methane point sources as quantified using MethaneAIR in sub-regions of the Permian and Uinta basins that together indicate diffuse area sources accounting for the majority of total regional oil and gas emissions. Our assessment offers key insights into plausible underlying drivers of basin-to-basin variabilities in oil and gas methane emissions, emphasizing the importance of integrating measurement-based data in developing high-resolution, spatially explicit methane inventories in support of accurate methane assessment, attribution, and mitigation. The high-resolution spatially explicit EI-ME inventory is publicly available at https://doi.org/10.5281/zenodo.10734300 (Omara et al. 2024). [ABSTRACT FROM AUTHOR]

To address the shortcomings of the recently proposed Fick's Law Algorithm, which is prone to local convergence and poor convergence efficiency, we propose a multi-strategy improved Fick's Law Algorithm (FLAS). The method combines multiple effective strategies, including differential mutation strategy, Gaussian local mutation strategy, interweaving-based comprehensive learning strategy, and seagull update strategy. First, the differential variation strategy is added in the search phase to increase the randomness and expand the search degree of space. Second, by introducing the Gaussian local variation, the search diversity is increased, and the exploration capability and convergence efficiency are further improved. Further, a comprehensive learning strategy that simultaneously updates multiple individual parameters is introduced to improve search diversity and shorten the running time. Finally, the stability of the update is improved by adding a global search mechanism to balance the distribution of molecules on both sides during seagull updates. To test the competitiveness of the algorithms, the exploration and exploitation capability of the proposed FLAS is validated on 23 benchmark functions, and CEC2020 tests. FLAS is compared with other algorithms in seven engineering optimizations such as a reducer, three-bar truss, gear transmission system, piston rod optimization, gas transmission compressor, pressure vessel, and stepped cone pulley. The experimental results verify that FLAS can effectively optimize conventional engineering optimization problems. Finally, the engineering applicability of the FLAS algorithm is further highlighted by analyzing the results of parameter estimation for the solar PV model. [ABSTRACT FROM AUTHOR]

The goal of this work is to present a time-frequency-based approach to vibration condition monitoring of gas compressor valves. Due to the cyclostationary nature of reciprocating compressors frequency analysis alone is typically insufficient to assess valve condition. Experimental data is collected on an instrumented Dresser-Rand ESH-1 dual-acting reciprocating compressor by seeding known leakage fault severity levels in the suction and discharge manifold valve assemblies. Fault severity is measured by the leakage hole area and the number of damaged valve elements. By applying a short-time Fourier transform signal processing method to externally mounted vibration measurements, it is possible to identify key regions of interest in the compression cycle. Statistical features are then extracted from these regions and used to train a Bayesian classifier. The presented machine learning approach achieves greater than 90% success in assessing the valve leakage health of the compressor. [ABSTRACT FROM AUTHOR]

Methane emissions from natural gas systems are increasingly scrutinized, and accurate reporting requires quantification of site- and source-level measurement. We evaluate the performance of 10 available state-of-the-art CH 4 emission quantification approaches against a blind controlled-release experiment at an inerted natural gas compressor station in 2021. The experiment consisted of 17 blind 2 h releases at a single exhaust point or multiple simultaneous ones. The controlled releases covered a range of methane flow rates from 0.01 to 50 kg h -1. Measurement platforms included aircraft, drones, trucks, vans, ground-based stations, and handheld systems. Herewith, we compare their respective strengths, weaknesses, and potential complementarity depending on the emission rates and atmospheric conditions. Most systems were able to quantify the releases within an order of magnitude. The level of errors from the different systems was not significantly influenced by release rates larger than 0.1 kg h -1 , with much poorer results for the 0.01 kg h -1 release. It was found that handheld optical gas imaging (OGI) cameras underestimated the emissions. In contrast, the "site-level" systems, relying on atmospheric dispersion, tended to overestimate the emission rates. We assess the dependence of emission quantification performance on key parameters such as wind speed, deployment constraints, and measurement duration. At the low wind speeds encountered (below 2 m s -1), the experiments did not reveal a significant dependence on wind speed. The ability to quantify individual sources degraded during multiple-source releases. Compliance with the Oil and Gas Methane Partnership's (OGMP 2.0) highest level of reporting may require a combination of the specific advantages of each measurement technique and will depend on reconciliation approaches. Self-reported uncertainties were either not available or were based on the standard deviation in a series of independent realizations or fixed values from expert judgment or theoretical considerations. For most systems, the overall relative errors estimated in this study are higher than self-reported uncertainties. [ABSTRACT FROM AUTHOR]

