Operating Conditions Research Articles

Study of the Incidence of CO and CO2 Gas Emission Levels and Temperature, of the Automotive Air Conditioning System Inside an Interprovincial Bus at Different Environmental and Operating Conditions

Study of the Incidence of CO and CO2 Gas Emission Levels and Temperature, of the Automotive Air Conditioning System Inside an Interprovincial Bus at Different Environmental and Operating Conditions

Performance analysis of a new multifunctional aircraft environmental control system under variable operating conditions

Performance analysis of a new multifunctional aircraft environmental control system under variable operating conditions

Synthesis of sodium alginate / polyvinyl alcohol / polyethylene glycol semi-interpenetrating hydrogel as a draw agent for forward osmosis desalination

Typically, hydrogels are described as three-dimensional networks of hydrophilic polymers that are able to capture a certain mass of water within their structure. Recently, hydrogels have been widely used as drawing agents in forward osmosis (FO) desalination processes. The major aim of this study is to prepare a novel semi-interpenetrating hydrogel by crosslinking sodium alginate (SA) and polyvinyl alcohol (PVA) by using the epichlorohydrin (ECH) crosslinker and polyethylene glycol (PEG) interpenetrated within the hydrogel’s network as a linear polymer. Based on the optimum composition of SA/PVA composite hydrogel obtained from our earlier research, the effect of various percentages of PEG on the response of the hydrogel was investigated. The optimal composition of SA/PVA/PEG hydrogel was characterized by scanning electron microscopy (SEM), compression strength testing, Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). The morphological and mechanical properties of the SA/PVA/PEG semi-interpenetrating hydrogel were also compared to those of the SA/PVA composite hydrogel. Moreover, the performance of the optimal SA/PVA/PEG hydrogel in a FO batch unit as a drawing agent was investigated based on the optimal operation conditions from our previous experiments. The results showed that the optimal PEG/polymer blend mass ratio was 0.25, which increased the swelling ratio (SR) (%) of the hydrogel from 645.42 (of the neat SA/PVA hydrogel) to 2683. The SA/PVA/PEG semi-interpenetrating hydrogel was superior to the SA/PVA copolymer hydrogel in pore structure and mechanical properties. Additionally, in terms of FO desalination, the achieved water flux by SA/PVA/PEG hydrogel is higher than that accomplished by SA/PVA hydrogel.

Analysis of Non-Road Mobile Machinery Homologation Standards in Relation to Actual Exhaust Emissions

This article presents issues related to the current approval procedures in the group of off-road vehicles. Our research aimed to demonstrate significant differences between actual railway vehicle operation and stationary homologation tests regarding exhaust emissions. The research cycle consisted of analyzing emissions of toxic compounds from exhaust systems under real operating conditions, supplemented by a temporal share analysis based on the denormalized NRTC test upon which the tested object was homologated. Based on the conducted analyses, a significant difference was found between the actual operation of the tested railway vehicle and the stationary homologation test. By interpreting emission intensities within the parameter ranges of the propulsion unit’s operation, key areas with a significant impact on the vehicle’s overall emissions were identified. Based on the obtained results, a critical opinion is expressed regarding current homologation standards for the off-road vehicle group and the necessity for further empirical research in the area of actual operation of the tested vehicle group.

Thermodynamic evaluation of decarbonized power production based on solar energy integration

This study aims to create an environmentally friendly system by utilizing solar and biomass energies as renewable sources, employing high temperature and pressure ranges for analysis. A new energy system is introduced, using biomass to produce hydrogen and other valuable commodities. The study evaluates power and hydrogen production technologies from a thermodynamic perspective, including conventional biomass gasification, calcium and iron thermochemical looping cycles, and gasification with supercritical water, incorporating carbon capture techniques. It assesses and compares the performance of locally available biomass material, such as cotton stalk, during gasification. Results show that employing the supercritical water gasification cycle yields the highest hydrogen production (8330 kg/h) and carbon capture rate (92.91 %), with potential for significant reduction in CO2 emissions. Supercritical water gasification also demonstrates electricity, heating, and CO2 production rates of 51.48 MW, 23.3 MW, and 16.6 MW, respectively. Integrating supercritical water gasification with solar energy enhances syngas productivity and system efficiency. Additionally, the highest performance is demonstrated in the SCWG case, which exhibits the lowest irreversibility at 320.32 MW. In conclusion, the system with supercritical water gasification emerges as the most efficient biomass conversion method, with higher energy and exergy efficiencies of 67.59 % and 49.74 %, respectively, under specific operating conditions. The developed model facilitates integration of solar energy into biomass gasification, enabling prediction and comparison of performance in terms of energy and exergy efficiencies.

