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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]

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]

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 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]

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]

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]

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]

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]

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]

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]

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]

This research gives an experimental investigation of the scroll compressor, with an emphasis on the effect of leakage on performance enhancement. The effect of gas leakage losses on compressor performance is studied both experimentally and conceptually. In the present study, we have modified the scroll compressor to bypass the refrigerant through an orifice called leakage and experimentally investigate the effect of valve opening area and angle to observe the effect of leak gas on compressor performance, compressor capacity loss, discharge line temperature rise, and discharge gas temperature. Experimental results indicated that the maximum percentage rise in suction superheat is observed to be 7.13% at a maximum effective valve opening area of 0.33 m2, whereas the rise in discharge line temperature lies in the range of 0.8% to 2.75% over the entire range of effective leak area. In addition, based on experimentation the 8.9 % maximum compressor capacity loss is observed. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced polytetrafluoroethylene (CF/PTFE) composites are frequently used in tribological dry gas applications, such as in dynamic seals in reciprocating hydrogen gas compressors and Stirling engines, due to their superior friction and wear. Due to the increasing concerns regarding fluoropolymers as possible pollutants of harmful per- and poly-fluoroalkyl substances (PFAS) emissions, replacements for PTFE should be investigated. The literature indicates that CF-reinforced polyetheretherketone (CF/PEEK) may have similar favorable tribological properties to CF/PTFE. However, the tribological behavior of CF/PEEK in dry gas is poorly understood, and no direct comparison has been made between the two materials. The aim of this study was to compare the effect of oxygen and moisture on the friction and wear of CF/PTFE and CF/PEEK. Tribological tests were carried out with a tri-pin-on-disc tribometer in a nitrogen environment with individually controlled contents of oxygen and moisture. The results showed that the effect of oxygen and moisture are distinctly different for CF/PTFE and CF/PEEK. While CF/PTFE performs best in oxygen-deficient environments, CF/PEEK performs best in moisture-enriched environments. Complementary tests with a PTFE composite filled with both CF and PEEK suggested that the environmental sensitivity can be significantly reduced by combining the two polymers. [ABSTRACT FROM AUTHOR]

Diaphragm plates, a key part of high-pressure hydrogen gas compressors, are easily cracked or broken due to repeated shape deformations caused by pressure, resulting in increasing difficulties in maintenance. This study aimed to improve the durability of diaphragm plates. This investigation focuses on the potential for friction and wear reduction through the application of surface polishing and Teflon coating on two diaphragm plate materials, namely stainless steel 301 and Inconel 718. To achieve this, various metal substrates with diverse surface morphologies were prepared and subjected to comprehensive assessments of their surface, mechanical, and tribological properties. Research findings revealed that the surface hardness and tensile strength of stainless steel 301 surpassed those of Inconel 718. Through friction and wear analysis, it was observed that Teflon-coated diaphragm plate material with a microstructure demonstrated superior friction performance. Furthermore, finite element analysis was employed to investigate the stress behavior of stainless steel 301 under different applied loads and conditions, offering valuable insights into the diaphragm's performance. From the results of this study, the excellence of the Teflon coating applied to the surface of stainless steel 301—the material of the hydrogen compressor diaphragm plate—was confirmed. [ABSTRACT FROM AUTHOR]

Methane emissions from natural gas systems are increasingly scrutinized and accurate reporting requires site- and source-level measurement-based quantification. We evaluate the performance of ten available, state-of-the-art CH4 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-hour releases at single or multiple simultaneous exhaust points. The controlled releases covered a range of methane flow rates from 0.01 kg h-1 to 50 kg h-1. Measurement platforms included aircraft, drones, trucks, van, and ground-based stations, as well as 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 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 the emission quantification performance against key parameters such as wind speed, deployment constraints and measurement duration. At the low windspeeds encountered (below 2 m s-1), the experiments did not reveal a significant dependence on wind speed. The ability to quantify individual sources was degraded during multiple-source releases. Compliance with the Oil and Gas Methane Partnership (OGMP2.0) 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 based on standard deviation in a series of independent realizations or fixed value from expert judgement or theoretical considerations. For most systems, site-level overall relative errors estimated in this study are higher than self-reported uncertainties. [ABSTRACT FROM AUTHOR]