Gas transportation through the pipeline network requires high pressure; otherwise, movement will be impossible. Due to friction with the walls of the pipes, the gas loses both speed and pressure. Therefore, it is necessary to increase the pressure in the main pipeline, which can extend for thousands of kilometers. For this purpose, compressor stations are located along the main network, facilitating the gas transport process by raising it to the required pressure. Compressor stations mainly consume the transported gas, with approximately 5% expended on gas compression. This article presents a study on the fuel cost for compressor stations, using mathematical models to optimize the operation of gas compressor units. The objective is to minimize gas consumption as a fuel and provide an optimization method with control over blower revolutions and valve installations to ensure safe transportation. Mathematical modeling of the described process detected the technically unjustified fuel gas consumption during the operation of gas compressor units at a specific compressor station under consideration. The paper proposes a method for minimizing costs, which can serve as the basis for providing recommendations to engineers-dispatchers. Compressor stations of the type under study lack measuring instruments for mass flow; therefore, the methods such as PID controllers, MPC, or neural networks are not applicable here. [ABSTRACT FROM AUTHOR]

• A cascade high-temperature heat pump to produce 1 MW steam at 160 °C is proposed. • District heat is introduced as available heat source for the proposed HTHP system. • Use of alternative low GWP hydrocarbons in the low-temperature loop are examined. • Water injected compressor delivers steam by just 0.9 K superheat directly to sink. • The proposed HTHP shows a better business case compared to the conventional boilers. This work aims to assess and optimize the performance of cascade high-temperature heat pump (HTHP) integrated with district heating (DH) to produce 1 MW steam at 160 °C for the industrial processes. The heat available in the primary loop of the DH network at 80 °C is considered as the heat source; which is cooled down 70 °C through the HTHP evaporator, before supplying the DH secondary loop. The use of alternative hydrocarbons in the low-temperature loop are examined; and considering the gas compressor limitation, the HTHP performance of using each refrigerant is optimized and compared to each other. The optimization results reveal that pentane- hydrocarbon with the highest critical temperature- is the most promising refrigerant to be paired with steam in the high-temperature loop, reaching the highest COP of 2.66. However, concerning safety and compressor sizing issues, butane is an excellent candidate; with volumetric heating capacity (VHC) of about two times more than that of pentane, in the expense of just about 4 % reduction in the HTHP COP. In addition, water injection theoretically controls the steam compressor discharge temperature successfully, with just 0.9 K superheating at the compressor outlet; and reduces its power consumption and the HTHP COP up to 4.3 % and 1.7 %, respectively. Moreover, techno-economic analysis demonstrates that the HTHP technology shows a better business case compared to the conventional natural gas and electric boilers. [ABSTRACT FROM AUTHOR]

Gas turbines operate under harsh conditions of high temperature and pressure for extended periods, inevitably experiencing performance degradation. Predicting the performance degradation trend of gas turbines and optimizing planned maintenance cycles are crucial for the economic and safety aspects of gas turbine operation. In this study, a novel data-driven approach for predicting gas turbine performance degradation is proposed. Initially, gas turbine operating data are augmented using a mechanism model. Subsequently, a data-driven performance model is constructed based on support vector regression (SVR) and gas turbine operational characteristics, enabling real-time calculation of performance degradation indicators. Building on this, an Autoregressive Neural Network (AR-Net) is employed to construct a model for predicting the trend of performance degradation. The proposed method is applied to predict performance degradation caused by fouling in the compressor of a gas turbine. Comparative analysis with three other performance degradation prediction methods indicates that the proposed approach accurately identifies the performance degradation trend of gas turbines, determining the optimal maintenance timing. This holds significant importance for the condition-based maintenance of gas turbines. [ABSTRACT FROM AUTHOR]