Investigation of Operational Parameters for Nanoelectrokinetic Purification and Preconcentration.

This work reports on experimental investigations into the operational parameters of nanoelectrokinetic purification and preconcentration, especially utilizing on ion concentration polarization (ICP). ICP as a nanoscale electrokinetic phenomenon has demonstrated promising advances in various fields utilizing an ion depletion zone (IDZ) with a steep electric field gradient inside the ICP layer. However, the inevitable electrokinetic instability occurring within the IDZ has posed a challenge in operating the ICP system stably. To address the need for a stable and efficient ICP operation in various devices and applications, we propose an operational strategy along with conducted research to determine optimal operating ranges. In order to investigate the operational parameters, a unit voltage (VTH) is introduced as the threshold for initiating ICP. We examined the applicability of VTH across various operating ranges to ensure its effectiveness and versatility. In ICP purification, we categorize three modes (steady, burst, and unsteady) based on IDZ expansion and stability under varying VTH and flow rate conditions, presenting optimal operational conditions that minimize the voltage margin. In ICP preconcentration, a systematic investigation is conducted to observe the influence of background electrolyte concentration and voltage conditions on preconcentration efficiency, offering insights into the correlation between preconcentration factor, electrical conditions, and preconcentration time. Therefore, this research would contribute to the practical understanding of nanoelectrokinetics, providing insight into experimental designs. These findings are expected to offer valuable guidance to researchers aiming to utilize ICP's potential across a spectrum of applications, from purification to preconcentration, in the realm of micro/nanofluidic systems.

Contribution to the Fracture Mechanics Characterization of Repair Welding of Thick-Walled Ductile Cast Iron Components

AbstractFor the spheroidal graphite cast iron materials, also known as ductile cast iron (DCI), EN-GJS-400-18-LT and EN-GJS-450-18, different welding procedures were examined for potential repair welding. A repair weld was performed on thick cast iron plates using the optimum procedure in each case. The weld was evaluated for all areas of the welded joint (weld metal, fusion line/heat-affected zone and base metal). In addition to the metallographic microstructural analysis, the characterization of the repair weld was carried out by means of hardness distribution measurements, static tensile testing and notched bar impact testing as well as fracture mechanics investigations under static and under cyclic loading in a wide load ratio range. On this basis, a generalized description of cyclic crack growth could be made according to the NASGRO® MODEL. NASGRO® is a fracture mechanics and fatigue crack growth software. In accordance with the possible operating conditions of repair-welded, thick-walled components, the static and impact tests were performed in the temperature range down to $$-$$ - 40 $${}^{\circ }\text {C}$$ ∘ C .

A self-supervised learning method for fault detection of wind turbines

Abstract As promising solutions to condition-based maintenance of wind turbines, artificial intelligence-based techniques have drawn extensive attention in the era of industry 4.0. However, accurate fault detection is still challenging owing to volatile operating conditions in real-world settings. To handle this problem, a novel method is proposed for fault detection of wind turbines. Specifically, a data augmentation scheme is developed to simulate the effects of time-varying environments and noise. Then, a self-supervised proxy task of variant prediction is designed and conducted. In this way, valid data representations can be extracted to represent the health status of wind turbines. Additionally, the compactness of data representations is guaranteed by the directional evolution, which can relieve the confusion of health conditions. The effectiveness of the proposed method is verified with actual measurements. Using the proposed method, several faults can be detected more than 10 days earlier, and blade breakage can be identified more than 22 hours earlier. Furthermore, the developed method outperforms several benchmark approaches.

Research on the Performance and Computational Fluid Dynamics Numerical Simulation of Plate Air Gap Membrane Distillation Module

Membrane distillation (MD) is widely used in the field of seawater desalination. Among its various sub-categories, air gap membrane distillation (AGMD) stands out due to its high thermal efficiency and compatibility with low-grade heat sources. This study delves into the impact of varying operating conditions on AGMD performance, employing numerical simulations which are grounded in experimental validation. The objective was to enhance the performance of AGMD, mitigate polarization phenomena, and provide a reference for optimizing membrane component design. The results show that the agreements between the simulated and the experimental values were high. When increasing the feed temperature and decreasing the coolant temperature, the impact of polarization phenomena on the performance of AGMD was reduced. The mass flux, Total Permeate Concentration (TPC), and heat flux increased by 81.69%, 36.89%, and 118.01%, respectively, when the feed temperature was increased from 50 °C to 75 °C. When the coolant temperature decreased from 22 °C to 7 °C, the mass flux increased by 37.06%. The response surface analysis revealed that the feed temperature has significant influence on AGMD performance, and there is a noticeable interaction between the feed temperature and coolant temperature. These findings will play key roles in practical applications.