There are many kinds of assembly structures in heavy-duty gas turbine compressor stator blades which have significant influence on the complex damping vibration characteristics. At present, compressor design is becoming more and more compact, so it is very meaningful to accurately obtain stator blade vibration characteristics of structures with contact damping. Firstly, a fretting slip friction dynamic model was introduced, and then a vibration analysis model of the compressor stator blade with outer ring structure was established based on the slip friction theory. Then, the vibration response of the compressor stator blade was obtained according to various working conditions, and the main factors affecting the vibration characteristics of the stator blade were revealed. Finally, the vibration response of the blade under a particular exciting force condition was simulated. The results show that the damping vibration characteristics of the compressor stator blades were affected by the excitation force and the normal load of the contact surface. The vibration response curve of the stator blade and the equivalent stiffness coefficient of the contact surface were analyzed, and the friction motion of the contact surface changed with the change of the working condition. The model can simulate the nonlinear vibration characteristics of stator blades. This method provides a reference for the vibration safety analysis of compressor stator blades. [ABSTRACT FROM AUTHOR]

Replacing the last-stage stator and the outlet guide vane of the low-pressure compressor of the marine gas turbine with a large turning blade can reduce the number of compressor blades and reduce the size and weight of marine gas turbines. At present, there are few studies on similar profiles, and it is necessary to verify the feasibility of this type of compressor profile with a large turning angle. The performance of this profile is investigated by combining experimental measurement with numerical simulation calculation. The analysis of the experimental and numerical results reveals that this profile has a large flow turning angle, a wide operating range, and low overall total pressure losses. The loss of the profile only suddenly increases at some large positive angles of attack due to the large separation of the suction surface. The results show that this profile can compress air and increase the turning ability at a low loss, and can play the role of both the original last-stage stator and the outlet guide vane. This research provides a reference for the design and analysis of marine gas turbines and guidance for the application of the blade to gas turbines in other fields. [ABSTRACT FROM AUTHOR]

Machine learning algorithms and the increasing availability of data have radically changed the way how decisions are made in today's Industry. A wide range of algorithms are being used to monitor industrial processes and predict process variables that are difficult to be measured. Maintenance operations are mandatory to tackle in all industrial equipment. It is well known that a huge amount of money is invested in operational and maintenance actions in industrial gas turbines (IGTs). In this paper, two variations of autoencoders were used to analyse the performance of an IGT after major maintenance. The data used to analyse IGT conditions were ambient factors, and measurements were performed using several sensors located along the compressor. The condition assessment of the industrial gas turbine compressor revealed significant changes in its operation point after major maintenance; thus, this indicates the need to update the internal operating models to suit the new operational mode as well as the effectiveness of autoencoder-based models in feature extraction. Even though the processing performance was not compromised, the results showed how this autoencoder approach can help to define an indicator of the compressor behaviour in long-term performance. [ABSTRACT FROM AUTHOR]

To investigate the influence of blade aspect ratio and solidity on the performance of heavy-duty gas turbine transonic compressors, a multi-objective optimization design platform was built by adopting the blade parameterization method based on the superposition of thickness distribution on the suction surface, the Kriging surrogate model, and the NSGA-II optimization method. The spanwise distribution of solidity and number of blades were the optimization variables. The multi-objective optimization was carried out with isentropic efficiency and stall margin as the objective parameters for the inlet stage transonic rotor of an F-class heavy-duty gas turbine compressor. The results show that the isentropic efficiency and stall margin at design condition with a constant mass flow rate can be improved by 0.96% and 18.7%, respectively, and the total pressure ratio can also increase. The analysis shows that, for regions where the shock wave–boundary layer interaction is obvious, increasing the solidity can reduce the shock wave loss, the shock wave–boundary layer interaction loss, and the end wall loss, and reducing the aspect ratio can reduce the blade boundary layer loss. The spanwise distributions of solidity and aspect ratio determine the stall margin by affecting the radial matching of the load of each blade section. Tip solidity near the tip region needs to be determined according to the pressure field established by the bulk of the flow. [ABSTRACT FROM AUTHOR]