The purpose of this work is to reduce the noise generated by a compressor that conveys methane gas. After certain measurements were conducted a high level of noise was observed in the 2000-3000 Hz range, therefore a solution for noise reduction at the source is addressed and presented in this paper. The research method is based on designing resonators to be applied on the stator of a centrifugal compressor used in a natural gas distribution station. First, the calculations are made on resonators with air as the working fluid and then are validated through real measurements in a Kundt tube. After validation, the working fluid is changed with gas, calculations are made once again, and acoustic simulations are performed. To facilitate acoustic simulations and reduce computational time, a simplified stator geometry was employed. This simplified model encompassed the region starting from the rotor's gas exit, where the resonators were deployed. The purpose of the acoustic simulation was to validate the frequency range influenced by the resonators and to estimate the overall noise reduction. Depending on the operating regime of the compressor, the rotor fundamental can vary within the frequency domain of 2000 - 3000 Hz. This broadband domain requires the usage of several resonators with different resonant frequencies. The proposed solution obtained an average value of attenuation, excluding the peaks of the attenuation, in the frequency domain of 2000 - 3000 Hz, of 9 dBA. If the fundamental frequency coincides with a resonance of the resonator, higher attenuation can occur. Also, fundamental attenuation can lead to attenuation of the harmonics. [ABSTRACT FROM AUTHOR]

It is great significant to explore the changes of compressor performance for hydrogen transportation. We found that a Gray-RBF neural network prediction model improved prediction accuracy. The prediction error of the model is 2.34 % by data verification. It was found that the hydrogen blending ratio was increased from 0 % to 30 %, the pipeline transmission power was reduced by 9.3 %. Simultaneously injecting hydrogen to natural gas causes the performance curve of the compressor to shift downwards. The pressure ratio decreases by 18.9 % and shaft power decreases by 28.6 % when the hydrogen blending ratio increases from 0 % to 30 %. The injection of hydrogen to natural gas causes the surge range of the compressor to increase, so the stable range to narrow. In general, this research may provide reference and guidance for the transportation research of hydrogen blended natural gas and compressor operation about gas industry. [Display omitted] • Creating a combination model improved the accuracy of performance prediction. • Injecting hydrogen into natural gas reduced the power of pipeline gas transmission. • Enlarging initial pressure caused the gas transmission power increase. • Injecting hydrogen into natural gas caused decreases of compressor performance curves. • Injecting hydrogen into natural gas increased the surge range of the compressor. [ABSTRACT FROM AUTHOR]

Ensuring the reliability of process gas compressors is critical for underground gas storage, as piston rod fractures can lead to serious accidents, such as natural gas leaks or explosions. On-time monitoring and early detection play a vital role in preventing catastrophic consequences, minimising costs, and reducing production losses due to unplanned downtime. This study presents a novel accelerated life-testing method designed to replicate the fracture events of reciprocating compressor piston rods. By accelerating the induced crack initiation and propagation to the final fracture, comprehensive analyses of the fracture results are performed to reveal the piston rod fracture mechanism and the resulting secondary damage to the unit. The research further presents an innovative approach for identifying piston rod crack propagation by means of acoustic emission. Through kinetic analysis and time–frequency domain analysis, the study elucidates two mechanisms responsible for triggering crack signals during the compressor operation: the contact impact between the crosshead pin and the bearing due to the piston rod load reversal, and crack propagation occurring before the maximum tensile load is reached. In addition, the study identifies the piston rod crack expansion signal frequency band and achieves a high-sensitivity identification of crack dynamic growth by extracting signal sub-band features associated with crack propagation. Then, a prediction model of the fatigue crack growth rate was established based on the AE energy release rate, which provides a quantitative assessment of dynamic crack propagation during compression. This method aims to provide a maintenance strategy for piston rod fractures, thereby increasing the operational safety of critical dynamic equipment in underground gas storage. [ABSTRACT FROM AUTHOR]

Gasoline produced by hydrotreating light and heavy naphtha and reforming hydrotreated heavy naphtha, hydrogen required for both processes produced by the reforming unit as a byproduct, compression, and recycling of hydrogen required for reforming reactions provided by recycle gas compressor (centrifugal multi-stages compressor), due to the design criteria of this compressor the anti-surge system pass 18000 kg/h, of hydrogen from discharge to suction of compressor with 3" control valve, at the low flow situation during the startup of the unit to avoid the lake of gas flow and avoid overpressure in the discharge of the compressor. Anti-surge system in this compressor contains no inter-stage cooler, the suction temperature of the compressor is designed at 43℃, and the discharge of the compressor is 79℃ when the anti-surge system is involved in the process, the suction temperature of the compressor becomes 70℃, and the discharge becomes 108℃ due to the heat accumulation of recycle gas out of the anti-surge system. In an aim to solve this problem, the outlet of the anti-surge system of the compressor connected with the process heat exchanger, to cool down the hydrogen inlet to suction of the compressor to approximately 46℃ and back to the design limits, the disadvantage of this solution is the absorption of the light end associated with recycle gas posing in the process heat exchanger, which reduces the total molecular weight of recycle gas through the anti-surge system from 13.336 to 10.51 kg/kg mol at start of the run, and from 16.155 to 12.15 kg/kg mol at the end of the run. [ABSTRACT FROM AUTHOR]