Modeling and Comparison Study of Industrial AC-Arcs

AbstractElectric arcs are a necessary heat source in many industrial processes that take place in Submerged Arc Furnaces (SAFs). Arcs exhibit non-linear electrical characteristics and behave in a complex manner. Therefore, an improved understanding of their behavior enables better control of furnace operation. Modeling of industrial arcs is a multiphysics process that involves simultaneously solving several coupled physical phenomena, such as electromagnetics, fluid dynamics, and heat transfer, including a radiative heat transfer from the plasma arc. Coupling fluid dynamics and electromagnetics is known as Magnetohydrodynamics (MHD). For practical applications, however, there are also simpler approaches to arc modeling, either based on simplified physical principles or empirical behavior. In this paper, a combined Cassie–Mayr model (CMM) and a channel arc model (CAM) are implemented and coupled with a submerged arc furnace electrical circuit model. The complete circuit model parameters such as resistances and inductances are estimated using modeling of a full size furnace, and then, actual measurements from a SAF are used to validate the models by comparing current and voltage waveform. Both models are then used to estimate harmonic distortion in a SAF for different arc current ratios, which should help operators to estimate the arc current in real time thus be able to lower and raise the electrode to keep operating conditions constant.

Parsimonious statistical techniques for the detection of drifts toward dangerous operational conditions in tokamaks

Abstract The approaching initial operation of major new tokomaks is rendering more pressing the need for effective disruption prediction techniques. The required tools should be not only accurate but also capable of operating with a minimum number of signals, because in the first campaigns of new devices typically only a very limited number of diagnostics is available. The present work reports the results obtained with two advanced statistical techniques, chaos onset and concept drift. These methods are capable of detecting the plasma drifting towards dangerous regions of the operational space using only global signals such as the plasma current or the locked mode amplitude. The obtained performances meet the requirements of mitigation in devices such as JT60-SA and ITER at the beginning of their operation. The computational times of the chaos onset approach are already of the order of 1 ms on laptop computers, whereas the concept drift technique requires implementation on FPGAs or GPUs to be compatible with real time requirements

Condition monitoring and warning of a belt drive system based on a logical analysis of data regression-based residual control chart

The belt drive system is commonly used to transmit power in different industrial systems to maintain high performance and safety. Online condition monitoring techniques (CMTs) are used to monitor the operational conditions of such systems. Vibration-based monitoring techniques (VMT) are among the CMTs that are used in the analysis and diagnosis of the state of a belt drive system. Machine learning techniques are integrated with the VMT based on Industry 4.0 aspects for vibration analysis and fault diagnosis. Most of these techniques are based on the collection of vibration data from the belt drive system under known normal and different known faulty operations. This enables a fault to be diagnosed when it is detected during the operation of a system. In this paper, a new condition monitoring and warning mechanism is proposed to monitor the operational conditions of a belt drive system. The mechanism is based on an integration of a logical analysis of data regression (LADR) with a residual control chart (RCC). It uses vibration data from the belt drive system under normal operation only. This mechanism exhibits better performance in fault detection and also in interpreting the root cause of the faults in a belt drive system. Experimental investigations on a belt drive test rig have been carried out to collect vibration data based on a design of experiment for operational factors during normal operation. The LADR-RCC is implemented to monitor the operation of the belt drive system and detect faulty states. The accuracy of LADR is compared with multiple linear regression-based RCC, support vector regression-based RCC and random forest-based RCC. The LADR-RCC demonstrates significant enhancements in fault detection. The advantage of LADR-RCC over other model-based RCC is that it finds the root cause of a fault that is experienced in the system.

Integration of Concentrating Solar Power With High Temperature Electrolysis for Hydrogen Production

Hydrogen has been identified as a leading sustainable contender to replace fossil fuels for transportation or electricity generation, and hydrogen generated from renewable sources can be an energy carrier for a carbon-free economy. Several hydrogen production methods are under development or deployment with various technical readiness levels and technoeconomic potentials. This study focuses on integrating concentrating solar thermal power (CSP) with high temperature electrolysis (HTE) using solid oxide electrolysis cells (SOEC). The CSP-HTE integration approach provides the benefits of thermal energy storage for continuous operation, improved capacity, and reduced thermal cycling for improved SOEC life. The CSP-HTE system analysis utilizes a Python-based system modeling program in connection with solar receiver thermal output derived from the NREL System Advisor Model (SAM) software. The system model facilitates component sizing, performance simulation, and evaluation of operation modes on an annual basis for various CSP-HTE configurations including CSP with thermal energy storage (TES). The SOEC operation conditions were simulated to assess component sizing and performance and to derive system capacity factors.