The Fuling shale gas field is facing a rapid gas production decline due to heavy liquid loading issues. Given the condition that most wells are located at remote areas in the mountains, the traditional gas lift methods that require either fixed compressor or skid-mounted gas lift trucks do not seem feasible and occur high operation costs. A new type of gas lift valve that can be opened or closed at a low valve dome pressure indicates the high sensitivity to low production pressure. Thus, the piping line pressure can be utilized to activate the valve due to its new advantages. In addition, the specially designed structure of the gas lift valve can be activated via pressure increases in the tubing to create a channel between the tubing and annulus. The valve that previously functioned as a dummy valve was then switched to a gas lift valve. Field application results show that all wells were successfully restarted by only utilizing the low piping pressure, and loaded liquid was lifted with gas production at an incremental rate that reached up to 27.4 × 10 kscm/d per well. Fewer slickline operations were conducted to replace the dummy valve. The result of the application shows that the new type of gas lift system has a wide range of application prospect for low pressure wells, especially for shale gas wells. [ABSTRACT FROM AUTHOR]

The increasing importance of renewable energy capacity in the power generation scenario, together with the fluctuating consumer energy demand, forces conventional fossil fuel power generation systems to promptly respond to relevant and rapid load variations and to operate under off-design conditions during a major fraction of their lives. In order to improve existing power plants' flexibility in facing energy surplus or deficit, retrofittable solutions for gas turbine compressors are proposed. In this paper, two different operation strategies, variable inlet guide vanes (IGVs) and blow-off extraction (BO), are considered for enabling partial load and minimum environmental load operation, and thus to identify implementation opportunities in existing thermal power plants. A typical 15-stage F-class gas turbine compressor is chosen as a test case and some energy demand scenarios are selected to validate the adopted solutions. The results of an extensive 3D, steady, CFD analysis are compared with the measurements coming from an experimental campaign carried out in the framework of the European Turbo-Reflex project. It will be shown how the combined strategies can reduce gas turbine mass flow rate and power plant output, without significantly penalizing efficiency, and how such off-design performance figures can be reliably predicted by employing state-of-the-art CFD models. [ABSTRACT FROM AUTHOR]

The compressors used in today's natural gas production industry have an essential role in maintaining the production line operational. Each of the compressors' components has routine maintenance tasks to avoid sudden failures. Hence, the significant advantages and benefits of performing preventative maintenance tasks in time are decreasing equipment downtime, saving additional costs, and improving the safety and reliability of the whole system. In this paper, anomaly classification and detection methods based on a neural network hybrid model named Long Short-Term Memory (LSTM)-Autoencoder (AE) is proposed to detect anomalies in sequence pattern of audio data, collected by multiple sound sensors deployed at different components of each compressor system for predictive maintenance. In research methodology, this paper has conducted experiments that employed different RNN architectures such as GRU, LSTM, Stacked LSTM, and Stacked GRU with various functions to create a baseline for model evaluation. Each architecture used audio signals dataset received from the compressor system for experiments to consider each neural network model's performance. According to performance results, an optimal model for anomaly detection with the best performance scores has been proposed in this research. Experiments combined one-dimensional raw audio signal features using SC and Mel spectrogram features were fed to deep learning models to evaluate performance. Hence, such hybrid methods can effectively detect normal and anomaly audio signals collected from a compressor system, increasing the compressor system's reliability and the sustainability of the gas production line. The combination of multiple-resource features in the proposed hybrid model showed a 100% score in all four-evaluation metrics such as accuracy, precision, recall, and F1 in LSTM-based autoencoder in both test and train results. [ABSTRACT FROM AUTHOR]

In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery of natural gas. So, it is economically important to optimize the operation of the booster compressor station. The booster compressor station optimization problem is a typical mixed integer nonlinear programming (MINLP) problem, and solving it accurately and stably is a challenge. In this paper, we propose an improved salp swarm algorithm based on good point set, adaptive population division and adaptive inertia weight (GASSA) to solve this problem. In GASSA, three improvement strategies are utilized to enhance the global search capability of the algorithm and help the algorithm jump out of the local optimum. We also propose a constraint handling approach. By using semi-continuous variables, we directly describe the on or off state of the compressor instead of using auxiliary binary variables to reduce the number of variables and the difficulty of solving. The effectiveness of GASSA is firstly verified using eight standard benchmark functions, and the results show that GASSA has better performance than other selected algorithms. Then, GASSA is applied to optimize the booster compressor station load distribution model and compared with some well-known meta-heuristic algorithms. The results show that GASSA outperforms other algorithms in terms of accuracy and reliability. [ABSTRACT FROM AUTHOR]