The oil–gas separator of the gas storage compressor serves as crucial equipment in a natural gas storage system to improve gas storage purity and efficiency. Its optimization is also essential to improve the separation efficiency and lifespan. Collision and centrifugal separation are two widely used optimized structures for oil–gas separators, and the enhancement in separation efficiency, as well as the decrease in pressure loss of optimized separators, has been thoroughly discussed. However, the velocity uniformity in the filter inlet has not been considered, which affects the filtration performance. Thus, the overall efficiency of the separator is reduced. Accordingly, optimization of an oil–gas separator with the consideration of velocity uniformity in filter inlets is introduced in this study. The effects of critical dimension parameters of optimized equipment on separator performance were analyzed. The results show that bb = 0.4, lb = 3, hb = 1.5, and kb = 0.5 and le = 0.9 and he = 4.11, as well as lc = 0.5 and dc = 0.52, are suitable for the case of placing baffles, adjusting the separator height and inlet position, as well as adding an inner cylinder, respectively. Subsequently, the analytic hierarchy process was employed to compare different optimized cases. It is observed that the overall rating for adding an inner cylinder reaches 88.46, which is the more suitable optimized method for the oil–gas separator. This work is relevant for oil–gas systems to improve their separation efficiency and enhance the gas storage performance. [ABSTRACT FROM AUTHOR]

Digital twin (DT) is a research topic that gained momentum in the Industry 4.0 era. The goal of DT is to create a virtual real-time intelligent system that is a typical twin of the physical system. DT provides analysis, prognosis, planning, and rapid response when needed. Digital shadow (DS) is an artifact concept of DT that provides a real-time replica of the physical system. Information in a DS is passed in one direction only, from the physical system to the virtual one. While in DT, the information goes in both directions. The definition and roles of DS and DT are overlapping. However, DS can be defined as the main component of a DT system. In this paper, DS roles are specified. Based on these roles, A DS framework architecture is proposed, and the communication system between its components. The proposed framework design is built using distributed system concepts such as event-driven architecture, microservices, and containerization. These concepts are well defined and utilized in the software engineering domain. The originality of the proposed framework is the definition of a systematic approach for designing and integrating digital models (DMs) from different vendors and domains. An experiment is designed to prove the framework's ability to shadow a physical system in real-time. Multiple DMs are implemented and deployed on the proposed DS framework. These DMs are used to shadow a natural gas compressor system. Experimental results prove the practicality of our proposed DS framework to operate in real-time. [ABSTRACT FROM AUTHOR]

• Thermodynamic analysis of absorption cooling-assisted CO 2 systems. • Performance enhancement over simple CO 2 system is analysed. • Simple CO 2 system with IHX coupled with DEDHVARS performs better at high T gc. • Enhanced COP and exergy efficiency. Studies have shown appreciable improvements in system performance by subcooling the working fluid in transcritical CO 2 refrigeration systems. The use of a dedicated vapour absorption refrigeration system (VARS) for subcooling the high side working fluid downstream of the heat rejection device is proved to be a viable option. The heat available in the discharged gas downstream of the compressor in the transcritical CO 2 system is used to drive a LiBr-H 2 O VARS. This study examines the performance of an absorption cooling-assisted transcritical CO 2 system. Three different configurations of the absorption system are considered, namely, single effect (SE), series double effect (DE), and series double effect with dual heat input (DEDH). The performance analysis is carried out for gas cooler exit temperatures (T gc) ranging from 30 to 50 °C and evaporation temperatures ranging from -10 to 5 °C. The average COP improvement of the CO 2 system is found to be 29 and 27% using SE and DEDH systems respectively. [ABSTRACT FROM AUTHOR]

The paper presents a method for calculating the thermodynamic parameters of refrigerant vapors during their compression in a scroll compressor. The method takes the properties of a refrigerant as a real gas into account, as well as the process of mixing two vapor portions inside the scroll unit when the full geometric degree of compression is reached. [ABSTRACT FROM AUTHOR]