Dynamical Janus Interface Design for Reversible and Fast-Charging Zinc-Iodine Battery under Extreme Operating Conditions.

Aqueous zinc (Zn) iodine (I2) batteries have emerged as viable alternatives to conventional metal-ion batteries. However, undesirable Zn deposition and irreversible iodine conversion during cycling have impeded their progress. To overcome these concerns, we report a dynamical interface design by cation chemistry that improves the reversibility of Zn deposition and four-electron iodine conversion. Due to this design, we demonstrate an excellent Zn-plating/-stripping behavior in Zn||Cu asymmetric cells over 1000 cycles with an average Coulombic efficiency (CE) of 99.95%. Moreover, the Zn||I2 full cells achieve a high-rate capability (217.1 mA h g-1 at 40 A g-1; C rate of 189.5C) at room temperature and enable stable cycling with a CE of more than 99% at -50 °C at a current density of 0.05 A g-1. In situ spectroscopic investigations and simulations reveal that introducing tetraethylammonium cations as ion sieves can dynamically modulate the electrode-electrolyte interface environment, forming the unique water-deficient and chloride ion (Cl-)-rich interface. Such Janus interface accounts for the suppression of side reactions, the prevention of ICl decomposition, and the enrichment of reactants, enhancing the reversibility of Zn-stripping/-plating and four-electron iodine chemistry. This fundamental understanding of the intrinsic interplay between the electrode-electrolyte interface and cations offers a rational standpoint for tuning the reversibility of iodine conversion.

The Behavior of Terminal Voltage and Frequency of Wind-Driven Single-Phase Induction Generators under Variations in Excitation Capacitances for Different Operating Conditions

This paper assesses the behavior of output voltage and frequency of wind-driven self-excited induction generators with variable excitation capacitances connected to the main and auxiliary windings under different operating conditions. The optimum values of the main winding excitation capacitance for fixed terminal voltage operation under different values of shunt capacitance, load, and speed are also evaluated. The obtained results show that the terminal voltage is highly affected by changing the main winding excitation capacitance. In addition, the frequency is greatly affected by changing the auxiliary winding excitation capacitance. However, under different operating conditions, variation in the output frequency under different values of the main winding capacitance, with fixed auxiliary winding capacitance, is acceptable. Extensive simulations were conducted and the results are discussed in this publication.

An improved transmission efficiency prediction method for nonlinear characteristics of the cycloid reducer

This study aims to accurately predict the nonlinear characteristics of transmission efficiency of cycloid reducers under different operating conditions. Firstly, equivalent modeling of the multi-source errors (MSEs) in the designed cycloid reducer is conducted. Force analysis algorithms considering MSEs are proposed for the cycloid drive mechanism, the output mechanism, and the bearings. Secondly, mathematical models are established for the load-dependent power losses, while an equivalent test is used for modeling load-independent power losses. Subsequently, an improved transmission efficiency prediction (TEP) method for cycloid reducers is proposed, which is then applied to the performance prediction of a prototype under different operating conditions. The advantages of the improved TEP method over the conventional method are discussed, and the influences of MSEs and load-independent power losses on the nonlinear characteristics of transmission efficiency are summarized. Finally, tests are conducted for the reducer prototype, and the test results are found to be in good agreement with the results obtained by the proposed TEP method. The main contribution of this study is to establish a solid algorithmic and modeling foundation for the optimal design of nonlinear transmission efficiency in cycloid reducers and provide reliable guidance for their engineering applications.

The Effect of Energy Management in Heating–Cooling Systems of Electric Vehicles on Charging and Range

In this study, an energy management model for electric vehicles including the entire vehicle such as the cabin, electric motors, battery, and the heating–cooling system was prepared. The heating and cooling processes for electric vehicles were run according to the internationally recognized driving cycles as well as at constant speeds to investigate them under different ambient conditions. The heating–cooling processes were managed in line with the cabin temperature target determined by considering the comfort conditions. The energy consumption of each of the system elements and the system in the heating–cooling process in electric vehicles was analyzed. Under different operating conditions, the variation of cabin temperature with time, instantaneous power, and cumulative energy consumption was calculated. The effect of heating and cooling processes on energy consumption, charging rate, and range were analyzed and interpreted. The results showed that the heating–cooling system for the heating process consumed more energy when the ambient temperature decreased, and the charge consumption ratio as well as the range deformation rate increased to about 30% when the ambient temperature was –10 °C. Similarly, the heating–cooling system for the cooling process consumed more energy when the ambient temperature increased, and the charge consumption ratio as well as the range deformation rate reached up to 40% when the ambient temperature was 40 °C. When the outdoor conditions were close to the thermal comfort temperature of 23 °C inside the cabin, the total energy consumption and the range deformation rates were reduced to less than 10%.