Gas compressors are major energy consumers in many modern industries, including energy and chemical production. However, they face challenges of high wasted energy in the form of low-grade compression heat, and the increased power input and blade corrosion due to high-humidity suction gas. This study proposes a novel compression heat self-utilisation system that integrates liquid desiccant-based cascade dehumidification with absorption refrigeration to achieve efficient recovery of compression heat and deep dehumidification of suction gas. For the core module, a test bench for the cascade dehumidification unit is constructed to validate its deep dehumidification performance under high gas-desiccant flow ratios. Based on the validated numerical model, the feasibility of applying the proposed system to a three-stage compression process in air separation systems is evaluated in terms of water vapour condensation, energy savings, and economic and environmental benefits. Results show that deep dehumidification is achieved experimentally, with the humidity ratio reduced from 20.00 g/kg to below 6.00 g/kg, thus preventing water vapour condensation even when the gas-desiccant flow ratio reaches 9.65. when applied to a typical air separation plant, the compression heat self-utilisation system achieves an energy saving rate of compression work of approximately 4.10%. The payback period is as short as 3.21 years, with potential carbon emission reductions of up to 4610 ton/year in tropical regions. The work not only offers data support for liquid desiccant-based deep dehumidification systems but also lays a foundation for its energy-saving application in large-scale industrial compressor trains. • A novel compression heat self-utilisation system is proposed and evaluated. • A prototype of a cascade deep dehumidification system is built and tested. • The self-utilisation system reduces compressor work by over 4.10%. • A low humidity of 6.00 g/kg is achieved with gas-liquid flow ratios over 9.65. • The system is highly applicable in high-temperature and high-humidity areas. [ABSTRACT FROM AUTHOR]

• Proposed a novel maintenance cycle predictive framework for large energy equipment based data-oriented. • The multi-level adversarial domain adaptation model generated a feature subspace, ensuring the transfer foundation of degradation knowledge. • The federated learning strategy improved predictive performance with limited training samples while ensuring data security. Failures in natural gas compressor units can lead to significant production incidents that impact energy security, making intelligent preventative maintenance of this equipment critically important. Given the limited and sensitive data from critical energy equipment like natural gas compressor units, this paper conducts preventative maintenance research based on domain adaptation and federated learning (DFPM), and proposes a novel maintenance cycle prediction framework. The feasibility of the proposed method was validated through historical operational data from field natural gas compressor units, providing a data-oriented reference for maintenance decision-making. Verification results demonstrate that the proposed multi-level adversarial domain adaptation method possesses superior feature representation capability, enhancing the preservation of the original degradation trend for time series data compared to traditional DA models. The novel federated adversarial strategy presented in this paper can effectively transfer source domain knowledge to the target domain, further enhancing the cross-unit predictive performance of the target domain model with limited samples. Additionally, this strategy with the chaotic multi-mode predictive model further improves the limitations of low parallelism and efficiency in traditional RNN-based prediction models while ensuring data security. This research provides a new perspective for the intelligent operation and maintenance of large energy equipment, which is of significance in practical engineering. [ABSTRACT FROM AUTHOR]

Various gas pipeline networks used for the transit of energy sources are some of the most important infrastructures. However, carrying gas from one point to another is not the only concern when planning the construction of a new network or expanding an already existing one. The reliability and environmental impact of the system are crucial when evaluating the network and risks posed by potential gas leaks, fires, explosions, etc. Even though everyone admits that reliability is a key aspect of any system, its constraints will still be most likely neglected in the assessment of the pipeline project. How much energy is wasted by pushing an additional amount of gas through the pipeline network, which will eventually gush out of the pipeline because of one crack or another? Moreover, if this additional power or fuel consumption and related environmental impact are significant, how could it be reduced? In this paper, an approach is introduced for the simulation and quantification of how much more power would be required if the pipelines are regarded as unreliable (i.e., by leaking, rupturing, or even exploding). By employing stochastic simulations and time-dependent topology (topology determined by the value of a variable representing time) of the pipeline network as a case study for the selected representative gas transmission network, the amount of additional power consumption in gas compressor stations due to uncertain cracking and the leaking rate was evaluated. Although the analysis of power consumption was performed for a hypothetical network, the estimates of the cracking rates, detection effectiveness, and leaking rates used were as close to the real cases as possible. [ABSTRACT FROM AUTHOR]