Due to the mismatch between gas production and consumption in the gas delivery system (GDS), reduced customer demand can easily lead to overpressure and gas release. Companies mainly use high-pressure release (HPR) to lower the GDS pressure, which results in significant energy losses for compression and gas separation. This paper (1) proposes a low-pressure release method (LPR) for users' low-demand scenarios to avoid regulating air separation units, and (2) provides a way for obtaining optimal parameters for LPR when used alone and together with HPR. LPR released low-pressure gas by lowing the compressor inlet guide vane opening (IGA) or the inlet valve opening to reduce the compressor load, outlet pressure, and GDS pressure, and reduce the energy consumption of the compressor. Case studies showed LPR reduced effectively the gas emissions and compressor operating energy. When LPR is used alone, the maximum reduction in gas emissions and compressor operating energy consumption compared with HPR was 6,049 Nm3 and 900 kW·h , accounting for 62.96% and 2.18%, respectively, and the gas emission rate was reduced from 0.11% to 0.04%. When LPR was used together with HPR, 43.88% oxygen emissions and 0.28% total compressor energy consumption were reduced, and the total conditioning time can be effectively reduced from 42 to 10 min. The method increases the ability of the compressor to regulate the GDS. [ABSTRACT FROM AUTHOR]

Compressor stations maintain pressure along natural gas pipelines to sustain gas flow. Unfortunately, they present human health concerns as they release chemical pollutants into the air, sometimes at levels higher than national air quality standards. Further, compressor stations are often placed in rural areas with higher levels of poverty and/or minority populations, contributing to environmental justice concerns. In this paper we investigate what chemical pollutants are emitted by compressor stations, the impacts of emitted pollutants on human health, and local community impacts. Based on the information gained from these examinations, we provide the following policy recommendations with the goal of minimizing harm to those affected by natural gas compressor stations: the Environmental Protection Agency (EPA) and relevant state agencies must increase air quality monitoring and data transparency; the EPA should direct more resources to monitoring programs specifically at compressor stations; the EPA should provide free indoor air quality monitoring to homes near compressor stations; the EPA needs to adjust its National Ambient Air Quality Standards to better protect communities and assess cumulative impacts; and decision‐makers at all levels must pursue meaningful involvement from potentially affected communities. We find there is substantial evidence of negative impacts to strongly support these recommendations. Plain Language Summary: Compressor stations allow natural gas to run smoothly through long pipelines. Compressor stations release several different types of pollutants; we discuss in this paper what each pollutant does to the human body and to communities as a whole. Compressor stations are often near socially vulnerable communities that are poor, non‐white, or elderly, which means they more often bear the burden of the pollution. We examine the shortcomings of current policies and regulations surrounding compressor stations and offer solutions to help protect vulnerable communities. Some of these solutions include better testing of air quality near compressor stations, free indoor air quality testing in homes near compressor stations, and better air quality standards to protect all communities from air pollution. Key Points: The impacts of compressor stations fall most heavily on the local communities around the stations, which are often socially vulnerableThe current National Ambient Air Quality Standards are not sufficient to fully protect human health and vulnerable communitiesThere is a severe need for more thorough air quality monitoring to understand the full impact of chemical emissions on community health [ABSTRACT FROM AUTHOR]

Bayesian networks have been widely applied to domains such as medical diagnosis, fault analysis, and preventative maintenance. In some applications, because of insufficient data and the complexity of the system, fuzzy parameters and additional constraints derived from expert knowledge can be used to enhance the Bayesian reasoning process. However, very few methods are capable of handling the belief propagation in constrained fuzzy Bayesian networks (CFBNs). This paper therefore develops an improved approach which addresses the inference problem through a max-min programming model. The proposed approach yields more reasonable inference results and with less computational effort. By integrating the probabilistic inference drawn from diverse sources of information with decision analysis considering a decision-maker's risk preference, a CFBN-based decision framework is presented for seeking optimal maintenance decisions in a risk-based environment. The effectiveness of the proposed framework is validated based on an application to a gas compressor maintenance decision problem. [ABSTRACT FROM AUTHOR]

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This study proposes the application of a precooler to the cascade mixed refrigerant Joule–Thomson (CMR J–T) cycle, herein referred to as the precooled CMR J–T (PCMR J–T) system. The purpose of the precooler is to utilize the temperature gradient characteristics within the two-phase region exhibited by the non-azeotropic mixed refrigerant. The precooler reduces the temperature of the high-temperature gas exiting the compressor by using cooling water from the condenser, thereby decreasing the capacity requirements of the high-temperature cycle (HTC). The working fluid comprises a nonflammable mixed refrigerant (R218, R23, R14, and Ar), and simulations were conducted by varying the HTC evaporation temperature and cooling water temperature for energy and exergy analysis. Under the analysis conditions, the capacity of each component in the HTC can be reduced by over 45%, leading to a maximum increase of 21.6% in the system's coefficient of performance. Furthermore, the exergy destruction in the PCMR J–T system decreases along with the reduction in component capacity, with the most significant reduction occurring at the HTC expansion valve. The exergy efficiency of the system increases by up to 47.4%. [ABSTRACT FROM AUTHOR]