A Multidimensional Health Indicator Based on Autoregressive Power Spectral Density for Machine Condition Monitoring

Condition monitoring (CM) is the basis of prognostics and health management (PHM), which is gaining more and more importance in the industrial world. CM, which refers to the tracking of industrial equipment’s state of health during operations, plays, in fact, a significant role in the reliability, safety, and efficiency of industrial operations. This paper proposes a data-driven CM approach based on the autoregressive (AR) modeling of the acquired sensor data and their analysis within frequency subbands. The number and size of the bands are determined with negligible human intervention, analyzing only the time–frequency representation of the signal of interest under normal system operating conditions. In particular, the approach exploits the synchrosqueezing transform to improve the signal energy distribution in the time–frequency plane, defining a multidimensional health indicator built on the basis of the AR power spectral density and the symmetric Itakura–Saito spectral distance. The described health indicator proved capable of detecting changes in the signal spectrum due to the occurrence of faults. After the initial definition of the bands and the calculation of the characteristics of the nominal AR spectrum, the procedure requires no further intervention and can be used for online condition monitoring and fault diagnosis. Since it is based on the comparison of spectra under different operating conditions, its applicability depends neither on the nature of the acquired signal nor on a specific system to be monitored. As an example, the effectiveness of the proposed method was favorably tested using real data available in the Case Western Reserve University (CWRU) Bearing Data Center, a widely known and used benchmark.

Pairing Voltage-Source Converters with PI Tuning Controller based on PSO for Grid-Connected Wind-Solar Cogeneration

This paper introduces a novel method to improve the efficiency of grid-connected wind-solar cogeneration systems. It involves the integration of Voltage-Source Converters (VSCs) with a Proportional-Integral (PI) tuning controller that has been optimized using Particle Swarm Optimization (PSO). Integrating renewable energy sources into power grids presents a set of challenges in terms of ensuring stability and optimizing power flow. VSCs are essential for effectively managing power flow between renewable sources and the grid. The PI controller is vital in maintaining voltage levels and ensuring stable operation. Conventional PI controller tuning methods commonly rely on heuristic approaches, which might only partially optimize performance across various operational conditions. In order to tackle this issue, PSO is utilized to fine-tune the parameters of the PI controller automatically. This results in a significant reduction in system deviations and a notable improvement in efficiency, even when faced with fluctuating wind and solar conditions. The simulation results conducted in MATLAB/Simulink confirm the effectiveness of the proposed approach in enhancing system stability and reducing response times. The PI controller optimized using PSO showcases exceptional adaptability to varying environmental and grid conditions, resulting in minimized power fluctuations and improved grid reliability. This study makes a valuable contribution to the field of renewable energy integration. It provides valuable insights into enhancing the performance of grid-connected wind-solar cogeneration systems through advanced control techniques and optimization algorithms such as PSO.

Energy transfer and conversion in the Allam cycle with a multi-stream heat exchanger

The Allam cycle is renowned for its high efficiency and low emissions in power generation, utilizing supercritical carbon dioxide as the working fluid. The regenerator, one of the key heat exchangers, plays a crucial role in the system. However, modeling the regenerator is challenging due to the presence of multiple pinch points. This study proposes a regenerator model that employs three multi-stream heat exchanger modules in Aspen Plus. A thermodynamic and economic analysis of the system was conducted and compared with a conventional system utilizing the two multi-stream heat exchanger modules. Simulation results show that the combustion chamber has the highest exergy loss in the system, accounting for 46.9 % of the total exergy loss. The turbine is identified as the most capital-intensive component, representing 44.9 % of the total equipment investment. Furthermore, a sensitivity analysis was conducted on key parameters. The results indicate that under certain operating conditions, the heat provided by the air separation unit is insufficient to reduce the temperature difference at the hot outlet of the regenerator. Compared to the conventional Allam cycle system using the 2R model, the 2R model predicts deviations of up to 28.9 %. This proposed model provides a new approach for the efficient allocation of energy utilization in the multi-stream heat exchange process within the Allam cycle system.