In this study, we conducted experiments and numerical analysis on a 270 kW industrial-scale centrifugal compressor used in the fuel supply system of an LNG carrier in order to improve the lumped-parameter surge model by considering the viscosity in the pipeline and to confirm whether the improved model would be applicable. The steady and unsteady compressor performance curves were constructed using measurements and predictions, respectively. The flow through the pipeline was assumed to be both steady and unsteady, and each governing equation under the assumptions was derived in accordance with the lumped-parameter model. In the steady flow case, the surge behavior of the modified model was in a good agreement with the lumped-parameter model at surge parameter B = 4.8716. In the unsteady flow case, however, the modified model showed a deviation from the lumped-parameter model, and the simulation from the modified model described the surge behavior 5% more accurately than the lumped-parameter model. Through experiments and numerical analysis, this study showed that the present models are useful and applicable for describing the surge behavior of an industrial-scale single-stage centrifugal compressor. [ABSTRACT FROM AUTHOR]

Combined cycle power plant (CCPP) usually plays an important role in balancing byproduct gas generation and consumption in integrated iron and steel plant. The low heat value fuel gases, such as blast furnace gas (BFG) or mixed gas with Coke oven gas (COG) and BFG, are preferred to be used in high-efficient CCPP for power generation. In practice, the general heat value of mixed gas can be set in the range of 3500–4400 kJ/Nm3. This paper presents a methodology to simulate operating parameters of CCPP with BFG. A generic model of gas turbine with open loop stage cooling employing air is used to simulate the performance of gas turbines cycle under different compressor pressure ratios and turbine inlet temperatures (TIT). The isentropic efficiencies for gas compressor and gas turbine are supposed to be constants and set corresponding to published industrial experience. The steam cycle is composed of classical double-pressure heat recovery steam generator (HRSG) and steam turbines according to gas turbine outlet temperature. Specific work, gas turbine cycle efficiency, cogeneration thermal efficiency and coolant air flow requirements are evaluated to find the optimal compressor pressure ratio and TIT. The research results are useful to select the optimum operating parameters of CCPP with BFG. Performance features were estimated with the help of compression ratios 12.5–20 and combustor exit temperature 1150–1350 ∘ C. [ABSTRACT FROM AUTHOR]

In this study, a data-driven methodology for the reliability analysis of natural gas compressor units is developed, and both the historical failure data and performance data are employed. In this methodology, firstly, the reliability functions of the catastrophic failure and degradation failure are built. For catastrophic failure, the historical failure data are collected, and the rank regression model is utilized to obtain the reliability function of the catastrophic failure. For degradation failure, a support-vector machine is employed to predict the unit's performance parameters, and the reliability function of the degradation failure is determined by comparing the performance parameters with the failure threshold. Finally, the reliability of the compressor unit is assessed and predicted by integrating the reliability functions of the catastrophic failure and the degradation failure, and both their correlation and competitiveness are considered. Furthermore, the developed methodology is applied to an actual compressor unit to confirm its feasibility, and the reliability of the compressor unit is predicted. The assessment results indicate the significant impact of the operating conditions on the precise forecasting of the performance parameters. Moreover, the effects of the value of the failure threshold and the correlation of the two failure modes on the reliability are investigated. [ABSTRACT FROM AUTHOR]

Turbine meters are used in compressed natural gas (CNG) stations in abundance to measure the volumetric flow rate of the inlet gas. These types of meters are very sensitive to oscillating and pulsating flows. When the station's reciprocating compressor starts to work, due to the piston and valve performance, pulsating flow will create in the suction line and downstream of turbine meter. This pulsation makes false pulses in the meter and finally makes difference between the measured gas flow from the metering of the gas company and the amount of gas that has been sold at the station. In this study, numerical simulation of dampeners has been investigated after turbine meter and before entering gas to compressor. The goal is eliminating or reducing the effects of operating compressor in CNG station on turbine meter and reducing measurement errors. Numerical simulation of dampener was investigated by Ansys-Fluent CFD software for a CNG station with the gas inlet pressure 250 psi, inlet and outlet pipe diameter of 2 inches. In this study, several parameters such as (1) height-to-diameter ratio in the cylinder, (2) distance between dampener and compressor, and (3) volume-to-minimum volume ratio according to API 618, have been checked. The numerical results show that by increasing height-to-diameter ratio up to 3, the pulsating amplitude on Plane 1 will be reduced, and this is the best ratio according to the present results. Also, by increasing the outlet pipe length, the pressure pulsation amplitude decreases from 3.4% of pressure line in 2 m length to 0.7% in 5 m length. Moreover, the results showed 2.4% increase and 1.9% decrease in the maximum and minimum pressure for CV = 1 and CV = 16.7, respectively. Comparing fluent numerical method with previous studies shows less than 2% difference that demonstrates the validity and reliability of present investigation. [ABSTRACT FROM AUTHOR]