The growing use of gas-fired power generators and electricity-driven gas compressors and storage has increased the interdependence between electric power infrastructure and natural gas infrastructure. However, the increasing interdependence may spread the failures from one system to the other, causing subsequent failures in an integrated power and gas system (IPGS). This paper investigates the structural vulnerability of a realistic IPGS based on complex network theory. Different from the existing works with a focus on the static vulnerability analysis for an IPGS, this paper considers both static and dynamic vulnerability analysis. The former focuses on vulnerability analysis under random and selective failures without flow redistribution, while the latter concentrates on vulnerability analysis under cascading failures caused by flow redistribution. Also, different from the existing works with a focus on the IPGS as a whole, we not only analyze the vulnerability of the IPGS but also analyze the vulnerability of the power subsystem (PS) and gas subsystem (GS), in order to understand how the vulnerability of the IPGS is affected by its PS and GS. The analysis results show that (1) if the PS and GS are more susceptible to cascading failures than selective and random failures, the IPGS as a whole is also more vulnerable to cascading failures. (2) There are different dominant factors affecting the IPGS vulnerability under cascading failures and selective failures. Under cascading failures, the GS has a more significant impact on the IPGS vulnerability; under selective failures, the PS has a more important impact on the IPGS vulnerability. (3) The IPGS is more vulnerable to failures on the critical nodes, which are identified from the IPGS as a whole rather than from the individual PS or GS. The results provide insights into the design and planning of IPGSs to improve their overall reliability. [ABSTRACT FROM AUTHOR]

The paper presents a novel methodological framework for monitoring the energy performance of dualshaft gas turbines-driven centrifugal compressors in gas processing plants. The framework specifically addresses the complexities and challenges associated with gas compressor operation. To achieve this, a comprehensive performance analysis was conducted using real industrial data obtained from five gas processing plants located in different regions and collected at various time intervals. The Cumulative Sum of Difference Analysis technique was utilized to identify deviations in energy consumption levels, effectively highlighting significant deviations from the expected data. Furthermore, a sensitivity analysis was performed to identify and analyze the key factors that impact energy consumption, including process gas temperature, pressure, efficiencies, gas composition, fuel gas quality, load factor, aging, and ambient conditions. A regression analysis was carried out to identify significant predictor variables that accurately represent the compressor's performance, and a steady-state simulation model was developed for a commonly employed compressor package. The resulting regression equation was validated through comparisons with both simulated and actual data. The results demonstrate that the regression equation provides a robust representation of the actual data, closely matching it. The cumulative sum of difference between the actual and regression equation was found to be 1.81 MMSCFD based on a dataset comprising 60 measurements, indicating a relatively small deviation. Moreover, the CUSUM between the actual and the simulation results was 9.06 MMSCFD.. [ABSTRACT FROM AUTHOR]

The intercooler is a crucial component of the rich gas compressor. Due to the shortcomings of the conventional segmental baffle intercooler, an optimization design of the novel industrial-grade twisted-elliptic-tube intercooler is proposed. This study aims to compare the heat-transfer performance of these two types of intercoolers in a delayed coking unit at Sinopec. During the plant revamp operation, the original segmental baffle intercooler was replaced by the novel twisted-elliptic-tube intercooler. Experimental determination and comparison analysis of the industrial locale operation of the two types of intercoolers before and after the revamps were conducted. The evaluation results show that the novel twisted-elliptic-tube intercooler has a higher cooling capacity, with a 13.2% increase, compared to the conventional intercooler. Under identical operating conditions, the overall heat-transfer coefficients increase by 87.8%. Moreover, the heat-transfer area and gas pressure drop decrease by 37.4% and 36.9%, respectively. The tube bundles' vibration and loud noise problems of the old intercooler are eliminated. The average exit temperature of the enriched gas that requires cooling is 38.4 °C, which is 7.3 °C lower than that of the conventional intercooler. These outcomes indicate that utilizing this innovative twisted-elliptic-tube heat exchanger can provide substantial advantages in terms of high heat-transfer efficiency and exceptional anti-vibration performance. [ABSTRACT FROM AUTHOR]