The increasing introduction of renewable energy capacity has changed the perspective on the operation of conventional power plants, introducing the necessity of reaching extreme off-design conditions. There is a strong interest in the development and optimization of technologies that can be retrofitted to an existing power plant to enhance flexibility as well as increase performance and lower emissions. Under the framework of the European project TURBO-REFLEX, a typical F-class gas turbine compressor designed and manufactured by Ansaldo Energia has been studied. Numerical analyses were performed using the TRAF code, which is a state-of-the-art 3D CFD RANS/URANS flow solver. In order to assess the feasibility of lower minimum environmental load operation, by utilizing a reduction in the compressor outlet mass-flow rate, with a safe stability margin, two different solutions have been analyzed: blow-off extractions and extra-closure of Variable Inlet Guide Vanes. The numerical steady-state results are compared and discussed in relation to an experimental campaign, which was performed by Ansaldo Energia. The purpose is to identify the feasibility of the technologies and implementation opportunity in the existing thermal power plant fleet. [ABSTRACT FROM AUTHOR]

In this article, a high-speed permanent magnet synchronous machine (PMSM), which is rated at 15 kW and 120 krpm for a gas compressor, is designed and optimized. According to the design specifications, two design schemes of different rotor topologies are presented and compared by the finite element method (FEM) to determine the preliminary scheme of the original machine. The performance of the original machine is obtained by FEM. Meanwhile, the losses of the original machine are analyzed and calculated for optimization. Especially, the conductor diameter of the winding is selected to reduce the copper loss of the machine. Finally, in order to reduce wind friction loss and increase power density, the dimensions of the stator core and the thickness of the permanent magnet (PM) are optimized. Compared with the original model, the wind friction loss is reduced by 17.2%, and the power density is increased by 6.64% in the optimized machine. [ABSTRACT FROM AUTHOR]

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The determination of the possibility for the reduction of the friction coefficient of ceramic parts from silicon carbide by pulse-periodic treatment with an ultraviolet nanosecond laser was carried out in the framework of this research. The gas-dynamic seal of the compressor rotor of the gas-turbine engine after hot isostatic pressing and mechanical treatment was exposed to surface microstructuring in a pulse-periodic mode. For experimental investigations, a laser with a maximum energy of the pulse of 50 µJ, a wavelength of 355 nm, and a pulse duration below 10 ns was used. It was determined that the surface quality was improved, and the surface roughness was reduced as a consequence of the realized laser polishing modes in the beam exposure area. The average value of the friction coefficient of the ceramic material surface decreased by 15% as result of pulse-periodic laser processing. [ABSTRACT FROM AUTHOR]

Design of radial passive magnetic bearings with active dampers (radial PMB-AD) and their application in a down-hole natural gas compressor (DHGC) are discussed. These compact and reliable bearings allowed noncontact suspension of a high-speed DHGC rotor spinning at 50 kr/min in a highly adverse environment more than 3 km (10 000 ft) below the ground with temperatures reaching 100 °C. The design was further complicated by the space limitations imposed by a well casing. The paper presents the design of PMB-AD modules, as well as their integration and testing as a part of a DHGC. [ABSTRACT FROM AUTHOR]

An investigation on many-body effects of solid argon at high pressure was conducted based on a many-body expansion of interaction energy. The three- and four-body terms in the expansion were calculated using the coupled-cluster method with single, double, and noniterative triple theory and incremental method, in which the configurations of argon trimers and tetramers were chosen as the same as those in the actual lattice. The four-body interactions in compressed solid argon were estimated for the first time, and the three-body interaction ab initio calculations were extended to a small distance. It shows that the four-body contribution is repulsive at high densities and effectively cancels the three-body lattice energy. The dimer potential plus three-body interaction can well reproduce the measurements of equation of state at pressure approximately lower than ~60 GPa, when including the four-body effects extends the agreement up to the maximum experimental pressure of 114 GPa. [ABSTRACT FROM AUTHOR]